Datasets:

TaylorAI

/

pubmed_commercial

like 12

PMC005xxxxxx/PMC5000442.txt

==== Front BMC Plant BiolBMC Plant BiolBMC Plant Biology1471-2229BioMed Central London 87410.1186/s12870-016-0874-5Research ArticleDissecting maize diversity in lowland South America: genetic structure and geographic distribution models Bracco Mariana marianabracco@unnoba.edu.ar 12Cascales Jimena jcascales@ege.fcen.uba.ar 13Hernández Julián Cámara jcamara@agro.uba.ar 4Poggio Lidia lidialidgia@yahoo.com.ar 13Gottlieb Alexandra M. gottlieb@ege.fcen.uba.ar 13Lia Verónica V. +54-11-4621-147lia.veronica@inta.gob.arveroliabis@yahoo.com 1351 Departamento de Ecología, Genética y Evolución, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Intendente Güiraldes y Costanera Norte s/n, 4to, Piso, Pabellón II, Ciudad Universitaria, C1428EHA Ciudad Autónoma de Buenos Aires, Argentina 2 Escuela de Ciencias Agrarias, Naturales y Ambientales, Universidad Nacional del Noroeste de la Provincia de Buenos Aires, Av. Pte. Dr. Arturo Frondizi, N° 2650 Pergamino, Buenos Aires Argentina 3 Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Avenida Rivadavia 1917, C1033AAJ Ciudad Autónoma de Buenos Aires, Argentina 4 Facultad de Agronomía, Universidad de Buenos Aires, Av. San Martín 4453, C1417DSE Ciudad Autónoma de Buenos Aires, Argentina 5 Instituto de Biotecnología, CICVyA, INTA, N. Repetto y De las Cabañas s/n 1686, Hurlingham, Buenos Aires Argentina 26 8 2016 26 8 2016 2016 16 1 18631 3 2016 15 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Maize landraces from South America have traditionally been assigned to two main categories: Andean and Tropical Lowland germplasm. However, the genetic structure and affiliations of the lowland gene pools have been difficult to assess due to limited sampling and the lack of comparative analysis. Here, we examined SSR and Adh2 sequence variation in a diverse sample of maize landraces from lowland middle South America, and performed a comprehensive integrative analysis of population structure and diversity including already published data of archaeological and extant specimens from the Americas. Geographic distribution models were used to explore the relationship between environmental factors and the observed genetic structure. Results Bayesian and multivariate analyses of population structure showed the existence of two previously overlooked lowland gene pools associated with Guaraní indigenous communities of middle South America. The singularity of this germplasm was also evidenced by the frequency distribution of microsatellite repeat motifs of the Adh2 locus and the distinct spatial pattern inferred from geographic distribution models. Conclusion Our results challenge the prevailing view that lowland middle South America is just a contact zone between Andean and Tropical Lowland germplasm and highlight the occurrence of a unique, locally adapted gene pool. This information is relevant for the conservation and utilization of maize genetic resources, as well as for a better understanding of environment-genotype associations. Electronic supplementary material The online version of this article (doi:10.1186/s12870-016-0874-5) contains supplementary material, which is available to authorized users. Keywords Genetic diversityGeographic distribution modelsGuaraní communitiesLowland South AmericaMaize landraceshttp://dx.doi.org/10.13039/501100003074Agencia Nacional de Promoción Científica y TecnológicaPICT 2012-0325Lia Verónica V. http://dx.doi.org/10.13039/501100002923Consejo Nacional de Investigaciones Científicas y TécnicasPIP 11220120100416COLia Verónica V. http://dx.doi.org/10.13039/501100005363Universidad de Buenos AiresEX178Poggio Lidia issue-copyright-statement© The Author(s) 2016 ==== Body Background There is general consensus that maize (Zea mays L. ssp. mays) was domesticated from its wild relative, the teosinte Zea mays ssp. parviglumis Iltis & Doebley, in the lowlands of south-western Mexico during the early Holocene, whence it spread rapidly northwards and southwards across America [1–4]. In South America, the earliest evidence of maize can be traced to at least 7000 calibrated years before present [4, 5]. In this region, however, the introduction date and dispersal routes of the cultigen, as well as the patterns of racial diversification, still remain unclear. Based on the cytogenetic analysis of South American landraces, McClintock et al. [6] suggested that different types of maize were early introduced into two initial centres of cultivation: northern South America and the central Andean highlands. They proposed that maize germplasm from the northern region had a vast influence on the races of the Caribbean Islands and on those in eastern South America, whereas races from the Andean centre spread extensively throughout the southwest. This hypothesis is consistent with the analysis of a microsatellite repeat within the alcohol dehydrogenase 2 gene (Adh2) in archaeological maize specimens, which revealed an east–west partitioning of allele frequencies. These studies provided evidence of two separate expansion events in South America; one occurring from the highlands of Central America into the Andean region, and the other from the alluvial regions of Panama into the lowlands and then along the northeast coast of the continent [7]. More recently, Vigouroux et al. [8] inferred an alternative model of maize introduction from the analysis of SSR (Simple Sequence Repeat) variability, based on a comprehensive assembly of landraces from the Americas. Using genetic distance clustering methods, these researchers concluded that maize cultivation was first introduced into South America from Colombia and Venezuela, subsequently into the Caribbean from South America via Trinidad and Tobago, and into the Andes from Colombia. Knowledge of the structure of genetic variation in present-day maize landraces, and how it is related to their geographical distribution, provides valuable insights for reconstructing dispersal routes. Maize landraces from the highlands of South America (i.e., the Andean region) have emerged repeatedly as a distinct entity, as evidenced by morphological, cytogenetic and molecular data [1, 6, 9, 10]. In contrast, no clear delimitation could be achieved among the landraces from the lowland regions of South America, adding further complexity to the testing of dispersal hypotheses. Over the years, studies of molecular diversity have referred to germplasm from the lowlands of South America by different names, such as Other South American maize [1], the Tropical Lowland group [8], the Lowland South American group [11], the South American Lowland, Bolivian Lowland and Costal Brazil groups [12], and the Middle South American group [13]. However, differences in geographical sampling between studies and the lack of integrative analyses make it difficult to assess whether these assemblages belong to the same gene pool and how they relate to each other. Recent research concerning the population dynamics of maize landraces has also provided evidence for a highland-lowland genetic structuring pattern. Bracco et al. [14] conducted a comparative evaluation of SSR variability in an extensive sample of maize landraces from Northeastern and Northwestern Argentina (NEA and NWA, respectively) and identified three distinct gene pools named NWA, NEA popcorns, and NEA flours. The affiliation between the NWA group and the Andean complex was already established by Lia et al. [15], whereas the relationships between landraces from lowland NEA and other regions of lowland South America have not been determined until this study. Regardless of what the most plausible hypothesis of maize dispersal may be, it is undisputed that its spreading was accompanied by a remarkable adaptation to heterogeneous environmental conditions [11, 16, 17]. Some difficulties may arise in modelling the geographic distribution of crop species, such as discriminating the relative contribution of demography, farmer’s selection and habitat suitability. Notwithstanding this, the methods used in geographic distribution modelling may offer a new perspective to understand current and historical patterns of local adaptation. Indeed, these approaches have provided valuable insights into the ecological requirements and possible impacts of climate change on teosintes and Mexican landraces [16, 17]. Herein we provide a comparative framework to analyse maize diversity and clarify the relationships among lowland South American gene pools. For this purpose, the sampling conducted by Bracco et al. [14] (345 individuals from Northern Argentina) was expanded by genotyping 232 individuals of 12 additional lowland landraces from NEA using SSR markers, and these data were analysed in combination with the datasets of Vigouroux et al. [8] and Lia et al. [15]. In addition, Adh2 microsatellite sequences were obtained from representative individuals of NWA and NEA to allow comparison with the archaeological and extant specimens from southern South America studied by Freitas et al. [7] and Grimaldo Giraldo [18]. Finally, the relationship between bioclimatic variables and the geographical distribution of the inferred gene pools was explored using species distribution modelling approaches. Methods SSR genotyping To fully represent the racial diversity of maize in NEA and to complement the data presented by Bracco et al. [14], 10 SSR loci (bnlg1866, phi037, bnlg1182, bnlg252, bnlg1287, bnlg1732, bnlg1209, bnlg1018, bnlg1070 and bnlg1360) were genotyped on 232 individuals from the Argentinean provinces of Chaco, Corrientes, Entre Ríos, Formosa and Misiones (Additional file 1: Figure A1). Landraces were collected in 1977, 1978 and 2005 directly from farmer fields and preserved at the Banco de Germoplasma EEA INTA Pergamino, or at the Laboratorio de Recursos Genéticos Vegetales “N.I. Vavilov”, Universidad de Buenos Aires. Racial identification, voucher specimens, collection sites and sample sizes of the accessions genotyped here are given in Additional file 1: Table A1. Seed germination, DNA extraction, and SSR genotyping were performed as detailed in Bracco et al. [19]. Primer sequences are available at the MaizeGDB website (http://www.maizegdb.org/data_center/locus). SSR Data analysis To put the SSR data in a continental context, our dataset was analysed in combination with those of Bracco et al. [14], Lia et al. [15] and Vigouroux et al. [8], yielding a final data matrix of 10 SSR and 1288 individuals. This compiled SSR data matrix consisted of 709 individuals belonging to 29 landraces from NEA and NWA, plus 579 individuals from the main genetic groups recognised by Vigouroux et al. [8], namely, Tropical Lowland (74 landraces, 187 individuals), Andean (89 landraces, 235 individuals), Highland Mexico (HM) (37 landraces, 87 individuals) and Northern and Southwestern US (US) (49 landraces, 70 individuals). Individuals identified as admixed in the original studies were excluded from the analysis. Allele size equivalences between maize landraces from NWA and those of Matsuoka et al. [1] were determined by Lia et al. [15]. Individuals from NWA were then used as allele size markers to genotype NEA landraces. The SSR data of Matsuoka et al. [1] are included within the data set of Vigoroux et al. [8], thus allowing the integration of all sources of data. The compiled SSR matrix is given in Additional file 2: Table A2. Model-based clustering Genetic clusters were inferred using the Bayesian approach implemented in STRUCTURE 2.3.4 [20]. However, given the differences between the number of loci genotyped in NEA and NWA landraces and those used by Vigouroux et al. [8], we first checked the consistency of the groups defined by these authors against the reduction of the number of loci (from 84 to 10) using STRUCTURE. As a result, we retrieved the same four groups reported by them, thus validating the use of this subset of SSR in our integrative analysis (data not shown). The overall probability of identity and the probability of identity given the similarity between siblings were estimated across the complete SSR data matrix according to Waits et al. [21], using GeneAlEx 6 [22]. The discriminant power of the selected loci on the combined dataset was supported by a probability of identity of 4.7 × 10−14 and probability of identity among siblings of 4.7 × 10−5. Analyses were performed using K values from 1 to 10, 10 replicate runs per K value, a burn-in period length of 105 and a run length of 106. No prior information on the origin of individuals was used to define the clusters. All the analyses were run under the correlated allele frequency model [23]. The run showing the highest posterior probability was considered for each K value. A measure of the second order rate of change in the likelihood of K (ΔK) [24] was calculated using Structure Harvester [25]. An individual was assigned to one of the clusters on the basis of having a membership coefficient higher than an arbitrary cut-off value of 0.80 (Q > 0.80) (Additional file 2: Table A2). Results were plotted with DISTRUCT 1.1 software [26]. The model of correlated allele frequencies of Falush et al. [23] was applied to estimate the drift parameter (F) for the genetic groups inferred by STRUCTURE. This parameter measures the extent of a cluster’s differentiation relative to a hypothetical population of origin and has a direct interpretation as the amount of genetic drift to which the cluster has been subjected [27]. A graphical representation of the densities of F was obtained using the density function of R 3.0.2 (R Core Team 2014). Discriminant Analysis of Principal Components (DAPC) Population structure was also examined by the Discriminant Analysis of Principal Components (DAPC) [28], using the adegenet 1.3-1 package [29] implemented in R 2.13.2 (R Core Team 2014). The function dapc was executed by retaining 150 principal components, which accounted for 96 % of total genetic variation and five discriminant functions, and using the clusters identified by the K-means algorithm [30]. The number of clusters was assessed using the function find.clusters, with n.iter = 1000000 and n.start = 25, evaluating a range from 1 to 40. Genetic diversity and differentiation Diversity indices were calculated for the genetic clusters inferred by Bayesian analysis, using only individuals unequivocally assigned to their respective clusters (Q > 0.80). The mean number of alleles per locus (A), allelic richness (Rs) [31] and gene diversity (He) [32] were estimated using the software Fstat 2.9.3.2 [33]. The presence of group-specific alleles (hereafter referred to as private alleles) was examined for each group. Private allelic richness, i.e., the mean number of private alleles per locus as a function of standardised sample size, was computed with ADZE 1.0 [34]. File conversion was conducted with Convert 1.31 [35]. Differentiation between STRUCTURE groups was assessed by the Allele frequency divergence estimate provided by the software. Cluster analysis was carried out applying the Neighbour-joining algorithm [36] implemented in PHYLIP 3.6 [37]. Branch support was estimated by bootstrapping (1000 pseudoreplicates) with Powermarker 3.25 [38]. Resulting trees were visualised with FigTree 1.3.1 [39]. Adh2 microsatellite analysis Individuals of 16 landraces from Northern Argentina (NWA + NEA) were sequenced for the Adh2 microsatellite region (Additional file 1: Table A3). The Adh2 gene segment employed for primer design (GenBank X02915) included part of the 5’ untranslated promoter region, the exons 1 and 2, and the intervening intron. PCR primers were designed with the Primer3 software 0.4.0 [40]: upstream, 5’-AAAATCCGAGCCTTTCTTCC-3’; downstream, 5’-CTACCTCCACCTCCTCGATG-3’. Cycling was carried out as in Freitas et al. [7], and the PCR products were checked and visualised as in Bracco et al. [14]. To determine whether individuals were homozygous or heterozygous, PCR products were subjected to native PAGE as described in Bracco et al. [19]. Bands from homozygous individuals (ca. 350 bp in length) were excised from agarose gels (2 % w/v) purified using an AccuPrep® Gel purification kit (BIONEER) and sequenced in an ABI 3130XL apparatus (Applied Biosystems). Chromatograms were edited with BioEdit 7.1.3.0 [41]. Both strands were assembled with the same program, and the microsatellite motifs were extracted for frequency calculation. All sequences were deposited in GenBank under accession numbers KU304471 to KU304494. The data gathered were analysed together with Adh2 microsatellite alleles derived from the archaeological landraces examined by Goloubinoff et al. [42], Freitas et al. [7] and Grimaldo Giraldo [18], under the assumption that genealogical continuity exists between the archaeological genetic structure and that of extant landraces. In addition, we extracted the SSR alleles from the modern, primitive and historic landraces studied by Freitas et al. [7] and Grimaldo Giraldo [18], and from Adh2 sequences retrieved from GenBank corresponding to Brazilian and Bolivian landraces (EU119984-9 and EF070151-6, respectively). The compiled data set (N = 497) was divided into three allele types following Freitas et al. [7], i.e. (GA)n, (GA)nTA and GAAA(GA)n. Statistical associations between allele types and geographic regions were evaluated with the likelihood ratio Chi-square test implemented in Infostat software 2013 [43]. Modelling of geographic distributions Geographic distributions were modelled using the Maximum Entropy method [44], implemented in MaxEnt 3.3.3.a (https://www.cs.princeton.edu/~schapire/maxent/). This program uses presence-only data in the form of geo-referenced occurrence records, and a set of environmental variables to produce a model of the distribution range of the species under study. The raw and logistic outputs of MaxEnt are monotonically related and can be interpreted as an estimate of habitat suitability [45, 46]. We modelled the geographic distribution of the genetic groups retrieved from Bayesian clustering, considering only individuals with Q > 80 %. Following the guidelines provided in Scheldeman & van Zonneveld [47], a minimum of 20 occurrence points was set as threshold for modelling. Thus, a total of 317 spatially unique records were used, corresponding to the following clusters: 22 for NEA Flours, 92 for Tropical Lowland, 120 for Andean, and 87 for Highland Mexico and US (HM-US). The NEA Popcorns could not be subjected to analysis because of the low number of unique sampling localities (<5). Given the stability of the MaxEnt method in the face of correlated variables [45], and to facilitate comparisons with previous models of the geographic distribution of maize [16], we used the variable Altitude and the 19 bioclimatic variables available at WORLDCLIM 1.4 (http://www.worldclim.org/) [48] at 2.5 arc-min resolution. These 19 variables are derived from monthly temperature and precipitation records, reflecting seasonal and annual variations. Models were generated using 20,000 background points from all over the world. This implies that landrace could have dispersed anywhere in the globe, which is a reasonable assumption for a domesticated crop such as maize. It has been shown that the predictive ability of MaxEnt models is influenced by the choice of feature types and regularisation parameters, particularly for small sample sizes [49]. By default, the program uses class-specific regularisation parameters tuned on the basis of a large international dataset [45]. In addition, when few samples are available, MaxEnt restricts the model to simple feature classes (i.e., linear, quadratic, hinge) [49]. Because the number of occurrences for the different groups ranged from 22 to 118, we followed the recommendations of Elith et al. [45]; thus, we constructed the models under two different settings: 1) hinge features only and default regularisation parameters; and 2) default feature and regularisation parameters. Models were compared using sample-size corrected Akaike’s Information Criteria (AICc) with ENMtools 1.3 [50, 51]. Model performance was assessed using the area under the receiver operating characteristic curve (AUC) [52] for both training and testing data sets. Ten-fold cross-validation was used to estimate errors around fitted functions and predictive performance on held-out data, except for the NEA Flours in which 4-fold cross-validation was used due to the low number of spatially unique records. Variable importance was determined by measuring the contribution of each variable to model improvement during the training process (percent of contribution), and by jackknife tests implemented in MaxEnt. Model predictions were visualised from MaxEnt logistic outputs using DIVA-GIS 7.2.1.1. [53]. Pairwise comparisons of model predictions were carried out by calculating the I statistic of Warren et al. [54] and Schoener’s D [55] as implemented in ENMtools 1.3. To evaluate whether the models generated for each genetic cluster are more different than expected if they were drawn from the same underlying distribution, we performed the niche identity test [54] included in ENMtools 1.3 with 100 replicates. All the maps used in this study were freely available at http://www.diva-gis.org/Data. Results Inference of genetic clusters Bayesian population structure analysis of the complete SSR data matrix (10 SSR, 1288 individuals) supported the existence of five distinct genetic clusters, as inferred from the joint assessment of the log-likelihood of the data conditional on K (LnP(D)) and the rate of change in the log likelihood of the data between successive K values (∆K) (Additional file 1: Figure A2). As suggested in previous studies [8], the peak of ∆K at K = 2 was considered an artefact resulting from the low likelihoods of K = 1. At K = 5, the retrieved clusters showed a clear geographic patterning. We recovered Highland Mexico and US landraces forming a single cluster, (hereafter referred to as HM-US), and two of the main groups previously described for South America by Vigouroux et al. [8], i.e. Andean and Tropical Lowland. The remaining two groups were primarily composed of NEA floury landraces (hereafter referred to as NEA Flours) and NEA popcorn landraces (hereafter referred to as NEA Popcorns) (Fig. 1). To test whether differences in sampling strategies and intensities among the groups could influence STRUCTURE results, we carried out a new STRUCTURE analysis with a reduced number of NEA individuals (a random subset of 50 individuals from NEA Flours and 50 individuals from NEA Popcorns). As a result, we retrieved the same five previously identified groups, suggesting that the observed distinctiveness of NEA landraces was not an artefact due to redundant sampling (Additional file 1: Figure A3).Fig. 1 Estimated population structure of maize landraces from the Americas. a STRUCTURE bar plots for K = 5. Each vertical line represents an individual and colours represent their inferred ancestry from K ancestral populations. Individuals are ordered by sampling region and source study. b Geographical distribution of the clusters inferred by STRUCTURE. Dotted lines indicate the geographic extent considered for each chart. c Posterior densities of the genetic drift parameter (F) from STRUCTURE correlated allele frequency model. 1 Data from Vigouroux et al. [8]; 2 data from Lia et al. [15]; 3 data from Bracco et al. [14]; 4 data from this study. * Brazilian accessions. HM-US: Highland Mexico and US; NWA: North Western Argentina; NEA: North Eastern Argentina Analysis of STRUCTURE outputs showed that membership coefficients (Q) in a given cluster were higher than 0.80 for 79 % of the individuals. Following this criterion, 145 individuals were assigned to HM-US, 275 to Andean, 157 to Tropical Lowland, 344 to NEA Flours, and 99 to NEA Popcorns, whereas 268 (21 %) were classified as admixed (Additional file 2: Table A2). Interestingly, accessions from Brazil previously ascribed to the Tropical Lowland group by Vigouroux et al. [8] had a relatively high contribution from the NEA Flours (average Q = 0.25), with some individuals reaching Q ≥0.80. Conversely, several NEA Flours individuals showed remarkable contributions from the Tropical Lowland gene pool, particularly those collected outside the Guaraní communities in the province of Misiones, Argentina (Fig. 1, Additional file 2: Table A2). The genetic drift parameter identified the Tropical Lowland (mean F = 0.032) and HM-US (mean F = 0.038) as the most similar to a common hypothetical ancestor, followed by the Andean (mean F = 0.087), whereas the NEA Flours (mean F = 0.172) and the NEA Popcorns (mean F = 0.539) appeared as the most divergent groups (Fig. 1c). The genetic structuring patterns obtained using DAPC were mostly concordant to those from Bayesian analysis, but group boundaries were less clearly defined. The k-means algorithm identified k = 20 as the most likely number of groups; however, a close inspection of individual assignments showed that many of these groups resulted from the subdivision of the five clusters obtained by STRUCTURE (Additional file 1: Figure A4). To visually compare the results between analyses, we generated DAPC scatterplots based on the first three principal components, with individuals being colour-coded according to their assignment by STRUCTURE. Figure 2 shows that individuals belonging to the different gene pools occupy different, yet partially overlapping, areas in the DAPC scatterplot, and that the Tropical Lowland cluster is placed in an intermediate position.Fig. 2 Multivariate analysis of SSR variation in maize landraces from the Americas. Scatterplot of the Discriminant Analysis of Principal Components (DAPC). Dots represent individual samples coloured according to the STRUCTURE assignments. HM-US: Highland Mexico and US Genetic diversity and differentiation Given the clear-cut differentiation among the NEA Flours, NEA Popcorns and the remaining regional gene pools, we analysed the levels and distribution of genetic variability among the inferred clusters. For this purpose, we computed diversity indices and pairwise allele frequency divergence estimates among groups (Table 1, Additional file 1: Table A4, Table A5).Table 1 Indicators of genetic diversity within the genetic clusters inferred by STRUCTURE He A Rs PAR PA NEA Flours (N = 344) 0.662b 11.1b 8.38c 0.51c 3 NEA Popcorns (N = 99) 0.383c 4.2c 4.04d 0.03d 0 Tropical Lowland (N = 157) 0.787a 17.4a 14.84a 2.24a 23 Andean (N = 275) 0.668b 15.5a 11.79b 0.95b,c 17 HM-US (N = 145) 0.823a 18.1a 15.87a 3.27a,b 39 H e gene diversity, A mean number of alleles per locus, R s allelic richness, PAR Private allelic richness, PA number of private alleles over all loci Rarefaction analyses were performed with a sample size of 73. Values with different letters are significantly different from each other (p < 0.05, Wilcoxon signed-rank test). HM-US: Highland Mexico and US Regardless of sample-size corrections, a consistent pattern was apparent for all the diversity estimates. The HM-US and Tropical Lowland exhibited the highest variability estimates, followed by the Andean, NEA Flours and NEA Popcorns. The HM-US also showed the highest number of private alleles in both global and pairwise comparisons (Additional file 1: Table A4). Allele frequency divergence ranged from 0.048 (HM-US vs. Tropical Lowland) to 0.236 (HM-US vs. NEA Popcorns) (Additional file 1: Table A5). The Neighbour-joining network placed the Tropical Lowland in a central position, flanked by the HM-US and Andean on one side and the NEA Flours and NEA Popcorns on the other side, albeit with low bootstrap support (Additional file 1: Figure A5). Adh2 sequence analysis To assess whether the marked differentiation detected for the NEA groups in the SSR analyses was in agreement with the ancient structuring pattern reported by Freitas et al. [7], we examined the microsatellite allele types at the Adh2 locus in a subset of NEA and NWA landraces from the SSR data matrix and analysed it in conjunction with previous data as described in the Methods section. To test the association between allele types and geographic regions, three groups were delimited based on the origin of the individuals, that is, Andean (west of 60° W), Middle Southern South America (MSSA, between 53°W and 60°W), and Eastern South America (ESA, east of 53°W). The MSSA region encompasses NEA and adjacent areas of Paraguay, Bolivia and western Brazil, whereas the ESA region encompasses northern, central and eastern Brazil. Six microsatellite allele types were recognised in the compiled Adh2 microsatellite dataset (N = 497), with the most frequent being (GA)n, (GA)nTA, and GAAA(GA)n (Additional file 1: Figure A6). Counts of microsatellite allele types for each region are provided in Additional file 1: Table A6. The relative abundance of these motifs in the Andean, MSSA and ESA regions is presented in Fig. 3. The distribution of allele types shows remarkable differences between the Andean and ESA regions (ML-G2 = 33.10; p <0.0001; d.f. = 2) and between the MSSA and ESA regions (ML-G2 = 15.26; p <0.0005; d.f. = 2). Conversely, differences between MSSA and the Andean region were non-significant.Fig. 3 Relative abundance (by region) of Adh2 microsatellite motifs in maize landraces from the Americas. Andean (west of 60°W), MSSA: Middle Southern South America (between 53°W and 60° W); ESA: Eastern South America (east of 53°W) Geographic distribution modelling The bounded geographic distribution of the genetic clusters identified here prompted us to investigate whether the observed genetic structuring was accompanied by distinct environmental requirements, especially for lowland germplasm. Habitat suitability models were obtained for four of the genetic clusters inferred by STRUCTURE, using two feature settings. Occurrence locations are given in Additional file 3: Table A7. Criterion-based model selection procedures using AICc were only applicable to the Andean and HM-US, favouring models fitted under default feature and regularisation parameters (Andean: AICc default = 2971.31; AICc hinge = 3138.87; HM-US: AICc default = 3629.28; AICc hinge = 4572.48). For the NEA Flours and Tropical Lowland, the number of parameters was higher than the number of occurrence points, thus precluding the use of AICc for model selection. Taking into account the results from model comparisons and that none of the groups showed differences in performance measures (i.e., AUCtrain and AUCtest) between default and hinge feature settings, we decided to continue our analysis based on the results with default settings. Cross-validated estimates of AUC were above 0.930 for all the groups, indicating high model discrimination ability (Table 2).Table 2 Geographic distribution models of the maize clusters inferred by Bayesian analysis. Evaluation and variable importance Genetic Cluster k-fold cv AUCtrain (mean ± SD) AUCtest (mean ± SD) Variable importance (percent contribution) Var1 Var2 Var3 NEA Flours 5 0.997 ± 0.001 0.994 ± 0.006 BIO3 (23.24) BIO18 (17.26) BIO4 (13.42) Tropical Lowland 10 0.968 ± 0.002 0.938 ± 0.019 BIO4 (40.3) BIO3 (22.9) BIO16 (9.49) Andean 10 0.992 ± 0.001 0.977 ± 0.018 Alt (35.75) BIO4 (32.38) BIO13 (7.04) HM-US 10 0.968 ± 0.003 0.949 ± 0.038 BIO2 (34.49) Alt (17.89) BIO1 (12.39) cv cross-validation, Alt altitude, BIO1 Annual mean temperature, BIO2 Mean diurnal range, BIO3 Isothermality; BIO4 Temperature seasonality, BIO13 Precipitation of wettest month, BIO16 Precipitation of wettest quarter, BIO18 Precipitation of warmest quarter, HM-US Highland Mexico and US Geographic distribution models produced by averaging cross-validation replicates are presented in Fig. 4. High values indicate a high probability of suitable conditions, intermediate values indicate conditions typical of those where the individuals are found, and low values indicate low probability of suitable conditions. The predicted distributions are in good agreement with the known cultivation areas for each group. A distinct spatial pattern is readily apparent, albeit with varying degrees of overlap among groups. The Tropical Lowland cluster showed the largest area of suitable habitats, which contrasts with the restricted predicted distribution of the NEA Flours. The Andean and HM-US also exhibited largely confined habitat suitability distributions associated with altitude.Fig. 4 Predicted habitat suitability distributions of the genetic groups inferred for maize landraces from the Americas. a NEA Flours; b Tropical Lowland; c Andean; d Highland Mexico and US (HM-US). Warmer (red) colours represent more suitable habitats The variables with highest average relative contribution are summarised in Table 2. The predictors with the most information not present in the other variables were: mean temperature of driest quarter (BIO9) for the NEA Flours, altitude for the Tropical Lowland, temperature seasonality (BIO4) for the Andean and precipitation of coldest quarter (BIO19) for the HM-US. Pairwise comparison of I and D indices applied to habitat suitability distributions revealed significantly different model predictions for each group (Table 3).Table 3 Comparison of habitat suitability distributions between the genetic clusters inferred for maize landraces of the Americas NEA Flours Tropical lowland Andean HM-US NEA Flours 0.612** 0.284** 0.414** Tropical lowland 0.294** 0.636** 0.558** Andean 0.127** 0.357** 0.424** HM-US 0.183** 0.301** 0.224** I statistic of Warren et al. [54] (above diagonal) and Schoener’s D [55] (below diagonal). Both indices measure the similarity of habitat suitability distributions and range from 0 (no overlap) to 1 (complete overlap). HM-US: Highland Mexico and US. **p < 0.01 Discussion Our results reveal the occurrence of three clearly distinct gene pools in the lowlands of South America, namely: Tropical Lowland, NEA Flours and NEA Popcorns. Although Vigouroux et al. [8] recognised some sub-groups within the Tropical Lowland with a geographical distribution similar to that of the NEA groups, their importance was overlooked probably due to the sampling strategy used by these authors. Both the Bayesian and DAPC methods show a clear separation among the NEA Flours, NEA Popcorns and the remaining clusters. Although DAPC inferred a larger optimal cluster number, the groups obtained are compatible with those from STRUCTURE since they represent subdivisions within the latter. These findings are consistent with the higher sensitivity of DAPC for detecting substructure in hierarchical models [28]. Notwithstanding these discrepancies and regardless of the presence (or not) of additional substructuring, it is clear that the genetic groups detected in the NEA are well differentiated from the other South American gene pools. As mentioned before, the composition of the Tropical Lowland cluster obtained in our analysis is similar to that reported by Vigouroux et al. [8], including, among others, lowland accessions from southwestern Mexico, which has been proposed as the centre of maize domestication. The central position of this assemblage in both the DAPC scatterplot and the Neighbour-joining network is consistent with the ancestral condition of the Tropical Lowland germplasm. Moreover, this group shows the lowest value of the genetic drift parameter (F), thus supporting its ancestral condition. In the present work, the Andean complex emerged as a clearly separate entity, in agreement with several previous studies [1, 6, 9, 10]. According to van Heerwaarden et al. [12] the Andean germplasm was the most divergent group from a common hypothetical ancestor, i.e. had the largest estimate of the drift parameter, but our results indicate an even greater degree of divergence for the NEA Flours and the NEA Popcorns, once again highlighting their uniqueness. In contrast with the results of Vigouroux et al. [8], our analyses failed to discriminate between Highland Mexico and US landraces, which were thus assigned to a single complex. This could be partly due to a decrease in the number of markers, and also to the inclusion of new individuals belonging to two well-differentiated groups (i.e. NEA Flours and NEA Popcorns). However, this lack of resolution is compatible with the similarities previously described by Vigouroux et al. [8], who suggested that the landraces of northern US were derived from those of the southwestern US, which in turn were derived from those of northern Mexico. The levels of diversity constitute an important factor in interpreting the high differentiation of the NEA groups. If these would have derived from any of the major groups in relatively recent times and then subjected to isolation by cultural or environmental factors, one would expect the diversity levels to be low and the allelic variants to be a subset of the original gene pool. Our analysis of diversity indices revealed that the variability levels of the NEA Flours were similar to those of the Andean group, whereas the NEA Popcorns had the lowest estimates (Table 1). Moreover, the NEA Flours also showed private alleles when compared to the other groups -though in small number- evidencing that the divergence found here is not only based on differences in the distribution of allelic frequencies. Interestingly, the highest diversity indices, including the number of private alleles, corresponded to the HM-US and Tropical Lowland groups, with the former having slightly higher values. Although differences were not statistically significant, these results are consistent with recent studies suggesting that maize landraces from the Mexican highlands received a substantial genetic contribution from the teosinte Zea mays ssp. mexicana [12]. In summary, the levels of genetic diversity found for NEA Flours do not coincide with those expected under a severe bottle-neck scenario followed by isolation; in contrast, the NEA Popcorns showed a remarkably low variability. The frequency distribution analysis of the Adh2 microsatellite allele types considered here revealed that statistically significant differences were found between ESA and MSSA, and between ESA and Andean regions. Since most of the data were collected from the literature, we could not establish a direct link between the geographic origin of all the individuals included in the analysis and their membership to any of the genetic groups inferred from our SSR analysis. However, the differences in the distribution of Adh2 microsatellite motifs between ESA and MSSA provide additional evidence favouring the existence of two distinct genetic groups in the lowlands of South America, with NEA Flours and NEA Popcorns sampling localities being contained within the boundaries of the MSSA category. On the other hand, the homogeneity found between Andean and MSSA is in agreement with the view of previous authors that Andean germplasm had an influence on the landraces of middle South America [6, 8, 10]. Local adaptation has played a key role in the dispersal and adoption of the different maize landraces which are currently cultivated in South America. Native landraces are maintained by local small-scale producers using traditional agro-technologies, with yield largely depending on weather conditions. On this basis, the knowledge of crop environmental requirements across different areas, together with a comprehensive genetic characterisation, may greatly contribute to elucidate the mechanisms underlying adaptation patterns at a local scale. Our work is the first one to investigate the relationship between genetic groups and environmental distribution models for South American maize. Distribution modelling studies focused on maize have been conducted at the landrace level [16, 17]. It is well-known, however, that the name given to a landrace does not always correspond to its genetic constitution, and that different entities assigned to the same landrace may differ more from each other than from the entities of other landraces. In an attempt to overcome these difficulties, we modelled the distribution of the genetic groups regardless of their designation because we assumed that the genetic composition is more informative on the adaptation to environmental conditions. Besides the evidence of differentiation provided by the analyses of SSR and Adh2 microsatellite variability, the inferred genetic groups from the lowlands of South America, i.e. Tropical Lowland and NEA Flours, also showed significantly different habitat suitability models, not only between each other but also with the other gene pools (Table 3). The two groups from the lowlands are strongly influenced by variables related to temperature (isothermality and temperature seasonality), though they seem to be affected differently by the rainfall regime, with a greater impact on NEA Flours. Altitude appears as a determinant factor for HM-US and Andean (Table 2), but with different maximum gain values (about 2500 and 3500 m, respectively). In agreement with our findings, recent studies of adaptation to high elevation in maize revealed that Highland Mexico and Andean landraces have largely distinct gene sets involved in highland adaptation [56]. On the other hand, it is worthy to mention that only the model of HM-US shows an important contribution of the variable mean diurnal range, probably because this group includes numerous temperate accessions. Like in our study, Hufford et al. [16] found that temperature seasonality is the most important variable for the teosintes and four indigenous maize landraces of Mexico. However, despite the fact that their landraces would probably be included in one or more of the groups inferred here, in general, they obtained different importance rankings for the variables. This could be related to the grouping criterion (i.e. landrace assignment vs. genetic structure), and to differences in the geographic scale considered. Indeed, it has been proposed that climatic variables are major limiting factors at large spatial scales, whereas the effect of climate is often masked by responses to local environmental variables such as soil, terrain, and habitat type at finer spatial scales [57]. In addition to our results of genetic and distribution modelling, diverse sources of evidence support the existence of a particular maize group from lowland middle South America. Most of the landraces of NEA Flours and all of the landraces of NEA Popcorns were collected from the Guaraní indigenous communities settled in the province of Misiones, Argentina. In contrast, NEA landraces collected outside these communities and currently maintained in the Germplasm Bank of INTA Pergamino, appeared to be greatly influenced by the Tropical Lowland gene pool (Fig. 1). In accordance with our findings, McClintock et al. [6] identified a South American complex named “Central Region group” of uncertain origin and age. The landraces of this group showed distinctive chromosome features contrasting markedly with landraces occurring in the vicinity; they were cultivated by the Guaraní and Kaingang communities principally distributed in Northeastern Argentina, Paraguay, southern Bolivia and southwestern Brazil. Moreover, the germplasm cultivated by the Guaraní people was included into the category “indigenous landraces” by Paterniani & Goodman [58], who recognised four major types: Avatí morotí, a floury yellow corn (the most abundant type), Avatí tupí or Cristal, a white Flint, and two popcorns, namely the round kernel type and the pointed kernel type. These authors assumed that popcorn maize was only cultivated in the region by the Guaraní people, whereas the Avatí morotí type was an ancient group which spread earlier, at a time when there were few maize landrace groups. In this context, it is reasonable to hypothesize that the landraces within the NEA Flours, which are locally known as Avatí (e.g. Avatí morotí, Avatí pará, Avatí yui) [59], correspond to either the Central Region or Avatí Morotí groups. Likewise, the remarkable genetic differentiation and the low variability levels among the NEA Popcorns coincide with the classification of Sanchez et al. [60] for the “Guaraní Popcorns” group based on morphological and isoenzymatic data; this also suggests a possible correspondence between both groups. Further study is needed to elucidate the precise origin of the NEA germplasm, as well as the route and date of their introduction. Conclusions Different authors have proposed middle South America as a contact region where the Andean landraces interbred with those of the eastern coast of South America [8, 11]. However, our data indicate that it is only a partial description of maize dynamics in middle South America. We believe that this region may have played a far more important role in the structuring of genetic variation since it harbours a unique, locally adapted gene pool. Here, we highlight its distinctiveness for the first time, and provide relevant information for the conservation and utilization of these genetic resources, as well as for a better understanding of environment-genotype associations in the context of maize population structure and historical processes. Additional files Additional file 1: Figure A1. Sampling localities of the individuals included in this study. Figure A2. Evaluation of STRUCTURE outputs. Figure A3. Sampling intensity and population structure. Figure A4. Discriminant Analysis of Principal Components (DAPC). Figure A5. Neighbour-joining network based on FST coefficients between the genetic clusters of maize landraces inferred by STRUCTURE. Figure A6. Frequency of the Adh2 microsatellite allele types in maize landraces from the Americas (N = 497). Table A1. Maize landraces from Northeastern Argentina genotyped for the present study. Table A3. Adh2 microsatellite allele types present in the landraces sequenced in this study. MSSA: Middle Southern South America. Table A4. Pair-wise comparison of private alleles between the genetic clusters inferred by STRUCTURE. Table A5. Differentiation among maize genetic clusters. Table A6. Adh2 microsatellite allele type counts per region including archaeological specimens, primitive and historic landraces (N = 497). Data from this study, Goloubinoff et al. [42], Freitas et al. [7] and Grimaldo Giraldo [18]. (DOCX 3582 kb) Additional file 2: Table A2. Compiled SSR data matrix (Excel). (XLSX 110 kb) Additional file 3: Table A7. Occurrence locations used for geographic distribution modelling. (XLSX 18 kb) Abbreviations AICcSample-size corrected Akaike’s Information Criteria AUCArea under the receiver operating characteristic curve DAPCDiscriminant Analysis of Principal Components ESAEastern South America HM-USHighland Mexico and United States MSSAMiddle Southern South America NEANortheastern Argentina NWANorthwestern Argentina SSRSimple Sequence Repeat. Acknowledgements We wish to thank the Guaraní communities and the Maize Germplasm Bank INTA Pergamino for providing the maize landraces used in this study and Dr. S. Pietrokovsky for kindly revising the English of the manuscript. We are also thankful to the anonymous reviewers whose comments and suggestions helped improve the manuscript. Funding Funding for this work was provided by the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET PIP 11220120100416CO 2013–2015), the Universidad de Buenos Aires (UBA, EX178), and the Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT, PICT 2012–0325). Availability of data and material The SSR and geo-referenced occurrence data sets supporting the conclusions of this article are included within the article and Additional files 2 and 3. The Adh2 microsatellite sequence data generated in this study is available in GenBank, with the accession numbers KU304471 to KU304494. Adh2 microsatellite motifs counts are included within Additional file 1. Authors’ contributions MB and JCH collected maize landraces from the Guaraní communities of Misiones. JCH conducted the taxonomic identification of landraces. MB and JC performed the genotyping experiments. MB, AMG and VVL analysed and interpreted the data. MB, AMG and VVL drafted and edited the manuscript. AMG and VVL conceived and designed the study. LP initiated the project and contributed to the work by the interpretation and discussion of the data. All authors reviewed and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate Not applicable. ==== Refs References 1. Matsuoka Y Vigouroux Y Goodman MM Sanchez GJ Buckler E Doebley J A single domestication for maize shown by multilocus microsatellite genotyping Proc Natl Acad Sci U S A 2002 99 6080 6084 10.1073/pnas.052125199 11983901 2. Iriarte J Holst I Marozzi O Listopad C Alonso E Rinderknecht A Evidence for cultivar adoption and emerging complexity during the mid-Holocene in the La Plata basin Nature 2004 432 614 617 10.1038/nature02983 15577908 3. Ranere AJ Piperno DR Holst I Dickau R Iriarte J The cultural and chronological context of early Holocene maize and squash domestication in the Central Balsas River Valley, Mexico Proc Natl Acad Sci U S A 2009 106 5014 5018 10.1073/pnas.0812590106 19307573 4. Grobman A Bonavia D Dillehay TD Piperno DR Iriarte J Holst I Preceramic maize from Paredones and Huaca Prieta, Peru Proc Natl Acad Sci U S A 2012 109 1755 1759 10.1073/pnas.1120270109 22307642 5. Blake M Staller J Tikot R Benz B Dating the initial spread of Zea mays Histories of Maize:multidisciplinary approaches to prehistory, linguistics, biogeography, domestication, and evolution of maize 2006 London Academic 55 72 6. McClintock B Kato TA Blumenschein A Chromosome Constitution of the Races of Maize, Its Significance in the Interpretation of Relationships Between Races and Varieties in the Americas 1981 Chapingo Colegio de Postgraduados 7. Freitas FO Bendel G Allaby RG Brown TA DNA from primitive maize landraces and archaeological remains: implications for the domestication of maize and its expansion into South America J Archaeol Sci 2003 30 901 908 10.1016/S0305-4403(02)00269-8 8. Vigouroux Y Glaubitz JC Matsuoka Y Goodman MM Sánchez GJ Doebley J Population structure and genetic diversity of New World maize races assessed by DNA microsatellites Am J Bot 2008 95 1240 1253 10.3732/ajb.0800097 21632329 9. Goodman MM Bird RM The Races of maize IV: tentative grouping of 219 Latin American races Econ Bot 1977 31 204 221 10.1007/BF02866591 10. Goodman MM Brown WL Sprague GF Dudley JW Races of corn Corn and corn improvement 1988 Madison American Society of Agronomy 33 79 11. Tenaillon MI Charcosset A A European perspective on maize history C R Biol 2011 334 221 228 10.1016/j.crvi.2010.12.015 21377617 12. van Heerwaarden J Doebley J Briggs WH Glaubitz JC Goodman MM de Jesus Sanchez Gonzalez J Genetic signals of origin, spread, and introgression in a large sample of maize landraces Proc Natl Acad Sci U S A 2011 108 1088 1092 10.1073/pnas.1013011108 21189301 13. Mir C Zerjal T Combes V Dumas F Madur D Bedoya C Out of America: tracing the genetic footprints of the global diffusion of maize Theor Appl Genet 2013 126 2671 2682 10.1007/s00122-013-2164-z 23921956 14. Bracco M Lia VV Hernández JC Poggio L Gottlieb AM Genetic diversity of maize landraces from lowland and highland agro-ecosystems of Southern South America: Implications for the conservation of native resources Ann Appl Biol 2012 160 308 321 10.1111/j.1744-7348.2012.00544.x 15. Lia VV Poggio L Confalonieri VA Microsatellite variation in maize landraces from Northwestern Argentina: Genetic diversity, population structure and racial affiliations Theor Appl Genet 2009 119 1053 1067 10.1007/s00122-009-1108-0 19639296 16. Hufford MB Martínez-Meyer E Gaut BS Eguiarte LE Tenaillon MI Inferences from the historical distribution of wild and domesticated maize provide ecological and evolutionary insight PLoS One 2012 7 e47659 10.1371/journal.pone.0047659 23155371 17. Ureta C Martínez-Meyer E Perales HR Álvarez-Buylla ER Projecting the effects of climate change on the distribution of maize races and their wild relatives in Mexico Glob Chang Biol 2012 18 1073 1082 10.1111/j.1365-2486.2011.02607.x 18. Grimaldo Giraldo CJ. Investigating the Evolutionary History of Maize in South America. PhD thesis, University of Manchester, Manchester, UK. 19. Bracco M Lia VV Gottlieb AM Cámara Hernández J Poggio L Genetic diversity in maize landraces from indigenous settlements of Northeastern Argentina Genetica 2009 135 39 49 10.1007/s10709-008-9252-z 18322805 20. Pritchard JK Stephens M Donnelly P Inference of population structure using multilocus genotype data Genetics 2000 155 945 959 10835412 21. Waits LP Luikart G Taberlet P Estimating the probability of identity among genotypes in natural populations: Cautions and guidelines Mol Ecol 2001 10 249 256 10.1046/j.1365-294X.2001.01185.x 11251803 22. Peakall R Smouse PE GENALEX 6: Genetic analysis in Excel. Population genetic software for teaching and research Mol Ecol Notes 2006 6 288 295 10.1111/j.1471-8286.2005.01155.x 23. Falush D Stephens M Pritchard JK Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies Genetics 2003 164 1567 1587 12930761 24. Evanno G Regnaut S Goudet J Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study Mol Ecol 2005 14 2611 2620 10.1111/j.1365-294X.2005.02553.x 15969739 25. Earl DA von Holdt BM STRUCTURE HARVESTER: A website and program for visualizing STRUCTURE output and implementing the Evanno method Conserv Genet Resour 2012 4 359 361 10.1007/s12686-011-9548-7 26. Rosenberg NA DISTRUCT: A program for the graphical display of population structure Mol Ecol Notes 2004 4 137 138 10.1046/j.1471-8286.2003.00566.x 27. Nicholson G Smith AV Jónsson F Assessing population differentiation and isolation from single-nucleotide polymorphism data J R Statist Soc B 2002 64 695 715 10.1111/1467-9868.00357 28. Jombart T Devillard S Balloux F Discriminant analysis of principal components: a new method for the analysis of genetically structured populations BMC Genet 2010 11 94 10.1186/1471-2156-11-94 20950446 29. Jombart T Adegenet: A R package for the multivariate analysis of genetic markers Bioinformatics 2008 24 1403 1405 10.1093/bioinformatics/btn129 18397895 30. Legendre P Legendre L Numerical ecology 1998 2 Amsterdan Elsevier 31. El Mousadik A Petit R High level of genetic differentiation for allelic richness among populations of the argan tree endemic to Morocco Theor. Appl. Genet 1996 92 7 832 839 10.1007/BF00221895 24166548 32. Nei M Molecular Evolutionary Genetics 1987 Tempe Arizona State University 33. Goudet J FSTAT: a computer program to calculate F-Statistics J Hered 2013 104 586 590 10.1093/jhered/est020 23576670 34. Szpiech ZA Jakobsson M Rosenberg NA ADZE: a rarefaction approach for counting alleles private to combinations of populations Bioinformatics 2008 24 2498 2504 10.1093/bioinformatics/btn478 18779233 35. Glaubitz JC CONVERT: A user-friendly program to reformat diploid genotypic data for commonly used population genetic software packages Mol Ecol Notes 2004 4 309 310 10.1111/j.1471-8286.2004.00597.x 36. Saitou N Nei M The neighbour-joining method: a new method for reconstructing phylogenetic trees Mol Biol Evo 1987 4 406 425 37. Felsenstein J Phylip: phylogeny inference package (version 3.2) Cladistics 1989 5 164 166 38. Liu K Muse SV PowerMarker: an integrated analysis environment for genetic marker analysis Bioinformatics 2005 21 2128 2129 10.1093/bioinformatics/bti282 15705655 39. Rambaut A FigTree, a graphical viewer of phylogenetic trees 2009 40. Untergasser A Cutcutache I Koressaar T Ye J Faircloth BC Remm M Primer3-new capabilities and interfaces Nucleic Acids Res 2012 40 1 12 10.1093/nar/gks596 21908400 41. Hall TA BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT Nucleic Acids Symp Ser 1999 41 95 98 42. Goloubinoff P Pääbo S Wilson AC Evolution of maize inferred from sequence diversity of an Adh2 gene segment from archaeological specimens Proc Natl Acad Sci U S A 1993 90 1997 2001 10.1073/pnas.90.5.1997 8446621 43. Di Rienzo JA, Casanoves F, Balzarini M, Gonzalez L, Tablada M, Robledo CW. Infostat version 2013. (2013) http://www.infostat.com.ar. Accessed 15 Oct 2013. 44. Phillips SJ Anderson RP Schapire RE Maximum entropy modeling of species geographic distributions Ecol Modell 2006 190 231 259 10.1016/j.ecolmodel.2005.03.026 45. Elith J Phillips SJ Hastie T Dudík M Chee YE Yates CJ A statistical explanation of MaxEnt for ecologists Divers Distrib 2011 17 43 57 10.1111/j.1472-4642.2010.00725.x 46. Merow C Smith MJ Silander JA A practical guide to MaxEnt for modeling species’ distributions: What it does, and why inputs and settings matter Ecography (Cop) 2013 36 1058 1069 10.1111/j.1600-0587.2013.07872.x 47. Scheldeman X, Van ZM. Training Manual on Spatial Analysis of Plant Diversity and Distribution. Rome: Bioversity International; 2010. http://www.bioversityinternational.org/e-library/publications/detail/training-manual-on-spatial-analysis-of-plant-diversity-and-distribution. Accessed 15 Nov 2015. 48. Hijmans RJ Cameron SE Parra JL Jones PG Jarvis A Very high resolution interpolated climate surfaces for global land areas Int J Climatol 2005 25 1965 1978 10.1002/joc.1276 49. Phillips SJ Dudík M Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation Ecography (Cop) 2008 31 161 175 10.1111/j.0906-7590.2008.5203.x 50. Warren DL Glor RE Turelli M ENMTools: A toolbox for comparative studies of environmental niche models Ecography (Cop) 2010 33 607 611 10.1111/j.1600-0587.2009.06041.x 51. Warren DL Seifert SN Ecological niche modeling in Maxent : the importance of model complexity and the performance of model selection criteria Ecol Appl 2011 21 335 342 10.1890/10-1171.1 21563566 52. Hanley JA McNeil BJ The meaning and use of the area under a receiver operating characteristic (ROC) curve Radiology 1982 143 29 36 10.1148/radiology.143.1.7063747 7063747 53. Hijmans RJ Guarino L Cruz M Rojas E Computer tools for spatial analysis of plant genetic resources data: 1. DIVA-GIS Plants Genet Resour Newsl 2001 127 15 19 54. Warren DL Glor RE Turelli M Environmental niche equivalency versus conservatism: Quantitative approaches to niche evolution Evolution 2008 62 2868 2883 10.1111/j.1558-5646.2008.00482.x 18752605 55. Schoener TW The Anolis lizards of Bimini: Resource partitioning in a complex fauna Ecology 1968 49 704 10.2307/1935534 56. Takuno S Ralph P Swarts K Elshire RJ Glaubitz JC Buckler ES Independent molecular basis of convergent Highland adaptation in maize Genetics 2015 26078279 57. Gaston KJ Measuring geographic range sizes Ecography (Cop) 1994 17 198 205 10.1111/j.1600-0587.1994.tb00094.x 58. Paterniani E Goodman MM Races of Maize in Brazil and Adjacent Areas 1977 Texcoco Centro Internacional de Mejoramiento de Maiz y Trigo 59. Cámara Hernández J Miante Alzogaray AM Bellón R Galmarini AJ Razas de maíz nativas de la Argentina 2012 Buenos Aires Editorial Facultad de Agronomía, Universidad de Buenos Aires 60. Sánchez JJG Goodman MM Stuber CW Racial diversity of maize in Brazil and adjacent areas Maydica 2007 52 13 30

PMC005xxxxxx/PMC5000443.txt

==== Front Malar JMalar. JMalaria Journal1475-2875BioMed Central London 149110.1186/s12936-016-1491-3ResearchHigh mobility, low access thwarts interventions among seasonal workers in the Greater Mekong Sub-region: lessons from the malaria containment project Canavati Sara E. sara.canavati@burnet.edu.ausaracanavati@yahoo.coms.canavatidelatorre@kellogg.oxon.org 12Quintero Cesia E. cesia.quintero@burnet.edu.au 1Lawford Harriet L. S. harrietlawford@gmail.com 3Yok Sovann yoksovann@yahoo.com 45Lek Dysoley soleyl@cnm.gov.kh 35Richards Jack S. jack.richards@burnet.edu.au 167Whittaker Maxine Anne maxine.whittaker@jcu.edu.au 81 Centre for Biomedical Research, Burnet Institute, Melbourne, Australia 2 Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, 420/6 Ratchawithi Road, Ratchathewi, Bangkok, 10400 Thailand 3 The National Centre For Parasitology, Entomology and Malaria Control, Ministry of Health, Corner Street 92, Trapaing Svay Village, Sankat Phnom Penh Thmey, Khan Sensok, Phnom Penh, Cambodia 4 Provincial Health Department, Pailin City, Pailin Province Cambodia 5 National Institute of Public Health, #2, St. 289, Toul Kork District, Phnom Penh, Cambodia 6 Department of Medicine, University of Melbourne, Melbourne, Australia 7 Department of Microbiology, Monash University, Melbourne, Australia 8 College of Public Health, Medical and Veterinary Sciences, Division of Tropical Health and Medicine, James Cook University, Townsville, QLD 4811 Australia 26 8 2016 26 8 2016 2016 15 1 43415 7 2016 16 8 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background During the process of malaria elimination in the Greater Mekong Sub-region, mobile and migrant populations (MMPs) have been identified as the most at-risk demographic. An important sub-group of MMPs are seasonal workers, and this paper presents an evaluation of the reach and effectiveness of interventions tailored towards this group and was carried out as part of the Containment Project from 2009–11. Methods A mixed-methods study was conducted in Pailin Province in Western Cambodia. Three-hundred-and-four seasonal workers were surveyed using a structured questionnaire. Qualitative data were gathered through a total of eight focus group discussions and 14 in-depth interviews. Data triangulation of the qualitative and quantitative data was used during analysis. Results High mobility and low access of the target population to the interventions, as well as lack of social and anthropological research that led to implementation oversights, resulted in under-exposure of seasonal workers to interventions. Consequently, their reach and impact were severely limited. Some services, particularly Mobile Malaria Workers, had the ability to significantly impact key factors, such as risky behaviours among those they did reach. Others, like Listening and Viewing Clubs and mass media campaigns, showed little impact. Conclusions There is potential in two of the interventions assessed, but high mobility and inadequate exposure of seasonal workers to these interventions must be considered in the development and planning of future interventions to avoid investing in low-impact activities and ensure that all interventions perform according to their maximum potential. This will be critical in order for Cambodia to achieve its aim of malaria elimination. The lessons learned from this study can be extrapolated to other areas of health care in Cambodia and other countries in order to reduce the gap between healthcare provided to MMPs, especially seasonal workers, and to the general population. Keywords Community malaria workerArtemisinin resistanceCambodiaMalaria eliminationHealth system strengtheningMobile malaria workerSustainable development goalsGlobal Fund to Fight AIDS, Tuberculosis and Malaria (CH)issue-copyright-statement© The Author(s) 2016 ==== Body Background The vulnerability of mobile and migrant populations In the final stages of elimination, the last foci of a disease is almost invariably found among vulnerable and marginalized demographic groups [1–4]. This is because these groups are systematically underserved, even by the world’s most well-resourced health systems. In order to “ensure the healthy lives and promote well-being for all at all ages” [5], as stated by Goal 3 of the Sustainable Development Goals, the unique needs of vulnerable and marginalized groups must be identified and confronted at the beginning of disease control and elimination efforts, and their broad range of health vulnerabilities must be addressed in a holistic and sustained manner. During the process of malaria elimination in the Greater Mekong Sub-region, mobile and migrant populations (MMPs) have been identified as the most at-risk groups due to activities in which they engage, as well as the health system’s inability to reach them with routine surveillance and response strategies used for the general population [6]. The Cambodian Containment Surveys of 2009–10 found the prevalence of malaria among MMPs to be substantially higher than among the general population [7] and that MMPs were three times more likely to suffer clinical episodes of malaria [8]. This clearly indicates that despite Cambodia’s national goal of eliminating all forms of malaria by 2025, MMPs are much farther from this target than the general population. MMPs are regularly engaged in forestry and cross-border activities, and as a result often live and sleep in mosquito-ridden forests, placing them at substantially higher risk of infection [9]. There is also a lack of health services appropriate for their needs. A scarcity of tailored malaria education means that MMPs often do not know how to prevent or recognize malaria, or when and where to seek timely treatment [10]. Due to their high mobility, the existing health system is unable to provide adequate treatment and follow-up even to those who do seek help. The over-representation of malaria incidence among MMPs is merely symptomatic of their broader lack of access to public services and their increased vulnerability to many preventable health problems. Development of MMP profiles and intervention packages A further barrier to addressing the needs of MMPs has been the fact that, although this is an extremely heterogeneous population, there are no clear definitions that will allow the identification of specific sub-group profiles with their particular risks and needs. In recognition of this gap, in 2012–2013 an MMP strategy that would enable malaria interventions to be tailored specifically to MMPs in Cambodia was undertaken by the National Malaria Control Programme and partners [11]. A standardized set of definitions appropriate to the Cambodian context was developed (Table 1), after which five different MMP profiles were identified based on a Population Movement Framework, MMP Activity Profiles, and a Malaria Risk Index, which is comprised of a vulnerability index, an exposure index and an access index [9]. Five strategic areas to be addressed were also identified: prevention, early diagnosis and treatment (EDAT), research, and surveillance, coordination and management [9]. Intervention packages that target each specific MMP profile while addressing each of these areas were then developed [9, 11]. An example of possible interventions per strategic area and MMP profile can be found in Table 2. It should be noted that a selection of these interventions were actually implemented in this study.Table 1 Mobile migrant population (MMP) strategy definitions Forest malaria Malaria ecosystem and transmission is closely related to forested areas in Southeast Asia Related activities of population Population movement in relation to malaria, the main focus should be on the interaction/exposure of MMP with the forest Local population Permanent resident in the area for more than 1 year Mobile population Resident in the area for less than 6 months Migrant population Resident in the area for more than 6 months and less than 1 year Visitors (from abroad to the country) Person admitted for short stays for purposes of leisure, recreation, holidays; visits to friends or relatives; business or professional activities. Visitors include excursionists, tourists and business travellers. Tourists, visiting relatives who might spend one or two nights in or near the forest (e.g., family event, ecotourism) Seasonal workers Agricultural activities occurring during planting season (end of dry season) and harvesting season (end of rainy season), usually in foothills/plains/valleys. (e.g., farming/chamkar, rubber, cassava plantations) Construction/mine workers Activities related to infrastructure construction or mining in forested areas, usually in upland forest/hills/valleys. (e.g., dam or road construction, gold or gem mines) Forest workers Activities in heavily forested and remote areas in small mobile groups, usually in upland forest/hills. (e.g., forest products gathering, hunting, logging, fishing) Security personnel Activities related to patrolling in forested border areas Table 2 Proposed interventions and delivery channels Delivery mechanisms Stage of journey Strategic area Categories of MMPs Forest workers Construction workers Seasonal workers Retail sales (subsidized); voucher system Lending scheme; retail sale; voucher system Lending scheme; retail sale; voucher system Behaviour change communication Pre-departure en route upon arrival Prevention Mass media; taxi driver scheme Mass media; IPC through MMWs; taxi driver scheme Mass media; IPC through MMWs; taxi driver scheme LLINs Pre-departure en route upon arrival Prevention Forest package; taxi driver scheme Forest package; taxi driver scheme; LLIN/ITN lending scheme Forest package; taxi driver scheme; LLIN/ITN lending scheme Diagnosis treatment Upon arrival EDAT MMWs; stand-by treatment MMWs; company health workers; MMWs MMP-surveillance Upon arrival Surveillance Local authorities Local authorities; company Local authorities; plantation/farm owner/manager MMP-malaria information systems Upon arrival Malaria surveillance mHealth; private/public private mix mHealth; private/PPM; MMWs mHealth; private/PPM; MMWs Evaluation of interventions Some of the interventions that were selected for the proposed intervention packages had already been implemented in Cambodia during the Containment Project [12], while others had not. This paper presents data from a mixed methods study that was undertaken in order to evaluate the effectiveness of prevention and EDAT interventions among seasonal workers in Pailin Province. MMPs who fit the ‘seasonal worker’ profile are a particularly prominent high-risk group in Pailin. Seasonal workers are engaged in agricultural activities during the planting and harvesting seasons, which take place at the end of the dry and rainy seasons, respectively. Usually they work in farms and plantations in foothills, plains and valleys; these include rice, corn and cassava farms, and rubber plantations (Table 2). The interventions assessed in this study were designed to specifically target seasonal worker MMPs. Therefore, the study sites consisted exclusively of farms and plantations, where seasonal workers stay. This paper aims to examine the reach and effectiveness of these interventions. It is hoped that lessons learned from this study can help to improve these interventions, and allow the rest of the proposed interventions packages to be implemented more effectively among seasonal workers. Methods Interventions assessed The following interventions were implemented in a Malaria Containment Project in Pailin Province, Western Cambodia in 2009–11: (1) a mass media education campaign broadcasted throughout areas of drug resistance was used to target MMPs. One film and several television and radio spots addressing malaria resistance, treatment and prevention were broadcast during what were believed to be peak viewing times [13, 14]. Listener and viewer clubs (LVCs) aimed to establish a collective ‘listening and/or viewing group’ that allowed participants to listen to or view programmes, and then actively engage in discussions. Mobile broadcasting units were set up in farms with no access to television or radio. Once a month, television and radio programmes were broadcast in the farm’s community centre, a space where workers often get together to socialize and drink after work. After the broadcast, the audience was engaged in a discussion and question and answer session [13, 14]; (3) an insecticide-treated net (ITN) lending scheme was implemented in farms where MMPs tended to work [15], as seasonal workers do not have access to the same free net-distribution scheme that villagers have. It empowered farm owners to lend ITNs to their employees and educate them on the benefits of using them; (4) taxi drivers in Palin Province were trained to provide malaria education and materials to MMPs and divert symptomatic passengers to a health facility upon obtaining their consent, due to the fact that 75 % of seasonal workers use taxis as their primary means of transportation [16]; and, (5) Mobile Malaria Workers (MMWs) were introduced in 2009 to provide health services to MMPs, as detailed elsewhere [17]. MMWs are a critical component of the national strategy to eliminate and contain drug-resistant malaria among MMPs in Cambodia. Among other things, they play a key role in providing EDAT to MMPs, including seasonal workers, who come to them seeking help for malaria symptoms. They also provide behaviour change communication to the MMPs and farm owners with whom they interact. Study team training and composition Just prior to the fieldwork, a three-day workshop took place. Training was given on the purpose and exact procedures of the interviews and note taking, as well as on conducting interviews. In addition, a detailed guide with the standard operating procedures was provided to the field team. There were a total of three teams with two members per team. All tools were pre-tested in a community not already selected for the survey. A mixed-methods assessment of these interventions was conducted. Quantitative strand Sampling A cross-sectional study was carried out using a structured questionnaire. The target population of the study were seasonal workers at all MMW-assisted farms in Pailin Province. These farms had between 20 and 100 migrant workers in each farm. The MMW project did not target farms with less than 20 workers, so these farms could not be assessed in the study. At the time of the study, 28 MMW-assisted farms were actively operating in Pailin Province. The required sample size was calculated using the main outcome indicator of the 2009 Containment Survey; a 60 % rate of long-lasting, insecticidal bed net (LLIN) use the night before the survey [8]. The sample size was, therefore, calculated to be 304 individuals based on an expected 60 % LLIN use, with a 5 % acceptable error, a type I error of 0.05 and a 10 % estimated non-response rate. The farm manager provided a list of names of seasonal workers in each farm, 80 % of whom were randomly selected to participate in the study; each farm was considered as one cluster; 304 individuals were selected with randomization at farm level. It included spouses in some cases, but no children were included. Data analysis Data were double-entered using an Epi Info® database. Analysis was performed using Stata® version 11 (StataCorp LP, College Station, TX, USA). Descriptive statistics, including basic frequencies and simple proportions, were calculated. The Mantel–Haenszel Chi square test or the Fisher’s exact test was used to calculate significance. Qualitative strand Data collection and sampling Qualitative data were gathered between December 2012 and January 2013 through eight focus group discussions (FGDs) (64 participants) and 14 in-depth interviews (IDIs) (14 participants) in two purposively selected farms. The data collection instruments were based on previously published methods [18] and on the Health Belief Model, and were further adapted throughout the study as necessary. Participants included MMWs, farm owners, seasonal workers, and taxi drivers. Purposive sampling was used to select participants to ensure gender distribution, a variety of ages, geographical provenances, intra-provincial travel capacities, and occupations. FGDs A total of eight FGDs were conducted among seasonal workers in MMW-assisted farms. Two farms in each health centre’s catchment area were purposively selected for geographical balance. As male and female workers have different risks and vulnerabilities, in each farm, two male and two female FGDs were conducted. Each FGD consisted of eight participants (N = 64). IDIs A total of 14 IDIs were conducted: three with farm owners, five with MMWs and six with taxi drivers. Farm owner and MMW IDIs took place at the same two farms as the FGDs. Taxi driver IDIs took place at the taxi stand in Pailin town. Data analysis FDGs and IDIs were recorded, fully transcribed, and translated into English. Data analysis consisted of examining, categorizing and tabulating or recombining the data. Thematic analysis around the key themes of the project was undertaken using Nvivo 9® software. These themes were clustered to form overarching, larger themes. Triangulation and critical case analysis added rigour to the process. Ethical issues Ethical clearance was obtained from the Cambodian National Ethics Committee for Health Research in August 2011 (130NECHR). Pailin local authorities, village chiefs, commune heads, and farm owners were informed of the purpose and expected duration of the study. Their approval and cooperation was sought in every aspect of data collection. For the quantitative strand, prior to the interview, the interviewer read carefully the consent form. This consent form contains information on the objectives of the survey, the risks, benefits and freedom of the participation, as well as information on confidentiality. Each survey participant provided informed written consent before participation. For the qualitative strand, the interviewers followed the Code of Ethics of the American Anthropological Association (AAA). As proposed by the AAA, all interviewees were informed before the start of the interview about the project’s goals, the topic and type of questions, the intended use of results for scientific publications, and their right to refuse the interview, interrupt the conversation at any time, and withdraw all given information during or after the interview. Anonymity was guaranteed and the confidentiality of interviewees assured by assigning a unique code number to each informant. Participants’ approval and cooperation was sought in every aspect of data collection. Results Demographic characteristics of seasonal worker study participants All of the 304 seasonal workers who were approached for the study gave consent and participated in the survey. The average age of participants was 32 years, 55.6 % were males. The majority were farmers working in rice fields (48.7 %) and agricultural labourers working on other crops (49 %). Most had completed primary or secondary school or post-secondary education (57.9, 17.8 and 4.6 %, respectively), but 19.7 % had never attended school. The majority were married (66.1 %) (Table 3). The length of stay in farms was relatively short; for most seasonal workers it was less than a month (45.8 %), although others stayed for a longer period of around one or 2 months (39.4 %). More than half of the participants reported that it was their first time working in Pailin (Table 4).Table 3 Sociodemographic characteristics of the seasonal workers Sociodemographic characteristics Total N % Gender  Male 169 55.6  Female 135 44.4 Age in years (mean, SD) [32, 10.6] Primary occupation  Agricultural labourer 149 49.0  Seller 1 0.3  Fisherman 1 0.3  Forestry worker 2 0.7  Farmer 148 48.7  Housewife 1 0.3  Other 1 0.7 Highest level of education  Never attended school 60 19.7  Completed primary (grade 6) 176 57.9  Completed secondary (grade 12) 54 17.8  More than secondary 14 4.6 Marital status  Single, never married 89 29.3  Married/living with someone as married 201 66.1  Widowed 7 2.3  Divorced/separated 6 2.0  Married but not living together 1 0.3 Normally stay in the farm all year  Yes 47 15.5  No 254 84.5 Accompanied bya  Family 35 74.5  Friends 7 14.9  Alone 5 10.6 aOut of those who stay at the farm all year Table 4 Frequency and duration of stay in Pailin farms Seasonal worker characteristics Total N % First time working in Pailin  Yes 166 54.6  No 138 45.4 Number of times worked in Pailin before (times)  1–2 73 52.8  3–4 28 20.3  >5 37 22.3 Frequency of coming to work in Pailin  Once a year 38 27.5  Twice a year 53 38.4  Three times a year 10 7.3  >3 times a year 14 10.1  I never leave 23 16.7 Length working in the farm (mean, SD) [18 weeks, 54] (weeks)  <2  181 59.5  3–4 41 13.5  5–6 10 3.3  7–8 12 4.0  >8  60 19.7 Duration planned for this tripa (months)  <2  151 49.7  >2  152 50.3 Ways to find places of manual labour  Friends 39 12.8  Farm owner 126 41.5  Used to come here before 23 7.5  Neighbour 109 35.9  Family member 73 24.0 aThe 2-month cut-off point was defined as short-term migrants compared to those who stay for longer periods >2 months Evaluation of interventions Education through mass media Television was used more frequently than radio. Nevertheless, access to both radio and television was low. Even amongst participants who routinely consumed these media when not working at a farm, 54.7 % had not listened to the radio in the last month and 46.4 % had not watched television (Table 5). Only 22.1 % used radio and 25.4 % television on a daily basis while at the farm. This lack of access to media was reportedly due to a lack of time, reliable electricity, or access to a television set. Even though television was used more frequently than radio, more respondents had access to a radio set than to a television. Radio was a more common source of health messages despite being used less frequently. Children’s viewing habits were influential in determining the television programming of their parents. Respondents listened to the radio less in rainy (March/April) and harvest (July) seasons than at other times of the year. This observation was unexpected and requires further exploration in future studies. The study also found that the radio and television spots were not broadcast during this particular population’s peak viewing and listening times. National television channels were most often viewed between 17.00–18.00 and 21.00–22.00; key radio listening times were 06.00–0.7.00, 11.00–13.00 and 17.00–19.00 h.Table 5 Media habits of seasonal workers in Pailin Province Media habits Overall N % How often listen to the radio  Once a week 12 6.6  2–4 times a week 26 14.4  5–6 times a week 4 2.2  Daily 40 22.1  Never 99 54.7 Last week, heard a message about malaria on the radio  Yes 28 36.4  No 49 63.6 How often watch television  Once a week 13 9.4  2–4 times a week 25 18.1  5–6 times a week 1 0.7  Daily 35 25.4  Never (during last month) 64 46.4 Last week, heard a message about malaria on television  Yes 14 51.9  No 13 48.2 Listener and viewer clubs Seasonal workers reported that the information presented through LVCs was interesting and easy to remember, as there were “many pictures”. Nevertheless, in general they were mostly ineffective at reaching seasonal workers; only 11.8 % of respondents had attended an LVC event. There was no significant increase in malaria knowledge among them. Seasonal workers had obtained the vast majority of their malaria-related knowledge from friends and family; official sources such as radio, television and MMWs were not predominant. Most of the malaria messaging reported by seasonal workers was inaccurate (Table 6).Table 6 Communication and key messages reported by seasonal workers Communication Overall N % Messages or information related to malaria prevention heard  Malaria is caused by mosquito bites 258 84.9  Wear long sleeved clothes from dusk to dawn to prevent mosquito bites 121 39.8  Sleep under a mosquito net every night 175 57.6  Sleep under an insecticide-treated net 140 46.1  Buy the bundled net at the market and dip it with Super-Malatab 11 3.6  Super-Malatab is free, safe and easy to use 2 0.7  Malaria is dangerous 5 1.6  Malaria can kill 1 0.3 Messages related to malaria diagnosis and treatment heard  Seek treatment for malaria from a MMW 202 66.5  Visit your MMW for free malaria diagnosis and treatment 39 12.8  Get a blood test before taking anti-malarial drugs 79 26.0  If you have fever, always seek a blood test for malaria at nearest health facility 59 14.4  Complete anti-malarial treatment 10 3.3  Do not buy cocktail; your malaria will not be cured 2 0.7 Messages related to using and caring for mosquito nets heard  Sleeping under an ITN is especially important for pregnant women 2 0.7  Sleeping under an ITN is especially important for children under 5 years old 3 1.0  Carry and sleep under a mosquito net when travelling 92 30.3  Carry and sleep under a mosquito net when visiting the forest 28 9.2  The less you wash your treated net the longer it will retain its effectiveness 30 9.9  Repair any holes in the net 52 17.1  Do not use too much soap when washing your net 27 8.9  Dry mosquito net indoors 124 40.8  Prepare floor before tying 143 47.0 Source of messages  MMW 68 22.4  Health facility staff 60 19.7  Private health provider/pharmacy 4 1.3  Teachers/religious leaders/monks 6 2.0  Family member/friend/neighbour 195 64.1  Television 81 26.6  Radio 88 29.0  Mobile video unit 5 1.6  Poster/leaflet/brochures/billboards 28 9.2  NGO staff 29 9.5 Have attended an event in the community with a screen/speaker on health messages  Yes 36 11.8  No 268 88.2 Mobile Malaria Worker services The majority of seasonal workers (71.1 %) did not know that an MMW was available for consultation in their region (Table 7), in large part because of the brevity of their stay there. As a result, they were the least common source of malaria education. MMWs were also the least common source for malaria education through non-media-related communication (15.6 %); the most common sources were family and friends (Table 8). In addition, MMWs were the least common source for seeking diagnosis when malaria infection was suspected (21.1 %) or obtaining drugs for malaria treatment (15.4 %). Seasonal workers instead sought care from other public health providers and private health providers (81.3 and 31.3 %, respectively) and obtained drugs from private health providers 46.2 % of the time (Table 9).Table 7 Seasonal workers’ perceptions of Mobile Malaria Workers (MMWs)’ role MMWs Overall N % Know the MMW  Yes 88 29.0  No 216 71.1 MMW visited the migrants while in the farma  Yes 76 86.4  No 12 13.6 Received malaria education from MMWa  Yes 81 92.0  No 7 8.0 Know that free malaria testing/treatment is available from MMWs  Yes 84 95.4  No 4 4.5 Previously contacted MMW when having fever  Yes 48 54.5  No 40 45.5 Ways migrants have contacted MMW  Went to the MMW 59 67.1  MMW visited the migrant worker 16 18.2  Migrant worker never contacted MMW 13 14.8 aOut of those who have meet the MMW (n = 88) Table 8 Interpersonal communication Interpersonal communication Overall N % Ever discussed any topics concerning malaria  Yes 218 71.7  No 86 28.3 Person with whom discussed malaria  Family member 118 82.6  Villager 46 21.1  Friend 93 42.7  MMW 34 15.6 Topics discussed  How to prevent malaria 163 74.8  How malaria is transmitted 102 46.8  How to treat malaria 53 24.3  Malaria drug resistance 4 1.8  Malaria testing 36 16.5  Where to seek advice 16 7.3  Who to seek advice from 4 1.8 Table 9 Options for seeking malaria treatment Variable Treatment sought at MMW N (%) Public health provider N (%) Private health provider N (%) Other N (%) First action if a migrant thinks he/she has malaria 64 (21.1) 247 (81.3) 95 (31.3) 102 (33.6)a Potential place visited for malaria test 64 (21.1) 263 (86.5) 89 (29.3) – Action taken if malaria test positive 54 (17.8) 271 (89.1) 113 (37.2) 14 (4.6)b Action to be taken if febrile patient with negative malaria test N/A 265 (87.17) 110 (36.18) 58 (19.1)c Multiple answers by all interviewed migrants (n = 304) where possible aOther includes take malaria test n = 86 (28.3 %); take drugs for malaria n = 16 (5.3 %) bOther includes traditional medicine n = 4 (1.3 %); stay home n = 2 (0.7); self treatment n = 8 (2.6) cOther includes stay home n = 7 (2.3); self-treat n = 43 (14.1); traditional medicine n = 8 (2.6) A typical conversation during FGDs between seasonal workers and the moderator went as follows:M: Don’t you know that in the fields there are volunteers who help treat malaria? P4: I don’t know because I’m just a new arrival. M: How many days have you been here? P4: 6 days. M: So, all of you, do you know that in the fields there are volunteers who help cure malaria fever? P1: Don’t know. P3: If we were living here for one or two years, surely we would know. M: So, do you know, brother? P6: No, I don’t. […] M: So none of you here know that there are volunteers in the fields, do you? P5: No! (FGD 04 Seasonal workers) The need for a more active mode of outreach to seasonal workers directly on the farms was a frequent subject of conversation among all participant categories. It was suggested that MMWs should post a sign or logo outside their home identifying themselves, so that seasonal workers and visitors know where to seek help. MMWs proposed going door-to-door to inform newcomers of their presence in the area. Even when seasonal workers did come to MMWs for diagnosis, stock-outs often forced them to obtain anti-malarials in the private sector:…If the health centres did not have medicine, I wrote letters to malaria centre…so that patients could get medicine from the centre. If the centre had no medicine, I sent them to a private clinic. (IDI 05, MMW, male). MMWs reported that seasonal workers’ limited exposure to malaria education in their place of origin was a significant problem:The difficulty is that we cannot educate them as we educate villagers living with us. They don’t know much about methods of preventing malaria and about symptoms of malaria. Due to their lack of knowledge, migrants try to bear with the disease and think that it is a cold, and after a few days it becomes severe malaria. (IDI 02, MMW, male). MMWs also reported difficulties in providing quality care to seasonal workers, as the lack of access to transportation makes it difficult to transfer them to a health centre when they need specialized care, and their high mobility makes it nearly impossible to provide follow-up once treatment was started. Seasonal workers themselves agreed that their high mobility and lack of access was a significant barrier:There is no hospital around the farm. We have to go far away to Pailin city. Those who have worked here for a very long time know where to go for treatment because they have access to the village malaria worker, but for us, we don’t know where to go because we keep moving from one farm to another. Whenever we get sick, we go to state-run hospital in Pailin City or buy medicine at pharmacy. (FGD 08, Seasonal workers). Nevertheless, seasonal workers who received health services from MMWs were highly satisfied with the quality of the services provided in over 90 % of encounters (Table 10). MMWs were their most trusted source of malaria information, as they perceived them to be most knowledgeable. Close to no misconceptions on malaria knowledge were found among MMWs in qualitative interviews. Seasonal workers who had received health education from an MMW were 2.1 times more likely to report sleeping under an ITN the night before the survey (P = 0.002). Those who reported sleeping under an ITN the night before were 2.1 times more likely to discuss malaria-related topics with others (P = 0.006). Interpersonal communication (IPC) was the preferred method of malaria education (71.7 %) for seasonal workers.Table 10 Reported satisfaction of services delivered by mobile malaria workers (MMWs) Reported satisfaction of MMW services Overall N % MMW able to provide advice 82 93.2 Easy to get in touch with the MMW 82 93.2 Easy to communicate with the MMW 84 95.5 MMW understands malaria 79 90.1 MMW provides support (testing and treatment) 82 93.2 Satisfied by MMW services 84 95.5 Would refer an ill friend to MMW 84 95.5 MMWs themselves felt well accepted, and interviews showed that their services are appreciated:Volunteers don’t look down on us. When we go to see them, even though they are working, or stay far from us, they will come fast. There isn’t any problem. (FGD 08, Seasonal workers). It was the consensus among MMWs, farm owners and seasonal workers, that the work of MMWs is highly beneficial, and also provides a financial benefit:For me, I think it is very good that malaria volunteers come and teach about malaria prevention. As a farm owner, I can be aware of how I can help prevent my workers from being attacked by such a disease, and I can see many benefits. First, the workers working here are not sick, so they can speed up their work for me. Second, it is the workers’ benefit that they do not need to spend their money on medicines, and they can save some money to go back home. Next year they will work with me again since they can keep a good deal of money, won’t they? (IDI 01, Farm owner). Migrant workers know that it is so beneficial when they come and get the medicine from me. If they are too ill to come, I can approach them. If they do not come to get the medicine from me, they have to spend up to 30,000 Riels (7.5 US$) for the motor taxi. (IDI 06, MMW, female). LLIN/ITN lending scheme The lending scheme had very high satisfaction rates. 98 % of seasonal workers who accessed the scheme were highly satisfied with the set-up; 97 % liked using an LLIN. 83 % had used the scheme in the past. Nevertheless, only 19.7 % of seasonal workers were found to have access to the LLIN lending scheme, as access very much dependent on the farm owners’ willingness to run the scheme. Some farm owners who did not participate in the lending scheme said they were too busy to take on this responsibility, or could not see what benefit it would bring them. Some declined to participate because “nets are meant to be free”. They also pointed to a lack of incentives that would compensate them for the additional effort invested in running the scheme. Farm owners who implemented the scheme seemed to have an interest in protecting their labour force from malaria. When asked if they would consider buying nets for their workers if the lending scheme came to an end, a number of them said they would, as having healthier employees is more advantageous to them. Others said that they would be prepared to advance labourers’ wages to enable workers to buy nets from local markets at the beginning of their stay. Seasonal workers currently enrolled in the scheme most often said that they had not brought a net with them because either their net was torn, they had been in a great hurry when migrating, or they did not have the money to buy one. Only 50 % of seasonal workers currently enrolled in the scheme were willing to pay out of their own pockets for a net if the scheme came to an end. Taxi driver scheme Taxi drivers indicated that the satisfaction they gained from playing a leadership role and protecting others from malaria infection were their main motivators for volunteering in the scheme. They said that they referred clients who were ill with fever to a hospital or MMW, and transported them there whenever possible. Although the majority of taxi drivers displayed competent malaria knowledge, particularly with regard to recognizing symptoms and accessing malaria services, many had crucial knowledge gaps regarding matters such as the role of mosquitoes in the spread of malaria and effective use of bed nets. Many drivers themselves did not use ITNs, instead opting for untreated nets. Discussion This is the first published study assessing the effectiveness of malaria interventions tailored specifically to seasonal workers in Pailin Province, the global epicentre of multidrug-resistant malaria. The study found that that even though these interventions were specifically designed for seasonal workers, they largely failed to have the expected impact because they were not accessible to their target population, or because seasonal workers were too mobile and did not remain in the area long enough to be impacted by continual exposure to the interventions. MMW services and the LLIN lending scheme were the most successful interventions for seasonal workers in Cambodia but overall their impact was limited due to low access. Similar issues have found to affect other health services being provided to MMPs [19, 20]. Mass media and LVCs Behaviour change communication strategies have been highly successful in Cambodia among the general population [21], and it is natural to seek to expand those messages using mass media strategies. Nevertheless, major constraints to effective use of mass media in this study included limited access to radio and television sets, and the discrepancy between peak viewing times of seasonal workers and the times during which radio and television malaria spots were broadcast. LVCs were also largely unsuccessful. This is likely because seasonal workers proved to be too highly mobile to be reached effectively and consistently by them; the average seasonal worker spent less than 1 month at the farm, and LVCs were held only once a month. It was also noted that workers who intended to consume alcohol and unwind often frequented the meeting places where LVCs were held, therefore making it a less effective environment for educational activities. MMW services Seasonal workers unanimously rated the quality of services provided by MMWs as exceptionally high on all counts and MMWs could be extremely effective in combating malaria if they were able to have face-to-face contact with seasonal workers. MMWs provided health messages through IPC, the preferred method of education for seasonal workers. When they did so, they became the most trusted source of information and were reportedly successful in modifying risky behaviours and disseminating malaria education. A recent study has documented that IPC is the most successful form of behaviour change communication in Western Cambodia [21]. MMWs in this study had very few malaria-related misconceptions, which was not the case for the main village malaria workforce in a recent assessment [17]. They were therefore an accurate source of IPC that, with sufficient exposure, could successfully counter the misconceptions that this study found were disseminated through the most common source of malaria education: friends and family. MMWs were also well received by both farm owners and workers, even viewed as an economic advantage to both. It is clear that they were effective, reliable and ideally suited to providing both prevention and EDAT to seasonal workers. It is therefore highly disappointing that MMWs were the least-accessed source of both education and malaria services due to a lack of awareness and access. The MMW programme has enormous potential that can be leveraged by pro-actively reaching out to seasonal workers immediately after their arrival. MMWs should employ marketing techniques to make their presence known in the area and should encourage community participation in prevention practices, as seen in other settings [22–26]. Lessons learned from village malaria workers and community health workers to improve motivation, satisfaction, barriers to follow-up, scale-up, expanding activities, and improving the effectiveness of interventions can be applied to MMWs [17, 27–35]. Of concern was the fact that a large proportion of seasonal workers sought treatment in the private sector, despite evidence that the private sector often treats malaria with counterfeit or sub-standard drugs that are a major driver of evolving multidrug-resistance in the area [36]. It has also been documented that stock-outs, as reported by MMWs in this study, are a major driver of private sector health-seeking among MMPs [17]. It is critical to resolve supply chain inefficiencies. LLIN/ITN lending scheme The ITN lending scheme demonstrated a significant level of success in addressing the lack of availability of ITNs among seasonal workers, and enjoyed a 98 % satisfaction rate. Nevertheless, with only 20 % of seasonal workers accessing it, it is clear that the scheme would need to be scaled-up significantly in order for it to be effective. Educating farm owners on the financial benefits of a healthy workforce, and providing incentives for launching the scheme should persuade more farm owners to implement it. However, it is essential that a plan for sustaining the scheme be developed prior to scale-up, as another study found that between 2011 and 2013, 16 % of loaned ITNs were broken, 24 % were lost and approximately 40 % were not returned [15]. In an unpublished respondent-driven sampling study conducted among migrant workers in Western Cambodia while this lending scheme was ongoing, a much higher proportion of migrant workers slept under a bed net in Pailin than in a neighbouring province, and the number of migrant workers that slept under a borrowed net was double that of the other province [37]. This suggests that the lending scheme made a noticeable positive impact. Taxi driver scheme The taxi driver scheme showed promising results due to high motivation from the drivers, and the added convenience of being able to transport patients to a health facility immediately. The inadequate knowledge of malaria-related subjects for some taxi drivers however, was concerning and presents many opportunities for improvement. A reminder sheet with basic facts and details could serve to support the delivery and consistency of key messages. The scheme could also be expanded to buses in order to target seasonal workers using cheaper forms of transportation, as they are likely to be even more economically disadvantaged [38]. Bus and taxi drivers could also be provided with ITNs to sell for a very small profit. Study limitations Potential limitations of the study relate to the self-reporting nature of the data and the lack of a comparison to actual observed behaviours. It is also important to note that some of the responses given by seasonal workers to MMWs may have been biased by the desire to provide socially acceptable answers (i.e., seasonal workers who had been in contact with an MMW were 2.1 times more likely to report sleeping under a bed net; this suggests that they had received malaria messages from the MMW that either had increased their knowledge and therefore alerted them to the social desirability of this answer, or successfully modified their behaviour. It is difficult to know the proportions of each). A further possible limitation relates to the high-mobility of the seasonal workers and the likelihood that this limited the duration of interventions and therefore their potential impact. This however, is the nature of seasonal workers lives and reflects the difficulty in implementing long-term interventions for this group. The need for future social and anthropological research In future, rigorous social and anthropological research should be undertaken when planning new interventions [39]. In doing so, it is crucial to remember that MMPs are a highly heterogeneous demographic, and what applies to one group may not apply to another [9, 40]. The use of social and anthropological research to more clearly define MMP profiles can then be used to tailor interventions more effectively (Table 11). For example, MMPs’ frequent travels between endemic and non-endemic areas are a major factor in their vulnerability to malaria, and anthropological studies have helped to tailor specific interventions to different MMP sub-groups during the various stages of migration (Table 2) [9, 41, 42]. Similarly, in this study, MMWs reported that seasonal workers from non-endemic areas had increased chances of infection by failing to protect themselves because of a lack of being exposed to basic malaria education, an issue that could be addressed by focused pre-departure interventions.Table 11 Summary of mobile migrant population profiles (Adapted from Guyant et al. [9]) Variables Forest workers Construction workers Security personnel Seasonal workers Visitors Profile FW CW SP SW T Main activities Hunting, fishing, logging, non-timber forest products Dam or road construction, mining Patrolling Farming, plantation, chamkar Population type Local, Mobile, Migrant Mobile, Migrant Mobile, Migrant Local, Mobile, Migrant Mobile Forest/malaria exposure Location from forest In forest In forest/forest fringe In forest Forest fringe Forest fringe Duration of stay in forest 1–4 weeks 1–6 months Weeks to months? 1–4 weeks 1 week Forest exposure High Medium to high High Low to medium Low Housing type Tents, none Huts, barracks, tents Huts, barracks, tents Tents, huts Wooden or concrete house Working conditions/access/outreach Work area Forest, hills Forest, hills Border forest Foot hills, plains, valleys Work location Mobile Fixed Semi-mobile Fixed Link/affiliation None or village for local population Company Government Farm owner/company None Main point of contact None or village for local population Company Military base Farm owner/company Guest houses/hotels Conclusions The study found that there was real potential in two out of five of the interventions assessed, although longer term sustainability was not evaluated. Nevertheless, low access and high mobility of seasonal workers affected the degree of exposure they had to the interventions, and therefore the degree to which they could be impacted by them. These two factors must be accounted for in the development and planning of future interventions to avoid investing in low-impact activities and ensure that all interventions perform according to their maximum potential. The lack of access is a barrier that must be overcome if malaria elimination is to be achieved. Lessons learned from this study can be extrapolated to other areas of health care, with the hope that they can reduce the gap between health care provided to MMPs and to the general population. Abbreviations EDATearly diagnosis and treatment FGDfocus group discussion IDIin-depth interview IPCinterpersonal communication ITNinsecticide-treated net LLINlong-lasting, insecticidal net LVCslistener and viewer clubs MMWsmobile malaria workers MMPsmobile and migrant populations Authors’ contributions SEC and MAW designed the study protocol and study tools; SEC and SY oversaw data collection for the surveys; SEC and CEQ analysed the data; HL, DL and JSR co-wrote the manuscript; SEC, CEQ and MAW wrote the manuscript; All authors read and approved the final manuscript. Acknowledgements We would like to thank the public health department staff of Pailin Province for their collaboration and assistance in data collection, and to all the individuals who kindly gave their time to participate in this study. We thank the reviewers for their valuable input in this paper. Competing interests The authors declare that they have no competing interests. Availability of data and materials All data and materials are fully available. Ethics approval and consent to participate Ethics was obtained from the Cambodian National Ethics Committee for Health Research in August 2011. For the qualitative strand, the interviewers followed the Code of Ethics of the American Anthropological Association. Each study participant provided informed written consent. Funding Funding for this study was obtained under Global Fund R9 from The Global Fund to Fight AIDS, Tuberculosis and Malaria. ==== Refs References 1. Cotter C Sturrock H Hsiang M Liu J Phillips A Hwang J The changing epidemiology of malaria elimination: new strategies for new challenges Lancet 2013 382 900 911 10.1016/S0140-6736(13)60310-4 23594387 2. Feachem R Phillips A Hwang J Cotter C Wielgosz B Greenwood B Shrinking the malaria map: progress and prospects Lancet 2010 376 1566 1578 10.1016/S0140-6736(10)61270-6 21035842 3. Fenner F A successful eradication campaign. Global eradication of smallpox Rev Infect Dis 1982 4 916 930 10.1093/clinids/4.5.916 6293036 4. Arora N Chaturvedi S Dasgupta R Global lessons from India’s poliomyelitis elimination campaign Bull World Health Organ 2010 88 232 234 10.2471/BLT.09.072058 20428393 5. WHO Health in 2015: from MDGs to SDGs 2015 Geneva World Health Organization 2015 6. Durnez L Mao S Denis L Roelants P Sochantha T Coosemans M Outdoor malaria transmission in forested villages of Cambodia Malar J 2013 12 329 10.1186/1475-2875-12-329 24044424 7. National Center for Parasitology The national strategic plan for elimination of malaria in the Kingdom of Cambodia 2011–2025 2011 Phnom Penh Ministry of Health 8. Leang R Bunkea T Dysoley L Nguon C Thompson MM Bruce J Cambodia containment surveys 2009 and 2010 2010 Phnom Penh Ministry of Health 9. Guyant P Canavati SE Chea N Ly P Whittaker M Roca-Feltrer A Malaria and the mobile and migrant population in Cambodia: a population movement framework to inform strategies for malaria control and elimination Malar J 2015 14 252 10.1186/s12936-015-0773-5 26088924 10. Wangroongsarb P Satimai W Khamsiriwatchara A Thwing J Eliades JM Kaewkungwal J Respondent-driven sampling on the Thailand-Cambodia border. II. Knowledge, perception, practice and treatment-seeking behaviour of migrants in malaria endemic zones Malar J 2011 10 117 10.1186/1475-2875-10-117 21554711 11. Strategy to address migrant and mobile populations for malaria elimination in Cambodia. Ministry of Health Cambodia. https://www.researchgate.net/publication/281678133_Strategy_to_address_migrant_and_mobile_populations_for_malaria_elimination_in_Cambodia. Accessed 23 Mar 2016. 12. Containment Project. http://www.searo.who.int/thailand/areas/malaria/containment/en/. Accessed 23 Jan 2016. 13. BBC World Service Trust Malaria survey 2009—knowledge, attitudes, practices and media information about malaria 2010 Phnom Penh, London BBC World Action 14. Khuon C Richter E LeRoux-Rutledge E Qualitative impact assessment of Cambodia global fund round 9 malaria project 2012 Phonm Penh Cambodia: Research and Learning Group, BBC Media Action 15. USAID Evaluation of the malaria control in Cambodia project 2012 Washington USAID 72 16. PMI/USAID Networks project vector control assessment in Greater Mekong Subregion: Review of malaria prevention—strategies, tools, stakeholders, target group segmentation, behavioural issues, private sector development options 2012 Washington PMI/USAID 17. Canavati SE Lawpoolsri S Quintero CE Nguon C Ly P Pukrittayakamee S Village malaria worker performance key to the elimination of artemisinin-resistant malaria: a Western Cambodia health system assessment Malar J 2016 15 282 10.1186/s12936-016-1322-6 27206729 18. Canavati SE. Community knowledge, attitudes and practices (KAP) on behaviour change communication (BCC) interventions for the control, prevention, diagnosis, and treatment of malaria among mobile and malaria populations (MMPs) in Pailin province, Western Cambodia: a quantitative and qualitative study. Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, 2013. 19. Jitthai N. Migration and malaria. In: Delacollette C, Supavej S, Singhasivanon P, editors. Mekong malaria III. Towards malaria elimination in the Greater Mekong Subregion. The Southeast Asian Journal of Tropical Medicine and Public Health 2013. 44. 20. Khamsiriwatchara A Wangroongsarb P Thwing J Eliades J Satimai W Delacollette C Respondent-driven sampling on the Thailand-Cambodia border. I. Can malaria cases be contained in mobile migrant workers? Malar J 2011 10 120 10.1186/1475-2875-10-120 21554744 21. Canavati SE de Beyl CZ Ly P Shafique M Boukheng T Rang C Evaluation of intensified behaviour change communication strategies in an artemisinin resistance setting Malar J 2016 15 249 10.1186/s12936-016-1276-8 27129496 22. Pellini A Ayres D Community participation in local governance in Cambodia: learning from the village networks approach Dev Pract 2007 17 404 409 10.1080/09614520701337004 23. Sirilak S Okanurak K Wattanagoon Y Chatchaiyalerk S Tornee S Siri S Community participation of cross-border migrants for primary health care in Thailand Health Policy Plan 2013 28 658 664 10.1093/heapol/czs105 23132916 24. Tynan A Atkinson J Toaliu H Taleo G Fitzgerald L Whittaker M Community participation for malaria elimination in Tafea Province, Vanuatu: Part II. Social and cultural aspects of treatment-seeking behaviour Malar J 2011 10 204 10.1186/1475-2875-10-204 21787434 25. Atkinson J-A Fitzgerald L Toaliu H Taleo G Tynan A Whittaker M Community participation for malaria elimination in Tafea Province, Vanuatu: Part I. Maintaining motivation for prevention practices in the context of disappearing disease Malar J 2010 9 93 10.1186/1475-2875-9-93 20380748 26. Ruebush TK Zeissig R Koplan JP Klein RE Godoy HA Community participation in malaria surveillance and treatment. III. An evaluation of modifications in the Volunteer Collaborator Network of Guatemala Am J Trop Med Hyg 1994 50 85 98 8304577 27. Perry H Zulliger R How effective are community health workers? 2012 Baltimore Johns Hopkins Bloomberg School of Public Health 28. Druetz T Ridde V Kouanda S Ly A Diabaté S Haddad S Utilization of community health workers for malaria treatment: results from a three-year panel study in the districts of Kaya and Zorgho, Burkina Faso Malar J 2015 14 71 10.1186/s12936-015-0591-9 25889306 29. Druetz T Kadio K Haddad S Kouanda S Ridde V Do community health workers perceive mechanisms associated with the success of community case management of malaria? A qualitative study from Burkina Faso Soc Sci Med 2015 124 232 240 10.1016/j.socscimed.2014.11.053 25462427 30. Perry HB Zulliger R Rogers MM Community health workers in low-, middle-, and high-income countries: an overview of their history, recent evolution, and current effectiveness Annu Rev Public Health 2014 35 399 421 10.1146/annurev-publhealth-032013-182354 24387091 31. Owek C Abong’o B Oyugi H Oteku J Kaseje D Muruka C Njuguna J Motivational factors that influence retention of community health workers in a Kenyan district Public Health Res 2013 3 109 115 32. Blanas DA Ndiaye Y Nichols K Jensen A Siddiqui A Hennig N Barriers to community case management of malaria in Saraya, Senegal: training, and supply-chains Malar J 2013 12 95 10.1186/1475-2875-12-95 23497188 33. Yasuoka J Poudel K Ly P Nguon C Socheat D Jimba M Scale-up of community-based malaria control can be achieved without degrading community health workers’ service quality: the village malaria worker project in Cambodia Malar J 2012 11 4 10.1186/1475-2875-11-4 22217322 34. Kheang ST Duong S Olkkonen A Increasing access to early malaria diagnosis and prompted treatment in remote cambodian villages Am J Public Health 2011 101 e6 e8 10.2105/AJPH.2011.300228 22021279 35. Liu A Sullivan S Khan M Sachs S Singh P Community health workers in global health: scale and scalability Mt Sinai J Med 2011 78 419 435 10.1002/msj.20260 21598268 36. Malaria Consortium Workshop to consolidate lessons learned on BCC and mobile/migrant populations in the strategy to contain artemisinin resistant malaria 2011 Luang Prabang Meeting Report, Santi Resort and Spa 37. Ly P Thwing J McGinn C Top S Habib N Vinjamuri BS Nguon C An assessment of malaria knowledge, treament seeking behaviors, and preventive practices among mobile and migrant populations in western Cambodia based on a respondent driven sampling approach 2010 Phnom Penh CNM 38. Heggenhougen HK Hackethal V Vivek P The behavioural and social aspects of malaria and its control: an introduction and annotated bibliography 2003 Geneva UNDP, World Bank, TDR 39. Peeters Grietens K Gryseels C Dierickx S Bannister-Tyrrell M Trienekens S Uk S Characterizing types of human mobility to inform differential and targeted malaria elimination strategies in Northeast Cambodia Sci Rep 2015 5 16837 10.1038/srep16837 26593245 40. Yeung S Van Damme W Socheat D White NJ Mills A Access to artemisinin combination therapy for malaria in remote areas of Cambodia Malar J 2008 7 96 10.1186/1475-2875-7-96 18510724 41. Gushulak B Macpherson D Health aspects of the pre-departure phase of migration PLoS Med 2011 8 e1001035 10.1371/journal.pmed.1001035 21629679 42. Bourdier F Bunnary C Sok Penh T Malaria and population dynamics in Cambodia 2010 Phnom Penh IRD

PMC005xxxxxx/PMC5000444.txt

==== Front BMC NeurolBMC NeurolBMC Neurology1471-2377BioMed Central London 67710.1186/s12883-016-0677-1Research ArticleUrgent referral for suspected CNS cancer: which clinical features are associated with a positive predictive value of 3 % or more? Mohammad Hasan Raza 07841873244hasanmohammad@doctors.org.uk 12Boardman Jeremy jeremy.boardman@lthr.nhs.uk 1Howell Laura LHowell@uclan.ac.uk 3Mills Roger J. RogerJohn.Mills@lthr.nhs.uk 1Emsley Hedley C. A. hedley.emsley@manchester.ac.uk 121 Department of Neurology, Royal Preston Hospital, Sharoe Green Lane, Fulwood, Preston PR2 9HT UK 2 Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester, M13 9PL UK 3 College of Health and Wellbeing, University of Central Lancashire, Fylde Road, Preston, PR1 2HE UK 26 8 2016 26 8 2016 2016 16 1 1521 6 2016 17 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Urgent referral for suspected central nervous system (CNS) cancer is recommended, but little analysis of the referral criteria diagnostic performance has been conducted. New 2015 NICE guidance recommends direct brain imaging for patients with symptoms with positive predictive values (PPV) of 3 %, but further guidance is needed. Methods A 12-month retrospective evaluation of 393 patients referred under previous 2005 NICE 2-week rule criteria was conducted. Analysis was based on the three groups of symptoms forming the referral criteria, (1) CNS symptoms, (2) recent onset headaches, (3) rapidly progressive subacute focal deficit/cognitive/behavioural/personality change. Comparison was made with neuroimaging findings. Results Twelve (3.1 %) of 383 patients who attended clinic had CNS cancer suggesting the combination of clinical judgement and application of 2005 criteria matched the 2015 guideline’s PPV threshold. PPVs for the three groups of symptoms were (1) 4.1 % (95 % CIs 2.0 to 7.4 %), (2) 1.2 % (0.1 to 4.3 %) and (3) 3.7 % (0.1 to 19.0 %). Sensitivities were (1) 83.3 % (95 % CIs 51.6 to 97.9 %), (2) 16.7 % (2.1 to 48.4 %), and (3) 8.3 % (0.2 to 38.5 %); specificities were (1) 37.2 % (32.3 to 42.3 %), (2) 55.5 % (50.3 to 60.7 %) and (3) 93.0 % (89.9 to 95.4 %). Of 288 patients who underwent neuroimaging, 59 (20.5 %) had incidental findings, most commonly cerebrovascular disease. Conclusions The 2015 guidance is less prescriptive than previous criteria making clinical judgement more important. CNS symptoms had greatest sensitivity, while PPVs for CNS symptoms and rapidly progressive subacute deficit/cognitive/behavioural/personality change were closest to 3 %. Recent onset headaches had the lowest sensitivity and PPV. Electronic supplementary material The online version of this article (doi:10.1186/s12883-016-0677-1) contains supplementary material, which is available to authorized users. Keywords CNS cancerRetrospective studyTwo-week referralPositive predictive valueNICE guidanceNo fundingissue-copyright-statement© The Author(s) 2016 ==== Body Background The 1990s saw rising waiting times in the United Kingdom (UK) for patients undergoing investigation of suspected cancer, including suspected central nervous system (CNS) cancer. This prompted the Department of Health to introduce guidelines in 2000 for referral, with structured pathways and a waiting time target of 2 weeks [1, 2]. The referral guidelines for suspected cancer were revised in 2005 [3] and completely overhauled in 2015 [4] because of concerns that cancer survival in the UK is lower than in other developed countries. The latest guidelines for adults with suspected CNS cancer (Table 1), which advocate direct referral for brain imaging to be performed within 2 weeks, represent a substantial shift from the 2005 guidelines (Table 2) which comprised clinical criteria based on groups of symptoms for urgent outpatient referral (typically to neurology) to be seen within 2 weeks, or for referral to be considered.Table 1 (From 2015 guidelines [4]) Consider an urgent direct access MRI scan of the brain (or CT scan if MRI is contraindicated) (to be performed within 2 weeks) to assess for brain or central nervous system cancer in adults with progressive, sub-acute loss of central neurological function Table 2 (From 2005 guidelines [3]) Refer urgently patients with:  • symptoms related to the CNS, including:    - progressive neurological deficit    - new-onset seizures    - headaches    - mental changes    - cranial nerve palsy    - unilateral sensorineural deafness     in whom a brain tumour is suspected  • headaches of recent onset accompanied by features suggestive of raised intracranial pressure, for example:    - vomiting    - drowsiness    - posture-related headache    - pulse-synchronous tinnitus     or by other focal or non-focal neurological symptoms, for example blackout, change in personality or memory  • a new, qualitatively different, unexplained headache that becomes progressively severe  • suspected recent-onset seizures (refer to neurologist) Consider urgent referral (to an appropriate specialist) in patients with rapid progression of:  • subacute focal neurological deficit  • unexplained cognitive impairment, behavioural disturbance or slowness, or a combination of these  • personality changes confirmed by a witness and for which there is no reasonable explanation even in the absence of other symptoms and signs of a brain tumour Currently, the extent of implementation of the 2015 guidelines for suspected CNS cancer is somewhat variable, with gradual transition being expected from the 2005 to the 2015 guidelines while the implications for clinical practice, including referral pathways and impact on imaging and reporting capacity etc., are understood. The 2015 guidelines advise that adults with clinical features that are associated with a positive predictive value (PPV) of 3 % or more for CNS cancer should be referred urgently for investigation [4]. The new guidelines are much less prescriptive in their wording, particularly, in respect of which clinical features might be the most relevant. Relatively little is known about the diagnostic performance of the 2005 referral criteria, or diagnosis rate of CNS cancer among patients referred using those criteria [5]. The likely effects of the 2015 guidelines upon referral behaviour and the implications for direct access imaging requests is, to all intents and purposes, unknown. An improved understanding of the diagnostic performance of the 2005 criteria and which clinical features are relevant in determining whether there is a 3 % or greater likelihood of CNS cancer will surely be helpful. In addition, relatively little is known about the implications for patients and clinical pathways upon the identification of incidental findings when imaging is being requested directly from primary care [6]. We have undertaken a retrospective study of patients referred under the ‘2 week rule’ for suspected CNS cancer according to the 2005 guidelines over a 12 month period. We have analysed (1) the diagnostic performance of the 2005 criteria, with a clinical and radiological diagnosis of CNS cancer as the primary outcome, (2) the symptom frequencies amongst all referred patients and those with CNS cancer, and (3) incidental findings. Methods Data extraction and validation Routine clinical data were extracted from referral letters, clinic letters and imaging reports for all patients referred under the ‘2 week rule’ for suspected CNS cancer to the regional neurology service based at the Royal Preston Hospital (serving a population of approximately 1.6 million) between 1st June 2012 and 31st May 2013. Data were extracted by one junior doctor (HM, who was an undergraduate at the time of data collection), and were independently validated by a second junior doctor (JB) working in neurology. One year after data collection, all patients’ records were reviewed to determine whether any other visits/imaging had occurred. Classification of 2005 referral criteria and analysis Referral criteria (2005 criteria) were grouped as follows: group 1 – symptoms related to the CNS (all new-onset or recent-onset seizures were included in this group), group 2 – headaches of recent onset accompanied by features suggestive of raised intracranial pressure (ICP), and group 3 – rapidly progressive subacute focal deficit/cognitive/behavioural or personality change. Presenting symptoms were classified into one of these three groups. The primary outcome was the presence/absence of CNS cancer on the basis of clinical assessment and, where applicable, neuroimaging findings (CT brain/MRI brain). Sensitivity, specificity, positive and negative predictive values were calculated for each symptom group. Statistical methods Statistical analysis was performed using Stata (StataCorp. 2013. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP) and StatsDirect (StatsDirect Ltd. StatsDirect statistical software. http://www.statsdirect.com. England: StatsDirect Ltd. 2013). Presenting symptoms were reported for all referrals and by CNS cancer diagnosis using frequencies and percentages. Comparisons of presenting symptoms by CNS cancer diagnosis were performed using the Fisher’s exact test. To avoid multiple testing, comparisons were made only for the overall presenting symptom groups: symptoms related to CNS cancer, headaches of recent onset accompanied by features suggestive of raised intracranial pressure and consider urgent referral. The significance threshold was set at p ≤ 0.05. Measures of diagnostic performance, sensitivity, specificity, positive predictive value and negative predictive value were reported for each of the symptom groups based on participants who were referred and attended clinic. Diagnosis of CNS cancer was based on clinical decision and radiological findings. Please see Additional file 1: Appendix for raw data calculations. Results Between 1st June 2012 and 31st May 2013, 393 adult patients were referred under the ‘2 week rule’ for suspected CNS cancer. Ten patients did not attend their appointment or were seen at another hospital. Three hundred and eighty-three patients attended clinic, of whom 95 did not undergo neuroimaging (and did not undergo imaging by July 2014) on account of the neurologist considering there to be no clinical suspicion of CNS cancer and no other indication for scanning. Two hundred and eighty eight patients underwent neuroimaging (Fig. 1).Fig. 1 Flow chart of patients recruited in the study CNS cancer diagnoses Twelve patients were found to have CNS cancer. This constitutes 3.1 % of the total number of referred patients who attended their appointment and 4.2 % of patients who underwent imaging. Histopathological diagnoses were grade IV glioblastoma in 4 cases, lung cancer metastases in 2 cases, and anaplastic oligoastrocytoma in 1 case. No biopsies were available in the remaining 5 cases. Radiological and clinical diagnoses of these 5 cases were: cystic glioma, metastases from unknown source in parasagittal region, lung metastases in posterior corpus callosum, non-small cell carcinoma metastases in right parietal tissue and C2 vertebral body metastases without frank spinal cord compression. Diagnostic performance of 2005 referral criteria The frequency of presenting symptoms and symptom groups are shown in Table 3. Two hundred and forty-three patients were referred with group 1 symptoms, 167 with group 2 symptoms, and 27 with group 3 symptoms. For group 1 (symptoms related to the CNS), the sensitivity was 83.3 % (95 % CI 51.6 to 97.9 %), specificity 37.2 % (95 % CI 32.3 to 42.3 %), PPV 4.1 % (95 % CI 2.0 to 7.4 %) and negative predictive value (NPV) 98.6 % (95 % CI 94.9 to 99.8 %). For group 2 (headaches of recent onset accompanied by features suggestive of raised intracranial pressure), the sensitivity was 16.7 % (95 % CI 2.1 to 48.4 %), specificity 55.5 % (95 % CI 50.3 to 60.7 %), PPV 1.2 % (95 % CI 0.1 to 4.3 %) and NPV 95.4 % (95 % CI 91.7 to 97.8 %). For group 3 (rapidly progressive subacute focal deficit/cognitive/behavioural or personality change), the sensitivity was 8.3 % (95 % CI 0.2 to 38.5 %), specificity 93.0 % (95 % CI 89.9 to 95.4 %), PPV 3.7 % (95 % CI 0.1 to 19.0 %) and NPV 96.9 % (95 % CI 94.5 to 98.4 %).Table 3 The prevalence of symptoms in referrals under the 2-week rule for suspected CNS cancer Presenting symptom All referrals (n = 383) No CNS cancer (n = 371) CNS cancer (n = 12) p Symptoms related to the CNS 243 (63.4) 233 (62.8) 10 (83.3) 0.224  Progressive neurological deficit 30 (7.8) 27 (7.3) 3 (25.0)  New-onset seizures 41 (10.7) 39 (10.5) 2 (16.7)  Headaches 173 (45.2) 168 (45.3) 5 (41.7)  Mental changes 21 (5.5) 19 (5.1) 2 (16.7)  Cranial nerve palsy 19 (5.0) 18 (4.9) 1 (8.3)  Unilateral sensorineural deafness 10 (2.6) 10 (2.7) 0 (0.0) Headaches of recent onset accompanied by features suggestive of raised intracranial pressure 167 (43.6) 165 (44.5) 2 (16.7) 0.075  Vomiting 28 (7.3) 28 (7.5) 0 (0.0)  Drowsiness 23 (6.0) 23 (6.2) 0 (0.0)  Posture-related headache 68 (17.8) 67 (18.1) 1 (8.3)  Pulse-synchronous tinnitus 3 (0.8) 3 (0.8) 0 (0.0)  Other focal/non-focal neurological problems 71 (18.5) 70 (18.9) 1 (8.3)  New, qualitatively different, unexplained headache that becomes progressively severe 43 (11.2) 43 (11.6) 0 (0.0) Consider urgent referral - rapidly progressive subacute focal deficit/cognitive/behavioural or personality change 27 (7.0) 26 (7.0) 1 (8.3) 0.590  Subacute focal neurological deficit 7 (1.8) 6 (1.6) 1 (8.3)  Unexplained cognitive impairment/behavioural disturbance or slowness, or a combination of these 17 (4.4) 17 (4.6) 0 (0.0)  Personality changes 9 (2.3) 9 (2.4) 0 (0.0) p-value derived from Fisher’s Exact Test comparing presence of symptom groups between patients with and without confirmed CNS cancer Incidental findings Of 288 patients who underwent neuroimaging, 59 (20.5 %) were found to have incidental findings (Table 4). Cerebrovascular disease (11.1 %), degenerative spine disease (3.5 %) and sinus disease (3.1 %) were the most frequent incidental findings.Table 4 Summary of incidental findings on neuroimaging Incidental finding Number of patients (%) Benign cystic lesion 5 (1.7 %) Cerebrovascular disease 32 (11.1 %)   Small vessel disease only 25 (8.7 %)   Large artery disease only 5 (1.7 %)   Mixed small vessel and large artery disease 2 (0.7 %) Degenerative spine disease 10 (3.5 %)   Cervical 9 (3.1 %)   Lumbar 1 (0.3 %) CNS demyelination 3 (1.0 %) Sinus disease 9 (3.1 %) Discussion This study, to our knowledge, is the first to consider the implications of the recently revised NICE guidelines for suspected CNS cancer, and specifically which clinical features are associated with a PPV of 3 % or more by analysing the diagnostic performance of previous referral criteria [5]. Anecdotally, there can appear to be excessive ‘2 week rule’ referrals for suspected CNS cancer to neurology clinics. With the 2015 guidelines advocating direct referral for imaging, fewer patients with suspected CNS cancer might be expected to attend neurology clinics, although the identification of incidental findings will inevitably also have implications for clinical care. In the present study, ‘2 week rule’ referrals constituted approximately 3 % of the total number of new outpatient referrals to the regional neurology service (ca. 12,000). The overall CNS cancer diagnosis rate among the ‘2 week rule’ referral population was 3.1 % (i.e. 12 CNS cancer diagnoses among 383 patients who were referred by this route and who attended clinic). This finding would appear to suggest that intriguingly, through clinical judgement and the application of the 2005 referral criteria, there was a pattern of referral behaviour for suspected CNS cancer matching the PPV threshold of 3 % at which patients should be urgently referred, according to the 2015 guidelines [4]. Now that the referral criteria are much less prescriptive, referrers will, more than ever, have to employ clinical judgement when considering referral. But which clinical features would suggest a PPV of 3 % or more? Headache often tends to prompt concerns in the patient and the referrer about the possibility of CNS cancer but performs very poorly as a predictor [7]. Probably undue emphasis is placed on headache per se, and the findings in the present study support the usual view that as a single symptom it does tend to be a poor discriminator with respect to the presence/absence of CNS cancer. Nonetheless, headache accounts for 4.4 % of primary care consultations and up to 30 % of outpatient neurology referrals in the UK [8, 9]. However, the current analysis highlights focal deficits (subacute or progressive), new-onset seizures, or cognitive/behavioural/personality changes, as being more strongly predictive of CNS cancer in the appropriate clinical context. New-onset seizures in particular, whether focal or secondary generalised, can be an important early manifestation of a brain tumour. In a previous study of clinical features and the risk of primary brain tumours, in which new-onset epilepsy had an overall risk of 1.2 %, rising to 2.3 % if the patient was >60 years of age, in marked contrast to the risk with headache, which was associated with a risk of less than 1 in 1000 [10]. It should be noted that diagnostic performance of all three symptom groups in this study was poor by comparison with usual expectations for a good diagnostic test which would have both a high sensitivity and specificity (both around 90.0 %) [11]. Headaches of recent onset accompanied by features suggestive of raised ICP were actually less frequent among patients found to have CNS cancer than among the total referral population. Potentially this suggests difficulties in clinical recognition of features of raised ICP. Uncertainty among referrers over headache diagnosis has certainly been reported previously [12]. Bypassing a neurology clinical opinion en route to brain imaging may raise some issues in patient management, particularly with respect to relative lack of a detailed neurological assessment which, at least anecdotally, can be helpful for contextualising incidental findings. Impact of the NICE guidance with respect to imaging and reporting capacity is uncertain. An international report published by the Organisation for Economic Cooperation and Development (OECD) found that the UK had fewer magnetic resonance imaging (MRI) scanners than almost any other Western country including developing countries such as Turkey and Slovakia [13]. Out of 32 countries in the OECD the UK stands 26th. For computerised tomography (CT) scanning, the UK is 30th of 32 [13]. Brain scans are preferably reported by a neuroradiologist, which creates issues of hospital’s reporting capacity. Implementation of the 2015 NICE criteria also needs to take into account the frequent identification of incidental findings. A systematic review and meta-analysis reported incidental findings of 2.7 % from 19,559 participants [14]. The study suggested that at the very least clinicians should counsel patients about the chance of incidental findings prior to requesting a scan and that a mechanism for their management would need to be implemented [14]. There is considerable uncertainty surrounding the management of some incidental findings on brain imaging, including balancing risk/benefit of intervention for intracranial aneurysms [15, 16], unruptured arteriovenous malformations [17], low grade glioma [18] and arachnoid cysts [14]. There is little evidence to guide the management of incidental radiological cerebrovascular disease. This lack of certainty can create significant patient anxiety, lead to additional referrals/investigations, sometimes with significant implications for the patient [19–21]. It seems wise for pre-imaging counselling to make reference not only to the possibility of incidental findings but also uncertainty in their management. By necessity, given the study design, the calculation of PPVs and NPVs is based on the referral population. This does limit the extent to which these values are directly applicable to the total population (i.e. including an unknown number of unreferred patients with relevant symptoms). Clearly, the balance of positive and negative imaging findings among unreferred patients is also unknown. Conclusions The new 2015 guidance is less prescriptive than previous CNS cancer referral criteria making clinical judgement even more important. Symptoms related to the CNS had the greatest sensitivity, while PPVs for symptoms related to the CNS and rapidly progressive subacute deficit/cognitive/behavioural/personality change were closest to the NICE referral figure of 3 %. Headaches of recent onset had the lowest sensitivity and PPV; diagnostic performance with respect to sensitivity and specificity was poor for all three symptom groups. The frequent occurrence of incidental findings also needs to be taken into account when requesting imaging and planning services. Additional file Additional file 1: Appendix. Raw data calculations. (DOCX 31 kb) Abbreviations CNSCentral nervous system CTComputerised tomography ICPIntracranial pressure MRIMagnetic resonance imaging NPVNegative predictive value NHSNational health service OECDOrganisation for Economic Cooperation and Development PPVPositive predictive value UKUnited Kingdom Acknowledgements None. Funding This project did not receive any specific funding. Availability of data and materials The datasets analysed during the current study are not publicly available due to confidentiality. Authors’ contributions All authors contributed substantially to the conception and design, acquisition of data, analysis or interpretation of data, were involved in drafting the manuscript and revising it critically for important intellectual content, and gave final approval of the version to be published, and participated sufficiently in the work to take public responsibility for appropriate portions of the content and has agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Competing interests The authors declare that they have no competing interest. Consent for publication Not applicable. Ethics approval and consent to participate This retrospective study, based entirely on existing patient records and imaging acquired during routine clinical care, was considered to constitute audit and not to require ethical approval [22]. According to the policy activities that constitute research at the Royal Preston Hospital this work met criteria for operational improvement activities exempt from ethical review. ==== Refs References 1. Department of Health. The NHS Cancer Plan A plan for investment, a plan for reform. (cited 24th April 2016). https://www.thh.nhs.uk/documents/_Departments/Cancer/NHSCancerPlan.pdf, 2000; Available from: HMSO. 2. NHS Executive. Referral guidelines for suspected cancer. DOH 2000. (cited 24th April 2015). http://webarchive.nationalarchives.gov.uk/20130107105354/http://www.dh.gov.uk/prod_consum_dh/groups/dh_digitalassets/@dh/@en/documents/digitalasset/dh_4012253.pdf. 3. NICE. Referral guidlines for suspected cancer. NICE, 2005: p. 21. (cited 24th April 2016). http://www.rcpch.ac.uk/sites/default/files/asset_library/Research/Clinical%20Effectiveness/Endorsed%20guidelines/Cancer,%20Referral%20for%20Suspected%20(NICE)/Referral%20for%20suspected%20cancer.quick%20reference%20guide.pdf. 4. NICE. Suspected cancer: recognition and referral. NCC-C, 2015 p. 244–253. (Cited 24th April 2016). https://www.nice.org.uk/guidance/ng12. 5. Hamdan A Mitchell P The two-week wait guideline for suspected CNS tumours: a decade analysis Br J Neurosurg 2013 27 5 642 5 10.3109/02688697.2013.771725 23472626 6. Salman RA-S Whiteley WN Warlow C Screening using whole-body magnetic resonance imaging scanning: who wants an incidentaloma? J Med Screen 2007 14 1 2 4 10.1258/096914107780154530 17362563 7. Scottish Intercollegiate Guidelines Network Diagnosis and management of headache in adults 2008 Edinburgh NHS Quality Improvement Scotland 8. Latinovic R Gulliford M Ridsdale L Headache and migraine in primary care: consultation, prescription, and referral rates in a large population J Neurol Neurosurg Psychiatry 2006 77 3 385 7 10.1136/jnnp.2005.073221 16484650 9. Larner A Guidelines for primary headache disorders in primary care: an ‘intervention’ study Headache Care 2006 3 1 1 2 10.1185/174234305X75216 10. Hamilton W Kernick D Clinical features of primary brain tumours: a case-control study using electronic primary care records Br J Gen Pract 2007 57 542 695 9 17761056 11. Bekkelund S Salvesen R Is uncertain diagnosis a more frequent reason for referring migraine patients to neurologist than other headache syndromes? Eur J Neurol 2006 13 12 1370 3 10.1111/j.1468-1331.2006.01523.x 17116222 12. Cooperation OFE, Staff D, Health at a Glance 2013: OECD Indicators. 2013: OECD. (cited 24th April 2016) https://www.oecd.org/els/health-systems/Health-at-a-Glance-2013.pdf. 13. Martin D. Deadly shortage of cancer scanners that shames UK: Britain has fewer MRI machines than almost any other Western country. 2014. (cited 24th April 2016). http://www.dailymail.co.uk/news/article-2672902/Deadly-shortage-cancer-scanners-shames-UK-Britain-fewer-MRI-machines-Western-country.html. 14. Morris Z Whitely WN Longtreth WT Weber F Lee YC Tsushima Y Incidental findings on brain magnetic resonance imaging: systematic review and meta-analysis BMJ 2009 339 b3016 10.1136/bmj.b3016 19687093 15. Wiebers DO Whisant JP Huston J Meissiner I Brown RD Piepgras DG Unruptured intracranial aneurysms: natural history, clinical outcome, and risks of surgical and endovascular treatment Lancet 2003 362 9378 103 10 10.1016/S0140-6736(03)13860-3 12867109 16. Lanterna LA Tredici G Dimitrov BD Biroli F Treatment of unruptured cerebral aneurysms by embolization with Guglielmi detachable coils: case-fatality, morbidity, and effectiveness in preventing bleeding—a systematic review of the literature Neurosurgery 2004 55 4 767 78 10.1227/01.NEU.0000137653.93173.1C 15458585 17. Wedderburn CJ van Beijnum J Bhattacharya JJ Counsell CE Papanastassiou V Ritchie V Outcome after interventional or conservative management of unruptured brain arteriovenous malformations: a prospective, population-based cohort study Lancet Neurol 2008 7 3 223 30 10.1016/S1474-4422(08)70026-7 18243054 18. Cavaliere R Lopes MBS Schiff D Low-grade gliomas: an update on pathology and therapy Lancet Neurol 2005 4 11 760 70 10.1016/S1474-4422(05)70222-2 16239183 19. Piatt JH Unexpected findings on brain and spine imaging in children Pediatr Clin North Am 2004 51 2 507 27 10.1016/S0031-3955(03)00214-1 15062682 20. Howard L Wessely S Leese M Page L McCrone P Husain K Are investigations anxiolytic or anxiogenic? A randomised controlled trial of neuroimaging to provide reassurance in chronic daily headache J Neurol Neurosurg Psychiatry 2005 76 11 1558 64 10.1136/jnnp.2004.057851 16227551 21. Kernick D Williams S Should GPs have direct access to neuroradiological investigation when adults present with headache? Br J Gen Pract 2011 61 587 409 10.3399/bjgp11X578124 21801533 22. Wade D Ethics audit and research: all shades of grey BMJ 2005 330 468 71 10.1136/bmj.330.7489.468 15731146

PMC005xxxxxx/PMC5000445.txt

==== Front BMC Med EducBMC Med EducBMC Medical Education1472-6920BioMed Central London 74010.1186/s12909-016-0740-zResearch ArticleCoping strategies and the Salutogenic Model in future oral health professionals Gambetta-Tessini Karla +61 03 9341 1521karlagambetta@gmail.comkarlag@student.unimelb.edu.au 1Mariño Rodrigo 1Morgan Mike 1Anderson Vivienne 21 Melbourne Dental School, The University of Melbourne, 5th floor, 720 Swanston St, Parkville, 3010 Melbourne, VIC Australia 2 Higher Education Development Centre, University of Otago, Dunedin, New Zealand 26 8 2016 26 8 2016 2016 16 1 22428 1 2016 15 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Attention to the role of context in shaping individuals’ coping strategies is necessary. This study used the Salutogenic Model (SM) as a framework to identify the coping strategies of oral health profession students from three countries. Methods Students from Australia, New Zealand and Chile were invited to participate in this cross-sectional study, and were given a questionnaire including socio-demographics, the Perceived Stress Scale, The SOC-13 and the Brief COPE. Descriptive analysis, correlation analysis and profile analysis were computed using SPSS v 20.0. Results Eight-hundred and ninety-seven valid questionnaires were returned, achieving a 44 % response rate. The coping dimension that the participants most commonly reported using was “Active Coping” with a mean value of 5.9 ± 1.5. Chilean respondents reported higher stress levels (19.8 vs. 17.7) and a lower Sense of Coherence (55.6 vs. 58.0) compared to Australian/New Zealand participants (p < 0.001). The SOC was positively correlated with active coping (p < 0.01) and positive reframing (p < 0.01). Profile analysis showed that when the differences in responses by sex were accounted for, there was no significant effect by country on the coping strategies used (p < 0.32). Conclusion This initial investigation provides insights into the students’ coping strategies and the validity of the SM. Students reporting high SOC scores where those who demonstrated the use of active coping and positive reframing as strategies to deal with stressful situations, which indicates the accuracy of the theoretical framework of the SM in health education environments. The results also suggest that a distinctive coping strategy pattern may apply to all participants, regardless of their country and sex. Electronic supplementary material The online version of this article (doi:10.1186/s12909-016-0740-z) contains supplementary material, which is available to authorized users. Keywords AustraliaChileCoping skillsDentalNew Zealandissue-copyright-statement© The Author(s) 2016 ==== Body Background Coping strategies are conscious efforts used by individuals to solve everyday problems, demands and conflicts [1]. These strategies are highly moderated by the environment, in particular when the person has to deal with obstacles and impediments to fulfil their goals [2]. Coping strategies can be classified in many ways. Nonetheless, the Salutogenic Model (SM) is a particularly useful framework for evaluating psycho-social characteristics. This model proposes that challenging situations and conflicts are characteristically inherent to the human condition [3]. The SM focus is on how individuals effectively manage and cope with adverse situations to preserve their health [3]. The salutogenic potential of individuals is represented by the Sense of Coherence (SOC), which is “the capability to perceive that one can manage in any situation independent of whatever is happening in life” [4]. In the SM, coping strategies help in shaping and increasing the person’s salutogenic potential; in other words, they can be protective against the damaging influences on health of psychological demands [5], such as psychological distress, depression, anxiety and burnout [6]. Medical, nursing and dental education environments have been described as stressful for students. Stress-related disorders reported amongst oral health professionals may develop during the early stages of their careers [7]. The literature indicates that university years are critical in developing good coping strategies, which are likely to buffer later work-related challenges and occupational stress [8]. Unfortunately, this issue has received limited research or policy attention. Furthermore, students are rarely introduced to strategies for coping with professional pressures, constant worries and demands, as part of their university programs [9]. There is little research available on SM and coping in health education environments. Research on the sources of stress in Australian contexts indicates that governmental regulatory pressures and examinations are the main stressors for oral health professionals and students, respectively [10, 11]. Nonetheless, these reports have been largely restricted to analyses of singular stress data collected within the boundaries of the nation. The salutogenic role of coping strategies and the influence of culture has not been fully investigated. Attention to the role of the cultural context in shaping coping behaviours may facilitate a better understanding of how to foster coping behaviours across nations, and the value of health education and health promotion programs aimed at health professionals across a range of cultural contexts. As a starting point in the exploration of coping mechanisms within health professional environments, this cross-cultural study was undertaken among oral health profession students in Australian/New Zealand and Chile to identify their coping strategies and their relationships with SOC and perceived stress levels. The present study expands on previous research and examines a critical question: do students’ coping strategies differ depending on their cultural backgrounds or do broad patterns of coping exist amongst them regardless of the cultural context? Attention to individual coping strategies that improve individuals’ salutogenic potential (i.e., SOC) may inform the development of policies and education programs aimed at promoting good coping techniques amongst students. Methods Participants and procedures This study was part of a larger investigation in a multinational sample of oral health profession students [12]. Participants included all students (n = 2049) aged 18-years-old and older at two Australian universities - The University of Queensland (UQ) and The University of Sydney (US), one New Zealand university - The University of Otago (UO), and two Chilean universities - The University of Talca (UT) and The University of Valparaiso (UV). The selection of schools was partly due to convenience. However, these countries were also selected for cultural reasons. Australia and New Zealand, despite their diverse ethnic composition [13], like other Western countries, place responsibility on the individual and individual-centred programs, empowerment and personal enrichment [11]. In contrast, countries like Chile are characterised by a more hierarchical societal structure, and a focus on the wellbeing of the group rather than individuals [14]. Ethics approval was obtained from The University of Melbourne HREC (#0932899) and from all participating universities. Data collection was extended to May 2011. During a regularly scheduled class meeting, all students from first to final year were briefed on the aims of the study and invited to participate. Participants were asked to voluntarily complete the anonymous questionnaire in their own time and to return it as soon as possible. There were two-week and four-week follow-up reminders. Instruments The questionnaire included:Socio-demographic information: age, sex and high school attended (private vs. public); and country, categorised as a) Australia/New Zealand and b) Chile. The Perceived Stress Scale (PSS): to establish the degree to which situations in one’s life are appraised as stressful over a one-month period [15]. The PSS is a 10-item instrument with scores ranging from 0 to 40. High scores indicate high stress levels. The internal reliability value for this scale was 0.85 [12]. The Orientation to Life Questionnaire (SOC-13): The Sense of Coherence was measured by the SOC-13. Scores of the SOC-13 ranged from low 13 to high 91 [3]. Higher scores indicate stronger SOC, with a Cronbach’s alpha of 0.79 [12]. The Brief Coping Orientation for Problems Experienced [16]: The Brief (COPE) scale has been utilised with Australian tertiary students [17], and a valid Spanish version is available [18]. Coping strategies were identified as Adaptive and Maladaptive [19]. The Brief COPE consists of fourteen dimensions with two items each (28 items in total), including adaptive coping strategies (e.g., active coping, planning, positive reframing, acceptance, humour, religion, seeking emotional and instrumental support) and maladaptive coping techniques (e.g., self-distraction, denial, venting, substance use, behavioural disengagement, and self-blame). The response options ranged from 1 (I have not been doing this at all) to 4 (I have been doing this a lot). Adaptive coping ranges from a score of 16 to 64, and maladaptive coping ranges from 12 to 48. The internal reliability value of the scale was 0.84 [12]. Data analysis The analysis provided descriptive information on the participants’ characteristics, coping items, SOC and stress levels. To identify the association between study variables and socio-demographic characteristics data analysis included bivariate analysis (i.e., ANOVA and chi-square). To identify the relationship between SOC, stress and coping strategies, Pearson’s correlation was used. In the last part of the analysis, a special application of multivariate analysis of variance (MANOVA) called profile analysis was performed to test the main effect of country and sex upon each individual coping dimension. This profile analysis was also used to explore coping strategies’ mean values by the interaction of country with sex. Due to the exploratory nature of this study, the significance criterion was set at 0.05. Data were handled and analysed using SPSS V 20.0. Results Nine survey packages were returned incomplete. A total of eight hundred and ninety-seven participants returned valid questionnaires, achieving a 44 % response rate. Of those, 66.8 % (n = 599) were from Chile and 33.2 % (n = 298) were from Australian/New Zealand universities. Participants’ socio-demographic characteristics are described elsewhere [12]. In brief, participants’ ages ranged from 18 to 38 years old with a mean value of 22.1 ± 2.7 years. The majority were females (59.3 %; n = 531). While the majority of Chilean participants came from private schools (78.6 %), the majority of Australian/New Zealand students came from public secondary schools (60.4 %). The largest group of participants lived with their parents (41.2 %; n = 340) with significant differences by country (χ2(1) = 6.66; p = 0.006). Chileans tended to live with their parents more often than Australian/New Zealand participants (44.2 % vs. 35.2 %). Participants showed a mean stress level score of 19.1 ± 7.0 for perceived stress level with PSS scores ranging from 0 to 40. Statistically significant differences were found by sex and country. Females reported higher stress levels than men (19.9 vs. 17.8; p < 0.001) and Chilean participants reported a higher level of stress than Australian/New Zealand respondents (19.8 vs. 17.6; p < 0.001). Participants reported a mean SOC value of 56.4 ± 10.9 with scores ranging from 17 to 91. Statistically significant differences were found only by country. Chilean participants reported lower SOC than Australian/New Zealand students (55.6 vs. 58.0; p < 0.05). Coping strategies Table 1 illustrates coping strategies, SOC and perceived stress mean values by respondents’ socio-demographic characteristics. The coping dimension that the participants reported using most commonly was “Active Coping” with a mean value of 5.9 ± 1.5. The least reported strategy dimension was “Substance Use” with a mean value of 2.8 ± 1.4. Females reported using significantly less substance use (2.6 vs. 3.1; p < 0.001) and humour (4.4 vs. 4.7; p < 0.05) as coping strategies than males. In contrast, males reported significantly less use of emotional support (5.0 vs. 5.9; p < 0.001), instrumental support (4.9 vs. 5.7; p < 0.001) and religion (4.0 vs. 4.5; p < 0.001) as strategies for coping with stress. Statistically significant differences were found in all coping dimensions between Australian/New Zealand and Chilean participants. Overall, Chilean respondents reported using more adaptive (44.8 vs. 38.1; p < 0.001) and maladaptive coping techniques (25.4 vs. 21.0; p < 0.001). Religion-associated items, emotional and instrumental support, humour, substance use, behavioural disengagement, and venting showed significant statistical differences by all selected independent variables (i.e., sex, country, high school attended).Table 1 Summary of mean (s.d) for SOC, perceived stress, coping dimensions by socio-demographic characteristics SOC Perceived stress Adaptive coping dimensions Maladaptive coping dimensions Type of coping strategy Active coping Emotional support Instrumental support Positive reframing Planning Humour Acceptance Religion Self-distraction Denial Substance use Behavioural disengagement Venting Self-blame Adaptive Maladaptive Total (897) 56.4 (10.9) 19.1 (7.0) 5.9 (1.5) 5.5 (1.8) 5.4 (1.9) 5.5 (1.6) 5.8 (1.5) 4.5 (1.8) 5.7 (1.4) 4.3 (2.1) 5.6 (1.5) 2.9 (1.4) 2.8 (1.4) 3.2 (1.4) 4.7 (1.7) 4.9 (1.7) 42.7 (8.7) 24.1 (5.5) Sex n (%) Female 531(59.3) 56.1 (11.1) 19.9 (6.9)** 6.0 (1.4) 5.9 (1.7)** 5.7 (1.8)** 5.6 (1.6)* 5.9 (1.6) 4.3 (1.8)* 5.7 (1.4) 4.5 (2.2)** 5.6 (1.5) 3.0 (1.4) 2.6 (1.3)** 3.2 (1.4) 4.8 (1.6)* 5.0 (1.7) 43.7 (8.5)** 24.2 (5.2) Male 364 (40.7) 56.8 (10.7) 17.9 (6.9)** 5.9 (1.4) 5.0 (1.8)** 4.9 (1.9)** 5.3 (1.6)* 5.7 (1.5) 4.7 (1.8)* 5.6 (1.5) 4.0 (2.0)** 5.5 (1.5) 2.9 (1.3) 3.1 (1.6)** 3.2 (1.4) 4.5 (1.7)* 4.9 (1.7) 41.1 (8.8)** 23.9 (5.8) Country n (%) Australia/New Zealand 298 (33.2) 58.0 (11.3)* 17.7 (6.8)** 5.5 (1.4)** 4.7 (1.7)** 4.6 (1.7)** 5.1 (1.6)** 5.3 (1.5)** 4.0 (1.8)** 5.5 (1.5)* 3.5 (1.8)** 5.1 (1.6)** 2.5 (1.0)** 2.6 (1.3)* 2.8 (1.1)** 3.9 (1.5)** 4.3 (1.6)** 38. 1 (8.1)** 21.0 (5.0)** Chile 599 (66.8) 55.6 (10.7)* 19.8 (7.0)** 6.2 (1.3)** 5.9 (1.8)** 5.8 (1.8)** 5.7 (1.6)** 6.0 (1.5)** 4.7 (1.8)** 5.8 (1.4)* 4.7 (2.1)** 5.8 (1.4)** 3.2 (1.5)** 2.9 (1.5)* 3.4 (1.4)** 4.9 (1.7)** 5.3 (1.7)** 44.8 (8.1)** 25.4 (5.2)** Previous education n (%) Public 305 (34.3) 56.9 (11.0) 18.5 (7.1) 5.8 (1.4)* 5.1 (1.8)** 4.9 (1.9)** 5.3 (1.6) 5.6 (1.6)* 4.3 (1.9)* 5.5 (1.5)* 3.8 (2.0)** 5.4 (1.6) 2.9 (1.3) 2.6 (1.3)* 3.0 (1.2)* 4.4 (1.6)* 4.8 (1.7)* 40.2 (9.5)** 23.1 (5.6)** Private 583 (65.7) 56.0 (10.9) 19.4 (6.9) 6.1 (1.4)* 5.7 (1.8)** 5.6 (1.8)** 5.5 (1.6) 5.9 (1.5)* 4.6 (1.8)* 5.8 (1.4)* 4.6 (2.1)** 5.6 (1.4) 3.0 (1.4) 2.9 (1.5)* 3.3 (1.4)* 4.8 (1.7)* 5.1 (1.5)* 43.8 (8.3)** 24.6 (5.5)** SOC Sense of Coherence, *Significant values p < 0.05, ** Significant values p <0.001. Results may not add due to missing values Statistically significant positive correlations were found between stress levels and most maladaptive coping techniques, particularly self-blame (r = 0.42; p < 0.01). On the other hand, active coping (r = -0.1; p < 0.01) and positive reframing (r = -0.13; p < 0.01) showed a significant negative correlation with perceived stress. Interestingly, some adaptive-classified dimensions correlated positively with stress levels. These included religion (r = 0.11; p < 0.01), emotional (r = 0.15; p < 0.01), and instrumental support (r = 0.15; p < 0.01). The coping strategies that correlated positively with the SOC were active coping (r = 0.14; p < 0.01) and positive reframing (r = 0.13; p < 0.01). Instrumental support negatively correlated with the SOC (r = -0.08; p < 0.05). All maladaptive coping strategies were negative correlated with the SOC (p < 0.01). Table 2 demonstrates these findings.Table 2 Correlation matrix between sense of coherence, perceived stress and coping dimensions SOC Adaptive coping dimensions Maladaptive coping dimensions Type of coping strategy Active coping Emotional support Instrumental support Positive reframing Planning Humour Acceptance Religion Self-distraction Denial Substance use Behavioural disengagement Venting Self-blame Adaptive Maladaptive SOC 1 0.14 ** −0.06 −0.08* 0.13** 0.07 0.03 0.01 −0.02 −0.12** −0.24** −0.22** −0.26** −0.24** −0.38** 0.03 −0.42** Perceived stress −0.61** −0.1** 0.15** 0.15** −0.13** 0.004 −0.03 −0.03 0.11** 1.32** 0.25** 0.11** 0.28** 0.25** 0.42** 0.04 0.40** SOC, sense of coherence. *Significant values p < 0.05, ** Significant values p < 0.01 Profile analysis Overall, the mean values of self-reported coping dimensions differed statistically over each of the 14 coping dimensions (F(1,853) = 243.44; p < 0.001). The statistical model indicated that participants reported higher mean values for adaptive strategies (e.g., active coping and planning) than maladaptive strategies (e.g., denial, substance use, and behavioural disengagement) (See Fig. 1). Of the maladaptive strategies, self-distraction 5.6 ± 1.5, self-blame 4.9 ± 1.7 and venting 4.7 ± 1.7 had the highest mean responses.Fig. 1 Profile analysis for means of coping dimensions by country and sex interactions Profile analyses showed the independent effect of sex and country on the coping strategies reported by participants. The mean values for coping strategies were significantly different by country (F(1, 853) = 6.679; p < 0.001). The analysis also indicated an independent effect of sex (F(1, 853) = 7.331; p < 0.001). Nevertheless, when the interaction of country with sex was tested, there were no significant differences between groups (i.e., Australian/New Zealand females, Australian/New Zealand males, Chilean females, and Chilean males) indicating that the groups’ overall pattern of responses do not deviate significantly from parallelism (F(1,853) = 3.121; p = 0.10) (See Fig. 1). The mean value of responses for each coping dimension on Fig. 1 shows that the greatest gap between groups was in the use of emotional and instrumental support. However, despite differences in these two dimensions, this analysis indicated that there were similar mean values in participants’ individual responses regardless of the interaction of country with sex (F(1, 853) = 0.980; p = 0.32). Discussion The present study showed that students reported the use of adaptive coping strategies as a way of successfully coping with demands, as the most used strategy was active coping. The least reported coping strategy was substance use, a maladaptive strategy, which is consistent with reports reflecting a reduction in smoking and drinking behaviours among dental students [20–22]. However, it has been reported that alcohol consumption remains a concern amongst Australian dentists [23]. The analysis also indicated that participants endorsed different dimensions of coping strategies, relating to adaptive and maladaptive techniques. Independent of country and sex, the profile analysis demonstrated an overall difference in the response of each of the eight adaptive dimensions and six maladaptive dimensions. Specifically, the main difference was found in the participants’ report of using instrumental and emotional support (See Fig. 1). In the SM, social support is counted as an independent psychosocial construct which includes both, a) functioning support; where the person finds instrumental or concrete support provided by others, and b) less concrete, or emotional, support [24]. Social support may improve the ability of the person to obtain meaningful information, resulting in a positive influence on health (i.e., a salutogenic outcome) [3]. Surprisingly, the present results showed that support-related dimensions positively correlated with perceived stress, and in particular, instrumental support negatively correlated with SOC. According to the SM, social support should function along with other resources, such as economic or material resources, intelligence and physiological health, to promote the individual’s perception of the world as more organised and structured. Further investigations of these other resources is warranted in health professional environments [12]. In the present study, the Brief COPE did not ask participants to specify from whom they seek support. However, students’ support sources are likely to include their closest friends or relatives, as previous research has indicated that students receive little support from instructors in dental education contexts [25]. Schools may play a decisive role in developing students’ capacity to cope with conflict and stress [7]. One way of increasing all students’ access to social support would be to ensure the development of school environments where students feel able to seek support from peers, administrative staff and academics as one way of coping with stress [26]. In the bivariate analysis, Australian/New Zealand respondents reported lower mean values for all coping dimensions, either adaptive or maladaptive strategies. However, they also reported a lower stress level and higher SOC compared to Chilean participants. This finding may illustrate the significance of the SOC in moderating individuals’ stress levels [27]. The SOC scores for dental students were lower than those reported in research involving medical students, which could explain why historically, dental students have expressed higher stress levels compared to medical students [28]. In addition no gender differences were reported in the SOC mean values, which is consistent with the Salutogenic theory, indicating that SOC is a construct that is not linked with gender [29]. The major strategies that increased SOC in the present study were active coping and positive reframing. Active coping is the process of making active attempts to remove or avoid conflict or to improve its effects. Positive reframing refers to transforming a demanding circumstance into a positive situation [30]. Both coping strategies ‘fit’ the central component of the SOC - “meaningfulness” - which refers to a person’s capacity to consider demands as positive challenges, and not as problems or troubles [3]. Consistent with other studies involving undergraduate students [31, 32], females tended to report more adaptive coping than males, such as, seeking emotional support, and turning to religion. However, in this study, when we controlled for country and sex, the responses did not differ. Thus, our results suggest that there might exist a single distinctive coping strategy pattern to which all participants subscribe, regardless of their country or sex. The present findings, however, do not imply that oral health students and the general population within the countries studied show similar coping patterns, or that cultural differences are not important. University students may well be different from the broader population which they are representing, as the coping strategy patterns might be moderated by the kind of principles being promoted by higher education, such as professional skills, knowledge and discipline [33]. Studies have indicated that in courses like dentistry, which involve a large amount of time in class, laboratory, clinical work and library study, students become immersed in the school environment [13]. Therefore, as part of the undergraduates’ professional socialisation, their permanent coping strategies may align with the school/department profile. As in any study, this study is not without limitations. The most obvious ones are the relatively low response rate, the study’s use of convenience sampling, and its reliance on self-reporting and self-selection. The survey package included the PSS, the Brief COPE and SOC along with socio-demographic questions. The length of the questionnaire may have generated some response fatigue and contributed to the low response rate. In this study, the use of convenience sampling led to an over-representation of Chilean students, which limits the generalisation of the results. Questions such as why and under what conditions participants choose their coping strategies were not addressed by the present study. However, despite the limitations, this initial investigation provides insights into health professional students’ ways of coping with stress, and raises some important questions for future research. For instance, research is needed to ascertain the usefulness of the SM in health professional environments. For example, research could explore whether similar results emerge in countries other than those included in this study and investigate other constructs of the SM. The results of this study provide information which could lead to educational programs tailored to specific individual characteristics, reported coping strategies and apparent areas of need. An international review reported that only four studies demonstrated effective stress reduction in oral health education programs which included attention to relaxation techniques, interpersonal approaches to dentistry, and stress management seminars for dealing with stress [34]. However, research is also necessary to examine prospectively their association with occupational/professional stress. Future research could also explore the relationship between reported stress, SOC and coping strategies in an inter-professional sample, for example, whether students or professionals in allied health programs report similar patterns of coping. The present cross-sectional study has implications regarding the influence of the cultural context in stress, SOC and coping strategies, which apply, not only to oral health students, but also to university students at large. Longitudinal studies that follow the development of coping skills and other psychosocial constructs from tertiary education to professional life may be of interest. Conclusions Early identification of students’ coping strategies may facilitate the development of interventions that foster adaptive coping strategies to create a more salutogenic environment and reduce stress levels for health professionals during the early stages of their formation. This may facilitate academic and professional success and contribute to the prevention of stress-related consequences, such as depression, anxiety, burnout and psychological distress [34]. The present data would also suggest that efforts to increase adaptive coping strategies could be exchanged across national borders. Additional file Additional file 1: Questionnaire. (DOC 408 kb) Abbreviations COPECoping orientation for problems experienced PSSPerceived stress scale SMSalutogenic model SOCSense of coherence Acknowledgements The authors deeply thank the students who gave consent to participate in the study, and the research collaborators at Universities were the study was carried out. Funding Postgraduate student research fund. Melbourne Dental School. The University of Melbourne. Availability of data and materials For ethical considerations data cannot be shared. See research questionnaire is attached to this publication [Additional file 1]. Authors’ contributions KGT investigated the research problem, developed the protocol for the study, carried out the fieldwork, conducted the data analysis and final drafting of the manuscript. RM participated in study design, data analysis, and interpretation of results. MM and VA were involved in the interpretation of the data and helped to draft the manuscript. All the authors read and approved to the final version of the manuscript. Author’s information KGT master by research topic was health-promoting attributes in dental students. RM and VA have a vast experience in dental and tertiary education. MM is currently the Head of Melbourne Dental School, The University of Melbourne. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate The reception of a completed questionnaire constituted consent for participation. Ethics approval was obtained from the Human Research Ethics Committee of the University of Melbourne (#0932899) and all participant universities. ==== Refs References 1. Lazarus RS Folkman S Stress, Appraisal, and Coping 1984 New York Springer Publishing Company, Inc. 2. Carver CS Connor-Smith J Personality and Coping Annu Rev Psychol. 2010 61 679 704 10.1146/annurev.psych.093008.100352 19572784 3. Antonovsky A Health, Stress, and Coping. New Perspectives on Mental and Physical Well-Being., first edition. edn 1979 San Francisco Jossey-Bass Inc., Publishers 4. Lindstrom B Eriksson M Contextualizing salutogenesis and Antonovsky in public health development Health Promot Int 2006 21 3 238 244 10.1093/heapro/dal016 16717056 5. Bernabe E Kivimaki M Tsakos G Suominen-Taipale AL Nordblad A Savolainen J Uutela A Sheiham A Watt RG The relationship among sense of coherence, socio-economic status, and oral health-related behaviours among Finnish dentate adults Eur J Oral Sci 2009 117 4 413 418 10.1111/j.1600-0722.2009.00655.x 19627353 6. Alzahem AM van der Molen HT Alaujan AH Schmidt HG Zamakhshary MH Stress amongst dental students: a systematic review Eur J Dent Educ 2011 15 1 8 18 10.1111/j.1600-0579.2010.00640.x 21226800 7. Rada RE Johnson-Leong C Stress, burnout, anxiety and depression among dentists J Am Dent Assoc 2004 135 6 788 794 10.14219/jada.archive.2004.0279 15270165 8. Heiman T Examination of the salutogenic model, support resources, coping style, and stressors among Israeli university students J Psychol 2004 138 6 505 520 10.3200/JRLP.138.6.505-520 15612607 9. Alexander RE Stress-related suicide by dentists and other health care workers - Fact or folklore? J Am Dent Assoc 2001 132 6 786 794 10.14219/jada.archive.2001.0278 11433860 10. Sanders AE Lushington K Sources of stress for Australian dental students J Dent Educ 1999 63 9 688 697 10518206 11. Johns RE Jepsen DM Sources of occupational stress in NSW and ACT dentists Aust Dent J. 2015 2 182 10.1111/adj.12323 25989535 12. Gambetta-Tessini K Mariño R Morgan M Evans W Anderson V Stress and Health-Promoting Attributes in Australian, New Zealand, and Chilean Dental Students J Dent Educ 2013 77 6 801 809 23740917 13. Mariño RJ Cultural consistency in Australian dental students from two different ethnic backgrounds J Dent Educ 2004 68 11 1178 15520237 14. Early P Erez M The Transplanted Executive: Why You Need to Understand How Workers in Other Countries See the World Differently 1997 New York Oxford University Press, Inc. 15. Cohen S Kamarck T Mermelstein R A global measure of perceived stress J Health and Soc Behav 1983 24 4 385 396 10.2307/2136404 6668417 16. Carver CS You want to measure coping but your protocol's too long: Consider the brief COPE Int J Behav Med 1997 4 1 92 100 10.1207/s15327558ijbm0401_6 16250744 17. Khawaja NG A comparison of International and Domestic Tertiary Students in Australia Aust J Guid Couns 2008 18 1 30 46 10.1375/ajgc.18.1.30 18. Perczek R Carver CS Price AA Pozo-Kaderman C Coping, mood, and aspects of personality in Spanish translation and evidence of convergence with English versions J Pers Assess 2000 74 1 63 87 10.1207/S15327752JPA740105 10779933 19. Grota BL The relationship among coping strategies, perceived stress, and sense of coherence. Ph.D 2005 United States -- Minnesota Walden University 20. Underwood B Fox K A survey of alcohol and drug use among UK based dental undergraduates Br Dent J 2000 189 6 314 317 11060952 21. Underwood B Fox K Manogue M Tobacco, alcohol and drug use among dental undergraduates at one English university in 1998 and 2008 Br Dent J 2010 208 4 164 165 10.1038/sj.bdj.2010.183 22. Barber MW Fairclough A A comparison of alcohol and drug use among dental undergraduates and a group of non-medical, professional undergraduates Br Dent J 2006 201 9 581 584 10.1038/sj.bdj.4814203 17099669 23. Winwood PC Winefield AH Lushington K The role of occupational stress in the maladaptive use of alcohol by dentists: A study of South Australian general dental practitioners Aust Dent J 2003 48 2 102 109 10.1111/j.1834-7819.2003.tb00017.x 14649399 24. Zimet GD Dahlem NW Zimet SG Farley GK The multidimensional scale of perceived social support J Pers Assess 1988 52 1 30 41 10.1207/s15327752jpa5201_2 25. Muirhead V Locker D Canadian dental students' perceptions of stress and social support Eur J Dent Educ 2008 12 3 144 148 10.1111/j.1600-0579.2008.00512.x 18666895 26. Lopez N Does peer mentoring work? Dental students assess its benefits as an adaptive coping strategy J Dent Educ 2010 74 11 1197 21045224 27. Eriksson M Lindstrom B Antonovsky's sense of coherence scale and the relation with health: a systematic review J Epidemiol Community Health 2006 60 5 376 381 10.1136/jech.2005.041616 16614325 28. Biro E Balajti I Adany R Kosa K Determinants of mental well-being in medical students Soc Psychiatry Psychiatr Epidemiol 2009 45 2 253 258 10.1007/s00127-009-0062-0 19399351 29. Lindmark U Stenstrom U Gerdin EW Hugoson A The distribution of ''sense of coherence'' among Swedish adults: a quantitative cross-sectional population study Scand J Public Health 2010 38 1 1 8 10.1177/1403494809351654 19843629 30. Carver CS Scheier MF Weintraub JK Assessing coping strategies: a theoretically based approach J Pers Soc Psychol 1989 56 2 267 283 10.1037/0022-3514.56.2.267 2926629 31. Doron J Stephan Y Boiche J Le Scanff C Coping with examinations: exploring relationships between students' coping strategies, implicit theories of ability, and perceived control Br J Educ Psychol 2009 79 3 515 528 10.1348/978185409X402580 19187577 32. Dyson R Renk K Freshmen adaptation to university life: Depressive symptoms, stress, and coping J Clin Psychol 2006 62 10 1231 1244 10.1002/jclp.20295 16810671 33. Altbach P Lewis L Not to Worry: The College Mold Doesn't Hold Commonweal Commonweal Foundation. 1992 119 14 17 34. Alzahem AM Van der Molen HT Alaujan AH De Boer BJ Stress management in dental students: a systematic review Adv Med Educ Pract. 2014 5 167 176 10.2147/AMEP.S46211 24904226

PMC005xxxxxx/PMC5000446.txt

==== Front J Med Case RepJ Med Case RepJournal of Medical Case Reports1752-1947BioMed Central London 103410.1186/s13256-016-1034-0Case ReportRecovery from a possible cytomegalovirus meningoencephalitis-induced apparent brain stem death in an immunocompetent man: a case report Rahardjo Theresia Monica theresiarahardjo@gmail.com 1Maskoen Tinni Trihartini ttmaskoen@yahoo.co.id 2Redjeki Ike Sri ikesriredjeki@yahoo.co.id 21 Anesthesiology Department, Faculty of Medicine, Maranatha Christian University, Bandung, Indonesia 2 Anesthesiology & Intensive Care Department, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia 26 8 2016 26 8 2016 2016 10 1 23823 2 2016 12 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Recovery from cytomegalovirus meningoencephalitis with brain stem death in an immunocompetent patient is almost impossible. We present a remarkable recovery from a possible cytomegalovirus infection in an immunocompetent man who had severe neurological syndromes, suggesting brain stem death complicated by pneumonia and pleural effusion. Case presentation A 19-year-old Asian man presented at our hospital’s emergency department with reduced consciousness and seizures following high fever, headache, confusion, and vomitus within a week before arrival. He was intubated and sent to our intensive care unit. He had nuchal rigidity and tetraparesis with accentuated tendon reflexes. Electroencephalography findings suggested an acute structural lesion at his right temporal area or an epileptic state. A cerebral spinal fluid examination suggested viral infection. A computed tomography scan was normal at the early stage of disease. Immunoglobulin M, immunoglobulin G anti-herpes simplex virus, and immunoglobulin M anti-cytomegalovirus were negative. However, immunoglobulin G anti-cytomegalovirus was positive, which supported a diagnosis of cytomegalovirus meningoencephalitis. His clinical condition deteriorated, spontaneous respiration disappeared, cranial reflexes became negative, and brain stem death was suspected. Therapy included antivirals, corticosteroids, antibiotics, anticonvulsant, antipyretics, antifungal agents, and a vasopressor to maintain hemodynamic stability. After 1 month, he showed a vague response to painful stimuli at his supraorbital nerve and respiration started to appear the following week. After pneumonia and pleural effusion were resolved, he was weaned from the ventilator and moved from the intensive care unit on day 90. Conclusions This case highlights several important issues that should be considered. First, the diagnosis of brain stem death must be confirmed with caution even if there are negative results of brain stem death test for a long period. Second, cytomegalovirus meningoencephalitis should be considered in the differential diagnosis even for an immunocompetent adult. Third, accurate therapy and simultaneous intensive care have very important roles in the recovery process of patients with cytomegalovirus meningoencephalitis. Keywords MeningoencephalitisCytomegalovirusBrain stem deathImmunocompetentIndonesian Government Insurance (BPJS)issue-copyright-statement© The Author(s) 2016 ==== Body Background Cytomegalovirus (CMV) causes severe diseases in immunocompromised patients, leading to significant morbidity and mortality, either through viral reactivation from latent CMV infection or primary CMV infection. Encephalitis, pneumonitis, hepatitis, uveitis, retinitis, colitis, and graft rejection are some of the clinical syndromes that can be observed in such patients. However, little attention has been paid to CMV infection in immunocompetent patients [1, 2]. CMV infection in immunocompetent patients is usually asymptomatic because cell-mediated host immune responses prevent the development of overt CMV disease. However, some severe clinical manifestations of CMV infection in several conditions of immunocompetent patients have been reported. Critically ill patients, severity of illness markers, mechanical ventilation, bacterial pneumonia, sepsis, and transfusion may be associated with CMV infection risk [3]. Of interest, the seroprevalence of CMV is 20 to 30 % higher in non-white populations worldwide, suggesting that Asian people have a higher risk of CMV infection [4]. The most severe manifestation of CMV infection in immunocompetent patients is meningoencephalitis, which is characterized by seizures and coma as clinical manifestations. Ventriculoencephalitis is a CMV infection with brain stem involvement characterized by severe cranial nerves dysfunction and can lead to brain stem death (BSD) [5, 6]. Lung involvement can manifest as pneumonia or interstitial pneumonitis [7]. There is no existing data on the recovery process in immunocompetent patients with CMV meningoencephalitis with BSD. Some studies have only focused on CMV manifestation in immunocompromised patients. A few notable cases of CMV diseases manifested as kidney, gastrointestinal tract, and liver abnormalities, but no brain stem involvement was observed [8]. A case of CMV meningitis was previously reported, but was not accompanied by encephalitis, BSD or pneumonia with pleural effusion as complicating factors [9]. We present an exceptional case of an immunocompetent patient who recovered from BSD caused by CMV meningoencephalitis. Case presentation A 19-year-old Asian man presented at our hospital’s emergency department with reduced consciousness and seizures. He had a Glasgow Coma Score of 11 to 12, and was agitated and confused during the first 2 days. He experienced two to three general tonic–clonic seizures of approximately 15 to 30 seconds’ duration each within hours of each other, and he was awake between seizures. His seizures started with stiffness in his whole body and his eyes were rolled back during seizures. His Glasgow Coma Score was reduced to 8 on the third day and he was intubated and sent to our intensive care unit (ICU). He had a continuous high fever, ranging from 39 °C to 40 °C, headache, confusion, and vomitus. His fever began to decline to 38.0 °C several hours before hospital admission. He and his family had no history of epilepsy, weakness and paralysis of limbs, drug abuse, tobacco smoking, or alcoholism. A physical examination showed nuchal rigidity and tetraparesis with accentuated tendon reflexes. Cranial nerves and ophthalmoscopy examinations were normal. An immediate electroencephalography (EEG) showed periodic epileptogenic waves at his right temporal area and general bitemporal cortical dysfunction. These findings suggested an acute structural lesion at his right temporal area or an epileptic state, and a possible viral cause. Evaluation of hematology showed dynamic changes of leukocytes and C-reactive protein (CRP) level during his illness. His white blood cell count and CRP reached peak level at day 70 when ventilator-associated pneumonia and pleural effusion occurred (Table 1). Coagulation parameters and a liver function test showed normal values. A cerebral spinal fluid examination showed a white blood cell count of 16/mm3, polymorphonucleocytes (PMN) of 13/mm3, mononuclear (MN) cells of 87/mm3, glucose level of 42/dL, and an increased protein level of 216 mg/dL, which suggested a nonspecific viral infection. Gram, India ink, and Ziehl–Neelsen stains were negative. Computed tomography (CT) scans were performed twice, on 2 September 2014 (day 6) and 22 September 2014 (day 26). The first CT scan result was normal (Fig. 1 left) but the second showed a smeared bright area in ependymal cells at the lower area of the third ventricle (Fig. 1 right). Serology tests were performed against herpes simplex virus and varicella zoster virus. These tests showed negative results for immunoglobulin (Ig) M and IgG. The possibility of human immunodeficiency virus was eliminated by a CD4 count of 750 cells/mm3. Different results were found in the serology test for CMV. First, a serology test showed negative results for IgM and IgG anti-CMV. A second serology test showed a borderline positive result for IgG anti-CMV with a titer of 0.9 U/mL. The last two serology tests showed positive results for IgG anti-CMV with titers of 5.0 U/mL and 3.8 U/mL. The four-fold increase in IgG anti-CMV from 0.9 U/mL to 5.0 U/mL within 8 days is an important finding (Table 2). Serial images of his thorax and clinical pulmonary infection score assessment accompanied by blood and sputum cultures were regularly performed, and confirmed a diagnosis of pneumonia in our patient. Based on his medical history, physical examinations, laboratory results, and supporting examinations, the diagnosis of CMV meningoencephalitis was made.Table 1 Inflammatory markers Markers Day 1 Day 9 Day 39 Day 70 Day 85 White blood cells (/mm3) 15,800 9000 9500 18,900 7800 C-reactive protein (mg/L) 10 5 6 25 7 Fig. 1 CT scan showed the first result was normal (left) but the second showed a smeared bright area in ependymal cells at the lower area of the third ventricle (right) Table 2 Cytomegalovirus serology result Cytomegalovirus Day 9 Day 19 Day 27 Day 39 Immunoglobulin M – – – – Immunoglobulin G – + (0.9 U/mL) + (5.0 U/mL) + (3.8 U/mL) His clinical condition deteriorated even though therapy with cefixime, acyclovir, dexamethasone, and phenytoin was administered intravenously. His cranial reflexes started to become reduced after 1 week in our ICU. On day 19, spontaneous respiration disappeared, cranial reflexes became negative, and BSD was suspected because he had no response to all brain stem tests, including an apnea test (Table 3). A vasopressor was used to maintain his hemodynamic stability. His family insisted life support should be continued indefinitely. This condition lasted for almost 2 weeks with no improvement and brain stem tests were regularly performed with negative results.Table 3 Brain stem death test results Cranial nerves Day 21 Day 23 Day 25 Day 27 Day 30 II, III – – – – – V, VII – – – – – V, VII – – – – – III, VI, VIII – Na Na – Na IX, X – – – – – X – – – – – Apnea test – Na Na Na Na Na not applied On day 30, he provided a vague response to painful stimuli at his supraorbital nerve. On day 35, he opened his eyes. Respiration started to appear on day 37, followed by gradual movement of his fingers. His consciousness improved from day 37, and he became fully conscious on day 50. Ganciclovir replaced acyclovir based on a four-fold increase of IgG anti-CMV serology in a test result on day 27. Other therapies on days 19 to 30 included antibiotics based on culture, corticosteroids, antibiotics, antipyretics, and antifungal agents. He also had pleural effusion and a water-sealed device was installed on day 75. A higher positive end-expiratory pressure (PEEP) on the ventilator was applied to maintain oxygenation and prevent alveoli collapse. After day 80, his respiration improved. On day 85, he was weaned from the ventilator and was able to breathe without it. He started to move his arms but his legs were still paralyzed. On day 90, he was moved from our ICU to in-patient care where he stayed for 10 days until he went home. Discussion CMV is a beta herpesvirus and can cause severe neurological syndromes. This virus is found worldwide. The seroprevalence of CMV varies in different geographical areas, ranging from 30 to 100 %. It usually attacks immunosuppressed patients. CMV encephalitis in acquired immunodeficiency syndrome occurs in at least 6 % of untreated patients with advanced human immunodeficiency virus disease. CMV pneumonia occurred in 15 to 20 % of transplant recipients and patients with acquired immunodeficiency syndrome, and is associated with a mortality rate of 85 %. Most CMV infections resulted from virus reactivation rather than primary infection. CMV infection is usually asymptomatic in immunocompetent persons. Some studies have shown that CMV infection occurs in critically sick patients who are admitted to ICUs and the prevalence ranges from 0 to 35 %. It can worsen the prognosis, prolong the ICU stay, extend ventilator use, and increase nosocomial infection [1, 4, 5, 10, 11]. The diagnosis of meningoencephalitis in our patient at the beginning of his illness was based on fever, headache, a stiff neck, nausea, and vomitus as signs and symptoms of meningitis. Encephalitis was suggested by altered mental status, loss of consciousness, and cranial nerves dysfunction. The viral etiology was strengthened by supporting examinations and laboratory results [12, 13]. A tentative diagnosis of CMV meningoencephalitis was made based on serology tests and CT scan result. The first serology test in our patient on day 9 showed negative results for IgM and IgG anti-CMV. A subsequent serology test on day 19 showed a borderline positive result for IgG anti-CMV. This was followed by a positive result for IgG anti-CMV and a four-fold increase in IgG anti-CMV on day 27. The second CT scan performed on day 26 showed a smeared bright area in ependymal cells at the lower area of his third ventricle. The positive results of IgG anti-CMV and CT scan supported the diagnosis of CMV meningoencephalitis. Recovery is needed to make a definite diagnosis. CMV reactivation, but not primary infection, was suggested in our patient based on serology method with a positive result of IgG anti-CMV, a four-fold increase in IgG anti-CMV, and a negative result for IgM anti-CMV. The negative result for IgM anti-CMV may have been due to unformed IgM or IgM that was produced but did not reach a detectable level. The immunocompetent status of our patient could also have affected the level of IgM anti-CMV formed. The negative result for IgG anti-CMV until day 19 is related to the time required for IgG production, known as the infection window period. This condition can occur in some viruses and is affected by the immunological status of the patient and immunosuppressive drugs. The subacute type of CMV infection in our patient, called ventriculoencephalitis, was supported by severe cranial nerve dysfunction, leading to BSD. All his cranial reflexes disappeared on day 19. All brain stem tests, including an apnea test that was performed on day 21, showed no responses. These findings supported the suspected condition of BSD. This condition was consistent with the results of a CT scan and serology results on day 26 and day 27, respectively. A second complete BSD examination could not be performed because the patient’s family refused a second apnea test. Therefore, the diagnosis of BSD could not be made. Our patient was on a ventilator and used a vasopressor with no improvement for almost 2 weeks. However, his family refused withdrawal of life support. During his illness, he was administered antivirals, corticosteroids, antibiotics, antipyretics, and antifungal medication [14]. There are no uniform guidelines available for diagnosis of CMV infection in such critically ill, but immunocompetent, patients. An ideal diagnostic test should be able to detect active CMV infection and differentiate it from CMV disease. CMV infection is defined as isolation of virus (viral culture), or detection of CMV proteins (pp65) or nucleic acid by a polymerase chain reaction from blood or other clinical samples. CMV disease is confirmed by clinical findings suggestive of organ involvement, as well as a demonstration of the virus by viral isolation, histopathological testing, immunohistochemical analysis, or in situ hybridization from the relevant clinical sample obtained from the site of involvement. Detection of CMV by polymerase chain reaction alone is insufficient for confirming CMV disease. Conventional methods for the diagnosis of CMV infection or disease are serology, including CMV-specific antigen and antibody detection, which were used in our patient, viral isolation by viral culture, and the molecular method for detection of viral DNA from blood and other clinical specimens [15–17]. Antiviral medication was changed from acyclovir to ganciclovir on day 27 after the diagnosis of CMV meningoencephalitis was supported by a serologic result. All brain tests, except for the apnea test, were performed on the same day and showed negative results. An extraordinary event occurred in our patient on day 30, after 4 days of ganciclovir treatment. We observed a vague response to painful stimuli at his supraorbital nerve when routine brain stem tests were performed. The response became apparent and he opened his eyes on day 35. However, respiration was still absent at this time and started to appear as small respiratory efforts on day 37, followed by motor activity at his fingers. He became fully conscious on day 50. He started to breathe without the ventilator on day 85 and moved out of our ICU on day 90. Ventilator-associated pneumonia and pleural effusion act as complicating factors that worsen and prolong the recovery process. Our patient was able to breathe on his own with continuous positive airway pressure of 5 mmHg on day 66, but his respiration started to decrease within the next week, accompanied by fever. His clinical pulmonary infection score increased by more than 6. Major pleural effusion was detected on day 75 and a water-sealed device was applied on the same day. His fever began to resolve after replacement of antibiotics on day 69 and his respiration started to improve. Cultures were regularly performed every 5 days and antibiotics were used according to the result. Antifungal medication was provided because our patient had a Candida score of greater than 3 [18]. Study limitation This case report has a few limitations. First, the diagnosis of BSD could not be made because our patient’s family did not give permission for a second apnea test. However, changes in result from a first to a second BSD test are small. Therefore, even though a second BSD test could not be performed, it was almost impossible that our patient would regain brain stem function by the time of a second test after the negative results of the first BSD test [19]. Second, there is the limitation that supportive and advance examinations were not performed because of financial reasons. Serology tests for IgM and IgG anti-CMV could only be performed four times, a CT scan two times, and EEG once. Magnetic resonance imaging was not performed. Magnetic resonance imaging is superior to CT scans in evaluating central neural system infections, including meningoencephalitis, but this limitation can be overcome by a positive result in a CT scan and serology test. Conclusions In conclusion, this case report shows an unusual recovery process from CMV meningoencephalitis in an immunocompetent patient with BSD. Even though there has been advancement in our understanding of the relationship between CMV infection with brain stem involvement and immunocompetence in a patient, our case is unusual. A diagnosis of BSD must be confirmed with extreme caution, even if all BSD tests show negative results for a long time. CMV meningoencephalitis should also be considered in the differential diagnosis in immunocompetent patients whose cerebral spinal fluid results show a suspected viral infection. Furthermore, accurate therapy and simultaneous intensive care are important in a patient’s recovery process. The availability of diagnostic testing also accelerates determination of diagnosis, and this will affect treatment and prognosis. Abbreviations BSDBrain stem death CMVCytomegalovirus CRPC-reactive protein CTComputed tomography EEGElectroencephalography ICUIntensive care unit IgImmunoglobulin Acknowledgement The authors thank A. Zulfariansyah for comments during the preparation of this paper. Funding Funding comes from government insurance, BPJS (mandatory health insurance scheme), and every patient who fulfills BPJS criteria is given the insurance automatically. Availability of data and materials Data and materials are available and can be requested directly from the corresponding author to some extent without revealing patient identity. Authors’ contributions TMR analyzed and interpreted the patient data regarding the disease. TTM and ISR contributed equally in writing the manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Written informed consent was obtained from the patient for publication of this case report and any accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal. ==== Refs References 1. Jain M Duggal S Chugh TD Cytomegalovirus infection in non-immunosuppressed critically ill patients J Infect Dev Ctries 2011 5 8 571 9 10.3855/jidc.1487 21841300 2. Rafailidis PI Mourtzoukou EG Varbobitis IC Falagas ME Severe cytomegalovirus infection in apparently immunocompetent patients: a systematic review Virol J 2008 5 47 10.1186/1743-422X-5-47 18371229 3. Osawa R Singh N Cytomegalovirus infection in critically ill patients: a systematic review Crit Care 2009 13 R68 10.1186/cc7875 19442306 4. Cannon MJ Schmid DS Hyde TB Review of cytomegalovirus seroprevalence and demographic characteristics associated with infection Rev Med Virol 2010 20 4 202 13 10.1002/rmv.655 20564615 5. Silva MTT Viral encephalitis Arq Neuropsiquiatr 2013 71 9-B 703 9 10.1590/0004-282X20130155 24141509 6. Sutcliffe AJ Current issues in the diagnosis of brain stem death Indian J Critical Care Med 2004 8 3 185 9 7. Wu RG Viral pneumonia in adult J Intern Med Taiwan 2013 24 317 27 10.1001/jamainternmed.2013.1569 8. Lancini D Faddy HM Flower R Hagan C Cytomegalovirus disease in immunocompetent adult MJA 2014 201 10 578 80 25390262 9. Farazi A Anaami M Arkan N Severe cytomegalovirus meningitis in an immunocompetent patient: a case report Eur J Appl Sci 2015 7 6 274 6 10. Eddleston M Peacock S Juniper M Warrell DA Severe cytomegalovirus infection in immunocompetent patients Clin Infect Dis 1997 24 52 6 10.1093/clinids/24.1.52 8994755 11. Limaye AP Boeckh M Cytomegalovirus (CMV) in critically-ill patients: pathogen or bystander? Rev Med Virol 2010 20 6 372 9 10.1002/rmv.664 20931610 12. Kumar R Aseptic meningitis: diagnosis and management Indian J Pediatr 2005 72 1 57 63 10.1007/BF02760582 15684450 13. Solomon T Hart IJ Beeching NJ Viral encephalitis: a clinician’s guide Pract Neurol 2007 7 288 305 10.1136/jnnp.2007.129098 17885268 14. Biron KK Antiviral drugs for cytomegalovirus diseases Antivir Res 2006 71 154 6 10.1016/j.antiviral.2006.05.002 16765457 15. Ljungman P Griffiths P Paya C Definitions of cytomegalovirus infection and disease in transplant recipients Clin Infect Dis 2002 34 1094 7 10.1086/339329 11914998 16. Ross SA Novak Z Pati S Boppana SB Diagnosis of cytomegalovirus infections Infect Disord Drug Targets 2011 11 5 466 74 10.2174/187152611797636703 21827433 17. Boeckh M Complications, diagnosis, management, and prevention of CMV infections: current and future Am Soc Hematol 2011 1 305 9 10.1182/asheducation-2011.1.305 18. Leroy G Lambiotte F Thevenin D Lemaire C Parmentier E Devos P Evaluation of “candida score” in critically ill patients: a prospective, multicenter, observational, cohort study Ann Intensive Care 2011 1 50 10.1186/2110-5820-1-50 22128895 19. Lusbader D O’Hara D Wijdicks EF MacLean L Tajik W Ying A Second brain death examination may negatively affect organ donation Neurology 2011 76 2 119 24 10.1212/WNL.0b013e3182061b0c 21172836

PMC005xxxxxx/PMC5000447.txt

==== Front BMC NeurolBMC NeurolBMC Neurology1471-2377BioMed Central London 66810.1186/s12883-016-0668-2Research ArticleAssociation between serum non-high-density lipoprotein cholesterol and cognitive impairment in patients with acute ischemic stroke Lu Da sikongwuji@hotmail.com 1Li Pan doc_panpan@163.com 1Zhou Yuying +86-13032286578qiying789@sina.cn 1Xu Xiaolin hhyyxxl@163.com 2Zhang Huihong zhhhtj@yeah.net 1Liu Liping liviallp@live.com 1Tian Zhiyan tianzhiyan75@163.com 11 Department of Neurology, Sixteenth wards, Tianjin Huanhu Hospital, Tianjin, 300060 China 2 Department of Neurology, Second wards, Tianjin Huanhu Hospital, Tianjin, 300060 China 26 8 2016 26 8 2016 2016 16 1 15426 4 2016 10 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Non-high density lipoprotein cholesterol (HDL-C) could be a good predictor of vascular disease outcomes. To evaluate the association between serum non-HDL-C and cognitive impairment in patients with acute ischemic stroke. Methods A total of 725 hospitalized patients with acute ischemic stroke were enrolled. They received conventional treatment. Cognitive function was assessed on the 3rd day after admission using mini-mental state examination (MMSE), Montreal Cognitive Assessment (MoCA), Activity of Daily Living Scale (ADL), and Neuropsychiatric Inventory (NPI, and Hamilton depression rating scale 21-item (HAMD-21). Lipid profile and biochemical markers were measured, and non-HDL-C was calculated. Results Compared with patients with normal non-HDL-C, those with high non-HDL-C showed lower MMSE (23.1 ± 4.9 vs. 26.0 ± 4.6, P < 0.001) and MoCA (20.4 ± 6.4 vs. 22.2 ± 5.3 P = 0.01) scores, higher NPI (6.2 ± 1.2 vs. 3.3 ± 1.5, P < 0.001) and HADM-21 (6.0 ± 2.2 vs. 4.5 ± 1.9, P < 0.001) scores, and higher homocysteine (16.0 ± 3.8 vs. 14.3 ± 2.0 mmol/L, P = 0.044), fasting blood glucose (6.4 ± 2.7 vs. 6.1 ± 2.1 mmol/L, P = 0.041), and HbA1c (6.80 ± 1.32 % vs. 6.52 ± 1.17 %, P = 0.013) levels. MMSE (r = -0.526, P < 0.001), MoCA (r = −0.216, P < 0.001), and NPI (r = 0.403, P < 0.001) scores were correlated with non-HDL-C levels. High non-HDL-C levels were an independent risk factor for cognitive disorders after acute ischemic stroke (P = 0.034, odds ratio = 3.115, 95 % confidence interval: 1.088–8.917). Conclusions High serum non-HDL-C levels, age, education, homocysteine levels, and HAMD score were independent risk factors of cognitive impairment in patients with acute ischemic stroke. The risk of cognitive disorders after acute ischemic stroke increased with increasing non-HDL-C levels. This parameter is easy to assess in the clinical setting. Keywords DyslipidemiaNon-high-density lipoprotein cholesterolIschemic strokeCognitive disordersthe Scientific and Technical planing Project of Tianjin13ZCZDSY01600Lu Da Scientific and Technical Key Project of Tianjin Health Bureau13KG121Lu Da issue-copyright-statement© The Author(s) 2016 ==== Body Background Acute ischemic stroke is an episode of neurological dysfunction caused by cerebral ischemia persisting for >24 h or until death [1], and represent 80–87 % of all strokes [2, 3]. In high income countries, the incidence of stroke is 217 per 100,000 person-years and the prevalence is 715 per 100,000 people, compared with low income countries where the incidence is 281 per 100,000 person-years and the prevalence is 393 per 100,000 people. Likely risk factors include history of transient ischemic attacks, cardiovascular diseases (hypertension, myocardial infarction), smoking, metabolic syndrome, heavy alcohol consumption, type 2 diabetes mellitus, high cholesterol levels, carotid artery stenosis, genetic factors, and biochemical factors [2, 3]. Vascular cognitive impairment (VCI) is one of the most common non-somatic manifestations in patients with acute ischemic stroke [4]. Dyslipidemia is not only an independent and maybe the most important risk factor for ischemic stroke, which tends to cause hidden, progressive, and somatic organic damage, but also affects the cognitive function of patients with ischemic stroke through accelerating systemic atherosclerosis, and it is believed to be a risk factor inducing cognitive disorders, even dementia [5]. Previous guidelines for blood lipid treatment preferred low-density lipoprotein cholesterol (LDL-C) as the primary target of lipid-lowering therapy [6]. However, some recent studies and epidemiological investigations indicated that serum non-high-density lipoprotein cholesterol (HDL-C) levels were superior to LDL-C in terms of predicting the risk of cardiovascular diseases. The National lipid association recommendations for patient-centered management of dyslipidemia issued by the American National Lipid Association (NLA) in 2015 proposes that non-HDL-C is preferable to LDL-C as the primary target of interventions [7], since non-HDL-C includes all lipoprotein particles other than the HDLs, therefore including the triglyceride-rich lipoproteins [chylomicrons, very-low-density lipoproteins (VLDL), and their remnants], which are now known to participate in atherosclerosis [7]. Nevertheless, the exact relationship between non-HDL-C and cognitive impairment after stroke is still poorly understood. Therefore, this study aimed to investigate the association between serum non-HDL-C levels and cognitive function after stroke, as well as the value of non-HDL-C levels in assessing the risk of cognitive disorders after acute ischemic stroke. Methods Study design This was a retrospective case-control study of patients with acute ischemic stroke hospitalized and registered at the Department of Neurology of the Tianjin Huanhu Hospital between January 2010 and December 2015. The study was approved by the ethical committee of the Tianjin Huanhu Hospital. The need for individual consent was waived by the committee because of the retrospective nature of the study. Patients Inclusion criteria were: 1) newly diagnosed with ischemic stroke according to the China cerebral vascular disease guidelines [8] based on computed tomography (CT) and/or magnetic resonance imaging (MRI); 2) onset time ≤7 days; and 3) aged >18 years old. Exclusion criteria were: 1) disturbance of consciousness, severe aphasia, or hemiplegia, and unable to complete neuropsychological testing; 2) Alzheimer’s disease (AD), depression, dementia with Lewy bodies (DLB), frontotemporal dementia (FTD), or dementia caused by other diseases such as malignant tumors, intracranial infection, neurodegenerative diseases, craniocerebral trauma, etc.; 3) heart, lung, liver, kidney, or endocrine system diseases, or connective tissue diseases, blood disease, or malnutrition; 4) history of mental diseases or behavior disorders; 5) history of ischemic stroke with cognitive disorders based on the medical files or inquiry to the family at admission; or 6) history of nootropics or antipsychotic drugs within 4 weeks. Data collection Patients’ gender, age, height, body mass index (BMI), level of education, family history of dementia, presence of vascular risk factors such as hypertension, diabetes, hyperlipidemia, heart diseases (atrial fibrillation, myocardial infarction, angina pectoris, asystole, etc.), history of stroke and/or transient ischemic attack (TIA), smoking history, and drinking history were recorded in details at admission. Grouping The patients were divided into three subgroups according to the Oxfordshire Community Stroke Project (OCSP) classification [9]: 1) total/partial anterior circulation infarction (TACI/PACI) group; 2) posterior circulation infarction (POCI) group; and 3) lacunar circulation infarction (LACI) group. TACI manifests as a triad, i.e. manifestations of complete middle cerebral artery syndrome: 1) cerebral and high nervous disorders (disturbance of consciousness, aphasia, acalculia, spatial disorientation, etc.); 2) homonymous hemianopia or conjugate eye deviation; and 3) motor and/or sensory disturbance at three contralateral parts (face, upper limbs, and lower limbs). PACI manifests as two out of three manifestations. POCI manifests as various degrees of vertebro-basilar artery syndromes: 1) ipsilateral cerebral palsy and contralateral sensory disorders; 2) bilateral sensory and motor disorders; 3) collaborative movement disorders of eyes and cerebellar dysfunction, which are unequal brain-stem and cerebellar infarctions caused by obstruction of vertebro-basilar artery and branches. LACI manifests as lacunar syndrome. Biochemistry Overnight fasting blood samples were routinely drawn. Fasting blood glucose, total cholesterol (TC), triglycerides (TG), HDL-C, and LDL-C were measured using an ADVIA-2400 automatic biochemical analyzer (Siemens, Erlangen, Germany) and the triglyceride test kit (GPO-PAP, Shanghai Huachen, Shanghai, China). A BNP II protein analyzer (Siemens, Erlangen, Germany) was used to test serum high-sensitivity CRP (hs-CRP) (C-reactive protein kit, Siemens Healthcare Diagnostics Products GmbH, Erlangen, Germany), glycated hemoglobin (HbA1c) (HBIC HbA1c kit, Siemens Healthcare Diagnostics Products GmbH, Erlangen, Germany), and homocysteine (Hcy) (Hcy kit, Siemens Healthcare Diagnostics Products GmbH, Erlangen, Germany). Non-HDL-C was calculated by subtracting HDL-C levels from TC. Non-HDL-C levels were classified into two grades according to the criteria recommended by the Patient-centered management of dyslipidemia developed by the NLA in 2015 [7]: normal group (non-HDL-C <3.4 mmol/l) and high group (non-HDL-C ≥3.4 mmol/l). The high group can be further divided into higher than normal (3.4 mmol/l ≤ non-HDL-C <4.2 mmol/l), critical high (4.2 mmol/l ≤ non-HDL-C <5.0 mmol/l), and very high (non-HDL-C ≥5.0 mmol/l). Neurological assessment After admission, patients were routinely given anti-platelet, anticoagulation, expansion, and other conventional treatments for stroke [3]. On the 3rd day after admission, their neuropsychological scales were routinely assessed by trained and skilled neurologists. Cognitive function was screened using the mini-mental state examination (MMSE) [10] and the Montreal Cognitive Assessment (MoCA) [11] scales. The total score of MMSE is 30 points, of which <17 points, <20 points, and <24 points in illiterate patients, patients with education level of primary school, and patients with education level of secondary school or above, respectively, are considered as cognitive disorders. The total score of MoCA is 30 points, where a score <26 points is considered as cognitive disorders, using a score +1 to correct for education level for patients with ≤12 years of education. MoCA presents a higher sensitivity in screening mild cognitive disorders, while MMSE is more effective and convenient for dementia patients with multiple-domain impairment. In this study, results of the above two scales were comprehensively considered since they were only used as quantitative indices of cognitive level variation with the change of non-HDL-C. Neuropsychological behavior was assessed using the neuropsychiatric inventory (NPI) [12] to determine the frequency and severity of behavioral disorders as well as distress. The NPI included 12 items and a total score of 144 points, where a higher score refers to more severe psychological and behavioral disorders. The activities of daily living (ADL) were assessed using the ADL scale [13], which includes 20 items: 11 items for basic ADL (BADL) and 9 items of instrumental ADL (IADL), for a total score of 80 points, where a higher score refers to a more severe impairment. The emotional state was assessed using the Hamilton Rating Scale 21-item HAMD-21 [14], where a score ≥7, ≥17, and ≥24 points refers to mild, moderate, and severe depression, respectively. Statistical analysis Statistical analysis was performed using SPSS 19.0 (IBM, Armonk, NY, USA). Normally-distributed continuous data are presented as mean ± standard deviation and were analyzed using the independent-samples t-test or ANOVA with the LSD post hoc test, as appropriate. Categorical data are expressed as frequency and were analyzed using the chi-square test. Correlations were assessed using the Pearson correlation test. Logistic regression (stepwise) was performed to determine the factors independently associated with higher cognitive impairment. Two-sided P-values <0.05 were considered statistically significant. Results Characteristics of the patients A total of 725 patients with acute cerebral infarction were hospitalized at the Department of Neurology of the Tianjin Huanhu Hospital between October 2010 and March 2015. They were divided into two groups according to the non-HDL-C levels: the normal group included 253 patients (192 men and 61 women, aged 54–85 years, mean age of 63.1 ± 11.9 years) and the high group included 472 patients (336 men and 136 women, aged 52–81 years, mean age of 62.2 ± 10.8 years). Furthermore, each group was further divided into three subgroups according to the OCSP classification: TACI/PACI, POCI, and LACI. Gender, age, years of education, as well as hypertension, diabetes, coronary atherosclerotic heart disease, smoking history, drinking history, family history of dementia, and stroke history were similar between the two groups (P > 0.05) (Table 1), but BMI in the normal non-HDL-C group was significantly lower than in the high non-HDL-C group (P = 0.009) (Table 1). TC, TG, HDL-C, LDL-C, HCY, fasting blood glucose, HbA1c, and other indicators were statistically different between the two groups (P < 0.05) (Table 1), except for hsCRP (P > 0.05). There was no significant difference in OCSP subtypes between the two groups (P > 0.05).Table 1 Socio-demographic and clinical characteristics of the patients Variables Normal non-HDL-C (n = 253) High non-HDL-C (n = 472) P Gender, n (%)  M 192 (75.9) 336 (71.2) 0.175  F 61 (24.1) 136 (28.8) Age (years) 63.1 ± 11.9 62.2 ± 10.8 0.289 BMI (kg/m2) 24.6 ± 3.4 25.3 ± 3.3 0.009 Years of education (years) 9.2 ± 4.3 9.1 ± 3.9 0.788 Hypertension, n (%) 167 (66.0) 317 (67.2) 0.753 Diabetes, n (%) 58 (22.9) 101 (21.4) 0.636 Coronary atherosclerotic heart disease, n (%) 43 (17.0) 88 (18.6) 0.583 Smoking history, n (%) 90 (35.6) 168 (35.6) 0.996 Drinking history, n (%) 67 (26.5) 122 (25.9) 0.853 Family history of dementia, n (%) 10 (4.0) 19 (4.0) 0.962 Stroke history, n (%) 94 (37.2) 151 (32.0) 0.161 Non-HDL-C (mmol/l) 2.77 ± 0.46 4.40 ± 0.86 <0.001 TC (mmol/l) 3.86 ± 0.52 5.54 ± 0.88 <0.001 TG (mmol/l) 1.27 ± 0.56 1.95 ± 0.31 <0.001 HDL-C (mmol/l) 1.08 ± 0.26 1.13 ± 0.25 0.027 LDL-C (mmol/l) 2.16 ± 0.46 3.39 ± 0.80 <0.001 HCY (mmol/l) 14.28 ± 2.01 16.02 ± 3.80 0.044 hsCRP (mg/l) 4.35 ± 0.78 4.47 ± 1.97 0.895 Fasting glucose (mmol/l) 6.05 ± 2.06 6.44 ± 2.66 0.041 HbA1c (%) 6.52 ± 1.17 6.80 ± 1.32 0.013 TACI/PACI, n (%) 167 (66.0) 309 (65.5) 0.264 POCI, n (%) 67 (26.5) 111 (23.5) LACI, n (%) 19 (7.5) 52 (11.0) BMI body mass index, non-HDL-C non-high-density lipoprotein cholesterol, TC total cholesterol, TG triglycerides, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol, HCY homocysteine, hsCRP high-sensitivity C-reactive protein, HbA1c glycated hemoglobin, TACI total anterior circulation infarction, PACI partial anterior circulation infarction, POCI posterior circulation infarction, LACI lacunar circulation infarction Impact of non-HDL-C levels on cognitive impairment The MMSE and MOCA scores in the high non-HDL-C group were significantly lower than in the normal non-HDL-C group (MMSE: P < 0.001; MoCA: P = 0.01). Assessments of neuropsychological behavior and emotion showed that the NPI and HADM-21 scores in the high non-HDL-C group were higher than in the normal non-HDL-C group (P < 0.001). Meanwhile, the ADL scale scores were similar between the two groups (P > 0.05) (Table 2).Table 2 Comparison of neuropsychological scale between the two groups Normal non-HDL-C (n = 253) High non-HDL-C (n = 472) P MMSE 26.0 ± 4.6 23.1 ± 4.9 <0.001 MoCA 22.2 ± 5.3 20.4 ± 6.4 0.010 NPI 3.3 ± 1.5 6.2 ± 1.2 <0.001 HADM-21 4.5 ± 1.9 6.0 ± 2.2 <0.001 ADL 25.7 ± 8.0 28.2 ± 4.1 0.230 MMSE mini-mental state examination, MoCA Montreal Cognitive Assessment, NPI Neuropsychiatric Inventory, ADL Activity of Daily Living Scale, HADM-21 Hamilton depression rating scale 21-item Association of non-HDL-C levels and neurological scores The high non-HDL-C group was further divided into the higher than normal non-HDL-C (208 cases), critical high non-HDL-C (183 cases), and very high non-HDL-C (81 cases). The NIHSS was significantly higher in patients with critical high non-HDL-C levels compared with patients with higher than normal levels (P < 0.05)(Table 3).Table 3 Comparison of the non-HDL-C differences according to neurological scores Higher than normal non-HDL-C levels (208 cases) Critical high non-HDL-C levels (183 cases) Very high non-HDL-C levels (81 cases) P NIHSS 4.0 ± 1.3 3.6 ± 1.1a 4.8 ± 1.8 0.043 NPI 3.9 ± 1.2 4.1 ± 1.2 4.9 ± 1.5ab 0.021 BI 84.1 ± 14.6 84.8 ± 14.4 82.9 ± 16.1 0.217 MMSE 24.9 ± 4.6 24.6 ± 5.1 22.6 ± 6.0ab <0.001 MoCA 20.5 ± 5.0 20.6 ± 5.9 18.3 ± 4.3ab 0.002 ADL 26.3 ± 8.2 26.5 ± 8.4 29.2 ± 10.3 0.450 HAMD 4.8 ± 1.3 4.7 ± 1.0 4.2 ± 2.7 0.634 NIHSS NIH stroke score, MMSE mini-mental state examination, MoCA Montreal Cognitive Assessment, NPI, Neuropsychiatric Inventory, ADL Activity of Daily Living Scalem, HADM-21 Hamilton depression rating scale 21-item aANOVA and LSD post hoc test: P < 0.05 vs. the higher than normal non-HDL-C group bANOVA and LSD post hoc test: P < 0.05 vs. the critical high non-HDL-C group Correlations of non-HDL-C level with various indices among patients with high non-HDL-C levels Pearson correlation analyses revealed that MMSE (weak correlation, r = -0.237, P < 0.001) and MoCA (weak correlation, r = −0.194, P < 0.001) scores were negatively correlated with non-HDL-C level in patients with acute ischemic stroke. In order to correct the impacts of gender, age, education level, disease history, and other confounding factors, we further performed partial correlation analyses, which showed that MMSE (moderate correlation, r = −0.526, P < 0.001) and MoCA (weak correlation, r = −0.216, P < 0.001) scores were negatively correlated with non-HDL-C levels, while NPI scores (weak correlation, r = 0.301, P < 0.001) were positively correlated with non-HDL-C levels (Table 4).Table 4 Correlation of non-HDL-C levels with neurological scores Items Pearson correlation analysis Partial correlation analysis r P r P MMSE −0.237 <0.001 −0.526 <0.001 NPI 0.059 0.2 0.301 <0.001 MoCA −0.194 <0.001 −0.216 <0.001 HAMD-21 0.028 0.494 0.046 0.316 ADL 0.036 0.388 0.047 0.311 The partial correlation analysis is corrected for the impact of gender, age, education level, and disease history MMSE mini-mental state examination, MoCA Montreal Cognitive Assessment, NPI Neuropsychiatric Inventory, ADL Activity of Daily Living Scale, HADM-21 Hamilton depression rating scale 21-item Effects of stroke site on cognitive function Assessment of cognitive function showed that MMSE and MoCA scores were significantly different among different subtypes of cerebral infarction in the two groups (P < 0.05), of which the score was the lowest in the TACI/PACI group, followed by the POCI and LACI groups. In addition, among different cerebral infarction subtypes, the MMSE and MoCA scores were significantly lower in the high level group compared with the normal level group (P < 0.001) (Table 5).Table 5 Comparison of MMSE and MoCA scores of patients with different cerebral infarctions between the two groups Normal level (n = 253) High level (n = 472) P MMSE  TACI/PACI 28.49 ± 1.19 21.94 ± 5.13 <0.001  POCI 29.01 ± 0.83 22.47 ± 4.22 <0.001  LACI 29.50 ± 0.51 23.98 ± 4.04 <0.001   P <0.001 0.019 MoCA  TACI/PACI 25.10 ± 2.97 17.29 ± 6.50 <0.001  POCI 26.05 ± 2.68 17.95 ± 5.68 <0.001  LACI 27.35 ± 1.93 19.62 ± 5.72 <0.001   P 0.003 0.045 MMSE mini-mental state examination, MoCA Montreal Cognitive Assessment, TACI/PACI total/partial anterior circulation infarction, POCI posterior circulation infarction, LACI lacunar circulation infarction Risk analysis of non-HDL-C levels to cognitive impairment after ischemic stroke Univariable analyses revealed that non-HDL-C levels, education level, age, history of diabetes, history of stroke, family history of dementia, HAMD score, and HCY level (P < 0.05) were associated with cognitive disorders after acute ischemic stroke (Table 6). These factors were included in the multivariable analysis and the results showed that high non-HDL-C levels, history of stroke, low education level, age, HAMD score, and HCY levels were independently associated with cognitive disorders after ischemic stroke (all P < 0.05).Table 6 Univariable and multivariable analyses of factors associated with cognitive disorders after acute ischemic stroke Univariable Multivariable Variables P OR 95 % CI P OR 95 % CI Gender, male 0.239 0.729 0.431–1.234 Age 0.001 1.043 1.018–1.068 0.001 1.039 1.016–1.064 BMI 0.623 0.982 0.913–1.056 Years of education <0.001 0.817 0.772–0.866 <0.001 0.808 0.757–0.861 Hypertension 0.324 1.207 0.831–1.755 Diabetes <0.001 1.276 1.175–1.385 0.341 1.400 0.700–2.797 Coronary heart disease 0.388 1.380 0.664–2.870 History of smoking 0.367 1.226 0.788–1.907 History of drinking 0.524 1.221 0.661–2.254 Family history of dementia 0.001 1.219 1.082–1.374 0.055 0.242 0.057–1.031 History of stroke 0.021 1.742 1.087–2.791 0.025 1.723 1.071–2.771 High TC 0.629 0.791 0.306–2.044 High TG 0.674 1.078 0.760–1.529 Low HDL-C 0.088 0.650 0.396–1.066 High LDL-C 0.900 1.025 0.694–1.514 High Non-HDL-C 0.034 3.115 1.088–8.917 <0.001 3.115 1.088–8.917 Normal level 0.170 1.691 0.799–3.579 0.088 1.691 0.799–3.579 Higher than normal 0.046 2.710 1.017–7.221 0.052 2.710 1.017–7.221 Critical high level 0.026 5.877 1.231–28.065 0.040 5.877 1.231–28.065 Very high level 0.013 7.006 1.502–32.675 0.932 7.006 1.502–32.675 High Hcy <0.001 1.060 1.032–1.088 <0.001 1.057 1.031–1.084 hsCRP 0.515 0.990 0.960–1.021 Fasting hyperglycemia [n (%)] 0.285 1.084 0.935–1.256 High HbA1c 0.960 1.002 0.939–1.068 NPI 0.218 1.039 0.978–1.104 HAMD-21 0.001 1.224 1.089–1.375 0.001 1.284 1.177–1.401 ADL 0.141 1.012 0.996–1.029 BMI body mass index, Non-HDL-C non-high-density lipoprotein cholesterol, TC total cholesterol, TG triglycerides, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol, HCY homocysteine, hsCRP serum high-sensitivity C-reactive protein, HbA1c glycated hemoglobin, MMSE mini-mental state examination, MoCA Montreal Cognitive Assessment, NPI Neuropsychiatric Inventory, ADL Activity of Daily Living Scale, HADM-21 Hamilton depression rating scale 21-item Discussion Non-HDL-C could be a good predictor of vascular disease outcomes. Therefore, this study aimed to evaluate the association between serum non-HDL-C and cognitive impairment in patients with acute ischemic stroke. Results showed that compared with normal non-HDL-C, patients with high non-HDL-C showed lower MMSE and MoCA scores, higher NPI and HADM-21 scores, and higher HCY, fasting blood glucose, and HbA1c levels. MMSE, MoCA, and NPI scores were correlated with non-HDL-C levels. High non-HDL-C levels were an independent risk factor of cognitive disorders after acute ischemic stroke. Non-HDL-C was initially used to predict the risk of cardiovascular diseases and is a strong predictor for all-cause mortality and cardiovascular disease mortality, and is significantly superior to LDL-C levels [15]. The Bypass Angioplasty Revascularization Investigation (BARI) study assessed the efficacy of secondary prevention in 1514 patients with multiple coronary diseases, and their 5-year follow-up revealed that non-HDL-C levels were an independent predictor for non-fetal myocardial infarction, while LDL-C levels failed to have significant predictive effect on the primary endpoint or mortality [16]. In another clinical longitudinal study with a follow-up >19 years in 2406 men and 2058 women, the risk of coronary disease in men with non-HDL-C levels >220 mg/dl was 2.14 times that of men with non-HDL-C levels <160 mg/dl, while that in people with LDL-C levels >190 mg/dl was 1.77 times that of people with LDL-C levels <130 mg/dl [15]. Recent studies proposed that serum non-HDL-C levels were closely associated with cerebral vascular diseases. Indeed, Wu et al. [17, 18] conducted a follow-up study of 95,916 18-98 year-old patients without stroke or myocardial infarction in Tangshan (Hebei, China) and found that serum non-HDL-C levels were an independent risk factor of ischemic stroke, and that high serum non-HDL-C levels were associated with an increase of >50 % of the risk of ischemic stroke in the healthy population, which was better than the association between LDL-C and the same risk. In their study, 13.0 % of the patients had asymptomatic intracranial arterial stenosis (ICAS) [17, 18]. In addition, they found that the elevation extent of serum non-HDL-C levels was positively correlated with ICAS incidence, and was an independent risk factor for it (OR = 1.15) [19]. Patients with mild cognitive impairment (MCI) caused by intracranial stenosis are prone to deteriorate and progress to dementia, and its mechanism might be because atherosclerosis cause vascular distortion and enwinding, but also might induce mechanical occlusion of intracranial vessels. In addition, an important atherosclerotic stenosis might indicate systemic atherosclerosis and extensive microvascular diseases, damage of microcirculation, increased resistance of small vessels and decreased vascular reactivity, ultimately leading to cerebral hypoperfusion. The cumulative effect of these interdependent hemodynamic disorders might play a key role in accelerating the onset and progression of cognitive disorders [20]. Some studies also found that serum non-HDL-C levels were significantly increased in patients with MCI compared with people with normal cognitive function, and the cognitive score was negatively correlated with the non-HDL-C levels (r = −0.761) [21]. This cross-sectional analysis first discovered that the non-HDL-C levels in 65.1 % of the patients with acute ischemic stroke was significantly higher than the normal value, and that it was positively correlated with the prevalence and damage extent of cognitive impairment after acute ischemic stroke. Thus, serum non-HDL-C level might have high value in predicting the disease since it was an independent risk factor of vascular cognitive impairment. In this study, various neurological scores were assessed in patients with different levels of serum non-HDL-C, and patients with serum non-HDL-C levels higher than the normal value tended to present significant cognitive impairment and were accompanied by apparent mental behavior and emotion disorders, significantly affecting their ability and quality of life. Multivariable regression analyses found that the risk of cognitive disorders after acute ischemic stroke was increased significantly when non-HDL-C levels were higher than normal. Therefore, serum non-HDL-C levels were an independent risk factor of cognitive disorders after cerebral stroke. A recent study showed that high LDL-C levels and low HDL-C levels were associated with β-amyloid-associated cognitive impairment, suggesting that cholesterol levels play an important role in cognitive function [22]. Additional studies are necessary to assess their precise role in neurodegenerative diseases and cognitive impairment. Damage from non-HDL-C to cognitive impairment after stroke could be associated with its strong association with the development of atherosclerosis. First, non-HDL-C particles include all potentially atherogenic lipoproteins [23–25]. Secondly, a high concentration of TG and VLDL-C in non-HDL-C reflects an increase of the liver’s potential to generate lipoproteins causing atherosclerosis, leading to decreased interaction of these lipoproteins with liver receptors and reduced clearance. Therefore, these lipoproteins tend to be retained in blood circulation for a longer time, thereby promoting atherosclerosis. Finally, some lipoprotein remnants containing abundant TG may enter the arterial walls, leading to occurrence and development of atherosclerosis [7, 26]. Therefore, compared with LDL-C, serum non-HDL-C plays a higher effect in inducing atherosclerosis and LDL-C alone tend to neglect the promoting effect of other lipoproteins on ischemic stroke. This study also showed that cognitive function scores were associated with the type of cerebral stroke in patients with high serum non-HDL-C levels and cerebral infarction. The score was the lowest in patients with CACI/PACI and the highest in patients with LACI, indicating an association with injury to specific brain regions. CACI/PACI mainly involve the middle cerebral artery territory; a large lesion in the dominant hemisphere or bilateral hemispheric lesions can obviously involve the temporal lobe, insula, corpus callosum, hippocampus, and other parts that are closely associated with cognitive and memory functions, whereas the LACI normally has a smaller effect on the cognitive function unless the above specific locations are involved [27]. Cross-sectional analyses revealed that elevation of serum non-HDL-C levels were accompanied by elevated blood glucose and serum HCY levels. Previous studies found that patients with type 2 diabetes often suffered from dyslipidemia, especially patients with uncontrolled blood glucose. Abnormal lipid metabolism is mainly associated with diabetic vascular diseases, where specific lipid modulation or low-fat diet is likely to prevent or delay the progression of diabetic vascular diseases, suggesting that lipid metabolism disorders and diabetes have common pathophysiology for cognitive disorders after cerebral stroke [28]. In addition, patients with diabetes often also suffer from impaired renal function, and it has been shown that patients with decreased flomerular filtration rate also had greater levels of cognitive impairment [29]. Nevertheless, since the relationships of all these factors are complex, additional studies are necessary to assess comprehensively all these factors together. In this study, regression analyses showed that the risk of cognitive disorders in patients with high serum HCY level was 1.057 times that of patients with a low level. which might be associated with high HCY-induced neurotoxicity [30]. These results agree with a recent study that showed that patients with vascular cognitive impairment have high HCY levels [31]. Accordingly, decreasing HCY levels seems to be associated with better cognitive outcomes in patients with Alzheimer’s disease [32], suggesting that lowering HCY levels after an ischemic stroke could improve the outcomes, but additional studies are necessary to address this issue. In addition, a low education level, age, high HAMD score, history of cerebral stroke, and family history of dementia were independent risk factors of cognitive disorders after ischemic stroke. These results are consistent with a previous study that showed that lower education, history of diabetes, high HAMD scores, high hsCRP levels, and high HbA1c levels were associated with cognitive impairment after acute ischemic stroke [33]. However, these results were all obtained in relatively small studies and need to be confirmed in larger trials. This study is not without limitations. This was a single-center retrospective cohort study with a small sample size and limited follow-up duration. Only a limited number of variables could be assessed because of the retrospective nature of the study. Additional studies are necessary to confirm these findings. Conclusions In conclusion, high serum non-HDL-C levels might significantly increase the risk of cognitive disorders after acute cerebral stroke. As an inexpensive and easily measured biomarker, non-HDL-C screening could be undertaken for primary prevention of cognitive disorders after acute cerebral stroke in Chinese adults, but also provide a new direction for investigating treatment for cognitive disorders after acute cerebral stroke. Abbreviations ADLActivity of Daily Living Scale BMIBody Mass Index HADM-21Hamilton Depression Rating Scale 21-Item HbA1cGlycated Hemoglobin HCYHomocysteine HDL-CHigh-Density Lipoprotein Cholesterol LACILacunar Circulation Infarction LDL-CLow-Density Lipoprotein Cholesterol MMSEMini-Mental State Examination MoCAMontreal Cognitive Assessment non-HDL-CNon-High-Density Lipoprotein Cholesterol NPINeuropsychiatric Inventory PACIPartial Anterior Circulation Infarction POCIPosterior Circulation Infarction S-CRPSerum High-Sensitivity C-Reactive Protein TACITotal Anterior Circulation Infarction TCTotal Cholesterol TGTriglycerides The authors acknowledge the invaluable participation of the patients. Funding This study was supported by the Scientific and Technical planing Project of Tianjin (13ZCZDSY01600) and Scientific and Technical Key Project of Tianjin Health Bureau (13KG121). Availability of data and materials The datasets analysed during the current study will not be publicly available to protect patient confidentiality. Authors’ contributions DL and PL carried out the studies, participated in collecting data, and drafted the manuscript. YYZ and XLX performed the statistical analysis and participated in its design. HHZ, LPL and ZYT helped to draft the manuscript. All authors read and approved the final manuscript. Competing interests All authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate This study was conducted according to the Helsinki II Declaration and approved by the ethics committee at the Tianjin Huanhu Hospital. This study was written informed consent was obtained from every participant. ==== Refs References 1. Sacco RL Kasner SE Broderick JP Caplan LR Connors JJ Culebras A An updated definition of stroke for the 21st century: a statement for healthcare professionals from the American Heart Association/American Stroke Association Stroke 2013 44 2064 89 10.1161/STR.0b013e318296aeca 23652265 2. Yew KS Cheng E Acute stroke diagnosis Am Fam Physician 2009 80 33 40 19621844 3. Donnan GA Fisher M Macleod M Davis SM Stroke Lancet 2008 371 1612 23 10.1016/S0140-6736(08)60694-7 18468545 4. Cho SJ Yu KH Oh MS Jung S Lee JH Koh IS Post-stroke memory impairment among patients with vascular mild cognitive impairment BMC Neurol 2014 14 244 10.1186/s12883-014-0244-6 25927318 5. Zou Y Zhu Q Deng Y Duan J Pan L Tu Q Vascular risk factors and mild cognitive impairment in the elderly population in Southwest China Am J Alzheimers Dis Other Demen 2014 29 242 7 10.1177/1533317513517042 24375574 6. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III) Jama 2001 285 2486 97 10.1001/jama.285.19.2486 11368702 7. Jacobson TA Ito MK Maki KC Orringer CE Bays HE Jones PH National lipid association recommendations for patient-centered management of dyslipidemia: part 1--full report J Clin Lipidol 2015 9 129 69 10.1016/j.jacl.2015.02.003 25911072 8. Oremus M Does the evidence say a 4-point change in ADAS-cog score is clinically significant? Alzheimers Dement 2014 10 416 7 10.1016/j.jalz.2013.12.017 24630567 9. Bamford J Sandercock P Dennis M Burn J Warlow C Classification and natural history of clinically identifiable subtypes of cerebral infarction Lancet 1991 337 1521 6 10.1016/0140-6736(91)93206-O 1675378 10. Molloy DW Standish TI A guide to the standardized Mini-Mental State Examination Int Psychogeriatr 1997 9 Suppl 1 87 94 10.1017/S1041610297004754 9447431 11. Hu JB Zhou WH Hu SH Huang ML Wei N Qi HL Cross-cultural difference and validation of the Chinese version of Montreal Cognitive Assessment in older adults residing in Eastern China: preliminary findings Arch Gerontol Geriatr 2013 56 38 43 10.1016/j.archger.2012.05.008 22698678 12. Wang T Xiao S Li X Wang H Liu Y Su N Reliability and validity of the Chinese version of the neuropsychiatric inventory in mainland China Int J Geriatr Psychiatry 2012 27 539 44 10.1002/gps.2757 21769938 13. Eto F Tanaka M Chishima M Igarashi M Mizoguchi T Wada H Comprehensive activities of daily living (ADL) index for the elderly Nihon Ronen Igakkai Zasshi 1992 29 841 8 10.3143/geriatrics.29.841 1491480 14. Faries D Herrera J Rayamajhi J DeBrota D Demitrack M Potter WZ The responsiveness of the Hamilton Depression Rating Scale J Psychiatr Res 2000 34 3 10 10.1016/S0022-3956(99)00037-0 10696827 15. Cui Y Blumenthal RS Flaws JA Whiteman MK Langenberg P Bachorik PS Non-high-density lipoprotein cholesterol level as a predictor of cardiovascular disease mortality Arch Intern Med 2001 161 1413 9 10.1001/archinte.161.11.1413 11386890 16. Bittner V Hardison R Kelsey SF Weiner BH Jacobs AK Sopko G Non-high-density lipoprotein cholesterol levels predict five-year outcome in the Bypass Angioplasty Revascularization Investigation (BARI) Circulation 2002 106 2537 42 10.1161/01.CIR.0000038496.57570.06 12427648 17. Wu J Chen S Liu L Gao X Zhou Y Wang C Non-high-density lipoprotein cholesterol vs low-density lipoprotein cholesterol as a risk factor for ischemic stroke: a result from the Kailuan study Neurol Res 2013 35 505 11 10.1179/1743132813Y.0000000206 23594748 18. Wu J Chen S Zhou Y Wang C Wang A Zhang Q Non-high-density lipoprotein cholesterol on the risks of stroke: a result from the Kailuan study PLoS One 2013 8 e74634 10.1371/journal.pone.0074634 24058611 19. Wu J Zhang Q Yang H Gao X Zhou Y Wang A Association between non-high-density-lipoprotein-cholesterol levels and the prevalence of asymptomatic intracranial arterial stenosis PLoS One 2013 8 e65229 10.1371/journal.pone.0065229 23734240 20. Zhu J Wang Y Li J Deng J Zhou H Intracranial artery stenosis and progression from mild cognitive impairment to Alzheimer disease Neurology 2014 82 842 9 10.1212/WNL.0000000000000185 24489130 21. Niu MJ Yin FZ Liu LX Fang Y Xuan XM Wu GF Non-high-density lipoprotein cholesterol and other risk factors of mild cognitive impairment among Chinese type 2 diabetic patients J Diabetes Complications 2013 27 443 6 10.1016/j.jdiacomp.2013.06.001 23845902 22. Reed B Villeneuve S Mack W DeCarli C Chui HC Jagust W Associations between serum cholesterol levels and cerebral amyloidosis JAMA Neurol 2014 71 195 200 10.1001/jamaneurol.2013.5390 24378418 23. Berger JS McGinn AP Howard BV Kuller L Manson JE Otvos J Lipid and lipoprotein biomarkers and the risk of ischemic stroke in postmenopausal women Stroke 2012 43 958 66 10.1161/STROKEAHA.111.641324 22308251 24. Canoui-Poitrine F Luc G Bard JM Ferrieres J Yarnell J Arveiler D Relative contribution of lipids and apolipoproteins to incident coronary heart disease and ischemic stroke: the PRIME Study Cerebrovasc Dis 2010 30 252 9 10.1159/000319067 20664258 25. Erqou S Kaptoge S Perry PL Di Angelantonio E Thompson A White IR Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality Jama 2009 302 412 23 10.1001/jama.2009.1063 19622820 26. Jacobson TA Ito MK Maki KC Orringer CE Bays HE Jones PH National Lipid Association recommendations for patient-centered management of dyslipidemia: part 1 - executive summary J Clin Lipidol 2014 8 473 88 10.1016/j.jacl.2014.07.007 25234560 27. Sarangi S San Pedro EC Mountz JM Anterior choroidal artery infarction presenting as a progressive cognitive deficit Clin Nucl Med 2000 25 187 90 10.1097/00003072-200003000-00006 10698414 28. DeBoer MD Obesity, systemic inflammation, and increased risk for cardiovascular disease and diabetes among adolescents: a need for screening tools to target interventions Nutrition 2013 29 379 86 10.1016/j.nut.2012.07.003 23022122 29. Kurella Tamura M Xie D Yaffe K Cohen DL Teal V Kasner SE Vascular risk factors and cognitive impairment in chronic kidney disease: the Chronic Renal Insufficiency Cohort (CRIC) study Clin J Am Soc Nephrol 2011 6 248 56 10.2215/CJN.02660310 20930087 30. Ma H Yan F Li Z Deng M Qu Q Investigation on plasma homocysteine level and cognition in population at high risk for stroke in Xi’an Zhonghua Liu Xing Bing Xue Za Zhi 2014 35 769 72 25301241 31. Jiang B Chen Y Yao G Yao C Zhao H Jia X Effects of differences in serum total homocysteine, folate, and vitamin B12 on cognitive impairment in stroke patients BMC Neurol 2014 14 217 10.1186/s12883-014-0217-9 25433800 32. Cacciapuoti F Lowering homocysteine levels with folic acid and B-vitamins do not reduce early atherosclerosis, but could interfere with cognitive decline and Alzheimer’s disease J Thromb Thrombolysis 2013 36 258 62 10.1007/s11239-012-0856-x 23224755 33. Wang Y Li P Zhang M Zhang H-h Liu S Zhou Y-y Cross-sectional analysis of cognitive impairment and relative factors after acute ischemic stroke Chi J Contemp Neurol Neurosurg 2013 13 279 85

PMC005xxxxxx/PMC5000448.txt

==== Front Biomed Eng OnlineBiomed Eng OnlineBioMedical Engineering OnLine1475-925XBioMed Central London 20910.1186/s12938-016-0209-7ResearchEquivalence between solar irradiance and solar simulators in aging tests of sunglasses Masili Mauro masili@usp.br http://orcid.org/0000-0002-5292-6687Ventura Liliane lilianeventura@usp.br Electrical Engineering Department, Engineering School of São Carlos, University of São Paulo, Av. Trabalhador Sãocarlense 400, São Carlos, SP 13566-590 Brazil 26 8 2016 26 8 2016 2016 15 1 8624 8 2015 14 7 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background This work is part of a broader research that focuses on ocular health. Three outlines are the basis of the pyramid that comprehend the research as a whole: authors’ previous work, which has provided the public to self-check their own sunglasses regarding the ultraviolet protection compatible to their category; Brazilian national survey in order to improve nationalization of sunglasses standards; and studies conducted on revisiting requirements of worldwide sunglasses standards, in which this work is inserted. It is still controversial on the literature the ultraviolet (UV) radiation effects on the ocular media, but the World Health Organization has established safe limits on the exposure of eyes to UV radiation based on the studies reported in literature. Sunglasses play an important role in providing safety, and their lenses should provide adequate UV filters. Regarding UV protection for ocular media, the resistance-to-irradiance test for sunglasses under many national standards requires irradiating lenses for 50 uninterrupted hours with a 450 W solar simulator. This artificial aging test may provide a corresponding evaluation of exposure to the sun. Methods Calculating the direct and diffuse solar irradiance at a vertical surface and the corresponding radiant exposure for the entire year, we compare the latter with the 50-h radiant exposure of a 450 W xenon arc lamp from a solar simulator required by national standards. Results Our calculations indicate that this stress test is ineffective in its present form. Conclusions We provide evidence of the need to re-evaluate the parameters of the tests to establish appropriate safe limits for UV irradiance. Significance This work is potentially significant for scientists and legislators in the field of sunglasses standards to improve the requirements of sunglasses quality and safety. Keywords Solar resistance testing for sunglassesSunglasses aging testSunglasses standardsUltraviolet A and B protection for sunglassesUV ocular protectionhttp://dx.doi.org/10.13039/501100001807Fundação de Amparo à Pesquisa do Estado de São Paulo (BR)2014/16938-02013/08038-7Masili Mauro Ventura Liliane issue-copyright-statement© The Author(s) 2016 ==== Body Background Ocular health is a serious concern worldwide, but particularly in tropical countries where UV indexes are extremely high in summer and still very high in the winter compared to countries that are farther apart from the tropics. In most countries in the southern hemisphere, and specifically in Brazil, a continental sized tropical country, sunglasses standards are not quite appropriate for the ultraviolet conditions, as well as for the people’s behavior profile about UV protection, and public should be more aware about ultraviolet protection as a whole. The authors of this work have been conducting researches in order to bridge these gaps. Three outlines are the basis of the pyramid that comprehends the research as a whole: (1) authors’ previous work [1], which has provided the public to self-check their own sunglasses regarding the ultraviolet protection compatible to their category. This has allowed population to self-test their own sunglasses for free and in an easy way to find out in 30 s whether their sunglasses are adequate or inappropriate to be worn by the Brazilian standard limits; (2) Brazilian national survey [2] has improved information such as how many daily hours Brazilians wear sunglasses, in which period of the day and season, in which are the environments most popularly worn, what kind of sunglasses are mostly purchased, and so forth. This information provides parameters for nationalization of sunglasses standards, such as how long sunglasses should last in such community; (3) studies conducted on revisiting requirements of worldwide sunglasses standards, such as the UV protection range extended to 400 nm in 2013 in Brazil as part of our researches. This work is a continuation of these researches. According to the International Commission on Non-Ionizing Radiation Protection (ICNIRP), ultraviolet (UV) radiation constitutes the portion of the electromagnetic spectrum spanning from 100 to 400 nm [3]. The International Commission on Illumination (CIE—Commission Internationale de l’Eclairage) [4, 5] subsequently split the UV spectrum into three important spectral bands with respect to the effects of UV radiation on biological systems. These bands are widely known as UV-C (100–280 nm), UV-B (280–315 nm), and UV-A (315–380 nm or 400 nm, depending on the standard). Investigations on UV radiation incident upon the eyes have noted pathological modifications to the cornea and to the internal structures of the eye [6, 7]. The possible effects include edema, pterygium, lens opacity (cataract), and retina damage [8, 9]. It is well known that sunglasses should provide filters for protection against UV radiation. National and regional standards [10–14] for the sunglasses industry require that sunglasses provide levels of protection linked to the luminous transmittance, i.e., on the category of lenses. The Australian/New Zealand standard [11], the first one for general use sunglasses, set a UV wavelength range from 280 to 400 nm. The 2013 version of Brazilian standard extended the upper limit of the UV-A range from 380 to 400 nm, becoming more consistent with the Australian/New Zealand standard [11], as Brazil, Australia, and New Zealand share greater risk of a higher UV dose [15]. However, the current Brazilian standard, NBR ISO 12312-1:2015 [10], which replaced the NBR 15111:2013, has returned the UV-A upper limit to 380 nm. In a recent work [2], the authors emphasized the importance of considering the UV-A limit of 400 nm for UV-protecting filters based on the radiant exposure (in J m−2) on the eye’s surface. It is also important to understand the lifetime of the optical properties of sunglasses. The exposure of sunglasses to the sun may deteriorate their UV protection and alter the category under which they are classified (lenses may become lighter when overexposed to the sun) over time. Moreover, Chou, Dain, and, Cheng [16] recently showed that transmittance is not the only factor effected by UV radiation exposure. They showed that exposure of lenses to high levels of UV radiation diminishes the impact resistance of lenses. Thus, it should be a requirement that both the transmittance and the impact tests should be performed subsequently to the aging test of the lenses. Aging tests of sunglasses lenses One of the requirements of the Brazilian standard NBR ISO 12312-1:2015 and other standards is to perform a test in which sunglasses are irradiated by a solar simulator for a specified period. The UV protection provided by the sunglasses prior to exposure to UV radiation is then compared to their UV protection capabilities following exposure in the solar simulator. This test provides a measure of any change in the UV protection as a result of exposure of the sunglasses to the sun. The procedure is referred to as the resistance-to-solar-irradiation test or the simply artificial aging test. It consists of irradiating the lenses of sunglasses with an ozone-free xenon arc lamp (450 W) using a cutoff filter (clear white crown glass B 270; 4 mm thick) between the lamp and the lenses under test, which are placed 300 mm away from the lamp. The lenses are subjected to artificial solar irradiation by the solar simulator for 50 ± 0.1 h [10, 12]. Following the exposure to radiation, spectrophotometry is performed to determine the sunglasses’ transmittance of radiation in the UV-A and UV-B ranges; then, these measurements are compared with the values found before the resistance-to-irradiation test. Thus, the extent to which the UV filters are deteriorated during the aging process can be estimated. The aim of this test is to establish a correlation between the periods of exposure to natural and simulated sunlight required by many standards for sunglasses. Furthermore, typical periods of exposure are considered based on data obtained from a national survey [2] in Brazil. This correlation varies among different countries and even among different locations within the same country, such as in Brazil. Attempts to match artificial aging tests with environmental counterparts have been problematic in many areas [17–20]. To the best of our knowledge, this is a pioneering effort to achieve such equivalence, at least for sunglasses standards. Therefore, the objective of whole project is to establish the equivalence between solar exposure during use of the sunglasses and the solar simulator parameters used to carry out the resistance-to-solar irradiation test. Hence, the goal is to provide additional information regarding the parameters used in the UV testing of solar lenses to contribute to the further optimization of the Brazilian standard. Other national standards may also benefit from the present work, especially those nations that are located at similar absolute latitudes. Methods The task of determining the global irradiance on the earth’s surface involves calculations of direct and diffuse solar irradiance. The geometry taken into account in this work refers to an individual who is standing up and wearing sunglasses. In this case, the direct beam irradiance is incident upon a vertical (plane) surface, with a well-known dependence on the incident angle with the normal direction to the surface, described by Lambert’s cosine law. The diffuse irradiance refers to the radiation scattered from the clouds and the atmosphere as well as from the ground and its surroundings. The starting point in this calculation is to determine the spectral irradiance (in W m−2 nm−1), called E(λ, r, t), at site level, where λ is the wavelength, r collectively represents all spatial coordinates, i.e., geographical position and altitude, and t is time of day. For this calculation, we use the SMARTS2 spectral model, proposed by Gueymard [21], which is free to download. The accuracy of this model has been assessed in the literature [21, 22]. The model uses the extraterrestrial solar spectrum (based on satellite data) and through radiative transfer models of the atmosphere, the spectral irradiance is determined at ground level. The model is capable of calculating the direct and the diffuse radiation components for any plane orientation. Specifically, for a vertical plane orientation, the cosine of the incident angle with the horizontal has to be included (oblique incidence). Alternatively, the sine of the zenith angle of solar rays may be used. The sum of the two components is the global irradiance. Thus, the global spectral irradiance can be expressed in the following form: 1 E(λ,r,t)=Eb(λ,r,t)sin[θz(r,t)]+Ed(λ,r,t), where indexes b and d represent direct and diffuse, respectively, and θz(r, t) is the zenith angle of the solar beams. Integration over the appropriate wavelength range yields the solar irradiance E(r, t) (in W∙m−2) in terms of the spectral irradiance E(λ, r, t) [Eq. (1)], as follows: 2 E(r,t)=∫λiλfE(λ,r,t)dλ. Therefore, the radiant exposure (in J·m−2) on a surface over a given period is calculated by integrating the irradiance E(r,t) over time, i.e., 3 H(r)=∫titfE(r,t)dt. To establish the equivalence between solar radiant exposure (3) and the radiant exposure emitted by a simulator lamp, we calculate the radiant exposure from the lamp using the above-mentioned equations, using the lamp’s spectral irradiance provided by the manufacturer instead of the solar spectral irradiance. Hence, the solar radiant exposure can be compared with the lamp’s radiant exposure. The fundamental idea is to compute the lamp’s radiant exposure [Eq. (3)] incident on the lenses within the simulator and the sun’s radiant exposure, both in the region 280–492 nm, and compare them with each other. When calculating the lamp’s radiant exposure, one must consider the distance of the samples from the bulb. On the other hand, for the sun’s radiant exposure, the calculation is more difficult due to many variables to be considered. Evidently, the solar irradiance changes during the day and throughout the year at each location, and it is primarily latitude dependent. Thus, we formulate three specific situations for solar irradiance to model, which are quite representative of the conditions that sunglasses are submitted to, as they are worn by an individual throughout a year. In each situation, a different amount of daily hours for wearing sunglasses is considered. Therefore, a daily average of the solar radiant exposure is obtained for each scenario and compared with the lamp’s radiant exposure. The ratio between both expresses a lamp–sun equivalence in “days of use” for each scenario. In other words, for instance, 1 h of exposure in the solar simulator is equivalent to different amount of exposure hours under different solar irradiance conditions, such as the scenarios previously described. A variety of assumptions, pertaining to both the solar simulator setup and the outdoor environment, can be taken into account to determine this equivalence relation. Those assumptions will be presented and discussed in the following section. In all of that, the oblique incidence (cosine corrected) will be accounted for. Results and discussion Calculations were carried out for the 27 Brazilian state capitals, which span all over the country, and for the specific town of São Paulo, São Paulo State, Brazil, which is a representative example for our purposes. São Paulo is the largest city in Brazil, with nearly 12 million inhabitants, located at latitude −23°32′51″ S, longitude −46°38′10″ W at an average altitude of 760 m. For the northern hemisphere readers, this latitude is approximately equivalent to the latitude of Havana, Cuba. The latitudes of the 27 Brazilian state capitals range from +2°49′11″ N down to −30°01′59″ S. Although our main calculations are performed for Brazilian cities, in fact, other southern hemisphere countries, which share same latitudes, would benefit from our results once those calculations are latitude driven. We also present results for 110 Northern Hemisphere national capitals once many of them are at higher latitudes than nations in Southern Hemisphere. The SMARTS2 model herein used [21], aside information about site location, date, and time, requires input parameters to characterize the atmosphere, such as ozone column, aerosols, turbidity, and others. In addition, it is also possible to input parameters which characterize the local environment, such as soil reflectance. Regarding the atmosphere, for Brazilian cities calculations we have selected the SMARTS2 built-in Tropical standard atmosphere, which has average typical gas concentrations and no pollutants. Likewise, for northern national capitals, we used the SMARTS2 built-in Mid Latitude standard atmosphere. In both cases, the local environment was mainly assumed as urban area with concrete soil. A clear sky assumption has also been made. Spectral irradiance data corresponding to a distance of 500 mm from the lamp’s bulb (XBO450–OFR xenon arc lamp) were provided by OSRAM over the range 280–2400 nm. Although values of the solar spectral irradiance are available up to a wavelength of 4000 nm, all calculations were carried out over the range 280–492 nm, both for sun and lamp spectral irradiances [see integration limits in Eq. (2)]. The reason for this choice is that this is the range of the fading action spectra, which is primarily in the UV region and, to a lesser extent, in the blue region, corresponding to short wavelength radiation. Moreover, it plays an important role for the ocular health. The standardized solar irradiance for air mass 1 (AM1) is 1000 W m−2, which is expressed as 1 sun. This is the approximate solar irradiance at the Earth’s surface on a horizontal plane at sea level on a clear day, with sun at zenith. Table 1 presents the calculated irradiance of the XBO450–OFR xenon arc lamp from OSRAM for several distances from the lamp bulb for orthogonal irradiation. The sun-equivalent irradiance was calculated as the ratio between the lamp’s irradiance and the standardized solar irradiance (1000 W m−2) at each desired distance. The lamp’s spectral irradiance was derived for the desired distances using the inverse square law for point-like light sources. Because the xenon arc length in this lamp is 2.7 mm, according to the manufacturer, a distance from the arc equivalent to five times its largest dimension provides a deviation of 1 % from the inverse square law [23]. In Table 1, the minimum distance from the tested lenses to the lamp used for calculations is 50 mm. For this particular distance, or shorter distances, the extension of the lenses to be irradiated should be taken into account, once the light incidence at the edges of the lenses is not orthogonal. Nevertheless, the standard requires transmittance measurements in a circle of 5 mm radius, centered on the optical axis of the lenses. This requirement ensures a nearly normal incidence in the region of interest, with a maximum deviation of order of 6 % from normal incidence. Therefore, for every distance longer than 50 mm from the bulb, the inverse square law remains valid.Table 1 Lamp (XBO450–OFR) irradiance as a function of the distance d (mm) from the lamp bulb and its equivalence in number of suns for AM1 XBO450—OFR OSRAM irradiance (W m−2 ) Distance from the bulb d (mm) Equivalent number of suns for AM1 467 300 0.5 672 250 0.7 1000 205 1.0 1051 200 1.1 1868 150 1.9 4202 100 4.2 16,808 50 16.8 1 sun (AM1) = 1000 W m−2 It is worth noting that when sunglasses are irradiated 300 mm away from the lamp’s bulb, as required by the standards NBR ISO 12312-1:2015 [10, 11], EN ISO 12312-1:2015 [12], and ISO 12312-1 [13], the equivalent sun irradiance is 0.5, as listed in the first row of Table 1. In other words, the irradiance is similar to that observed when sunglasses are orthogonally exposed to 50 % of the solar irradiance at AM1. The remaining data in Table 1 present the equivalent lamp–sun irradiance values for decreasing distances between the sunglasses and the lamp. Because the inverse square law was used to convert the lamp’s irradiance at 500 mm to that at a desired distance, it should be noted that when the distance is halved, the irradiance is quadrupled. To achieve an exact match between the lamp’s irradiance and one equivalent sun at AM1, the distance from the bulb should be 205 mm. Brazilian standard [10] and Australian/New Zealand standard [11] require that sunglasses should be irradiated for 50 uninterrupted hours at a distance of 300 mm from the lamp’s bulb in the resistance-to-radiation test. Reasons for that particular distance and period seem unclear and likely lost in history. Under these conditions, according to Table 1, 1 h of lamp exposure is equivalent to 0.5 h of orthogonal sun exposure at AM1, i.e., this simulation system is equivalent to 0.5 sun. Therefore, irradiating sunglasses for 50 h under a simulator should be equivalent to exposing the sunglasses to the sun for 25 h at AM1. This result is not realistic because the atmospheric path of solar beams varies with solar displacement. In addition, it should be considered that when an individual wears sunglasses, the lenses are not orthogonally exposed to the sun because they are usually worn in the vertical position, in which the lenses are not orthogonal to the sun’s rays. Therefore, the incidence angles of solar rays with respect to the sunglasses lenses are relevant, and the sun’s elevation should thus be taken into account, i.e., one should account for oblique incidence. Some researchers have shown the personal effects of outdoor solar exposure [24, 25] addressing the dermatological aspects. In this sense, concerns regarding solar exposure are pertinent and the effectiveness of solar simulation on the standards and its parameters are relevant. In order to establish the correspondence of solar simulator and natural sun exposure on sunglasses worn by an individual, some pertinent considerations, named boundary conditions are required. On authors’ public on-going web survey, 55,000 people have already answered the questions and as a result, most users in Brazil wears sunglasses for at least 2–4 h a day, and purchase new ones every 2 years. Therefore, three possible scenarios are reasonable to be explored to set a correspondence of sun simulation on sunglasses and natural sun exposure with boundary conditions. In a recent publication [2], the authors showed that the profile of solar irradiance on vertical surfaces has two distinctive peaks, which indicate the highest irradiances at a given time of day. One of the peaks refers to the time equivalent to the middle of the morning period (average of 143 min after sunrises); the second peak refers to the middle of the afternoon period (average of 143 min before sunsets). Using the established irradiance profiles, three scenarios of solar exposure were analyzed: (1) Sunglasses exposed to the sun over the period spanning from 30 min before the first peak (sunrise in the morning) to 30 min after the second peak, before sunset. The precise time at which each peak occurs shifts throughout the year, and this drift is accounted for. Hence, for each day, the period of exposure to the sun is different. For our purposes, the exposure period is called photoperiod; (2) The photoperiod spanning from sunrise to sunset. This range corresponds to the maximum possible irradiation from the sun and is included herein for comparison purposes; This second scenario, apparently unreal, is quite important for outdoor workers, especially in tropical countries, where a large part of the population is outdoor worker. (3) The 60 min of exposure time centered at the morning peak. We note that in the three scenarios considered in this work, sunglasses were assumed to be worn in the upright position, tracking the position of the sun and accounting for the oblique incidence. One may argue that, on a daily basis, although the assumption of a vertical position is accurate, the tracking of the sun may be not. The latter assumption can be relaxed by assuming a random vertical positioning of the sunglasses. In this case, the sunglasses are, on average, facing the sun for half of the wearing period, and in the other half, they are worn with the lenses directed away from the sun. Hence, the incident radiant exposure onto the sunglasses is 50 % of the previously calculated amount. Thus, our proposed times for the stress test could be halved. Also, actual human exposure conditions can be less than our worst-case assumptions, but reduction of UV by automotive windscreens, shading, etc. are not experienced by many who only wear their sunglasses in open environments, e.g., beachgoers, lifeguards, farmers, and most outdoor workers. Aging test For lenses irradiated for 50 h at a distance of 300 mm from the lamp during the aging test, the accumulated radiant exposure [Eq. (3)] delivered by the lamp to the lenses is 7.8 MJ m−2. Comparisons of the lamp’s radiant exposure with the sun’s radiant exposure in the three chosen scenarios were made based on these conditions. In this work, the authors also considered that the sunglasses faced the sun, vertically (with the sunglasses positioned on the face of an individual), for the entire period. For each scenario, we selected a southern summer day (day 355) and a winter day (day 172) to compare the radiant exposure levels. Obviously, those seasons are reversed for Northern Hemisphere. The chosen days represent the solstices, i.e., the year’s longest and shortest photoperiods, because similar to the reason for selecting a position in which sunglasses face the sun for the entire test period, these days provide the most extreme conditions. In addition, the sun’s daily average radiant exposure is herein presented. The daily average was calculated by summing the solar radiant exposure over the entire year and dividing it by 365.25 days. Last column of Table 2 presents the results of the lamp–sun equivalence for each scenario, in which the lamp–sunglasses distance is 300 mm, as established by the standards. The equivalences in “days of use” presented in the last column of Table 2 are determined by the ratio between the lamp’s radiant exposure (6th column) and the global solar radiant exposure (5th column), both italicized for clarity.Table 2 Comparison between the daily solar radiant exposure in São Paulo (SP), Brazil, and the radiant exposure provided by the lamp over a 50-h period (distance between sunglasses and lamp is 300 mm) for 2 specific days of the year: the shortest (day 172) and longest (day 355) days Radiant exposure (MJ m−2) Photoperiod (h) Lamp–sun equivalence (days) Solar Lamp Direct Diffuse Global Direct From peak to peak  Day 172 1.5 0.5 2.0 7.8 4.0 4  Day 355 2.3 1.4 3.7 7.8 8.6 2  Daily average 2.1 1.0 3.2 7.8 6.9 2  Lamp 50.0 From sunrise to sunset  Day 172 3.0 1.0 4.0 7.8 10.7 2  Day 355 3.3 1.7 5.0 7.8 13.6 2  Daily average 3.2 1.4 4.6 7.8 12.1 2  Lamp 50.0 First band peak only  Day 172 0.4 0.1 0.5 7.8 1.0 16  Day 355 0.4 0.1 0.5 7.8 1.0 16  Daily average 0.4 0.1 0.5 7.8 1.0 16  Lamp 50.0 In addition, the daily average is shown In the first scenario, sunglasses were exposed to solar radiation from half an hour before the first peak in the direct solar radiant exposure profile up to half an hour past the second peak for a particular day. In this scenario, the global solar radiant exposure, which is the sum of the direct and diffuse components, amounts to 3.7 MJ m−2 for day 355 (southern summer day). Hence, the lamp’s radiant exposure (over a 50-h period), which sums to 7.8 MJ m−2, is two times greater than the solar radiant exposure of day 355 (see second row in Table 2). Thus, the exposure time of 50 h in the simulator is equivalent to the exposure to sunlight for approximately 2 days of specific day 355. In this scenario, day 355 has 8.6 h (from peak to peak) of exposure time to sunlight. Therefore, the national standard requirements for aging tests—in which lenses are exposed for 50 h to a 450 W lamp (XBO450–OFR) at a distance of 300 mm from the lamp bulb—appears to be inadequate for aging tests, at least with regard to the superficial radiant exposure equivalence between the exposure to the lamp and to the natural environment. Even for a less severe scenario, such as exposure on a winter day (e.g., day 172, for southern hemisphere), the solar radiant exposure components that reach a vertical surface are 1.5 MJ m−2 (direct) and 0.5 MJ m−2 (diffuse), resulting in a global radiant exposure of 2.0 MJ m−2. Assuming the same testing conditions described previously, the lamp-exposure time (50 h) is equivalent to 4 days (the photoperiod for day 172 is 4.0 h). Once more, the requirements defined for the aging tests are not sufficient. Calculations were performed for each day of the year to allow the results to be averaged throughout the year, yielding a daily average. Table 2 summarizes the average results alongside the results for the particular days referenced above. The table also presents a comparison with results obtained for the entire photoperiod of each day, i.e., from sunrise to sunset. Table 2 presents the central results of this work. It can be observed that the test for sunglasses’ resistance to radiation (and the aging process thereof) required by the standards only probes the deterioration of the UV protection of the lenses for quite a short period and is therefore insufficient to guarantee their safety in terms of eye protection. Thus, the solarization test is ineffective and has no practical value. To overcome these limitations of the standard requirements, one may either increase the exposure time of the lenses to the lamp or decrease the distance of the lenses from the lamp. Increasing the exposure time is certainly possible, although doing so may increase the cost and certification time, eventually causing the procedure to become impractical. According to Table 1, decreasing the distance from the lamp may be a more effective alternative because of the inverse square law for point sources. For instance, setting the distance from the lamp to 50 mm yields the results presented in Table 3. As expected, a sixfold reduction in distance increases the lamp–sun equivalence to a factor of 36, compared with values presented in last column of Table 2. On the other hand, increasing the exposure times avoids the consequential temperature rise that may come from decreasing the distance. A third alternative would be to change the 450 W lamp to higher power lamp, e.g., a 1600 W lamp, which is commercially available. However, this would require a major evaluation of this requirement in the standards, especially the specifications of the simulator as a whole.Table 3 Comparison between the daily solar radiant exposure in São Paulo (SP), Brazil, and the radiant exposure provided by the lamp over a 50-h period (distance between sunglasses and lamp is 50 mm) for 2 specific days of the year: the shortest (day 172) and longest (day 355) days Radiant exposure (MJ m−2) Lamp–sun equivalence (days) Solar Lamp Global Direct 1. From peak to peak Day 172 2.0 280.3 140 Day 355 3.7 280.3 76 Daily average 3.2 280.3 88 2. From sunrise to sunset Day 172 4.0 280.3 70 Day 355 5.0 280.3 56 Daily average 4.6 280.3 61 3. First band peak only Day 172 0.5 280.3 561 Day 355 0.5 280.3 561 Daily average 0.5 280.3 561 In addition, the daily average is shown Based on informed estimates, it is quite reasonable to assume that the UV protection of sunglasses should be required to last at least 2 years (730.5 days) under the first scenario considered in this work. To simulate such a case, simply decreasing the distance from the lamp in the stress tests is insufficient, and the exposure time must be increased. For instance, on third row in Table 3, at lamp-sunglasses distance of 50 mm, the lamp provides 280.3 MJ m−2 for the 50 h of simulation period. Under the assumptions of the first scenario, the solar radiant exposure is, in average, 3.2 MJ m−2 per day. Thus, the ratio lamp–sun is 88 days. Hence, to increase the lamp–sun equivalence from 88 days to 730.5 days (2 years), the total radiant exposure of the lamp should be increased by a factor of 8.3, i.e., from 280.3 MJ m−2 to 2326.5 M m−2. This means to increase the period of the 450 W lamp simulator by the same factor, i.e., from 50 to 414.6 h of exposure, at a distance of 50 mm. To simulate the unlikely scenario of an individual who wears sunglasses from sunrise to sunset (in São Paulo, Brazil), the lamp–sun equivalence should be increased even more, and the lamp-exposure time should be increased to 603.7 h. Table 4 presents the calculated data for radiant exposure lamp–sun equivalence, in days, for decreasing distances between the lamp and tested sunglasses. The data were calculated for 27 state capitals in Brazil. For each scenario and particular distance, the minimum and maximum values are listed. The entries labeled MED in Table 4 are the median values among all 27 locations in Brazil for which the calculations were carried out. Once the latitude distribution of all locations considered in this work is non uniform, the median was calculated instead of the average to avoid unintended deviations. As expected, the lamp–sun equivalences as functions of distance, shown in each row of Table 4, follow an inverse square law.Table 4 Calculated radiant exposure lamp–sun equivalences (in “days of use”) for different scenarios and for a decreasing distance d (mm) between the lamp and sunglasses. The minimum and maximum lamp–sun equivalences are listed Distance (d) from lamp (mm) 300 250 200 150 100 50 1. From peak to peak  Min 2 3 5 9 21 83  Max 3 4 6 11 26 103  Med 2 3 5 9 21 84 2. From sunrise to sunset  Min 2 2 4 7 15 60  Max 2 3 4 7 16 62  Med 2 3 4 7 16 62 3. First band peak only  Min 15 22 34 60 134 537  Max 15 22 35 62 139 556  Med 15 22 35 62 139 555 Additionally, the medians of all 27 cities are shown Evidently, a typical person wears sunglasses throughout the year over a period of less than 8–12 h a day on average (our survey [2] indicates an average of 2 h daily). In such cases, the user may wear his/her sunglasses over a longer season while retaining the UV protection of the lenses. Tables 2, 3 and 4 present results calculated for the third scenario, in which an individual wears sunglasses for a typical period of 1 h daily when this period is assumed to coincide with the maximum exposure to solar radiation. To simulate this case, the lamp-exposure time should be 67.3 h (at a distance of 50 mm) to ensure a protection lifetime of 2 years (730.5 days). Based on the survey of the Brazilian population, most users wears the same pair of sunglasses for a minimum of 2 years and for a period of 2 h a day. Therefore, the standard must guarantee that sunglasses should be safe over this period. In this case, the solarization test should be performed for 134.6 h (at a distance of 50 mm). In this respect, our contribution is the refinement of the parameters required by current standards for solar simulator exposure. In order to extend the scope of this work, Table 5 presents, similarly, the same results as Table 4 for 110 national capitals from Northern Hemisphere. It is worth noting that the results for the lamp–sun equivalences are very similar to the values from Brazil, with a slight difference in favor of Norther Hemisphere due to the higher latitudes in general. Nevertheless, the results indicates that the solarization test of sunglasses is inadequate even for countries in Northern Hemisphere.Table 5 Calculated radiant exposure lamp–sun equivalences (in “days of use”) for different scenarios and for a decreasing distance d (mm) between the lamp and sunglasses Distance (d) from lamp (mm) 300 250 200 150 100 50 From peak to peak  Min 2 3 5 9 19 78  Max 7 10 16 28 63 252  Med 3 4 7 12 27 107 From sunrise to sunset  Min 2 2 4 6 14 57  Max 2 3 5 9 21 84  Med 2 3 4 7 16 62 First band peak only  Min 14 21 32 57 129 516  Max 23 33 52 93 209 836  Med 16 22 35 62 139 557 The minimum and maximum lamp–sun equivalences are listed. Additionally, the medians of all 110 national capitals from northern hemisphere are shown As in Brazil the sun delivers 0.5 MJ m−2 a day, for the third scenario, in 24 months, it would be delivered an amount of 365.3 M m−2 (0.5 M m−2 × 730.5 days). Therefore, for implementing such requirement for the “resistance to radiation test” of the standards, an appropriate solar simulator, which provides irradiance, should be architected in order to supply accelerated simulation of sun exposure. It should assemble adequate lamp power, exposure time, distance from the bulb and controlled temperature that the sample will be exposed to. Conclusions The present test parameters for exposing samples to a solar simulator, as specified by the Brazilian and many national standards, should be revisited to establish safe limits for UV filters of sunglasses. By changing the exposure time within the solar simulator and the distance of the samples from the lamp, respectively, to 67.3 h and 50 mm, sunglasses can be safe to wear for a period of 2 years for users who wear them for a maximum of 2 h a day. It is worth noting that the temperature inside a solar simulator should not exceed limits that deteriorate the optical properties of sunglasses. Thus, it has to be assured by further investigation that the temperature inside the solar simulator at this distance from the lamp does not reach inappropriate levels. Our calculations were made to ensure the safety of sunglasses worn in Brazil, but are also valuable to countries that share same latitudes. Additionally, results for 110 national capitals in northern hemisphere were presented, broadening the reach of this effort to help establish safe limits for UV filters of sunglasses. Abbreviations UVultraviolet ICNIRPInternational Commission on Non-Ionizing Radiation Protection CIEInternational Commission on Illumination (Commission Internationale de l’Eclairage) SMARTS2simple model of the atmospheric radiative transfer of sunshine v. 2 AMair mass Authors’ contributions Both authors actively participated in the design of this study, calculations interpretation of results and in the preparation of the manuscript. Both authors read and approved the final manuscript. Acknowledgements Not applicable. Competing interests The authors declare that they have no competing interests. Availability of data and material The main calculations used the SMARTS2 freeware codes, available from Ref. [21]. Funding The authors are grateful to FAPESP (Grant number: 2013/08038-7, coordinator Mauro Masili and 2014/16938-0, coordinator Liliane Ventura), which financially supports our research. ==== Refs References 1. Mello MM Lincoln VAC Ventura L Self-service kiosk for testing sunglasses Biomed Eng Online. 2014 13 45 10.1186/1475-925X-13-45 24761766 2. Masili M Schiabel H Ventura L Contribution to the radiation protection for sunglasses standards Radiat Prot Dosimetry 2015 164 3 435 443 10.1093/rpd/ncu274 25205833 3. International Commission on Non-ionizing Radiation Protection ICNIRP). Guidelines on limits of exposure to ultraviolet radiation of wavelengths between 180 nm and 400 nm (incoherent optical radiation Health Phys 2004 87 2 171 186 10.1097/00004032-200408000-00006 15257218 4. Commission Internationale de L’Éclairage (CIE) International lighting vocabulary 2011 Vienna CIE Standard S 017/E:2011 5. Commission Internationale de L’Éclairage Standardization of the terms UV-A1, UV-A2 and UV-B 1999 Vienna CIE Standard S 134/1:1999 6. Doughty MJ Cullen AP Long-term effects of a single dose of ultraviolet-B on albino rabbit cornea-I In vivo analyses. Photochem Photobiol. 1989 49 2 185 196 10.1111/j.1751-1097.1989.tb04095.x 2710827 7. Sliney DH UV radiation ocular exposure dosimetry J Photochem Photobiol, B 1995 31 69 77 10.1016/1011-1344(95)07171-5 8568605 8. Zuclich JA Ultraviolet-induced photochemical damage in ocular tissues Health Phys 1989 56 5 671 682 10.1097/00004032-198905000-00012 2651362 9. Söderberg PG Experimental cataract induced by ultraviolet radiation Acta Ophthalmol Suppl. 1990 196 1 75 2161611 10. Associação Brasileira de Normas Técnicas Proteção pessoal dos olhos—Óculos de sol e filtros de proteção contra raios solares para uso geral 2015 Brasília NBR ISO 12312-1:2015 11. Australian/New Zealand Standard Sydney, Australia and Wellington 2003 New Zealand Sunglasses and fashion spectacles. AS, NZS. Standards Australia/Standards New Zealand 1067 12. International Organization for Standardization Eye and face protection—sunglasses and related eyewear Part 1: sunglasses for general use 2013 Geneva ISO 12312-1:2013 13. European Standards Organisation (CEN) Eye and face protection—Sunglasses and related eyewear Part 1 sunglasses for general use 2015 Brussels CEN EN ISO 12312-1:2013/Amd 1:2015 14. American National Standards Institute (ANSI) Ophthalmics nonprescription sunglasses and fashion eyewear requirements 2015 New York ANSI 15. Gies P Australia has more than enough solar UV radiation Clin Exp Optom 2003 86 2 71 73 10.1111/j.1444-0938.2003.tb03064.x 12643802 16. Chou BR Dain SJ Cheng BB Effect of ultraviolet exposure on impact resistance of ophthalmic lenses Optom Vis Sci 2015 92 12 1154 1160 10.1097/OPX.0000000000000730 26540475 17. International Organization for Standardization Textiles—tests for colour fastness—Part B02: colour fastness to artificial light: Xenon arc fading lamp test 2014 Geneva ISO 105-B02:2014 18. International Organization for Standardization Textiles—tests for colour fastness—Part B04: colour fastness to artificial weathering: xenon arc fading lamp test 1994 Geneva ISO 105-B04:1994 19. International Organization for Standardization Textiles—tests for colour fastness Part B06: colour fastness and ageing to artificial light at high temperatures: Xenon arc fading lamp test 1998 Geneva ISO 105-B06:1998 20. International Organization for Standardization Paints and varnishes—determination of resistance to cyclic corrosion conditions Part 2 Wet (salt fog)/dry/humidity/UV light 2013 Geneva ISO 11997-2 21. Gueymard CA SMARTS, a simple model of the atmospheric radiative transfer of sunshine: algorithms and performance assessment. Technical Report No. FSEC-PF-270-95 1995 Cocoa Florida Solar Energy Center 22. Koepke P Bais A Balis D Buchwitz M De Backer H de Cabos X Comparison of models used for UV index calculations Photochem Photobiol 1998 67 6 657 662 10.1111/j.1751-1097.1998.tb09109.x 9687266 23. Ryer A Light measurement handbook 1998 Newburyport International light Inc. Technical Publications Dept 96 24. Helihy E Gies P Roy CR Jones M Personal dosimetry of solar UV radiation for different outdoor activities Photochem Photobiol 1994 60 3 288 294 10.1111/j.1751-1097.1994.tb05106.x 7972383 25. Kimlin MG Parisi AV Wong JCF Quantification of personal solar UV exposure of outdoor workers, indoor workers and adolescents at two locations in Southeast Queensland Photodermatol Photoimmunol Photomed 1998 14 1 7 11 10.1111/j.1600-0781.1998.tb00002.x 9582080

PMC005xxxxxx/PMC5000449.txt

==== Front BMC PsychiatryBMC PsychiatryBMC Psychiatry1471-244XBioMed Central London 101410.1186/s12888-016-1014-3Research ArticleValidity assessment of the symptom checklist SCL-90-R and shortened versions for the general population in Ukraine Sereda Yuliia yulia.v.sereda@gmail.com 1Dembitskyi Serhii serg_dem@meta.ua 21 Senior Scientific Associate, Department for Monitoring of Social and Economic Transformations, Institute for Economics and Forecasting, National Academy of Sciences, Kiev, Ukraine 2 Senior Scientific Associate, Department of Methodology and Methods of Sociology, Institute of Sociology, National Academy of Sciences, Kiev, Ukraine 26 8 2016 26 8 2016 2016 16 1 30021 1 2016 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The Symptom Checklist-90-Revised (SCL-90-R) is a widely used symptomatic distress questionnaire. A translated version of the SCL-90-R has been applied in Ukrainian general population surveys several times but has not yet been validated in this country. The SCL-90-R and its short versions (BSI-53, SCL-27, BSI-18, SCL-14 and SCL-9-K) were investigated in order to comparatively assess their properties and applications in Ukraine. Methods Secondary analysis of three nationally representative cross-sectional surveys (1997, 1999 and 2014) using SCL-90-R was applied. Two thousand sixty nine respondents participated in 2014; the sample size for the 1997 and 1999 surveys was 1810 respondents per wave. Statistical data analysis is based on calculating internal consistencies with Cronbach’s Alpha, confirmatory factor analysis, nonparametric correlations and effect sizes for the equivalence of the full and short versions. Results The scales of SCL-90-R and its shortened versions showed equally high internal consistencies. With regard to factorial validity, 2014 data confirmed the dimensional structure of all versions. Unsatisfactory results were found in 1997 and 1999 for SCL-90-R and in 1997 for SCL-27, based on the Chi-square criterion (χ2/degrees of freedom > 5), though other indexes suggested satisfactory model fit (RMSEA < 0.06; CFI, TLI > 0.95). Analysis of the equivalence of shortened and full versions of the SCL-90-R has shown the presence of small effect sizes. Conclusion BSI-18 and SCL-9-K are recommended for use in general population surveys as more economical versions of SCL-90-R. Both versions revealed satisfactory validity in 1997, 1999 and 2014. Electronic supplementary material The online version of this article (doi:10.1186/s12888-016-1014-3) contains supplementary material, which is available to authorized users. Keywords SCL-90-RShort versionsMental disordersSymptomatic distressSelf-report questionnairehttp://dx.doi.org/10.13039/100000061Fogarty International CenterD43TW000233Sereda Yuliia http://dx.doi.org/10.13039/501100004742National Academy of Sciences of Ukraine0114U003415Dembitskyi Serhii issue-copyright-statement© The Author(s) 2016 ==== Body Background Symptom Checklist-90-Revised (SCL-90-R) is a widely used questionnaire developed by Leonard R. Derogatis [1] to determine a number of psychological symptoms. In Ukraine, SCL-90-R was first used in the study “Mental health of children after the Chernobyl disaster” [2]. Later, it was applied in three surveys with samples that were representative of the entire population (1997, 1999 and 2014), but it has not yet been validated. SCL-90-R includes 90 symptoms and evaluates nine symptomatic dimensions: somatization, obsessive-compulsive disorder, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism [1]. Given the demand for briefer measures to be used as a screening tool for psychiatric disorders, shortened versions of SCL-90-R were developed, such as BSI-53 [3], SCL-27 [4], BSI-18 [5], SCL-14 [6, 7] and SCL-9-K [6, 8]. BSI-53 includes all nine symptomatic dimensions with a reduced number of symptoms, whereas SCL-27, BSI-18 and SCL-14 have both reduced factor structures and reduced numbers of items. SCL-9-K is the shortest measure, including nine symptoms within a single dimession (general severity factor). Numbers of indicators for symptomatic dimensions in SCL-90-R and its shortened versions are presented in Table 1.Table 1 Dimensional structure and items of the SCL-90-R and its shortened versions SCL-90-R BSI-53 SCL-27 BSI-18 SCL-14 SCL-K-9 Scale Indicators Scale Indicators Scale Indicators Scale Indicators Scale Indicators Scale Indicators SOMA 1, 4, 12, 27, 40, 42, 48, 49, 52, 53, 56, 58 SOMA 4, 12, 40, 48, 49, 52, 56 VEG 4, 39, 40, 48, 49, 53 SOMA 12, 40, 48, 52, 56, 58 VEG 42, 52, 56, 58 OCD 3, 9, 10, 28, 38, 45, 46, 51, 55, 65 OCD 9, 28, 45, 46, 51, 55 DYS 9, 14, 51, 55 INT 6, 21, 34, 36, 37, 41, 61, 69, 73 INT 34, 37, 41, 69 SOP 37, 41, 61, 69 DEPR 5, 14, 15, 20, 22, 26, 29, 30, 31, 32, 54, 71, 79 DEPR 15, 29, 30, 32, 54, 79 DEP 15, 30, 54, 59 DEPR 15, 29, 30, 32, 54, 79 DEP 26, 28, 30, 54, 77, 79 ANX 2, 17, 23, 33, 39, 57, 72, 78, 80, 86 ANX 2, 23, 33, 57, 72, 78 ANX 2, 33, 57, 72, 78, 86 HOST 11, 24, 63, 67, 74, 81 HOST 11, 24, 63, 67, 74 PHOB 13, 25, 47, 50, 70, 75, 82 PHOB 13, 47, 50, 70, 75 AGO 13, 25, 33, 50, 82 AGO 13, 25, 47, 82 PARA 8, 18, 43, 68, 76, 83 PARA 8, 18, 43, 76, 83 MIS 18, 68, 76, 83 PSYC 7, 16, 35, 62, 77, 84, 85, 87, 88, 90 PSYC 7, 77, 85, 88, 90 ADD 19, 44, 59, 60, 64, 66, 89 ADD 19, 44, 59, 89 GSI all above GSI all above GSI all above GSI all above GSI all above GSI 24, 28, 31, 34, 43, 57, 58, 75, 77 SOMA Somatization, OCD Obsessive-Compulsive Disorder, INT Interpersonal Sensitivity, DEPR Depression, ANX Anxiety, HOST Hostility, PHOB Phobic Anxiety, PARA Paranoid Ideation, PSYC Psychoticism, GSI Global Severity Index, DEP Depressive Symptoms, DYS Dysthymic Symptoms, VEG Vegetative Symptoms, AGO Agoraphobic Symptoms, SOP Symptoms of Social Phobia, MIS Symptoms of Mistrust The vast majority of psychometric studies studies on SCL-90-R were conducted on clinical samples, such as patients of mental health centers and agencies [9, 10], patients with depression [11], patients undergoing personality-centered therapy [12], forcibly hospitalized patients with mental disorders [13], adults and adolescents hospitalized with crisis intervention [14], substance abusers [15], patients with panic disorders [16], veterans undergoing psychiatric treatment [17], patients waiting for bariatric surgery [18], volunteers for drug trials [19] etc. A number of studies estimated properties of SCL-90-R on non-clinical samples, in particular those representative of the entire population or of certain communities; such studies were conducted in Canada [20], Denmark [21], Finland [22], Germany [23], Hungary [24], Japan [25], Italy [26], Norway [27], Thailand [28] and the USA [29]. Overall, there is increasing agreement on the multidimensional nature of the SCL-90-R, although various solutions from bifactor structure [24] to the nine original dimesions [16, 22, 23, 25] have been reported. A few studies support the unidimensional structure of the SCL-90-R as broad construct of distress [21, 28]. Weakness of the validity of SCL-90-R is explained by different reasons, including limitations of sample design and statistical measures. A German study revealed that subscale internal reliabilities are better for clinical samples when compared to non-clinical samples, which might result in revision of the SCL-90-R for the general population [23]. R. Urbán et al. [24] highlighted that the vast majority of studies inappropriately used methods considering responses on a linear scale instead of an ordinal scale, and implemented the maximum likelihood estimator for measuring factor validity, which underestimates the fit of the models in confirmatory factor analysis, resulting in weak structural validity. Comparative validation of the SCL-90-R and its shortened versions requires further investigation. While the vast majority of papers focus on the full version of the SCL-90-R, Müller et al. [30] examined the validity of eleven shortened versions and recommended SCL-10S as an instrument to measure psychological distress. Recently, Prinz et al. compared the psychometric properties of five shortened versions and concluded that BSI-18 appears to be the most economical variant and most clinically meaningful instrument [6]. None of the comparative validation studies of the SCL-90-R were conducted on non-clinical samples. Given that previous studies did not come up with a single solution regarding factor validity of the SCL-90-R, we attempt to investigate SCL-90-R in order to comparatively assess its properties and application in Ukraine. Moreover, we concentrate on the comparative validation of SCL-90-R and its five shortened versions (BSI-53, SCL-27, BSI-18, SCL-14, SCL-9-K) in order to assess the extent to which they can reliably measure psychological distress as well as certain distress subscales. In particular, we examine which shortened version provides superior reliability, validity and practical utility in national monitoring surveys with representative samples. Our choice of shortened versions is driven by the evidence that BSI-53 and SCL-27 showed superior discriminant validity while BSI-18, SCL-14 and SCL-9-K demonstrated better performance regarding the general severity factor among the shortest versions in the previous studies [6, 30]. Methods Design The research is based on a secondary analysis of data collected by the Institute of Social Sciences, National Academy of Sciences of Ukraine (a social monitoring “Ukrainian Society” for 1997 and 1999, principal investigator Prof. Dr. Evgeniy Golovakha), as well as the joint monitoring of the Ukrainian Institute for Social Research after A. Yaremenko, Social Monitoring Center and the Department for Monitoring of Social and Economic Transformations, Institute for Economics and Forecasting, National Academy of Sciences of Ukraine (2014 study, principal investigator Olga Balakireva). In 1997 and 1999, 1810 respondents were interviewed; 2069 respondents were interviewed in 2014. Each of the three cross-sectional studies is representative of the main socio-demographic characteristics of the adult population of Ukraine. In the 1997 and 1999 arrays the sex ratio was 45 % male and 55 % female, and the mean age was 45 years; in the 2014 array, 44 % were male and 56 % were female, and the mean age was 46 years. The 2014 study included 24 regions of Ukraine and Kiev, while in 1997 and 1999, 24 regions of Ukraine, Kiev and the Crimea were included. In all three studies data collection was administered through a face-to-face questionnaire. SCL-90-R was first translated and adapted for Ukraine by Dr. Nataliia Panina for a survey of mothers evacuated from Pripyat, Chernobyl in 1986 [2]. The adequacy of the Ukrainian and Russian translation to the English version was assessed through a back-translation by a professional translator. Tools In all three studies, the questionnaire SCL-90-R was completed as one section of a general questionnaire that included a wide range of social, political and economic aspects. The questionnaire was translated into both Ukrainian and Russian, as different languages were used for different regions of the country. Shortened versions of the symptomatic questionnaire (BSI-53, SCL-27, BSI-18, SCL-14, SCL-9-K) were calculated on the basis of SCL-90-R questions during the secondary analysis. Statistical analysis Included reliability assessment of SCL-90-R subscales, factorial validity of symptomatic measurements and equivalence of individual variants of SCL-90-R. All methods were applied for all three studies (1997, 1999 and 2014). To assess the reliability of individual symptomatic measures and the Global Severity Index (GSI) in all six versions (SCL-90-R, BSI-53, SCL-27, BSI-18, SCL-14, SCL-9-K) Cronbach’s alpha coefficients were calculated. Values of the coefficient that were higher than 0.7 were considered acceptable [31]. To confirm the factor validity of symptomatic measurements of the full and abbreviated versions of SCL-90-R, confirmatory factor analysis (CFA) was carried out. Given that all indicators have ordinal scales, a Diagonally Weighted Least Squares method (DWLS) was used to estimate the parameters of the CFA, which allows estimation of robust standard errors and correction of the test statistics. Missing values (up to 5 %) were excluded. To assess the quality of the factor models the following indices have been estimated: χ2 (Minimum Function Chi-square), RMSEA (The Root Mean Square Error of Approximation), CFI (Comparative fit index) and TLI (Tucker-Lewis index). An acceptable model fit was considered χ2/degrees of freedom < 5; RMSEA < 0.06; and CFI, TLI > 0.95 [32]. Since the distribution of all indicators of symptomatic measurements and GSI in the full and shortened versions of the SCL-90-R deviated from normal, nonparametric methods were used for the analysis of equivalence. To analyze the equivalence of the full and shortened versions of SCL-90-R, median and interquartile distances were estimated, the statistical significance of the median differences was calculated on the basis of the Wilcoxon median test, and effect sizes and Spearman’s Rho correlations were defined. We used Vargha and Delaney’s A effect sizes, according to which a small effect is over 0.56; a medium effect is over 0.64, and a large effect is over 0.71 [33]. The size of the correlations was based on the following interpretation limits: rho < 0.30, small correlation; 0.30 > rho < 0.50, medium correlation and rho > 0.50, large correlation [34]. The equivalence of different versions of the SCL-90-R was also evaluated in the context of the size difference of the group with a high risk of psychological distress in the general population, depending on the method, or in other words, the extent to which the prevalence of “probable cases” differs. According to Derogatis’ criterion for the general population, if the GSI has a T-value ≥ 63, such individuals may be characterized by the presence of severe symptoms of distress [35]. It is also common to use the criterion of GSI > 1 to determine the proportion of people with severe symptoms of distress [36]. R (package «lavaan» for CFA) and SPSS, version 20 were used for the statistical analysis. Results Reliability In the 1997 study Cronbach’s alpha coefficients for different symptomatic measurements ranged from 0.59 (depressive symptoms in SCL-27) to 0.96 (GSI in the SCL-90-R); in 1999 - from 0.63 (depressive symptoms in SCL-27) to 0.97 (GSI in the SCL-90-R), and in 2014 - from 0.66 (depressive symptoms in SCL-27) to 0.98 (GSI in SCL- 90-R) (see Table 2). Cronbach’s alpha coefficients of below an acceptable level of reliability were observed for interpersonal sensitivity in BSI-53 and symptoms of social phobia in the SCL-27 (1997 and 1999), for hostility and phobic anxiety in the 1997 study (in BSI-53), for psychoticism in 1997 and 1999 (in BSI-53), for symptoms of mistrust in 1997 and 1999 (in SCL-27) and for agoraphobic symptoms in 1997 and 1999 (in SCL-14). However, in the 2014 study, the only symptomatic dimension with an unsatisfactory level of reliability was a depressive symptoms scale in SCL-27.Table 2 Reliability of the SCL-90-R subscales and the shortened versions BSI, SCL-27, BSI-18, SCL-14 and SCL-K-9 in the Ukrainian general population SCL-90-R BSI-53 SCL-27 BSI-18 SCL-14 SCL-K-9 Scale Cronbach’s alpha Number of items Scale Cronbach’s alpha Number of items Scale Cronbach’s alpha Number of items Scale Cronbach’s alpha Number of items Scale Cronbach’s alpha Number of items Scale Cronbach’s alpha Number of items 1997 1999 2014 1997 1999 2014 1997 1999 2014 1997 1999 2014 1997 1999 2014 1997 1999 2014 SOMA 0.90 0.89 0.93 12 SOMA 0.85 0.84 0.89 7 VEG 0.80 0.80 0.87 6 SOMA 0.84 0.84 0.89 6 VEG 0.85 0.84 0.88 4 OCD 0.81 0.83 0.90 10 OCD 0.76 0.79 0.86 6 DYS 0.74 0.78 0.81 4 INT 0.80 0.82 0.87 9 INT 0.62 0.66 0.77 4 SOP 0.64 0.69 0.76 4 DEPR 0.83 0.85 0.91 13 DEPR 0.73 0.75 0.82 6 DEP 0.59 0.63 0.66 4 DEPR 0.73 0.75 0.82 6 DEP 0.72 0.73 0.86 6 ANX 0.81 0.86 0.92 10 ANX 0.74 0.80 0.87 6 ANX 0.73 0.79 0.86 6 HOST 0.74 0.75 0.82 6 HOST 0.69 0.70 0.78 5 PHOB 0.74 0.78 0.87 7 PHOB 0.68 0.71 0.82 5 AGO 0.71 0.75 0.83 5 AGO 0.64 0.68 0.81 4 PARA 0.74 0.75 0.84 6 PARA 0.72 0.72 0.81 5 MIS 0.64 0.69 0.76 4 PSYC 0.79 0.78 0.90 10 PSYC 0.68 0.65 0.82 5 GSI 0.96 0.97 0.98 83 GSI 0.94 0.95 0.97 49 GSI 0.90 0.92 0.95 27 GSI 0.88 0.90 0.94 18 GSI 0.84 0.85 0.92 14 GSI 0.81 0.85 0.89 9 SOMA Somatization, OCD Obsessive-Compulsive Disorder, INT Interpersonal Sensitivity, DEPR Depression, ANX Anxiety, HOST Hostility, PHOB Phobic Anxiety, PARA Paranoid Ideation, PSYC Psychoticism, GSI Global Severity Index, DEP Depressive Symptoms, DYS Dysthymic Symptoms, VEG Vegetative Symptoms, AGO Agoraphobic Symptoms, SOP Symptoms of Social Phobia, MIS Symptoms of Mistrust It should be noted that the GSI in different versions of SCL-90-R ranged from 0.81 to 0.98, indicating good reliability. In general, we can note satisfactory reliability for all versions of the symptomatic checklist. Factorial validity According to the RMSEA criteria < 0.06 and CFI, TLI > 0.95, all models have demonstrated satisfactory validity: the results of confirmatory factor analysis generally support the internal structure of symptomatic measures in the SCL-90-R (nine factors), BSI-53 (nine factors), SCL-27 (six factors), BSI-18 (three factors), SCL-14 (three factors) and SCL-90-R (a single factor) (Table 3). A comparison of models fit lower RMSEA and higher CFI and TLI in 2014 compared to the 1997 and 1999 studies. A three-factor model SCL-14 and ten-factor model BSI-53 in the 2014 study are characterized by the lowest χ2/DF ratios and the highest CFI and TLI values compared to other models; i.e. these versions of the symptomatic questionnaire demonstrate the best factorial validity.Table 3 Factor validity of SCL-90-R, BSI-53, SCL-27, BSI-18, SCL-14 and SCL-9-K in the Ukrainian general population: confirmatory factor analysis fit Fit SCL-90-R BSI-53 SCL-27 BSI-18 SCL-14 SCL-K-9 1997 1999 2014 1997 1999 2014 1997 1999 2014 1997 1999 2014 1997 1999 2014 1997 1999 2014 χ2 (DWLS) 25299 21196 15672 6323 6117 4714 1844 1258 1243 575 530 543 415 279 183 111 118 121 DF 3870 3870 3870 1280 1280 1280 309 309 309 132 132 132 74 74 74 27 27 27 χ2 / DF 6.5 5.5 4.0 4.9 4.8 3.7 6.0 4.1 4.0 4.4 4.0 4.1 5.6 3.8 2.5 4.1 4.4 4.5 p-value 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 RMSEA (< 0,06) 0.057 0.052 0.042 0.048 0.047 0.038 0.053 0.042 0.040 0.044 0.041 0.040 0.051 0.040 0.027 0.042 0.044 0.042 CFI (> 0,95) 0.967 0.979 0.995 0.980 0.984 0.996 0.977 0.989 0.996 0.991 0.993 0.997 0.988 0.993 0.999 0.993 0.995 0.997 TLI (> 0,95) 0.966 0.978 0.995 0.979 0.983 0.996 0.974 0.987 0.996 0.990 0.992 0.997 0.985 0.991 0.998 0.991 0.993 0.997 χ2 (DWLS) = Minimum Function Chi-square for Diagonally Weighted Least Squares DF degrees of freedom, RMSEA Root Mean Square Error of Approximation, CFI Comparative fit index, TLI Tucker-Lewis index In the 1997 study, the model fit of SCL-14 according to the χ2/DF ratio criterion was outside the acceptable limit (χ2/DF = 5,6). According to this criterion, poor model fit was also recorded in 1997 and 1999 with respect to SCL-90-R (χ2/DF = 6,5 in 1997; χ2 / DF = 5,5 in 1999), and with respect to SCL-27 (χ2 / DF = 5,6 in 1997). Satisfactory model fit based on all criteria (χ2/DF < 5; RMSEA < 0.06 and CFI, TLI > 0.95) and during all three time periods characterizes BSI-53, BSI-18, and SCL-K-9. Analysis of factor loadings on certain indicators of latent factors – symptomatic measures confirms satisfactory internal consistency (see Additional files 1, 2, 3, 4, 5 and 6 for details). The values of factor loadings in both the shortened and the full version of SCL-90-R exceeded 0.50, except for the indicator “nervousness” in the depression subscale in the SCL-90-R (1997 and 1999 studies). All factor loadings were statistically significant at the 1 % level. There were strong correlations among all latent factors (see Additional files 7, 8, 9, 10 and 11 for details). For example, in the 2014 factor model of SCL-90-R the minimum and maximum correlation of certain symptomatic dimensions is 0.74 (somatization and hostility) and 0.99 (interpersonal sensitivity and paranoid tendencies); in BSI-53 - 0.78 (somatization and hostility, somatization and paranoid tendencies) and 0.99 (interpersonal sensitivity and phobic anxiety); in the SCL-27 - 0.78 (autonomic dysfunction and suspicion) and 0.98 (agoraphobia and social phobia); in BSI-18 - 0.86 (somatization and depression) and 0.98 (depression and anxiety); in the SCL-14 - 0.71 (autonomic disorder and agoraphobia) and 0.87 (agoraphobia and depression). Equivalence of the full and shortened versions of the SCL-90-R Correlations between the full and shortened versions of the SCL-90-R are expectedly very high. Spearman’s Rho correlation coefficients vary in the range of 0.7-0.9 (Table 4). However, if we look at the difference in median values between similar components of SCL-90-R on the one hand, and BSI-53, SCL-27, BSI-18, SCL-14 and SCL-9-K on the other, it appears that in almost all cases, the difference in medians is statistically significant at the 5 % level. Equivalence of medians between full and shortened versions of the questionnaire in all three analyzed studies is observed only for the somatization subscale in the BSI-18. It is noticeable that similar subscales in different versions differ not so much in a measure of central tendency, but in variance. Such differences cause statistically significant differences in small effect sizes. Analysis of the size effects (the so-called “scientific significance”) shows that in all three studies the difference between symptomatic measures of SCL-90-R and BSI-53 is not significant (Vargha and Delaney’s A ≤ 0,56). When comparing SCL-90-R and SCL-27, there is a small effect size for somatization and interpersonal sensitivity (0.56 < k ≤ 0,64, in 1997, 1999 and 2014), whereas effect sizes on other symptomatic dimensions are insignificant. With regard to the comparison of SCL-90-R and such shortened versions as BSI-18, SCL-14, and SCL-9-R, in all three studies minor effect sizes were found, which indicates good equivalence.Table 4 Medians (M) and interquartile ranges (IQR) of the SCL-90-R and the shortened versions: BSI-53, SCL-27, BSI-18, SCL-14, SCL-K-9 and the results of the Wilcoxon signed-rank test (W (p-value)), Vargha and Delaney’s A effect sizes (ES) and Spearman’s correlations (S.Rho) in the general population of Ukraine 1997 1999 2014 SCL-90-R BSI-53 SCL-90-R BSI-53 SCL-90-R BSI-53 Scale M IQR Scale M IQR W (p-value) ES (VD.A) Rho Scale M IQR Scale M IQR W (p-value) ES (VD.A) Rho Scale M IQR Scale M IQR W (p-value) ES (VD.A) Rho SOMA 0.67 0.92 SOMA 0.57 1.00 0.008 0.56 0.95 SOMA 0.67 0.92 SOMA 0.57 1.00 0.013 0.55 0.95 SOMA 0.58 1.00 SOMA 0.43 1.00 0.002 0.56 0.95 OCD 0.40 0.60 OCD 0.33 0.83 <0.001 0.51 0.93 OCD 0.40 0.70 OCD 0.33 0.67 <0.001 0.52 0.93 OCD 0.40 0.80 OCD 0.33 1.00 <0.001 0.50 0.95 INT 0.44 0.67 INT 0.25 0.75 0.729 0.54 0.89 INT 0.44 0.67 INT 0.25 0.75 0.380 0.54 0.90 INT 0.33 0.67 INT 0.25 0.75 <0.001 0.53 0.91 DEPR 0.38 0.62 DEPR 0.33 0.67 <0.001 0.51 0.90 DEPR 0.46 0.69 DEPR 0.50 0.67 <0.001 0.50 0.91 DEPR 0.38 0.77 DEPR 0.33 0.83 <0.001 0.51 0.93 ANX 0.40 0.60 ANX 0.33 0.67 <0.001 0.51 0.93 ANX 0.40 0.60 ANX 0.33 0.50 <0.001 0.49 0.94 ANX 0.30 0.70 ANX 0.33 0.67 <0.001 0.50 0.95 HOST 0.33 0.50 HOST 0.40 0.60 <0.001 0.47 0.98 HOST 0.33 0.50 HOST 0.40 0.60 <0.001 0.47 0.99 HOST 0.33 0.67 HOST 0.40 0.80 <0.001 0.47 0.99 PHOB 0.14 0.29 PHOB 0.00 0.40 0.034 0.50 0.94 PHOB 0.14 0.29 PHOB 0.00 0.40 <0.001 0.49 0.97 PHOB 0.00 0.43 PHOB 0.00 0.40 <0.001 0.50 0.97 PARA 0.50 0.67 PARA 0.40 0.80 0.001 0.47 0.99 PARA 0.50 0.67 PARA 0.40 0.60 0.022 0.48 0.99 PARA 0.33 0.83 PARA 0.40 1.00 <0.001 0.48 0.99 PSYC 0.10 0.40 PSYC 0.00 0.40 <0.001 0.51 0.91 PSYC 0.10 0.40 PSYC 0.20 0.40 <0.001 0.50 0.92 PSYC 0.10 0.44 PSYC 0.00 0.40 <0.001 0.50 0.94 ADD 0.43 0.57 ADD 0.38 0.75 0.221 0.51 0.91 ADD 0.29 0.57 ADD 0.25 0.75 <0.001 0.51 0.92 ADD 0.43 0.71 ADD 0.25 0.75 0.088 0.52 0.92 GSI 0.41 0.53 GSI 0.41 0.55 <0.001 0.51 0.99 GSI 0.42 0.51 GSI 0.41 0.51 <0.001 0.50 0.99 GSI 0.35 0.60 GSI 0.35 0.61 <0.001 0.50 0.99 SCL-90-R SCL-27 SCL-90-R SCL-27 SCL-90-R SCL-27 SOMA 0.67 0.92 VEG 0.50 1.00 <0.001 0.60 0.89 SOMA 0.67 0.92 VEG 0.50 0.75 <0.001 0.61 0.89 SOMA 0.58 1.00 VEG 0.25 0.75 0.010 0.59 0.90 OCD 0.40 0.60 DYS 0.25 0.75 0.567 0.53 0.77 OCD 0.40 0.70 DYS 0.50 1.00 <0.001 0.52 0.80 OCD 0.40 0.80 DYS 0.50 1.00 <0.001 0.50 0.86 INT 0.44 0.67 SOP 0.50 0.83 <0.001 0.58 0.86 INT 0.44 0.67 SOP 0.33 0.83 <0.001 0.58 0.87 INT 0.33 0.67 SOP 0.33 1.00 0.010 0.57 0.88 DEPR 0.38 0.62 DEP 0.00 0.40 <0.001 0.50 0.81 DEPR 0.46 0.69 DEP 0.00 0.40 <0.001 0.50 0.83 DEPR 0.38 0.77 DEP 0.00 0.60 0.076 0.52 0.87 PHOB 0.14 0.29 AGO 0.25 0.75 0.001 0.51 0.84 PHOB 0.14 0.29 AGO 0.25 0.75 <0.001 0.50 0.84 PHOB 0.00 0.43 AGO 0.25 0.75 <0.001 0.48 0.85 PARA 0.50 0.67 MIS 0.50 1.00 <0.001 0.49 0.95 PARA 0.50 0.67 MIS 0.50 1.00 0.042 0.49 0.94 PARA 0.33 0.83 MIS 0.50 1.00 <0.001 0.49 0.96 GSI 0.41 0.53 GSI 0.41 0.56 <0.001 0.51 0.95 GSI 0.42 0.51 GSI 0.41 0.56 <0.001 0.51 0.96 GSI 0.35 0.60 GSI 0.35 0.63 <0.001 0.51 0.97 SCL-90-R BSI 18 SCL-90-R BSI 18 SCL-90-R BSI 18 SOMA 0.67 0.92 SOM 0.50 1.00 0.113 0.54 0.94 SOMA 0.67 0.92 SOM 0.50 1.00 0.190 0.54 0.94 SOMA 0.58 1.00 SOM 0.33 1.00 0.170 0.56 0.94 DEPR 0.38 0.62 DEP 0.33 0.67 <0.001 0.51 0.90 DEPR 0.46 0.69 DEP 0.50 0.67 <0.001 0.50 0.91 DEPR 0.38 0.77 DEP 0.33 0.83 <0.001 0.51 0.93 ANX 0.40 0.60 ANX 0.33 0.50 <0.001 0.51 0.93 ANX 0.40 0.60 ANX 0.33 0.50 <0.001 0.50 0.94 ANX 0.30 0.70 ANX 0.33 0.67 <0.001 0.50 0.95 GSI 0.41 0.53 GSI 0.50 0.67 <0.001 0.46 0.92 GSI 0.42 0.51 GSI 0.50 0.67 <0.001 0.49 0.93 GSI 0.35 0.60 GSI 0.39 0.72 <0.001 0.48 0.94 SCL-90-R SCL-14 SCL-90-R SCL-14 SCL-90-R SCL-14 SOMA 0.67 0.92 SOM 0.75 1.25 <0.001 0.52 0.89 SOMA 0.67 0.92 SOM 0.75 1.00 <0.001 0.51 0.90 SOMA 0.58 1.00 SOM 0.50 1.25 <0.001 0.53 0.91 DEPR 0.38 0.62 DEP 0.50 0.67 <0.001 0.48 0.88 DEPR 0.46 0.69 DEP 0.50 0.83 <0.001 0.47 0.90 DEPR 0.38 0.77 DEP 0.33 0.83 <0.001 0.49 0.91 PHOB 0.14 0.29 PHO 0.00 0.25 <0.001 0.57 0.81 PHOB 0.14 0.29 PHO 0.00 0.25 <0.001 0.57 0.83 PHOB 0.00 0.43 PHO 0.00 0.25 <0.001 0.54 0.88 GSI 0.41 0.53 GSI 0.43 0.64 <0.001 0.49 0.90 GSI 0.42 0.51 GSI 0.50 0.64 <0.001 0.47 0.90 GSI 0.35 0.60 GSI 0.36 0.64 <0.001 0.51 0.93 SCL-90-R SCL-K-9 SCL-90-R SCL-K-9 SCL-90-R SCL-K-9 GSI 0.41 0.53 GSI 0.56 0.89 <0.001 0.43 0.91 GSI 0.42 0.51 GSI 0.56 0.78 <0.001 0.41 0.91 GSI 0.35 0.60 GSI 0.50 0.78 <0.001 0.45 0.91 SOMA Somatization, OCD Obsessive-Compulsive Disorder, INT Interpersonal Sensitivity, DEPR Depression, ANX Anxiety, HOST Hostility, PHOB Phobic Anxiety, PARA Paranoid Ideation, PSYC Psychoticism, GSI Global Severity Index, DEP Depressive Symptoms, DYS Dysthymic Symptoms, VEG Vegetative Symptoms, AGO Agoraphobic Symptoms, SOP Symptoms of Social Phobia, MIS Symptoms of Mistrust When comparing full and shortened versions in the context of probable case prevalence according to Derogatis’ criterion (T-value for GSI ≥ 63), in 1997 and 1999 only SCL-9-K shows prevalence estimates that go beyond the 95 % confidence interval for the severe symptoms prevalence calculated by SCL-90-R (Fig. 1). In 2014, the variance of prevalence estimates in different versions of SCL-90-R is minimal.Fig. 1 Prevalence and 95 % confidence intervals of severe symptoms in Ukraine according to different criteria (T-score≥63 and GSI>1) According to the criterion of GSI > 1, the variance is greater: in 1997, 1999 and 2014 proportions of the population with severe symptoms based on BSI-18 and SCL-K-9 were significantly higher at the 5 % level than those based on SCL-90-R. In 1997, significantly higher proportions than in the full version of the SCL-90-R were also observed for SCL-14. Temporal stability If we consider reliability and validity of the five versions in terms of dynamics, there is acceptable consistency of scales and model fit of latent constructs in all three studies (1997, 1999, 2014). Unfortunately, the secondary analysis does not allow us to estimate sensitivity to changes, as analyzed datasets of different years were not drawn from a single cohort. Discussion Overall, our analysis supported the reliability and the original factor structure of the Ukrainian version of SCL-90-R and its five shortened versions, as well as the acceptable equivalency of selected measures. At the level of GSI analysis it is more profitable economically to use shortened versions, particularly SCL-K-9, which consists of nine points, and in whose favor are good reliability indicators, factor validity indicators and small effect sizes. For the analysis at the level of certain symptomatic dimensions, BSI-53 offers greater opportunities, where there are fewer questions than in the SCL-90-R, but there is the same 9-dimensional structure, satisfactory reliability and factorial validity. However, the 53-symptom questionnaire is quite cumbersome for annual monitoring surveys of the general population. According to the results of this paper, the best solution would be to use BSI-18, where the factorial structure of the three symptomatic measures is confirmed, satisfactory factor model fit is observed in all three studies (1997, 1999, and 2014), and there is a good internal consistency of the subscales. In SCL-27, the problematic aspect for Ukraine is the lack of satisfactory reliability of the depression scale. However, lower reliability indicators in certain symptomatic measurements may result from sensitivity of the Cronbach’s alpha criterion to the number of indicators within one symptomatic state [6, 37]. The scale of depressive symptoms in the SCL-27 is calculated on the basis of a small number of indicators (four symptoms). In the previous studies the lack of factor structure confirmation was a key target of criticism; in our opinion, such results could arise not so much because of the peculiarities of the country or of the analyzed groups, but because of the limitations in the sample size and the use of irrelevant methods, such as not accounting for ordinal scales of indicators in the SCL-90-R [23, 26–28]. Ukrainian study revealed that confirmatory factor analysis on 2014 data has confirmed the structure of symptomatic scales in both full and shortened versions of the SCL-90-R. However, in the 1997 and 1999 studies, which had a smaller sample size than the 2014 study, a number of models (SCL-90-R, SCL-27, and SCL-14) have shown unsatisfactory fit according to the χ-square criterion, although on other fit indices (RMSEA, CFI, TLI) satisfactory results have been obtained. Analysis of the equivalence of shortened and full versions of the SCL-90-R has shown the presence of small effect sizes, which is consistent with the results of validation in other countries [11, 22]. On the other hand, analysis of probable cases prevalence by different criteria (T-score > 63 or GSI > 1) indicates that SCL-K-9 shows higher prevalence of severe symptoms. However, the analysis of equivalence of the shortened versions and SCL-90-R for assessing the prevalence of distress requires further investigation, in particular clarification of the criteria for threshold values of probable cases in Ukraine as well as in certain population groups. Despite a generally positive assessment of the validation of SCL-90-R as well as its shortened versions in Ukraine, a number of limitations should be noted. Firstly, SCL-90-R wasn’t the main objective of the study in any of the three analyzed surveys. The symptomatic checklist was located at the end of the monitoring questionnaire, which included a wide range of issues. This could affect the completion of the questionnaire due to fatigue of the respondents. Secondly, the 1997/1999 and 2014 studies, although they are similar in design (all three are cross-sectional and representative of the population, and used the same method of data collection), they have differences in a number of procedural aspects: sample building, a set of cluster profiles, period of field stage, and being carried out by different organizations for different objectives. Thirdly, all the periods when SCL-90-R was used in Ukraine among the general population, were characterized as periods of severe social crisis. 1997 and 1999 were characterized by significant economic difficulties, and 2014 – by the political crisis and military conflict in the east of the country, which involved a number of challenges for the whole country. There is a lack of a comparable assessment conducted during a relatively prosperous period (for example, in the 2000s before the financial crisis) that would allow for evaluation of the sensitivity of the questionnaire to such changes. Fourthly, convergent and discriminant validity of the full and shortened versions in Ukraine remain questionable as none of the appropriate alternative screening tools were used simulteniously with the SCL-90-R. Among the strengths of our study is the fact that the results can be generalized to the entire population of Ukraine. The presence of three waves of the study at different times allowed us to check the temporal stability of the factor structure and reliability of the tool during different stages of social and economic development of the country. Another strong point of the study is the use of CFA with polychoric correlations, which allowed for improvement of the model fit. A certain advantage of the analysis is the use of non-parametric methods of analysis, in particular the description of data through the median and interquartile distance, using Spearman’s Rho correlations and Vargha and Delaney’s A effect sizes. The traditional approach to the analysis of certain symptomatic dimensions usually includes the calculation of averages, standard deviations, Pearson’s correlations and parametric effect sizes. Our study has shown that all symptomatic measurements have distributions which deviate from normal even in large samples, so the use of non-parametric methods for the validation SCL-90-R is more appropriate. Prospects for further validation of SCL-90-R studies in Ukraine suggest evaluation of the discriminant and convergent validity using alternative questionnaires measuring psychological distress, conducting cohort studies to determine the sensitivity of the questionnaire to social changes and studying the relevant thresholds for determining probable cases of psychological distress as well as its symptomatic dimensions. Conclusion This validation study of the full and shortened versions of the SCL-90-R has shown that SCL-K-9 might be an optimal solution for assessing general distress in national population monitoring studies in Ukraine. If it is necessary to analyze certain symptomatic dimensions of distress, using BSI-18 is recommended. Additional files Additional file 1: Confirmatory factor analysis of the SCL-90-R in the Ukrainian general population: factor loadings. Results of confirmatory factor analysis. Factor loadings for nine dimensions of the SCL-90-R in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 12 kb) Additional file 2: Confirmatory factor analysis of the BSI-53 in the Ukrainian general population: factor loadings. Results of confirmatory factor analysis. Factor loadings for nine dimensions of the BSI-53 in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 11 kb) Additional file 3: Confirmatory factor analysis of the SCL-27 in the Ukrainian general population: factor loadings. Results of confirmatory factor analysis. Factor loadings for six dimensions of the SCL-27 in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 10 kb) Additional file 4: Confirmatory factor analysis of the BSI-18 in the Ukrainian general population: factor loadings. Results of confirmatory factor analysis. Factor loadings for three dimensions of the BSI-18 in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 9 kb) Additional file 5: Confirmatory factor analysis of the SCL-14 in the Ukrainian general population: factor loadings. Results of confirmatory factor analysis. Factor loadings for three dimensions of the SCL-14 in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 9 kb) Additional file 6: Confirmatory factor analysis of the SCL-K-9 in the Ukrainian general population: factor loadings. Results of confirmatory factor analysis. Factor loadings for the SCL-K-9 in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 8 kb) Additional file 7: Confirmatory factor analysis of the SCL-90-R in the Ukrainian general population: correlations between latent factors. Results of confirmatory factor analysis. Correlations between the latent variables measured by SCL-90-R items in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 10 kb) Additional file 8: Confirmatory factor analysis of the BSI-53 in the Ukrainian general population: correlations between latent factors. Results of confirmatory factor analysis. Correlations between the latent variables measured by BSI-53 items in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 11 kb) Additional file 9: Confirmatory factor analysis of the SCL-27 in the Ukrainian general population: correlations between latent factors. Results of confirmatory factor analysis. Correlations between the latent variables measured by SCL-27 items in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 10 kb) Additional file 10: Confirmatory factor analysis of the BSI-18 in the Ukrainian general population: correlations between latent factors. Results of confirmatory factor analysis. Correlations between the latent variables measured by BSI-18 items in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 9 kb) Additional file 11: Confirmatory factor analysis of the SCL-14 in the Ukrainian general population: correlations between latent factors. Results of confirmatory factor analysis. Correlations between the latent variables measured by SCL-14 items in 1997, 1999 and 2014 studies that are representative of the Ukrainian population. (XLSX 9 kb) Acknowledgements We would like to thank Prof. Dr. Evgeniy Golovakha, Vice Director of Science of the Institute of Sociology, National Academy of Sciences in Ukraine, for his patient guidance, encouragement and advice. Completing this study would have been all the more difficult were it not for the support provided by Olga Balakireva, the Head of the Department for Monitoring of Social and Economic Transformations, Institute for Economics and Forecasting, National Academy of Sciences in Ukraine. We must express our gratitude to Dr. Evelyn J. Bromet, Distinguished Professor of the Department of Psychiatry and Behavioral Science, State University of New York at Stony Brook, who introduced Symptom Checklist-90 Revised within the framework of the Stony Brook–Kyiv Chernobyl Project, a collaboration between US investigators and independent scientists in Ukraine. This project contributed to the application of SCL-90-R in Ukrainian national surveys. Finally, we would like to thank Dr. Nataliia Panina (deceased) for her work on developing the Ukrainian version of SCL-90-R. Funding We gratefully acknowledge support from the National Institutes of Health [grant number D43 TW000233] funded by the Fogarty International Center and the National Academy of Sciences in Ukraine within the research project “Development and adaptation of data measurement tools for public sociological surveys in the transforming society” [grant number 0114U003415]. Availability of data and materials Datasets supporting our results can be found in the Institute of Sociology, National Academy of Sciences in Ukraine (1997 and 1999 studies) and in the Department for Monitoring of Social and Economic Transformations, Institute for Economy and Forecasting, National Academy of Sciences in Ukraine (2014 study). The datasets are in Ukrainian. According to the policy of both institutes, data is not deposited in publicly available repositories. However, it might be available under request. Authors’ contributions YS carried out the validation methodology, performed the statistical analysis, and helped to interpret the data and to draft the manuscript. SD participated in the design of the study and the literature review, analyzed the data and drafted the first version of the manuscript. Both authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate Independent ethics committee at the Sociological Association of Ukraine ruled that no formal ethics approval was required in this particular case because the study represents a secondary analysis of data that was completely anonymous when provided to the authors, and it was impossible to identify participants from any resulting reports. This complies with the Code of Professional Ethics of Sociologist adopted by the 5th Congress of the Sociological Association of Ukraine [38]. Informed consent to participate in the study was obtained from participants. ==== Refs References 1. Derogatis LR SCL-90-R: Administration, Scoring of Procedures Manual-II for the R (evised) Version and Other Instruments of the Psychopathology Rating Scale Series: Clinical Psychometric Research Incorporated 1992 2. Bromet EJ Goldgaber D Carlson G Panina N Golovakha E Gluzman SF Gilbert T Gluzman D Lyubsky S Schwartz JE Children’s well-being 11 years after the Chornobyl catastrophe Arch Gen Psychiatry 2000 57 6 563 71 10.1001/archpsyc.57.6.563 10839334 3. Derogatis LR Spencer P Brief symptom inventory: BSI 1993 Upper Saddle River Pearson 4. Hardt J Gerbershagen HU Cross‐validation of the SCL‐27: A short psychometric screening instrument for chronic pain patients Eur J Pain 2001 5 2 187 97 10.1053/eujp.2001.0231 11465984 5. Derogatis LR Brief symptom inventory 18 2000 Minneapolis NCS Pearson 6. Prinz U Nutzinger DO Schulz H Petermann F Braukhaus C Andreas S Comparative psychometric analyses of the SCL-90-R and its short versions in patients with affective disorders BMC Psychiatry 2013 13 104 10.1186/1471-244X-13-104 23537095 7. Harfst T Koch U Kurtz von Aschoff C, Nutzinger D, Rüddel H, Schulz H: Entwicklung und Validierung einer Kurzform der Symptom Checklist-90-R DRV-Schriften 2002 33 71 3 8. Klaghofer R Brähler E Konstruktion und Teststatistische Prüfung einer Kurzform der SCL-90–R 2001 9. Martinez-Azumendi O Fernandez-Gomez C Beitia-Fernandez M [Factorial variance of the SCL-90-R in a Spanish out-patient psychiatric sample] Actas Esp Psiquiatr 2001 29 2 95 102 11333527 10. Grande TL, Newmeyer MD, Underwood LA, Williams CR. Path Analysis of the SCL-90-R: Exploring Use in Outpatient Assessment. Measurement and Evaluation in Counseling and Development. 2014;47(4):271–90. 11. Paap MC Meijer RR Cohen-Kettenis PT Richter-Appelt H de Cuypere G Kreukels BP Pedersen G Karterud S Malt UF Haraldsen IR Why the factorial structure of the SCL-90-R is unstable: comparing patient groups with different levels of psychological distress using Mokken Scale Analysis Psychiatry Res 2012 200 2–3 819 26 10.1016/j.psychres.2012.03.012 22494703 12. Paap M Meijer RR Van Bebber J Pedersen G Karterud S Hellem FM Haraldsen IR A study of the dimensionality and measurement precision of the SCL‐90‐R using item response theory Int J Methods Psychiatr Res 2011 20 3 e39 55 21812065 13. Rauter UK Leonard CE Swett CP SCL-90-R factor structure in an acute, involuntary, adult psychiatric inpatient sample J Clin Psychol 1996 52 6 625 9 10.1002/(SICI)1097-4679(199611)52:6<625::AID-JCLP4>3.0.CO;2-J 8912105 14. Bonynge ER Unidimensionality of SCL-90-R scales in adult and adolescent crisis samples J Clin Psychol 1993 49 2 212 5 10.1002/1097-4679(199303)49:2<212::AID-JCLP2270490213>3.0.CO;2-V 8486803 15. Zack M Toneatto T Streiner DL The SCL-90 factor structure in comorbid substance abusers J Subst Abuse 1998 10 1 85 101 10.1016/S0899-3289(99)80143-6 9720009 16. Bech P Bille J Møller S Hellström L Østergaard SD Psychometric validation of the Hopkins Symptom Checklist (SCL-90) subscales for depression, anxiety, and interpersonal sensitivity J Affect Disord 2014 160 98 103 10.1016/j.jad.2013.12.005 24445132 17. Clark A Friedman MJ Factor structure and discriminant validity of the SCL-90 in a veteran psychiatric population J Pers Assess 1983 47 4 396 404 10.1207/s15327752jpa4704_10 6620108 18. Ransom D Ashton K Windover A Heinberg L Internal consistency and validity assessment of SCL-90-R for bariatric surgery candidates Surg Obes Relat Dis 2010 6 6 622 7 10.1016/j.soard.2010.02.039 20627709 19. Derogatis LR Rickels K Rock AF The SCL-90 and the MMPI: a step in the validation of a new self-report scale Br J Psychiatry 1976 128 280 9 10.1192/bjp.128.3.280 1252693 20. Fortin MF Coutu-Wakulczyk G Engelsmann F Contribution to the validation of the SCL-90-R in French-speaking women Health Care Women Int 1989 10 1 27 41 10.1080/07399338909515836 2925532 21. Olsen LR Mortensen EL Bech P The SCL‐90 and SCL‐90R versions validated by item response models in a Danish community sample Acta Psychiatr Scand 2004 110 3 225 9 10.1111/j.1600-0447.2004.00399.x 15283743 22. Holi MM Sammallahti PR Aalberg VA A Finnish validation study of the SCL-90 Acta Psychiatr Scand 1998 97 1 42 6 10.1111/j.1600-0447.1998.tb09961.x 9504702 23. Schmitz N Hartkamp N Kiuse J Franke GH Reister G Tress W The Symptom Check-List-90-R (SCL-90-R): a German validation study Qual Life Res 2000 9 2 185 93 10.1023/A:1008931926181 10983482 24. Urban R Kun B Farkas J Paksi B Kokonyei G Unoka Z Felvinczi K Olah A Demetrovics Z Bifactor structural model of symptom checklists: SCL-90-R and Brief Symptom Inventory (BSI) in a non-clinical community sample Psychiatry Res 2014 216 1 146 54 10.1016/j.psychres.2014.01.027 24524946 25. Tomioka M Shimura M Hidaka M Kubo C The reliability and validity of a Japanese version of symptom checklist 90 revised Bio Psycho Social Med 2008 2 1 1 8 26. Prunas A Sarno I Preti E Madeddu F Perugini M Psychometric properties of the Italian version of the SCL-90-R: a study on a large community sample Eur Psychiatry 2012 27 8 591 7 10.1016/j.eurpsy.2010.12.006 21334861 27. Vassend O Skrondal A The problem of structural indeterminacy in multidimensional symptom report instruments. The case of SCL-90-R Behav Res Ther 1999 37 7 685 701 10.1016/S0005-7967(98)00182-X 10402693 28. Wongpakaran T Wongpakaran N Boripuntakul T Symptom checklist-90 (SCL-90) in a Thai sample J Med Assoc Thai 2011 94 9 1141 9 21970206 29. Chapman LK Petrie J Vines L Factor structure analysis of the SCL-90-R in a community-based sample of African American women Psychiatry Res 2012 199 2 140 4 10.1016/j.psychres.2012.03.028 22633011 30. Müller JM Postert C Beyer T Furniss T Achtergarde S Comparison of eleven short versions of the Symptom Checklist 90-Revised (SCL-90-R) for use in the assessment of general psychopathology J Psychopathol Behav Assess 2009 32 2 246 54 10.1007/s10862-009-9141-5 31. Peterson RA. A meta-analysis of Cronbach’s coefficient alpha. J Consum Res. 1994;381–391. 32. Yu C-Y. Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes. University of California Los Angeles; 2002 33. Vargha A Delaney HD A critique and improvement of the CL common language effect size statistics of McGraw and Wong J Educ Behav Stat 2000 25 2 101 32 34. Cohen J. Statistical power analysis for the behavioral sciences. Routledge academic. Mahwah, NJ: Lawrence Erlbaum Associates; 2013. 35. Derogatis LR Fitzpatrick M The SCL-90-R, the Brief Symptom Inventory (BSI), and the BSI-18 2004 36. Olsen LR Mortensen EL Bech P Mental distress in the Danish general population Acta Psychiatr Scand 2006 113 6 477 84 10.1111/j.1600-0447.2005.00743.x 16677224 37. Eisen SV Dill DL Grob MC Reliability and validity of a brief patient-report instrument for psychiatric outcome evaluation Psychiatr Serv 1994 45 3 242 7 10.1176/ps.45.3.242 38. Panina N Professional Ethics and Sociology in Ukraine (On Adoption of the Code of Professional Ethics of Sociologist by the Sociological Association of Ukraine) 2007

PMC005xxxxxx/PMC5000450.txt

==== Front Cardiovasc DiabetolCardiovasc DiabetolCardiovascular Diabetology1475-2840BioMed Central London 41310.1186/s12933-016-0413-6Original InvestigationMetformin improves circulating endothelial cells and endothelial progenitor cells in type 1 diabetes: MERIT study Ahmed Fahad W. fahadwali@yahoo.com 12Rider Rachel rachel.rider@ghnt.nhs.uk 1Glanville Michael michael.glanville@newcastle.ac.uk 2Narayanan Kilimangalam kilimangalam.narayanan@ghnt.nhs.uk 1Razvi Salman salman.razvi@newcastle.ac.uk 13Weaver Jolanta U. +44 191 445 2181Jolanta.Weaver@newcastle.ac.uk 121 Department of Diabetes, Queen Elizabeth Hospital, Gateshead, UK 2 Institute of Cellular Medicine, Newcastle University, Framlington Place, Newcastle, NE2 4HH UK 3 Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK 26 8 2016 26 8 2016 2016 15 1 1163 4 2016 20 6 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Type 1 diabetes is associated with increased cardiovascular disease (CVD). Decreased endothelial progenitor cells (EPCs) number plays a pivotal role in reduced endothelial repair and development of CVD. We aimed to determine if cardioprotective effect of metformin is mediated by increasing circulating endothelial progenitor cells (cEPCs), pro-angiogenic cells (PACs) and decreasing circulating endothelial cells (cECs) count whilst maintaining unchanged glycemic control. Methods This study was an open label and parallel standard treatment study. Twenty-three type 1 diabetes patients without overt CVD were treated with metformin for 8 weeks (treatment group-TG). They were matched with nine type 1 diabetes patients on standard treatment (SG) and 23 age- and sex-matched healthy volunteers (HC). Insulin dose was adjusted to keep unchanged glycaemic control. cEPCs and cECs counts were determined by flow cytometry using surface markers CD45dimCD34+VEGFR-2+ and CD45dimCD133−CD34+CD144+ respectively. Peripheral blood mononuclear cells were cultured to assess changes in PACs number, function and colony forming units (CFU-Hill’s colonies). Results At baseline TG had lower cEPCs, PACs, CFU-Hills’ colonies and PACs adhesion versus HC (p < 0.001-all variables) and higher cECs versus HC (p = 0.03). Metformin improved cEPCs, PACs, CFU-Hill’s colonies number, cECs and PACs adhesion (p < 0.05-all variables) to levels seen in HC whilst HbA1c (one-way ANOVA p = 0.78) and glucose variability (average glucose, blood glucose standard deviation, mean amplitude of glycaemic excursion, continuous overall net glycaemic action and area under curve) remained unchanged. No changes were seen in any variables in SG. There was an inverse correlation between CFU-Hill’s colonies with cECs. Conclusions Metformin has potential cardio-protective effect through improving cEPCs, CFU-Hill’s colonies, cECs, PACs count and function independently of hypoglycaemic effect. This finding needs to be confirmed by long term cardiovascular outcome studies in type 1 diabetes. Trial registration ISRCTN26092132 Electronic supplementary material The online version of this article (doi:10.1186/s12933-016-0413-6) contains supplementary material, which is available to authorized users. http://dx.doi.org/10.13039/501100000273Diabetes Research &amp; Wellness FoundationOpen Funding 2012Weaver Jolanta U. Diabetes Research Fund in Gateshead0000Weaver Jolanta U. issue-copyright-statement© The Author(s) 2016 ==== Body Background Type 1 diabetes mellitus is characterised by an increased risk of cardiovascular disease (CVD) compared with the non-diabetic population [1, 2]. The life expectancy of adults at age of 20 with type 1 diabetes is reduced by up to 13 years with CVD being the leading cause of premature death [3]. Even with good glycaemic control the CVD risk remains more than twice that of non-diabetic individuals [4, 5]. Despite current use of statins and ACE-inhibitors, CVD risk in type 1 diabetes remains higher than non-diabetic population. Patients with type 1 diabetes mellitus without overt CVD or diabetes-related complications have been shown to have features of endothelial dysfunction [6]. There is a need to explore newer treatment options to improve endothelial dysfunction and reduce CVD risk. Endothelial dysfunction itself results from imbalance between vascular damage and vascular repair. Vascular damage results in the release of circulating endothelial cells (cECs) from the vascular intima. cECs are mature endothelial cells characterised by presence of endothelial cell surface markers like CD144 and absence of heamatopoetic (e.g. CD45) and progenitor cell markers (e.g. CD133). CD144 is important for maintaining endothelium integrity through cell to cell adhesion [7]. cECs are formed through detachment from vascular intima due to irreversible loss of integrity as a response to endothelial activation by mechanical stress, inflammatory cytokines, growth factors, infectious agents, lipoprotein, and oxidative stress [7, 8]. Furthermore, cECs are elevated in type 1 and type 2 diabetes [9, 10], and are a predictor of CVD events in similar high risk populations [11]. cECs count (a marker of vascular damage) is directly related to HbA1c in type 1 diabetes [9]. In response to vascular damage, vascular repair is promoted by local endothelial cells and bone-marrow derived cells, called endothelial progenitor cells (EPCs). EPCs were first described in 1997 [12]. These cells have the ability to home to the site of vascular injury, proliferate and contribute to endothelial repair [13], thereby maintaining endothelial health. Circulating endothelial progenitor cells (cEPCs) are a heterogenous population of cells characterised by the expression of surface antigen CD34+, VEGFR-2+ and/or CD133+ identified by flow cytometry. CD34+ and CD133+ are hematopoietic stem cell markers [14, 15]. VEGFR-2 is a surface marker of endothelial lineage. Progenitor cells undergo various stages of maturation. CD133 marker is lost as cEPCs mature. Thus, more mature cEPCs are positive for CD34 and VEGFR-2 [16]. VEGFR-2 plays an important role in angiogenesis by promoting endothelial cell growth and cell permeability [17]. cEPCs predict microvascular complication in type 2 diabetes [18] and future CVD events in patients with CVD [19]. In addition cEPCs count is inversely related to HbA1c [20]. Proangiogenic cells (PACs), previously known as early EPCs are the cultured peripheral blood mononuclear cells (PBMNC) whereas colonies derived from replated PBMNC are known as colony forming units (CFU-Hill’s colonies) [21]. PACs and CFU-Hill’s colonies are reduced in both type 1 and type 2 diabetes and CFU-Hill’s colonies have been shown to predict CVD events [20–24]. PAC count is inversely related to HbA1c and much more suppressed in the presence of diabetes-related complications [23–25]. In addition, the functional capacity of cultured PACs is impaired in patients with diabetes [23]. As the outcome of CVD management using the same therapies is worse in diabetic versus nondiabetic patients [26], there is a need to identify additional treatment options and study the mechanism of action behind the cardio-protective properties. Metformin has been shown to have cardio-protective properties in type 2 diabetes, [27, 28]. In the UKPD trial [27] the incidence of myocardial infarction was reduced after a median follow-up of 10 years. Furthermore, metformin also reduced cardiac infarct size and improved endothelial function in diabetes [29, 30]. It has been shown that metformin under diabetic environment protects ECs regardless of its glycaemic effects [31]. In nondiabetic patients however, there were mixed findings regarding metformin’s cardio-protective effect. Metformin had no effect on reducing left ventricular dysfunction and re-perfusion cardiac injury in non-diabetic patients following an acute myocardial infarction and coronary arterial bypass graft [32, 33]. Thus, the data are in keeping with a cardio-protective effect of metformin in diabetes, although the underlying mechanism is unclear. Since metformin has been shown to improve endothelial function in type 1 diabetes, we hypothesised that metformin modulates cEPCs and cECs count and this cardio-protective effect is mediated beyond improving glycaemic control. Thus the primary aim of our trial was to study if metformin improved cEPCs number in type 1 diabetes whilst, maintaining unchanged diabetic control. Secondary aims were to determine if metformin also improved cECs number, PACs number and function and CFU-Hill’s colonies. Methods We recruited 23 patients with type 1 diabetes with inclusion criteria of HbA1c <8.5 % (69 mmol/mmol), absence of macrovascular disease or stage 3b renal impairment (eGFR <45 ml/min/1.73 m2) or active proliferative retinopathy, as the ‘treatment group’ (TG). Nine matched type 1 diabetes patients were recruited as a standard group (SG). Both, TG and SG did not have any new intervention during the trial except for metformin in TG. Patients with suspected hypoglycemia unawareness were excluded. The study protocol (Fig. 1) included a run-in phase of 6 weeks to ensure stable glucose control. Following this period metformin was given for 8 weeks to TG with a dose titrated up to a maximum of 1 g twice a day over 2–3 weeks or to highest tolerated dose. The SG underwent similar follow-up except for metformin treatment. Furthermore, the TG was compared with 23 age- and gender-matched non-diabetic healthy controls (HC). All subjects gave their written informed consent and the Local Ethics Committee approved the study. Patients with type 1 diabetes were recruited either from, Queen Elizabeth Hospital, Gateshead or Royal Victoria Infirmary, Newcastle, UK. Healthy controls were recruited from the staff from the above or students from Newcastle University, UK.Fig. 1 Schematic diagram illustrating MERIT study design. CGM continuous glucose monitoring Routine laboratory investigations (full blood count, U&Es, liver function test, thyroid function test, and HbA1c), 12-lead ECG, blood pressure, weight, height and BMI were performed at baseline and at the end of the study. We aimed for unchanged glycaemic control during the study, which was assessed by HbA1c (four times points over 14 weeks) and continuous glucose monitoring (CGM) (Ipro2- Medtronic) (minimum of 48 h) was performed in those receiving metformin to ensure unchanged glycemic control. EasyGV Version 8.8.2. R2 was used to calculate glucose variability index [34]. Peripheral EDTA blood samples were collected before and after the study from TG and SG and at baseline from HC. Endothelial progenitor cells Flow cytometric evaluation of circulating endothelial progenitor cells (cEPCs) and circulating endothelial cells (cECs) 100 µl of whole blood [6] was incubated with 5 µl of V500 CD45 (B.D Bioscience), 20 µl of PerCP-Cy5.5 CD34 (BD Bioscience), 5 µl of PE VEGFR-2+ (R&D), 5 µl APC CD133 (Miltenyi Biotec USA), 10 µl of FITC CD144 for 30 min. Subsequently, 2 mls of pharmlyse (BD Bioscience) was used to lyse the red cells. The sample was then analysed by flow cytometry on BD FACS Canto™ II system and results by using BD FACSDiva™ software. On average 450,000 events were counted. cEPCs were defined as CD45dimCD34+VEGFR-2+ cells and cECs as CD45dim, CD133−, CD34+, and CD144+ events. cEPC count was expressed as % leukocytes (Intra-assay variation <8 %) and cECs as per ml of blood. In-vitro assays Methods for each of in vitro assay are described in details in Additional file 1. Assays described are: (1) enumeration of proangiogenic cells (PACs); (2) Colony forming units (CFU-Hills’ colonies; and (3) PAC function: fibronectin adhesion assay. Statistical analysis The results are expressed as mean ± SD unless stated otherwise. Within group (treatment or standard) comparison was evaluated by paired Student t test or Wilcoxon Signed Rank test depending on the distribution. Between-groups, comparison was by unpaired Student t test or the Mann–Whitney test. Correlation between different parameters were calculated by Pearson correlation or Spearman’s rho analysis. Multivariate regression analysis of delta changes in parameters were used to determine if independent metabolic variables predicted an improvement in cEPCs, PACs, CFU-Hill’s colonies, cECs and PACs function. One-way ANOVA was used to analyse the difference between HbA1c values. Adjustment for multiple comparisons was made by using the Bonferroni correction. Statistical significance was accepted at p < 0.05 (two-tailed significance). As the aim of the study was to assess the effect of metformin on cEPCs in type 1 diabetes, therefore, statistical power calculation was undertaken only for the TG. Based on our pilot work and in order to reduce CVD risk in patients with type 1 diabetes, we aimed to detect a difference of 0.0021 in cEPCs (% leukocytes) in the treatment group (before and after metformin treatment), with α = 0.05 and a power of 90 %, a minimum of 20 patients were required. SPSS v21.0 (SPSS Inc, Ill) was used to perform statistical analysis. Results Clinical characteristics Baseline characteristics of three groups are shown in Table 1. All groups were well matched for age, gender and blood pressure. TG and SG had a similar duration of diabetes (DOD), HbA1c, baseline insulin dose, lipid profile and creatinine. BMI was lower in SG in comparison to TG.Table 1 Subject’s clinical and metabolic characteristics TG (n = 23) p value TG V1 vs V2 HC (n = 23) p value HC vs TG V1 SG (n = 9) p value SG V1 vs V2 p value SG V1 vs TG V1 TG V1 TG V2 SG V1 SG V2 Age year 46 ± 13 – – 46 ± 12.6 1 47.4 ± 13.6 – – 0.8 Sex M/F n 11/12 – – 11/12 – 5/4 – – – DOD years 23 ± 13.6 – – – – 23.7 ± 14.1 – – 0.9 BMI kg/m2 28.7 (24-32) 29 (23-32)  >0.05 26.2 ± 4.7 0.1 23.8 (22–27) 23.7 (21.3–27.1) 0.3 <0.05 Systolic BP mmHg 125 ± 10.8 121 ± 14 0.2 119.4 ± 9 0.2 132.8 ± 6.2 130.8 ± 12.1 0.7 0.05 Diastolic BP mmHg 76.2 ± 9.2 74 ± 7 0.1 75.7 ± 9 0.9 77 ± 8.2 72.9 ± 3.6 0.4 0.8 HbA1c mmol/mol 56.9 ± 10.5 55.9 ± 8.5 0.5 34.8 ± 2.9 <0.0001 58.6 ± 7.4 59 ± 9 0.7 0.6 HbA1c  % 7.3 ± 0.9 7.3 ± 0.8 0.6 5.3 ± 0.3 <0.0001 7.5 ± 0.70 7.5 ± 0.8 0.6 Insulin dose units 44 (20–69) 39 (18–66) <0.001 – – 52.3 ± 11 52.9 ± 11 0.5 0.4 Smoking y/e/n 4/2/17 – – 0/0/23 2/1/6 – – – Total cholesterol mmol/l 4.5 ± 0.8 4.4 ± 1 0.2 4.96 ± 0.8 0.1 4.8 ± 1.3 4.9 ± 1.4 0.8 0.7 Triglyceride mmol/l 0.9 ± 0.4 0.9 ± 0.4 0.9 1.5 ± 0.9 0.008 0.7 ± 0.32 0.7 ± 0.3 0.6 0.2 HDL-cholesterol mmol/l 1.8 ± 0.5 1.6 ± 0.4 <0.05 1.6 ± 0.4 0.1 1.9 ± 0.6 2.1 ± 0.6 0.4 0.5 Creatinine umol/l 73 (68–94) 70 (63–77) 0.01 78 (70–87) 0.3 75 (65–87) 77 (62.8–83.5) 0.7 0.7 WCC 6.4 ± 2.4 6.3 ± 2 0.7 6.3 ± 1.6 0.9 5.8 ± 1.5 5.6 ± 1.7 0.9 0.5 Values are given as mean ± SD or * median [Interquartile range (IQ)] kg kilogram, BMI body mass index, BP blood pressure, M male, F female, DOD duration of diabetes, Y yes, E ex-smoker, N no, TG V1 Pre-treatment, TG V2 Post treatment, SG V1 Pre-observation, SG V2 Post observation, WCC White cell count In TG, at recruitment twelve patients took aspirin and/or ACE inhibitor and/or statins in addition to insulin. No new medication other than metformin was started during the trial (except for metformin in the TG). No medication dosage was changed other than the dose of insulin and metformin. HC took no aspirin, ACE inhibitors and/or statins. Five patients in the SG took aspirin or/and ACE inhibitor and/or statins in addition to insulin. There was no difference in medication between TG and SG. After treatment with metformin, BMI, total cholesterol, triglyceride, blood pressure and HbA1c remained unchanged. Over 14 weeks HbA1c values were as follows −6 week (56.4 ± 8.3 mmol/mol, 7.3 ± 3 %), 0 week (56.85 ± 10.5 mmol/mol, 7.3 ± 0.9 %), +6 week (56.8 ± 8.5 mmol/mol, 7.3 ± 0.8 %) and +8 week (56 ± 0.8 mmol/mol, 7.3 ± 0.8 %); one-way ANOVA, p = 0.78). The coefficient of variation of HbA1c over 14 weeks was 4.8 %. Furthermore, continuous glucose monitoring confirmed unchanged glucose control and variability (Average glucose CGM mmol/l: 9 ± 3 vs 8 ± 2.3, p = 0.17; blood glucose standard deviation: 3.3 ± 1.1 vs 3 ± 1.2, p = 0.3; mean amplitude of glycaemic excursion; 7 ± 2.7 vs 6 ± 3, p = 0.3; continuous overall net glycaemic action: 7.7 ± 2 vs 7.3 ± 2.2, p = 0.4; Total area under curve (AUC) (calculated): 12341 ± 2900 vs 11500 ± 3182, p = 0.3; AUC above limit-7.8 (CGM): 1.86 vs 1.97, p = 0.7. Insulin dose, HDL cholesterol and creatinine were significantly reduced in the TG treatment group after metformin treatment. There were no changes in any variables in SG. Side effects None of the volunteers in the study suffered any side effects requiring discontinuation of metformin. Fifteen patients took the full recommended dose of metformin (1000 mg BD). One patient took 500 mg BD due to low low eGFR (46 ml/min/1.73 m2). Five patients had gastrointestinal side effects that required dose reduction (two patients took 500 mg TDS; two took 500 mg BD, and one took 500 mg OD). No patient suffered any major or severe episode of hypoglycaemia. Major episode of hypoglycaemia was defined as any episode of low blood sugar requiring intervention of another person to resolve the event. Severe hypoglycaemia was defined as any episode of hypoglycaemia resulting in loss of consciousness. There was no significant effect of metformin on minor hypoglycaemic events (% ≤3.9 mmol/l and area under curve 3.9 mmol/l on CGMS: 8.6 % vs 13.3 %; p = 0.2 and 0.08 vs 0.1; p = 0.5 respectively). Study biomarkers Figure 2 provides a comparison of cEPCs while Table 2 provides a comparison of cECs, PACs, CFU-Hill’s colonies and PACs adhesion function between the TG, SG and HC.Fig. 2 Circulating endothelial progenitor cells CD45dimCD34+ VEGFR-2+. Results given as per 100 leukocytes. TG V1 treatment group pre-metformin, TG V2 treatment group post-metformin, SG V1 standard group pre observation, SG V2 standard group post 8 weeks observation. Line denotes in each box as median and + in each box denotes mean value Table 2 Indices of vascular health measured bef ore and after metformin therapy Treatment group (TG) p value TG V1 vs V2 Healthy controls p value TG V1 vs HC p value TG V2 vs HC Standard group (SG) p value SG V1 vs V2 p value TG V1 vs SG V1 V1 (Pre metformin) V2 (Post metformin) HC V1 V2 PACs per hpf 16.6 ± 8.9 28.4 ± 12.8 <0.0005* 40.3 ± 20.2 <0.0005* 0.07* 17.6 ± 12 15 ± 11 0.6 0.8 FAA per hpf 26.9 ± 21 61 ± 42 <0.0005* 67 ± 29 <0.0005* 0.15 35.9 ± 15 37 ± 16 0.9 0.1 Hill colonies per well 8.3 ± 6.8 13.8 ± 9 <0.0005* 20.57 <0.0005* 0.1* 10.4 ± 6.6 11 ± 6.2 0.8 0.5 (CECs) CD45dimCD34+CD133−CD144+ per ml^ 74.4 (46.4–221) 47.6 (21.8–76.7) <0.05* 42.6 (12.7–66) 0.03* 0.7 99.8 (59.4–210.5) 119.5 (80.5–527.5) 0.5 0.7 Values given as mean ± SD or ^ median (Interquartile range) PACs proangiogenic cells, FAA fibronectin adhesion assay- Adhesion of PACs, cECs circulating endothelial cells, combination of CD45dimCD34+CD133− and CD144+, TG V1 pre-treatment, TG V2 post treatment, SG V1 pre-observation, SG V2 post observation * Results after Bonferroni correction Circulating endothelial progenitor cells cEPCs count was similar in TG and the SG at baseline (p = 0.4). cEPCs (CD45dimCD34+VEGFR-2+) were significantly lower (60 %) in TG versus HC [Treatment group pre-metformin (TG V1 vs HC); median intraquartile range (IQ): 0.0028 (0.0016–0.006) vs 0.0068 (0.006–0.009)  % leukocytes; p < 0.0005)]. Eight weeks metformin treatment significantly increased cEPCs in TG by more than 75 % and normalised the levels of cEPCs count when compared to HC [TG V1 vs TG V2 (Treatment group post metformin); median (IQ): 0.0028 (0.0016–0.006) vs 0.005 (0.0035–0.0085) % leukocytes; p = 0.002]. In SG 8 weeks of standard follow-up did not result in any change in cEPCs count [SG V1 vs SG V2: median (IQ): 0.0032 (0.002–0.004) vs 0.0035 (0.003–0.005)  % leukocytes; p = 0.6]. Figure 3 provides before and after treatment plots for cEPC in TG.Fig. 3 Twenty-three plots representing cEPC pre and post metformin treatment in treatment group Circulating endothelial cells cECs number was similar in TG and SG at baseline. However, cECs were significantly higher (74 %) in TG versus HC. Metformin treatment led to a significantly reduction of cECs (36 %) in TG. Furthermore, metformin treatment normalised cECs numbers versus HC. cECs numbers did not change after eight-week follow-up in the SG. Culture Assay for PACs and CFU-Hill’s colonies PACs and CFU-Hill’s colonies numbers were similar in TG and the SG at baseline. PACs and CFU-Hill’s colonies counts were significantly lower (59 and 60 % respectively) in TG compared with HC. Eight weeks metformin treatment significantly increased PACs and CFU-Hill’s colonies in TG by 71 and 66 % respectively. Metformin treatment seemed to bring PACs and CFU-Hill’s colonies count closer to HC levels. After 8 weeks of follow-up in SG, the PACs and CFU-Hill’s colonies numbers remained unchanged. PACs adhesion to fibronectin The adhesion of PACs was similar in TG and SG at baseline. The adhesion of PACs in TG was 60 % lower when compared to HC. Metformin led to a significant increase (127 %), in PACs adhesion in TG and to the level seen in HC. The PACs number remained unchanged after eight weeks of follow-up in SG. Correlation Univariate analysis in TG In univariate analysis in TG, there was no correlation between changes in HbA1c, BMI, insulin dosage, total cholesterol, HDL cholesterol, LDL cholesterol, cEPCs, PACs, CFU-Hill’s colonies levels and PACs adhesion. There was an inverse correlation between changes in CFU-Hill’s colonies and cECs number (r = −0.6; p = 0.003) in TG. There was an inverse correlation between changes in PACs number and triglycerides (r = −0.6; p = 0.001) in TG. Multivariate regression in TG In multivariate regression analysis none of independent variables (changes in HbA1c, BMI, insulin dosage, LDL cholesterol) predicted changes in cEPCs, PACs number and function, CFU-Hill’s colonies and cECs. Univariate and multivariate regression analysis are given in Additional file 1: Tables S1 and S2 respectively. Discussion In this study, we have demonstrated for the first time that in patients with relatively well controlled type 1 diabetes mellitus (mean HbA1c 7.3 or 56.4 mmol/mol), metformin therapy improved markers of vascular damage (cECs) and repair (cEPCs). We believe that this study may have positive clinical implication for patients with increased CVD risk by rebalancing the emphasis in their management from limiting damage alone to also improving vascular repair. Further evidence that our patients might benefit from metformin comes from the fact that CFU-Hill’s colonies, PACs number and adhesion properties improved significantly. It is well established that CFU-Hill's colonies number are inversely related to Framingham risk score. Therefore, CFU-Hill’s colonies are yet another predictor of CVD [21]. In addition, PACs adhesion function is an important factor in cEPCs homing, cell-cell contact and transmigration events for neovascularisation and vascular repair [35]. Metformin not only improved the level of cEPCs but also brought PACs number/adhesion and CFU-Hill’s colonies closer to the HC levels. In addition, for the first time we have shown that in TG there was an inverse correlation between changes in cECs and CFU-Hills’ colonies. This shows that changes in markers of vascular/endothelial damage are linked inversely with a marker of CVD risk (CFU-Hill’s colonies). The additional benefit suggested by our study for patients with type 1 diabetes is that the vascular health/repair may be improved in already well-controlled patients and without a need for further improvement in glycaemic control. Patients with type 1 diabetes are currently advised to achieve HbA1c <7 % or <54 mmol/mol in order to reduce CVD events. However, this is associated with inherent risk of experiencing hypoglycaemia. The recent work by the EURODIAB Prospective Complications Study has demonstrated a U shaped association between all-cause mortality and HbA1c. That is, all-cause mortality is highest at low (5.6 %; 37.7 mmol/l) and high (11.8 %; 105.5 mmol/mol) HbA1c [36]. Thus, an additional advantage of using metformin in type 1 diabetes suggested by our study is that markers of vascular health and repair may be improved without lowering blood glucose concentrations to a tightly control HbA1c level. Metformin has been shown to improve cEPCs in type 2 diabetes [37]. However, there was a significant improvement in HbA1c. Thus, the change in cEPCs number could have been attributed to improved diabetic control. We have shown that the effect of metformin on all vascular biomarkers studied was beyond improving diabetic control. Indeed, HbA1c and glycaemic variability remained unchanged after 8 weeks of therapy. The glucose independent mechanism behind the metformin cardio-protective effect is of particular interest as this drug has some beneficial cardiac properties in non-diabetic animals [38]. When used in non-diabetic animals, metformin improved the outcome and revascularization following surgically induced myocardial infarction and hindlimb ischemia [38, 39]. Insulin dosage was reduced significantly, but it was not correlated with changes in cEPCs number or PACs adhesion. This is interesting, as insulin has been shown to improve cEPCs number [40, 41] and function in type 2 diabetes [42, 43]. However, the improvement in cEPCs number in Fadini et al. [41] could be attributed to improvement in HbA1c. This is in contrast with Humpert et al. [40], who showed that effect of insulin on the cEPCs number is independent of HbA1c. If the former was likely, given the reduction in insulin dosage in our study, cEPCs, PACs and CFU-Hill’s colonies number and PACs adhesion should have decreased, but this is not the case. This suggests that the insulin dose reduction did not have any effect on improving cEPCs or PACs function. Reduction in insulin dose had no effect on any variable including cEPCs in univariate or multivariate analysis. cECs are recognised markers of vascular damage. Our study showed that metformin therapy improved the cECs count in type 1 diabetes and brought it closer to the matched HC. Even though cECs improved significantly, we believe that our study did not show the full effect of metformin on cECs, as some of our patients were using cardio-protective drugs already: statins and ACE inhibitors. Indeed, in TG subjects on ACE inhibitors and or statins less reduction of cECs was observed. Eight weeks of metformin treatment did not result in any significant change or BMI. This is in contrast with a recent study which showed that 6 months of metformin in people with type 1 diabetes resulted in the loss of nearly 2.5 kg weight when compared to placebo [30]. However, we requested that patient would not aim to improve their diabetic control whilst in the study, so it is possible explanation for the lack of weight loss. Surprisingly, HDL cholesterol levels were reduced after metformin therapy, though, were similar to the control group and remained well within the normal range. However, there was no correlation between changes in cEPCs with BMI nor HDL cholesterol in univariate analysis. Thus, in our study it seems that BMI and HDL cholesterol are not responsible for metformin’s effect on the cEPCs number. This is in contrast with available evidence where HDL cholesterol has been shown to play a role in number EPCs and ischemia induced endothelial repair [44–46]. Furthermore, the multivariate analysis also showed that change in BMI was not a predictor of cEPCs either. Our work can be supplemented further by understanding the mechanism through which metformin improves cEPC and cECs numbers. It is established that EPC differentiation and mobilization is impaired in diabetes mellitus patients [47]. Hyperglycaemia induces endothelial cell death via suppression of SIRT1. In-vitro work has shown metformin’s effect on improved cell survival (at physiological levels) although in mouse cells in high glucose levels (40 mM) by reducing premature senescence and apoptosis via increased SIRT expression/activity [48]. Metformin has been shown to promote SIRT 1 activity via AMPK pathway. This reduced the oxidative stress caused by hyperglycaemia in a dose-dependent manner [49]. Thus, we speculate that observed effect of metformin on cEPCs in our study may be due to improved cell survival, decreased senescence and/or increased recruitment from the bone marrow. Other beneficial effects of metformin have been achieved, although at very high unphysiological metformin levels only, such as activation of AMPK-mTOR and AMPK-eNOS-NO pathway [50]. EPC mobilisation can be increased via activation of eNOS pathway in diabetes mellitus [51]. Thereby, we can infer that activation of eNOS pathway can increase EPC mobilisation. However, this speculative and needs confirmation using metformin at physiological concentration. For that purpose, we have constructed an angiogenic model to study the mechanism of metformin at physiological concentration. In this experiment, metformin improved angiogenesis through increased angiogenic signal. It not only increased VEGF-A levels but also downregulated angiogenic inhibitors; CXCL-10 and TIMP-1 [52]. Our work can be meaningfully extended by addressing the limitations of our study. Although, there was a small number of patients in this study it was adequately powered. Our type 1 diabetes cohort was heterogeneous with a wide range of diabetes duration and age. This may seem to be a limitation but can also be seen as an advantage to improve generalisability of the results of our study. CGMS was done at the beginning and middle of the study and not at the end of the study. However, CGMS in the middle of the treatment phase was done at the maximum dose of tolerated metformin. Therefore, it is representative of metformin effect on blood glucose levels. We did not use randomised design nor long intervention (8 weeks only). As this research was designed as a proof of concept study exploring the effect of metformin on cEPCs and cECs, data generated from our work can be used to design randomised trials of longer duration in order to repurpose this widely used type 2 diabetes drug, for patients with type 1 diabetes [53]. Our work can be supplemented by exploring the effect of metformin treatment on endothelial function, inflammatory and adhesion markers. Conclusions In summary, our study has shown for the first time that metformin treatment may result in cardiovascular benefit by increasing markers of vascular repair or health (cEPCs, CFU-Hill's colonies, and PACs) and reducing markers of vascular damage (cECs). In a pivotal study by Werner et al. [19], higher levels of cEPCs lead to reduced CVD events. It appears that a 75 % rise in cEPCs number in type 1 diabetes patients as seen in our study might equate to the reclassification of our patients into a lower CVD risk group with approximate Hazard Ratio for CVD death of 0.77 thus 23 % reduction [19]. However, this needs to be confirmed by large randomised controlled trial examining cardiovascular events. Additional file 10.1186/s12933-016-0413-6 Correlation matrix of associations between the changes in cEPCs, PACs, PAC adhesion, CFU-Hill colonies and CECs in treatment group. Table S2. The univariate and multivariate relationship between changes in cEPC, PACs, CFU-Hill Colonies, CECs and PAC adhesion to changes in other metabolic markers. Authors’ contributions FWA recruitment and follow up of patients, laboratory experiments, acquisition of data, analysis and interpretation of the data and drafting of manuscript. RR follow up of patients and advising patients on adjusting insulin therapy. MG support in laboratory experiment. SR recruitment of patients and drafting of manuscript. KN recruitment of patients and drafting of manuscript. JUW conception and design of the study, securing the funding, recruitment of patients, laboratory experiments, acquisition of data, analysis and interpretation of the data and drafting of manuscript. JUW is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors read and approved the final manuscript. Acknowledgements We thank Professor I Spyridopoulos for helpful discussions at the conception of the study, Medtronic Diabetes UK for providing Ipro2 for continuous glucose monitoring. We thank Clinical Research Facility and its staff in Royal Victoria Infirmary, Newcastle for use of the facility. Competing interests The authors declare that they have no competing interests. Ethics approval NRES Committee North East—Sunderland: REC reference number: 12/NE/0044. Funding Diabetes Research and Wellness Foundation and Diabetes Research Fund in Gateshead. ==== Refs References 1. Soedamah-Muthu SS Fuller JH Mulnier HE Raleigh VS Lawrenson RA Colhoun HM High risk of cardiovascular disease in patients with type 1 diabetes in the U.K.: a cohort study using the general practice research database Diabetes Care 2006 29 798 804 10.2337/diacare.29.04.06.dc05-1433 16567818 2. Livingstone SJ Looker HC Hothersall EJ Wild SH Lindsay RS Chalmers J Cleland S Leese GP McKnight J Morris AD Risk of cardiovascular disease and total mortality in adults with type 1 diabetes: Scottish registry linkage study PLoS Med 2012 9 e1001321 10.1371/journal.pmed.1001321 23055834 3. Livingstone SJ Levin D Looker HC Lindsay RS Wild SH Joss N Leese G Leslie P McCrimmon RJ Metcalfe W Estimated life expectancy in a Scottish cohort with type 1 diabetes, 2008–2010 JAMA 2015 313 37 44 10.1001/jama.2014.16425 25562264 4. Snell-Bergeon JK Maahs DM Diabetes: Elevated risk of mortality in type 1 diabetes mellitus Nat Rev Endocrinol 2015 11 136 138 10.1038/nrendo.2014.245 25583696 5. Lind M Svensson A-M Kosiborod M Gudbjörnsdottir S Pivodic A Wedel H Dahlqvist S Clements M Rosengren A Glycemic control and excess mortality in type 1 diabetes New Engl J Med 2014 371 1972 1982 10.1056/NEJMoa1408214 25409370 6. Sibal L Aldibbiat A Agarwal SC Mitchell G Oates C Razvi S Weaver JU Shaw JA Home PD Circulating endothelial progenitor cells, endothelial function, carotid intima-media thickness and circulating markers of endothelial dysfunction in people with type 1 diabetes without macrovascular disease or microalbuminuria Diabetologia 2009 52 1464 1473 10.1007/s00125-009-1401-0 19484217 7. Goon PK Lip GY Boos CJ Stonelake PS Blann AD Circulating endothelial cells, endothelial progenitor cells, and endothelial microparticles in cancer Neoplasia 2006 8 79 88 10.1593/neo.05592 16611400 8. Burger D Touyz RM Cellular biomarkers of endothelial health: microparticles, endothelial progenitor cells, and circulating endothelial cells J Am Soc Hypertens 2012 6 85 99 10.1016/j.jash.2011.11.003 22321962 9. Asicioglu E Gogas Yavuz D, Koc M, Ozben B, Yazici D, Deyneli O, Akalin S: Circulating endothelial cells are elevated in patients with type 1 diabetes mellitus Eur J Endocrinol 2010 162 711 717 10.1530/EJE-09-0795 20061332 10. McClung JA Naseer N Saleem M Rossi GP Weiss MB Abraham NG Kappas A Circulating endothelial cells are elevated in patients with type 2 diabetes mellitus independently of HbA(1)c Diabetologia 2005 48 345 350 10.1007/s00125-004-1647-5 15660261 11. Koc M Richards HB Bihorac A Ross EA Schold JD Segal MS Circulating endothelial cells are associated with future vascular events in hemodialysis patients Kidney Int 2005 67 1078 1083 10.1111/j.1523-1755.2005.00173.x 15698448 12. Asahara T Murohara T Sullivan A Silver M van der Zee R Li T Witzenbichler B Schatteman G Isner JM Isolation of putative progenitor endothelial cells for angiogenesis Science 1997 275 964 967 10.1126/science.275.5302.964 9020076 13. Urbich C Dimmeler S Endothelial progenitor cells functional characterization Trends Cardiovasc Med 2004 14 318 322 10.1016/j.tcm.2004.10.001 15596109 14. Timmermans F Plum J Yöder MC Ingram DA Vandekerckhove B Case J Endothelial progenitor cells: identity defined? J Cell Mol Med 2009 13 87 102 10.1111/j.1582-4934.2008.00598.x 19067770 15. Yoder MC. Human endothelial progenitor cells. In: Cold Spring Harb Perspect Med, vol. 2; 2012. 16. Hristov M Erl W Weber PC Endothelial progenitor cells: mobilization, differentiation, and homing Arterioscler Thromb Vasc Biol 2003 23 1185 1189 10.1161/01.ATV.0000073832.49290.B5 12714439 17. Collet G Lamerant-Fayel N Tertil M El Hafny-Rahbi B Stepniewski J Guichard A Foucault-Collet A Klimkiewicz K Petoud S Matejuk A Hypoxia-regulated overexpression of soluble VEGFR2 controls angiogenesis and inhibits tumor growth Mol Cancer Ther 2014 13 165 178 10.1158/1535-7163.MCT-13-0637 24170768 18. Rigato M Bittante C Albiero M Avogaro A Fadini GP Circulating progenitor cell count predicts microvascular outcomes in type 2 diabetic patients J Clin Endocrinol Metab 2015 100 2666 2672 10.1210/jc.2015-1687 25942480 19. Werner N Kosiol S Schiegl T Ahlers P Walenta K Link A Bohm M Nickenig G Circulating endothelial progenitor cells and cardiovascular outcomes N Engl J Med 2005 353 999 1007 10.1056/NEJMoa043814 16148285 20. Hörtenhuber T Rami-Mehar B Satler M Nagl K Höbaus C Höllerl F Koppensteiner R Schernthaner G Schober E Schernthaner G-H Endothelial progenitor cells are related to glycemic control in children with type 1 diabetes over time Diabetes Care 2013 36 1647 1653 10.2337/dc12-1206 23340890 21. Hill JM Zalos G Halcox JP Schenke WH Waclawiw MA Quyyumi AA Finkel T Circulating endothelial progenitor cells, vascular function, and cardiovascular risk N Engl J Med 2003 348 593 600 10.1056/NEJMoa022287 12584367 22. Tepper OM Galiano RD Capla JM Kalka C Gagne PJ Jacobowitz GR Levine JP Gurtner GC Human endothelial progenitor cells from type II diabetics exhibit impaired proliferation, adhesion, and incorporation into vascular structures Circulation 2002 106 2781 2786 10.1161/01.CIR.0000039526.42991.93 12451003 23. Loomans CJ de Koning EJ Staal FJ Rookmaaker MB Verseyden C de Boer HC Verhaar MC Braam B Rabelink TJ van Zonneveld AJ Endothelial progenitor cell dysfunction: a novel concept in the pathogenesis of vascular complications of type 1 diabetes Diabetes 2004 53 195 199 10.2337/diabetes.53.1.195 14693715 24. Fadini GP Miorin M Facco M Bonamico S Baesso I Grego F Menegolo M de Kreutzenberg SV Tiengo A Agostini C Avogaro A Circulating endothelial progenitor cells are reduced in peripheral vascular complications of type 2 diabetes mellitus J Am Coll Cardiol 2005 45 1449 1457 10.1016/j.jacc.2004.11.067 15862417 25. Dessapt C Karalliedde J Hernandez-Fuentes M Prieto PM Maltese G Dattani N Atkar R Viberti G Gnudi L Circulating vascular progenitor cells in patients with type 1 diabetes and microalbuminuria Diabetes Care 2010 33 875 877 10.2337/dc09-1468 20067966 26. Nauta ST Deckers JW Akkerhuis KM van Domburg RT Short- and long-term mortality after myocardial infarction in patients with and without diabetes: changes from 1985 to 2008 Diabetes Care 2012 35 2043 2047 10.2337/dc11-2462 22815296 27. Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998; 352:854–865. 28. Fung CS Wan EY Wong CK Jiao F Chan AK Effect of metformin monotherapy on cardiovascular diseases and mortality: a retrospective cohort study on Chinese type 2 diabetes mellitus patients Cardiovasc Diabetol 2015 14 137 10.1186/s12933-015-0304-2 26453464 29. Lexis CH Wieringa W Hiemstra B van Deursen V Lipsic E van der Harst P van Veldhuisen D van der Horst IC Chronic metformin treatment is associated with reduced myocardial infarct size in diabetic patients with st-segment elevation myocardial infarction Cardiovasc Drugs Ther 2014 28 163 171 10.1007/s10557-013-6504-7 24292206 30. Pitocco D Zaccardi F Tarzia P Milo M Scavone G Rizzo P Pagliaccia F Nerla R Di Franco A Manto A Metformin improves endothelial function in type 1 diabetic subjects: a pilot, placebo-controlled randomized study Diabetes Obes Metab 2013 15 427 431 10.1111/dom.12041 23167274 31. Eriksson L Nyström T Activation of AMP-activated protein kinase by metformin protects human coronary artery endothelial cells against diabetic lipoapoptosis Cardiovasc Diabetol 2014 13 152 10.1186/s12933-014-0152-5 25391818 32. Lexis CH van der Horst IC Lipsic E Effect of metformin on left ventricular function after acute myocardial infarction in patients without diabetes: the gips-iii randomized clinical trial JAMA 2014 311 1526 1535 10.1001/jama.2014.3315 24687169 33. Elmessaoudi S Nederlof R Zuurbier CJ van Swieten HA Pickkers P Noyez L Dieker HJ Coenen MJ Donders ART Vos A Effect of metformin pretreatment on myocardial injury during coronary artery bypass surgery in patients without diabetes (MetCAB): a double-blind, randomised controlled trial Lancet Diabetes Endocrinol 2014 3 615 623 10.1016/S2213-8587(15)00121-7 34. Hill NR Oliver NS Choudhary P Levy JC Hindmarsh P Matthews DR Normal reference range for mean tissue glucose and glycemic variability derived from continuous glucose monitoring for subjects without diabetes in different ethnic groups Diabetes Technol Ther 2011 13 921 928 10.1089/dia.2010.0247 21714681 35. Urbich C Dimmeler S Endothelial progenitor cells: characterization and role in vascular biology Circ Res 2004 95 343 353 10.1161/01.RES.0000137877.89448.78 15321944 36. Schoenaker DAJM Simon D Chaturvedi N Fuller JH Soedamah-Muthu SS Glycemic control and all-cause mortality risk in type 1 diabetes patients: the EURODIAB prospective complications study J Clin Endocrinol Metab 2014 99 800 807 24423327 37. Chen LL Liao YF Zeng TS Yu F Li HQ Feng Y Effects of metformin plus gliclazide compared with metformin alone on circulating endothelial progenitor cell in type 2 diabetic patients Endocrine 2010 38 266 275 10.1007/s12020-010-9383-8 20972736 38. Gundewar S Calvert JW Jha S Toedt-Pingel I Ji SY Nunez D Ramachandran A Anaya-Cisneros M Tian R Lefer DJ Activation of AMP-activated protein kinase by metformin improves left ventricular function and survival in heart failure Circ Res 2009 104 403 411 10.1161/CIRCRESAHA.108.190918 19096023 39. Takahashi N Shibata R Ouchi N Sugimoto M Murohara T Komori K Metformin stimulates ischemia-induced revascularization through an eNOS dependent pathway in the ischemic hindlimb mice model J Vasc Surg 2015 61 489 496 10.1016/j.jvs.2013.09.061 24993950 40. Humpert PM Neuwirth R Battista MJ Voronko O von Eynatten M Konrade I Rudofsky G Wendt T Hamann A Morcos M SDF-1 genotype influences insulin-dependent mobilization of adult progenitor cells in type 2 diabetes Diabetes Care 2005 28 934 936 10.2337/diacare.28.4.934 15793201 41. Fadini GP de Kreutzenberg SV Mariano V Boscaro E Bertolini F Mancuso P Quarna J Marescotti M Agostini C Tiengo A Avogaro A Optimized glycaemic control achieved with add-on basal insulin therapy improves indexes of endothelial damage and regeneration in type 2 diabetic patients with macroangiopathy: a randomized crossover trial comparing detemir versus glargine Diabetes Obes Metab 2011 13 718 725 10.1111/j.1463-1326.2011.01396.x 21410861 42. Humpert PM Djuric Z Zeuge U Oikonomou D Seregin Y Laine K Eckstein V Nawroth PP Bierhaus A Insulin Stimulates the Clonogenic Potential of Angiogenic Endothelial Progenitor Cells by IGF-1 Receptor-Dependent Signaling Mol Med 2008 14 301 308 10.2119/2007-00052.Humpert 18309377 43. Oikonomou D Kopf S von Bauer R Djuric Z Cebola R Sander A Englert S Vittas S Hidmark A Morcos M Influence of insulin and glargine on outgrowth and number of circulating endothelial progenitor cells in type 2 diabetes patients: a partially double-blind, randomized, three-arm unicenter study Cardiovasc Diabetol 2014 13 137 10.1186/s12933-014-0137-4 25300286 44. OvO Verhaar Nieuwdorp M Westerweel PE Hoefer IE Basser P Stroes ESG Reconstituted HDL increases circulating endothelial progenitor cells in patients with type 2 diabetes Arterioscler Thromb Vasc Biol 2007 27 1864 10.1161/ATVBAHA.107.143875 17634523 45. Nagai MS Masataka S Shin-ichiro M Kerry-Anne R Naoki T Yuji K Katsuhiko Y Takao O Keijiro S Ryozo: Reconstituted high-density lipoprotein stimulates differentiation of endothelial progenitor cells and enhances ischemia-induced angiogenesis Arterioscler Thromb Vasc Biol 2007 27 813 10.1161/01.ATV.0000259299.38843.64 17272742 46. Rossi F Bertone C Montanile F Miglietta F Lubrano C Gandini L Santiemma V HDL cholesterol is a strong determinant of endothelial progenitor cells in hypercholesterolemic subjects Microvasc Res 2010 80 274 279 10.1016/j.mvr.2010.05.003 20478316 47. Avogaro GPF Mattia A Saulavigilide K Elisa B Roberta C Mariacristina M Nicol P Carlo A Diabetes impairs stem cell and proangiogenic cell mobilization in humans Diabetes Care 2013 36 943 10.2337/dc12-1084 23111057 48. Arunachalam G Samuel SM Marei I Ding H Triggle CR Metformin modulates hyperglycaemia-induced endothelial senescence and apoptosis through SIRT1 Br J Pharmacol 2014 171 523 535 10.1111/bph.12496 24372553 49. Xu ZZ Haibing C Jun L Tao L Bingqing Z Ying Z Huiyi J Ying H Qing G Sirtuin 1-mediated cellular metabolic memory of high glucose via the LKB1/AMPK/ROS pathway and therapeutic effects of metformin Diabetes 2012 61 217 10.2337/db11-0416 22124463 50. Li WD Du XL Qian AM Hu N Kong LS Wei S Li CL Li XQ Metformin regulates differentiation of bone marrow-derived endothelial progenitor cells via multiple mechanisms Biochem Biophys Res Commun 2015 465 803 809 10.1016/j.bbrc.2015.08.091 26319555 51. Lu A Wang L Qian L The role of eNOS in the migration and proliferation of bone-marrow derived endothelial progenitor cells and in vitro angiogenesis Cell Biol Int 2015 39 484 490 10.1002/cbin.10405 25492215 52. Bakhashab S Ahmed FW Schulten H-J Bashir A Karim S Al-Malki AL Gari MA Abuzenadah AM Chaudhary AG Alqahtani MH Metformin improves the angiogenic potential of human CD34+ cells co-incident with downregulating CXCL10 and TIMP1 gene expression and increasing VEGFA under hyperglycemia and hypoxia within a therapeutic window for myocardial infarction Cardiovasc Diabetol 2016 15 1 12 10.1186/s12933-016-0344-2 26739706 53. Bromage DI Yellon DM The pleiotropic effects of metformin: time for prospective studies Cardiovasc Diabetol 2015 14 109 10.1186/s12933-015-0273-5 26271457

PMC005xxxxxx/PMC5000451.txt

==== Front BMC PsychiatryBMC PsychiatryBMC Psychiatry1471-244XBioMed Central London 101110.1186/s12888-016-1011-6Research ArticleAssessment of personality-related levels of functioning: a pilot study of clinical assessment of the DSM-5 level of personality functioning based on a semi-structured interview Thylstrup Birgitte bt.crf@psy.au.dk 1Simonsen Sebastian 2Nemery Caroline caroline_nemery@hotmail.com 3Simonsen Erik es@regionsjaelland.dk 4Noll Jane Fjernestad jafn@regionsjaelland.dk 4Myatt Mikkel Wanting Mikkel.Wanting.Myatt@regionh.dk 2http://orcid.org/0000-0002-6849-6554Hesse Morten mh.crf@psy.au.dk 11 Center for Alcohol and Drug Research, Aarhus University, Bartholins Allé 10, 8000 Aarhus C, Denmark 2 Regional Services for Mental Health, Capital Region, Stolpegårdsvej 20, 2820 Gentofte, Denmark 3 BOMI, Renter for Neurorehabilitation, Maglegårdsvej 15, Roskilde, Denmark 4 Regional Services for Mental Health, Nørregade 54, 4100 Ringsted, Denmark 25 8 2016 25 8 2016 2016 16 1 29822 3 2016 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The personality disorder categories in the Diagnostic and Statistical Manual of Mental Disorders IV have been extensively criticized, and there is a growing consensus that personality pathology should be represented dimensionally rather than categorically. The aim of this pilot study was to test the Clinical Assessment of the Level of Personality Functioning Scale, a semi-structured clinical interview, designed to assess the Level of Personality Functioning Scale of the DSM-5 (Section III) by applying strategies similar to what characterizes assessments in clinical practice. Methods The inter-rater reliability of the assessment of the four domains and the total impairment in the Level of Personality Functioning Scale were measured in a patient sample that varied in terms of severity and type of pathology. Ratings were done independently by the interviewer and two experts who watched a videotaped Clinical Assessment of the Level of Personality Functioning Scale interview. Results Inter-rater reliability coefficients varied between domains and were not sufficient for clinical practice, but may support the use of the interview to assess the dimensions of personality functioning for research purposes. Conclusions While designed to measure the Level of Personality Functioning Scale with a high degree of similarity to clinical practice, the Clinical Assessment of the Level of Personality Functioning Scale had weak reliabilities and a rating based on a single interview should not be considered a stand-alone assessment of areas of functioning for a given patient. Keywords PersonalityLevels of functioningAssessmentInterviewClinical practiceissue-copyright-statement© The Author(s) 2016 ==== Body Background Perhaps nothing is more central to treating mental health problems than the patient’s personality [1]. Since the introduction of Axis II into the diagnostic nomenclature in the DSM-III, it has been possible for clinicians and researchers to consider personality in practice and research. However, the personality disorder (PD) categories in the Diagnostic and Statistical Manual of Mental Disorders IV [2] have been extensively criticized on a number of grounds. For instance, it has been noted that there is considerable overlap between categories in both general population [3] and clinical samples [4], that most of the PD diagnoses do not represent categorical phenomena at the latent variable level [5], and that the way in which clinicians diagnose PD does not correspond to the way that researchers have found to be the most reliable and valid [6]. There is now a growing consensus that personality pathology should be represented dimensionally rather than categorically [5, 7, 8]. While the DSM-IV categorical model was retained in the DSM-5 Section II as the official diagnostic system, a novel approach to the assessment of personality pathology was included in Section III to stimulate further research and possible inclusion in future DSM iterations [9]. The new system is a hybrid of dimensional and categorical ratings that include personality traits as well as diagnoses [10]. An innovative component is the Level of Personality Functioning Scale (LPFS), which defines personality pathology in terms of impairments in self-functioning (Identity and Self-direction) and interpersonal functioning (Empathy and Intimacy), and can be used to assess both the presence and severity of personality pathology [9]. The four domains are rated individually, and for diagnostic purposes the clinician selects the level of functioning that most closely captures the patient’s overall level of impairment [11]. The LPFS constitutes the first step toward the diagnosis of a personality disorder under Section III [10]. Following the LPFS assessment, the clinician must assess pathological personality traits according to five trait domains: negative affectivity, detachment, antagonism, disinhibition, and psychoticism. The diagnostic assessment of the level of personality functioning scale During the development of the LPFS, Morey and colleagues first published data in support of the validity of a global dimension of personality pathology related to both self and interpersonal functioning [11], and in a subsequent study, Morey and colleagues found support for the concurrent and clinical validity of the LPFS [12]. Similarly, other measures such as the Inventory of Personality Organization and the Objects Relations Inventory have been used as indicators of levels of personality functioning [13]. A study by Hopwood and colleagues [14] of PD patients participating in the Collaborative Longitudinal Personality Disorders Study [15] demonstrated that generalized severity is the most important single predictor of concurrent and prospective dysfunction in the assessment of personality pathology, and may be one of the most important features to assess when working with personality pathology [11, 16]. The alternative model has received substantial criticism after its publication, especially for being too complicated for general clinical use and research [10]. While this criticism may in part reflect the difficulty of adjusting to new ideas when conducting any assessment or intervention, it underlines the importance of finding the right balance between the time and resources used when obtaining qualified assessment tools for clinical use as well as research. However, there is at present no officially approved clinical instrument to assess the LPFS, and since a substantial amount of evidence from clinical research points to the difficulties in obtaining valid and reliable diagnostic information about personality pathology, there is a need for a diagnostic instrument that can be used to assess each particular aspect of the LPFS in a standardized, reliable, meaningful and clinically acceptable way. Several research groups are currently working on developing a standardized instrument, but to the best of our knowledge, only two studies have published data on the inter-rater reliability of the LPFS ratings. To challenge the claim that the constructs in the LPFS are too complex for most clinicians to rate e.g. [1, 17–19], Zimmerman and colleagues [20] studied whether 22 psychology undergraduate students were able to apply the LPFS with sufficient reliability. The ratings were based on an operationalized psychodynamic interview of 10 female patients conducted by an experienced clinician, of which five patients were diagnosed with a PD according to the SCID-II and five were not. The study indicated that the concerns about the complexity of the LPFS constructs were premature with an acceptable Intra Class Correlation (ICC) for the total dimension (ICC) = .51, 95 % confidence intervals [CI] (.31, .78). However, the ICC was more mixed for the four domains, ranging from .25 for Empathy to .63 for Intimacy. Although a social relations model analysis found evidence of significant perceiver variance for Empathy, the students’ ratings converged with expert-rated proxy measures of the severity of personality pathology, that is the presence and number of patients with DSM-IVPD diagnoses and OPD level of structural integration. The second reliability study was conducted by Few and colleagues [21] with 109 community adults receiving outpatient mental health treatment. In this study, the LPFS was rated by trained graduate students based on a video-taped SCID-II interview conducted by graduate students, and the reliability was based on both interviewer and video-ratings. In this study, the inter-rater reliabilities for Identity, Self-Direction, Empathy, and Intimacy were .49, .47, .49 and .47, respectively. These two studies have contributed significantly to the ongoing research regarding the LPFS, although there are reasons for concern about the clinical generalizability of the inter-rater reliability in both. For one, both studies involved patients diagnosed with a PD at the low to moderate end of the severity continuum, which corresponds to levels zero to two in the LPFS, and did not involve patients with a more severe PD, such as schizotypal, paranoid and antisocial PD, corresponding to levels three and four in the LPFS. Secondly, the LPFS was assessed by untrained and inexperienced raters in the Zimmerman study, and the findings might therefore set a lower bound for the inter-rater reliability. Also, in both studies, the ratings were based on interviews which are hardly representative of a standard clinical interview. In the Few study, both the interviews and ratings were carried out by specifically trained graduate students, and also in this context it seems unlikely that a general clinician would conduct and rate the LPFS in a similar way. Finally, Hutsebaut and colleagues developed a semi-structured interview to assess the LPFS [22], the Alternative Model for Personality Disorders (AMPD). Each section of the AMPD opens with a general question, but specific questions are asked that probe directly for facets of the LPFS. The inter-rater reliability of the AMPD is substantially higher than the inter-rater reliability that has been reported in the two previous studies, with intraclass correlations ranging from .58 to .82 in the clinical sample, and from .81 to .92 when combining the patient sample with additional non-clinical cases. The Clinical Assessment of the Level of Personality Functioning Scale (CALF) The aim of the present study was to assess inter-rater reliability of a semi-structured interview developed for the assessment of the four domains in the LPFS, the Clinical Assessment of the Levels of Personality Functioning Scale (CALF). The CALF was designed to be relatively brief, lasting less than an hour, and to be suitable early on in the assessment process. In order to assess duration of interview and identify questions that were problematic, or areas that required further questions before the current study, a previous version of the CALF was tested with patients undergoing treatment for substance use disorders and prison inmates in a high-security prison for offenders who were deemed to need treatment for severe psychiatric disorders, and a small community sample. Further we wanted to increase the diversity of personality pathology studied with the LPFS by sampling a range of patients who varied in terms of both severity and type of pathology within different treatment settings. If the inter-rater reliability was also acceptable under such conditions, this would increase the acceptability of using the CALF to assess patients based on the LPFS in clinical practice, making a strong case against the need for the costly retraining of expert clinicians to carry out the clinical interviews and rate the LPFS. Methods Procedure To have access to a range of patients who varied in severity and type of pathology in this study, we sampled patients from three different sources: an outpatient psychotherapy clinic that specifically served patients with PDs, a general outpatient psychiatric clinic, and substance dependent patients in ongoing day or residential treatment with no drug or alcohol use in the past 30 days, including some from a high security prison. All participants were informed about the aim and content of the study and gave informed consent to participate. The CALF interviews were conducted by six trained experts and lasted for between 44 and 69 min (M = 57.3, SD = 9.6); all interviews were videotaped. Following this, the videotaped interviews were distributed between six experts with each interview co-rated by two experts, who had not carried out the interview that was being rated. Interviewers and raters The interviews and ratings were conducted by four psychologists and two MDs with extensive experience with clinical assessment and assessment research, three men and three women with a mean age of 38.9 years (range 31 to 46 years). Additionally, two of the interviews were conducted by a female psychology student, age 31 years, under supervision by one of the MDs. Participants Participants were recruited from a patient (n = 36) and a community sample (n = 7). The patient sample consisted of 36 patients, 19 men and 17 women, with a mean age of 36 years (range: 18 to 56 years): Substance dependent patients (n = 19); Personality disordered patients (n = 12); Patients with anxiety or depression (n = 5). The community sample consisted of seven women with a mean age of 34 years (range: 24 to 45 years). Measures The Level of Personality Functioning Scale (LPFS) rates the four domains Identity and Self-direction (self-functioning) and Empathy and Intimacy (interpersonal functioning) on a scale from 0 (no impairment) to 4 (highest level of impairment). Within each domain, a comprehensive description is given for each criterion. For the purpose of this study, the total score was summarized as the mean of the four domain scores. No formal training was provided for the raters, and the instructions for determining the ratings were restricted to handing out written copies of the LPFS. The CALF interview Like the Metacognition Assessment Interview (MAI) [23], the Adult Attachment Interview (AAI), the Psychopathy Checklist [24], and the Clinical Diagnostic Interview [25], the CALF is structured, but the interview and interpretation rely primarily on the inference of the underlying processes (contrasts, absence, brevity of explanations, and ability to shift perspectives and to reflect on both emotional, factual and cognitive processes) rather than relying only on the explicit content of the response. The four domains in the LPFS are rated based on the totality of the interview rather than on patient responses to the questions in the corresponding section. For each section, the interviewer has to rate the level of dysfunction by giving a score from 0 to 4, with 0 indicating no impairment and 4 indicating extremely severe impairment. The CALF opens with questions about general demographics, followed by questions about current problems with mental health and current treatments. The main body of the interview consists of four sections, each of which concerns one of the dimensions in the LPFS, but where some of the questions within each section also provide information on the level of functioning within other domains. Specifically, the CALF prompts patients to talk about the four domains based on their general life situation within the last three to five years. All sections open with a global question concerning the specific domain, followed by prompts for specific examples and qualifications of the response. All sections conclude with questions about contentment and concerns for the given domain, and whether recent changes, events or periods of higher or lower distress have affected specific areas of functioning within this domain. Section 1 assesses Self-direction. According to the LPFS, Self-direction concerns the ability to set and pursue realistic and meaningful goals in life. Questions in this section concern the patient’s goals in life, and prompt questions concerning the respondent’s ability to set reasonable goals based on a realistic assessment of personal capacities. Since the pilot testing showed that current life goals may be difficult to evaluate in terms of how realistic they are and how consistently the patient pursues these goals, we included past life goals and how these had been pursued. Following this, the patient is asked about the value and meaning of current and past goals, what has been done to obtain the goals and whether they have been obtained, possible future obstacles, and what the patient can do to overcome these obstacles. Finally, the patient is asked if he or she considers herself to be in control of her life in general, and whether she is satisfied with the goals that he or she is presently pursuing. Section 2 assesses Intimacy. In the LPFS, Intimacy includes both close relationships and relationships in the community, and is more concerned with the reciprocity and the depth of the relationships than with the size of network of perceived support. In order to identify the degree of reciprocity, this section opens with questions about who the patient sees in daily life and the frequency of contact. Next, the patient is asked to identify a single person who is particularly important and to describe what he or she likes about that person, and then to describe what the other person likes about her. Finally, this section asks about conflicts that have resulted in the discontinuation of social contacts, an area which is also considered in the assessment of the capacity for Empathy. Section 3 concerns Empathy, which is referred to in the LPFS as the capability to understand and respond adequately to the experiences and motivations of others, and the awareness of how one’s own actions affect others. The section opens with questions about disagreements and who the patient disagrees with. Next, the patient is asked to identify a disagreement with a person, and is asked about the motivations and intentions behind the disagreement (of both those of the patient and the other person), and whether and how the disagreement was resolved. The purpose of these questions is primarily to assess the patient’s capacity for understanding and considering the perspectives and needs of others in a conflict, the ability to understand their reactions, and the ability to learn from disagreements. Section 4 adds further information concerning the Identity dimension. Usually, responses to the previous sections in the CALF interview are highly salient for the issues covered in the Identity section, because they provide rich information about self-image, self-worth, and the capacity for independent functioning. However, an important aspect of Identity that is not necessarily covered by the previous sections is the patient’s access to and ability to regulate a wide range of emotions. To assess this aspect of Identity, the patient is asked about feelings of sadness, anxiety, anger and pleasure, what triggers these feelings, the intensity and duration of the feeling, and how the patient reacts to the feeling. Finally, the section contains questions about differences between private and public identities. Statistical analysis The number of patients included was determined primarily on pragmatic grounds. Hence, a post hoc power analysis was conducted to assess the power to assess correlations which indicated that with a sample size of 34, the power to detect a correlation of 0.50 was 86 % with α = 0.05. For the dependent variable, the LPFS score, we summed the scores on each of the four domains to yield a number that could range from 0 (no dysfunction) to 12 (maximal dysfunction). To assess the agreement between interviewer ratings and video-based ratings, one of the ratings from experts who had conducted the video rating of the interview was randomly selected, and the rating from that person was correlated with the interviewer’s rating for Pearson correlations. This was done for the individual rating of each domain, as well as for the sum of the four domains. For each correlation, the 95 % confidence intervals were calculated by using Fisher’s Z transformation. Further, to assess agreement between different video ratings of the same video, we calculated agreement using intraclass correlations from mixed effects regression models. For these correlations, we report the confidence intervals, and the p-values based on the assumption that the distribution of the likelihood-ratio test statistic is a 50:50 mixture of χ2 distributions with k and k + 1° of freedom. All analyses were carried out on Stata 13 for Windows [26]. The analyses were repeated, so that all analyses were first conducted using only the patient sample, and in a second round, the community individuals were included in the analyses. Results In the patient sample, the mean score on the LPFS was 8.18 for the interviewer ratings (range: 1 to 13, standard deviation [SD] = 2.98), and 7.59 for the video ratings (range: 1 to 12, SD = 3.22). In the community sample, the mean score for interviewer rating was 0.86 (range: 0 to 4, SD = 1.46), and the mean video rating was 2.00 (range: 0 to 8, SD = 2.89). Agreement between video ratings and interviewer ratings For five patients, the interviewer did not rate the LPFS, leaving 31 patients for this analysis (17 psychiatric patients and 14 patients with substance use disorders). The power to detect a correlation of 0.5 was 83 % with a sample size of 31, which is still within the acceptable range. For the full LPFS, the Pearson correlation between video rating and interviewer was 0.59 (p < .001). The domain correlations between the interviewer and video-based ratings are shown in Table 1. Correlations ranged from 0.16 (Identity, ns) to 0.66 (Self-direction, p < .001). The correlation between the sum of the LPFS as rated by interviewer and by video rater is illustrated in Fig. 1. When community controls were included, all coefficients increased, and all became significant.Table 1 Pearson correlations between interviewer-rated LPFS and randomly selected video-rated LPFS Clinical sample (n = 31) P-value Total sample (n = 38) P-value Identity .202 (−.164 to .519) .276 .588 (.331 to .764) .000 Self-direction .672 (.417 to .829) .000 .716 (.514 to .843) .000 Intimacy .495 (.171 to .723) .005 .650 (.417 to .803) .000 Empathy .360 (.007 to .634) .046 .419 (.114 to .651) .000 Total .582 (.287 to .776) .001 .689 (.474 to .827) .000 Notes: LPFS Levels of personality functioning scale Values in parentheses are 95 % confidence intervals Fig. 1 Scatterplot of video-rated LPFS as a function of interviewer-rated LPFS Agreement between different video raters For six patients, only one video had been rated by a video rater, leaving 30 patients for the inter-rater analysis of the video-based ratings. The intraclass correlations between two independent video raters are summarized in Table 2. The intraclass correlations range from 0.31 to 0.60. Again, the highest inter-rater agreement was found for Self-direction, and the weakest for Identity. When community controls were included, all coefficients increased, and all became significant.Table 2 Intraclass correlations between video-rated LPFS Clinical sample (n = 30) P-value Total sample (n = 37) P-value Identity .31 (.09 to .67) .039 .59 (.38 to .77) .000 Self-direction .58 (.35 to .79) .000 .62 (.41 to .79) .000 Intimacy .46 (.22 to .73) .004 .62 (.42 to .79) .000 Empathy .57 (.33 to .78) .000 .59 (.38 to .78) .000 Total .54 (.30 to .77) .000 .65 (.46 to .81) .000 Notes: ICC Intraclass correlation LPFS Levels of personality functioning scale Values in parentheses are 95 % confidence intervals Discussion In this study, we tried a semi-structured interview, the CALF, developed to measure the LPFS. The CALF was designed to be conducted in a clinical setting, applying strategies similar to what characterizes assessments in clinical practice, which often involves the inference of the underlying processes in the patient’s narrative. However, the findings were only minimally encouraging for the use of the CALF as a diagnostic instrument for the LPFS. Most inter-rater correlations were statistically significant, but none were in the range where two different assessments were so similar, that one could substitute the other (i.e., more than 50 % shared variance). This is in spite of the fact that we had a very diverse sample of patients in which a wide range of variation could be expected in the LPFS. In terms of specific domains, the strongest inter-rater reliability was found for Self-direction, both in terms of different video raters and when comparing video ratings to interviewer ratings. Self-direction is characterized by the ability to set and consistently pursue realistic and meaningful goals, and it appears that especially by asking the patient to describe his or her past goals and clarify which of them have been obtained and what has been done to reach them, the interviewer will get a reliable estimate of the patient’s level of functioning in this area. The two interpersonal areas, Empathy and Intimacy, gave more modest inter-rater reliability estimates, and although the correlations were statistically significant and may contribute to the overall clinical picture, such ratings should not be considered stand-alone assessments of these areas of functioning in a research context, let alone in a clinical context. Finally, the inter-rater reliability of the Identity scale was low, indicating that in order to obtain acceptable reliability, a different approach is probably needed than the one found in the current version of CALF. We have no good explanation for the lower reliability on the Identity scale. It may be that Identity is a complicated construct with no universally agreed upon definition e.g. [27], or that the rating of the Identity domain draws more heavily on answers obtained in the other sections of the CALF. The concerns about the inter-rater reliability in this study are similar to those raised in previous research. Although the present study is a small study that only yields preliminary evidence on the inter-rater reliability of the LPFS, the correlations were strong enough to suggest further research on the rating of the LPFS. A central question is here how a clinical interview format best supports a reliable standardized assessment of the LPFS, and whether using assessment strategies that mirror how psychiatrists and psychologists work in clinical practice may find a place within such format [6]. A major challenge to the dimensional approach in the LPFS is that, unlike specific types of psychopathology, overall personality functioning and the four domains in the LPFS do not manifest in clear, well-defined symptoms, but address complex and diverse phenomena. The question is how this can be reflected in the assessment approach in a way that supports assessment reliability and validity. One extreme would be a fully structured interview in which patients’ answers would be transformed into relevant scores with only slight perceiver inference. The other extreme would be a minimally structured and phenomenologically oriented interview, in which the clinician would infer the LPFS scores based on information which is influenced by several factors besides the patient’s answers [28]. However, although sufficient reliability is easier to obtain when perceiver inference is kept to a minimum, this could come at the price of reduced validity concerning the rating of the complex constructs in the LPFS. Other related studies that have assessed concepts similar to the concepts in the LPFS have used interviews based on a structured format, which also facilitates the patients in talking freely about personal and affect-laden aspects like the CALF, in order to observe metacognitive capacities, narrative coherence, and the representational style of the interviewee, all of which are core elements which influence the assessment of personality functioning. In the Metacognition Assessment Interview (MAI) [23], the patient is asked to describe an autobiographical episode about the worst psychological situation within the last six months, and following this, the clinician adheres to a structured list of questions to assess four functional domains (monitoring, integrating, differentiating and decentering). In the Adult Attachment Interview (AAI), the patient is asked about the demographics of his or her childhood followed with questions about the nature of the relationships with parents, and an elaboration on specific episodes when positive adjectives are used when describing these relationships [29]. Thus, like the CALF, both the MAI and the AAI contain specific questions as well as more open questions about highly personal and affect-laden topics, in which patient statements are used to make inferences about an underlying quality see also [30]. The CALF was designed to assess level of personality functioning in a way that closely mimics what clinicians do in general practice, by requiring the interviewer to prompt for examples and clarifications within broad life functioning areas, rather than by probing for specific behaviors or emotions that match the criteria in the LPFS levels. While it is both a weakness and strength that the CALF also assesses what is left unsaid, this study shows that videotaped assessment interviews can be used to assess the processing of various non-verbal types of data, such as speed of speech, body language and voice intonation [31–33], which would be of particular interest when a patient is being interviewed about salient areas of functioning in life. Given that the present study, like the previous studies that we know of which have assessed the LPFS [20–22], assessed inter-rater agreement based on the rating of same data give a lower bound on the reliability of the assessment. Had different interviews of the same patient been assessed, instead of assessing the same interview, the results would almost certainly have pointed to lower reliability. In turn, this means that correlations with other variables are bound to be considerably lower. Directions for further research The inclusion of underlying processes in patient narratives in the assessment of the LPFS may be highly useful for clinical practice, in which self-reporting may be biased due to impairment in realistic self-appraisal and the ability to reflect upon and understand aspects of functioning, including mental processes and their impact on others. The CALF interview was an attempt to do this in a way that corresponds to how clinicians do in real world settings. However, before assessment of narratives can be meaningfully included in the assessment of personality functioning, improvements in inter-rater reliability are required. Limitations There are a number of important limitations to this study. First, the raters were not a random sample of psychologists and psychiatrists, but rather an expert group with a special interest in PDs. Further, the number of patients and controls was small, and larger samples are needed in future studies. Finally, the interviewers were not blind to the patients’ clinical status. Conclusion The present study showed that only weak inter-rater reliability was obtained, when the Clinical Assessment of the Level of Personality Functioning Scale interview was used to assess the Levels of Personality Functioning Scale. The interview was designed to rely on a relatively high level of inference, and the weak reliability is likely to be an effect of this fact. Based on the present findings, rating based on the Clinical Assessment of the Level of Personality Functioning Scale interview should not be considered a stand-alone assessment of areas of functioning for a given patient. Funding The project was funded entirely by intra-murral sources. Availability of data and materials A copy of the data can be obtained from researchers by contacting the corresponding author. A beta translation of the full interview is available from the corresponding author. Authors’ contributions All authors took part in the study. MH, BT, SS, and CN drafted the manuscript, and the other authors commented and gave their final approval of the final version. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate The Committee on Health Research Ethics in the Capital Region of Denmark reviewed the project description and concluded that it did not require ethical evaluation (journal # H-3-2012-FSP56). All patients gave written and verbal consent to participate in the study. ==== Refs References 1. Clarkin JF Huprich SK Do Dsm-5 personality disorder proposals meet criteria for clinical utility? J Pers Disord 2011 25 2 192 205 10.1521/pedi.2011.25.2.192 21466249 2. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author; 2000. 3. Grant BF Stinson FS Dawson DA Chou SP Ruan WJ Co-occurrence of DSM-IV personality disorders in the United States: results from the national epidemiologic survey on alcohol and related conditions Compr Psychiat 2005 46 1 1 5 10.1016/j.comppsych.2004.07.019 15714187 4. Zimmerman M Rothschild L Chelminski I The prevalence of DSM-IV personality disorders in psychiatric outpatients Am J Psychiat 2005 162 10 1911 8 10.1176/appi.ajp.162.10.1911 16199838 5. Haslam N Holland E Kuppens P Categories versus dimensions in personality and psychopathology: a quantitative review of taxometric research Psychol Med 2012 42 903 20 10.1017/S0033291711001966 21939592 6. Westen D Divergences between clinical and research methods for assessing personality disorders: Implications for research and the evolution of axis II Am J Psychiat 1997 154 7 895 903 10.1176/ajp.154.7.895 9210738 7. Krueger RF, Hopwood CJ, Wright AG, Markon KE. Challenges and strategies in helping the DSM become more dimensional and empirically based. Current psychiatry reports. 2014;16(12). 8. Widiger TA Livesley WJ Clark LA An integrative dimensional classification of personality disorder Psychol Assess 2009 21 3 243 55 10.1037/a0016606 19719338 9. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing; 2013. 10. Skodol AE Morey LC Bender DS Oldham JM The alternative DSM-5 model for personality disorders: a clinical application Am J Psychiat 2015 172 7 606 13 10.1176/appi.ajp.2015.14101220 26130200 11. Morey LC Berghuis H Bender DS Verheul R Krueger RF Skodol AE Toward a model for assessing level of personality functioning in DSM-5, part II: empirical articulation of a core dimension of personality pathology J Pers Assess 2011 93 4 347 53 10.1080/00223891.2011.577853 22804673 12. Morey LC Bender DS Skodol AE Validating the proposed diagnostic and statistical manual of mental disorders, 5th edition, severity indicator for personality disorder J Nerv Ment Dis 2013 201 9 729 35 10.1097/NMD.0b013e3182a20ea8 23995027 13. Lowyck B Luyten P Verhaest Y Vandeneede B Vermote R Levels of personality functioning and their association with clinical features and interpersonal functioning in patients with personality disorders J Pers Disord 2013 27 3 320 36 10.1521/pedi.2013.27.3.320 23735041 14. Hopwood CJ Malone JC Ansell EB Sanislow CA Gill CM McGlashan TH Personality assessment in Dsm-5: empirical support for rating severity, style, and traits J Pers Disord 2011 25 3 305 20 10.1521/pedi.2011.25.3.305 21699393 15. Gunderson JG Shea MT Skodol AE McGlashan TH Morey LC Stout RL The collaborative longitudinal personality disorders study: development, aims, design, and sample characteristics J Pers Disord 2000 14 4 300 15 10.1521/pedi.2000.14.4.300 11213788 16. Skodol AE Clark LA Bender DS Krueger RF Morey LC Verheul R Proposed changes in personality and personality disorder assessment and diagnosis for DSM-5 part I: description and rationale Personal Disord 2011 2 1 4 22 10.1037/a0021891 22448687 17. Pilkonis PA Hallquist MN Morse JQ Stepp SD Striking the (Im)proper balance between scientific advances and clinical utility: commentary on the DSM-5 proposal for personality disorders Personal Disord 2011 2 1 68 82 10.1037/a0022226 21804929 18. Tyrer P Diagnostic and statistical manual of mental disorders: a classification of personality disorders that has had its day Clin Psychol Psychot 2012 19 5 372 4 10.1002/cpp.1810 19. Tyrer P Crawford M Mulder R Blashfield R Farnam A Fossati A The rationale for the reclassification of personality disorder in the 11th revision of the International Classification of Diseases (ICD-11) Personal Ment Health 2011 5 4 246 59 10.1002/pmh.190 20. Zimmermann J Benecke C Bender DS Skodol AE Schauenburg H Cierpka M Assessing DSM-5 level of personality functioning from videotaped clinical interviews: a pilot study with untrained and clinically inexperienced students J Pers Assess 2014 96 4 397 409 10.1080/00223891.2013.852563 24224740 21. Few LR Miller JD Rothbaum AO Meller S Maples J Terry DP Examination of the Section III DSM-5 diagnostic system for personality disorders in an outpatient clinical sample J Abnorm Psychol 2013 122 4 1057 69 10.1037/a0034878 24364607 22. Hutsebaut J Feenstra DJ Kamphuis JH Development and preliminary psychometric evaluation of a brief self-report questionnaire for the assessment of the DSM-5 level of personality functioning scale: the LPFS brief form (LPFS-BF) Personal Disord 2016 7 2 192 7 10.1037/per0000159 26595344 23. Semerari A Cucchi M Dimaggio G Cavadini D Carcione A Battelli V The development of the metacognition assessment interview: instrument description, factor structure and reliability in a non-clinical sample Psychiatry Res 2012 200 2–3 890 5 10.1016/j.psychres.2012.07.015 22906953 24. Hare RD Neumann CS Psychopathy as a clinical and empirical construct Annu Rev Clin Psychol 2008 4 217 46 10.1146/annurev.clinpsy.3.022806.091452 18370617 25. Westen D Muderrisoglu S Assessing personality disorders using a systematic clinical interview: evaluation of an alternative to structured interviews J Pers Disord 2003 17 4 351 69 10.1521/pedi.17.4.351.23967 14521183 26. Stata Statistical Software. 13 ed. Texas: StataCorp LP.; 2013. 27. Jørgensen CR Disturbed sense of identity in borderline personality disorder J Pers Disord 2006 20 6 618 44 10.1521/pedi.2006.20.6.618 17192141 28. Nordgaard J Revsbech R Saebye D Parnas J Assessing the diagnostic validity of a structured psychiatric interview in a first-admission hospital sample World Psychiatry 2012 11 3 181 5 10.1002/j.2051-5545.2012.tb00128.x 23024678 29. George C Kaplan N Main M The adult attachment interview 1985 Berkeley University of California 30. Hopwood CJ Zimmermann J Pincus AL Krueger RF Connecting personality structure and dynamics: towards a more evidence-based and clinically useful diagnostic scheme J Pers Disord 2015 29 4 431 48 10.1521/pedi.2015.29.4.431 26200845 31. Blair KS Richell RA Mitchell DG Leonard A Morton J Blair RJ They know the words, but not the music: affective and semantic priming in individuals with psychopathy Biol Psychol 2006 73 2 114 23 10.1016/j.biopsycho.2005.12.006 16574302 32. Klaver JR Lee Z Hart SD Psychopathy and nonverbal indicators of deception in offenders Law Human Behav 2007 31 4 337 51 10.1007/s10979-006-9063-7 33. Aziz-Zadeh L Sheng T Gheytanchi A Common premotor regions for the perception and production of prosody and correlations with empathy and prosodic ability PLoS One 2010 5 1 e8759 10.1371/journal.pone.0008759 20098696

PMC005xxxxxx/PMC5000452.txt

==== Front J NeuroinflammationJ NeuroinflammationJournal of Neuroinflammation1742-2094BioMed Central London 66310.1186/s12974-016-0663-yResearchCortisol-induced immune suppression by a blockade of lymphocyte egress in traumatic brain injury Dong Tingting dtt623@gmail.com Zhi Liang zhiliang90@hotmail.com Bhayana Brijesh Bhayana.Brijesh@mgh.harvard.edu Wu Mei X. (617)-726-1298mwu5@mgh.harvard.edu Wellman Center for Photomedicine, Massachusetts General Hospital, Department of Dermatology, Harvard Medical School, 50 Blossom Street, Boston, MA 02114 USA 25 8 2016 25 8 2016 2016 13 1 19730 3 2016 18 7 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Acute traumatic brain injury (TBI) represents one of major causes of mortality and disability in the USA. Neuroinflammation has been regarded both beneficial and detrimental, probably in a time-dependent fashion. Methods To address a role for neuroinflammation in brain injury, C57BL/6 mice were subjected to a closed head mild TBI (mTBI) by a standard controlled cortical impact, along with or without treatment of sphingosine 1-phosphate (S1P) or rolipram, after which the brain tissue of the impact site was evaluated for cell morphology via histology, inflammation by qRT-PCR and T cell staining, and cell death with Caspase-3 and TUNEL staining. Circulating lymphocytes were quantified by flow cytometry, and plasma hydrocortisone was analyzed by LC-MS/MS. To investigate the mechanism whereby cortisol lowered the number of peripheral T cells, T cell egress was tracked in lymph nodes by intravital confocal microscopy after hydrocortisone administration. Results We detected a decreased number of circulating lymphocytes, in particular, T cells soon after mTBI, which was inversely correlated with a transient and robust increase of plasma cortisol. The transient lymphocytopenia might be caused by cortisol in part via a blockade of lymphocyte egress as demonstrated by the ability of cortisol to inhibit T cell egress from the secondary lymphoid tissues. Moreover, exogenous hydrocortisone severely suppressed periphery lymphocytes in uninjured mice, whereas administering an egress-promoting agent S1P normalized circulating T cells in mTBI mice and increased T cells in the injured brain. Likewise, rolipram, a cAMP phosphodiesterase inhibitor, was also able to elevate cAMP levels in T cells in the presence of hydrocortisone in vitro and abrogate the action of cortisol in mTBI mice. The investigation demonstrated that the number of circulating T cells in the early phase of TBI was positively correlated with T cell infiltration and inflammatory responses as well as cell death at the cerebral cortex and hippocampus beneath the impact site. Conclusions Decreases in intracellular cAMP might be part of the mechanism behind cortisol-mediated blockade of T cell egress. The study argues strongly for a protective role of cortisol-induced immune suppression in the early stage of TBI. Keywords TBIT lymphocytesCortisolInflammationcAMPhttp://dx.doi.org/10.13039/100000181Air Force Office of Scientific ResearchFA9550-11-1-0415FA9550-13-1-0068Wu Mei X. http://dx.doi.org/10.13039/100000090Congressionally Directed Medical Research ProgramsW81XWH-13-2-0067Wu Mei X. issue-copyright-statement© The Author(s) 2016 ==== Body Background Acute traumatic brain injury (TBI) is a major cause of mortality and disability in the early decades of life in many developed countries. At least 5.3 million people in the USA currently require long-term or life-long assistance with the activities of daily living after TBI [1]. TBI results in cerebral structural damage and functional deficits due to both primary and secondary injury. The primary injury is caused directly by the external mechanical force at the moment of trauma leading to skull fractures, brain contusions, lacerations, diffused axonal injuries, vascular tearing, intracranial hemorrhages, etc. The primary injury is followed by development of secondary neuronal damage that evolves over a period of months [2], thereby providing a golden opportunity for prevention and intervention. Tremendous efforts have been made in the past decades toward exploring the cellular and molecular mechanisms underlying secondary brain damage as well as identification of specific targets for prevention and/or therapeutics against this disorder [2]. It is now believed that a cascade of molecular, neurochemical, neuronal cell apoptosis, cellular, and immune processes contribute to secondary brain damage as a consequence of mitochondrial dysfunction, cerebral hypoxia, and disruption of calcium homeostasis in cells at the impact site [2, 3]. A growing body of evidence indicates that inflammation induced by primary brain injury plays dual and opposite roles in the outcome of TBI [4]. On one hand, it contributes to reparation and regeneration processes of the primary brain injury, for instance, clearance of necrotic and apoptotic cells by phagocytic cells and promoting neuron growth at the injured site [5, 6]. On the other hand, it facilitates secondary brain injury via the production of various inflammatory cytokines such as interleukin-1-alpha (IL-1α) and interleukin-1-β (IL-1β), tumor necrosis factor alpha (TNF-α), and interleukin-6 (IL-6) [7, 8]. The brain is well known to be an immune privilege site, and infiltration of inflammatory cells to it is largely restricted by the blood-brain barrier (BBB) under a physiological condition [9]. However, TBI often results in an invasion of neutrophils, monocytes, and lymphocytes from the periphery and activation of microglia due to disruption of the BBB. This initiates a cascade of inflammatory responses [10]. Likewise, T lymphocytes have been shown to infiltrate the brain parenchyma post-injury, but their role in the secondary brain injury development following TBI remains poorly understood [11]. Both pre-clinical and clinical studies have shown significant, acute increases of cortisol levels in serum and cerebrospinal fluid in response to TBI [12, 13]. The increased cortisol might suppress inflammation in the brain in order to protect the injured brain tissues from inflammation insult, in light of the well-documented anti-inflammatory function of cortisol, a steroid hormone. The current investigation revealed that an elevated level of serum cortisol was inversely correlated with the number of peripheral lymphocytes, in particular, T cells following brain trauma. Cortisol appeared to sequester lymphocytes in the secondary lymphoid tissues by blocking their egress, contributing to reduced inflammation and cell death at injured brain tissues. The study sheds novel insight into the mechanism underlying cortisol-mediated suppression of inflammation and protective roles of cortisol in TBI at the early stage. Methods Animals Eight-week-old female C57BL/6 mice were purchased from Charles River Laboratories and maintained in a 12-h light/dark cycle. All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of the Massachusetts General Hospital and performed according to the National Institutes of Health guidelines for the Care and Use of Laboratory Animals. TBI induction Mice were subjected to a closed head TBI by a standard controlled cortical impact on the left lateral with intact skull and scalp as previously described [7, 14]. In brief, the mice were anesthetized with isoflurane and placed on a mobile plate with their hair removed from the head. A flat face 2-mm diameter tip of the pneumatic impact device (AMS 201, AmScien Instruments, Richmond, VA) was positioned on the left hemisphere center, lowered gradually down to touch the scalp, and recorded as zero depth (sham control). The punch depth was then set 2 mm using a screw-mounted adjustment. A 4.9 ± 0.2 m/s velocity and 80 ms contact time were specified by setting 150 pounds per square inch (psi) for a high pressure and 30 psi for a low pressure impact. These parameters were selected to yield a trauma giving rise to a neurological severity score (NSS) of 3–5 at 1 h post-TBI also called mild TBI (mTBI). After recovery from anesthesia, the mice were returned to cages with post-operative care. Quantification of circulating lymphocytes Blood samples were collected from tail vein in 1 and 4 h after TBI to assess plasma cortisol and circulating lymphocytes or 4 h after hydrocortisone injection (Sigma, 10 mg/kg) to confirm suppressive effects of cortisol on peripheral leukocytes. In separate groups of mice, TBI was induced as above, immediately followed with i.p. injection of either sphingosine 1-phosphate (S1P) (Enzo Life Sciences, 5 μM/kg) or rolipram (Sigma, 30 μM/kg), and blood samples were collected 1 h later. Cells were pelleted, suspended, and treated with ammonium-chloride-potassium (ACK) buffer to lyse erythrocytes. The cells were then counted and stained with PE-anti-CD3 antibody for T cells, APC-anti-CD19 antibody for B cells, FITC-anti-Ly6G antibody for neutrophils, or PE-Cy7-anti-F4/80 antibody for monocytes, followed by flow cytometry analysis on BD FACSAria. Quantification of plasma cortisol by liquid chromatography-tandem mass spectrometry (LC-MS/MS) Quantitative analysis of hydrocortisone in serum samples was performed on an LC-MS/MS instrument. Fludrocortisone acetate was used as a reference standard; known amounts of this compound were added to the serum extract prior to the LC injections. The following working parameters were used for the LC-MS/MS analysis: scan type, MRM (363 → 121 transition for hydrocortisone and 423 → 239 transition for fludrocortisone acetate); polarity, positive; ionization, ESI; column, C18, 2.1 × 50 mm, 1.8 μm; gradient, solution A = acetonitrile, solution B = 10 mM ammonium acetate in water, 20 → 100 % of A over 5 min with a flow rate of 0.4 ml/min. Intravital imaging of T cell egress in lymph nodes T cells were isolated from lymph nodes and spleens of normal C57BL/6 mice and treated with a mixture of rat anti-mouse monoclonal antibodies against CD19, CD32, and CD16 followed by depletion of antibody-bound cells with BioMag goat anti-rat IgG (Polysciences Inc., Warrington, PA) as previously described [15]. The purified T cells were stained with 20 μM 5-(and-6)-(((4-chloromethyl) benzoyl) amino) tetramethylrhodamine (CMTMR, Invitrogen) for 20 min at 37 °C. The labeled cells were adoptively transferred to cognate C57BL/6 mice by tail intravenous injection of 1 × 107 cells per mouse. The recipient mice were then subcutaneously injected with 15 μg anti-LYVE-1 Ab (R&D Systems) conjugated with Alexa Fluor-647 (monoclonal antibody labeling kit, Invitrogen) in a hind footpad, followed by i.p. injection with 10 mg/kg of hydrocortisone or saline 16 h later. After 2 h of hydrocortisone injection, the mouse was anesthetized and placed on an electrically heated plate to maintain the temperature at 36 °C and had their popliteal lymph nodes exposed by a small skin incision. The lymph node to be imaged was bathed with a continuous flow of warm saline in order to maintain a local temperature at 36 °C during imaging. Intravital imaging of the lymph node was performed using a home-built microscope and the images were acquired using an in-house developed software [16]. The in vivo confocal microscope was equipped with three photomultiplier tubes (PMT, Hamamatsu, R9110) which were optimized to provide bright images with a high contrast. Each x-y plane spanned 250 × 250 μm at a resolution of 2 pixels per μm. Stacks of images were acquired with a z-axis resolution of 3 μm per section, and time-series images were obtained in a 20-s interval. To determine whether a cell was inside, outside, or on the border of a cortical sinus, its location relative to the sinusoid wall was assessed in the x-y and/or the z plane. The moving distances and velocities of the tacking cells were tracked for each video segment and calculated using ImageJ software. Transwell assay for cell migration T cell migration was analyzed in 48-well micro chemotaxis chamber (Neuro Probe) as previously described [17]. T cells isolated from normal C57BL/6 mice as above were suspended at 1 × 105 cells in 100 μl in RPMI medium supplemented with 3 % fetal bovine serum (charcoal stripped), 2 mM l-glutamine, 100 U/ml penicillin, 100 μg/ml streptomycin, and 20 μM of either hydrocortisone or vehicle followed by adding the cells to the upper chamber of the transwell. S1P at 20 nM or vehicle was prepared in the same medium and added to the lower chamber of the transwell. Migration was performed for 4 h at 37 °C in a humidified 5 % CO2 incubator. The number of migrated cells was determined by counting the cells in the lower chamber. S1P administration S1P (Enzo Life Sciences) was prepared according to the manufacturer’s instructions. Briefly, S1P was dissolved in methanol (0.5 mg/ml) and aliquoted, followed by evaporation of the solvent under a stream of nitrogen to deposit a thin film on the inside of the tube. Prior to use, the aliquots were resuspended in PBS with 4 mg/ml bovine serum albumin (BSA) to a final concentration of S1P at 500 μM. The S1P or the vehicle was i.p. injected into the mice at a dosage of 200 μl per mouse immediately after TBI. Measurement of intracellular cAMP T cells (2 × 106/ml) freshly isolated from normal C57BL/6 mice were incubated at 37 °C in serum free Aim V medium (Invitrogen) and pretreated with 10 μM rolipram (Sigma) or saline for 15 min, followed by a treatment with 100 μM hydrocortisone or vehicle at 37 °C for 5 min. Intracellular cAMP was extracted with hydrochloric acid (HCl) and measured using a cAMP EIA kit following the manufacturer’s instruction (Assay Designs). Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) Total RNA was extracted from mouse cortex beneath the impact site 3 days after indicated treatments. The RNA was reverse transcribed with a high capacity RNA-to-cDNA kit (Applied Biosystems, Foster City, CA, USA) and amplified by qRT-PCR) in Roche Lightcycler 480 with a SYBR Green I Master kit (Roche Diagnostics, Indianapolis, IN, USA). The PCR program was preincubation at 95 °C, 5 min, followed by 45 cycles of 95 °C, 10 s, 60 °C, 10 s, and 72 °C, 10 s. The relative levels of each target gene were normalized to endogenous β-actin and calculated using comparative Ct method (ΔΔCt method) [18]. The primer sequences used were 5′-GAAGAGCCCATCCTCTGTGA-3′ (forward) and 5′-TTCATCTCGGAGCCTGTAGTG-3′ (reverse) for IL-1β; 5′-GGCTCAGCCAGATGCAGTTAA-3′ (forward) and 5′-CCTACTCATTGGGATCATCTTGT-3′ (reverse) for CCL2; 5′- GCCGTCATTTTCTGCCTCA-3′ (forward) and 5′-CGTCCTTGCGAGAGGGATC-3′ (reverse) for CXCL10; 5′- GGGCTGGCATTGTTCTCTAATGTC-3′ (forward) and 5′-GGATGGTAGCTGGAAGATCGAAAG-3′ (reverse) for ICAM-1; 5′-GTCTACTGAACTTCGGGGTGAT-3′ (forward) and 5′-ATGATCTGAGTGTGAGGGTCTG-3′ (reverse) for TNF-α; and 5′-CGAGGCCCAGAGCAAGAGAG-3′ (forward) and 5′-CGGTTGGCCTTAGGGTTCAG-3′ (reverse) for β-actin. Histological examination Mice were anesthetized and fixed by cardiac perfusion with cold PBS followed by 10 % formalin. Brains were carefully removed, fixed overnight in 10 % formalin, and subjected to histopathological processing and analysis. Hematoxylin and eosin (H&E)-stained sections of 5-μm-thickness were scanned by Nanozoomer Slide Scanner (Olympus America, Center Valley, PA). Immunofluorescence assays Acetone-fixed tissue sections were incubated with a blocking buffer (3 % BSA, 10 % goat serum and 0.4 % Triton X-100 in PBS) for 1 h at room temperature, followed with primary antibody diluted in the blocking buffer at 4 °C overnight. After reaction with a secondary antibody for 2 h at room temperature and washing, the slides were mounted with DAPI (4′, 6′-diamidino-2 phenylindole)-containing mounting medium (Invitrogen, USA). The primary antibody was rabbit anti-Caspase-3 (active) antibody at a 1:100 dilution (Millipore, USA) and rat anti-CD3 antibody at a 1:100 dilution (BioLegend, USA). TUNEL staining was carried out by an ApopTag® Fluorescein In Situ Apoptosis Detection Kit (Millipore, USA). Images were captured using a confocal microscope (Olympus FV1000, Olympus, Japan). Percentages of Caspase-3+ cells were determined by the number of Caspase-3+ cells relatively to DAPI+ cells in each field of the 20 randomly selected views of hippocampus area, which represented a total of ten sections from five injured brains in each group. Optical density of TUNEL staining was also calculated in 20 randomly selected views from a total of ten sections from five injured brains in each group by ImageJ software. Statistical analysis The data are presented as mean ± standard errors of measurement (SEM). The statistical analysis was performed using the non-parametric Mann-Whitney t test for comparison between two groups and one-way ANOVA or two-way ANOVA for comparison among multiple groups by the Graphpad Prism 6.0 software (GraphPad Software, CA, USA). A value of P < 0.05 was considered statistically significant. Results Elevation of cortisol but reduction of circulating lymphocytes following TBI Our previous study showed that introduction of inflammation worsened secondary brain damage following mTBI [7]. The mTBI was created by a gentle hit of the brain with an intact skull and scalp by a standard controlled impact, which resulted in extensive cell death at the impact site and significant neurologic severity score (NSS) ranging from 3 to 5 [7]. However, the abnormality was fully recovered functionally and histologically in 4 weeks [7], resembling the majority of mTBI in humans [7]. To determine contributing factors to the full recovery of mTBI, we measured plasma cortisol and found that this steroid hormone rose sharply 1 h post-TBI and declined thereafter (Fig. 1a), similar to what has been reported in patients suffering from traumatic injury or after surgery [12, 13]. In parallel to the elevated level of plasma cortisol was a transient but significantly diminished number of peripheral lymphocytes, with a 42 % decrease in 1 h after injury and a 20 % decrease in 4 h as compared to control mice (Fig. 1b). The decrease appeared to be more predominant in T cells than in B cells, with a 53 % decrease of T cells (Fig. 1c) compared to only a 28 % decrease of B cells (Fig. 1d) at 1 h post-injury. There were no significant differences in the number of circulating monocytes and neutrophils compared to controls at these time points examined. The finding that transient lymphocytopenia is inversely correlated with the amount of plasma cortisol in the animals is consistent with the well-documented immune suppression of cortisol [19].Fig. 1 Inverse relationship between cortisol and lymphocytes in blood following TBI. a Plasma cortisol was quantified before and 1 and 4 h after TBI. In parallel, the numbers of peripheral lymphocytes (b), T cells (c), and B cells (d) were analyzed at the same time points. A total number of leukocytes (e) or indicated cells (f) were measured in blood by flow cytometry 4 h after i.p. injection of 10 mg/kg hydrocortisone. Data are expressed as means ± SEM. n = 5 in (a) or 6 in (b, c, d, e, f). Significance was determined using one-way ANOVA (a, b, c, d) or non-parametric Mann-Whitney t test (e, f). *P < 0.05, **P < 0.01, ***P < 0.001, and NS, no significance compared before and after TBI or HC treatment. The experiment was repeated three times with similar results Exogenous hydrocortisone depresses the number of leukocytes in the periphery The inverse correlation between plasma cortisol and the number of circulating lymphocytes following mTBI raised an intriguing possibility that plasma cortisol might be directly responsible for TBI-induced lymphocytopenia. To determine this, mice were intraperitoneally administered hydrocortisone at a dose of 10 mg/kg followed by enumeration of circulating leukocytes. As shown in Fig. 1e, exogenous hydrocortisone reduced the number of leukocytes by 81 % in the periphery over the control mice in 4 h after administration. The reduction was most profound in T cells followed by B cells, neutrophils, and monocytes, all of which are key cellular components in the inflammatory cascade (Fig. 1f). These results corroborate that the reduced number of peripheral lymphocytes is ascribed directly to an elevated level of endogenous cortisol triggered by TBI. Hydrocortisone blocks T cell egress from the cortical sinus in lymph nodes Although cortisol is well known as a suppressant of inflammation, the underlying mechanism is not fully understood. Previous studies with 51Cr-labeled lymphocytes suggested that a decrease in egress of lymphocytes, rather than increased homing or cell death, was the mechanism for the lymphopenia induced by traumatic stress [20]. In support of this, flow cytometric analysis of peripheral T and B cells after propidium iodide (PI) staining did not reveal any significant difference in cell death in the mice (data not shown). We questioned whether cortisol blocked lymphocyte egress, lowering the number of peripheral lymphocytes as did immune suppression drug FTY720, an analog of S1P [15, 21, 22]. We thus tracked T cell egress in part because T cells were key contributors to the acute phase of brain injury [23] and the cells appeared to be more affected by cortisol. To this end, purified naive T cells were labeled with a red vital fluorescent dye CMTMR and infused into cognate mice followed by subcutaneous injection of LYVE-1 antibody to mark lymphatic vessels. The cortical sinusoid region in and adjacent to T cell zones of the popliteal lymph node was imaged 2 h later after hydrocortisone injection by intravital confocal microscopy as we previously described [15]. As can be seen in Fig. 3a, the number of T cells was severely reduced within the cortical sinusoid in the presence compared to the absence of hydrocortisone (Fig. 2a). Consistent with this, when tracking 200 cells in 10~15 randomly selected imaging stacks, we found that the frequency of T cells entering cortical sinusoids diminished to 15 from 45 % in the presence compared to the absence of hydrocortisone (Fig. 2b). On the contrary, T cells moving away from the sinusoids increased from 40 to 75 % in the mice (Fig. 2c). It can be envisioned that as a majority of T cells are moving away from the sinusoids, their egress could be largely prevented, explaining only few T cells within the sinusoids (Fig. 2a) and a reduced number of T cells in the periphery (Fig. 1f). Cortisol also reduced the ability of T cells to adhere on the sinusoids (Fig. 2e), in a good agreement with a low entry frequency (Fig. 2b), because T cell sticking to the sinusoid facilitated entry of the cell into a sinusoid [15]. During T cell egress, T cells continuously move toward and crawl along the sinusoid to search for a “hot entry port” and upon finding the “port,” the cell enters the sinusoid via it [24, 25], but many of them move away from the sinusoid prior to reaching it or after several attempts to associate with or adhere on the sinusoids [15, 26]. Hydrocortisone appeared not to affect the number of T cells that crawled on the sinusoids (Fig. 2d) but greatly increased the number of T cells moving away the sinusoids (Fig. 2c).Fig. 2 T cell egress is blocked by hydrocortisone. The representative images taken from control or hydrocortisone (HC)-treated mice are shown in (a). LYVE-1+ cortical sinuses are shown in blue pseudocolor in order to distinguish them with CMTMR labeled T cells (red) and the representative sinus area is delineated by a dotted white line. The dotted yellow line outlines the area within 30 μm of distance from the outer boundaries of cortical sinuses. Note: few T cells within cortical sinus in the presence of HC. Scale bar, 50 μm. Frequencies at which T cells entered (b), moved away (c), crawled on (d), or stuck to (e) (kept adhering to one point on the sinus wall and never displaced during the imaging period after they engaged the sinus) the cortical sinuses in control and HC-treated mice were calculated by manually tracking individual cells in each time-lapse image, with a total of 200 cells randomly selected in 10~15 imaging stacks. Each dot represents data from a single time-lapse image, and bars represent the means. Significance was measured using non-parametric Mann-Whitney t test. *P < 0.05, ***P < 0.001 in the presence or absence of hydrocortisone. Data are combined from two independent experiments each with two lymph nodes imaged in each treatment. The experiment was repeated two times with similar results S1P or rolipram increases the number of peripheral T cells after TBI We went on to determine whether a high level of S1P, an egress-promoting agent, could override cortisol-mediated blockade of T cell egress. We first assessed T cell migration toward S1P in the presence or absence of hydrocortisone in vitro, an assay that is commonly used for assessing S1P function [27]. T cells, along with hydrocortisone or vehicle, were added to the upper chamber and S1P or vehicle was included in the lower chamber of the transwell. As can be seen in Fig. 3a, S1P significantly increased migration of T cells into the lower chamber in the presence or absence of hydrocortisone, suggesting that a high level of S1P may overcome the inhibitory effect of hydrocortisone and restore the number of circulating T cells in mice with mTBI. Indeed, when mice were i.p. administered S1P immediately after TBI, the number of T cells was completely normalized in the blood 1 h post-S1P injection in TBI mice (Fig. 3c). In light of a well-established role for S1P in egress of lymphocytes, the result corroborates the ability of cortisol to block T cell egress, leading to a diminished number of lymphocytes in circulation immediately after mTBI. Moreover, the result also confirmed the ability of hydrocortisone to vigorously blunt T cell migration in the presence or absence of S1P (Fig. 3a), implicating that cortisol hampered T cell egress via an intrinsic signaling pathway of T cells, probably via regulation of cAMP degradation, a key secondary messenger molecule signaling downstream of the S1P1 receptor as depicted in Fig. 6. Our previous investigation showed that FTY720 blocked T cell egress by persistent activation of heterotrimeric Gαi proteins leading to prolonged inhibition of cAMP production, apart from induction of S1P1 receptor internalization [15]. We therefore measured cAMP after hydrocortisone treatment and found that hydrocortisone lowered cAMP levels significantly (Fig. 3b). The low level of cAMP induced by hydrocortisone was reversed by rolipram (Fig. 3b), a cAMP phosphodiesterase inhibitor that prevents cAMP degradation, corroborating an antagonistic effect of rolipram on cortisol-mediated reduction of cAMP, probably via the same target or the same signaling pathway as illustrated in Fig. 6. In support, i.p. injection of rolipram immediately after mTBI also significantly increased the number of T cells in the periphery, albeit to a much lesser degree in comparison with S1P (Fig. 3c). The results clearly suggest that hydrocortisone blocks T cell egress via a downstream target of the S1P1 receptor.Fig. 3 S1P or rolipram increases peripheral T cells in TBI mice. a T cell migration was analyzed in 48-well micro chemotaxis chamber, with 20 μM hydrocortisone or vehicle in the upper chamber and 20 nM S1P or vehicle in the lower chamber. The number of migrated cells was assessed 4 h later in the lower chambers. b T cells were pretreated with 10 μM rolipram or saline for 15 min and then with 100 μM hydrocortisone or vehicle treatment for 5 min, after which intracellular cAMP level was measured. c Peripheral T cells were measured before and 1 h after TBI. S1P or rolipram was i.p. injected immediately after TBI. Results are expressed as means ± SEM. n = 9 for (a), 6 for (c), or 4 for (b). Significance was determined using two- (a, b) or one-way (c) ANOVA. *P < 0.05, **P < 0.01, ***P < 0.001, and NS, no significance compared between indicated groups. The experiment was repeated three times with similar results A protective role for cortisol in TBI pathogenesis We next verified positive correlations of circulating lymphocytes with inflammation occurring at the impact site of the brain and directly associated the low inflammation at the injured site with cortisol-mediated blockade of lymphocyte egress in mTBI mice. To this end, several inflammatory mediators, including IL-1β, CCL2, CXCL10, ICAM-1, and TNF-α, were assayed by qRT-PCR at the impact site 3 days after mTBI in the presence or absence of SIP or rolipram [7]. Our previous study showed that mTBI up regulated proinflammatory mediators at 6 h and dwindled down gradually [7]. Consistent with this, transcription levels of these proinflammatory mediators in the mice were not significantly different from controls (Fig. 4). In contrast, S1P robustly bolstered all five inflammatory mediators at the impact sites, confirming a positive relationship between the number of circulating lymphocytes and inflammatory responses occurring at the impact brain tissues (Fig. 4 vs Fig. 3c). Moreover, out of the five inflammatory mediators tested, CCL2 and CXCL10 were also produced at levels significantly higher in TBI mice given rolipram than those mice given vehicle control or uninjured mice (Fig. 4a–c). Histologically, we observed no overt alterations in the gross morphology or at a low magnification on day 7 after injury either in presence or in absence of S1P or rolipram (Fig. 5a). But a robust increase in the number of morphologically abnormal cells was evidenced in the cerebral cortex (B) and hippocampus (C) beneath the injured site in TBI mice receiving S1P compared to TBI controls under a high magnification (Fig. 5b, c). Notably, healthy cell nuclei were relatively large consisting of several discernible nucleoli in the nucleoplasm in the cerebral neocortex and hippocampus in the absence of S1P or normal control mice (Fig. 5b, c). In contrast, morphologically abnormal cells were characterized by dark red staining of the nucleoplasm with eosin and presented only at the injured site (Fig. 5b, c, the third pannel). Although the types of these abnormal cells were unknown, probably both neurons and glias, the cells appeared undergoing apoptosis as revealed by two apoptotic markers, Caspase-3 and TUNEL staining. S1P significantly elevated Caspase-3 activation in the hippocampus (Fig. 5f, i) and TUNEL staining in the cerebral cortex (Fig 5g, j) in comparison with TBI only or controls. When rolipram was given, morphologically abnormal cells were also increased, but largely limited to the cerebral neocortex (Fig. 5b, c bottom). The apoptosis cells were also found both in the cortex (Fig 5g, j) and hippocampus (Fig. 5f, i) in TBI mice receiving rolipram albeit to a much lesser extent in comparison with S1P, consistent with less effect of rolipram on T cell egress in vivo (Fig. 3c). The increase of cell death at the injured site of the brain was proportionally correlated with T cell infiltration in the tissue as revealed by anti-CD3 antibody staining (Fig. 5d, e, h). T cells were hardly presented in the uninjured control mice or mice with mTBI, in agreement with a complete recovery of the injury in mTBI mice. However, the number of T cells increased robustly in the injured brain after i.p. injection of S1P and to a much lesser degree rolipram, as a consequence of elevating levels of T cells in circulation. The results conclude that a high level of peripheral lymphocytes can directly contribute to the heightened inflammation at the injured site of the brain in the early phase of TBI.Fig. 4 S1P or rolipram exaggerates inflammatory responses in injured brain. IL-1β (a), CCL2 (b), CXCL10 (c), ICAM-1 (d), and TNF-α (e) were analyzed at the impact site of the cerebral cortex in 3 days after TBI by qRT-PCR. The data are expressed as means ± SEM and normalized to β-actin. n = 5, significance was measured using one-way ANOVA. *P < 0.05, **P < 0.01, ***P < 0.001 and NS, no significance compared between indicated groups. ### P < 0.001 compared between TBI and TBI + rolipram in CCL2 and CXCL10 expression level by non-parametric Mann-Whitney t test. The experiment was repeated three times with similar results Fig. 5 A protective role for cortisol in TBI pathogenesis. a Histologic examination of normal control and injured brain at 7 days after TBI with or without administration of S1P or rolipram. The impact site was pointed by an arrow. The region of the cerebral cortex was highlighted in a dashed black line square and enlarged in panel (b); and the hippocampus was outlined by a dashed white line square and magnified in panel (c). Representative results of six mice in each group. d Representative immunofluorescence results of anti-CD3 antibody staining at hippocampus beneath the injured site and enlarged in panel (e). f Representative immunofluorescence staining for Caspase-3 expression at hippocampus beneath the injured site. g Representative TUNEL staining for apoptosis cells at the injury site. Percentages of CD3-positive cells in panel (e), Caspase-3-positive cells in panel (f), and optical density of TUNEL staining in panel (g) were determined by ImageJ and expressed as means ± SEM in (h), (i), or (j), respectively. n = 6, significance was measured using one-way ANOVA. *P < 0.05, **P < 0.01, ***P < 0.001 and NS, no significance compared between indicated groups. The experiment was repeated three times with similar results Discussion Brain has been viewed as an immune-privileged organ with little immunological and inflammatory activity under a physiological condition. This is primarily attributed to the relative impermeability of the blood-brain barrier (BBB) to cellular and molecular components of the immune and inflammatory reactions. However, upon brain injury, both immediate and secondary dysfunctions of the BBB occur as a consequence of disrupting the tight junction complexes and the integrity of the capillary basement membranes [9]. Neutrophils can be found aggregated in the microvasculature as early as 2 h post trauma [28]. Their infiltration in damaged neural tissue commences within 24 h [29], followed by macrophages within 36–48 h after trauma [30]. T lymphocytes have been shown to infiltrate the brain within 2–3 days post injury in a rat TBI model [31]. In those studies, severe or moderate TBI was induced via opening scalp and skull and infiltration of inflammatory cells was apparent [28–31], which is likely to be detrimental and associated with a severe loss of brain tissue and permanent impairment of cognitive neuron function [32]. Cortisol-mediated suppression of inflammation alone may be too weak to be effective in severe TBI. In contrast, mTBI was generated in our study with an intact scalp and skull and overt infiltration of inflammatory cells was not observed, which might be ascribed primarily to cortisol-mediated blockade of lymphocyte egress. In support of limiting inflammation at the injured site by cortisol-mediated blockade on lymphocyte egress at the initial phase of TBI, when the blockade was abolished by administering S1P, the number of circulating T cells was elevated significantly and positively correlated with increasing inflammatory responses (Fig. 4), T cell infiltration, and cell death (Fig. 5) at the impact site. The cortisol-mediated immune suppression observed in this TBI model is highly relevant to what happens in humans as a majority of mTBI recovers fully in humans in a few weeks. The observation hints that immediate immune suppression following TBI can prevent secondary brain damage and thus is beneficial to mTBI patients. Pre-clinical and clinical studies have supported the use of methylprednisolone, a glucocorticoid drug, as an acute neuroprotectant after acute spinal cord injury [33, 34]. Supplement with hydrocortisone post trauma also improves neurological recovery and leads to beneficial outcomes [35]. Moreover, progesterone, an indirect precursor of cortisol, has shown promise to be a neuroprotective agent, and it is currently under clinical trials for the treatment of TBI [36, 37]. The benefit of inhibiting T cell egress by cortisol is also consistent with a better outcome of cerebral ischemia in T cell-deficient mice than in wild-type controls [38]. Moreover, lymphocyte-deficient Rag1−/− mice are profoundly protected from stab wound injury of the cortex [39]. Apparently, the linkage between lymphocyte infiltration and adverse outcome post-TBI contradicts the key role of T cells in the reparative process. Several studies have shown that T cells are required for neurogenesis and depletion of T cells impairs neuronal cell proliferation [5, 40]. Perhaps, dynamic regulation of the timing and degree of lymphocyte infiltration is pivotal for its neuroprotection. Yet, despite the beneficial role, excess cortisol has adverse effects on mood, cognition, and neurodegeneration [41, 42]. It is thus necessary to monitor cortisol levels post injury and give it preferably to patients with corticosteroid insufficiency [41]. Alternatively, suboptimal FTY720 or anti-S1P antibody may be used to suppress lymphocyte egress at the early phase of TBI to prevent secondary brain damage [43, 44]. Cortisol is widely recognized for its role in the stress response and for its physiologic anti-inflammatory effects. The mechanism underlying its anti-inflammatory effects may be multifaceted including transcriptional suppression of proinflammatory genes [45, 46] and inhibition of the functions of macrophages and neutrophils [47], and the like. Exogenous glucocorticosteroid administration, especially in supraphysiological doses, also induces cell death of immature T and B cells, but mature T cells and activated B cells are resistant to cell death induced by cortisol at this low dose [48]. Because the number of circulating T cells could be restored in traumatic mice by S1P or rolipram (Fig. 3c), cortisol-induced T lymphocytopenia following TBI was unlikely ascribed to cell death. Our study demonstrating a blockade of T cell egress by cortisol adds a novel mechanism to our current understanding of the anti-inflammatory activity of this steroid hormone. Substantial evidence has shown that T cell egress is initiated by binding of S1P to the S1P1 receptor [21, 49]. The S1P1 receptor is a G protein-coupled receptor and activates exclusively heterotrimeric Gαi proteins that inhibit adenylate cyclase, leading to brief reduction of cAMP production followed by normalization and increases of cAMP in the cells (Fig. 6) [50]. On the contrary, FTY720 binds to the S1P1 receptor and causes the receptor internalization and prolonged reduction of cAMP, which promotes a sinus-moving away signal and blunts T cell egress [15]. The level of cAMP was lower in the presence than in the absence of hydrocortisone (Fig. 3b) but it was elevated by rolipram. Because rolipram can partially overcome the inhibitory effect of cortisol and increase cAMP levels in the presence of cortisol (Fig. 3b), cortisol may activate cAMP phosphodiesterase (PDE4) either directly or indirectly (Fig. 6). The secondary messenger cAMP is a signaling target downstream the S1P1 receptor, and thus, hydrocortisone inhibits T cell migration (Fig. 3c) or egress (Fig. 3c), at least in part, by lowering cAMP level in the cells independent of the S1P1 receptor.Fig. 6 Schematic illustration of a possible mechanism underlying cortisol-mediated blockade of T cell egress. cAMP is one of the important second messengers downstream the S1P1 receptor and its production takes central part in the control of T cell egress. One of the cortisol (HC) activities may activate cAMP phosphodiesterase (PDE4) either directly or indirectly and enhance degradation of cAMP to 5′-AMP. Cortisol-facilitated degradation of cAMP may be one of the mechanisms where cortisol compromises T cell egress in the presence of S1P. On the contrary, rolipram inhibits PDE4, leading to increased levels of cAMP and promoting T cell egress Conclusions We report here that following mTBI, plasma cortisol levels are significantly and transiently elevated, which appears to be directly responsible for the brief lymphocytopenia in the periphery by its ability to block lymphocyte egress from secondary lymphoid tissues. Abrogation of cortisol action on lymphocyte egress by injection of S1P or rolipram was associated with prolonged and increased inflammatory responses and elevated cell death and T cell infiltration at the injured site of the brain cortex, concluding that lymphocyte infiltration of brain in the early phase of brain injury is detrimental. The current work highlights a protective role of cortisol-induced immune suppression in the early phase of TBI and offers valuable information with respect to prevention of TBI soon after injury by a blockade of lymphocyte egress. Abbreviations TBITraumatic brain injury mTBIMild traumatic brain injury S1PSphingosine 1-phosphate LC-MS/MSLiquid chromatography-tandem mass spectrometry cAMPCyclic adenosine monophosphate IL-1αInterleukin-1-alpha IL6Interleukin-6 TNF-αTumor necrosis factor-alpha BBBBlood-brain barrier NSSNeurological severity score ACKAmmonium-chloride-potassium HClHydrochloric acid BSABovine serum albumin H&EHematoxylin and eosin DAPI4′, 6′-diamidino-2 phenylindole PBSPhosphate-buffered saline qRT-PCRQuantitative reverse-transcription polymerase chain reaction TUNELTerminal deoxynucleotidyl transferase dUTP nick end labeling CMTMR5-(and-6)-(((4-chloromethyl) benzoyl) amino) tetramethylrhodamine PMTPhotomultiplier tubes SEMStandard errors of measurement HCHydrocortisone PIPropidium iodide IL-1βInterleukin-1-beta CCL2Chemokine (C-C motif) ligand 2 CXCL10C-X-C motif chemokine 10 ICAM-1Intercellular adhesion molecule 1 PDE4Phosphodiesterase Acknowledgements The authors would like to thank members of the Photopathology Core at Wellman Center for the experimental assistance with the histopathology, flow cytometry, and microscopy services. Funding This work is supported by FA9550-11-1-0415 and FA9550-13-1-0068, Department of Defense/Air Force Office of Scientific Research Militory Photomedicine Program, W81XWH-13-2-0067, Department of Defense, CDMRP/BAA, and the fund of Wellman Center for Photomedicine to MXW. Availability of data and materials No data will be shared. The current manuscript does not currently use any software, database (including arrays), or method necessary to be freely available to public. Authors’ contributions TD and LZ designed and performed the research and analyzed the data. BB and TD wrote the manuscript. MXW designed and supervised the research and wrote the manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of the Massachusetts General Hospital and performed according to the National Institutes of Health guidelines for the Care and Use of Laboratory Animals. ==== Refs References 1. Selassie AW Zaloshnja E Langlois JA Miller T Jones P Steiner C Incidence of long-term disability following traumatic brain injury hospitalization, United States, 2003 J Head Trauma Rehabil 2008 23 2 123 31 10.1097/01.HTR.0000314531.30401.39 18362766 2. Bramlett HM Dietrich WD Progressive damage after brain and spinal cord injury: pathomechanisms and treatment strategies Prog Brain Res 2007 161 125 41 10.1016/S0079-6123(06)61009-1 17618974 3. Marklund N Bakshi A Castelbuono DJ Conte V McIntosh TK Evaluation of pharmacological treatment strategies in traumatic brain injury Curr Pharm Des 2006 12 13 1645 80 10.2174/138161206776843340 16729876 4. Finnie JW Neuroinflammation: beneficial and detrimental effects after traumatic brain injury Inflammopharmacology 2013 21 4 309 20 10.1007/s10787-012-0164-2 23296919 5. Ziv Y Ron N Butovsky O Landa G Sudai E Greenberg N Immune cells contribute to the maintenance of neurogenesis and spatial learning abilities in adulthood Nat Neurosci 2006 9 2 268 75 10.1038/nn1629 16415867 6. Wieloch T Nikolich K Mechanisms of neural plasticity following brain injury Curr Opin Neurobiol 2006 16 3 258 64 10.1016/j.conb.2006.05.011 16713245 7. Zhang Q Zhou C Hamblin MR Wu MX Low-level laser therapy effectively prevents secondary brain injury induced by immediate early responsive gene X-1 deficiency J Cereb Blood Flow Metab 2014 34 8 1391 401 10.1038/jcbfm.2014.95 24849666 8. Morganti-Kossman MC Lenzlinger PM Hans V Stahel P Csuka E Ammann E Production of cytokines following brain injury: beneficial and deleterious for the damaged tissue Mol Psychiatry 1997 2 2 133 6 10.1038/sj.mp.4000227 9106236 9. Bradbury MW The blood-brain barrier Exp Physiol 1993 78 4 453 72 10.1113/expphysiol.1993.sp003698 8398100 10. Cederberg D Siesjo P What has inflammation to do with traumatic brain injury? Childs Nerv Syst 2010 26 2 221 6 10.1007/s00381-009-1029-x 19940996 11. Clausen F Lorant T Lewen A Hillered L T lymphocyte trafficking: a novel target for neuroprotection in traumatic brain injury J Neurotrauma 2007 24 8 1295 307 10.1089/neu.2006.0258 17711391 12. Santarsieri M Niyonkuru C McCullough EH Dobos JA Dixon CE Cerebrospinal fluid cortisol and progesterone profiles and outcomes prognostication after severe traumatic brain injury J Neurotrauma 2014 31 8 699 712 10.1089/neu.2013.3177 24354775 13. Wagner AK McCullough EH Niyonkuru C Ozawa H Loucks TL Acute serum hormone levels: characterization and prognosis after severe traumatic brain injury J Neurotrauma 2011 28 6 871 88 10.1089/neu.2010.1586 21488721 14. Dong T Zhang Q Hamblin MR Wu MX Low-level light in combination with metabolic modulators for effective therapy of injured brain J Cereb Blood Flow Metab 2015 35 9 1435 44 10.1038/jcbfm.2015.87 25966949 15. Zhi L Kim P Thompson BD Pitsillides C Bankovich AJ Yun SH FTY720 blocks egress of T cells in part by abrogation of their adhesion on the lymph node sinus J Immunol 2011 187 5 2244 51 10.4049/jimmunol.1100670 21788441 16. Kim P Puoris’haag M Cote D Lin CP Yun SH In vivo confocal and multiphoton microendoscopy J Biomed Opt 2008 13 1 010501 10.1117/1.2839043 18315346 17. Thompson BD Jin Y Wu KH Colvin RA Luster AD Birnbaumer L Inhibition of G alpha i2 activation by G alpha i3 in CXCR3-mediated signaling J Biol Chem 2007 282 13 9547 55 10.1074/jbc.M610931200 17289675 18. Schmittgen TD Livak KJ Analyzing real-time PCR data by the comparative C(T) method Nat Protoc 2008 3 6 1101 8 10.1038/nprot.2008.73 18546601 19. Coutinho AE Chapman KE The anti-inflammatory and immunosuppressive effects of glucocorticoids, recent developments and mechanistic insights Mol Cell Endocrinol 2011 335 1 2 13 10.1016/j.mce.2010.04.005 20398732 20. Bolton PM Kirov SM Donald KJ The effects of major and minor trauma on lymphocyte kinetics in mice Aust J Exp Biol Med Sci 1979 57 479 92 10.1038/icb.1979.49 317644 21. Matloubian M Lo CG Cinamon G Lesneski MJ Xu Y Brinkmann V Lymphocyte egress from thymus and peripheral lymphoid organs is dependent on S1P receptor 1 Nature 2004 427 6972 355 60 10.1038/nature02284 14737169 22. Graler MH Goetzl EJ The immunosuppressant FTY720 down-regulates sphingosine 1-phosphate G-protein-coupled receptors FASEB J 2004 18 3 551 3 14715694 23. Kelso ML Gendelman HE Bridge between neuroimmunity and traumatic brain injury Curr Pharm Des 2014 20 26 4284 98 24025052 24. Grigorova IL Schwab SR Phan TG Pham TH Okada T Cyster JG Cortical sinus probing, S1P1-dependent entry and flow-based capture of egressing T cells Nat Immunol 2009 10 1 58 65 10.1038/ni.1682 19060900 25. Wei SH Rosen H Matheu MP Sanna MG Wang SK Jo E Sphingosine 1-phosphate type 1 receptor agonism inhibits transendothelial migration of medullary T cells to lymphatic sinuses Nat Immunol 2005 6 12 1228 35 10.1038/ni1269 16273098 26. Sinha RK Park C Hwang IY Davis MD Kehrl JH B lymphocytes exit lymph nodes through cortical lymphatic sinusoids by a mechanism independent of sphingosine-1-phosphate-mediated chemotaxis Immunity 2009 30 3 434 46 10.1016/j.immuni.2008.12.018 19230723 27. Sensken SC Nagarajan M Bode C Graler MH Local inactivation of sphingosine 1-phosphate in lymph nodes induces lymphopenia J Immunol 2011 186 6 3432 40 10.4049/jimmunol.1002169 21289303 28. Schoettle RJ Kochanek PM Magargee MJ Uhl MW Nemoto EM Early polymorphonuclear leukocyte accumulation correlates with the development of posttraumatic cerebral edema in rats J Neurotrauma 1990 7 4 207 17 10.1089/neu.1990.7.207 2127947 29. Soares HD Hicks RR Smith D McIntosh TK Inflammatory leukocytic recruitment and diffuse neuronal degeneration are separate pathological processes resulting from traumatic brain injury J Neurosci 1995 15 12 8223 33 8613756 30. Giulian D Chen J Ingeman JE George JK Noponen M The role of mononuclear phagocytes in wound healing after traumatic injury to adult mammalian brain J Neurosci 1989 9 12 4416 29 2480402 31. Holmin S Mathiesen T Shetye J Biberfeld P Intracerebral inflammatory response to experimental brain contusion Acta Neurochir (Wien) 1995 132 1-3 110 9 10.1007/BF01404857 7754844 32. Marklund N Hillered L Animal modelling of traumatic brain injury in preclinical drug development: where do we go from here? Br J Pharmacol 2011 164 4 1207 29 10.1111/j.1476-5381.2010.01163.x 21175576 33. Bracken MB Shepard MJ Collins WF Holford TR Young W Baskin DS A randomized, controlled trial of methylprednisolone or naloxone in the treatment of acute spinal-cord injury. Results of the Second National Acute Spinal Cord Injury Study N Engl J Med 1990 322 20 1405 11 10.1056/NEJM199005173222001 2278545 34. Bracken MB Shepard MJ Collins WF Jr Holford TR Baskin DS Eisenberg HM Methylprednisolone or naloxone treatment after acute spinal cord injury: 1-year follow-up data. Results of the second National Acute Spinal Cord Injury Study J Neurosurg 1992 76 1 23 31 10.3171/jns.1992.76.1.0023 1727165 35. Chen X Zhao Z Chai Y Luo L Jiang R Dong J Stress-dose hydrocortisone reduces critical illness-related corticosteroid insufficiency associated with severe traumatic brain injury in rats Crit Care 2013 17 5 R241 10.1186/cc13067 24131855 36. Wright DW Kellermann AL Hertzberg VS Clark PL Frankel M Goldstein FC ProTECT: a randomized clinical trial of progesterone for acute traumatic brain injury Ann Emerg Med 2007 49 4 391 402 10.1016/j.annemergmed.2006.07.932 17011666 37. Xiao G Wei J Yan W Wang W Lu Z Improved outcomes from the administration of progesterone for patients with acute severe traumatic brain injury: a randomized controlled trial Crit Care 2008 12 2 R61 10.1186/cc6887 18447940 38. Hurn PD Subramanian S Parker SM Afentoulis ME Kaler LJ Vandenbark AA T- and B-cell-deficient mice with experimental stroke have reduced lesion size and inflammation J Cereb Blood Flow Metab 2007 27 11 1798 805 10.1038/sj.jcbfm.9600482 17392692 39. Fee D Crumbaugh A Jacques T Herdrich B Sewell D Auerbach D Activated/effector CD4+ T cells exacerbate acute damage in the central nervous system following traumatic injury J Neuroimmunol 2003 136 1-2 54 66 10.1016/S0165-5728(03)00008-0 12620643 40. Wolf SA Steiner B Akpinarli A Kammertoens T Nassenstein C Braun A CD4-positive T lymphocytes provide a neuroimmunological link in the control of adult hippocampal neurogenesis J Immunol 2009 182 7 3979 84 10.4049/jimmunol.0801218 19299695 41. De Kloet ER Hormones and the stressed brain Ann N Y Acad Sci 2004 1018 1 15 10.1196/annals.1296.001 15240347 42. Lupien SJ Maheu F Tu M Fiocco A Schramek TE The effects of stress and stress hormones on human cognition: implications for the field of brain and cognition Brain Cogn 2007 65 3 209 37 10.1016/j.bandc.2007.02.007 17466428 43. O’Brien N Jones ST Williams DG Cunningham HB Moreno K Production and characterization of monoclonal anti-sphingosine-1-phosphate antibodies J Lipid Res 2009 50 11 2245 57 10.1194/jlr.M900048-JLR200 19509417 44. Brinkmann V FTY720 (fingolimod) in multiple sclerosis: therapeutic effects in the immune and the central nervous system Br J Pharmacol 2009 158 5 1173 82 10.1111/j.1476-5381.2009.00451.x 19814729 45. Clark AR Anti-inflammatory functions of glucocorticoid-induced genes Mol Cell Endocrinol 2007 275 1-2 79 97 10.1016/j.mce.2007.04.013 17561338 46. Reichardt HM Schutz G Glucocorticoid signalling—multiple variations of a common theme Mol Cell Endocrinol 1998 146 1-2 1 6 10.1016/S0303-7207(98)00208-1 10022757 47. Tuckermann JP Kleiman A Moriggl R Spanbroek R Neumann A Illing A Macrophages and neutrophils are the targets for immune suppression by glucocorticoids in contact allergy J Clin Invest 2007 117 5 1381 90 10.1172/JCI28034 17446934 48. Cox JH Ford WL The migration of lymphocytes across specialized vascular endothelium. IV. Prednisolone acts at several points on the recirculation pathways of lymphocytes Cell Immunol 1982 66 2 407 22 10.1016/0008-8749(82)90190-3 6279318 49. Pappu R Schwab SR Cornelissen I Pereira JP Regard JB Xu Y Promotion of lymphocyte egress into blood and lymph by distinct sources of sphingosine-1-phosphate Science 2007 316 5822 295 8 10.1126/science.1139221 17363629 50. Rosen H Goetzl EJ Sphingosine 1-phosphate and its receptors: an autocrine and paracrine network Nat Rev Immunol 2005 5 7 560 70 10.1038/nri1650 15999095

PMC005xxxxxx/PMC5000453.txt

==== Front BMC Complement Altern MedBMC Complement Altern MedBMC Complementary and Alternative Medicine1472-6882BioMed Central London 131510.1186/s12906-016-1315-6Research ArticleGlucosamine sulfate suppresses the expression of matrix metalloproteinase-3 in osteosarcoma cells in vitro http://orcid.org/0000-0002-8867-2973Pohlig Florian Florian.Pohlig@mri.tum.de Ulrich Jörg Lenze Ulrich Mühlhofer Heinrich M. L. Harrasser Norbert Suren Christian Schauwecker Johannes Mayer-Kuckuk Philipp von Eisenhart-Rothe Rüdiger Department of Orthopedic Surgery, Klinikum rechts der Isar, Technical University Munich, Ismaninger Str. 22, 81675 Munich, Germany 25 8 2016 25 8 2016 2016 16 1 3136 4 2016 23 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Glucosamine, a common dietary supplement, has a possible anti-sarcoma effect. However, an understanding of the underlying mechanism of such an effect is limited. For this study we hypothesized that glucosamine suppresses the basal level of matrix metalloproteinase expression in human osteosarcoma cell lines. Methods We examined the osteosarcoma cell lines, MG-63 and SaOS-2. Cells were exposed to 0, 10, 50 and 100 μg/ml glucosamine sulfate for 48 h and treatment toxicity was determined through measurement of cell viability and proliferation. Relative gene expression of matrix metalloproteinase (MMP)-2, -3 and -9 was quantified by real-time polymerase chain reaction. Protein levels of MMP-2 and -9 were assessed by ELISA. Results Administration of 10, 50 or 100 μg/ml glucosamine sulfate had no effect on the cell viability of MG-63 and SaOS-2 cells. A significant reduction of MMP expression in both cell lines was observed only for MMP-3, while a decrease in MMP-9 was seen in SaOS-2 cells. The expression of MMP-2 was not significantly affected in either cell line. Protein level of MMP-3 was reduced in both cell lines upon stimulation with 10 μg/ml glucosamine sulfate whereas for MMP-9 a decrease could only be observed in SaOS-2 cells. Conclusion In this study, we found a pronounced suppressive effect of glucosamine sulfate particularly on MMP-3 and also MMP-9 mRNA and protein levels in osteosarcoma cell lines in vitro. The data warrants further investigations into the potential anti-tumor efficacy of glucosamine sulfate in osteosarcoma. Electronic supplementary material The online version of this article (doi:10.1186/s12906-016-1315-6) contains supplementary material, which is available to authorized users. Keywords Glucosamine sulfateNeutraceuticalDietary supplementOsteosarcomaMatrix metalloproteinaseMMP-3MMP-9issue-copyright-statement© The Author(s) 2016 ==== Body Background In a landmark preclinical study Quastel and Cantero examined the effect of glucosamine on tumor growth in vivo [1]. They observed that daily administration of glucosamine reduced tumor growth and prolonged overall survival in mice bearing sarcoma 37 tumors [1]. Importantly, no toxicity was associated with the glucosamine treatment. More recently, extended clinical trials in more common tumor types underscored the potential anti-tumor effect of glucosamine in patients [2]. For example, the prospective VITamins And Lifestyle (VITAL) study showed that dietary glucosamine supplementation of glucosamine reduces the incidence of colorectal and lung cancer by more than 25 %, resulting in a 13 % reduction in cancer mortality [3, 4]. Despite the evidence for a possible anti-sarcoma effect of nutritional glucosamine supplementation, our understanding of the underlying mechanisms is limited. Early studies by Molnar et al. were restricted to describing the morphological changes that occur in Sarcoma 180 cells, a transplantable mouse sarcoma isolated from ascites [5, 6]. More recent work by Gervasi and co-workers, has investigated the effect of glucosamine supplementation in human HT1080 fibrosarcoma cells. They found that treatment with N-acetyl-D-glucosamine reduces concanavalin A-induced matrix metalloproteinase (MMP)-2 activity [7]. These findings have been corroborated by two studies conducted in Kim’s laboratory; these studies show that an amino derivative of glucosamine reduces phorbol 12-myristate 13-acetate (PMA)-induced upregulation of MMP-2 and MMP-9 in HT-1080 cells was reduced in the presence of an amino derivative of glucosamine [8, 9]. They also demonstrated that glucosamine derivatives suppress MMP-2 and -9 gene expression in addition to decreasing the proteolytic processing of MMP precursors [8, 9]. Further, work by Lin et al. has shown that glucosamine represses interleukin-1ß (Il1ß)-induced expression of MMP-3 in the SW-1353 chondrosarcoma cell line [10]. Interestingly, despite of numerous regulatory processes from MMP gene expression to the active enzyme, previous studies with colorectal and breast cancer specimens showed a close correlation between the level of gene expression and disease-free survival [11, 12]. Based on these studies, we hypothesized that (1) the reported effects of glucosamine are most probably not limited to the reported sarcoma cell types and may extend to osteosarcoma cells, (2) glucosamine suppresses the basal expression of MMPs in the absence of specific MMP inducers such as concanavalin A or PMA, and (3) glucosamine potentially suppresses MMP-3, MMP-9 and MMP-2 expression to different extents. Herein, we report, for the first time, that glucosamine sulfate exerts a pronounced suppressive effect on MMPs, particularly on MMP-3 and -9 in osteosarcoma cell lines in vitro. Methods Materials All reagents were purchased from Sigma Aldrich (Sigma-Aldrich, St. Louis, USA) unless stated otherwise. Nutritional grade glucosamine sulfate powder (2(C6H13NO5).H2SO4) was purchased from Vita Natura (Bonn, Germany). A glucosamine sulfate solution was prepared to a final concentration of 100 μg/ml in cell culture medium (detailed below). The solution was sterile filtered, aliquoted, and stored at −20 °C until further use. Cell culture MG-63 osteosarcoma cells were obtained from the American Type Culture Collection (ATCC, Manassas, USA). SaOS-2 cells were purchased from Deutsche Sammlung für Mikroorganismen (DMSZ, Braunschweig, Germany). Both cell lines were cultured as a monolayer in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 1 % MEM-Vitamine, 1 % glutamine, 10 % fetal bovine serum (FBS), 1 U/mL penicillin/streptomycin and 2 % HEPES buffer (all obtained from Biochrom, Berlin, Germany) at 37 °C and 5 % CO2. Cells were passaged at 80–90 % confluency and culture medium was replaced every second day. Glucosamine sulfate treatment Treatments were performed in a 6 well plates. MG-63 (2 × 106) and SaOS-2 (4 × 106) were seeded in 3 ml of medium and cultured for 24 h. Different seeding densities were used to compensate for the higher proliferation rate of MG-63 cells. The following day, the medium was replaced with fresh medium containing 2 % FBS and a final concentration of 10, 50 or 100 μg/ml glucosamine sulfate (achieved with a 1:9, 1:1 and 1:0 dilution of the glucosamine stock solution) and cells were incubated for 48 h. Following the incubation period, cells were dissociated with trypsin, counted and collected by centrifugation. RNA was then isolated from the cell pellets as described below. Toxicity assay To detect potential toxicity associated with glucosamine sulfate treatment and exclude a downregulation of mRNA and protein expression due to cytotoxic cell death, a WST-1 cytotoxicity assay (Roche, Mannheim, Germany) was performed. Briefly, 2 × 105 MG-63 and 4 × 105 SaOS-2 were seeded in 200 μL medium in 48 well plates. Cells were then stimulated with different concentrations of glucosamine sulfate for 48 h (described above) prior to addition of 20 μl of WST reagent were added. Plates were incubated for 2 h before absorption was measured at 450 nm and a reference wavelength of 690 nm. Quantitative gene expression analysis RNA was isolated from cells using the RNeasy Tissue Kit® (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. In brief, MG-63 or SaOS-2 cells were resuspended in RLT buffer, transferred to a Qiashredder® and then lysed. RNA from lysates was immobilized on a silica matrix and eluted with distilled water. Harvested RNA was quantified by photometry. Isolated RNA was transcribed to cDNA using QuantiTect® Reverse Transcriptions Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. The relative gene expression of MMP-2, -3 and -9 was quantified by real-time polymerase chain reaction (PCR) using a thermo cycler with TaqMan® Array and specific primers (MMP-2: Hs01548727_m1; MMP-3: Hs01548727_m1; MMP-9: Hs01548727_m1; glyceraldehyde 3-phosphate dehydrogenase (GAPDH): NM_002046.3) (Applied Biosystems, Grand Island, USA). GAPDH was used as internal control. The thermal cycler conditions were: 40 cycles consisting of a 15 s denaturation phase at 95 °C and a combined 1 min annealing and extension phase at 60 °C. Enzyme-linked immunosorbent assay (ELISA) Protein analysis was performed from cells stimulated with 10 μg/ml glucosamine sulfate. After washing with PBS, a precipitation step with acetone and resuspension with cell extraction buffer (Invitrogen™, Frederick, USA) was performed. Sandwich ELISA Kits for human MMP-3 and MMP-9 (Invitrogen™, Frederick, USA) were used for quantitative analysis according to the manufacturer’s instructions. In brief, 50 μl of diluted cell lysate was transferred to each microplate well previously coated with monoclonal antibody. After incubation with MMP-3 and MMP-9 specific detection antibodies as well as substrate solution the enzyme concentration was quantified spectrophotometrically in an ELISA Reader at 450 nm. Statistics Quantitative PCR and ELISA data were compared using SPSS software (IBM, Armonk, USA) and the t-test for unpaired samples. The results are shown as mean ± standard deviation. A p-value of ≤0,05 was considered statistically significant. Results To assess the effect of glucosamine sulfate on MMP expression, glucosamine sulfate concentrations of 10 μg/ml, 50 μg/ml and 100 μg/ml were used. These concentrations were based on previous reports [8, 13]. Prior to quantitative analysis of MMP gene and protein expression, the potential cytotoxicity of the glucosamine sulfate treatment was examined. Glucosamine sulfate treatment did not significantly reduce the viability of either MG-63 (Fig. 1a) or Saos-2 (Fig. 1b) cells, indicating that the examined concentrations were not toxic.Fig. 1 Cell viability as absorbance at A450–A690 in a WST-1 assay in the unstimulated control and upon administration of 10, 50 and 100 μg/ml glucosamine sulfate in MG-63 (a) and SaOS-2 cells (b); a statistical comparism was carried out for the control and each of the glucosamine sulfate treated groups; * indicates statistical significance with p ≤ 0,05 Subsequent analysis of MMP gene expression in response to 10 μg/ml glucosamine sulfate administration demonstrated a significant reduction of MMP-3 by approximately 68 % in MG-63 cells (p = 0,037) and 63 % in SaOS-2 cells (p = 0,003) compared to the untreated control (Fig. 2). Although MMP-9 expression was not significantly reduced in MG-63 cells, it was significantly reduced by approximately 34 % in SaOS-2 cells (p = 0,04; Fig. 2). Our analysis indicated that 10 μg/ml of glucosamine sulfate has no significant effect on MMP-2 gene expression in either MG-63 or Saos-2 cells (Fig. 2). Increasing the glucosamine sulfate concentration to 50 μg/ml significantly reduced MMP-3 gene expression by approximately 74 % in MG-63 cells (p = 0,021), while the reduction of MMP-3 in Saos-2 cells did not reach significance (Fig. 3). The expression of MMP-9 and MMP-2 was not significantly altered by 50 μg/ml glucosamine sulfate in either cell line (Fig. 3). Similar to the effect of 50 μg/ml glucosamine sulfate on MMP-3 expression in MG-63 cells, administration of 100 μg/ml resulted in a significant decrease of MMP-3 expression by about 73 % in MG-63 cells (p = 0,021; Fig. 4). However, the gene expressions of MMP-9 and MMP-2 were not significantly altered by 100 μg/ml glucosamine sulfate.Fig. 2 Relative gene expression of MMP-3, -9 and -2 in MG-63 and SaOS-2 cells upon administration of 10 μg/ml glucosamine sulfate; a statistical comparism was carried out for the control and each of the glucosamine sulfate treated groups; * indicates statistical significance with p ≤ 0,05 Fig. 3 Relative gene expression of MMP-3, -9 and -2 in MG-63 and SaOS-2 cells upon administration of 50 μg/ml glucosamine sulfate; a statistical comparism was carried out for the control and each of the glucosamine sulfate treated groups; * indicates statistical significance with p ≤ 0,05 Fig. 4 Relative gene expression of MMP-3, -9 and -2 in MG-63 and SaOS-2 cells upon administration of 100 μg/ml glucosamine sulfate; a statistical comparism was carried out for the control and each of the glucosamine sulfate treated groups; * indicates statistical significance with p ≤ 0,05 Protein expression analysis demonstrated similar results. Upon administration of 10 μg/ml glucosamine sulfate MMP-3 protein level was reduced by about 23 % in MG-63 (p = 0,60) and 28 % in SaOS-2 cells (p = 0,38) (Fig. 5a). MMP-9 revealed an insignificant increase of approximately 22 % upon stimulation with 10 μg/ml GlS in MG-63 cells (p = 0,54). SaOS-2 cells exhibited a decrease of MMP-9 protein level of about 29 % (p = 0,49) (Fig. 5b).Fig. 5 Protein levels as absorbance at A450–A690 in an ELISA assay of (a) MMP-3 and (b) MMP-9 in MG-63 and SaOS-2 cells upon administration of 10 μg/ml glucosamine sulfate; * indicates statistical significance with p ≤ 0,05 Discussion In this study, we observed that (1) glucosamine sulfate inhibits MMP gene and protein expressions in MG-63 and SaOS-2 osteosarcoma cell lines, (2) glucosamine sulfate suppresses basal MMP expression in osteosarcoma cells, and (3) glucosamine sulfate most significantly affects MMP-3 expression compared to MMP-9 and MMP-2. MMPs are overexpressed in many different types of cancer, and consequently these proteinases are frequently investigated therapeutic target [14]. To date, a considerable number of pharmacological MMP inhibitors have been developed and tested in clinical trials [15]. However, their therapeutic efficacy thus far has proved limited [16]. The potential reasons for this lack of efficacy include: (1) limitations associated with the extensive homology between MMP catalytic domains; none of the tested drugs have been highly selective for specific MMPs, which could result in anti-tumor MMPs being inhibited; (2) unanticipated long-term drug intolerance that can reduce drug compliance; (3) the exclusion of early-stage cancer patients from clinical trials; these patients are anticipated to benefit most from MMP blockade; and (4) the drug doses used have been based on short-term kinetic studies in healthy volunteers and are not necessarily predictive of chronic therapeutic drug levels in cancer [16]. Thus, alternative strategies for MMP inhibition in cancer patients are of considerable interest. In the present study, we demonstrate that a relatively low concentration of 10 μg/ml glucosamine sulfate reduces MMP-3 expression more than 50 % in both of the osteosarcoma cell lines investigated. This finding is particularly relevant because recent work by Tsai et al. found that MMP-3 is overexpressed in human osteosarcomas [17]. Further, their data identified miR-519d down-regulation via connective tissue growth factor (CTGF) signaling as a pathway osteosarcoma cells utilize to upregulate MMP-3 and MMP-2 expression [17]. But also mitogen-activated protein kinase (MAPK) pathways seem to play a pivotal role in mediating inflammatory and oncogenic signals and consequently inducing MMP-3 expression [18]. In this context Scotto d’Abuso and coworkers identified a decreased phosphorylation of c-jun-amino-terminal kinase (JNK) and p38 in human chondrocytes upon stimulation with glucosamine [19]. Moreover, their study showed a decreased activity of c-jun and junD depicting important transcription factors of MMPs [19]. The decreased phosphorylation of MAPKs by glucosamine may, in turn, be explained by coupling of N-acetylated glucosamine (N-acetylglucosamine) to serine or threonine residues of those proteins [19]. This O-glycosylation is thought to act in a manner analogous to phosphorylation [20, 21]. In support of these findings, recent clinical studies have demonstrated a close correlation between MMP-3 expression and the development of lung metastases in breast and lung cancers [22, 23]. In our study, which analized the expression of three MMPs, we found that glucosamine sulfate treatment exerted an unexpectedly specific effect. For example, the expression of MMP-3 was significantly reduced by glucosamine sulfate, but MMP-2 expression was not. In fact, a modest, yet statistically insignificant, increase was seen. Although these observations require further investigations, they suggest, that glucosamine sulfate is not a broad MMP inhibitor, but may rather be useful for more specific MMP suppression. The data presented here support the potential use of glucosamine sulfate as a nutritional supplement in osteosarcoma patients for two main reasons. First, the glucosamine used in this study was a commercially available dietary glucosamine, formulated as glucosamine sulfate, which, together with glucosamine hydrochloride constitutes the principle nutritional formulation for glucosamine supplements [24, 25]. Previous studies have used either the non-dietary quaternized amino glucosamine [9] and N-acetyl-D-glucosamine [7], or sulfated glucosamine synthesized in-house [8]. Second, the most pronounced effect of glucosamine sulfate was observed at a concentration of 10 μg/ml. This concentration is within the range of the human serum concentrations that can be achieved with oral glucosamine intake, as previously published by Biggee et al. [26]. As such, it can be foreseen that glucosamine sulfate supplementation during osteosarcoma treatment could have a potentially beneficial effect. Upon diagnosis the vast majority of patients are treated with multi-agent neoadjuvant chemotherapy, followed by wide surgical resection of the tumor and adjuvant chemotherapy. Such regimes result in excellent primary tumor control, however, pulmonary metastases, which are challenging to control, develop in more than 30 % of patients [27]. One of the advantages of glucosamine of glucosamine dietary supplementation in osteosarcoma patients is that it will, most likely, integrate seamlessly into the standard treatment protocol. Other advantages of glucosamine dietary supplementation, namely the lack of toxicity, unrestricted availability, and low treatment costs this would enable supplementation to start permit upon initial diagnosis and continue over long periods of time, past primary tumor treatment. This may eventually reduce the incidence of pulmonary metastasis from osteosarcoma. As such, we anticipate that glucosamine sulfate treatment during osteosarcoma therapy will receive further attention, similar to the renewed interest in other nutraceuticals in augmenting standard cancer therapy [28]. However, we appreciate that the nutritional translation of the present findings will require a substantial further investigations in vitro and in preclinical models. Conclusion In conclusion, we have shown that glucosamine sulfate exerts a pronounced suppressive effect on MMPs in osteosarcoma cell lines in vitro; this effect was most pronounced for MMP-3 and MMP-9 to a lesser extent. The data warrants further studies into the potential antitumor effect of glucosamine sulfate in osteosarcoma. Additional file Additional file 1: Minimal data set underlying our findings. (XLSX 35 kb) Abbreviations CTGFConnective tissue growth factor DMEMDulbecco’s Modified Eagle Medium ELISAEnzyme-linked immunosorbent assay FBSFetal bovine serum GAPDHGlyceraldehyde 3-phosphate dehydrogenase Il1ßInterleukin-1ß JNKc-jun-amino-terminal kinase MAPKMitogen-activated protein kinase MMPMatrix metalloproteinase PCRPolymerase chain reaction PMAPhorbol 12-myristate 13-acetate Acknowledgements None. Funding The present study was funded by the authors’ institution. Availability of data and materials A minimal data set underlying our findings has been added as Additional file 1. Authors’ contributions Conception and design of the study: FP, UL, JS, JU. Generation, collection, assembly, analysis and/or interpretation of data: JU, FP, NH, HMLM, CS, UL. Drafting and revising the manuscript: FP, PMK, CS, RvER, HMLM, NH. Approval of the final version of the manuscript: PMK, RvER, JS, FP. All authors read and approved the final manuscript. Competing interests All authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate In the present study only commercially available cells were used and no human or animal subjects were involved. Thus no approval by an institutional review board and no consent to participate were required. ==== Refs References 1. Quastel JH Cantero A Inhibition of tumour growth by D-glucosamine Nature 1953 171 4345 252 254 10.1038/171252a0 13036842 2. Chesnokov V Gong B Sun C Itakura K Anti-cancer activity of glucosamine through inhibition of N-linked glycosylation Cancer Cell Int 2014 14 45 10.1186/1475-2867-14-45 24932134 3. Satia JA Littman A Slatore CG Galanko JA White E Associations of herbal and specialty supplements with lung and colorectal cancer risk in the VITamins and Lifestyle study Cancer Epidemiol Biomarkers Prev 2009 18 5 1419 1428 10.1158/1055-9965.EPI-09-0038 19423520 4. Bell GA Kantor ED Lampe JW Shen DD White E Use of glucosamine and chondroitin in relation to mortality Eur J Epidemiol 2012 27 8 593 603 10.1007/s10654-012-9714-6 22828954 5. Molnar Z Bekesi JG Effects of D-glucosamine, D-mannosamine, and 2-deoxy-D-glucose on the ultrastructure of ascites tumor cells in vitro Cancer Res 1972 32 2 380 389 5058193 6. Molnar Z Bekesi JG Cytotoxic effects of D-glucosamine on the ultrastructures of normal and neoplastic tissues in vivo Cancer Res 1972 32 4 756 765 5014787 7. Gervasi DC Raz A Dehem M Yang M Kurkinen M Fridman R Carbohydrate-mediated regulation of matrix metalloproteinase-2 activation in normal human fibroblasts and fibrosarcoma cells Biochem Biophys Res Commun 1996 228 2 530 538 10.1006/bbrc.1996.1694 8920947 8. Rajapakse N Mendis E Kim MM Kim SK Sulfated glucosamine inhibits MMP-2 and MMP-9 expressions in human fibrosarcoma cells Bioorg Med Chem 2007 15 14 4891 4896 10.1016/j.bmc.2007.04.048 17498959 9. Mendis E Kim MM Rajapakse N Kim SK The inhibitory mechanism of a novel cationic glucosamine derivative against MMP-2 and MMP-9 expressions Bioorg Med Chem Lett 2009 19 10 2755 2759 10.1016/j.bmcl.2009.03.126 19375915 10. Lin YC Liang YC Sheu MT Lin YC Hsieh MS Chen TF Chen CH Chondroprotective effects of glucosamine involving the p38 MAPK and Akt signaling pathways Rheumatol Int 2008 28 10 1009 1016 10.1007/s00296-008-0561-4 18340449 11. Zeng ZS Huang Y Cohen AM Guillem JG Prediction of colorectal cancer relapse and survival via tissue RNA levels of matrix metalloproteinase-9 J Clin Oncol 1996 14 12 3133 3140 8955659 12. McGowan PM Duffy MJ Matrix metalloproteinase expression and outcome in patients with breast cancer: analysis of a published database Ann Oncol 2008 19 9 1566 1572 10.1093/annonc/mdn180 18503039 13. Zhang L Liu WS Han BQ Peng YF Wang DF Antitumor activities of D-glucosamine and its derivatives J Zhejiang Univ Sci B 2006 7 8 608 614 10.1631/jzus.2006.B0608 16845712 14. Deryugina EI Quigley JP Matrix metalloproteinases and tumor metastasis Cancer Metastasis Rev 2006 25 1 9 34 10.1007/s10555-006-7886-9 16680569 15. Overall CM Kleifeld O Tumour microenvironment - opinion: validating matrix metalloproteinases as drug targets and anti-targets for cancer therapy Nat Rev Cancer 2006 6 3 227 239 10.1038/nrc1821 16498445 16. Zucker S Cao J Selective matrix metalloproteinase (MMP) inhibitors in cancer therapy: ready for prime time? Cancer Biol Ther 2009 8 24 2371 2373 10.4161/cbt.8.24.10353 19959934 17. Tsai HC Su HL Huang CY Fong YC Hsu CJ Tang CH CTGF increases matrix metalloproteinases expression and subsequently promotes tumor metastasis in human osteosarcoma through down-regulating miR-519d Oncotarget 2014 5 11 3800 3812 10.18632/oncotarget.1998 25003330 18. Chandhanayingyong C Kim Y Staples JR Hahn C Lee FY MAPK/ERK signaling in osteosarcomas, ewing sarcomas and chondrosarcomas: therapeutic implications and future directions Sarcoma 2012 2012 404810 10.1155/2012/404810 22577336 19. Scotto d’Abusco A Calamia V Cicione C Grigolo B Politi L Scandurra R Glucosamine affects intracellular signalling through inhibition of mitogen-activated protein kinase phosphorylation in human chondrocytes Arthritis Res Ther 2007 9 5 R104 10.1186/ar2307 17925024 20. Zachara NE Hart GW O-GlcNAc a sensor of cellular state: the role of nucleocytoplasmic glycosylation in modulating cellular function in response to nutrition and stress Biochim Biophys Acta 2004 1673 1-2 13 28 10.1016/j.bbagen.2004.03.016 15238246 21. Zachara NE Hart GW Cell signaling, the essential role of O-GlcNAc! Biochim Biophys Acta 2006 1761 5-6 599 617 10.1016/j.bbalip.2006.04.007 16781888 22. Pettersson F Del Rincon SV Emond A Huor B Ngan E Ng J Dobocan MC Siegel PM Miller WH Jr Genetic and pharmacologic inhibition of eIF4E reduces breast cancer cell migration, invasion, and metastasis Cancer Res 2015 75 6 1102 1112 10.1158/0008-5472.CAN-14-1996 25608710 23. Seccareccia E Pinard M Wang N Li S Burnier J Dankort D Brodt P The inhibitor of kappa B kinase-epsilon regulates MMP-3 expression levels and can promote lung metastasis Oncogenesis 2014 3 e116 10.1038/oncsis.2014.28 25133483 24. Navarro SL White E Kantor ED Zhang Y Rho J Song X Milne GL Lampe PD Lampe JW Randomized trial of glucosamine and chondroitin supplementation on inflammation and oxidative stress biomarkers and plasma proteomics profiles in healthy humans PLoS One 2015 10 2 e0117534 10.1371/journal.pone.0117534 25719429 25. Qato DM Alexander GC Conti RM Johnson M Schumm P Lindau ST Use of prescription and over-the-counter medications and dietary supplements among older adults in the United States JAMA 2008 300 24 2867 2878 10.1001/jama.2008.892 19109115 26. Biggee BA Blinn CM McAlindon TE Nuite M Silbert JE Low levels of human serum glucosamine after ingestion of glucosamine sulphate relative to capability for peripheral effectiveness Ann Rheum Dis 2006 65 2 222 226 10.1136/ard.2005.036368 16079170 27. Jaffe N Osteosarcoma: review of the past, impact on the future. The American experience Cancer Treat Res 2009 152 239 262 10.1007/978-1-4419-0284-9_12 20213394 28. Ahmad A Li Y Sarkar FH The bounty of nature for changing the cancer landscape Mol Nutr Food Res 2016

PMC005xxxxxx/PMC5000454.txt

==== Front Global HealthGlobal HealthGlobalization and Health1744-8603BioMed Central London 19110.1186/s12992-016-0191-7CommentaryPerspectives on the methods of a large systematic mapping of maternal health interventions Chersich Matthew mchersich@wrhi.ac.za 12Becerril-Montekio Victor victor.becerril@insp.mx 3Becerra-Posada Francisco becerraposadaf@who.int 4Dumbaugh Mari mari.dumbaugh@unibas.ch 56Kavanagh Josephine msjokav@gmail.com 2Blaauw Duane Duane.Blaauw@wits.ac.za 2Thwala Siphiwe Siphiwe.Thwala2@wits.ac.za 2Kern Elinor kern@section27.org.za 2Penn-Kekana Loveday Loveday.Penn-Kekana@lshtm.ac.uk 27Vargas Emily emilymariavr@gmail.com 38Mlotshwa Langelihle langelihle.mlotshwa@unibas.ch 25Dhana Ashar ashdha@hotmail.co.za 2Mannava Priya pmannava@gmail.com 9Portela Anayda portelaa@who.int 10Tristan Mario mtristan@ihcai.org 11Rees Helen hrees@wrhi.ac.za 112Bijlmakers Leon 131 Wits Reproductive Health and HIV Institute, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa 2 Centre for Health Policy and MRC Health Policy Research Group, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa 3 Centre for Health Systems Research, National Institute of Public Health (Instituto Nacional de Salud Pública), Cuernavaca, Mexico 4 Pan American Health Organization, Washington D.C, USA 5 Department of Epidemiology and Public Health, Society, Gender and Health Unit, Swiss Tropical and Public Health Institute, Basel, Switzerland 6 University of Basel, Basel, Switzerland 7 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom 8 Innovation in Public Health Department, National Institute of Health, Bogotá D.C, Colombia 9 Centre for International Health, Burnet Institute, Melbourne, Victoria Australia 10 Department of Maternal, Newborn, Child and Adolescent Health, World Health Organization, Geneva, Switzerland 11 IHCAI Foundation, San Jose, Costa Rica 12 London School of Hygiene & Tropical Medicine, London, United Kingdom 13 Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands 25 8 2016 25 8 2016 2016 12 1 5110 3 2016 17 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Mapping studies describe a broad body of literature, and differ from classical systematic reviews, which assess more narrowly-defined questions and evaluate the quality of the studies included in the review. While the steps involved in mapping studies have been described previously, a detailed qualitative account of the methodology could inform the design of future mapping studies. Objectives Describe the perspectives of a large research team on the methods used and collaborative experiences in a study that mapped the literature published on maternal health interventions in low- and middle-income countries (2292 full text articles included, after screening 35,048 titles and abstracts in duplicate). Methods Fifteen members of the mapping team, drawn from eight countries, provided their experiences and perspectives of the study in response to a list of questions and probes. The responses were collated and analysed thematically following a grounded theory approach. Results The objectives of the mapping evolved over time, posing difficulties in ensuring a uniform understanding of the purpose of the mapping among the team members. Ambiguity of some study variables and modifications in data extraction codes were the main threats to the quality of data extraction. The desire for obtaining detailed information on a few topics needed to be weighed against the benefits of collecting more superficial data on a wider range of topics. Team members acquired skills in systematic review methodology and software, and a broad knowledge of maternal health literature. Participation in analysis and dissemination was lower than during the screening of articles for eligibility and data coding. Though all respondents believed the workload involved was high, study outputs were viewed as novel and important contributions to evidence. Overall, most believed there was a favourable balance between the amount of work done and the project’s outputs. Conclusions A large mapping of literature is feasible with a committed team aiming to build their research capacity, and with a limited, simplified set of data extraction codes. In the team’s view, the balance between the time spent on the review, and the outputs and skills acquired was favourable. Assessments of the value of a mapping need, however, to take into account the limitations inherent in such exercises, especially the exclusion of grey literature and of assessments of the quality of the studies identified. Electronic supplementary material The online version of this article (doi:10.1186/s12992-016-0191-7) contains supplementary material, which is available to authorized users. Keywords Scoping reviewResearch methodologyMapping of researchSystematic mappingMaternal healthHealth systemshttp://dx.doi.org/10.13039/501100004963Seventh Framework ProgrammeFP7/2007-2013Chersich Matthew NWO/Wotro (Netherlands Organisation for Scientific Research, WOTRO Science for Global Development)issue-copyright-statement© The Author(s) 2016 ==== Body Background A systematic mapping of a body of literature explicitly sets out to examine the studies done on a topic or research area, as a means of describing a broad research field [1]. Naturally, the focus and extent of a mapping of literature varies with its aims, but can include the syntheses of research findings on particular topics, or of research methodologies, study settings, or even of characteristics such as authorship and funding of specific research fields [2]. Mapping studies use data extracted from full text publications or bibliometric methodology [3], to systematically identify and summarise a body of literature. The methodology shares some features with ‘scoping reviews’, or rapid non-systematic syntheses of literature [4, 5]. These are commonly done as part of the initial steps in the planning of a systematic review, or even to help make a decision about whether or not to undertake a systematic review. Text mining technologies are a relatively new alternative to classic screening methods and will expedite mapping and scoping reviews in future [6]. Much of the methods used in a systematic mapping of literature are consistent with the first steps in a systematic review [7, 8], such as searching databases to locate a body of literature, screening articles for eligibility and extracting data from full text articles. A mapping, however, unlike systematic reviews, often does not assess the quality of the included studies, or extract data on the outcomes of interventions that are studied. A mapping of a body of literature can, however, serve to identify articles on several specific topics, which may then be followed by a series of reviews on these topics. The maps can thus inform subsequent systematic reviews on one or more narrowly defined research questions [9]. Finally, mapping can be used to address research questions that are difficult to answer through classic systematic reviews. For example, using classic review methods, it would be difficult to devise a rigorous search strategy for identifying articles on health systems interventions in maternal health, or studies that report effects of interventions on specific sub-groups, while these are possible in a mapping. The mapping study which is the topic of this paper aimed to synthesize research published on maternal health in low- and middle-income countries (LMICs) from 2000 to 2012, with a specific focus on interventions related to health inequities and systems. The year 2000 was selected because that was the onset of the Millennium Development Goals period, while the end date reflected the time that the review began. Studies had to include health systems, health promotion or community-based interventions; or interventions on one of five clinical tracer conditions: haemorrhage, hypertension, HIV, sexually transmitted infections other than HIV, or malaria. A sensitive search strategy combining controlled vocabulary and free-text terms was developed, following several exploratory searches and piloting. In the final search, terms for maternal health were combined with terms for LMICs, using the ‘AND’ function of search engines. The study also aimed to build capacity and reinforce collaboration across several research institutions and global regions. This paper provides a qualitative critique of the mapping methods and outputs from the perspectives of the study team. As an overarching question, this article attempts to answer the question: ‘Did the number and quality of outputs match the time-intensive and repetitive nature of the work?’ Such information has not been provided previously in similar methodological assessments of mapping [4, 8, 9]. This paper discusses the perspectives of the review team about the methodology, and their overall experience of the project gathered through an unstructured, self-administered questionnaire. We also present the collaborative and learning experiences of the team, so as to assess the extent to which the study aims around collaboration and capacity building have been achieved. Methods Between October and November 2015, the study coordinator (MFC) emailed all members of the mapping team a list of open-ended questions and probes (Additional file 1). Those who had initially joined the team, but later discontinued participation, were also invited to offer their views. The data collection tool focused on the team’s perspectives on the strengths and weaknesses of various phases of the review, in particular the identification of relevant literature, especially non-English articles; data extraction from full text articles; and the data analysis and dissemination of the findings. Figure 1 shows the two-staged review process. The first stage involved screening of literature, data extraction, analysis and dissemination of a mapping that sums a body of literature on maternal health (Stage 1). This was followed by a number of systematic reviews on specific PICO questions (Population, Intervention Comparator Outcomes) for certain interventions or target populations, using the articles identified on these in the previous stage (Stage 2). The enquiry among team members focused on factors influencing the quality of the mapping procedures and how that could be improved. The questions and probes also encompassed a broader set of themes, specifically on whether the review’s objectives were clear and how these had changed over time; the perceived level of participation, collaboration and communication among the team; and the effectiveness of the capacity building activities of the study. Finally, views were elicited on the overall experience of the study; and whether it was considered worth the time and financial investments incurred.Fig. 1 Review process and key challenges At least two attempts were made to obtain responses from team members. Responses, emailed to the study coordinator, were not anonymised. Inputs were received from 15 of 18 researchers invited to participate. The responses were coded thematically, following a grounded-theory approach [10]. Key themes were identified and used to structure this report. The results text was reviewed by all team members for completeness and accuracy of interpretation. Illustrative quotes are included, together with a description of the respondents, where relevant. The findings are grouped into three major themes, beginning with a critique of the different phases of the study and the factors in each phase that may have influenced the quality of the review. Thereafter, we assess the collaborative experiences of the team, as well as the success of the project in achieving its capacity building objectives. Finally, we consider the balance between the resources spent on the study and the project’s outputs. Factors influencing the quality of the review Identification of relevant literature The search covered seven databases, including a regional database for South and Central America (Literatura Latino-Americana e do Caribe em Ciências da Saúde, Additional file 2). The search was considered as having adequately captured the literature, some team members even felt that the search criteria were not tight enough, resulting in too many articles to sort through. The volume was indeed large: 45,959 abstracts were uploaded, 10,881 duplicates removed, and 35,078 titles and abstracts screened independently by two reviewers. Differences between reviewers were resolved by a third, more senior reviewer. Details of reasons for excluding articles at each stage are provided elsewhere [2, 11]. A few team members felt that the search strategy could have included more specific “health system” terms like governance and accountability, so as to avoid missing articles on these topics. The exclusion of “grey literature” particularly concerned one team member with a health systems background, who noted that such literature documents the vast majority of implementation experiences and of high-quality research [12]. Of interest, a researcher who was involved in developing systematic reviews on individual review questions (Stage 2 articles using the MASCOT/MHSAR database), felt that others involved in those reviews ‘may have felt uncomfortable with using a study method that was foreign’. These concerns stemmed from fears that the mapping approach, which aims to identify articles on several different topics at one time, might not have located all relevant studies on the topics at hand, unlike with classic systematic reviews where separate searches are done for each individual review question. Though several non-English databases were searched, and no language restrictions were employed, some felt that additional efforts could have been made to locate this literature. They were concerned that much of this research is published in journals which are not indexed by the major biomedical databases. An information specialist commented that: ‘perhaps sources of information from other countries [not found in the literature review] could have been pursued more vigorously’ and a senior researcher from Costa Rica wondered if ‘this work [non-English literature] was not fully used’. Including publications in multiple languages and allocating them to native speakers was more complex than anticipated, with potential pitfalls at each stage of the review. Partners in non-English countries were especially important for locating full text articles. The South African who led the location and uploading of full text articles noted that: ‘tremendous efforts were made by participants all over the world to find the articles missing in each other’s libraries.’ Full text papers were located for 93 % of the abstracts classified as eligible for full text screening (4,175/4,472). Finally, some external data sources were used and variables from these were merged into the database for particular analyses, allowing for comparison between our data and broader variables. These data included the journal’s Impact Factor [13]); Gross Domestic Product of each LMIC [14]; total number of health articles published per country [15]; and the number of maternal deaths [16] and of women with HIV infection in each LMIC [17]. Extraction of data from full text articles Defining the variables was technically the hardest part of the study, and it is fair to say that the coordinators underestimated how much discussion and time was required to finalise the coding system. The 17 study variables, operationalised as data extraction codes, covered the following: country where the study was done; country of affiliation of the first author; study design; intervention topic; whether the study examined health inequalities, health systems or health promotion; intervention recipient; period of pregnancy targeted; type of health or health systems outcomes reported; and research funder. Actual outcomes were not captured and, as in most similar mapping studies [1, 8], we did not assess the quality of the research methodology in individual studies. Some variables were harder to define than others. Even what constitutes an ‘intervention’ was debated vigorously; the boundary between provision of routine services and an intervention was not always easy to delineate. As a further example, the provision of medical supplies or commodities is one of the six WHO Health System Building Blocks [18] and studies in which medical supplies are provided as part of routine service delivery might therefore, strictly speaking, be classified as health system interventions. Given these complexities, some months into the study, a decision was made to exclude studies that reported only on utilisation or other features of routine services. Difficulties defining variables in the protocol made it harder for data extractors to apply these codes and to standardise their work. One extractor based in Mexico summed this well: ‘sometimes in reviews it is not easy to follow “the rules”’. ‘The only difficulty I found was keeping abreast with the changes in the protocol, and due to this, sometimes the inclusion and exclusion criteria were not always clear. Whilst recognizing that flexibility needs to be maintained, for next time, it would be better to avoid changing inclusion and exclusion criteria, data to be collected etc.’ Australian public health practitioner It quickly became clear that the initial protocol did not cover all the complexities and ambiguities that arose, and some protocol amendments were required over time. The coordinator felt he had to balance the need for finalising the data extraction codes, with getting the review underway, and thereby taking advantage of the initial enthusiasm of the team. Participants in the review recognised the difficulties in developing a ‘perfect’ protocol, with a junior researcher in South Africa acknowledging that: ‘I believe some ambiguity is expected when working with an unfamiliar research design’. The large majority, however, indicated they would have preferred the protocol and extraction codes to have been completely finalised before the project commenced. Several participants across the team held that changes in variables to be extracted ‘took some adjusting’, ‘affected the screening’ and ‘would slow one down’. The introduction of new sets of data extraction codes, such as codes for identifying articles on specific topics of interest to WHO guidelines, was even seen as altering the aims of the review. For one team member who had been involved from the very outset of the project, these new codes ‘almost took over the review’. Ultimately, much of the difficulty with coding came down to striking a balance between wanting more detailed data (which required more extraction codes), and the desire for having only a few simplified codes, which would be easier to standardise and quicker to extract. Similarly, one has to weigh up collecting information on a diverse range of issues and thus securing a larger breadth of information and outputs, against the alternative of having more codes on fewer topics, with greater depth of investigation. One respondent from the Mexican MASCOT partner supported the former approach: ‘In my opinion, the diversity of codes is what made it possible to obtain sufficiently rich outputs’. However, in particular, the health systems experts in the study felt differently. In their view, using broad categories (for example simply labelling a study as covering “human resources”), only provided superficial insights. As a result, they developed more detailed variables and went back to extract additional data from articles classified as “health systems” papers. The majority of reviewers had a background in health systems, rather than in maternal health or health promotion. Lack of familiarity with a topic made coding more difficult and time-consuming; one reviewer with a background in clinical medicine noted, for example, that: ‘codes for health promotion were very difficult to work with, given my limited understanding of that area’. Many argued that papers on specific topics, such as HIV or health promotion, should have been assigned to small teams of people, based on topic knowledge and interest: ‘In my opinion, it is better if each team that has a research topic, creates the codes and leads the data extraction’, reflected a Colombian masters graduate. Finally, several members of the team worked full-time on screening and data extraction for a few months, which perhaps raised the quality of their work. One said: ‘I was able to dedicate my attention fully to the review of articles, immerse myself in the topic, take breaks as appropriate and develop a consistent frame for reviewing articles’. In her view, ‘others who only reviewed articles sporadically might not have had the chance to develop that consistency and familiarity with the approach and/or the extraction tool.’ She also felt that having several people working full-time would allow: ‘those individuals to work closely together, with frequent contact and discussions of difficult or ambiguous papers, with other team members doing quality checks, etc., and might increase quality.’ International collaboration and capacity building The review team consisted of 15 members, drawn from eight countries across five continents. The team drew on collaborators from two research projects (MASCOT and MHSAR; Table 1). Ensuring a common understanding of the project’s purposes and processes across the team was difficult, as, by design, the project had several overlapping objectives and multiple outcome measures. Conceptualisation of the project itself also evolved over time. A junior researcher in South Africa recounted that: ‘for me, with time everything became clear’, while others felt differently, for example, a team member from Colombia said: ‘At the beginning, the objectives, tasks were clear; but at the end I was a little confused, especially about the coding and final goal.’ ’..the end product was a little different from the initial aim’ South African researcher ‘I saw it as an excellent opportunity to collaborate with an interdisciplinary team in a unique way – having never met most of my colleagues on the review team, but forming relationships nonetheless’ Consultant who did health promotion coding Table 1 Partners involved in the mapping  The systematic mapping was initially conceptualised as part of the MASCOT project. However, it soon became apparent that the scale of the project exceeded the resources available in MASCOT. The mapping team thus partnered with another multi-country research project (MHSAR), which had some overlapping objectives. Towards the project end, the team linked with the WHO Department of Maternal, Newborn, Child and Adolescent Health, who were about to embark on a series of systematic reviews to support WHO’s guidelines on health promotion interventions for maternal and newborn health.  The MASCOT project, supported by the European Commission’s FP7 research programme, included countries from Europe, Africa and Latin America (http://www.cohred.org/mascot). It consisted of 5 research institutions, 3 university groups and an NGO, representing 11 countries. The overarching aim was to identify and share country-specific strategies for tackling inequalities affecting maternal and child health (MCH). MASCOT also aimed to stimulate knowledge transfer and exchange mechanisms between and within countries for shaping policies, programmes and health actions intended to remediate MCH inequalities. Finally, the project identified coordinating mechanisms for South-South and North-south collaboration, specifically those that examine MCH status, national health research systems’ capacities and best practices, and research supported MCH strategies.  Funded by the Netherlands Organisation for Scientific Research (NWO/WOTRO), through its Global Health Policy and Health Systems Research programme, the Maternal Health and Health Systems in South Africa and Rwanda research project (MHSAR) aims to synthesize and generate knowledge on how health systems strengthening can improve maternal health, and which health system initiatives have the largest impact on maternal health. The project consortium includes research centers in two universities in South Africa, one in the Netherlands, and the Ministry of Health in Rwanda. Including both the MASCOT and MHSAR teams in the project provided the resources needed to complete the mapping, and widened the project’s scope beyond its original conceptualisation. The coordinator was the go-between for the two consortia, while many respondents indicated they would have preferred more direct communication across the teams. This might have reduced ambiguities about “how the two projects’ interests were being addressed by the review’ (Mexican researcher at a leading Public Health Institute) and ‘what each consortium contributed to the study’ (South African researcher employed by both projects). The later joining of staff working on the WHO guidelines on health promotion interventions for maternal and newborn health meant that three groups participated in the final stages of the project. A team member of the WHO component felt that overall: ‘most people didn’t really understand the whole of what was happening.’ While clearly there are potential pitfalls in expanding the review team, new people brought onto the project often provided bursts of energy and additional expertise. Communication among the diverse and geographically dispersed team posed challenges. Conference calls were generally held monthly and five face-to-face meetings took place (three among the MASCOT consortia and two within MHSAR). Most felt that conference calls should have been more frequent (even weekly) and should have covered: ‘common problems’; ‘the lessons learnt by people reviewing abstracts’; and ‘the more subjective points of the review-we were still at some points discussing “what is an intervention?” late in the review’. Additional calls could also have served to: “push people to work more efficiently on meeting their deadline’; and would ‘have been great for debriefing moments and helping to assist each other’. Respondents believed that face-to-face meetings, where screening and extraction codes are applied together, might have been particularly useful. One respondent who worked full time on the review for a few months neatly summed this point: ‘When we did have these calls I found them helpful and I think they increased the quality of the review’. Management of the database, screening for eligibility and data extraction were done using web-based systematic review software (EPPI-Reviewer 4, http://eppi.ioe.ac.uk/cms/). Contact between team members mostly took place through the software, with one respondent from Colombia noting that ‘the software was our office, our working place, and it was the place for closest relationship with the team members’. The EPPI support team provided timely inputs to resolve a few minor glitches which occurred with the software. Aside form some software updates, project activities were never disrupted by website or software issues. Although the nature of the study meant that much of the work was done by individuals working alone, ironically, the collaborative nature of the work was seen as a major strength of the study. The opportunity to collaborate drove many to join the study. A researcher based in Mexico, for example, noted that he ‘joined maybe mostly because of the diversity of participants from several countries and continents’. Not everyone, however, felt part of a larger team. One explained that ‘I felt like I was part of a team, but only in relation to certain individuals (about four). We had more frequent contact and I felt I could go to them with questions or ambiguous papers’. A MASCOT coordinator similarly noted that: ‘Even though it was a team, we were from so many different countries working individually, it was hard to have a “team spirit” all the time.’ Finally, meeting the people who had been ‘virtual’ colleagues for some time was a highlight of the project for some. A South African researcher captured this sentiment well: ‘The climax was the Mexico visit, where I got to meet in person people that I had been “virtually” working with for over a year’. Maintaining momentum of the study and team cohesion was relatively easy in the initial stages of the project, as these provided many opportunities for teamwork and interaction, especially with tasks done in duplicate. A lead researcher from the Mexican MASCOT partner felt that: ‘The abstract screening was for me a most exciting process, particularly when it came to interacting with my fellow reviewers and the review coordinator.’ Participation diminished in the later stages, particularly during data analysis and dissemination. Some even felt excluded during these phases and on hindsight they felt that more efforts should have been made to secure their involvement throughout. This might also have improved the quality of the study outputs, as noted by the project lead in Costa Rica: ‘The analysis could be improved with more systematic discussions with co-authors.’ Building capacity of staff Each stage of the study presented junior researchers with opportunities and scope for learning, encompassing both aspects of review methodology and content knowledge. Skill level and suitability for each stage were hard to predict and many acquired new skills by taking on tasks they had not done before. The vast majority of the team had not been involved in similar studies before; one public health graduate reflected that: ‘this was my first time being part of a ‘systematic review’ and so I was always eager to learn. It was sometimes challenging to keep up with other participants in other parts of the world, who seemed to work faster than I did.’ ‘In terms of the overall project - I think it built a lot of people’s capacity‘(researcher involved in stage 1 and 2 of project) ‘Made good friends and good contacts - and it has been good for my career’ (London-based researcher) ‘Not only about research methodology, database searching and screening, but also about maternal health’ (information specialist) ‘So much that one can learn; patience and different skills e.g. the software’ (graduate student) ‘I saw it as an excellent opportunity to gain exposure to a wide breadth of recent maternal health literature’ (graduate student) Using the software also constituted a considerable learning curve for team members. Its apparent complexity even deterred some people from participating in the review. The overall MASCOT coordinator explained: “Maybe some people did not understand the software and did not commit”. Ultimately, team members’ proficiency and affinity with the software rose over time. A Mexican researcher recounted that: ”Sometimes issues of the software gave me grief, but it was interesting, and at a later stage I was able to assist other people’. Another reviewer based in the United States said: “I now feel confident in using data extraction software and was able to go on and create another review using EPPI Reviewer shortly afterwards”. Finally, a Colombian graduate student noted that: ‘I am now conducting a systematic review and I miss this software so much’. Screening and coding took up a disproportionately large amount of time compared to data analysis, limiting opportunities for capacity building during the stage of conceptualising and completing articles. One researcher noted that: ”The ratio between time on coding and time on analysis was always going to be a challenge given the time needed for coding.” Of note, one article was led by a doctoral student [19], working closely with a few members of the team. A more planned and structured approach to capacity building might have raised participation in article writing. Finally, three team members commenced their doctoral studies shortly after the review. One South African said: “I had no idea what exactly I wanted to look into in my PhD. The more I got involved [in the mapping study], I slowly started thinking about what research ideas I was interested in.” Another, also from South Africa, noted that it” was a great project to be involved in before my PhD”. She went on to say that “as the review unfolded, I became really interested. For me, it was a way of familiarizing myself with health systems literature as this was a new field for me, which I went on to pursue in my PhD studies”. Was the project worth it? Without exception, respondents viewed the volume of work involved as large. In addition to the 10,881 titles and abstracts that were reviewed in duplicate, 4,175 full text papers were assessed for eligibility. Locating and uploading of the full text articles was particularly arduous. The final mapping entailed data extraction on 17 variables from 2,292 full text papers. A South African masters graduate captured this well: The sheer volume of the work overwhelmed many, I think. There was a time where we were screening endlessly with thousands more abstracts to go. It did feel like a mission impossible’. Overcoming the challenge of the work, however, and gaining new skills was viewed as an important outcome in itself. A Spanish-speaking team member from Colombia noted: ‘I face my fears of language barriers, methodology and way of working’. Overall, most felt that the balance between the amount of work done and the project’s outputs was favourable (Table 2). A member of the Mexico group summed these sentiments as: ‘To me, the long time spent in what can be seen as a repetitive kind of work, was never something tedious or annoying. The outputs definitely make it worthwhile’. For many, the largest impact of the study was its contribution to the WHO guidelines on Health Promotion interventions for maternal and newborn health. One team member, who assisted mainly with screening of articles, felt that the project’s most important contribution was the bringing together of published literature: ‘I think the outputs are well worth the investment…so much is published and if not brought together in a coherent way, what is the point?’ The overall coordinator of the MASCOT project held the view that the study’s value was its relevance around the world: “I think these findings might be relevant for all regions, as they bring light to many issues”. The dissemination of results and use of findings is key, same as use of research results for decision making. As with all research, one needs to consider and prioritise: ‘The question here is HOW to better use these results? Who is the audience? How to reach them?’ How to make sure the current database is visible, disseminated and research and other institutions use it’ Leading policy maker in Latin America Table 2 Study outputs • Symposium in South Africa involving about 100 people • Policy Brief circulated widely in South Africa • Open-access database of all included studies and data extracted, intended for use by other researchers [20] • Three articles published on the findings of the mapping [19] • A thematic series in Globalisation and Health, containing all articles from the mapping, a complementary mapping of literature in high-income countries [21] ; and a series of editorials [22] • Mapping contributed to the systematic reviews done to support the WHO guidelines on Health Promotion interventions for maternal and newborn health [23]. The mapping identified articles on specific topics, for example maternity waiting homes, and these then formed the basis for the systematic reviews on those topics. Mapping contributed to the evidence summaries for eleven of the twelve recommendations in the guidelines • The mapping methodology and findings were presented at two meetings at WHO headquarters in Geneva, Switzerland • Systematic reviews that draw on articles identified on specific topics in the mapping, such as on male involvement in maternal health and birth preparedness [24–26] As with much research, however, it is difficult to quantify how much this work adds to the existing knowledge base, and to changes in local or international policy. When asked if, overall, the review outputs were ‘worth it’, the Dutch coordinator of MHSAR replied: ‘[it was] an enormous time investment for a large group of people; but we should all realise that there are other benefits and spin-off effects, beyond the few journal papers that have resulted from this work.’ Another reviewer from South Africa, who commenced masters studies in the United States after the project, felt its principal contribution centred on the novelty of its outputs: ‘I feel that the novelty of the project definitely adds a different dimension to the maternal health research landscape’. The team also believed that the methodology of the mapping was novel and would help to advance this kind of technique and inform similar studies in the future. Conclusions The paper sums the perspectives and experiences of the mapping team on the methodology, collaboration and learning opportunities provided by the study. Of note, several factors were identified which could affect the quality of a mapping study and thus the validity of its conclusions. Importantly, the selection and definition of the mapping variables should be finalised prior to onset of the screening, as far as possible, even if that delays the start of the study. Other factors that may influence quality include difficulties in locating non-English literature, lack of familiarity with the subject matter of the mapping, and limited communication and cross-learning among the team. Communication and coordination of a team spread over five continents was difficult and similar projects might consider having smaller teams working full time, and more frequent face-to-face meetings and conference calls. During the early stages of the study, levels of collaboration were high, though more regular and structured communication was needed. The project was notably less successful at securing participation and learning in its later stages, specifically during data analysis and dissemination. Moreover, there was little interaction between the MASCOT and MHSAR project teams. Disappointingly, no new projects have yet been developed between the research entities involved in this collaboration. Despite its challenges, the overall predominant view of the team was summed by a leading policy maker in Latin America as: ‘The joint international effort was a great experience, a new line of research could have started and maybe someone would follow.’ Though acknowledging the considerable volume of work involved in such a mapping, the team gave a favourable assessment of the balance between the amount of work required and the value of the study outputs. Also, the study offered a wide range of opportunities for capacity building, both in terms of learning about some aspects of systematic review methodology and software, and in obtaining broad knowledge in the field of maternal health. In these areas, the study seemingly achieved its aims, even though capacity building was less successful during data analysis and dissemination. The series of articles summing the mapping findings and the mapping’s role in identifying the studies that were then included in the systematic reviews for WHO guidelines were especially valued. Two features of the underlying design of the mapping study bear mention. The exclusion of grey literature makes it difficult to claim that a mapping sums all research on a topic. Also, the lack of assessment of the quality of the studies included in the mapping, as done in systematic reviews, influences the validity of the study’s conclusions. Without assessing the quality of the studies, those with weak and strong methods are given equal weighting. Proxies for study quality were used in the mapping, such as study design and the Impact Factor of the journal in which an article was published, but these cannot replace a formal assessment of the quality of a study. A mapping or scoping of literature is also not a necessary precursor to a systematic review, and may not be an efficient means of doing so, given the burden of work involved. It might be useful thus to conceptualise mapping studies as synthesizing a body of literature, as distinct from an evaluation of literature as is done in a systematic review. A mapping, such as this study, aims to provide detailed information about the nature of a research field and to investigate a wide range of issues. This, however, means that mapping studies run the risk of being construed as unfocused as, by their nature, they have broad, sometimes difficult to define objectives. Moreover, having such a large team, with members drawn from three projects, poses serious challenges in ensuring a uniform understanding of the protocol, the coding process and intended outputs. The desire to gather a wide breadth of information, as opposed to depth on a few topics, heightens the challenge of clearly delineating the objectives of the mapping.[8] Another mapping study had a similar experience: as that team grew increasingly familiar with the literature being mapped, it became necessary to clarify the study concepts and to revise its research questions [1]. Essentially, the value ascribed to the project stemmed principally from the project’s novelty and contribution to evidence, and its collaborative and capacity building opportunities. The validity of the outputs, however, is tempered by deficiencies in mapping methodology, especially the lack of assessment of the quality of included studies. Based on the perspectives of the review team, the practical ingredients needed to complete such a project are: a sizable team, ideally with some staff working full-time; support for locating and uploading of full text articles; and optimising the number of data extraction codes used, yet retaining some measure of depth and breadth of the data obtained. In addition to these factors, prerequisites for a successful mapping include: strong collaboration across the team, a shared understanding of the review purposes, and standardised screening and data extraction procedures across the team. We conclude that, with all these elements in place, and with sufficient focus and funding for dissemination, mapping studies can make useful contributions to the literature and to building the skills of research teams. Additional files Additional file 1: Tool for gathering perspectives of participants on mapping methodology.ᅟ(DOCX 20 kb) Additional file 2: Mapping search strategy and protocol. (PDF 1497 kb) Abbreviations LMICsSlow- and middle-income countries MASCOTMultilateral Association for Studying health inequalities and enhancing North-South and South-South Cooperation MH-SARMaternal Health and Health Systems in South Africa and Rwanda Acknowledgements We acknowledge the considerable work of Caroline van de Ven from Radboud UMC Nijmegen in data extraction for the review. Funding The MASCOT/MHSAR review was funded by the European Union’s Seventh Framework Programme (FP7/2007-2013; grant agreement number 282507) and NWO/Wotro (Netherlands Organisation for Scientific Research, WOTRO Science for Global Development). All funding was in the form of general financial support, which included staff salaries, travel and subscriptions for the review software. The authors have not been paid to write this article by a pharmaceutical company or other agency. Availability of data and materials The database for the mapping is available at http://eppi.ioe.ac.uk/webdatabases4/Intro.aspx?ID=11. The questionnaire used for the study is included as a Additional file. Authors’ contributions MFC, VBM, LB, FBP, EV conceived of the study, and participated in its design and coordination. All authors provided data on their perspectives of the study methods. Authors had participated in the screening of titles and abstracts for eligibility for the mapping study, and in extraction of data from full text articles. MFC carried out data analysis and wrote an initial draft of the manuscript. All authors critically revised and approved the final manuscript. Authors’ informations FBP was working at COHRED at the time of study, COHRED was MASCOT Coordinator. Competing interest The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate Not applicable. ==== Refs References 1. Daudt HM van Mossel C Scott SJ Enhancing the scoping study methodology: a large, inter-professional team's experience with Arksey and O'Malley's framework BMC Med Res Methodol 2013 13 48 10.1186/1471-2288-13-48 23522333 2. Footman K Chersich M Blaauw D Campbell OM Dhana A Kavanagh J Dumbaugh M Thwala S Bijlmakers L Vargas E A systematic mapping of funders of maternal health intervention research 2000–2012 Glob Health 2014 10 72 10.1186/s12992-014-0072-x 3. Bouchard L Albertini M Batista R de Montigny J Research on health inequalities: A bibliometric analysis (1966–2014) Soc Sci Med 2015 141 100 8 10.1016/j.socscimed.2015.07.022 26259012 4. Arksey H O'Malley L Scoping studies: towards a methodological framework Int J Soc Res Methodol 2005 8 19 32 10.1080/1364557032000119616 5. Levac D Colquhoun H O'Brien KK Scoping studies: advancing the methodology Implement Sci 2010 5 69 10.1186/1748-5908-5-69 20854677 6. Shemilt I Simon A Hollands GJ Marteau TM Ogilvie D O'Mara-Eves A Kelly MP Thomas J Pinpointing needles in giant haystacks: use of text mining to reduce impractical screening workload in extremely large scoping reviews Res Synth Methods 2014 5 31 49 10.1002/jrsm.1093 26054024 7. Shamseer L Moher D Clarke M Ghersi D Liberati A Petticrew M Shekelle P Stewart LA Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation BMJ 2015 349 g7647 10.1136/bmj.g7647 25555855 8. Pham MT Rajic A Greig JD Sargeant JM Papadopoulos A McEwen SA A scoping review of scoping reviews: advancing the approach and enhancing the consistency Res Synth Methods 2014 5 371 85 10.1002/jrsm.1123 26052958 9. Gough D Thomas J Oliver S Clarifying differences between review designs and methods Syst Rev 2012 1 28 10.1186/2046-4053-1-28 22681772 10. Strauss A Corbin J Basics of qualitative research techniques and procedures for developing grounded theory 1998 2 Thousand Oaks Sage Publications 11. Chersich MF Blaauw D Dumbaugh M Penn-Kekana L Dhana A Thwala S Bijlmakers L Vargas E Kern E Becerra-Posada F Local and foreign authorship of maternal health interventional research in low- and middle-income countries: systematic mapping of publications 2000–2012 Glob Health 2016 12 35 10.1186/s12992-016-0172-x 12. Stansfield C Weightman AL Kavanagh J Johansen M Cochrane update: identifying health-related research resources relevant to low- and middle-income countries J Public Health (Oxf) 2013 35 477 80 10.1093/pubmed/fdt091 23978846 13. Journal Citation Reports http://wokinfo.com/products_tools/analytical/jcr/ 14. The World Bank: GDP (current$) 2000–2012. http://data.worldbank.org/indicator/NY.GDP.MKTP.CD?page=2 15. Rottingen JA Regmi S Eide M Young AJ Viergever RF Ardal C Guzman J Edwards D Matlin SA Terry RF Mapping of available health research and development data: what's there, what's missing, and what role is there for a global observatory? Lancet 2013 382 1286 307 10.1016/S0140-6736(13)61046-6 23697824 16. Kassebaum NJ Bertozzi-Villa A Coggeshall MS Shackelford KA Steiner C Heuton KR Gonzalez-Medina D Barber R Huynh C Dicker D Global, regional, and national levels and causes of maternal mortality during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013 Lancet 2014 17. UNAIDS: Global report: UNAIDS report on the global AIDS epidemic 2013. UNAIDS / JC2502/1/E 2013.http://www.unaids.org/sites/default/files/media_asset/UNAIDS_Global_Report_2013_en_1.pdf 18. WHO: Everybody business: strengthening health systems to improve health outcomes : WHO’s framework for action 2007.http://www.who.int/healthsystems/strategy/everybodys_business.pdf 19. Footman K Chersich M Blaauw D Campbell O Dhana A Kavanagh J Dumbaugh M Thwala S Bijlmakers L Vargas E A systematic mapping of funders of maternal health intervention research 2000 inverted question mark2012 Glob Health 2014 10 72 10.1186/s12992-014-0072-x 20. MASCOT/MH/SAR mapping database: 2015.http://eppi.ioe.ac.uk/webdatabases4/Intro.aspx?ID=11 21. Perry M Becerra F Kavanagh J Serre A Vargas E Becerril V Community-based interventions for improving maternal health and for reducing maternal health inequalities in high-income countries: a systematic map of research Glob Health 2015 10 63 10.1186/s12992-014-0063-y 22. Globalization and Health thematic series: Health systems interventions for improving maternal health.http://www.globalizationandhealth.com/series/maternal_mortality 23. WHO: WHO recommendations on health promotion interventions for maternal and newborn health 2015.http://www.who.int/maternal_child_adolescent/documents/health-promotion-interventions/en/ 24. Solnes Miltenburg A Roggeveen Y Shields L van Elteren M van Roosmalen J Stekelenburg J Portela A Impact of birth preparedness and complication readiness interventions on birth with a skilled attendant: a systematic review PLoS One 2015 10 10.1371/journal.pone.0143382 26599677 25. George AS Branchini C Portela A Do interventions that promote awareness of rights increase use of maternity care services? a systematic review PLoS One 2015 10 10.1371/journal.pone.0138116 26444291 26. Comrie-Thomson L Tokhi M Ampt F Portela A Chersich M Khanna R Luchters S Challenging gender inequity through male involvement in maternal and newborn health: critical assessment of an emerging evidence base Cult Health Sex 2015 17 Suppl 2 S177 89 10.1080/13691058.2015.1053412 26159766

PMC005xxxxxx/PMC5000455.txt

==== Front BMC NephrolBMC NephrolBMC Nephrology1471-2369BioMed Central London 33410.1186/s12882-016-0334-3Research ArticleChloride content of solutions used for regional citrate anticoagulation might be responsible for blunting correction of metabolic acidosis during continuous veno-venous hemofiltration Jacobs Rita Rita.Jacobs@uzbrussel.be Honore Patrick M. 00 32 2 474 90 97Patrick.Honore@az.vub.ac.be Diltoer Marc Marc.Diltoer@uzbrussel.be Spapen Herbert D. Herbert.Spapen@uzbrussel.be Intensive Care Department, Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, 1090 Brussels, Belgium 26 8 2016 26 8 2016 2016 17 1 1192 2 2016 17 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Citrate, the currently preferred anticoagulant for continuous veno-venous hemofiltration (CVVH), may influence acid-base equilibrium. Methods The effect of 2 different citrate solutions on acid-base status was assessed according to the Stewart-Figge approach in two consecutive cohorts of critically ill adult patients. The first group received Prismocitrate 10/2 (PC10/2; 10 mmol citrate/L). The next group was treated with Prismocitrate 18/0 (PC18; 18 mmol citrate/L). Both groups received bicarbonate-buffered fluids in post-dilution. Results At similar citrate flow, the metabolic acidosis present at baseline in both groups was significantly attenuated in PC18 patients but persisted in PC10/2 patients after 24 h of treatment (median pH 7,42 vs 7,28; p = 0.0001). Acidosis in the PC10/2 group was associated with a decreased strong ion difference and an increased strong ion gap (respectively 43 vs. 51 mmol/L and 17 vs. 12 mmol/L, PC10/2 vs. PC18; both p = 0.001). Chloride flow was higher in PC10/2 than in PC18 subjects (25.9 vs 14.3 mmol/L blood; p < 0.05). Conclusion Correction of acidosis was blunted in patients who received 10 mmol citrate/L as regional anticoagulation during CVVH. This could be explained by differences in chloride flow between the applied citrate solutions inducing hyperchloremic acidosis. Keywords CitrateAnticoagulationContinuous veno-venous hemofiltrationAcid-base balanceChlorideAcidosisAlkalosisHyperchloremic acidosisStrong ion gapStewart-Figge approachissue-copyright-statement© The Author(s) 2016 ==== Body Background Continuous veno-venous hemofiltration (CVVH) under regional citrate anticoagulation (RCA) is increasingly used for treatment of acute kidney injury (AKI) in critically ill patients [1]. As a calcium-chelating agent, citrate effectively blocks coagulation activation in the extracorporeal circuit which enhances filter lifespan at low risk of bleeding [2]. However, citrate may cause adverse metabolic effects. Citrate metabolization produces bicarbonate, hence generating metabolic alkalosis. Conversely, in patients with decreased capacity to metabolize citrate (eg hepatic failure), accumulation can lead to high anion-gap metabolic acidosis [3–5]. Acid-base status is also affected by the amount of administered chloride and bicarbonate buffer, and occasionally by respiratory (over)compensation [6, 7]. Finally, when administered as a trisodium salt, excess citrate may induce hypernatremia [8]. Egi et al. were the first to document changes in acid-base balance in patients undergoing RCA-CVVH [9]. Since then, many attempts were undertaken to find the optimal citrate solution that allowed swift and effective control of acidosis whilst avoiding rebound alkalosis during continuous renal replacement therapy (CRRT) [10, 11]. Within this context, we studied the metabolic impact of two different commercially available citrate formulas (Prismocitrate 10/2 (PC10/2; 10 mmol citrate/L, Gambro-Hospal) and Prismocitrate 18/0 (PC18; 18 mmol citrate/L, Gambro-Hospal) in a cohort of critically ill patients with AKI undergoing RCA-CVVH. We based our metabolic approach on the Stewart-Figge method [12–15] to assess whether a difference existed in occurrence of metabolic acidosis between the two citrate protocols and to determine which factor(s) affected this metabolic disorder. Methods The study was performed in the intensive care unit (ICU) of the University Hospital Brussels and conducted in compliance with the Helsinki Declaration. The Central Ethical Committee of the University Hospital approved the study protocol (BUN 143201318818). Due to its retrospective and observational before-after design, the need for informed consent was waived. Patients were eligible when presenting AKI requiring RCA-CVVH treatment. Inclusion criteria were: age ≥ 18 years, presence of at least an AKI “RIFLE injury” score [16], and no contra-indication for RCA. Exclusion criteria were: patients already treated with CVVH during their ICU stay or receiving CVVH at time of enrolment, a high likelihood of dying within the first 24 h, impossibility to provide a correct vascular access, and Child-Pugh grade C liver cirrhosis. Baseline characteristics, including causes of AKI and incidence of shock are given in Table 1.Table 1 Patient characteristics and causes of AKI Prismocitrate 10/2 Prismocitrate 18 P value Number of patients (n) 28 31 Age (years) (median [range]) 73 (65–82) 68 (55–82) 0.298 Male gender (n, %) 17/28 (61 %) 21/31 (68 %) 0.598 Underlying disease/condition & cause of AKI (n, %)  Sepsis 9/28 (32 %) 9/31 (29 %) 0.98  Post cardiac surgery 5/28 (18 %) 10/31(32 %) 0.33  Post general surgery 7/28 (25 %) 4/31(13 %) 0.39  Other 7/25 (25 %) 8/31(26 %) 0.90 APACHE II score (median [range]) 32 (23–41) 27 (20–34) 0.109 Mechanical ventilation (days) (median [range]) 11 (1–24) 14.6 (2–26) 0.167 Vasopressor requirement (n, %) 86 % 77 % 0.451 Abbreviations: APACHE II acute physiology and chronic health evaluation score II, LOS length of stay, AKI acute kidney injury Patients were not randomized to receive either PC10/2 or PC18 but consecutively included within one treatment group. In fact, RCA with PC10/2 was initially applied in all patients on CVVH. At a given moment, we decided to replace PC10/2 by PC18. The reasons for changing the concentration of citrate were the followings: initially, all patients requiring CVVH in our ICU received PC10/2 for regional anticoagulation. To obtain better metabolic control (and especially better control of metabolic acidosis), we decided to replace PC10/2 (10 mmol citrate/L) by PC18 (18 mmol citrate/L). For practical reasons (storage capacity, short shelf-life of the citrate liquids, potential prescription errors), the hospital pharmacy did not make the two citrate solutions simultaneously available but delivered the PC18 solution after the PC10/2 stock was entirely consumed. Thus, a first group of patients received PC10/2 and, subsequently, a second group of patients was started on PC18. Regarding citrate dosage used during the study, these two dosage regimens (PC 18 & PC 10/2) fall within accepted dosing range for citrate anticoagulation. Solutions were not homemade but are CE-labelled and marketed by Gambro-Baxter. In- and exclusion criteria were identical for both study periods. CVVH was performed with the Prismaflex device (Gambro, Lund, Sweden) using an acrylonitrile 69 surface treated (AN69 ST) 150 membrane. Veno-venous access was obtained via a 13 F double-lumen polyurethane catheter (Joline, Swiss Confederation) inserted in the right internal jugular or a femoral vein. CVVH was delivered according to a dedicated protocol inspired by Tolwani et al. [17] and presented in detail previously [6]. This included standardized order sets and initial settings for all patients. Blood flow rate was set at 150 mL/min. Calcium chloride initially ran at 6 mL/h through a separate central venous line. Calcium infusion was titrated to maintain plasma ionized calcium levels between 1,0 and 1,2 mmol/L [6]. PC10/2 was delivered before the filter and started at a rate of 2200 mL/h. A bicarbonate-buffered solution (Prismasol 2) was infused in post-dilution, starting at 800 mL/h. In the PC18 group, citrate was delivered at a starting rate of 1500 mL/h and another bicarbonate buffer (Prismocal B22) in post-dilution at 400 mL/h. Detailed characteristics of the citrate and substitution fluids are shown in Table 2. Arterial blood gases, lactate, and serum electrolytes, including systemic and post-filter ionized calcium, were analyzed every 4 h. Acid-base status was evaluated with the Stewart-Figge method. This approach postulates that acid-base balance and pH depend on the difference between concentrations of strong cations and strong anions (ie the strong ion difference; SID), the PaCO2, and the total concentration of weak acids. It introduces the term “apparent strong ion difference” (SIDa) calculated as: ([Na+] + [K+] + [Mg2+] + [Ca2+]) - ([Cl−] - [lactate−]) (concentrations in mmol/L). The normal range for SIDa is approximately 40–44 mmol/L [18]. Since this equation does not account for weak acids (albumin, phosphate and CO2), the effective strong ion difference (SIDe) was calculated as (1000 × 2.46 × 10−11 × pCO2 / 10-pH) + [albumin] × (0.12 × pH - 0.631) + [phosphate] × (0.309 × pH - 0.469) (with pCO2 in mmHg, albumin in g/L and phosphate in mmol/L) [17]. The SIDa to SIDe difference should equal zero unless unmeasured charges are present in the blood. These charges are captured by the strong ion gap (SIG = SIDa - SIDe). A positive SIG value represents unmeasured anions that are needed to account for the measured pH, measured levels of strong ion and weak acids, and to assure iso-electricity [18]. Statistical analysis was performed using SPSS version 20 for Windows (SPSS Inc., Chicago, IL, USA). Chi-square and Fisher exact test were used to compare categorical variables between groups. The Mann-Whitney U test was applied for comparison of non-normally distributed parameters and the Wilcoxon test was used for comparing variables within a group. Values were expressed as medians (range) unless indicated otherwise.Table 2 Composition of citrate and bicarbonate-buffered solutions including their calculated SIDa Components (values in mmol/L) Prismocitrate 10/2 Prismocitrate 18 Prismasol 2 Prismocal B22 Citrate 10 18 Citric acid 2 Sodium (Na+) 136 140 140 140 Chloride (Cl-) 106 86 111.5 120.5 Calcium (Ca2+) 1.75 0 Magnesium (Mg2+) 0.5 0.75 Lactate 3 3 Hydrogen carbonate (HCO3-) 32 22 Potassium (K+) 2 4 Glucose 6.1 6.1 SIDa 30 54 29.75 21.25 Values for citrate, citric acid,electrolytes, lactate and SIDa are expressed in mmol/L Results Twenty-eight patients were enrolled in the PC10/2 group and 31 patients in the PC18 group. Treatment groups did not significantly differ for age, gender, type of disease, disease severity, presence of shock, and duration of mechanical ventilation. The evolution of relevant acid-base variables and electrolyte levels during the study are displayed in Table 3. Pre-treatment pH and chloride levels were comparable between groups ([7.26 (7.12–7.40) vs. 7.33 (7.22–7.44); p = 0.095] and [105 (99–112) vs. 106 (99–113) mmol/L; p = 0.326], PC10/2 vs. PC18). After 24 h of treatment, pH remained low in the PC10/2 group whereas it normalized in the PC18 group [7.28 (7.22–7.34) vs. 7.42 (7.37–7.47); p = 0.0001]. PC10/2 patients had higher baseline lactate concentrations. Thereafter, lactate equally decreased in both groups [from 4.6 (0–10.3) to 3.1 (0.2 – 6); p > 0.05 in PC10/2 patients and from 2.5 (0–5) to 2.1 (0.3–3.9); p > 0.05 in PC18 patients]. Lactate levels between groups were not anymore significantly different at 24 h.Table 3 Relevant acid base variables and electrolytes at baseline (T0) and after 24 h (T24) Variables Prismocitrate 10/2 Prismocitrate 18 P value pH T0 7,26 (7,12 – 7,40) 7,33 (7,22 – 7,44) 0.095 pH T24 7,28 (7,22 – 7,34) 7,42 (7,37 – 7,47) 0.0001 Na + T0 138 (133–144) 142 (134–149) 0.042 Na + T24 136 (133–139) 139 (135–145) 0.006 K+ T0 4,5 (3,7 – 5,3) 4,4 (3,7 – 5,3) 0.873 K+ T24 3,8 (3,4 – 4,2) 3,8 (3,4 – 4,2) 0.632 Cl- T0 105 (99–112) 106 (99–113) 0.326 Cl- T24 105 (102–108) 100 (95–105) 0.0001 Ca2+ T0 7,3 (6,4 – 7,2) 7,4 (6,6 – 8,2) 0.611 Ca2+ T24 8,6 (7,9 – 9,3) 9,2 (8,3 – 10,1) 0.004 Mg2+ T0 2 (1,6 – 2,4) 2,3 (1,8 – 2,8) 0.01 Mg2+ T24 1,8 (1,4 – 2,2) 2 (1,7 – 2,3) 0.040 SIDa T0 43 (38–48) 47 (41–53) 0.003 SIDe T0 27 (18–36) 39 (31–47) 0.0001 SIG T0 17 (11–23) 10 (6–16) 0.0001 SIDa T24 43 (40–43) 51 (47–55) 0.0001 SIDe T24 24 (19–29) 39 (35–43) 0.0001 SIG T24 17 (13–21) 12 (8–16) 0.0001 Lactate T0 4,6 (0–10,3) 2,5 (0–5) 0,031 Lactate T24 3,1 (0,2 – 6) 2,1 (0,3–3,9) 0,140 Values for electrolytes, SIDa, SIDe, SIG, and lactate are expressed as medians (range) in mmol/L Calculated SIDa values between groups were significantly different at baseline [43 (38–48) vs. 47 (41–53) mmol/L; p = 0.003]. After 24 h, SIDa had increased in PC18 patients [from 47 (41–53) to 51 (47–55) mmol/L; p = 0.001] but remained unchanged in the PC10/2 group [from 43 (38–48) to 43 (40–43); p > 0.05], resulting in a significantly higher SIDa in PC18 as compared with PC10/2 subjects (43 vs. 51 mmol/L; p = 0.001). At initiation of therapy, sodium concentration was lower in the PC10/2 than in the PC18 group [138 (133–144) vs. 142 (134–149) mmol/L; p = 0.04]. After 24 h, sodium concentration decreased in both groups, remaining significantly lower in the PC10/2 group as compared with the PC18 group [136 (133–139) vs. 139 (135–145) mmol/L; p = 0.006]. Calculated citrate flow was not statistically different between the two treatment periods (2.9 vs. 3 mmol/L of blood accessing the filter; p > 0.05). However, when differences in chloride concentration (106 vs. 86 mmol/L) and chloride flow (9.9 vs 5.4 mmol/L of blood accessing the filter) between the two citrate formulations were related to variations in citrate volume given between the two periods (2200 vs.1500 mL/h), the chloride flow per liter blood accessing the filter was found to be significantly higher in the PC10/2 group (25.9 vs. 14.3 mmol/L blood; PC10/2 vs. PC18; p < 0.05). This accounted for the difference in chloride levels between groups after 24 h of treatment [105 (102–108) vs.100 (95–105) mmol/L, PC10/2 vs. PC18; p = 0.0001]. SIG at 24 h also remained higher in the PC10/2 group (17 vs.12 mmol/L, PC10/2 vs. PC18; p = 0.001). At the end of study, none of the PC10/2 patients reached a pH >7.5 but 25 % had a SIDa > 45 mmol/L. In the PC18 group, 10.3 % of the patients had pH values > 7.5 whereas 93 % were diagnosed with a SIDa > 45 mmol/L. Discussion The buffering capacity of a citrate solution depends on the conversion of trisodium citrate to citric acid (Na3citrate + 3H2CO3 → citric acid (C6H8O7) + 3NaHCO3) and thus to the proportion of sodium as a cation. Hence, 1 mmoL trisodium citrate provides the same buffer strength as 3 mmol sodium bicarbonate, assuming that citrate is completely metabolized. Citric acid does not act as a buffer [4, 8, 18]. Following citrate metabolism, the remaining sodium increases the SIDa. Increasing SIDa (eg by infusing Plasmalyte®) produces alkalosis while the administration of a zero-SIDa solution (eg NaCl 0.9 %) will decrease SIDa and contribute to metabolic acidosis. Our findings suggest that a higher chloride-containing citrate solution (PC10/2) for RCA-CVVH may significantly reduce alkalosis-buffering capacity. One would expect that administration of PC10/2 (30 mmol/L of buffer equivalent) should be associated with a metabolic acidosis. Looking from a pure buffer equivalence perspective, this acidosis is considered to be primarily determined by a decrease in SIDa [10, 11]. Accordingly, PC18 (54 mmoL of buffer equivalent) should lead to more rapid correction of acidosis and progressive development of metabolic alkalosis. Before the start of CVVH, both patient groups had mild metabolic acidosis. This acidosis resulted from increased unmeasured anions (high SIG) in the presence of an increased lactate level and was more pronounced in the patients receiving PC10/2 [19–21]. Within 24 h, acidosis was completely reversed in all patients who received the solution with a higher citrate concentration (PC18) along with a decrease in serum chloride and an increase in SIDa. In contrast, patients who received PC10/2, developed hyperchloremic acidosis. SIDa and SIG in this group remained unchanged which counteracted citrate-induced metabolic alkalosis. Since citrate flow entering the filter was similar during the two study periods (the difference in citrate concentrations being compensated by variations in citrate volume), the observed largely uncorrected acidosis and higher SIG at 24 h in the PC10/2 group is most plausibly explained by the higher chloride content of the PC10/2 solution. The lower bicarbonate concentration in the substitution fluid administered in PC18 as compared with PC10/2 subjects (22 vs. 32 mmol/L) cannot account for the less rapid correction of acidosis. Rather, this low bicarbonate load should have attenuated late rebound alkalosis. Baseline lactate was higher in the PC10/2 group. However, lactate levels had decreased in both PC10/2 and PC18 patients at 24 h. At that time, concentrations were no longer different between groups making it unlikely that lactate significantly contributed to the persisting metabolic acidosis in patients receiving PC10/2. This leads to hypothesize that the high chloride-containing citrate solution used for RCA-CVVH significantly reduces alkalosis-buffering capacity and thus blunts correction of acidosis. This “blunting effect” may be explained by differences in chloride flow between the applied citrate solutions inducing hyperchloremic acidosis. Our findings argue against currently used therapeutic approaches. To date, clinicians try to correct metabolic acidosis during CVVH by administering additional bicarbonate infusion [17, 22]. However, excess intravenous bicarbonate may cause unwarranted side-effects and even increase mortality [22]. Consequently, new citrate formulations have been implemented to avoid rebound metabolic alkalosis whilst assuring timely correction of acidosis and obviating the need to infuse intravenous bicarbonate. Our study underscores a potential role of the “forgotten” chloride anion in acid-base equilibrium [11, 18, 20]. Different citrate formulations, albeit infused at similar flow rates and sharing equivalent citrate-related buffer strength, may exhibit divergent capacity and speed to correct acidosis because of a substantial difference in chloride content. The lower SIDa and the higher SIG after 24 h of CVVH in patients treated with PC10/2 as compared with PC18 were related to a higher plasma chloride concentration. Interestingly, this untoward “side-effect” associated with citrate formulations has been alluded to [22–26] but was never studied in depth. Tolwani et al. compared a 0.67 % with a 0.5 % trisodium citrate replacement solution for continuous veno-venous hemodiafiltration (CVVHDF). The 0.5 % citrate solution (18 mmol/L citrate) maintained an appropriate acid-base balance whereas the 0.67 % solution (23 mmol/L citrate) resulted in a mild but unexplained alkalosis [17]. Citrate and chloride flow were comparable between groups and citrate concentration likely similar as both filter lifespan and post-filter ionized calcium were not different [17]. We suggest that applying the Stewart-Figge principle instead of a strictly pH-directed approach allows to unravel this intriguing metabolic issue. The 0.5 and 0.65 % citrate solutions used by Tolwani et al. [17] had a SID of respectively 54 and 69 mmol/L (ie equivalent of bicarbonate generation). Knowing that both solutions contained 140 mmol/L sodium, the principle of solution electro-neutrality requires chloride levels of respectively 89 and 74 mmol/L [18]. Thus, notwithstanding the use of a chloride-rich dialysate (118.5 mmol/L), the significantly lower chloride content of the 0.65 % citrate liquid induced metabolic alkalosis. Our study results, although obtained under different CRRT conditions, do corroborate these findings. Egi et al. found that increasing the citrate dose during RCA-CVVH significantly attenuated magnitude and duration of metabolic acidosis [9]. When administering respectively 11 and 14 mmol/L citrate (ie a SIDa of respectively 33 and 42 mmol/L), they observed an alkalinizing effect depending on the SIDa of the replacement fluid and an acidifying effect due to an increase in unmeasured anions [9, 17]. The highly different citrate flow between groups (1.83 vs. 3.10 mmol/L blood, 22 vs. 28 mmol/h, and 520 vs. 672 mmol/day) might explain the observed alkalinizing effect [9]. Compared with our patients, hyperchloremic metabolic acidosis did not occur as the difference in chloride flow was less pronounced (18 vs.16.5 mmol/L blood) for a chloride content of 108 vs. 99 mmol /L [9, 11]. Interestingly, the recent observation that hypochloremic dialysis can correct metabolic acidosis by reducing unmeasured anions indirectly adds support to our findings [27]. Some limitations of our study must be recognized. Its observational and unblinded “before-after” design without randomizing patients towards a specific treatment may have rendered comparisons between groups less accurate. A possible effect of the different bicarbonate post-dilution solutions with different SIDs was not integrated in global acid-base evaluation. However, this probably had marginal importance since, unlike our findings, it should have improved acidosis in the patients receiving the lower citrate concentration [11]. As the PC10/2 formulation was initiated within the context of a newly implemented citrate protocol, an inherent learning process might have biased our results. Still, data were obtained during 24 h of treatment and an appropriate control group was available. It is unclear whether any back-diffusion of chloride [28] during CVVH occurred. Finally, one might argue that different results might be obtained with CVVHDF. However, it is doubtful that CVVHDF would have obviated hyperchloremia as chloride was provided continuously [28, 29]. Apart from being more labor-intensive and expensive [28, 30], CVVHDF also provides no superior control of electrolyte balance [31] and eventual competition between convection and diffusion at the inner part of the membrane may blunt diffusion capacity [32]. Conclusions In conclusion, the Stewart-Figge approach allowed to elaborate previous experience showing that metabolic acidosis is attenuated and buffer capacity increased when a citrate solution that contains less chloride is used for RCA. We postulate that a greater divergence in chloride flow accounts for the significant difference in severity and duration of metabolic acidosis observed in patients undergoing CVVH who receive different citrate solutions at similar flow rate and with equal buffer capacity. Our findings, albeit provocative and suggesting a change in attitude towards a more optimal metabolic control during RCA-CVVH, remain hypothetical and definitely need confirmation by a large randomized controlled trial. Bullet Points RCA-CRRT in patients with AKI and metabolic acidosis should be performed with Prismocitrate 18. Metabolic alkalosis can be corrected by switching to Prismocitrate 10/2 or even better by infusing natrium chloride 0.9 % instead of bicarbonate solution as substitution fluid. The Stewart-Figge method may represent a better tool to assess changes in acid-base metabolism during RCA-CRRT. A divergence in chloride but not citrate flow may be a plausible explanation for the difference in severity and duration of metabolic acidosis. Abbreviations AKIAcute kidney injury ANAcrylonitrile CRRTContinuous renal replacement therapy CVVHContinuous veno-venous hemofiltration CVVHDFContinuous veno-venous hemodiafiltration RCARegional citrate anticoagulation SIDaApparent strong ion difference SIDeEffective strong ion difference SIGStrong ion gap STSurface treated Acknowledgements None. Funding None. Availability of data and materials We provide all relevant data in the paper. Supporting files are not used. Authors’ contributions RJ, PMH and HDS designed the study. RJ was in charge of the data base and chart review. RJ, PMH, MD and HDS had full access to the database. MD performed the statistical analysis. RJ, PMH, MD and HDS contributed to data interpretation. RJ, PMH, MD and HDS drafted the manuscript. All authors have read and approved the final version. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable as only summary congregated data are presented. Ethics approval and consent to participate The Central Ethical Committee of the University Hospital approved the study protocol (BUN 143201318818). Due to its observational before-after design, the need for informed consent was waived. ==== Refs References 1. Lameire N Kellum JA for the KDIGO AKI Guideline Work Group Contrast-induced acute kidney injury and renal support for acute kidney injury: a KDIGO summary (Part 2) Crit Care 2013 17 205 10.1186/cc11455 23394215 2. Mehta RL McDonald BR Regional citrate anticoagulation for continuous arterio-venous hemodialysis in critically ill patients Kidney Int 1990 38 976 81 10.1038/ki.1990.300 2266683 3. Claure-Del Granado R Bouchard J Acid–base and electrolyte abnormalities during renal support for acute kidney injury: recognition and management Blood Purif 2012 34 186 93 10.1159/000341723 23095419 4. Tolwani A Wille KM Advances in continuous renal replacement therapy: citrate anticoagulation update Blood Purif 2012 34 88 93 10.1159/000342378 23095407 5. Shum HP Chan KC Yan WW Regional citrate anticoagulation in predilution continuous venovenous hemofiltration using prismocitrate 10/2 solution Ther Apher Dial 2012 16 81 6 10.1111/j.1744-9987.2011.01001.x 22248200 6. Jacobs R Honoré PM Bagshaw SM Diltoer M Spapen HD Citrate Formulation Determines Filter Lifespan during Continuous Veno-Venous Hemofiltration: A Prospective Cohort Study Blood Purif 2015 40 194 202 10.1159/000438820 26302765 7. Jacobs R, Honore PM, De Regt J, de Mars M, Spapen HS. The Stewart Approach. Text book of Renal Replacement Therapy in Critical Care. Saarbrucken, Germany: Lambert Academic Publishing; 2016;84–100 8. Oudemans-van Straaten HM Bosman RJ Koopmans M van der Voort PH Wester JP van der Spoel JL Dijksman LM Zandstra DF Citrate anticoagulation for continuous venovenous hemofiltration Crit Care Med 2009 37 545 52 10.1097/CCM.0b013e3181953c5e 19114912 9. Egi M Naka T Bellomo R The acid–base effect of changing citrate solution for regional anticoagulation during continuous veno-venous hemofiltration Int J Artif Organs 2008 31 228 36 18373316 10. Lanckohr C Hahnenkamp K Boschin M Continuous renal replacement therapy with regional citrate anticoagulation: do we really know the details? Curr Opin Anaesthesiol 2013 26 428 37 10.1097/ACO.0b013e3283620224 23673990 11. Jacobs R Honore PM Spapen HD Some metabolic issues should not be neglected when using citrate for continuous renal replacement therapy! Crit Care 2015 19 50 10.1186/s13054-015-0766-3 25738824 12. Tolwani AJ Wille KM Anticoagulation for continuous renal replacement therapy Semin Dial 2009 22 141 5 10.1111/j.1525-139X.2008.00545.x 19426417 13. Mallat J Michel D Salaun P Thevenin D Tronchon L Defining metabolic acidosis in patients with septic shock using Stewart approach Am J Emerg Med 2012 30 391 8 10.1016/j.ajem.2010.11.039 21277142 14. Morgan TJ The Stewart approach-one clinician’s perspective Clin Biochem Rev 2009 30 41 54 19565024 15. Kishen R Honoré PM Jacobs R Joannes-Boyau O De Waele E De Regt J Van Gorp V Boer W Spapen HD Facing acid–base disorders in the third millennium – The Stewart approach revisited Int J Nephrol Renovasc Dis 2014 7 209 17 24959091 16. Bellomo R Ronco C Kellum JA Mehta RL Palevsky P Acute Dialysis Quality Initiative workgroup Acute renal failure - definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group Crit Care 2004 8 R204 12 10.1186/cc2872 15312219 17. Tolwani AJ Prendergast MB Speer RR Stofan BS Wille KM A practical citrate anticoagulation continuous venovenous hemodiafiltration protocol for metabolic control and high solute clearance Clin J Am Soc Nephrol 2006 1 79 8 10.2215/CJN.00040505 17699194 18. Kellum JA Elbers PW Stewart’s textbook of acid–base 2009 201 3 19. Joannidis M Oudemans-van Straaten HM Clinical review: patency of the circuit in continuous renal replacement therapy Crit Care 2007 11 218 10.1186/cc5937 17634148 20. Nagaoka D Nassar Junior AP Maciel AT Taniguchi LU Noritomi DT Azevedo LC Neto LM Park M The use of sodium-chloride difference and chloride-sodium ratio as strong ion difference surrogates in the evaluation of metabolic acidosis in critically ill patients J Crit Care 2010 25 525 31 10.1016/j.jcrc.2010.02.003 20381294 21. Hetzel GR Schmitz M Wissing H Ries W Schott G Heering PJ Isgro F Kribben A Himmele R Grabensee B Regional citrate versus systemic heparin for anticoagulation in critically ill patients on continuous venovenous haemofiltration: a prospective randomized multicentre trial Nephrol Dial Transplant 2011 26 232 9 10.1093/ndt/gfq575 20876598 22. Wilson RF Spencer AR Tyburski JG Dolman H Zimmerman LH Bicarbonate therapy in severely acidotic trauma patients increases mortality J Trauma Acute Care Surg 2013 74 45 50 10.1097/TA.0b013e3182788fc4 23271076 23. Leung AK Shum HP Chan KC Chan SC Lai KY Yan WW A retrospective review of the use of regional citrate anticoagulation in continuous venovenous hemofiltration for critically ill patients Crit Care Res Pract 2013 23424680 24. Aiken CG History of medical understanding and misunderstanding of Acid base balance J Clin Diagn Res 2013 9 2038 41 24179938 25. Mallat J Barrailler S Lemyze M Pepy F Gasan G Tronchon L Thevenin D Use of sodium-chloride difference and corrected anion gap as surrogates of Stewart variables in critically ill patients PLoS One 2013 8 10.1371/journal.pone.0056635 23418590 26. Davenport A Potential adverse effects of replacing high volume hemofiltration exchanges on electrolyte balance and acid–base status using the current commercially available replacement solutions in patients with acute renal failure Int J Artif Organs 2008 31 3 5 18286449 27. Marques FO Libório AB Daher EF Effect of chloride dialysate concentration on metabolic acidosis in maintenance hemodialysis patients Braz J Med Biol Res 2010 43 996 1000 10.1590/S0100-879X2010007500094 20878015 28. Libório AB da Silva AC Noritomi DT Andrade L Seguro AC Impact of chloride balance in acidosis control: The Stewart approach in hemodialysis critically ill patients J Crit Care 2006 21 333 8 10.1016/j.jcrc.2006.03.011 17175420 29. Lee YS Clinical Significance of Strong Ion Gap: between ICU and Hemodialysis Patients with Metabolic Acidosis Electrolyte Blood Press 2007 5 1 8 10.5049/EBP.2007.5.1.1 24459493 30. Honore PM, Jacobs R, De Regt J, de Mars M, Spapen HS. Citrate during CRRT. Text book of Renal Replacement Therapy in Critical Care. Saarbrucken, Germany: Lambert Academic Publishing; 2016;130–157 31. Morimatsu H Uchino S Bellomo R Ronco C Continuous renal replacement therapy: does technique influence electrolyte and bicarbonate control? Int J Artif Organs 2003 26 289 96 12757027 32. Honoré PM Joannes-Boyau O Collin V Boer W Gressens B Janvier G Practical daily management of extra-renal continuous removal Reanimation 2008 17 472 8 10.1016/j.reaurg.2008.04.008

PMC005xxxxxx/PMC5000456.txt

==== Front BMC Health Serv ResBMC Health Serv ResBMC Health Services Research1472-6963BioMed Central London 170210.1186/s12913-016-1702-1Research ArticleConvergent validity of the interRAI-HC for societal costs estimates in comparison with the RUD Lite instrument in community dwelling older adults http://orcid.org/0000-0001-5707-2345van Lier Lisanne I. l.vanlier@vumc.nl 1van der Roest Henriëtte G. hg.vanderroest@vumc.nl 1van Hout Hein P. J. hpj.vanhout@vumc.nl 1van Eenoo Liza liza.vaneenoo@kuleuven.be 2Declercq Anja anja.declercq@kuleuven.be 2Garms-Homolová Vjenka garmsho@htw-berlin.de 3Onder Graziano graziano.onder@rm.unicatt.it 4Finne-Soveri Harriet harriet.finne-soveri@thl.fi 5Jónsson Pálmi V. palmivj@landspitali.is 6Hertogh Cees M. P. M. cmpm.hertogh@vumc.nl 1Bosmans Judith. E. j.e.bosmans@vu.nl 71 Department of General Practice and Elderly Care Medicine and EMGO+ Institute for Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands 2 LUCAS, Centre for Care Research and Consultancy KU Leuven (University of Leuven), Minderbroederstraat 8, box 5310, B-3000 Leuven, Belgium 3 HTW Berlin, FB III-Economics, Treskowallee 8, D-10318 Berlin, Germany 4 Department of Geriatrics, Università Cattolica del Sacro, Largo F. Vito 1, 00168 Rome, Italy 5 Department of Wellbeing, National Institute for Health and Wellbeing, P.O. BOX 30, FI-00271 Helsinki, Finland 6 Department of Geriatrics, Landspitali National University Hospital and Faculty of Medicine, University of Iceland, Landakot, 101, Reykjavik, Iceland 7 Department of Health Sciences and EMGO+ Institute of Health and Care Research, Faculty of Earth and Life Sciences, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands 25 8 2016 25 8 2016 2016 16 1 4405 12 2015 24 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The interRAI-Home Care (interRAI-HC) instrument is commonly used in routine care to assess care and service needs, resource utilisation and health outcomes of community dwelling home care clients. Potentially, the interRAI-HC can also be used to calculate societal costs in economic evaluations. The purpose of this study was to assess the convergent validity of the interRAI-HC instrument in comparison with the RUD Lite instrument for the calculation of societal costs among care-dependent community dwelling older adults. Methods A within-subject design was used. Participants were 65 years and older and received professional community care in five countries. The RUD Lite was administered by trained (research) nurses or self-reports within 4 weeks after the interRAI-HC assessment. Agreement between the interRAI-HC and RUD Lite estimates was assessed using Spearman’s correlation coefficients. We hypothesised that there was strong correlation (Spearman’s ρ > 0.5) between resource utilisation estimates, costs of care estimates and total societal cost estimates derived from both instruments. Results Strong correlation was found between RUD Lite and interRAI-HC resource utilisation assessments for eight out of ten resource utilisation items. Total societal costs according to the RUD Lite were statistically significantly lower than according to the interRAI-HC (mean difference €-804, 95 % CI −1340; −269). The correlation between the instruments for total societal costs and all six cost categories was strong. Conclusions The interRAI-HC has good convergent validity as compared with the RUD-Lite instrument to estimate societal cost of resource utilisation in community dwelling older adults. Since interRAI-HC assessments are part of routine care in many community care organisations and countries already, this finding may increase the feasibility of performing economic evaluations among community dwelling older adults. Electronic supplementary material The online version of this article (doi:10.1186/s12913-016-1702-1) contains supplementary material, which is available to authorized users. Keywords Convergent validityCorrelationResource utilisationCosts of careSocietal costsRoutine care assessmentInterRAI-HCRUD LiteCommunity careOlder adultshttp://dx.doi.org/10.13039/501100004963Seventh Framework Programme305912van Hout Hein P. J. issue-copyright-statement© The Author(s) 2016 ==== Body Background The population in Europe is ageing rapidly [1]. Between 2010 and 2050, the proportion of adults aged 65 years and older is expected to increase from 8 to 16 % [2]. Many older adults experience difficulties in activities of daily living due to chronic illnesses or health-related disabilities which limit their ability to live independently in their homes which may be further complicated by cognitive problems [3]. However, most older adults want to continue to live independently in their own environment for as long as possible, and this is also encouraged by many European governments [2, 3]. As a consequence, the demand for (long-term) formal and informal care services is expected to grow substantially in the coming decades, which will put heavy pressure on health care systems across Europe [2, 4]. Since budgets available for health care are limited, policy makers need to make decisions on how to allocate health care resources in the most efficient way. Economic evaluations can inform such allocation decisions by providing information on the relative efficiency of alternative health care interventions [5]. To estimate costs in economic evaluations, the utilisation of health care and social care resources needs to be quantified. Specific instruments have been developed to collect information on resource utilisation retrospectively by means of self-report structured questionnaires or interviews, such as the Resource Utilization in Dementia (RUD) Lite instrument [6]. Another way to collect this information from clients, is by using routine care assessments, that are administered by a health professional who is involved in the care for the client. When using routine care assessments, individuals are not exposed to additional questionnaires for measuring resource utilisation in economic evaluations which may be an important advantage in vulnerable patient groups such as care-dependent older adults. An example of a routine care instrument for this specific population is the interRAI Home Care instrument (interRAI-HC). The interRAI-HC is a standardised multidimensional geriatric assessment instrument that has been designed to assist in care planning, outcome measurement, quality improvement, and resource allocation for clients who receive care at home [7–9]. In the interRAI-HC, resource allocation is based on the advanced case-mix classification system “Resource Utilization Groups III Home Care (RUG-III-HC)” [10, 11]. The RUGs are based on client characteristics and do not reflect ‘actual’ care utilisation rates. Although the interRAI-HC was not specifically developed to estimate costs of resource utilisation, Brown et al. [12] have previously used this instrument to do this. However, when using the interRAI-HC to calculate costs of resource utilisation over a period of three months or longer, utilisation of health care services has to be extrapolated to longer periods. It is unclear whether this results in valid estimates of resource utilisation and costs over a period of three months or more. This is in contrast with the RUD Lite instrument which was specifically developed to measure utilisation of formal and informal care services and is widely used to estimate societal costs in community-dwelling people with dementia [6, 13, 14]. In order to evaluate whether the interRAI-HC can be validly used to estimate resource utilisation and associated costs, the convergent validity of the interRAI-HC instrument is studied in comparison with the RUD Lite instrument in a sample of care-dependent community dwelling older adults. Both resource utilisation of formal and informal care services and cost estimates between the two instruments will be compared. Methods Design This study is part of the cross-European IBenC (“Identifying best practices for care-dependent elderly by Benchmarking Costs and outcomes of community care”) project that aims to provide insight into the costs and quality of community care delivery systems across Europe [15]. The study was approved by relevant legal authorised medical ethical committees in the countries that participated in the IBenC project (Belgium, Finland, Germany, Iceland, Italy, and The Netherlands). For this sub-study, a within-subject design was used to evaluate the convergent validity of the interRAI-HC instrument in comparison with the RUD Lite instrument to measure resource utilisation and estimate costs from a societal perspective. Convergent validity was evaluated, since there is no gold standard for resource utilisation measurements. The data collection was conducted between January 2013 and March 2015. Setting and sample Participants of the IBenC project were community dwelling adults aged 65 years and older who received care by a home care or community care organisation, or by a primary care nurse, and who were expected to receive care for at least six more months. In each participating country, one to six care organisations participated in the IBenC study. Per country, a subsample of at least 50 participants and their primary informal caregivers were selected for participation in this sub-study. Terminally ill persons and cognitively impaired persons (score of three or higher on the Cognitive Performance Scale (CPS) [16]) without an informal caregiver who was willing to participate as a proxy, were not included in the sub-study. Procedure Clients receiving care from community care organisations that were involved in the IBenC project and who fulfilled the inclusion criteria were invited to participate, or automatically enrolled in the IBenC study in accordance with local ethical regulations. Prior to the start of the assessments, written informed consent was obtained from the participants. When a participant was known to be cognitively impaired (CPS ≥ 3 [16]), informed consent from a close relative, legal representative or legal guardian on behalf of the participant was obtained. Two third of the participating community care organisations used the interRAI-HC instrument in routine care to monitor the health and care status of their clients. In community care organisations that did not use the interRAI-HC instrument in routine care, (research) nurses were trained to perform the interRAI-HC assessments. The assessments were completed based on observation from the (research) nurse, information from medical records, and information obtained by interviewing the client and their informal caregiver (if available). InterRAI-HC assessments were performed at baseline, after 6 and 12 months. At the start of the data collection period, participants were invited by community care organisations to participate in an additional assessment with the RUD Lite (according to local protocols). The RUD Lite assessment took place at the home of the participant within 4 weeks after the index interRAI-HC assessment and was performed as an interview by a trained (research) nurse. A brief description of the aims of the IBenC study was provided during the training. If the participant was cognitively impaired, the (primary) informal caregiver completed the assessment. During the assessment, participants without cognitive impairment were asked for consent to contact their primary informal caregiver, in order to interview him or her on the amount of informal care provided to the participant. If participants did not consent, they answered these questions themselves. In Finland, the RUD Lite assessments were completed by participants or informal caregivers themselves by means of a written questionnaire. In case of difficulty due to, for example, cognitive impairment participants were assisted by a nurse (n = 18). InterRAI-HC instrument In the interRAI-HC [7–9], information on the utilisation of home health care (home health aid), home nursing, homemaking services, physical therapy, occupational therapy, and psychological treatment, is collected by registering the number of days and the total number of minutes of care received in the 7 days prior to the assessment. With regard to physical therapy, occupational therapy, and psychological treatment, we assumed that the number of days per week the service was received, reflected the number of sessions received during a week. The utilisation of the supportive care service “meals on wheels” is registered in number of days the service was used during the 7 days prior to the assessment. The number of hospital admissions, emergency room visits and visits to a physician (specialist, authorised assistant or general practitioner) are registered over the 90 days prior to the assessment. The total number of hours of all informal care and active monitoring provided by informal carers to a participant are assessed in the 3 days prior to the assessment. In order to estimate the amount of resource utilisation over a period of 3 months, resource utilisation items with a recall period of 7 days were extrapolated to reflect a period of 3 months. Resource utilisation estimates (number of days, hours of care, or number of sessions) were multiplied by 13 (3months correspond to 13 weeks). Informal care hours were divided by three and multiplied by 91. The interRAI-HC assesses the number of hospital stays but does not assess the number of nights. To estimate the number of nights, we used country-specific averages of length of stay during hospital admission in the year 2012 and multiplied these rates by the number of hospital admissions (see Table 1 [17]).Table 1 Overview of used unit cost (in € 2015) and average length of stay (days) Care service Costs (€) per unit Home care  Home health and domestic care (including home health care, home nursing and home making services) 38.00 per hour Physician visits  General practitioner visit 30.40 per visit  Outpatient clinic visits 78.16 per visit Other health care services  Physical therapy 39.08 per session  Occupational therapy 23.88 per session  Psychological treatment 86.85 per session Hospital admissions  Hospital admission with overnight stay   General ward 496.11 per day with overnight stay   ICU 2369.82 per day with overnight stay  Average length of hospital staya   Belgium 6.7 days   Finland 11.0 days   Germany 9.2 days   Iceland 5.8 days   Italy 7.7 days   The Netherlands 5.2 days  Emergency room visit (without overnight stay) 163.92 per visit Supportive care services  Meals on wheels 7.06 per day Informal care  Informal care 13.57 per hour aSource: OECD, 2015 The interRAI-HC includes several functional scales which were used to describe the study population. Cognitive functioning was assessed using the Cognitive Performance Scale (CPS, range 0–6). Moderate or severe cognitive impairment was considered to be present if CPS ≥ 3 [16]. The Depression Rating Scale (DRS, range 0–14) was used to assess depressive symptoms. A score of three or more on the DRS indicates minor or major depressive disorder [18]. Activities of daily living (ADL) needs were assessed using the interRAI Activities of Daily Living Hierarchy Scale (ADLH, range 0–6) with higher scores indicating higher ADL needs [19]. Difficulty in performing instrumental activities (iADL) was assessed using the interRAI Instrumental ADL Performance Scale (iADLP, range 0–48) with higher scores indicating more iADL dependencies [20]. Pain was considered to be present if the score on the Pain Scale (range 0–3) was one or higher [21]. Multimorbidity was defined to be present when an individual indicated to have two or more chronic medical conditions [22]. RUD Lite The RUD Lite was specifically developed to measure resource utilisation from a societal perspective among older adults with dementia [6, 13, 14, 23, 24]. Although the RUD Lite was originally developed to measure resource utilisation in people with dementia, the services that are covered by the instrument are also used by vulnerable community-dwelling older adults without dementia. The validity of the instrument has been studied extensively, especially the items that assess caregiver time [13, 24]. Therefore, we chose this instrument to compare resource utilisation according to the interRAI-HC with. Moreover, the RUD Lite (version 3.2) was available in five of the six languages of the countries that participated in the IBenC project. The RUD instrument is divided into two subsections; a section that assesses background information of the client and his/her utilisation of health care services and a section that assesses caregiver time. For this specific study, the recall period for all items in the questionnaire was extended from 30 days to 3 months to match up with interRAI-HC recall periods. The frequency of service use was changed from the number of visits during the last month into the average number of visits per week during the last 3 months. We made two versions, a client version, in which the questions were directly targeted at the clients, and a caregiver version. The latter was used when the caregiver answered the questions instead of the client. The adapted language versions were translated for use in the IBenC study by a process of forward translation, reconciliation and back translation review. The translations were performed by independent qualified translators. Utilisation of home health care, home nursing, and homemaking services, was registered as average number of times per week and average number of hours and minutes per visit the service was received in the 3 months prior to the assessment. Use of meals on wheels was recorded as average number of service meals received per week. Physical therapy, occupational therapy, psychological treatments, emergency room visits, general practitioner visits and outpatient clinic visits were registered as total number of visits in the 3 months prior to the assessment. The number of hospital admissions and the total length of stay (number of nights) stratified by ward type (general ward and Intensive Care Unit (ICU)) in the past 3 months was recorded. Informal care provision (personal ADL and instrumental ADL) and supervision (or surveillance) provided by the primary informal caregiver was assessed as total number of days during the last 3 months, as well as the number of hours and minutes on a typical care day during this period. In order to estimate the amount of resource utilisation over a period of 3 months, the average use of care services recorded on a weekly basis was extrapolated by multiplying the estimates by 13. The number of days on which informal care was provided was multiplied by the recorded number of hours of informal care received. Also, the share of care provisioning by the primary informal caregiver was recorded (1–20 %, 21–40 %, 41–60 %, 61–80 %, 81–100 %) and the number of other informal caregivers involved. The total amount of time of informal care was estimated by dividing the median value of the answer categories by the amount of caregiving time. Cost estimates Standardised costs were used for all countries in order to avoid variations in costs due to country specific differences in care valuation. Since European standard costs are lacking, resource utilisation was valued using Dutch standard costs [25]. Because of country specific categorisation of health care and social service provisioning, it was not possible to make a clear distinction between the utilisation of different types of home care services. Therefore, hours of home health care, home nursing and homemaking services were first summed into “home health and domestic care”, and then valued using the weighted standard cost for home care [25]. All costs were adjusted to the year 2015 using consumer price indices [26]. Six cost categories were distinguished: home health and domestic care, physician visits, other health care services, hospital admissions, supportive care services, and informal care. Additionally, these cost categories were summed into total societal costs. Table 1 lists the care services per cost category and prices per unit as used in this study. With regard to physician visits, in contrast to the RUD Lite, the interRAI-HC makes no distinction between outpatient clinic visits and general practitioner visits. We assumed that most visits were visits to an outpatient clinic. Therefore, physician visits assessed with the interRAI HC were valued using the price of outpatient clinic visits. Statistical analysis All analyses were performed using SPSS statistics 20 [27]. Demographic and clinical characteristics of the participants, utilisation of formal and informal care, and costs estimates were described using descriptive statistics and frequencies. Differences in baseline characteristics between participants from different countries were evaluated using Chi-square tests for categorical variables and ANOVAs for continuous variables. Mean differences in utilisation rates and costs between the RUD Lite and interRAI-HC were statistically tested using paired sample t-tests. Because of the skewed distribution of the resource utilisation and cost data, 95 % confidence intervals (CIs) were estimated using bias-corrected accelerated bootstrapping (5000 replications) [28]. The agreement between the resource utilisation measurements and cost estimates of the interRAI-HC instrument and the RUD Lite instrument was assessed using Spearman’s ρ correlation coefficients, since the distribution of resource utilisation and costs were skewed. According to Cohen et al. correlation of 0.10–0.30 corresponds to weak correlation, 0.30–0.50 to moderate correlation and 0.50 or higher corresponds to strong correlation [29]. To evaluate the convergent validity of the interRAI-HC for resource utilisation measurement as compared to the RUD Lite, we hypothesised that the strength of the correlation between interRAI-HC and the RUD Lite resource utilisation items was strong (Spearman’s ρ > 0.50). Ten predefined hypotheses on resource utilisation were tested: hours of home health and domestic care, number of physician visits, number of physical therapy sessions, number of occupational therapy sessions, number of psychological treatment sessions, number and duration of hospital admissions, number of emergency room visits, number of meals on wheels, and hours of informal care. We also hypothesised that the correlation between cost of care estimates within the six cost categories and the total societal cost of resource utilisation collected with the interRAI-HC and the RUD Lite was strong (seven hypotheses, Spearman’s ρ > 0.50). In total 17 hypotheses were tested. The correlation between the total societal costs of resource utilisation according to the two instruments were also analysed using a Bland-Altman plot [30]. For each participant, the mean of the total societal costs based on the RUD Lite and the interRAI-HC was plotted against the difference in mean total societal costs between the RUD Lite and the interRAI-HC. The variability of the differences in total societal cost estimates between the two instruments and the limits of agreement, calculated as mean difference +/- 1.96 SD, were visualized in this plot. The limits of agreement can be interpreted as the interval in which approximately 95 % of the differences in total societal cost estimates between the two instruments should lie. The smaller the range between these two limits, the better the agreement between both instruments is. Participants from Italy (n = 102) were excluded from data-analyses due to protocol violation; the resource utilisation section of the RUD Lite was completed with data derived from the client’s administrative chart which also formed the basis for the interRAI-HC assessment. Furthermore, participants from Belgium (n = 103) were also excluded from the main analysis since the amount of caregiving time was not assessed. This item was not available in the Belgian interRAI-HC software. Sensitivity analysis A sensitivity analysis was performed to test the correlation between cost of care estimates from a health care perspective, meaning that informal care costs were excluded from the analysis. We hypothesised that the correlation between total health care cost estimates with the interRAI-HC and the RUD Lite was strong as well (Spearman’s ρ > 0.50). In this sensitivity analysis, Belgian participants were included. The interRAI-HC does not collect information on length of hospital stay. Therefore, country-specific averages of length of stay (in days) during hospital admission of the year 2012 based on the OECD database were used to estimate the number of nights spend in the hospital based on the number of hospital admissions as collected with the interRAI-HC. We did a sensitivity analysis in which we subtracted 1 from the average number of hospital days to obtain an estimate of the average number of hospitalisation nights. Furthermore, a sensitivity analysis was performed to assess the correlation between both instruments stratified for people with cognitive problems (CPS ≥3) and people without cognitive problems. Different administration modes of the RUD Lite questionnaire were used in this study; the RUD Lite was administered as an interview with the client, with the client and caregiver together or with the caregiver alone. Also, in Finland the RUD Lite questionnaires were completed on paper by the client or caregiver themselves. In a few cases, nurses from the care agency assisted the client completing the questionnaire. A sensitivity analysis was performed to evaluate the effect of the different administration modes of the RUD Lite on the correlation between the RUD Lite and the interRAI-HC. Results Study sample The subsample consisted of 790 participants. In total, 134 (17 %) subjects were excluded from the main analysis due to missing values on one or more resource utilisation items: 103 from Belgium, three from Germany, 23 from Finland, and five from the Netherlands. Compared to the participants, the excluded subjects were statistically significantly (p < 0.05) younger, suffered relatively more often from cognitive impairment and depression, scored higher on ADL and iADL, experienced multimorbidity less frequently, and had a higher number of caregivers. In total, 656 (83 %) participants were included in the analyses. Participants were on average 83.2 years of age (SD 7.2), 67 % was female and 24 % of the participants was dependent in at least one of four ADLs (personal hygiene, toilet transfer, locomotion and/or eating (score of two or higher on ADLH)). Statistically significant differences (p < 0.05) between participants across countries were found for age, living status, CPS, DRS, ADL, iADL, pain, multimorbidity and number of caregivers (see Table 2).Table 2 Characteristics of the study population Total (n = 656) Finland (n = 346) Germany (n = 60) Iceland (n = 103) Netherlands (n = 147) Test statistics p-value Mean age (SD) 83.2 (7.2) 83 (7.2) 84.1 (8.0) 84.7 (6.2) 82.2 (7.2) F = 2.97 0.03 Female (n, %) 439 (67 %) 231 (67 %) 38 (63 %) 71 (69 %) 99 (67 %) χ 2 = 0.55 0.91 Living alone (n, %) 472 (72 %) 277 (80 %) 36 (60 %) 65 (63 %) 94 (64 %) χ 2 = 24.17 <0.01 Cognitive impairment (CPS ≥ 3) (n, %) 61 (9 %) 40 (12 %) 13 (22 %) 6 (6 %) 2 (1 %) χ 2 = 25.44 <0.01 Depressive symptoms (DRS ≥ 3) (n, %) 82 (13 %) 25 (7 %) 7 (12 %) 12 (12 %) 38 (26 %) χ 2 = 32.86 <0.01 Mean ADLH score (SD) 0.8 (1.4) 0.7 (1.3) 2.4 (1.9) 0.5 (0.9) 0.7 (1.4) F = 31.55 <0.01 Mean iADLH score (SD) 25.4 (12.8) 27.3 (12.6) 27.8 (16.3) 23.5 (11.1) 21.3 (11.8) F = 8.52 <0.01 Pain (Pain Scale > 0) (n, %) 392 (60 %) 226 (66 %) 19 (32 %) 69 (67 %) 78 (53 %) χ 2 = 29.75 <0.01 Multimorbidity (n, %) 376 (57 %) 208 (60 %) 23 (38 %) 63 (61 %) 82 (56 %) χ 2 = 10.71 0.01 Having an informal caregiver (n, %) χ 2 = 137.15 <0.01 No caregiver present 81 (12 %) 58 (17 %) 6 (10 %) 0 (0 %) 17 (12 %) One caregiver 235 (36 %) 157 (45 %) 37 (62 %) 3 (3 %) 38 (26 %) Two or more caregivers 340 (52 %) 131 (38 %) 17 (28 %) 100 (97 %) 92 (63 %) In 21 % of the cases, the RUD Lite was administered as an interview with the participant, another 18 % with the participant and caregiver together, and 9 % with the caregiver alone. In Finland, paper versions of the RUD Lite were completed by the participant (16 %), the participant and the caregiver together (26 %) or by caregiver themselves (7 %). In 18 cases (3 %), Finnish nurses from the care agency assisted the participant completing the questionnaire. Resource utilisation Table 3 provides an overview of the utilisation rates of formal and informal care services over a period of 3 months as assessed with the RUD Lite and the interRAI-HC. Resource utilisation as assessed with the RUD Lite was significantly higher for number of physician visits, and significantly lower for number of hours of home health and domestic care services received, duration of hospital admissions and number of meals as compared to interRAI-HC assessments. All other differences in resource utilisation estimates between the RUD Lite and interRAI-HC were not statistically significant.Table 3 Resource utilisation over a three month period assessed with the RUD Lite and InterRAI-HC RUD Lite (n = 656) InterRAI-HC (n = 656) Mean Difference (RUD Lite minus interRAI-HC) Spearman’s ρ (range countries) Service use category Use of service, n (%) Mean (SD) Use of service, n (%) Mean (SD) Mean (95 % CI) Home care  Home health and domestic care hours 544 (83 %) 62.4 (75.3) 641 (98 %) 68.5 (65.9) −6.1 ( −10.9; −1.4) 0.56* (0.38*- 0.81*) Physician visits  Physician visits (GP + outpatient clinic visits 385 (59 %) 1.7 (2.6) 275 (42 %) 1.2 (2.3) 0.5 (0.3; 0.6) 0.62* (0.03–0.75*)  General practitioner visits 296 (45 %) 1.0 (1.6) - - - -  Outpatient clinic visits 189 (29 %) 0.7 (1.8) - - - - Other health care services  Physical therapy sessions 137 (21 %) 2.6 (6.6) 89 (14 %) 2.6 (7.2) 0.1 (−0.3; 0.5) 0.68* (0.27*–0.82*)  Occupational therapy sessions 24 (4 %) 0.2 (1.1) 15 (2 %) 0.5 (3.8) −0.3 (−0.7;−0.1) 0.14* (−0.01–1.00*)  Psychological treatment 5 (1 %) 0.0 (0.2) 4 (1 %) 0.1 (1.1) −0.1 (−0.1;−0.0) 0.67* (0.00-0.86*) Hospital admissions  Hospital admission with overnight stay, times 93 (14 %) 0.2 (0.6) 99 (15 %) 0.3 (1.1) −0.1 (−0.2; 0.0) 0.57* (0.13–1.00*)  Hospital admission with overnight stay, nights 86 (13 %) 1.2 (4.9) 99 (15 %) 2.3 (7.5)a −1.1 (−1.7;−0.6) 0.54* (0.14–1.00*)  Nights general ward 84 (13 %) 1.2 (4.8) - - - -  Nights ICU 4 (1 %) 0 (0.2) - - - -  Emergency room visits without overnight stay 92 (14 %) 0.2 (1.1) 87 (13 %) 0.2 (0.7) 0.0 (0.0; 0.1) 0.35* (0.00–0.74*) Supportive care services  Meals on wheels 235 (36 %) 25.1 (39.2) 279 (43 %) 31.4 (39.5) −6.3 (−8.7;−4) 0.72* (0.59*–0.92*) Informal care  Informal caregiver time 413 (63 %) 212 (498.9) 483 (74 %) 211.2 (426.4) 0.8 (−28.1; 31.6) 0.61* (0.48*–0.80*) * p < 0.01 a Estimated using OECD data [17] Table 3 also shows that eight out of 10 predefined hypotheses regarding the correlation between RUD Lite and interRAI-HC resource utilisation measurement were confirmed (number of hours of home health and domestic care services received, number of physician visits, physical therapy sessions and psychological treatment sessions, the number and duration of hospital admissions, the number of meals, and the amount of informal caregiver time). For the number of occupational therapy sessions and emergency room visits, our hypotheses could not be confirmed (Spearman’s ρ < 0.5). Country-specific resource utilisation estimates and the correlation between the two types of assessments can be found in Additional file 1. In short, for Iceland, we found moderate correlation (0.3 < Spearman’s ρ < 0.5) for the number of emergency room visits and physician visits, and strong correlation for all other resource utilisation services (Spearman’s ρ > 0.5). The results from Germany showed strong correlation for the number of physician visits, the number of meals and the amount of informal caregiver time, and moderate to weak correlation for the other resource utilisation services (0.1 < Spearman’s ρ < 0.5). For Finland, strong correlation was found for two services, including physical therapy sessions, and number of meals. For the Netherlands, weak correlation (0.1 < Spearman’s ρ < 0.3) was found for the number of occupational therapy sessions and strong correlation was found for all other resource utilisation services. Costs of care Table 4 provides an overview of the estimated costs over a period of 3 months as assessed with the RUD Lite and the interRAI-HC. Estimated costs assessed with RUD Lite as compared to interRAI-HC assessments were significantly lower for home health and domestic care (mean difference €-233, 95 % CI −415; −54), hospital admissions (mean difference €-517, 95 % CI −786; −246), supportive care services (mean difference €-45, 95 % CI −61; −29), and total societal costs (mean difference €-804, 95 % CI −1340; −269). The differences in other cost categories between RUD Lite and interRAI-HC assessments were not significant.Table 4 Cost estimates (€) over a three month period assessed with the RUD Lite and interRAI-HC RUD Lite (n = 656) InterRAI-HC (n = 656) Mean Difference (RUD Lite minus interRAI-HC) Spearman’s ρ (range countries) Service use category Mean (SD) Mean (SD) Mean (95 % CI) Home health and domestic care 2369 (2860) 2603 (2505) −233 (−415; −54) 0.56* (0.37*–0.81*) Physician visits 83 (158) 93 (178) −10 (−21; 2) 0.57* (0.06–0.72*) Other health care services 108 (265) 118 (316) −10 (−29; 8) 0.66* (0.35*–0.79*) Hospital admissions 680 (2568) 1197 (3737) −517 (−786; −246) 0.53* (0.14–0.91*) Supportive care services 177 (277) 222 (279) −45 (−61; −29) 0.72* (0.59*–0.92*) Informal care 2877 (6770) 2866 (5787) 10 (−382; 428) 0.61* (0.48*–0.80*) Total societal costs 6295 (8221) 7099 (7428) −804 (−1340; -269) 0.60* (0.51*–0.79*) * p < 0.01 All seven predefined hypotheses on the correlation of the cost of care estimates between the RUD Lite and interRAI-HC were confirmed (Spearman’s ρ > 0.5). Country-specific cost estimates and correlation between the RUD Lite and interRAI-HC assessment can be found in Additional file 2. The results of Iceland showed strong correlation between the RUD Lite and interRAI-HC for all cost categories and total societal costs, except for costs of physician visits (Spearman’s ρ < 0.5). Strong correlation was also found for the estimated costs of supportive care services, informal care, and total societal costs in Germany, and for the estimated costs of supportive care services and total societal costs in Finland. For the Netherlands, strong correlation was found for all costs categories and total societal costs estimates between both instruments. The Bland-Altman plot shows that cost differences for the total societal costs between the two methods are becoming larger as the mean of the cost estimates based on the two methods is increasing (see Fig. 1). This becomes especially clear for participants for whom the mean of the two methods is €10000 or more. The 95 % limits of agreement are wide (−14271; 12663), showing considerable variation between the two methods of cost estimation.Fig. 1 Bland and Altman plot comparing differences in costs assessed with the RUD Lite and interRAI-HC Sensitivity analysis A total of 691 subjects were included in the analysis in which the correlation between cost of care estimates from a health care perspective was tested. The difference in total health care costs was €-685 between the RUD Lite and interRAI-HC (95 % CI -1007; −375). The correlation between the instruments for total health care costs was strong (Spearman’s ρ = 0.58). The use of country-specific averages of length of stay during hospital admission based on the OECD database minus one day resulted in a smaller difference in total societal costs between the RUD Lite and the interRAI cost estimates (mean difference €-345 instead of €-804), but this difference was still statistically significant (95 % CI −590; −106). After stratification for cognitive impairment, the difference in total societal costs was €-1288 between the RUD Lite and interRAI-HC resource utilisation assessment for people with cognitive impairment (95 % CI −3609; 1321), and €-755 for people without cognitive impairment (95 % CI −1256; −220). Strong correlation was found for total societal costs estimates in both people with cognitive impairment (Spearman’s ρ = 0.52), and people without cognitive impairment (Spearman’s ρ = 0.59). The difference in total societal cost was €-1231 between the RUD Lite and interRAI-HC when the RUD Lite was administered as an interview with exclusively the participant (95 % CI −1890; −628). Relatively smaller mean differences in total societal costs estimates between the RUD Lite and interRAI-HC were found when the participant and the caregiver were interviewed together (mean difference €349, 95 % CI −1419; 2183) or when exclusively the caregiver was interviewed (mean difference €-204, 95 % CI −1957; 1524). When exclusively the caregiver was interviewed, a slightly adapted version of the RUD Lite was used, in which the questions were targeted at the caregiver instead of at the client. The caregiver answered the questions regarding care utilisation on behalf of the client. When paper versions of the RUD Lite were used (Finland), the difference in total societal costs between the RUD Lite and interRAI-HC was €-2660 when the participant completed a paper version of the RUD Lite him/herself (95 % CI −4522; −1214); €-486 when the participant and the caregiver completed the RUD Lite together (95 % CI −2137; 1325); €-238 when the RUD Lite was completed by the caregiver alone (95 % CI −1684; 1286), and €-111 when the participant received help from a nurse when completing the questionnaire (95 % CI −809; 617). Moderate correlation between the RUD Lite and interRAI-HC for total societal cost estimates was found when the RUD Lite was completed on paper by the participant with or without help from a nurse (Spearman’s rho = 0.43), and strong correlation was found for all other administration modes (Spearman’s rho = 0.53 - 0.72). Discussion Main findings The objective of this study was to evaluate the convergent validity of the interRAI-HC instrument in comparison with the RUD Lite instrument for estimating resource utilisation and associated costs in community-dwelling care-dependent older adults from five European countries. In total, 15 of the 17 predefined hypotheses (88 %) were confirmed: strong correlation was found between resource utilisation assessments with RUD Lite and interRAI-HC for eight out of ten hypotheses (home health and domestic care, physician visits, physical therapy, psychological treatment, hospital admissions (number and duration), meals on wheels, and informal caregiver time), and all seven cost of resource utilisation hypotheses (home health and domestic care, physician visits, other health care services, hospital admissions, supportive care services, informal care and total societal care costs). The hypotheses for the number of occupational therapy sessions and emergency room visits could not be confirmed. For the purpose of the study, only information on utilisation of formal and informal care services that was included in both questionnaires was taken into account. These care services cover health care services that are most frequently used by older adults in the community [31]. However, the interRAI-HC also includes a wide range of irregularly provided care services and preventive examinations. Most of these services are provided for specific diseases (e.g., chemotherapy) or very infrequently (e.g., mammography), as shown by Brown et al. [12] These services and examinations are expected to contribute only marginally to the total societal costs in a community dwelling population of older adults, and were, therefore, not included in this study [12]. On the other hand, the RUD Lite assesses cost categories that are not included in the interRAI-HC. These include care related transportation, psychiatrist, social worker and hours of day care received. Future research is needed to assess the contribution of these items to the total societal cost estimates and, subsequently, the necessity to include these additional items in the interRAI-HC to make the instrument more suitable for cost of care assessments. The resource utilisation services included in this study are similar to other cost studies among older adults [32, 33]. Metzelthin et al. calculated the cost of care utilisation over a 24 month period for 346 community dwelling frail older adults in the Netherlands [33]. In that study, information on resource utilisation was collected from health care insurance registries, local hospitals, and directly from the respondents by means of telephone interviews and postal questionnaires. The cost estimates reported (over a 3 month period), were in line with the estimates found in our study. Only for home health and domestic care, hospital care, and informal care, approximately 150 to 400 % higher costs were found in the current study. Strengths and limitations One of the strengths of this study is that participants from four Western European countries were included in the main analysis, making the results generalisable to various care contexts. Although some country differences in the correlation between the RUD Lite and the interRAI were present (See Additional files 1 and 2), the study results show good convergent validity of the interRAI-HC for resource utilisation measurement and costs of care estimates across countries. Another strength is that the interRAI-HC assessments were in most care organisations part of routine care. This has kept the burden for participants low. Additionally, costs were assessed from a societal perspective which is generally recommended by national guidelines [34]. The RUD Lite was chosen as reference instrument because previous studies showed that it has good clinimetric properties when assessing costs of resource utilisation of formal and informal care services [13, 24]. However, the RUD Lite cannot be considered a gold standard for measuring resource utilisation of formal and informal care services because it relies on self-report. Also, since the interRAI used a recall period of 3 months for some service utilisation items, the recall period of the RUD Lite was extended from 30 days to 3 months. Although it is suggested in the literature that recall periods up to 6 months can be reliably used to measure resource utilisation [35], it is unclear to what extent the validity of the RUD Lite is affected by this adaptation. This can be considered a potential limitation of the study. Another limitation of the study is that we had to exclude approximately one sixth of the subjects from analyses due to missing values on the resource utilisation items in the interRAI-HC or RUD Lite. Also, cognitively impaired persons (CPS ≥ 3 [16]) without an informal caregiver who was willing to participate as a proxy, were not included in this study. This may affect the generalisability of the results. Significant differences were found in most of the demographic and clinical characteristics between the participants and the excluded subjects. Furthermore, the utilisation of some health care services, such as occupational therapy and psychological treatment was very low in some countries (1 % of the study population used this service on average). Therefore, the results found for these services should be interpreted with caution. A number of assumptions was made in this study. Although hospital admissions are known to be a major cost driver for total health care costs, the interRAI-HC does not record the number of nights spent in a hospital. Therefore, we used the average number of hospitalisation days according to the OECD to calculate the total number of days a participant was admitted to a hospital. The OECD database provides internationally comparable statistics on a wide range of topics. We included data from the year 2012 as this was the most recent year for which complete data for all countries that participated in the IBenC project was available. Secondly, the interRAI-HC does not distinguish between general practitioner visits and outpatient clinic visits. A pragmatic choice was made to value physician visits with the price of outpatient clinic visits, since we assumed that most visits were to an outpatient clinic. However, this might have led to an overestimation of the costs for physician visits in the interRAI-HC. Another limitation concerns variation in assessor, mode and timing of the administration of the RUD Lite and the interRAI-HC across countries: two countries administered the instruments by the same assessor during the same contact or after a short period of time (Netherlands, Belgium), while in another country the assessors differed (Iceland) and the period was longer (Germany) or self-report instead of interview took place (Finland). In situations where the instruments were administered on the same day by the same assessor, the correlation between both instruments may be overestimated as compared to situations in which the assessor differed or the assessments took place on different days. Subsequently, we explored the effect of mode of the administration of the RUD-Lite on the correlation between both instruments and found lower correlation when the RUD Lite was completed by the participants themselves on paper instead as an interview. The use of self-report in Finland may thus potentially explain the weak to moderate correlation found for most resource utilisation services in this country. Conclusions To the best of our knowledge, this is the first study to assess the convergent validity for societal cost of resource utilisation of an instrument that can be used in routine care, the interRAI-HC, as compared to a specifically developed resource utilisation instrument, the RUD Lite. The results show that the interRAI-HC has good convergent validity to estimate societal costs in community dwelling older adults. Next to the benefits of using the interRAI-HC as comprehensive geriatric assessment instrument, such as improved care planning, possibility to benchmark quality of care and efficiently allocate resources, this finding shows that the interRAI-HC can be used to estimate costs for use in economic evaluations thereby substantially improving the feasibility of performing economic evaluations among community dwelling older adults. Since the interRAI-HC is globally widely used in routine care in many organisations, the information is readily available and additional patient burden for the purpose of cost of care assessments can be avoided. However, to make the interRAI-HC more suitable for costs of care assessments, it is recommended to add the number of overnight hospital stays to the instrument, as well as to make a distinction between admission days on a general ward and an ICU and between visits to a general practitioner and a specialist. These adaptations are expected to result in more accurate cost estimates. Also, it is recommended to assess the influence of using country-specific valuations on the correlation between the cost of care estimates. Additional files Additional file 1: Country specific resource utilisation. Resource utilisation estimates over a three month period assessed with the RUD Lite and InterRAI-HC by country (DOCX 44 kb) Additional file 2: Country specific cost of care estimates. Comparison of cost of care estimates (€) over a three month period between care utilisation assessed with the RUD Lite and interRAI-HC by country. (DOCX 28 kb) Acknowledgements We thank the care organisations and the respondents for their participation in this study and the (research) nurses for conducting the interviews. Funding The IBenC study is funded by the 7th Framework Programme of the European Commission (grant number 305912). The European Commission was not involved in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Availability of data and material The datasets during and/or analysed during the current study available from the corresponding author on reasonable request. Authors’ contributions LL, HR, HH, and JB designed the study. LL, HR and JB conducted the analyses. LL drafted the manuscript. All authors revised and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate The study was performed in accordance with the Declaration of Helsinki and was approved by relevant legal authorised medical ethical committees in the countries that participated in the IBenC project (Belgium, Finland, Germany, Iceland, Italy, and The Netherlands). Prior to the start of the assessments, written informed consent was obtained from the participants. When a participant was known to be cognitively impaired, informed consent from a close relative, legal representative or legal guardian on behalf of the participant was obtained. Names and reference numbers: Belgium: Commissie Medische Ethiek van de universitaire ziekenhuizen KU Leuven, reference number: ML10265 Finland: Tutkimuseettinen työryhmä (TuET), reference number: THL/796/6.02.01/2014 Germany: Ethikkommission des Institut für Psychologie und Arbeitswissenschaft (IPA) der TU - Berlin, reference number: GH_01_20131022 Iceland: Vísindasiðanefnd, reference number: 13-176-S1 Italy: Comitato Etico, reference number: 2365/14 The Netherlands: Medical Ethics Review Committee of the VU University Medical Center (METc VUmc), reference number: 2013.333 ==== Refs References 1. Lanzieri G The greying of the baby boomers. A century-long view of ageing in European populations Stat Focus 2011 23 1 12 2. World Health Organisation: Ageing and life-course. Facts about ageing. http://www.who.int/ageing/about/facts/en/ (2014). Accessed 1 May 2015. 3. Colombo F, Llena-Nozal A, Mercier J, Tjadens F. Help Wanted? Providing and Paying for Long-Term Care. In: OECD Health Policy Studies, OECD Publishing. 2011. https://www.oecd.org/els/health-systems/47836116.pdf. Accessed 5 May 2015. 4. Genet N Boerma WG Kringos DS Bouman A Francke AL Fagerström C Home care in Europe: a systematic literature review BMC Health Serv Res 2011 11 207 10.1186/1472-6963-11-207 21878111 5. Drummond MF Sculpher MJ Torrance GW O’Brien BJ Stoddart GL Methods for the economic evaluation of health care programmes 2005 3 Oxford Oxford University Press 6. Wimo A Wetterholm AL Mastey V Winblad B Wimo A Karlsson B Jönsson B Winblad B Evaluation of the resource utilization and caregiver time in Anti-dementia drug trials—a quantitative battery The Health Economics of Dementia 1998 London Wiley 465 99 7. Morris JN Fries BE Steel K Ikegami N Bernabei R Carpenter GI Comprehensive clinical assessment in community setting: applicability of the MDS-HC J Am Geriatr Soc 1997 45 1017 24 10.1111/j.1532-5415.1997.tb02975.x 9256857 8. Landi F Tua E Onder G Carrara B Sgadari A Rinaldi C Minimum data set for home care: a valid instrument to assess frail older people living in the community Med Care 2000 38 1184 90 10.1097/00005650-200012000-00005 11186297 9. Hirdes JP Ljunggren G Morris JN Frijters DHM Finne Soveri H Gray L Reliability of the interRAI suite of assessment instruments: a 12-country study of an integrated health information system BMC Health Serv Res 2008 8 277 10.1186/1472-6963-8-277 19115991 10. Björkgren MA Fries BE Shugarman LR A RUG-III case-Mix system for home care Can J Aging 2000 19 106 25 10.1017/S0714980800013921 11. Poss JW Hirdes JP Fries BE McKillop I Chase M Validation of Resource Utilization Groups version III for Home Care (RUG-III/HC): evidence from a Canadian home care jurisdiction Med Care 2008 46 380 7 10.1097/MLR.0b013e31815c3b6c 18362817 12. Brown PM Wilkinson-Meyers L Parsons M Weidenbohm K McNeill R Brandt T Cost of prescribed and delivered health services resulting from a comprehensive geriatric assessment tool in New Zealand Health Soc Care Community 2009 17 514 21 10.1111/j.1365-2524.2009.00855.x 19694038 13. Wimo A Jonsson L Zbrozek A The resource utilization in dementia (RUD) instrument is valid for assessing informal care time in community-living patients with dementia J Nutr Heal Aging 2010 14 685 90 10.1007/s12603-010-0316-2 14. Wimo A Gustavsson A Jonsson L Winblad B Hsu MA Gannon B Application of resource utilization in dementia (RUD) instrument in a global setting Alzheimer’s Dement 2013 9 429 35 10.1016/j.jalz.2012.06.008 23142433 15. IBenC “Identifying best practices for care-dependent elderly by Benchmarking Costs and outcomes of community care”. http://www.ibenc.eu (2015). Accessed 28 May 2015. 16. Morris JN Fries BE Mehr DR Hawes C Phillips C Mor V MDS cognitive performance scale J Gerontol 1994 49 174 82 10.1093/geronj/49.4.M174 17. OECD Statistics Length of hospital stay Acute Care, days 2013 Paris OECD 18. Burrows AB Morris JN Simon SE Hirdes JP Phillips C Development of a minimum data set-based depression rating scale for use in nursing homes Age Ageing 2000 29 165 72 10.1093/ageing/29.2.165 10791452 19. Morris JN Fries BE Morris SA Scaling ADLs within the MDS J Gerontol A Biol Sci Med Sci 1999 54 546 53 10.1093/gerona/54.11.M546 20. InterRAI: Scales: Status and Outcome Measures. http://interrai.org/scales.html (2015). Accessed 19 May 2015. 21. Fries BE Simon SE Morris JN Flodstrom C Bookstein FL Pain in U.S. nursing homes: validating a pain scale for the minimum data set Gerontologist 2001 41 173 9 10.1093/geront/41.2.173 11327482 22. Van den Akker M Buntix F Metsemakers JFM Roos S Knottnerus JA Multimorbidity in general practice: prevalence, incidence, and determinants of co-occurring chronic and recurrent diseases J Clin Epidemiol 1998 51 367 75 10.1016/S0895-4356(97)00306-5 9619963 23. Wimo A Windblad B Resource utilisation in dementia: RUD Lite Brain Ageing 2003 3 48 59 24. Wimo A Nordberg G Validity and reliability of assessments of time. Comparisons of direct observations and estimates of time by the use of the resource utilization in dementia (RUD)-instrument Arch Gerontol Geriatr 2007 44 71 81 10.1016/j.archger.2006.03.001 16777246 25. Hakkaart-van Rooijen L, Tan S, Bouwmans C. Handleiding Voor Kostenonderzoek. Methoden En Standaard Kostprijzen Voor Economische Evaluaties in de Gezondheidszorg. Geactualiseerde Versie, 2010. In: Zorginstituut Nederland (The National Health Care Institute). 2010. 26. Statline. Statistics Netherlands, The Hague. 2010 http://statline.cbs.nl/Statweb/publication/?DM=SLNL&PA=71311ned&D1=0&D2=0&D3=142,155,168,181,194,219,232,245,258,l&HDR=G1,T&STB=G2&VW=T. Accessed 2 Apr 2015. 27. IBM Corp IBM SPSS Statistics for Windows Version 20.0 2011 Armonk IBM Corp 28. Efron B Tibshirani RJ An introduction to the bootstrap 1993 New York Chapman & Hall 29. Cohen J Statistical Power Analysis for the Behavioral Sciences 1998 2 Erblaum Hillsdale 30. Bland JM Altman DG Statistical methods for assessing agreement between Two methods of clinical measurement Lancet 1986 1 307 10 10.1016/S0140-6736(86)90837-8 2868172 31. Chen Y-M Berkowitz B Older adults’ home- and community-based care service use and residential transitions: a longitudinal study BMC Geriatr 2012 12 44 10.1186/1471-2318-12-44 22877416 32. Brettschneider C Luck T Fleischer S Roling G Beutner K Luppa M Cost-utility analysis of a preventive home visit program for older adults in Germany BMC Health Serv Res 2015 15 1 11 10.1186/s12913-015-0817-0 25603697 33. Metzelthin SF van Rossum E Hendriks MRC De Witte LP Hobma SO Sipers W Reducing disability in community-dwelling frail older people: cost-effectiveness study alongside a cluster randomised controlled trial Age Ageing 2015 44 390 6 10.1093/ageing/afu200 25566783 34. Hjelmgren J Berggren F Andersson F Health economic guidelines - Similarities, differences and some implications Value Heal 2001 4 225 50 10.1046/j.1524-4733.2001.43040.x 35. van den Brink M van den Hout WB Stiggelbout AM Putter H van de Velde CJH Kievit J Self-reports of health-care utilization: diary or questionnaire? Int J Technol Assess Health Care 2005 21 298 304 10.1017/S0266462305050397 16110708

PMC005xxxxxx/PMC5000457.txt

==== Front BMC Public HealthBMC Public HealthBMC Public Health1471-2458BioMed Central London 347810.1186/s12889-016-3478-yResearch ArticleHealth or harm? A cohort study of the importance of job quality in extended workforce participation by older adults Welsh Jennifer Jennifer.Welsh@anu.edu.au 1Strazdins Lyndall Lyndall.Strazdins@anu.edu.au 1Charlesworth Sara Sara.Charesworth@rmit.edu.au 2Kulik Carol T. Carol.Kulik@unisa.edu.au 3Butterworth Peter Peter.Butterworth@unimelb.edu.au 41 National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Building 62, Crn Mills and Eggleston Road, Canberra, ACT 2601 Australia 2 School of Management, College of Business, RMIT University, 448 Swanston St, Melbourne, VIC 3000 Australia 3 School of Management, University of South Australia, Elton Mayo Building, Corner of North Terrace and George Street, Adelaide, SA 5001 Australia 4 Centre for Mental Health, Melbourne School of Population and Global Health; and Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Level 4, 207 Bouverie St, Parkville, VIC 3010 Australia 25 8 2016 25 8 2016 2016 16 1 88511 1 2016 15 6 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background As people are living longer, they are being encouraged to work longer. While it is assumed that extended employment will be good for health, the evidence has been mixed. This study considers whether employment and job quality exert an influence on four indicators of health status in older workers. Methods Data for this study came from 836 older workers (440 men and 396 women) aged 50–59 years at baseline who participated in the Household, Income and Labour Dynamics in Australia (HILDA) Survey. Using linear regression, we examine within-person change in self-rated, physical and mental health and one health behaviour (physical activity) at two time points over a nine year follow-up period. Results There were minimal differences in the way health changed for older adults who continued working compared to those who retired voluntarily. However, when we decomposed employment in terms of job quality, health outcomes diverged. Compared to voluntary retirees, older workers who had worked in good quality jobs reported marginally better self-rated health (0.14,−0.02–0.29); but did not differ in their physical (2.31,−1.09–5.72) or mental health (0.51,−1.84–2.87). In contrast, older workers who held poor quality jobs for most of the follow-up period declined in their self-rated (−1.13,−0.28 − –0.02), physical (−4.90, 8.52– − 1.29) and mental health (−4.67, 7.69– − 1.66) relative to voluntary retirees. Older workers who held poor quality jobs for just some of the follow-up period did not differ from voluntary retirees in terms of their health. However there was evidence of a linear relationship between length of exposure to poor quality jobs and decline in health outcomes. Conclusion Extended working lives mean that people will be ‘exposed’ to work for longer, and this exposure will occur at a life stage characterised by declining health for many. Our findings show that ensuring older workers have access to secure jobs which allow for control over work time, skill use and fair rewards will be essential if policy goals to boost participation and productivity, as well as reduce the health and care costs of the elderly, are to be met. Electronic supplementary material The online version of this article (doi:10.1186/s12889-016-3478-y) contains supplementary material, which is available to authorized users. Keywords Job qualityEmploymentRetirementPopulation ageingMental healthPhysical activityFunctioningSelf-rated healthhttp://dx.doi.org/10.13039/501100000923Australian Research CouncilLP 130100227FT110100686FT120100346FT130101444Welsh Jennifer Strazdins Lyndall Charlesworth Sara Butterworth Peter issue-copyright-statement© The Author(s) 2016 ==== Body Background All OECD countries face increasing health burdens related to non-communicable diseases. In 2012, 83 % of the burden of disease in high income countries was attributable to chronic health conditions such as cardiovascular disease, cancers, depression and diabetes, a number which has increased by 3 % since 2000 [1]. These countries are also dealing with the challenges posed by population ageing. The old age dependency ratio (the number of individuals aged 65 years or older relative to those within prime working age, 20–64 years) is projected to increase across the OECD from 24 % in 2005 to 52 % in 2050, meaning that there will be less than two workers for every person aged 65 years or older [2]. While the scale of the problem varies between countries, these changes are projected to have profound social and economic ramifications across the OECD. The most pressing of these ramifications will be a shrinking labour force (i.e. smaller pool of tax payers) coupled with increased demand for public spending on age-related pensions, health and aged care. Action is needed across multiple fronts and boosting participation rates of those aged 55–64 years is widely seen as an important part of the solution [3]. This paper investigates how four key health indicators are affected by policies designed to boost the number of older workers. Currently, about two-thirds of people aged between 50 to 64 years participate in paid work in developed economies. Although cross-national variation is large [3], mobilising this untapped pool of older workers is expected to produce multiple and complementary benefits. A greater number of older adults in employment can increase both labour supply and consumption, benefiting the economy and increasing the tax base [3]. Greater participation by older workers decreases reliance on state-funded pensions and may improve financial preparedness for retirement [4]. On a societal level, extended participation recognises the value of older adults, the skills they possess and their capacity to contribute in meaningful and productive ways [5]. Further, it is often assumed that extended employment delivers health benefits [6] although there is currently no analysis of the health effects of extended participation for older adults. While health is integrally connected to whether older workers stay in the labour market or leave early, the extent to which working into later life will deliver net benefits to health is not clear. Not all jobs improve health [7, 8]. It is therefore possible that health benefits or costs of extended employment depend on a range of factors, especially job quality and working conditions. Extended working lives mean that people will be ‘exposed’ to work for longer, and this exposure will occur at a life stage that is often characterised by declining health. So far the evidence for the health benefits or costs of staying employed for older workers has been mixed and inconsistent [9, 10]. Much of the research is confounded by the ‘healthy worker effect’, whereby older workers in good health remain in the labour market and those with poor health leave early [11]. Once prior health is considered the evidence becomes more consistent. Studies have shown that compared to sustained employment, retirement is associated with short term improvements in self-rated health [12] and decreased morbidity from chronic health conditions [13], but has no effects on mortality [14] or physical or mental health [15]. Continued employment appears to support incidental physical activity in older workers but compromises leisure-time physical activity [16]. Thus, considering whether retirement decisions are driven by health (a form of involuntary retirement) or not (voluntary retirement) is vital [9]. A second weakness in the evidence on the health benefits or costs of extended employment relates to job quality. Previous research has underscored how the work-health relationship depends on the characteristics of people’s jobs and the demands or supports in the work environment. The concept of job quality has emerged as way of understanding the co-occurrence of job characteristics that support or undermine the well-being of workers, including their health [17, 18]. There are varying definitions of job quality and it is useful to distinguish between employment quality and job quality. Employment quality is focused more on aspects relating to the employment contract, such as wages and working hours, and job quality relating more to the way work is organized, such as workloads and job control [19]. In our study we define job quality in terms of the psychosocial characteristics known to be important for health and wellbeing: the use of worker’s skills, job control, job security, and the balance between effort and reward. Numerous studies attest to the way jobs can have a direct impact on workers’ health, although few focus on older workers. For example, work demands and job control have been identified as key social determinants of cardiovascular disease and stress [20] and adverse working conditions and job hazards have been associated with poorer mental health [21]. There is also evidence that psychosocial stress related to the characteristics of employment can erode health more generally [8] and compromise health behaviours [22]. Further, recent studies indicate that poor quality jobs can be more detrimental to mental health than unemployment [7, 23]. In contrast, good quality jobs, marked by characteristics such as job control, employee flexibility and low levels of strain, support better health outcomes [8, 24] and have been associated with more health-promoting behaviours such as physical activity [25]. Mature age workers experience higher rates of chronic disease than their younger counterparts (see for example [26]), and therefore may be more vulnerable to work-related health risks. Where job quality is integrated into research on older workers, it is largely as a predictor of retirement, not of the health of those who stay employed. European studies have revealed that job characteristics and psychosocial strain are related to retirement and retirement intentions e.g. [27, 28]. There may be different triggers to early retirement for different groups of workers. For example job autonomy and psychological stress are more likely to predict exit among professional workers whereas physical demands and psychological stress are more important for blue-collar workers [29]. However, there currently is no evidence on the associations between job quality and health changes in older workers. Our study integrates these lines of evidence to propose that job quality will determine if continuing to work while older delivers benefits or costs to health. Method Data and sample Data for this study came from the Household, Income and Labour Dynamics of Australia (HILDA) Survey. The HILDA Survey is a nationally representative, household-based panel survey of Australian adults aged 15 years and older. Data is collected annually, primarily through interviews; however a small amount of information (relating to more sensitive topics, including health) is collected using a mailed back Self-Completion Questionnaire (SCQ), which is returned by approximately 90 % of the responding sample. In wave one, 13,969 respondents from 11,693 households were interviewed, representing a 61 % household response rate and 92.3 % individual response rate [30]. Response rates for the subsequent waves are approximately 90 %, which is comparable to other similar household based panel surveys [31]. Comparisons with census data reveal that the sample is broadly representative of the adult Australian population [32]. This study used nine waves of data. Our baseline was wave 2 as a number of important items changed between waves 1 and 2, and wave 11 was the end point (where we made use of a retirement module). There were 13,041 individuals from 7,245 households who responded in wave 2. Respondents were included in this study if they satisfied the following criteria: aged 50–59 in 2002 (the year of wave 2 data collection); employed in wave 2; and, were present and returned their SCQ in both waves 2 and 11 of the survey. The participation flow diagram is presented in Fig. 1.Fig. 1 Participation flow and study numbers Measures Respondents were considered employed if they worked in a job, business or farm in the past seven days, or if they usually met those criteria but did not work in the past week because of holidays, sickness, or other reason. Respondents were considered retired if they did not participate in paid work in the previous seven days, and cited “retirement/ voluntarily inactive” as the main reason for doing so. All retired respondents were also asked in wave 11 if their decision to retire was “something that you wanted to do or something you felt you were forced or pressured to do”, which allowed us to classify people into two retirement groups. If they were “pressured/forced to” or “part wanted, part pressured/forced” they were considered involuntary retirees, whereas those who reported that they “wanted to” were termed voluntary retirees. People who were employed at baseline and in wave 11 were categorised as continuing workers. We measured three health outcomes and one health behaviour. Physical functioning and poor mental health were measured with two subscales of the SF-36, which has been validated in the HILDA Survey [33]. The physical functioning subscale measures limitations in everyday activities over the previous four week period. Respondents are asked to rate (on a scale from 1 “yes, limited a lot” to 3 “no, not limited at all”) if they are limited by their health in a list of 10 activities, ranging from ‘vigorous activities’ (e.g. running) to simple everyday activities such as ‘bathing and dressing yourself’. The mental health subscale measures how often in the past four weeks respondents experienced positive (e.g. feeling ‘happy’) and negative (e.g. being ‘nervous’) emotions, symptomatic of common mental disorders [34]. Responses are recorded on a six-point scale from “all of the time” to “none of the time” to reflect mental distress and symptoms associated with common mental disorders (For information on the psychometric properties of these scales in the HILDA survey, see [33]). Self-rated health was measured with one-item which asked respondents to rate their health ‘in general’ on a five point scale from “poor” to “excellent”. This measure has been shown to be a good indicator of health and mortality [35]. Physical activity was measured with a single item: ‘in general, how often do you participate in moderate or physical activity for at least 30 min’. Participants responded on a six-point scale which ranged from “not at all” to “everyday”. For all four health measures, we calculated a change in health score between 2 time points over the nine year follow-up period by subtracting wave 11 scores from the baseline (wave 2) score. Negative scores represented deterioration in health, positive scores represented improvements to health and a score of 0 represented no change. Job quality was measured with a validated measure of psychosocial job quality developed from the HILDA Survey [36]. This measures four components of job quality: skill use (two-items), job control (three-items), job security (three-items) and effort-reward fairness (one-item) (full item list is in Table 1). Following approaches used by others [8, 37], we averaged the items for each component and then dichotomised them at the point closest to the bottom quartile. A composite measure was created by summing the number of times respondents were in the bottom quartile for each component; scores were 0 (never in the bottom quartile), 1 (lowest quartile on one component) or 2 (lowest quartile on two, three or four components).Table 1 HILDA Job Quality Components and Items Component Item Skill use My job requires learning new skills I use my skills in my current job Job control I have the freedom to decide how I do my work I have a lot of say about what happens at my job I have the freedom to decide when I do my job Job security I have a secure future in my job The company I work for will be in business in the next 5 years I worry about the future of my job (reverse coded) Effort-reward fairness I get paid fairly for the things I do Notes: Responses for each item range from 0 “strongly disagree to 6 “strongly agree” We measured cumulative job quality by calculating the number of years respondents reported two or more poor conditions (a score of 2 in the measure described above) over the follow-up period (waves 3 to 11). This was calculated using a ratio measure because almost 50 % of respondents had missing data on at least one-item across the follow-up (see missing data below). The measure was created by calculating the number of years the respondent reported a poor quality job divided by the number of waves for which the respondent had a score. Scores ranged from 0 % (never reported a poor quality job) to 100 % (always reported a poor quality job) and were then categorised into three groups: never (0 %), sometimes (1–49 %) and mostly (50–100 %) worked in a poor quality job. The validity of this measure was checked against a count measure of poor job quality summing the number of waves in which respondents reported having two or more poor conditions (and was not calculated for those with missing data). Scores on this measure ranged from never, sometimes (poor job for 1–4 years) and mostly (poor job for 5 or more years). Control variables We also measured sociodemographic and health characteristics at baseline to include in our models as covariates. Age was measured continuously in years; participant gender and whether or not the respondent reported a health condition were coded as dichotomous categories. Additional control variables Sensitivity analyses (described below) tested whether controlling for a larger number of baseline variables altered our results. As set out in Table 2, the additional covariates included: household post tax income, measured in quintiles; education; marital status; employment status, occupational grouping; and contract status. We also controlled for adult care (respondents who reported anything greater than 0 h per week caring for an adult due to illness, disability or old age), grandchild care (anything greater than 0 h per week caring for other people’s children on a regular and unpaid basis) and two important health behaviours: smoking status and alcohol consumption (abstainers: never or no longer drink; light drinkers: drinks alcohol ‘rarely’ to ‘1–2 times per week’; and drinkers: drinks ‘3 or times per week’ to every day).Table 2 Baseline characteristics of the sample by retirement groups Continued working Voluntarily Retired Involuntarily Retired Total N = 556 (66.5 %) N =192 (30.0 %) N = 88 (10.5 %) N = 836 (100 %) N Row % N Row % N Row % N Col % Age (mean) 53.2 55.3 55.1 Gender  Men 310 70.5 84 19.1 46 10.5 440 56.3  Women 246 62.1 108 27.3 42 10.6 396 43.7 Health condition  No 477 66.7 169 23.6 69 9.7 715 85.7  Yes 79 65.3 23 19.0 19 15.7 121 14.3 Household income (mean AUD/quintile)  Poorest: $15,096 96 60.0 37 23.1 27 16.9 160 17.2  2: $31,015 107 64.9 40 24.2 18 10.9 165 19.4  3: $46,203 122 73.1 33 19.8 12 7.2 167 21.6  4: $64,084 120 70.2 38 22.2 13 7.6 171 21.6  Richest: $111,051 111 64.2 44 25.4 18 10.4 173 20.2 Education level  High school or below 232 62.5 90 24.3 49 13.2 371 41.9  Certificate or diploma 174 70.2 50 20.2 24 9.7 248 30.9  Bachelor or higher 150 69.1 52 24.0 15 6.9 217 27.2 Marital Status  Married/de facto 434 65.9 159 24.1 66 10.0 659 78.0  Single 122 68.9 33 18.6 22 12.4 177 22.0 Employment status  Full-time (≥35 h) 419 69.7 124 20.6 58 9.7 601 75.5  Part-time (<35 h) 137 58.3 68 28.9 30 12.8 235 24.5 Occupation  White collar 253 66.1 95 24.8 35 9.1 383 45.6  Blue collar 134 68.7 36 18.5 25 12.8 195 24.0  Pink collar 169 65.5 61 23.6 28 10.9 258 30.5 Contract status  Ongoing/ fixed term 331 65.5 121 24.0 53 10.5 505 86.4  Casual 52 56.5 23 25.0 17 18.5 92 13.6 Adult care giving  No 459 68.1 152 22.6 63 9.4 674 88.2  Yes 62 56.4 29 26.4 19 17.3 110 11.8 Grand child care  No 464 67.1 157 22.7 71 10.3 692 89.2  Yes 56 61.5 24 26.4 11 12.1 91 10.9 Smoking status  Never a smoker 296 67.9 102 23.4 38 8.7 436 53.8  Past smoker 180 65.7 61 22.3 33 12.0 274 32.4  Smoker 76 64.4 25 21.2 17 14.4 118 13.9 Alcohol consumption  Abstainer 60 65.2 20 21.7 12 13.0 92 10.9  Light 277 69.4 77 19.3 45 11.3 399 49.6  Drinkers 218 63.4 95 27.6 31 9.0 344 39.5 Note: Percentages may not sum to 100 due to rounding Statistical approach The first set of analyses considered health changes between the two time points (wave 2 and wave 11) among older adults comparing those who remained employed and those who retired voluntarily and involuntarily. The second set decomposed the group of continuing workers to consider the extent their job quality determined health costs or benefits of sustained employment. Linear regression models were used to test whether group membership predicted change in health scores. Each health outcome was represented as a change score (the difference between the wave 11 and wave 2 scores). For each health outcome, a series of models were used to: (i) evaluate the significance of the differences observed in health between respondents classified as voluntary retirees and the other groups of interest; and (ii) estimate the change observed in health within each group. Both sets of analyses were adjusted for potential confounders. For each outcome measure, we report crude change scores from simple models including only employment status, and adjusted change scores, derived from models which included the coefficients from the full multivariate model (estimates were derived using the ‘margins’ command within Stata). To aid comparison across the different outcome measures, the final adjusted change scores were expressed as a percentage of the potential range of each scale (dividing the estimated change score for each group by the original scale range). Retirement was added into the models using two categories, with voluntary retirees as the reference group. Separate analyses were computed for each health outcome, and following the method presented by others [38], relative and overall change scores were adjusted for age, gender, presence of a health condition and baseline health score. The equation used to generate these models is given below: Yj=β0+β1X1+β2X2+βCiXCi+∈ where Y is change for each of the health measures j (physical functioning, mental health, self-rated health or physical activity) β0 is the intercept X1 and X2 are the key (dummy coded) covariates representing involuntary retirement and continuing employment β1 and β2 are the corresponding coefficients, XCi represents the additional covariates included in the model (e.g., age, gender, health condition), with βCi the corresponding coefficients. These models were repeated and extended by the further decomposition of the continuing employment category X2: Yj=β0+β1X1+β3X3+β4X4+β5X5+βCiXCi+∈ to differentiate those respondents who never had a poor quality job (X3), who in some waves had a poor quality job (X4), and those who had a poor quality job in most waves (X5). The strength of this approach is that it estimates within-person changes between the two time points and allows for meaningful health comparisons between retirement and employment. Sensitivity analyses tested whether further adjustment for additional baseline sociodemographic and health behaviours characteristics (see additional control variables above) altered the relationship substantively. We then examined the social distribution of poor quality jobs to identify which groups of older workers were most at risk. Cramér’s V was calculated to test the overall associations between job quality and sociodemographic variables. Missing data for those who met the study criteria were low (less than 5 %), with the exception of job quality. While missing data on the individual job quality items was low (approximately 10 %), almost 50 % of continuing workers had missing data on at least one job quality item at some point in the study, and had a missing score for our composite job quality measure as a result. Approximately 90 % of missing data on this job quality measure was ‘valid’, that is, respondents were not in the labour force at that point in the study; the remaining sources of missing were due to non-participation in a particular wave (generally less than 1 % per wave), failing to return the SCQ (1–2 % per wave) or item refusal (<1 % per wave). To overcome this, a ratio measure of job quality was used in our main analyses (see measures above). However, a series of sensitivity analyses tested whether excluding those with missing data altered the relationship. All other missing data was excluded using listwise deletion. Statement on ethics The HILDA Survey is administered by the Melbourne Institute and was approved by the Melbourne University Ethics committee. Respondents provided consent to take part in the study and parental consent was obtained for respondents aged less than 18 years. Our secondary analysis was approved by the Human Research Ethics Committee at the University of South Australia (project ID: 0000032602) and the Australian National University Human Ethics Committee (project ID: 2014/117). Results There were 923 respondents who met the study inclusion criteria. However, 78 respondents were excluded because they reported something other than retirement as the main reason for not being employed (such as home duties, own or others’ illness/ disability or doing unpaid work) and nine respondents were excluded because they did not provide a reason for their retirement. This resulted in a final sample of 836 respondents, of whom 556 (66.5 %) were classified as continuing workers, 192 (22.9 %) as voluntary retirees and 88 (10.5 %) as involuntary retirees. Of the continuing workers, 172 (31.2 %) never reported a poor quality job, 203 (36.8 %) reported a poor quality job in some of the follow-up period and 176 (31.9 %) mostly reported a poor job quality in that period. Five (<1 %) continuing workers never reported job quality information and were dropped from the second set of analyses. The overall sample had a mean age of 53.9 year at baseline. However, continuing workers were on average two years younger than those who retired during the follow-up period. Table 2 describes the sample characteristics. Health changes over nine years: Comparing employment and retirement Table 3 presents the results from the first analysis testing the association of (voluntary and involuntary) retirement and employment, with health and physical activity. Between the two time points in the follow-up period, self-rated health and physical functioning declined, mental health improved and there were no changes evident in reported physical activity. As expected, involuntary retirees reported the poorest health and the lowest levels of physical activity at baseline, and showed the greatest deterioration in self-rated, mental and physical health over the follow-up period. However, their rates of physical activity increased after retirement. Continuing workers and voluntary retirees reported similar levels of health at baseline and in crude change between the two time points; however unlike both groups of retirees, continuing workers reported a decrease in their physical activity over time.Table 3 Mean health at baseline, crude mean change and adjusted difference in change in health Group Membership Baseline mean Crude change scores Model coefficient (adjusted)ab Adjusted change scores (%)ac (95 % CI) (95 % CI) (95 % CI) (95 % CI) Self-Rated health (scale 1–5) N = 813  Involuntarily retired 3.10 (2.92–3.28) −0.38 (−0.56– − 0.20) −0.37 (−0.57– − 0.17) *** −10.80 (−14.20– − 7.40)***  Voluntarily retired 3.49 (3.38–3.60) −0.17 (−0.29– − 0.05) 0.00 (ref) −3.40 (−5.40– − 1.20)**  Continued working 3.60 (3.53–3.67) −0.21 (−0.27– − 0.14) −0.01 (−0.14–0.11) −3.60 (−4.80– − 2.40)*** Physical Functioning (scale 0–100) N = 808  Involuntarily retired 75.26 (70.16–80.36) −7.06 (−11.81– − 2.32) −9.24 (13.97– − 4.52)*** −11.93 (−16.06– − 7.80)***  Voluntarily retired 85.89 (83.38–88.40) −3.48 (−6.16– − 0.81) 0.00 (ref) −2.69 (−5.00– − 0.37)*  Continued working 87.27 (85.92–88.62) −3.75 (−5.31– − 2.19) −0.58 (−3.39–2.24) −3.26 (−4.73– − 1.80)*** Mental Health (scale 0–100) N = 834  Involuntarily retired 76.47 (72.97–79.97) −0.38 (−3.43–2.68) −4.92 (−8.22– − 1.62)** −1.60 (−4.52–1.32)  Voluntarily retired 78.65 (76.58–80.71) 3.57 (1.58–5.55) 0.00 (ref) 3.33 (1.59–5.06)***  Continued working 78.99 (77.77–80.22) 1.38 (0.15–2.61) −1.67 (−3.79–0.46) 1.66 (0.57–2.75)** Physical Activity (scale 0–6) N = 833  Involuntarily retired 3.22 (2.86–3.57) 0.49 (0.10–0.88) 0.12 (−0.25–0.49) 4.17 (−1.17–9.67)  Voluntarily retired 3.79 (3.58–4.00) 0.08 (−0.13–0.30) 0.00 (ref) 2.33 (−0.83–5.50)  Continued working 3.76 (3.63–3.88) −0.10 (−0.23–0.03) −0.22 (−0.45–0.01)^ −1.50 (−3.33–0.50) Notes: ^p < 0.1, *p < 0.05,**p < 0.01, ***p < 0.001. aAdjustments made for the following baseline characteristics: age, sex, health condition and health score. bSignificance refers to the difference between the group and the reference category (voluntary retirees). cSignificance refers to whether there was a change in the group’s health or physical activity. On all scales higher scores represent better health/ more physical activity Linear regression models were used to predict difference between the three groups in their change in health and physical activity between two time points. Figure 2 presents the adjusted change scores for the three groups. The results for the three health outcomes were consistent for voluntary retirees and continuing workers: these two groups of respondents reported similar, small deteriorations in their self-rated and physical health, and small improvements in their mental health. The models showed no evidence of significant difference for self-rated health (p = 0.825), physical functioning (p = 0.687) or mental health (p = 0.123). In comparison, involuntary retirees’ reported significantly greater deterioration in their self-rated health (p < 0.001), physical functioning (p < 0.001) and mental health (p = 0.003) relative to voluntary retirees. Whereas voluntary retirees reported a 3.40 % (−5.40– − 1.20) decrease in their self-rated health and a 2.69 % (−5.00– − 0.37) decrease in their physical functioning, involuntary retirees reported a 9.00 % (−0.71– − 0.37) and an 11.93 % (−16.06– − 7.80) decrease respectively. Strikingly, involuntary retirees reported a (nonsignificant) 1.60 % (−4.52–1.32) decrease in their mental health score over time whereas voluntary retirees reported a 3.33 % (1.59–5.06) improvement in mental health.Fig. 2 Baseline and adjusted follow up health and physical activity scores for each of the retirement and employment groups. Notes: Baseline scores are unadjusted; follow-up scores are adjusted for age, sex, health condition and health score. Adjusted estimates are calculated using the equations presented in the methods section Changes in physical activity showed a different pattern to the other outcomes. After adjustment, there was no significant difference between voluntary and involuntary retirees in frequency of physical activity from baseline to the end of the follow-up (p = 0.533). There was a trend among continuing workers (compared to voluntary retirees) for reduced levels of physical activity over time (p = 0.056). In comparison to voluntary retirees who reported a small but non-significant increase of 2.33 % in physical activity from baseline to follow-up, continuing workers reported a small but non-significant decrease of 1.50 %. Health changes, employment and job quality A second set of analyses decomposed the continuing workers into three separate categories based upon job quality, to investigate how this influenced the association between employment and change in health between the two time periods. The first column of Table 4 shows how baseline health varied as a function of job quality. Those continuing workers who had mostly worked in poor quality jobs showed poorer self-rated and mental health, and lower levels of physical functioning at baseline compared with those who had never or only sometimes worked in poor quality jobs.Table 4 Crude mean change and adjusted mean difference in change for all retirement groups Group Membership Baseline mean Crude change scores Model coefficient (adjusted)ab Adjusted change scores (%)ac (95 % CI) (95 % CI) (95 % CI) (95 % CI) Self-Rated Health (scale 1–5) N = 808  Involuntary retirement 3.10 (2.92–3.28) −0.38 (−0.56– − 0.20) −0.38 (−0.58– − 0.18)*** −11.00 (−14.20– − 7.60)***  Voluntary retirement 3.49 (3.38–3.60) −0.17 (−0.29– − 0.05) 0.00 (ref) −3.40 (−5.60– − 1.20)**  Never poor job 3.73 (3.61–3.85) −0.12 (−0.23– − 0.01) 0.14 (−0.02–0.29)^ −0.60 (−2.80–1.40)  Poor job some waves 3.66 (3.54–3.77) −0.25 (−0.36– − 0.14) −0.03 (−0.18–0.12) −4.00 (−6.00– − 2.00)***  Poor jobs most waves 3.41 (3.27–3.54) −0.23 (−0.34– − 0.12) −0.13 (−0.28–0.02)^ −6.00 (−8.00– − 3.80)*** Physical Functioning (scale 0–100) N = 803  Involuntary retirement 75.26 (70.16–80.36) −7.06 (−11.81– − 2.32) −9.25 (−13.97–4.53)*** −12.02 (16.15– − 7.89)***  Voluntary retirement 85.89 (83.38–88.40) −3.48 (−6.16– − 0.81) 0.00 (ref) −2.77 (−5.08– − 0.46)**  Never poor job 88.38 (85.96–90.79) −1.64 (−4.56–1.28) 2.31 (−1.09–5.72) −0.45 (−2.91–2.00)  Poor job some waves 87.06 (84.76–89.37) −1.98 (−4.24–0.29) 1.39 (−1.77–4.55) −1.38 (−3.38–0.63)  Poor jobs most waves 86.42 (84.05–88.79) −7.48 (−10.35– − 4.62) −4.90 (−8.52– − 1.29)*** −7.67 (−10.43– − 4.92)*** Mental Health (scale 0–100) N = 829  Involuntary retirement 76.47 (72.97–79.97) −0.38 (−3.43–2.68) −4.97 (−8.28– − 1.66)*** −1.65 (−4.58–1.28)  Voluntary retirement 78.65 (76.58–80.71) 3.57 (1.58–5.55) 0.00 (ref) 3.32 (1.58–5.06)***  Never poor job 81.91 (80.03–83.78) 2.10 (0.29–3.91) 0.51 (−1.84–2.87) 3.83 (2.28–5.38)***  Poor job some waves 80.54 (78.69–82.39) 0.99 (−0.74–2.27) −1.17 (−3.54–1.19) 2.15 (0.61–3.69)***  Poor jobs most waves 74.65 (72.16–77.15) 0.78 (−2.00–3.55) −4.67 (−7.69– − 1.66)*** −1.35 (−3.66–0.96) Physical Activity (scale 0–6) N = 828  Involuntary retirement 3.22 (2.86–3.57) 0.49 (0.10–0.88) 0.12 (−0.25–0.49) 4.17 (−1.17–9.67)  Voluntary retirement 3.79 (3.58–4.00) 0.08 (−0.13–0.30) 0.00 (ref) 2.17 (−1.00–0.53)  Never poor job 3.89 (3.67–4.11) −0.08 (−0.29–0.14) −0.13 (−0.40–0.15) 0.17 (−3.00–3.17)  Poor job some waves 3.61 (3.40–3.82) −0.01 (−0.23–0.20) −0.20 (−0.48–0.07) −1.17 (−4.33–2.00)  Poor jobs most waves 3.82 (3.59–4.06) −0.24 (0.48–0.01) −0.32 (−0.61– − 0.03)* −3.17 (−6.83–0.50) Notes: ^p < 0.1, *p < 0.05,**p < 0.01, ***p < 0.001. aAdjustments made for baseline characteristics: age, sex, health condition and health score. bSignificance refers to the difference between the group and the reference category (voluntary retirees). cSignificance refers to whether there was a change in the group’s health or physical activity. On all scales higher scores represent better health/ more physical activity There were no statistically significant differences for changes in self-rated health between voluntary retirees and any of the job quality groups. Relative to voluntary retirees, workers who had never worked in a poor quality job reported marginally less deterioration in their self-rated health (p = 0.084) and workers who mostly worked in a poor quality job reported marginally more deterioration (p = 0.096). Compared to voluntary retirees whose self-rated health decreased by 3.40 % (−5.60– − 1.20), workers who had never worked in a poor quality job reported a decrease of just 0.60 % (−2.80–1.40) and those who mostly worked in poor quality jobs reported a decrease of 6.00 % (−8.00– − 3.80). There was no difference evident between voluntary retirees and workers who had only sometimes worked in poor quality jobs (p = 0.691). The quality of employment was related to change in mental health, physical functioning and physical activity among continuing workers, generating distinctive changes in health compared with voluntary retirees. Older adults who mostly worked in a poor quality job reported greater deterioration over time in their physical functioning (p = 0.008), mental health (p = 0.002) and physical activity (p = 0.029) compared to voluntary retirees. Voluntary retirees reported a deterioration of 2.77 % (−5.08– − 0.46) in their physical functioning compared to a 7.67 % (−10.43– − 4.92) deterioration for workers who mostly worked in a poor quality job. Voluntary retirees reported a 3.32 % (1.58–5.06) improvement in their mental health, whereas older workers who mostly had a poor quality job reported a deterioration of 1.35 % (−3.66–0.96). Similarly, voluntary retirees reported a 2.17 % (−1.00– − 0.53) increase in physical activity, but workers who mostly worked in a poor quality job reported a 3.17 % (−6.83–0.50) decrease. In contrast, there were no significant differences between voluntary retirees and those who had never or only sometimes reported working in poor quality jobs. Nonetheless, point estimates provided evidence of a linear trend between the length of exposure to poor quality employment and the likelihood of poorer health outcomes. The predicted health outcomes by job quality are plotted in Fig. 2. Sociodemographic patterning of job quality Our results indicate that the health benefits or costs of sustained employment are dependent upon job quality. We now describe the social patterning of job quality, to identify which older workers may be most at risk. As shown in Table 5, Cramer’s V estimates revealed relatively weak associations between categories of job quality and sociodemographic variables. Where associations were evidence, the patterning revealed that poor job quality was aligned with social disadvantage. Older men were more likely than women to work in the best or worst quality jobs, with older women more likely to sometimes work in a poor quality job over this period of follow up. Working in a relatively good quality job was linked with higher education attainment; 39.8 % of those with lower levels of education reported poor job quality for most of the follow-up compared to 20.7 % of those with tertiary education. Among older workers, those who were married were more likely to report never working in a poor quality job (33.0 %) compared to single older workers (24.8 %), as were full-time compared to part-time workers (33.9 % compared to 23.0 %). Casual workers (50.0 %) compared to ongoing or fixed-term employed (28.8 %) workers were also more likely to report a poor quality job for most of the follow-up period. White collar workers were less likely to report poor job quality for most of the follow-up period; just 24.3 % white collar workers reported that their job was poor quality for most of the waves compared to 30.4 % of pink collar and almost half (48.5 %) of blue collar workers. There were only small differences by adult or grandchild care responsibilities, and almost no difference by health status. There was, however, a clear gradient in income and job quality; 42.1 % of those in the poorest households reported mostly or always having a poor quality job, compared to just 15.3 % of those in the richest.Table 5 Sociodemographic profile of those who experienced poor job quality for none, some or most of their follow-up for those who continued working Reported poor quality job during follow-up Total Cramér’ssr Never Some Most N = 551 V N = 172 N = 203 N = 176 (100 %) N Row % N Row % N Row % N Gender 0.138  Men 105 33.9 96 31.0 109 35.2 310  Women 67 27.8 107 44.4 67 27.8 241 Education level 0.152  High school or below 53 22.9 86 37.2 92 39.8 231  Certificate or diploma 51 30.0 66 38.8 53 31.2 170  Bachelor or higher 68 45.3 51 34.0 31 20.7 150 Marital Status 0.089  Married or de facto 142 33.0 159 37.0 129 30.0 430  Single 30 24.8 44 36.4 47 38.8 121 Employment status 0.105  Full-time 141 33.9 150 36.1 125 30.1 416  Part-time 31 23.0 53 39.3 51 37.8 135 Contract Status 0.160  Ongoing or fixed term 108 32.7 127 38.5 95 28.8 330  Casual 10 19.2 16 30.8 26 50.0 52 Occupation 0.163  White collar 98 39.0 92 36.7 61 24.3 251  Blue collar 29 22.0 39 29.6 64 48.5 132  Pink collar 45 26.8 72 42.9 51 30.4 168 Adult-care giving 0.069  No 150 32.9 165 36.2 141 30.9 456  Yes 14 23.0 26 42.6 21 34.4 61 Grandchild care 0.084  No 148 32.2 162 35.2 150 32.6 460  Yes 15 26.8 27 48.2 14 25.0 56 Health condition 0.017  No 146 30.9 174 36.9 152 32.2 472  Yes 26 32.9 29 36.7 24 30.4 79 Household income (quintiles) 0.177  Poorest 6 22.1 12 35.8 18 42.1 36  2 17 22.4 33 41.1 34 36.5 84  3 26 26.1 35 34.5 32 39.5 93  4 42 35.3 55 37.0 56 27.7 153  Richest 81 48.7 68 36.0 36 15.3 185 Notes: Percentages may not sum to 100 due to rounding Sensitivity analyses We tested the robustness of our results with two sets of sensitivity analyses. First, we included further covariates into our linear regression models to test if the observed patterns of health changes could be explained by a more comprehensive list of sociodemographic or health behaviour characteristics measured at baseline. The results (not shown here but available online in Additional file 1: Table S1) for the models which tested employment and job quality groupings revealed that the pattern and direction of the estimates for the predicted change in health outcomes and physical activity were largely unchanged (see Additional file 1: Tables S1 and S2). We also tested our models which decomposed employment by job quality using a count (not ratio) measure of job quality to consider if the choice of approach to handle missing data altered the results. Results of these models were also unchanged from analyses using the reported ratio measure (see Additional file 1: Table S3). Discussion This paper examines the health effects of extended labour force participation, using a nationally representative sample of older Australian adults. Better understanding the nature of the relationship between health and employment into older age is vital as policy efforts to increase the pool of older workers are scaling up, responding to the demographic shifts and economic challenges of population ageing. While rarely discussed, the health outcomes of these policies will decide the extent that the anticipated benefits for individuals, workplaces and societies are realised. Unintended negative health consequences could compromise population health and undermine productivity, thereby increasing government spending on health and age-related services [39]. Our first set of analyses addressed a key conceptual and methodological problem: viewing retirees as a unitary group in terms of their health. Separating voluntary from involuntary retirees revealed distinctive health trajectories. Those who left the workforce involuntarily showed the poorest self-rated, mental and physical health at baseline and the sharpest declines in their health, a finding which accords well with previous research [14, 15]. By modelling involuntary retirement separately, we control for this health selection effect and minimise the potential for misinterpretation of the relationship between health and continued labour force participation relative to (voluntary) retirement. Furthermore, we then show that retirement, when voluntary, is not accompanied by health decline; our second key finding. Voluntary retirees and continuing workers were found to have similar levels of health at the beginning of the study, and similar changes to their physical, self-rated and mental health over the follow-up period [15]. Both groups reported only modest declines in their self-rated health and physical functioning, and small improvements in their mental health. There was some evidence of a slight decline in physical activity linked to extended participation: while the difference between voluntary retirees and extended workers was only marginal, this finding suggests a potential trade-off between extended participation and physical activity, with long term implications for health [40]. In the second stage of our analysis, we investigated if the health effects of extended participation depended on the quality of the jobs held by older workers. By examining job quality, we consider the diversity of labour market experiences, which may generate a variety of health outcomes. Consistent with previous research [7, 8], our results revealed a distribution of health outcomes by job quality, which was itself socially patterned. Older workers who never reported a poor quality job bucked typical age-related trends in their health outcomes and reported no significant deteriorations to their health. While the changes they experienced to their physical functioning, mental health or physical activity health did not differ significantly from voluntary retirees, they did report modest, favourable, changes to their self-rated health. In contrast, older workers who continued to participate in jobs of poor quality reported significantly larger declines in physical functioning, mental health and physical activity levels relative to those who voluntarily retired. Significant health costs were only present in those who reported a poor quality job for most of the follow-up period, although there was evidence that health outcomes declined with longer exposure to poor quality employment. Limitations There are several limitations of our study. The first is that we examined changes over two time points in a nine year period, not health trajectories using data from all nine waves. Health changes, especially in terms of chronic disease, are likely to take several years to be discernible, hence our analysis across a nine year span. Using more data points and modelling changes year by year might provide a deeper understanding of the dynamics of employment-related health trajectories in older workers. We did not model whether the association between job quality and health outcomes differed for those in part-time employment, or by occupation or industry. Controlling for these characteristics at the study baseline did not substantially alter the pattern of results. However it is possible that changes to these factors over the follow-up period are important for the association between employment and health, particularly for physical activity. There are also limitations related to our measures. All of our measures were self-reported and two of our outcome measures (self-reported health and physical activity) were single items. Our single-item measure of physical activity also does not allow us to distinguish incidental activity from leisure time activity but future research should examine these associations using more measures of health and examine the ways in which these relationships differ for different types of workers. Our final limitation relates to our measure of job quality. Our measure has shown to be a good indicator of a number of key aspects of psychosocial work environment, such as job control and effort reward fairness. Nevertheless, it does not measure other features of the work environment also crucial for health [18, 41] and is thus likely to provide a conservative estimate of the job quality-health relationship. Future research would benefit from using an expanded measure, that includes employment preferences, workloads, and physically demanding work, as well as considering whether some aspects of job quality are more important than others for supporting optimal health among older workers. Conclusion While previous research has shown how job quality shapes early retirement intentions, our study reveals that job quality will also determine how the health of older workers is shaped and distributed when labour force participation is extended. On the one hand, extended employment in a high quality job could protect the health of older workers, slowing age-related declines in physical health and supporting greater age-related improvements to mental health. On the other hand, employment in poor quality jobs may erode good health, amplifying age-related declines in physical health and blocking access to age-related improvements to mental health. Our analysis reveals that both outcomes are possible consequences of increasing the participation rates of older workers, and that these very different outcomes are driven by job quality. Our analysis of the sociodemographic distribution of job quality indicates that, at least in the Australian context, a relatively large number of older workers may be vulnerable; more than two-thirds of our sample reported poor quality jobs at some point during study period. Furthermore, the social patterning of job quality followed traditional axes of disadvantage: women, as well as single, less educated workers and people living in households with lower incomes were less likely to report being in optimal quality jobs, as were part-time, less skilled and casually employed workers. Poor quality employment could therefore compound social disadvantage, raising the possibility that policies to extend employment could exacerbate health inequities, unless they are paired with policies to address job quality. Furthermore, failure to address employment-related health declines has the potential to undermine the long-term success of these policies by increasing the demand for health and age-related services. If the anticipated social, health and economic benefits of extended labour force participation are to be realised, it will be essential that older workers have access to good quality jobs. That is, secure jobs that deliver fair rewards, allow for use of workers’ skills and provides some measure of job control. Additional file Additional file 1: Supplementary tables.doc–tables presenting the results of the analyses which are adjusted for a larger number of covariates (Tables S1 and S2) and adjusted for the count (rather than ratio) measure of job quality (Table S3). (DOCX 21 kb) Abbreviations HILDAHousehold, Income and Labour Dynamics in Australia Survey NILFNot in the Labour Force OECDOrganisation for Economic Co-operation and Development SCQSelf-completion Questionnaire Acknowledgements This paper uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Social Services (DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper, however, are those of the authors and should not be attributed to either DSS or the Melbourne Institute, or our Industry Partners. Funding This paper is supported by an Australian Research Council Linkage Project LP 130100227, which is led by Barbara Pocock, Carol T Kulik, Sara Charlesworth, and Lyndall Strazdins, in partnership with Equal Opportunity for Women in the Workplace Agency and Women in Super. Lyndall Strazdins, Sara Charlesworth and Peter Butterworth are supported by Australian Research Council Future Fellowships FT110100686, FT120100346 and FT130101444 respectively. Availability of data and materials Licences are required for the HILDA Survey and can be sought from the Melbourne Institute. Authors’ contributions JW, LS and PB were involved in the study design. JW conducted the statistical analyses, PB and LS advised on the statistical analyses. JW, LS, SC and CK wrote the initial drafts of the paper. LS, SC, CK and PB provided comments on the manuscript. All authors read and approved the manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate Our secondary analysis was approved by the Human Research Ethics Committee at the University of South Australia (project ID: 0000032602) and the Australian National University Human Ethics Committee (project ID: 2014/117). Respondents provided consent to take part in the study and parental consent was obtained for respondents aged less than 18 years. ==== Refs References 1. Global Health Estimates 2014 Summary Tables: DALY by cause, age and sex, by word bank income category, 2000–2012 [Available from: http://www.who.int/healthinfo/global_burden_disease/en/] 2. OECD Age Dependency Ratios Society at a Glance 2006: OECD Social Indicators 2007 Paris OECD Publishing 3. OECD Live Longer, Work Longer Ageing and Employment Policies 2006 Amsterdam OECD Publishing 4. Deloitte Access Economics Increasing participation among older workers: The grey army advances 2012 Canberra Report prepared for the Australian Human Rights Commission 5. Australian Human Rights Commission Age Discrimination–exposing the hidden barrier for mature age workers 2010 6. Waddell G Burton AK Is work good for your health and well-being? 2006 London The Stationery Office 7. Broom DH D’Souza RM Strazdins L Butterworth P Parslow R Rodgers B The lesser evil: Bad jobs or unemployment? A survey of mid-aged Australians Soc Sci Med 2006 63 575 586 10.1016/j.socscimed.2006.02.003 16597477 8. Butterworth P, Leach L, Strazdins L, Olesen S, Rodgers B, Broom D. The psychosocial quality of work determines whether employment has benefits for mental health: results from a longitudinal national household panel survey. Occup Environ Med. 2011. 9. van der Heide I Van Rijn RM Robroek SJW Burdorf A Proper KI Is retirement good for your health? A systematic review of longitudinal studies BMC Public Health 2013 13 1180 10.1186/1471-2458-13-1180 24330730 10. Zantinge EM van den Berg M Smit HA Picavet HSJ Retirement and a healthy lifestyle: opportunity or pitfall? A narrative review of the literature Eur J Pub Health 2014 24 3 433 439 10.1093/eurpub/ckt157 24148557 11. Pit SW Shrestha R Schofield D Passey M Health problems and retirement due to ill-health among Australian retirees aged 45–64 years Health Policy 2010 94 2 175 181 10.1016/j.healthpol.2009.09.003 19853957 12. Coe NB Zamarro G Retirement effects on health in Europe J Health Econ 2011 30 1 77 86 10.1016/j.jhealeco.2010.11.002 21183235 13. Atalay K Barrett GF The causal effect of retirement on health: New evidence from Australian pension reform Econ Lett 2014 125 3 392 395 10.1016/j.econlet.2014.10.028 14. Hult C Stattin M Janlert U Järvholm B Timing of retirement and mortality-A cohort study of Swedish construction workers Soc Sci Med 2010 70 10 1480 1486 10.1016/j.socscimed.2009.10.043 19932547 15. Jokela M Ferrie JE Gimeno D Chandola T Shipley MJ Head J Vahtera J Westerlund H Marmot MG Kivimäki M From midlife to early old age: Health trajectories associated with retirement Epidemiology 2010 21 3 284 290 10.1097/EDE.0b013e3181d61f53 20220519 16. Brown WJ Heesch KC Miller YD Life events and changing physical activity patterns in women at different life stages Behav Med 2009 37 3 294 305 10.1007/s12160-009-9099-2 17. Green F Demanding Work: The Paradox of Job Quality in the Affluent Economy 2006 Princeton Princeton University Press 18. Eurofound Health and well-being at work: A report based on the fifth European Working Conditions Survey 2012 Dublin Eurofound 19. Muñoz De Bustillo R Fernández-Macías E Antón J-I Esteve F Measuring More than Money: The Social Economics of Job Quality 2011 Cheltenham Edward Elgar Publishing 20. Wilkinson R Marmot M Social Determinants of Health: The Solid Facts 2003 Geneva The World Health Organisation 21. Cottini E Lucifora C Inequalities at work Job quality, Health and Low pay in European Workplaces AIAS, GINI Discussion Paper 86 2013 22. Wu B Porell F Job Characteristics and Leisure Physical Activity J Aging Health 2000 12 4 538 559 10.1177/089826430001200405 11503731 23. Butterworth P Leach LS McManus S Stansfeld SA Common mental disorders, unemployment and psychosocial job quality: is a poor job better than no job at all? Psychol Med 2012 43 8 1763 1772 10.1017/S0033291712002577 23190443 24. Strazdins L Shipley M Broom D What Does Family-friendly Really Mean?: Wellbeing, Time, and the Quality of Parents’ Jobs Australian Bulletin of Labour 2007 33 2 202 225 25. Kouvonen A Kivimäki M Elovainio M Virtanen M Linna A Vahtera J Job strain and leisure-time physical activity in female and male public sector employees Prev Med 2005 41 2 532 539 10.1016/j.ypmed.2005.01.004 15917049 26. Australian Institute for Health and Welfare Older Australia at a glance Cat no AGE 52 2007 4 Canberra AIHW 27. Von Bonsdorff ME Huuhtanen P Tuomi K Seitsamo J Predictors of employees’ early retirement intentions: an 11-year longitudinal study Occup Med 2010 60 2 94 100 10.1093/occmed/kqp126 28. Volanen SM Suominen S Lahelma E Koskenvuo K Koskenvuo M Silventoinen K Sense of coherence and intentions to retire early among Finnish women and men BMC Public Health 2010 10 1 1 12 10.1186/1471-2458-10-22 20043862 29. Wang M Shultz KS Employee Retirement: A Review and Recommendations for Future Investigation J Manag 2010 36 1 172 206 30. Summerfield M Freidin S Hahn M Li N Macalalad N Mundy L Watson N Wilkins R Wooden M HILDA User Manual-Release 13 2014 Melbourne Melbourne Institute of Applied Economic and Social Research, University of Melbourne 31. Watson N Wooden M Re-engaging with Survey Non-respondents: The BHPS, SOEP and HILDA Survey Experience. Melbourne Institute Working Paper No. 2/11 2011 Melbourne Melbourne Institute of Applied Economic and Social Research, The University of Melbourne 32. Watson N Wooden M Sample Attrition in the HILDA Survey Aust J Labour Econ 2004 7 293 308 33. Butterworth P Crosier T The validity of the SF-36 in an Australian National Household Survey: demonstrating the applicability of the Household Income and Labour Dynamics in Australia (HILDA) Survey to examination of health inequalities BMC Public Health 2004 4 1 44 10.1186/1471-2458-4-44 15469617 34. Ware JE Jr Sherbourne CD The MOS 36-Item Short-Form Health Survey (SF-36): I. Conceptual Framework and Item Selection Med Care 1992 30 6 473 483 10.1097/00005650-199206000-00002 1593914 35. Idler EL Benyamini Y Self-Rated Health and Mortality: A Review of Twenty-Seven Community Studies J Health Soc Behav 1997 38 1 21 37 10.2307/2955359 9097506 36. Leach L Butterworth P Rodgers B Strazdins L Deriving an evidence-based measure of job quality from the HILDA survey Aust Soc Policy J 2010 9 67 86 37. Charlesworth S Welsh J Strazdins L Baird M Campbell I Measuring poor job quality amongst employees: the VicWAL job quality index Labour Ind 2014 24 2 103 123 10.1080/10301763.2014.915787 38. Mein G Martikainen P Hemingway H Stansfeld S Marmot M Is retirement good or bad for mental and physical health functioning? Whitehall II longitudinal study of civil servants J Epidemiol Community Health 2003 57 1 46 49 10.1136/jech.57.1.46 12490648 39. Barnay T Health, Work and Working Conditions: A Review of the European Economic Literature OECD Economics Department Working Papers, No 1148 2014 Paris OECD Publishing 40. Warburton DER Nicol CW Bredin SSD Health benefits of physical activity: the evidence Can Med Assoc J 2006 174 6 801 809 10.1503/cmaj.051351 16534088 41. Mäkikangas A Feldt T Kinnunen U Warr’s scale of job-related affective well-being: A longitudinal examination of its structure and relationships with work characteristics Work Stress 2007 21 3 197 219 10.1080/02678370701662151

PMC005xxxxxx/PMC5000458.txt

==== Front Biomed Eng OnlineBiomed Eng OnlineBioMedical Engineering OnLine1475-925XBioMed Central London 20410.1186/s12938-016-0204-zResearchOutflow monitoring of a pneumatic ventricular assist device using external pressure sensors Kang Seong Min ng0213@kangwon.ac.kr 1Her Keun hktree@schmc.ac.kr 2http://orcid.org/0000-0003-4045-4384Choi Seong Wook swchoe@kangwon.ac.kr 11 Department of Mechanical and Biomedical Engineering, College of Engineering, Kangwon National University, 192-1 Hyoja-Dong, Chuncheon-si, South Korea 2 Department of Cardiovascular and Thoracic Surgery, Soonchunhyang University Hospital, Bucheon-si, South Korea 25 8 2016 25 8 2016 2016 15 1 10023 3 2016 4 7 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background In this study, a new algorithm was developed for estimating the pump outflow of a pneumatic ventricular assist device (p-VAD). The pump outflow estimation algorithm was derived from the ideal gas equation and determined the change in blood-sac volume of a p-VAD using two external pressure sensors. Objectives Based on in vitro experiments, the algorithm was revised to consider the effects of structural compliance caused by volume changes in an implanted unit, an air driveline, and the pressure difference between the sensors and the implanted unit. Methods In animal experiments, p-VADs were connected to the left ventricles and the descending aorta of three calves (70–100 kg). Their outflows were estimated using the new algorithm and compared to the results obtained using an ultrasonic blood flow meter (UBF) (TS-410, Transonic Systems Inc., Ithaca, NY, USA). Results The estimated and measured values had a Pearson’s correlation coefficient of 0.864. The pressure sensors were installed at the external controller and connected to the air driveline on the same side as the external actuator, which made the sensors easy to manage. Ministry of Food and Drug Safety (Korea)16172MFDS339Choi Seong Wook issue-copyright-statement© The Author(s) 2016 ==== Body Background A ventricular assist device (VAD) is effective for treatment of systolic end-stage heart failure, and can support the patient’s blood circulation until heart transplantation [1–8]. In fact, patients’ 1-year survival rates were three times higher when a VAD was used compared to drug therapies alone [6–8]. Despite the advantages of VADs, they are not widely implemented because of their high cost and risk of critical failure [6–9]. Malfunctions and inappropriate control of VADs can seriously damage organs and vessels; therefore, the outflow of VADs must be monitored to detect device failure or changes in the patient’s physiology [10–15]. The estimation of outflow using blood pressure sensors or motor speed has been studied; specifically, estimation according to the VAD outflow has been compared to that measured by an ultrasonic blood flow meter (UBF) [13–19]. The inlet blood pressure of the VAD has been shown to detect abnormal blood inflow; however, blood pressure sensors are difficult to manage for long periods because of their limited life span and difficulties in preventing thrombosis and fibrosis around the sensors [15, 16]. Outflow estimation has been studied based on the relationship between the motor speed and current consumption under normal hemodynamic conditions [17–20]. However, pathological changes in the patient’s physiologic state, or unexpected device failures, change the relationship between motor speed and current consumption. Although measurement with a UBF has been used to monitor the outflow of the VAD, the large size and complicated management process requires improvement [10, 13]. Pulsatile VADs (p-VAD) or artificial hearts may provide more effective measurements, since p-VADs pulsate blood in the implanted unit with transferred air expanding the air pocket [2, 8, 12, 21, 22]. The internal pressure can change the volume of the air pocket in the implanted unit; however, the air pressure cannot be used to calculate the volume change without considering the air moving to and from the implanted unit [22]. Measurement of the number of molecules of air with a VAD is not possible due to the structural deformation that the devices cause, as well as regulation of pulsation and suction force. Instead, the air through the airline can be measured using two air pressure sensors [21]. The change in volume of the air pocket in the implanted unit is calculated according to the amount of air molecules and the internal pressure in the implanted unit. In this study, a new algorithm for determining the stroke volume (SV) and outflow of p-VADs was developed by measuring the internal pressure and the number of air molecules in the external unit. The data obtained using this algorithm was verified by in vivo and in vitro experiments. Methods Design of the stroke volume estimation system of a p-VAD The SV of a pneumatic p-VAD is determined by the expanding volume of the air pocket in the unit, which is driven by an external pneumatic actuator (as shown in Fig. 1) [12]. However, there is a major difference between the expanding air volume of the implanted unit and the ejected air volume from the external actuator [21]. The air pressure of the implanted unit depends not only on the driving force from the external unit, but also on the inlet and outlet blood pressures of the implantable unit [22]. The inlet and outlet blood pressures could be changed according to the patient’s hemodynamic conditions. To detect the pump SV and the expanding volume of the air pocket in an implanted unit, data including the number of air molecules was considered in addition to the internal pressure of the implanted unit, according to an ideal gas equation.Fig. 1 Variation of stroke volume (SV) according to air movement in the external driving unit. a Initial state volume (V’), b variation in volume according to air movement in cylinder (V’) Although the number of air molecules in the air pocket could not be determined by the internal pressure alone, the transfer of air molecules through the air driveline could be measured by the differential air pressure sensor. Differential pressure can also be useful to estimate the internal pressure in the implanted unit without the requirement of an additional sensor in the implanted unit, by considering the length of the air driveline. Therefore, the p-VAD system estimated SV and pump outflow with a differential pressure sensor (MPX2100AP; Freescale Semiconductor, Inc., Austin, TX, USA) and an absolute pressure sensor, which were embedded in the external actuator as shown in Fig. 2. The measuring points, A and B, of those pressure sensors were also located in the external actuator.Fig. 2 Configuration of the pump outflow estimation system of an external driving unit (① The mean pressure sensor, ② the differential pressure sensor (A to B), ③ the airline, and ④ the actuator) Table 1 Estimation parameters and measured (Unit) Parameters for estimation Measured parameters RAV (mmHg s/cc) – 0.11 ± 0.01 RAB (mmHg s/cc) 0.125 (Eq. 4) 0.15 ± 0.5 lA–V (mm) – 41 ± 0.5 lA–B (mm) – 201 ± 0.5 k1 (mol/mmHg2 s) – 2.69 ± 0.05 (at 25 °C) k2 – 5 (Eqs. 2, 3) 4.9 ± 0.05 C (cc/mmHg) 0.21 (Eq. 3) 0.3 ± 0.01 In this study, the LibraHeart I (LibraHeart, Inc., Jeju, Korea) was used as a p-VAD with a tube-shaped blood sac that was designed to reduce the region of stationary blood to prevent thrombosis [12, 23]. Similar to a conventional p-VAD, the LibraHeart I has an external actuator and an implanted unit. The external actuator ejected air through the driveline. The volume of air transferred through the driveline was obtained by dividing the resistance between the two measured points by the differential pressure, according to Ohm’s law. However, because resistance according to air density, the amount of transferred air was determined using Eq. (1), which was derived from an ideal gas equation: 1 [nA-B]0t=k1PA(t)∫0tPdiff(t)dt k1=1RRA-BT,Pdiff(t)=PA(t)-PB(t) nA−B: mole number of passing air molecules at A PA(t): pressure at A PB(t): pressure at B Pdiff(t): difference in pressure between A and B R: gas constant (= 62.4 × 103 cc mmHg/mol K) k1: mole number—air pressure ratio (of air passing from A to B). The air that passed through the driveline affected the air volume and pressure. Moreover, the driveline air changed the volume of the air pocket to that of the blood ejection or filling volume. To obtain the difference in air pocket volume, the internal pressure of the unit was measured along with the volume of transferred air. When the molecules of passing air were the same as that determined by Eq. (1), the internal pressure was measured using a differential pressure sensor and an absolute sensor according to Eq. (2). 2 PV(t)=PA(t)-k2Pdiff(t) k2=lA-VlA-B PV(t): pressure at the implanted unit of the VAD lA−V: length from A to the implanted unit of the VAD (lA−V) lA−B: length from A to B k2: length ratio between lA−V and lA−B. The air pocket volume of the implanted unit was determined by the differential and absolute pressure set at A and B in Fig. 2. It is important to note that the internal pressure of the implanted unit and the air driveline expand those internal volume and their internal volume expansion decreases the effect of air pocket expansion on SV. Equation 3 suggests that the implanted unit is deformed and expanded by the internal pressure. The effective internal volume, V(t) was obtained with Eq. 4 to find the effect of both air pocket expansion and the expansion of structure space on the SV. The SV was determined as the difference between the maximum and minimum of the effective internal volume from Eq. 5. Table 1 shows the previously measured parameters and the used parameters for the estimation from the Eqs. 1 to 5. 3 V′(t)=CPA(t)+PV(t)2-Pext=C2PA(t)-k2Pdiff(t)2-Pext k2=lA-VlA-B 4 V(t)=1RA-BPAt∫0tPdifftdtPVt-V′(t) 5 SV|pulse_period=[maxVt-min(V(t))]t-pulse_periodt In vitro and In vivo experiments for verifying the stroke volume To evaluate the accuracy of the suggested SV estimation, a series of in vitro experiments were performed using a mock circulation system and compared to the results obtained using a UBF (Fig. 3). The probe of the UBF was positioned on the outlet tube of the implanted unit. A clamp was installed to adjust the blood pressure from 80 to 120 mmHg and, by adjusting the chamber, the peak-to-peak pressure changes were maintained at 40 mmHg. The SV was estimated from preloads ranging from 0 to −180 mmHg and afterloads ranging from 0 to 180 mmHg.Fig. 3 Mock circulatory system used to evaluate the pump outflow during the in vitro experiment. (① External driving unit, ② ultrasonic blood flow meter (UBF; TS-410, Transonic Systems Inc.) ③ pressure measurement device (MP36; Biopac Inc., Daegu, Korea), ④ outlet chamber used to simulate aortic pressure, ⑤ clamp to simulate the resistance of systemic perfusion, ⑥ the inlet chamber to simulate the left atrial pressure, ⑦ the UBF (PXL Clamp flow sensor; Transonic Systems Inc.), and ⑧ the implanted unit) In this study, LibraHeart I p-VADs were connected to three calves, whose weights ranged from 76 to 98 kg, and the estimates of pump outflows were compared (Fig. 4). For connecting the left-ventricular assist device (LVAD), a thoracotomy was used to insert a catheter between the apex of the left ventricle and the descending aorta. For anesthesia, intramuscular ketamine (10 mg/kg) and inhaled isoflurane (1–2 %) were administered. Units were fixed to the animals’ backs and connected to the UFB probe for comparison to the estimated results. The inputs and outputs of implanted units were connected to the implanted catheter using 90 cm of Tygon tubing. The UBF probe was positioned on the cannula at the outlet side of the device. Following the operation, pump outflows for two animals were measured within 1 week due to failures in maintaining the flowmeter probe. The remaining animal was assessed after 3 months. The pump rate was set between 45 and 65 bpm and the SV of the p-VAD was maintained at 2–3 L/min.Fig. 4 Short/long-term animal experiment (① the implanted unit, ② the ultrasonic sensor, ③ closed circuit television (CCTV), ④ the UBF, and ⑤ the external driving unit) Results The results from the in vitro experiments are shown in Fig. 5. Figure 5a reveals a close relationship between the estimated SV and the volume measured by UBF. The preload was increased from 0 to −180 mmHg, with a reduction in the p-VAD outflow from 2.42 ± 0.23 to 1.15 ± 0.17 L/min. The Pearson’s correlation coefficient for the measured and estimated pump outflow was 0.966. Figure 5b shows the estimated and measured SV, based on the afterload. As the afterload was increased from 0 to 180 mmHg, the pump outflow was reduced from 2.41 ± 0.19 to 1.25 ± 0.27 L/min. When the afterload was changed over wide ranges, the Pearson’s correlation coefficient between the measured and estimated pump outflows was 0.88. Figure 5c shows the estimated and measured SVs according to the pump rate. Pump rate was changed from 40 to 80 bpm and the SV changed from 1.55 ± 0.17 to 2.81 ± 0.26 L/min.Fig. 5 Correlation between the estimated and measured pump outflow. Correlations for a the in vitro preload, b in vitro afterload, and c in vitro bpm are shown The results of the in vivo experiment are shown in Fig. 6. A close relationship was observed between the measured and estimated pump outflows. To increase the preload and afterload, the inlet and outlet cannula on both sides of the device were clamped. The mean outflow of blood was maintained at 2.1 L/min until the preload and afterload were increased and the outflow was decreased to 0.6 L/min. For the three independent animal experiments, the Pearson’s correlation coefficients were 0.901, 0.878, and 0.867.Fig. 6 Correlation between the estimated and measured pump outflows, in vivo The results of the long term in vivo experiment are shown in Fig. 7. Figure 7a shows the estimated and measured SV during 95 days, Fig. 7b reveals a close relationship between the estimated SV and the measured volume using UBF and their Pearson’s correlation coefficient was 0.863. Figure 7c, d and e shows that the SV estimation did not changed in course of time.Fig. 7 Long-term in vivo experiments shown are a variations between the estimated and measured pump outflow over 95 days, b the correlation between the estimated and measured pump outflow, c the error rate during early period from 0 to 30 days after the operation, d the error rate during middle period from 31 to 60 days and e the error rate during final period over 61 days Discussion and conclusion The estimation method suggested herein can be applied to conventional pneumatic p-VADs; however, it cannot be applied to the continuous rotary pumps that are primarily used at present [8]. The p-VAD is currently used for children or infants, where it has been applied to pneumatic artificial hearts [2, 24]. Moreover, the suggested method can also be applied to an intracortical balloon pump (IABP) to determine any expanding of the volume of the balloon. Thus, the technique can improve the safety of medical devices that are driven by air pockets or balloons [25]. The technique described herein estimates the inner pressure of the air pocket and considers the load on both of the implanted devices. The previously used UBF indicated blood flow only and could not be used to determine the cause of abnormal flow. Furthermore, while the current and motor speed could not be used to determine whether the abnormal findings were due to a failure of the device or hemodynamic changes in the patient, the estimation method presented herein determined that the device failed [19, 20]. In this study, errors caused by temperature changes were not observed. During in vitro experiments with a mock circulation system, the temperature of the mock system and the air pocket were between 21° and 25°. During the in vivo experiments, the implanted unit was attached to the animal’s back and the air tube was maintained at ambient temperature. Within a closed chamber (EBE-4HW6P4C-20, ESPEC corp., Japan) of which internal temperature was adjusted from 5° to 40°, the correlation between the estimation SV and the measured was not changed. Even when the calculated effective volume V(t) in Eq. 4 was different according to temperature changes, the SV in Eq. 5 was not changed since the peak-to-peak value of V(t) waveform was not affected by temperature. Within this temperature range, the material compliance and structural volume were not changed and the temperature seemed to equally affect to the air volumes and pressures of the air driveline near sensors and the implanted unit. When the atmospheric pressure was decrease from 770 to 680 mmHg, the LVAD outflow slightly decreased and the SV estimation also decreased same to the measurement. If the temperature and pressure were out of the measuring range, the material compliance and structural space can change and cause the estimation error. The effects of severe temperature and pressure on material, structure and SV estimation will be studied with an advanced chamber. In this study, the preload and afterload to the VAD affected the SV estimation differently. In our estimations, the compliance of air drive line and implanted case was set a value (0.05 cc/mmHg). However, the compliance could be different according to its internal air pressure. When the internal pressure was higher than atmospheric pressure, the compliance was maintained constant value, however, when the internal pressure was −100 mmHg lower than atmospheric pressure, the tube structure were deformed and its compliance got high compliance because of the buckling phenomenon and the abnormal bending curvature of the airline. The compliance of our structure was measured from 200 to −100 mmHg and the compliance was rarely changed within this range. In the in vitro experiments that applied preload below −30 mmHg to the LVAD, temporarily low internal air pressure below −100 mmHg frequently had been shown in the air drive line and implanted case. Those unexpected compliance increase caused the error of SV estimation results when the preload was applied to the VAD. The LibraHeart I p-VAD used in this study contains a tube-shaped blood sac that reduces stagnation, which could otherwise cause thrombogenesis in the blood sac. Although the VAD has a blood sac that is different to that of other pneumatic p-VADs, it also contains an air pocket that is driven by an external actuator. Thus, the estimation method that was applied to the LibraHeart I in this study can also be applied to other devices. The method presented herein also facilitates management of the device, since the data were obtained using sensors located on the external actuator. Authors’ contributions KSM did in vitro experiments and wrote this manuscript, HK participated in the animal experiments. CSW analyzed obtained data. All authors read and approved the final manuscript. All authors read and approved the final manuscript. Acknowledgements This research was supported by a Grant (16172MFDS339) from the Ministry of Food and Drug Safety, awarded in 2016. Competing interests The authors declare that they have no competing interests. ==== Refs References 1. Slaughter MS Singh R The role of ventricular assist devices in advanced heart failure Rev Esp Cardiol 2012 65 11 983 985 10.1016/j.recesp.2012.02.030 2. Calvaruso DF Ocello S Implantation of a Berlin heart as single ventricle by-pass on fontan circulation in univentricular heart failure ASAIO. 2007 53 e1 e2 10.1097/MAT.0b013e31815a2500 3. Trivedi JR Cheng A Singh R Williams ML Slaughter MS Survival on the heart transplant waiting list: impact of continuous flow left ventricular assist device as bridge to transplant Ann Thorac Surg 2009 98 830 834 10.1016/j.athoracsur.2014.05.019 25087934 4. Frazier OH Myers TJ Westaby S Gregoric ID Use of the Jarvik 2000 left ventricular assist system as a bridge to heart transplantation or as destination therapy for patients with chronic heart failure Ann Surg 2003 237 631 637 12724629 5. Kar B Basra SS Shah NR Loyalka P Percutaneous circulatory support in cardiogenic shock: interventional bridge to recovery Circulation 2012 125 1809 1817 10.1161/CIRCULATIONAHA.111.040220 22492948 6. Lietz K Long JW Kfoury AG Slaughter MS Silver MA Milano CA Rogers JG Naka Y Mancini D Miller LW Outcomes of left ventricular assist device implantation as destination therapy in the post-REMATCH era: implications for patient selection Circulation 2007 116 497 505 10.1161/CIRCULATIONAHA.107.691972 17638928 7. Dembitsky WP Tector AJ Park S Moskowitz AJ Gelijns AC Ronan NS Piccione W Jr Holman WL Furukawa S Frazier OH Weinberg AD Heatley G Poirier VL Damme L Long JW Left ventricular assist device performance with long-term circulatory support: lessons from the REMATCH trial Ann Thorac Surg 2004 78 6 2123 2130 10.1016/j.athoracsur.2004.02.030 15561049 8. Rose EA Gelijns AC Moskowitz AJ Heitjan DF Stevenson LW Dembitsky W Long JW Ascheim DD Tierney AR Levitan RG Watson JT Ronan NS Shapiro PA Lazar RM Miller LW Gupta L Frazier H Desvigne-Nickens P Oz MC Poirier VL Meier P Long-term use of a left ventricular assist device for end-stage heart failure N Engl J Med 2001 345 1435 1443 10.1056/NEJMoa012175 11794191 9. Refaat M Chemaly E Lebeche D Gwathmey JK Hajjar RJ Ventricular arrhythmias after left ventricular assist device implantation Pacing Clin Electrophysiol 2008 31 1246 1252 10.1111/j.1540-8159.2008.01173.x 18811803 10. Estep JD Vivo RP Cordero-Reyes AM Bhimaraj A Trachtenberg BH Torre-Amione G Chang SM Elias B Bruckner BA Suarez EE Loebe M A simplified echocardiographic technique for detecting continuous-flow left ventricular assist device malfunction due to pump thrombosis J Heart Lung Transplant 2014 33 575 586 10.1016/j.healun.2014.01.865 24656286 11. Park SM Lee JH Choi SW Detection of premature ventricular contractions on a ventricular electrocardiogram for patients with left ventricular assist devices Artif Organs 2014 38 12 1040 1046 10.1111/aor.12306 24749943 12. Choi SW Nam KW Lim KM Shim EB Won YS Woo HM Kwak HH Noh MR Kim IY Park SM Effect of counter-pulsation control of a pulsatile left ventricular assist device on working load variations of the native heart BioMed Eng OnLine 2014 13 35 10.1186/1475-925X-13-35 24708625 13. Choi SW Park SM Analysis of left ventricular impedance in comparison with ultrasound images Artif Organs 2012 36 5 479 486 10.1111/j.1525-1594.2011.01381.x 22188560 14. Kishimoto Y Takewa Y Arakawa M Umeki A Ando M Nishimura T Fujii Y Mizuno T Nishimura M Tatsumi E Development of a novel drive mode to prevent aortic insufficiency during continuous-flow LVAD support by synchronizing rotational speed with heartbeat J Artif Organs 2013 16 129 137 10.1007/s10047-012-0685-x 23340818 15. AIOmari AH Savkin AV Karantionis DM Lim E Lovell NH Non-invasive estimation of pulsatile flow and differential pressure in an implantable rotary blood pump for heart failure patients Physiol Meas 2009 30 371 386 10.1088/0967-3334/30/4/003 19282557 16. Choi SW Nam KW Venous pressure regulation during pulsatile extracorporeal life support Artif Organs 2008 32 10 822 827 10.1111/j.1525-1594.2008.00649.x 18959672 17. Wakisaka Y Okuzono Y Taenaka Y Chikanari K Masuzawa T Establishment of flow estimation for an implantable centrifugal blood pump ASAIO 1997 43 659 662 10.1097/00002480-199709000-00066 18. Wakisaka Y Okuzono Y Taenaka Y Chikanari K Endo S Masuzawa T Takano H Development of a flow estimation and control system of an implantable centrifugal blood pump for circulatory assist ASAIO 1998 22 488 492 19. Pennings KA Martina JR Rodermans BF Frans JR Vosse NVD Mol VAD Rutten MC Pump flow estimation from pressure head and power uptake for the HeartAssist5, HeartMate II, and HeartWare VADs ASAIO 2013 59 420 426 10.1097/MAT.0b013e3182937a3a 20. Yoshizawa M Sato T Tanaka A Abe K Takeda H Yambe T Nitta S Nose Y Sensorless estimation of pressure head and flow of a continuous flow artificial heart based on input power and rotational speed ASAIO 2002 48 443 448 10.1097/00002480-200207000-00020 21. Kim YI Her K Kang SM Choi SW Estimation of ventricular assist device outflow with the pressures in air pressure line J Biomed Eng Res 2014 35 119 214 10.9718/JBER.2014.35.5.119 22. Kang SM Choi SW Blood flow and pressure evaluation for a pulsatile conduit-shaped ventricular assist device with structural characteristic of conduit shape Trans Korean Soc Mech Eng B 2009 35 1191 1198 10.3795/KSME-B.2011.35.11.1191 23. Kang SM Her K Choi SW Biocompatibility evaluation of a bent-typed left ventricular assist device during long-term animal experiment and emergent situation Trans Korean Soc Mech Eng B 2014 38 739 745 10.3795/KSME-B.2014.38.9.739 24. Tarzia V Braccioni F Bortolussi G Guratto E Gallo M Bottio T Vinanello A Gerosa G Cardiopulmonary exercise testing responses to different external portable drivers in a patient with a CardioWest total artificial heart J Artif Organs 2016 19 2 188 191 10.1007/s10047-015-0868-3 26497137 25. Nolan TDC Hattler BG Federspiel WJ Development of a balloon volume sensor for pulsating balloon catheters ASAIO 2004 50 3 225 233 10.1097/01.MAT.0000123635.20778.52

PMC005xxxxxx/PMC5000459.txt

==== Front BMC GenomicsBMC GenomicsBMC Genomics1471-2164BioMed Central London 301810.1186/s12864-016-3018-2SoftwareSoftware-based analysis of bacteriophage genomes, physical ends, and packaging strategies Merrill Bryan D. brymerr921@gmail.com Ward Andy T. andytward9@gmail.com Grose Julianne H. julianne_grose@byu.edu http://orcid.org/0000-0002-9060-0485Hope Sandra sandrahope2016@gmail.com Department of Microbiology and Molecular Biology, Brigham Young University, 4007 LSB, Provo, UT 84602 USA 26 8 2016 26 8 2016 2016 17 1 67925 4 2015 13 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Phage genome analysis is a rapidly growing field. Recurrent obstacles include software access and usability, as well as genome sequences that vary in sequence orientation and/or start position. Here we describe modifications to the phage comparative genomics software program, Phamerator, provide public access to the code, and include instructions for creating custom Phamerator databases. We further report genomic analysis techniques to determine phage packaging strategies and identification of the physical ends of phage genomes. Results The original Phamerator code can be successfully modified and custom databases can be generated using the instructions we provide. Results of genome map comparisons within a custom database reveal obstacles in performing the comparisons if a published genome has an incorrect complementarity or an incorrect location of the first base of the genome, which are common issues in GenBank-downloaded sequence files. To address these issues, we review phage packaging strategies and provide results that demonstrate identification of the genome start location and orientation using raw sequencing data and software programs such as PAUSE and Consed to establish the location of the physical ends of the genome. These results include determination of exact direct terminal repeats (DTRs) or cohesive ends, or whether phages may use a headful packaging strategy. Phylogenetic analysis using ClustalO and phamily circles in Phamerator demonstrate that the large terminase gene can be used to identify the phage packaging strategy and thereby aide in identifying the physical ends of the genome. Conclusions Using available online code, the Phamerator program can be customized and utilized to generate databases with individually selected genomes. These databases can then provide fruitful information in the comparative analysis of phages. Researchers can identify packaging strategies and physical ends of phage genomes using raw data from high-throughput sequencing in conjunction with phylogenetic analyses of large terminase proteins and the use of custom Phamerator databases. We promote publication of phage genomes in an orientation consistent with the physical structure of the phage chromosome and provide guidance for determining this structure. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3018-2) contains supplementary material, which is available to authorized users. Keywords PhageTerminasePhameratorPhylogenetic treeDNA packagingComparative genomicsSequencingDepartment of Microbiology and Molecular Biology, Brigham Young UniversityLDS Philanthropiesissue-copyright-statement© The Author(s) 2016 ==== Body Background Bacteriophages are the most abundant and diverse biological entities on earth [1]. Thousands of students and professors at hundreds of universities around the world are studying bacteriophages [2]. Low sequencing costs allow researchers to sequence and publish the genomes of phages they study. As a result, phage genomes are being added to GenBank at an exponential rate (Fig. 1).Fig. 1 Total Caudovirales sequenced since 2000. This figure includes all complete genomes of Caudovirales sequenced and deposited in the “Nucleotide” NCBI database since 2000 Phamerator is a computer program [3] written to analyze the many Mycobacteriophages isolated and sequenced through the Howard Hughes Medical Institute (HHMI) Science Education Alliance-Phage Hunters Advancing Genomics and Evolutionary Science (SEA-PHAGES) program [2]. Phamerator is popular among the large groups studying Mycobacteriophages [4] and Bacillus phages [5, 6] and is steadily gaining traction in other areas of phage research [7–11]. Herein we describe software-based methods to study phage genomes, determine phage genome ends, and identify phage DNA packaging strategies. There are several limitations to the original version of Phamerator that we sought to overcome. First, as originally written, Phamerator could only read existing databases hosted on remote servers and could not create custom databases to be explored on local computers. Second, no detailed documentation existed to describe how to make custom databases or use features other than the graphical user interface. The goal of this work was to enhance the existing code, and to make Phamerator accessible to all phage researchers by providing instructions on how to build and use a custom database in Phamerator. In addition, we describe best practices when preparing phage genomes for publication and effective downstream analysis using Phamerator and other programs. These contributions enable phage researchers to use this powerful program and provide a basis for more consistent deposition of phage genomes into NCBI that will facilitate downstream analyses. Phamerator computer coding and database setup Phamerator is written in Python and runs in the Linux Ubuntu operating system [3]. Ubuntu can be installed on any computer as a virtual machine through programs like VirtualBox (https://www.virtualbox.org). Phamerator compiles Structured Query Language (SQL) databases of bacteriophage genomes using GenBank [12] formatted files. Phamerator compares all gene products in the database using ClustalW [13] or ClustalO [14] and BLASTP [15] and then groups these gene products into “phamilies” (phams) based on percent identity or BLASTP expect value (E-value) with other gene products in the pham. Phamerator also prepares linear genome maps for gene order and content (genome synteny) comparison, and includes nucleotide homology output. Researchers can manually assign phages into different clusters within a database, such as groups based on genome similarity, [11, 16, 17], genera [18] or host preference [8]. Phamerator database setup requires four main processing steps. In the first and second steps, Phamerator aligns all possible pairs of gene products in the database using both BLASTP and ClustalW and saves all statistically significant results. In the third step, the user specifies an E-value and a percent identity used to group proteins into phamilies. Other versions of Phamerator have been modified to instead use kClust to assign phamilies [19, 20] and run natively on Windows, Linux, and MacOS. These phamilies can help identify homologous gene products [3]. In the final step, Phamerator identifies conserved domains in every protein in the database using the Conserved Domain Database (CDD) [21]. These tools provide powerful analyses to study gene synteny and conservation. Phamerator reads the phage data stored in the SQL database and displays it in a graphical user interface. Phamerator has two main graphical outputs: linear genome maps and phamily circles. The features and purposes of these graphics are described in the original Phamerator publication [3]. Main features of Phamerator for comparative phage genomics Researchers can display a linear genome map of any number of phages in a database. The maps depict gene products as boxes that are colored by phamily or other parameters (Fig. 2). Colored lines connecting adjacent phage genomes indicate BLASTN homology from purple (low E-value, high percent identity) to red (high E-value, lower percent identity). These maps highlight mosaicism and synteny, and can be adjusted to align homologous genes or sections. Hovering the mouse over gene products will display text describing identified conserved domains and conservation of that gene product throughout phages in a user-defined cluster or throughout the whole database. Figure 2 demonstrates how a linear genome map containing phage genomes in a similar orientation can be used to identify homologous genes, conserved proteins, and conserved domains when compared to other phages in the database. Additional file 1 is a table that lists all of the phages included in the database used to generate the Phamerator figures in this paper.Fig. 2 Phamerator genome map comparison. This linear genome map includes two similar phages published in a similar orientation. Colored lines connecting the genomes indicate the level of nucleotide similarity from purple (low E-value, high percent identity) to red (high E-value, lower percent identity). Horizontal yellow bars inside gene product boxes indicate conserved domains and represent the length of that domain relative to the length of the gene. When the mouse is hovered over one of the yellow conserved domains, a popup box will appear describing that domain (e.g., tail assembly protein, indicated by a dotted outline). When the mouse is hovered over a pham label, a popup box will appear (indicated by a dotted outline) which identifies the clusters and phages that contain a protein in a pham. Using these features, researchers can quickly identify conserved domains in any protein and which other phages in the database contain a homologous protein Phamerator also creates phamily circles for each gene product phamily (Fig. 3). These circles display phage names around the perimeter. Phages are organized around the circle according to user-defined cluster assignments. If a phage contains a gene product in the pham being displayed, the gene product number appears next the phage name. Inside the circle, lines connect proteins in the same pham based on ClustalW or BLASTP relationships. A blue line connecting two gene products indicates that they share greater than 32.5 % identity, a red line connecting two gene products indicates that they have an E-value of less than 1e-50 (Fig. 3). If the ClustalW and BLASTP parameters used to build phamilies vary, then lines may not be drawn if relationships fall below the default values of 32.5 % and 1e-50. Section 3.2, step 9 of Additional file 2 describes the process of building phamilies. We set ClustalW and BLASTP cutoff values for building protein phamilies in this database at 32.5 % and 1e-35, respectively. At this time, changing the parameters for building phamilies will not affect the parameters used to display pham circles.Fig. 3 Phamily circle of pham 271, a Lambda family phage holin. This phamily circle displays the relationships of nine proteins that belong to pham 271. Conserved domains indicate these proteins are phage holins in the Lambda family. Cluster designations which reflect experimentally determined packaging strategies (see Additional file 1) are indicated inside the circle. Gene products connected by red lines are included in the pham because they have an E-value of less than 1e-50. Gene products connected by blue lines are included in the pham because they share more than 32.5 % identity Phamerator exports two user-friendly spreadsheets: the “pham table” and the “cluster table”. The pham table lists phams down the left column and phage names across the top row. Gene products in each phage are placed on the row of the phamily they belong to. The cluster table also lists phams down the left column but lists the user-defined phage clusters across the top row. The number of gene products from each cluster that belong to each pham is listed. Each table lists conserved domains organized by phamily. Additional file 3 is a table that contains an example pham table and cluster table from a Phamerator database, while Fig. 4 contains excerpts from this table. By using sort and filter tools within a spreadsheet editor, these spreadsheets can be used to extract data including gene products common to a select group of phages, all gene products with an identified conserved domain, all members of the largest phamily, and more. Users can also quickly export custom sets of genomes, genes, or proteins.Fig. 4 Excerpts of pham table exported from Phamerator. a The pham table is sorted by gene number in Bacillus phage Basilisk. Conserved domains and phamily members are identified for each gene. b Excerpts displaying only genes found in T3 and T7 (the T3/T7 conserved core genome). c A pham table filtered for conserved domains containing the word “terminase”. All phams containing gene products that are terminases are displayed Phage genome orientation Effective Phamerator analysis of similar phage genomes requires consistency in the genome orientation and the location of the first base. As phage genomes are published it is important that the orientation and complementarity are intentional, reflect physical properties of the phage chromosome, and are consistent with well-characterized phages. Phage genomes are currently deposited with a wide variety in the base one calls for even very similar phages [11]. Thus, one crucial step in preparing phage genomes from GenBank files for Phamerator and other analyses is to rearrange genomes that are oriented incorrectly so that genome content and gene order may be easily compared. Proper identification of physical ends and phage packaging strategies allows researchers to arrange phage genomes correctly before publishing them. Although wet lab methods for determining phage ends and packaging strategies have been described previously [22], these experiments consume time and resources and may be inconclusive. Software-based methods using raw next-generation sequencing data provide insight into physical ends and packaging strategies [23]. These data can guide, clarify, or potentially replace wet lab experiments, especially when working with large datasets. Implementation Modifications to the original Phamerator code fixes errors and allows for continued compatibility The original Phamerator code was retrieved and modified by the Brigham Young University (BYU) Life Sciences IT Department and the authors of this paper. The original Phamerator code is found at http://phamerator.csm.jmu.edu/files/phamerator.release/ and can be installed using Bazaar using instructions available at http://phagesdb.org. Our modifications to Phamerator allow local, custom databases to be easily created, altered, and viewed. These databases can contain both newly sequenced phage genomes and phage genomes retrieved from NCBI. The modified Phamerator code is deposited at http://github.com/byuphamerator/phamerator-dev/. A detailed list of changes is provided in Table 1.Table 1 Phamerator Features and Modifications Feature Updates provided in new version Justification Biopython compatibility Works with BioPython 1.64 Continued compatibility with future Biopython versions Building the Phamerator database Added prompts for username, password, server location, and database name at each step The new prompts replace what was once written directly into the code ClustalO alignments ClustalO may be used instead of ClustalW to perform alignments ClustalO is newer and is faster Computation progress Fixed script displaying the progress of BLAST and ClustalW Helps users estimate when these jobs will finish Pham and cluster tables Column listing conserved domains for each pham was added to these tables Used to quickly determine putative functions of proteins in a pham Domain and pham labels in genome maps Added whitespace to the right of these maps Labels near the end of these maps are now visible Delete BLAST and ClustalW scores Users are prompted to delete or keep all scores when adding or removing phages Scores can be deleted following major modifications to the database This table describes features of Phamerator, the updates provided by the new version we provide, and the justification of why these modifications were necessary The Graphical User Interface (GUI) of Phamerator is run on various operating systems with the aid of virtual software The graphical interface of Phamerator has wide usage among universities involved in the SEA-PHAGES program and is growing in popularity among other phage researchers as well. SEA-PHAGES members can download a pre-configured Ubuntu virtual hard drive file (www.hhmi.org/seawiki) and gain access to the Mycobacteriophage database managed by Graham Hatfull at the University of Pittsburg and Steve Cresawn at James Madison University. The virtual hard drive can be run using VirtualBox (www.virutalbox.org) or other virtualization software. At BYU, Phamerator is accessible in the Windows environment by forwarding an X11 window over SSH from a Linux virtual machine (VM) running on a server. This always-on VM keeps local computers fast as resources aren't spent running a local VM. This server VM allows multiple users on each VM, also saving users the time it takes to install and manage a virtual machine. North Carolina State University (NCSU) has also successfully built their own Phamerator databases which they currently use for teaching and research purposes. A Virtual Computing Lab at NCSU allows students to log on to a Ubuntu virtual machine from anywhere on campus and access Phamerator. After a Phamerator database of phage genomes is compiled and processed it can be viewed and studied using the graphical user interface. Prior to our work, database setup was exclusive to the SEA-PHAGES program. The following section describes how to prepare a Phamerator database using GenBank-formatted genome sequences so that any user can prepare a custom database for analysis. A custom Phamerator database can be generated Phamerator has three main parts: the graphical user interface (GUI), the Python scripts, and the SQL database. The GUI is the window used to view linear genome maps, pham circles, etc. Each Python script performs a specific function such as importing phages or computing Clustal scores. The SQL database is a set of linked tables where all of the phage gene sequences, alignment scores, etc. are stored. The database must be populated with phage genomes and processed before the end-user can view the desired genomes and access the features of Phamerator. The following steps are used to create a Phamerator database containing user-specified phage genome sequences.Install Ubuntu on a computer or inside a virtual machine. Install Phamerator and the programs it needs to run. Create a blank MYSQL database. Insert table headers into the blank database so Phamerator knows where to store and access phage data. Create GenBank-formatted files for recently sequenced phage genomes or retrieve phage GenBank files from NCBI. Use a program, such as DNA Master (http://cobamide2.bio.pitt.edu), to fix any formatting errors. Import phage genome files into the SQL database. Run Clustal comparisons on all phage gene products in the database. Each Clustal “job” compares one phage gene product against all others in the database and records significant alignments. Run BLASTP comparisons on all phage gene products in the database. Each BLASTP “job” compares one phage gene product against all others and records significant E-values. Run phamBuilder to group similar gene products into phamilies. Gene products are joined into a pham when they are similar to at least one other member by either a Clustal percent identity or BLASTP E-value at or above user-defined cutoffs. Commonly used values are 32.5 % identity and 1e-50 E-value [3]. Run cddSearch to identify conserved domains in gene products in the database using the CDD. Export the database to a single SQL file to be shared with others. Detailed instructions to execute these steps have been deposited at our website, http://phagehunters.byu.edu/Phamerator and are also included as Additional file 2. The instructions describe the process in detail to assist users through the technical tasks required to set up Phamerator. For example, Phamerator is currently only available for computers running Ubuntu. In most cases, this means that Ubuntu must be installed as a virtual machine. Processing a Phamerator database requires a computer with a powerful processor. An additional 40 GB of hard drive space is needed to set up a local copy of the CDD so conserved domains can be added to gene products in Phamerator. In the instruction manual, we provide descriptions of common errors that can occur due to variations in GenBank files and include a troubleshooting section for these errors. For example, GenBank files imported into Phamerator must contain unique locus tags, a “gene” feature, and a “CDS” feature for each gene. In addition, to avoid translation errors during importing, each gene in the file must use the “Bacterial and Plant Plastid” translation table. Furthermore, genomes that are arranged incorrectly or contain genes that wrap around the genome from the end to the beginning must first be modified using a program such as DNA Master, written by Dr. Jeffrey Lawrence and available online at http://cobamide2.bio.pitt.edu. Results and Discussion Publication of phage genomes without a standardized genome start location or orientation hinders analysis using comparative genomics software Similar phage genomes that begin near the same gene allow for easy identification and visualization of homologous regions using software such as Phamerator and other comparative analysis programs. When newly published genomes begin at a different gene or are reverse complemented relative to similar genomes, it becomes difficult to make direct comparisons. For example, Fig. 5a is a linear genome map of the three Sf6-like headful packaging phages as they are published on GenBank (E4 cluster, see Fig. 6). Phage Sf6 is oriented so that the terminase (gp2) is near the beginning of the genome in the forward direction. Although APSE-1 and CUS-3 are highly similar, they are not published in a similar orientation, making comparisons difficult. The terminases in APSE-1 and CUS-3 are gp18 and gp21, respectively. APSE-1 is published using the correct complementarity but the base one call is ~8.5 kb upstream relative to Sf6. The published genome of CUS-3 is reverse complemented relative to Sf6 and begins ~17.5 kb upstream (Fig. 5b). Although Phamerator can reverse complement genomes and align specific genes, it cannot assume a circular sequence and rearrange genomes to easily identify homology and synteny. Conflicting genome orientations is a problem not only with Phamerator, but is something that must be addressed before using other popular genome alignment comparisons such as MAUVE [24] or dot plot analysis programs. DNA Master is a program that can be used import GenBank files, rearrange genomes, and export FASTA or GenBank files (see instruction manual), but this can be time-consuming. We adduce a best practice to publish phage genomes in light of physical ends and packaging strategies and not based on artificial circularity or a previously published phage genome that may be oriented incorrectly. Accurate base one calls prior to publication will facilitate rapid, precise comparisons between similar phage genomes using Phamerator and many other programs. Prior to building a custom Phamerator database, we assess each phage genome to ensure consistency in the genome start position and orientation.Fig. 5 Linear genome map of three circularly permuted phages from the E4 cluster, which package chromosomes via the headful strategy. a Only Sf6 is arranged correctly. The large terminase protein is outlined in orange. Relative to phage SF6, APSE-1 and CUS-3 are arranged incorrectly and CUS-3 is also reverse-complemented. Lines connecting CUS-3 and SF6 indicate nucleotide homology. b Using DNA Master, APSE-1 and CUS-3 were rearranged and reversed complemented and these new files were reanalyzed using Phamerator for comparison. Original gene numbers were preserved Fig. 6 Neighbor-joining tree of large terminase proteins. This tree was generated by ClustalX [13], displayed in Mega6 [40], and contains large terminase sequences from phages with experimentally determined packaging mechanisms and physical ends (see Additional file 1). Bootstrap values are for 1000 trials. The scale bar shows 0.1 amino acid substitutions per site. We manually assigned clusters in Phamerator that correspond to packaging strategies. For example, phages that use 3’ cos ends (HK97) are assigned to cluster A1. This phylogenetic tree indicates that large terminase proteins sharing phamilies and packaging strategies also clade together Sequencing data can reveal phage DNA packaging strategy to select the genome start and orientation Regardless of the packaging strategy or physical ends, all tailed bacteriophages (Caudovirales) end up with a linear DNA molecule packaged in the capsid of the mature virion [22]. This genome is then injected into a new host, wherein most phage chromosomes circularize. The mechanism of circularization is dependent on the packaging strategy and the type of physical ends produced. Therefore, identification of the packaging strategy can reveal the location of the physical start of a phage genome, and sequencing data can often be analyzed to determine the packaging strategy used [23, 25, 26]. Bacteriophages that use homologous recombination to generate circular chromosomes following infection must have an identical sequence at each end of the linear chromosome (Fig. 7a). Some phages use exact direct terminal repeats (DTRs) to accomplish this. These repeats can be short (200–700 bp) or long (up to 16 kbp). Following homologous recombination, the circular chromosome contains exactly one copy of the DTR (b). The circular chromosome is replicated via theta and sigma (or rolling circle) replication, forming linear concatemers. The concatemers contain only one copy of the repeat sequence between each genome-length (Fig. 7c). The repeat between the next genome-length and the one being packaged are duplicated so that each virion receives a chromosome with an identical repeat at each end [27–29]. The raw data for these sequences indicate that twice as many reads cover the exact DTR when compared with the rest of the genome since the exact DTR is found twice in each phage chromosome. Thus, a phage likely has exact DTRs if it has an area where the number of reads mapped to the consensus suddenly doubles relative to the surrounding sequence.Fig. 7 Physical structure, circularization, and packaging mechanism of a phage with exact direct terminal repeats (DTR) at each end. a The DNA inside the phage virion before infection has the same sequence at both ends. These ends are identical in each virion. b After infection, the ends undergo homologous recombination to form a circular DNA molecule. c A linear concatemer is generated via rolling circle replication. The repeated ends are duplicated while the DNA is being packaged. Each virion has identical repeats at each end The Pile-up Analysis Using Starts & Ends (PAUSE) program (https://cpt.tamu.edu/computer-resources/pause) looks for DTRs based on changes in coverage depth in reads that are aligned to the assembled phage genome and predicts the sequence and length of exact DTRs. PAUSE takes two inputs: (1) the finished FASTA file containing a phage genome and (2) the raw sequencing data in SFF or FASTQ format. Instructions for PAUSE are available at https://cpt.tamu.edu/analysis-with-pause/. PAUSE returns a plot of genome length versus coverage and predicts where DTR sequences begin and end (Fig. 8a). Consed [30] or another genome viewer can show individual reads mapped to the genome to visualize these changes in coverage. The beginning and end of DTR sequences are marked by sharp increases or drops in fold coverage (Fig. 8b). Each phage genome can be scrutinized to see if it contains repeats. If so, the sequence can be oriented true to the phage chromosome it represents with a repeat region on each end and the genome in the middle.Fig. 8 Analysis of exact DTRs in Bacillus phage Basilisk. a PAUSE analysis graphs the number of reads mapped to the Basilisk genome. The region between the sense and antisense starts and ends indicates the location of the short exact DTR in Bacillus phage Basilisk, which was used to call base one [6]. b Consed shows a sharp increase in coverage near the left end (sense start) of the exact DTR in Bacillus phage Basilisk. This location corresponds to the sense start which is marked by a tall read spike in Fig. 8a If no exact DTRs are identifiable, the phage may have cohesive ends or may be circularly permuted due to headful packaging. Phages with cohesive ends have a 3’ or 5’ overhang on each end of the phage chromosome (Fig. 9a). Before the chromosome is replicated, complementary overhangs will base-pair and the DNA is ligated into a circular molecule (Fig. 9b). A polymerase travels around the circular chromosome and produces linear concatemers up to ten genomes in length [31]. Overhangs are created when the large terminase identifies a specific cos site in the concatemer, starts packaging the DNA, and cleaves the DNA when the next cos site appears (Fig. 9c). The terminase cuts precisely at the cos site each time and packaging occurs with exactly one genome-length sequence in each phage capsid.Fig. 9 Physical structure, circularization, and packaging mechanism of a phage with cohesive ends. a Structure of DNA inside phage virion before infection. Phages with cohesive ends can have 3’ or 5’ overhangs. b Shortly after infection, the sticky ends are ligated. The chromosome is replicated via rolling circle replication during the lytic phase. c Exactly one genome length is packaged into each phage capsid. The terminase protein cuts at the cos site, leaving 5’ or 3’ overhangs Phages with cohesive ends occasionally produce a distinctive pattern in read coverage at the cos site. To identify an area to search for this pattern, we first determine the location of the large terminase gene using BLASTX and an Entrez query of “terminase.” The cos site is often near the terminase genes. Chromosomes of phages with cohesive ends do not contain any repeated elements like phages that have exact DTRs or are circularly permuted and may or may not generate an artificially circular sequence. However, the ends of a few sequenced chromosomes can be ligated together producing reads that go from one end of the genome to the other. This relatively rare ligation event results in a sudden drop in fold coverage over the precise location of the cos site (4–19 base pairs) (Fig. 10). The lower-coverage cos site will also be flanked by many reads that begin or end at an identical location immediately flanking the cos site. If this coverage drop at the cos site is identifiable, the ends of the phage genome in Consed will show reads that run off one end of the genome and coincide with bases at the other end if the genome is complete (Fig. 11). If the genome ends don’t show any reads wrapping around, it is likely that the cohesive ends were not sequenced. In this case, the returned assembly likely spans one cohesive end to the other and does not actually include the overhang sequence on either end. At this point, it is possible to design PCR primers that will identify the sequence of these ends [2].Fig. 10 Consed visualization of cos overhang sequence. Consed shows a sharp drop in coverage over the 3’ overhang in Mycobacterium phage Atkinbua Fig. 11 Consed visualization of wrap-around reads. The assembled contig for Mycobacterium phage Girly (http://phagesdb.org) contains reads that wrap around the ends of genome. The highlighted sequence to the left of the genome start a is the same as the last few base pairs at the end of the genome b The chromosomes of free virions that use headful packaging have a direct terminal repeat sequence on each end but these sequences vary among progeny phages; i.e., these repeats are not exact (Fig. 12a). The phage chromosomes circularize using homologous recombination (Fig. 12b) and form linear concatemers following replication. The terminase protein recognizes a specific site on the DNA called the pac sequence. The terminase cuts at or often near the pac site and begins inserting the first genome-length of the concatemer into a capsid until the capsid is full (Fig. 12c) and packages more than one genome-length (102–110 %) into each capsid. Unlike phages with exact DTRs that package the exact same sequence in each virion, phages that use headful packaging are unlikely to produce two virions that have the same sequence length starting and ending at the same location. Because slightly more than a genome-length is packaged, the first DNA base packaged in a given capsid can theoretically be any base in the genome and progeny virion chromosomes are circularly permuted.Fig. 12 Physical structure, circularization, and packaging mechanism of a phage that uses headful packaging. a This figure represents the first phage chromosome packaged from a linear concatemer. The DNA inside the phage virion before infection has a similar DNA sequence at both ends. The repeat sequences at the ends of each chromosome vary from phage to phage. The bracket indicates exactly one genome-length (from one pac sequence to the next). b After infection, the ends undergo homologous recombination to form a circular DNA molecule that contains exactly one genome-length and one pac site. A linear concatemer is generated via rolling circle replication. c Beginning at the pac site, the terminase inserts the DNA into the capsid. The terminase creates imprecise cuts after slightly more than one genome length is packaged into the capsid, generating a repeated sequence at each end. Thus, the position of the pac site varies in each subsequent virion Phages that have circularly permuted DTRs due to headful packaging will always show reads that run off one end of the genome when sequenced completely. These wrap-around reads contain bases coinciding with the other end of the genome (Fig. 11). If PAUSE shows consistent read depth throughout the genome, wrap-around reads are identified by Consed, no putative exact DTR repeat regions are identified, and there are no sudden drops in coverage near the large terminase gene indicative of cohesive ends (Fig. 10), then the phage is likely circularly permuted and uses headful packaging. Phages rely on terminase proteins to identify replicated phage chromosomes from among the other DNA inside of the host. Terminases package phage chromosomes into phage capsids and cut concatemers into genome-sized lengths. The role of the terminase varies depending on the packaging mechanism. Therefore, terminases with similar amino acid sequences usually package DNA using similar mechanisms and create similar physical ends [22, 23]. Phylogenetic analysis has been used to gain additional insight into the packaging strategies of novel or poorly-studied phages [32–34] and is one way to predict the type of ends, including whether a phage has host ends. Analysis of large terminase proteins from phages listed in Additional file 1 indicate that large terminases with similar packaging strategies tend to clade together (Fig. 6). The clades of the phylogenetic tree correspond exactly to the cluster grouping that was assigned in Phamerator based on the Phams to which each large terminase belongs (A1-F2). Casjens and Gilcrease reported packaging strategies based on phylogenetic analysis and defined 11 groups: 5’ cos (Lambda, P2); 3’ cos (HK97), headful (P2, Sf6, T4, 933 W, GTA), host ends (Mu and D3112), and short DTRs (T7) [22]. Here, we propose five additional groups based on phylogenetic and Phamerator analysis: short DTRs (N4, C-st); headful (phiPLPE, phiKZ); and long DTRs (SPO1). There are several considerations in making a phylogenetic tree containing large terminases. Although large terminases are well-conserved and are even similar among phages that infect different hosts, the overall diversity of large terminases is often too great to reliably analyze them all in one phylogenetic tree. This diversity causes instability of the branches and nodes as additional sequences are added. When adding a large terminase protein to a phylogenetic tree, some stability can be maintained by also including several BLAST hits that are similar to the terminase being queried, especially those hits that come from phages with experimentally determined packaging strategies. Read pileups, wrap-around reads, changes in coverage density, and terminase phylogenies can guide researchers in making the appropriate “base one” call prior to publication or in designing wet lab experiments to verify the phage ends and packaging strategies. Exact DTRs in phages can be annotated [35] and these genomes are generally published with one repeat sequence on each end [6]. The complementarity of the genome is considered when making a base one call for phages that have exact DTRs, have host ends, or use protein-primed replication. For phages with cohesive ends, 5’ overhangs are placed at the beginning of the published genome, and 3’ overhangs are placed at the end. Base one calls for circularly permuted phages are more complicated because software-based methods cannot yet identify the pac sequence or pac fragment by looking at changes in coverage. Wet lab methods can occasionally identify the pac fragment as a piece of DNA that spans between the origin of replication and the site where the terminase makes the first cut. Because the large terminase protein is responsible for identifying and cutting at the pac site, the sequence of the pac site and the sequence of the large terminase protein often lie very close to each other, with the pac site often just upstream of the large terminase protein [22]. We typically determine base one calls in circularly permuted phages at or just upstream of the large terminase gene with the large terminase gene in the forward direction. Standardizing base one call methods for all phage types, especially for circularly permuted phages, will facilitate comparison of phage genomes and easier identification of homologs. Although the analyses we describe of high-throughput data can give a good indication of the packaging strategy and the physical ends of the phage chromosome, the data may not always provide a definitive answer. For instance, at least two packaging mechanisms are known produce linear chromosomes with no wrap-around sequences, exemplified by phage Mu and phage phi29. Such packaging strategies may be difficult to distinguish from phages with cohesive ends that do not generate artificially circular sequences. Phage Mu inserts copies of its DNA into the host chromosome via replicative transposition [36]. When Mu DNA is excised from the host chromosome prior to being packaged, segments of the host chromosome become the ends of the linear phage DNA. Each segment of DNA packaged into a progeny phage contains different ends since they all came from different parts of the bacterial chromosome. These chromosomes are circularized [37] but are not believed to produce artificially circular genomes when sequenced. Phages like Bacillus phage phi29 also circularize in the host but have a protein covalently linked to each end that serves to prime DNA replication [38]. Phages with host ends or terminal proteins do not generate artificially circular sequences because there is no repeated sequence at the phage ends. Raw sequencing data may rule out cohesive ends, headful packaging, and exact DTRs without confirming whether a phage has host ends or covalent terminal proteins. Wet lab experiments, similarity to previously sequenced and characterized phages, or comparison of large terminase proteins are necessary to verify whether phages have host ends or covalent terminal proteins [22]. A custom Phamerator database can be used to identify packaging strategies based on the large terminase protein Using Phamerator, phamily circles (introduced in Fig. 3) can be created for each phamily in the database and are also a useful tool for identifying packaging strategies. As discussed above, gene products are included in phamilies if they have a sufficiently high E-value or percent identity with at least one other gene product in the phamily. If the requirements for inclusion in a pham are stringent (similar to the default parameters), two terminases in the same pham likely use the same packaging strategy. If a particular phage contains a gene product belonging to the pham, then the gene number is listed next to the phage name (Fig. 13). As described previously, ClustalW and BLASTP relationships are indicated by connecting blue and red lines, respectively (Fig. 13a), except where phamily building parameters fall below 32.5 % and 1e-50. In this case, gene product numbers will be listed next to proteins in a pham but no connecting lines will be drawn (see Fig. 13b). In this database, the large terminases of phages using the same packaging strategy grouped into phamilies that contained no other members as represented by the lack of any line connecting phages of different clusters (clusters were intentionally pre-assigned by packaging strategy). Figure 13c depicts the relationships of all phamilies containing large terminase proteins by overlaying 15 phamily circles generated by Phamerator on top of each other (the Phamerator database used in this analysis can be downloaded from http://phagehunters.byu.edu/Phamerator).Fig. 13 Phamily circles indicate relationships of large terminase proteins. Clusters (A1-F2) were intentionally set to group phages with similar packaging strategies together. a Pham 323 contains only three large terminase proteins, indicated by bolded gp designations. The three phages that encode these terminases belong to cluster E4, which includes phages that use headful packaging (Sf6) [41, 42]. b Pham 2966 contains only three large terminases, indicated by bolded gp designations. The three phages that contain these terminases belong to cluster C3, which includes phages that have short exact DTRs (C-st). These proteins meet the cutoff parameters to be included in pham 2966, but do not meet the parameters required to draw connecting lines (see Fig. 13a). c An overlay of 15 pham circles represents large terminase proteins for every phage in the database. This circle indicates that large terminases grouped into the same pham belong to phages that use the same packaging strategy. In this database, no terminases were grouped with terminases belonging to phages that use a different packaging strategy. Gene products connected by red lines have an E-value of less than 1e-50. Gene products connected by blue lines share more than 32.5 % identity Conclusions Our modifications to Phamerator combined with new documentation for setting up custom databases and troubleshooting errors make this powerful software widely available and user-friendly. We plan to release additional updates to Phamerator that will add new features and resolve persistent problems, including: display of pham circle relationships using parameters identical to those used to build phamilies, display of pham tooltips when the map alignment is changed, display of pham circles when no phages are assigned to the singleton cluster, and display of phage tRNAs on the linear genome map. Using the techniques we described, high-throughput sequencing data can be used to determine packaging strategies and physical ends of phage chromosomes. Understanding the principles of phage genome packaging and utilizing phage genome comparison software will lead to informed decisions when publishing phage genomes, standardizing phage genome submission. Because phage genomes are being added to GenBank at a rapid rate, publishing them in a consistent manner will allow straightforward phage characterization and comparison using Phamerator and other programs. Methods Accession numbers for the 43 phage genomes and large terminase proteins used in this paper are listed in Additional file 1. We downloaded bacteriophage genomes in GenBank format from NCBI and used them to build a Phamerator database according to the instructions found in Additional file 2. Phage gene products in these genomes were compiled into a pham if they shared a BLASTP E-value of 1e-35 or less or 32.5 % identity as computed by ClustalO with at least one other gene product in the pham. The phylogenetic tree of 43 large terminase proteins was computed using the neighbor-joining method using ClustalX [13] with a bootstrap value 1000 and was displayed using Dendroscope [39]. Additional files Additional file 1: Table of phages and large terminase proteins used in Phamerator database. (XLSX 15 kb) Additional file 2: Phamerator instructions. (PDF 820 kb) Additional file 3: Pham table and cluster table generated by Phamerator. (XLSX 774 kb) Acknowledgements The authors gratefully acknowledge Dr. Steven Cresawn for writing Phamerator initially, and for providing feedback as we modified Phamerator. We appreciate the assistance of Byron Doyle and Scott Carlson of BYU Life Sciences IT for making changes to the Phamerator code and managing the GitHub repository. We also appreciate the knowledge and assistance of Dan Russell and Dr. Graham Hatfull at the University of Pittsburgh, and are grateful for the support of the HHMI SEA-PHAGES program. Funding Funding for this work was provided by the Microbiology and Molecular Biology Department at Brigham Young University and by generous donations through LDS Philanthropies. Availability of data and materials The code for the Phamerator software is available at the GitHub website, https://github.com/byuphamerator/phamerator-dev/. Our instructions to setup the Phamerator software and to create a Phamerator database is available at our website at http://phagehunters.byu.edu/Phamerator. The Nexus file containing the phylogenetic tree of the large terminases (Fig. 6) is available in the TreeBase repository at https://treebase.org/treebase-web/home.html. The custom Phamerator SQL database we constructed to generate the phamily circles of large terminases (Fig. 13) is available as an example Phamerator database, “terminasephages.sql,” on our website at http://phagehunters.byu.edu/Phamerator. Authors’ contributions BDM, JHG, and SH were responsible for the design and coordination of the research. BDM drafted the manuscript and wrote the Phamerator instructions. BDM and ATW made further modifications to the Phamerator code, edited the Phamerator instructions, gathered and analyzed data, and generated figures. ATW created the Phamerator database used in this analysis. SH and JHG edited extensively. All authors contributed to editing of the manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethical approval and consent to participate Not applicable. ==== Refs References 1. McAuliffe O Ross RP Fitzgerald GF McGrath S Van Sinderen D The new phage biology: from genomics to applications Bacteriophage: Genetics and Molecular Biology 2007 Norfolk, England Caister Academic Press 2. Jordan TC Burnett SH Carson S Caruso SM Clase K DeJong RJ Dennehy JJ Denver DR Dunbar D Elgin SC Findley AM Gissendanner CR Golebiewska UP Guild N Hartzog GA Grillo WH Hollowell GP Hughes LE Johnson A King RA Lewis LO Li W Rosenzweig F Rubin MR Saha MS Sandoz J Shaffer CD Taylor B Temple L Vazquez E A broadly implementable research course in phage discovery and genomics for first-year undergraduate students mBio 2014 5 1 e01051 01013 10.1128/mBio.01051-13 24496795 3. Cresawn SG Bogel M Day N Jacobs-Sera D Hendrix RW Hatfull GF Phamerator: a bioinformatic tool for comparative bacteriophage genomics BMC Bioinformatics 2011 12 395 10.1186/1471-2105-12-395 21991981 4. Jacobs-Sera D Marinelli LJ Bowman C Broussard GW Guerrero Bustamante C Boyle MM Petrova ZO Dedrick RM Pope WH SEA-PHAGES Program A Modlin RL Hendrix RW Hatfull GF On the nature of mycobacteriophage diversity and host preference Virology 2012 434 2 187 201 10.1016/j.virol.2012.09.026 23084079 5. Lorenz L Lins B Barrett J Montgomery A Trapani S Schindler A Christie GE Cresawn SG Temple L Genomic characterization of six novel Bacillus pumilus bacteriophages Virology 2013 444 1–2 374 383 10.1016/j.virol.2013.07.004 23906709 6. Grose JH Belnap DM Jensen JD Mathis AD Prince JT Merrill B Burnett SH Breakwell DP The genomes, proteomes and structure of three novel phages that infect the Bacillus cereus group and carry putative virulence factors J Virol 2014 88 20 11846 11860 10.1128/JVI.01364-14 25100842 7. Smith MC Hendrix RW Dedrick R Mitchell K Ko CC Russell D Bell E Gregory M Bibb MJ Pethick F Jacobs-Sera D Herron P Buttner MJ Hatfull GF Evolutionary relationships among actinophages and a putative adaptation for growth in Streptomyces spp J Bacteriol 2013 195 21 4924 4935 10.1128/JB.00618-13 23995638 8. Merrill BD Grose JH Breakwell DP Burnett SH Characterization of Paenibacillus larvae bacteriophages and their genomic relationships to Firmicute bacteriophages BMC Genomics 2014 15 1 745 10.1186/1471-2164-15-745 25174730 9. Marinelli LJ, Fitz-Gibbon S, Hayes C, Bowman C, Inkeles M, Loncaric A, Russell DA, Jacobs-Sera D, Cokus S, Pellegrini M, Kim J, Miller JF, Hatfull GF, Modlin RL. Propionibacterium acnes bacteriophages display limited genetic diversity and broad killing activity against bacterial skin isolates. mBio.2012;3(5):e00279–12. 10. Sencilo A Jacobs-Sera D Russell DA Ko CC Bowman CA Atanasova NS Osterlund E Oksanen HM Bamford DH Hatfull GF Roine E Hendrix RW Snapshot of haloarchaeal tailed virus genomes RNA Biol 2013 10 5 803 816 10.4161/rna.24045 23470522 11. Grose JH Casjens SR Understanding the enormous diversity of bacteriophages: the tailed phages that infect the bacterial family Enterobacteriaceae Virology 2014 468–470 421 443 10.1016/j.virol.2014.08.024 25240328 12. Benson DA Clark K Karsch-Mizrachi I Lipman DJ Ostell J Sayers EW GenBank Nucleic Acids Res 2014 42 Database issue D32 D37 10.1093/nar/gkt1030 24217914 13. Larkin MA Blackshields G Brown NP Chenna R McGettigan PA McWilliam H Valentin F Wallace IM Wilm A Lopez R Thompson JD Gibson TJ Higgins DG Clustal W and Clustal X version 2.0. Bioinformatics 2007 23 21 2947 2948 10.1093/bioinformatics/btm404 17846036 14. Sievers F Wilm A Dineen D Gibson TJ Karplus K Li WZ Lopez R McWilliam H Remmert M Soding J Thompson JD Higgins DG Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega Mol Syst Biol 2011 7 539 10.1038/msb.2011.75 21988835 15. Altschul SF Gish W Miller W Myers EW Lipman DJ Basic local alignment search tool J Mol Biol 1990 215 3 403 410 10.1016/S0022-2836(05)80360-2 2231712 16. Hatfull GF Jacobs-Sera D Lawrence JG Pope WH Russell DA Ko CC Weber RJ Patel MC Germane KL Edgar RH Hoyte NN Bowman CA Tantoco AT Paladin EC Myers MS Smith AL Grace MS Pham TT O’Brien MB Vogelsberger AM Hryckowian AJ Wynalek JL Donis-Keller H Bogel MW Peebles CL Cresawn SG Hendrix RW Comparative genomic analysis of 60 Mycobacteriophage genomes: genome clustering, gene acquisition, and gene size J Mol Biol 2010 397 1 119 143 10.1016/j.jmb.2010.01.011 20064525 17. Grose JH Jensen GL Burnett SH Breakwell DP Genomic comparison of 93 Bacillus phages reveals 12 clusters, 14 singletons and remarkable diversity BMC Genomics 2014 15 1 855 10.1186/1471-2164-15-855 25280881 18. King AMQ, Adams MJ, Carstens EB, Lefkowitz EJ. Virus taxonomy: Classification and nomenclature of viruses: Ninth report of the International Committee on Taxonomy of Viruses. London: Academic Press; 2012. 19. Lamine JG, DeJong RJ, Nelesen SM. PhamDB: a web-based application for building Phamerator databases. Bioinformatics. 2016;32(13):2026–8. 20. Hauser M Mayer CE Söding J kClust: fast and sensitive clustering of large protein sequence databases BMC Bioinformatics 2013 14 1 1 12 10.1186/1471-2105-14-248 23323762 21. Marchler-Bauer A Zheng CJ Chitsaz F Derbyshire MK Geer LY Geer RC Gonzales NR Gwadz M Hurwitz DI Lanczycki CJ Lu F Lu SN Marchler GH Song JS Thanki N Yamashita RA Zhang DC Bryant SH CDD: conserved domains and protein three-dimensional structure Nucleic Acids Res 2013 41 D1 D348 D352 10.1093/nar/gks1243 23197659 22. Casjens SR Gilcrease EB Determining DNA packaging strategy by analysis of the termini of the chromosomes in tailed-bacteriophage virions Methods Mol Biol 2009 502 91 111 10.1007/978-1-60327-565-1_7 19082553 23. Li S Fan H An X Fan H Jiang H Chen Y Tong Y Scrutinizing virus genome termini by high-throughput sequencing PLoS One 2014 9 1 e85806 10.1371/journal.pone.0085806 24465717 24. Darling ACE Mau B Blattner FR Perna NT Mauve: multiple alignment of conserved genomic sequence with rearrangements Genome Res 2004 14 7 1394 1403 10.1101/gr.2289704 15231754 25. Ritz MP, Perl AL, Colquhoun JM, Chamakura KR, Kuty Everett GF: Complete genome of Bacillus subtilis myophage CampHawk. Genome Announc.2013;1(6):e00984–13. 26. DeCrescenzo AJ, Ritter MA, Chamakura KR, Kuty Everett GF. Complete genome of Bacillus megaterium siphophage Slash. Genome Announc.2013;1(6):e00862–13. 27. Chung Y-B Nardone C Hinkle DC Bacteriophage T7 DNA packaging J Mol Biol 1990 216 4 939 948 10.1016/S0022-2836(99)80012-6 2266564 28. Zhang X Studier FW Multiple Roles of T7 RNA Polymerase and T7 Lysozyme During Bacteriophage T7 Infection J Mol Biol 2004 340 4 707 730 10.1016/j.jmb.2004.05.006 15223315 29. Dunn JJ Studier FW Gottesman M Complete nucleotide sequence of bacteriophage T7 DNA and the locations of T7 genetic elements J Mol Biol 1983 166 4 477 535 10.1016/S0022-2836(83)80282-4 6864790 30. Gordon D Green P Consed: a graphical editor for next-generation sequencing Bioinformatics 2013 29 22 2936 2937 10.1093/bioinformatics/btt515 23995391 31. Adams MB Hayden M Casjens S On the sequential packaging of bacteriophage P22 DNA J Virol 1983 46 2 673 677 6842684 32. Dorscht J Klumpp J Bielmann R Schmelcher M Born Y Zimmer M Calendar R Loessner MJ Comparative genome analysis of Listeria bacteriophages reveals extensive mosaicism, programmed translational frameshifting, and a novel prophage insertion site J Bacteriol 2009 191 23 7206 7215 10.1128/JB.01041-09 19783628 33. Fouts DE Rasko DA Cer RZ Jiang LX Fedorova NB Shvartsbeyn A Vamathevan JJ Tallon L Althoff R Arbogast TS Fadrosh DW Read TD Gill SR Sequencing Bacillus anthracis typing phages Gamma and Cherry reveals a common ancestry J Bacteriol 2006 188 9 3402 3408 10.1128/JB.188.9.3402-3408.2006 16621835 34. Casjens SR Gilcrease EB Winn-Stapley DA Schicklmaier P Schmieger H Pedulla ML Ford ME Houtz JM Hatfull GF Hendrix RW The generalized transducing Salmonella bacteriophage ES18: complete genome sequence and DNA packaging strategy J Bacteriol 2005 187 3 1091 1104 10.1128/JB.187.3.1091-1104.2005 15659686 35. The GenBank Submissions Handbook [http://www.ncbi.nlm.nih.gov/books/NBK51157/]. Accessed 19 Aug 2016. 36. Harshey RM The Mu story: how a maverick phage moved the field forward Mob DNA 2012 3 1 21 10.1186/1759-8753-3-21 23217166 37. Harshey RM Bukhari AI Infecting bacteriophage Mu DNA forms a circular DNA-protein complex J Mol Biol 1983 167 2 427 441 10.1016/S0022-2836(83)80343-X 6306260 38. Ortin J Vinuela E Salas M DNA-protein complex in circular DNA from phage phi29 Nature New Biol 1971 234 52 275 10.1038/newbio234275a0 5002464 39. Huson DH Scornavacca C Dendroscope 3: an interactive tool for rooted phylogenetic trees and networks Syst Biol 2012 61 6 1061 1067 10.1093/sysbio/sys062 22780991 40. Tamura K Stecher G Peterson D Filipski A Kumar S MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol Biol Evol 2013 30 12 2725 2729 10.1093/molbev/mst197 24132122 41. Bravo A Alonso JC Trautner TA Functional analysis of the Bacillus subtilis bacteriophage SPP1 pac site Nucleic Acids Res 1990 18 10 2881 2886 10.1093/nar/18.10.2881 2161515 42. Chai SH Kruft V Alonso JC Analysis of the Bacillus subtilis bacteriophages SPP1 and SF6 gene 1 product: a protein involved in the initiation of headful packaging Virology 1994 202 2 930 939 10.1006/viro.1994.1415 8030254

PMC005xxxxxx/PMC5000460.txt

==== Front Malar JMalar. JMalaria Journal1475-2875BioMed Central London 149010.1186/s12936-016-1490-4ResearchSelection of N86F184D1246 haplotype of Pfmrd1 gene by artemether–lumefantrine drug pressure on Plasmodium falciparum populations in Senegal http://orcid.org/0000-0001-5481-8623Mbaye Aminata aminatambaye155@gmail.com 1Dieye Baba dieyebaba2004@yahoo.fr 1Ndiaye Yaye D. ydndiaye@gmail.com 1Bei Amy K. amy.bei@gmail.com 12Muna Affara maffara@mrc.gm 4Deme Awa B. deme.awa@gmail.com 1Yade Mamadou S. borombakh66@gmail.com 1Diongue Khadim khadimase@gmail.com 1Gaye Amy amygaye08@live.fr 1Ndiaye Ibrahima M. pee72003@hotmail.com 1Ndiaye Tolla ndiayetola@gmail.com 1Sy Mouhamad symouhamad92@gmail.com 1Diallo Mamadou A. mad1fa@hotmail.com 1Badiane Aida S. asbadiane@gmail.com 1Ndiaye Mouhamadou mouhamadou.ndiaye@ucad.edu.sn 1Seck Mame C. mcseck203@yahoo.fr 1Sy Ngayo ngayosy50@hotmail.com 1Koita Ousmane okoita@icermali.org 5Krogstad Donald J. donkrogstad@gmail.com 3Nwakanma Davis dnwakanma@mrc.gm 4Ndiaye Daouda dndiaye23@gmail.com 121 Laboratory of Parasitology/Mycology HALD, Cheikh Anta Diop University of Dakar, PO Box 5005, Dakar, Senegal 2 Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, MA USA 3 Tulane University, New Orleans, LA USA 4 Malaria Research Centre, Serrekunda, Gambia 5 University of Bamako, Bamako, Mali 25 8 2016 25 8 2016 2016 15 1 4339 6 2016 16 8 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The use of artemisinin as a monotherapy resulted in the emergence of artemisinin resistance in 2005 in Southeast Asia. Monitoring of artemisinin combination therapy (ACT) is critical in order to detect and prevent the spread of resistance in endemic areas. Ex vivo studies and genotyping of molecular markers of resistance can be used as part of this routine monitoring strategy. One gene that has been associated in some ACT partner drug resistance is the Plasmodium falciparum multidrug resistance protein 1 (pfmdr1) gene. The purpose of this study was to assess the drug susceptibility of P. falciparum populations from Thiès, Senegal by ex vivo assay and typing molecular markers of resistance to drug components of ACT currently used for treatment. Methods The ex vivo susceptibility of 170 P. falciparum isolates to chloroquine, amodiaquine, lumefantrine, artesunate, and artemether was determined using the DAPI ex vivo assay. The high resolution melting technique was used to genotype the pfmdr1 gene at codons 86, 184 and 1246. Results A significant decrease in IC50 values was observed between 2012 and 2013: from 13.84 to 6.484 for amodiaquine, 173.4 to 113.2 for lumefantrine, and 39.72 to 18.29 for chloroquine, respectively. Increase of the wild haplotype NYD and the decrease of the mutant haplotype NFD (79 and 62.26 %) was also observed. A correlation was observed between the wild type allele Y184 in pfmdr1 and higher IC50 for all drugs, except amodiaquine. Conclusion This study has shown an increase in sensitivity over the span of two transmission seasons, marked by an increase in the WT alleles at pfmdr1. Continuous the monitoring of the ACT used for treatment of uncomplicated malaria will be helpful. Keywords Plasmodium falciparumHaplotypeArtemether–lumefantrinepfmdr1SenegalInternational Center of Excellence in Malaria Research West AfricaU19AI089696Ndiaye Daouda issue-copyright-statement© The Author(s) 2016 ==== Body Background Among the five species of Plasmodium causing human malaria, Plasmodium falciparum is the deadliest. The latest World Malaria Report showed that of the 214 million cases of malaria recorded in 2014, 88 % were registered in sub-Saharan Africa where most of cases were caused by P. falciparum [1, 2]. In the late 1950s, resistance of P. falciparum to chloroquine (CQ) emerged in South America and Southeast Asia [3]; since then, resistance has spread rapidly around the world and in Africa the first cases were reported in 1978 [4]. The introduction of other anti-malarial drugs [sulfadoxine-pyrimethamine (SP), mefloquine (MQ), etc.] has led to the emergence of strains of P. falciparum that are resistant to multiple drugs in some endemic areas [5]. As a result, since April 2001, the World Health Organization (WHO) has recommended the use of artemisinin-based combination therapy (ACT) in countries where P. falciparum is resistant to CQ, SP, and amodiaquine (AMQ), to avoid early emergence of resistance to these molecules [6]. Despite these efforts, cases of resistance to artemisinin (ART) have emerged in Cambodia and in other regions of Southeast Asia [7]. Indeed, in these countries, ART was used as monotherapy for uncomplicated falciparum malaria. Monitoring the sensitivity of P. falciparum to ACT becomes essential for therapeutic management of malaria. Such monitoring can be done by various methods, including in vivo efficacy studies, in vivo clearance time assays [8], in vitro chemo-sensitivity to anti-malarial drugs (RSA), and genotyping of pfk13 molecular markers of ART resistance [9]. For the P. falciparum multidrug-resistant protein 1 (pfmdr1) gene, several single nucleotide polymorphisms were described, but the more common were N86Y, Y184F, S1034C, N1042D, and D1246Y. Studies have shown an association of pfmdr1 gene, specifically the codon 86, and a decrease of sensitivity to AMQ and artesunate (ARS) [10, 11]. Studies have also shown the 86Y and 1246Y mutations are strongly related to the reduction of in vivo sensitivity to artesunate-amodiaquine combination (ASAQ). Also, the N86 and D1246 alleles are related to a decrease of susceptibility to artemether–lumefantrine combination (AL) [12–14]. Moreover, the haplotype N86F184D1246 is selected by a high drug pressure of AL [15, 16], while 1034C, 1042D and 1246Y mutations have been reported to confer resistance against quinine (QN) and increased susceptibility to MQ, halofantrine (HF) and ART [17, 18]. In Senegal, ACT has been implemented as first-line treatment for uncomplicated falciparum malaria since 2006, following WHO recommendation [19]. AL and ASAQ combination are used for first-line treatment of uncomplicated P. falciparum malaria [2]. Ex vivo studies have been conducted to study the sensitivity of current anti-malarial drugs used against circulating P. falciparum populations in Senegal [20–23]. This work aims to study the consequences of use of ACT (ASAQ and AL) for uncomplicated malaria treatment in Senegal by using the ex vivo sensitivity to ARS, AMQ, artemether (AMT) and lumefantrine (LUM) of P. falciparum isolates from Thiès collected during the transmission period of malaria combined to the pfmdr1 gene polymorphism at codon N86Y, N184F and D1246Y. Methods Study sites Patient recruitment took place during the seasonal malaria period (from September to December) in Section de Lutte Anti-Parasitaire (SLAP) clinic in Thiès in 2012 and 2013. This centre has the privilege to control malaria treatment in Thiès region. The epidemiological profile of this region is characterized as sahelian with a short, seasonal transmission period, generally fewer than 4 months after the rainy season ends. The vectors found are Anopheles arabiensis and Anopheles gambiae and the entomological inoculation rate is generally low and varies from 1 year to another (0–20 infectious bites/person/year). The region of Thiès is located at 70 km from Dakar and malaria incidence in this region ranges between five and 15 per 1000 inhabitants [21, 24]. Individuals who presented at the health centre with malaria symptoms were tested by both microscopy and rapid diagnostic test (when available). The selected patients, aged from 5 to 20 years, had uncomplicated malaria due to P. falciparum with a parasitaemia higher than 15,000 µl. Exclusion criteria included individuals who had clinical features of severe malaria or who had a history of taking anti-malarial treatment prior to the visit. Informed consent or assent of the patient and their guardian (for children) was obtained before collecting the blood. The Human Subjects Committee of Tulane University and the Ethics Committee of the Senegal Ministry of Health in Dakar both approved the protocols used in these studies. The work was supported by the International Centres of Excellence for Malaria Research, (ICEMR) West Africa (U19AI089696). Blood sample collection Venous blood was collected in EDTA tubes and filter papers were collected by finger prick. Patients were treated with AMT-LUM or ARS-AMQ combination. These samples were sent to Aristide Le Dantec Hospital within 6 h of blood draw. Drugs and drug preparation AMQ hydrochloride (USP), ARS (Sigma), AMT (SIGMA), CQ diphosphate (Sigma) and LUM (USP) were used in ex vivo assays. These molecules were dissolved directly in dimethyl sulfoxide (DMSO) solvent at a concentration of 10 mM. A first dilution (1/1000) with RPMI 1640 media was done to obtain an intermediate solution. A serial dilution (1/2) was then operated to get a range of concentrations for each drug. The range of concentration varied from 100 to 0.39 nM for AMQ, 75 to 0.29 nM for ARS, 150 to 0.58 nm for AMT, 750 to 2.93 nM for CQ, and 2000 to 7.81 nM for LUM. The 96-well plates were then loaded with drugs at a final volume 20 µl per well and stored at −20 °C until use. Ex vivo assay Parasitized blood samples from the field were first centrifuged to remove the plasma, then washed two times with unsupplemented media. Samples with a parasitaemia between 0.4 and 1 % were suspended in complete media, supplemented with AB serum and Albumax II to adjust the haematocrit to 2 % before being distributed into 96-well plates preloaded with drugs. If parasitaemia was higher than 1 %, a dilution with an O+ blood sample without P. falciparum strains was done. The plates were incubated at 37 °C under the following gas conditions (1 % O2, 5 % CO2 and 94 % N2) for 48 or 72 h, until parasite re-invasion as assessed by microscopy. The ex vivo response of parasites to the different anti-malarial drugs was evaluated using the DAPI molecular probe as described previously [25]. Plates were briefly thawed, spun, and re-suspended with 100 µl (3.64 nM of DAPI concentration) of DAPI-buffer and incubated for 30 min in the dark. They were washed with the PBS before reading at excitation wavelength of 358 nm and emission wavelength of 460 nm using a Fluoroskan Ascent reader. Percent growth was calculated relative to the RPMI-only control wells for each plate. The control strain used to validate results was sensitive to CQ P. falciparum 3D7 laboratory strain from MR4. DNA extraction and genotyping The genomic DNA was extract from filter papers using the QIAmp DNA mini kit (Qiagen) following manufacturer’s instructions. The high resolution melting (HRM) technique was used for genotyping codons N86Y, Y184F and D1246Y of pfmdr1 gene and codon K76T of pfcrt using specific primers and probes, as previously described [26]. Statistical analysis All statistical analyses were performed using Graph Pad Prism software (Version 5.0). Mann–Whitney test was used to compare the distribution of IC50 s between years. For the difference of pfmdr1 polymorphism, the online Z test for two populations’ proportion was used. p value was considered significant when it was less than 0.05. Results Ex vivo susceptibility of Plasmodium falciparum parasites from Thiès Among a total of 120 and 50 samples collected, respectively, in 2012 and 2013 in Thiès, 114 and 48, respectively, were tested. The eight non-tested samples had a parasitaemia lower than 15,000 parasites/µl. Parasites’ responses to drugs at Thiès in 2012 and 2013 are listed in Table 1. Ex vivo result was validated by testing the 3D7 strain sensitive to CQ and good sensitivity was found with a significant increase. The geometric mean of IC50 values reported in 2012 and 2013 were, respectively, 13.84 and 6.484 nM (p < 0.0001) for AMQ; 173.4 and 113.2 nM (p = 0.01) for LUM; 3.322 and 3.673 nM (p = 0.34) for ARS; 39.72 and 18.29 nM (p < 0.0001) for CQ. AMT was only tested in 2013, the geometric mean found was 6.222 nM.Table 1 Ex vivo susceptibility of Plasmodium falciparum isolates from Thiès in 2012 and 2013 Drug 2012 2013 p value 3D7 IC50 (nM) Mean with 95 % IC (nM) Range (nM) 3D7 IC50 (nM) Mean with 95 % IC (nM) Range (nM) Min Max Min Max AMQ 5.488 13.84 (11.84–16.13) 0.7425 63.13 3.321 6.484 (5.208–8.071) 1.925 43.85 <0.0001 LUM 417.5 173.4 (142.0–211.8) 21.26 981.1 164.3 113.2 (85.9–149.1) 17.05 414 0.01 ARS 17.88 3.322 (2.852–3.869) 0.5222 10.16 2.805 3.673 (3.046–4.428) 1.22 18.54 0.34 AMT – – – 7 6.222 (5.013–7.724) 1.188 33.6 – CQ 17.58 39.72 (30.92–51.02) 2.850 402.9 9.287 18.29 (29.07–87.59) 6.474 384.1 <0.0001 The chloroquine-sensitive strain 3D7 was tested and gave adequate results <100 nM [44]. The difference of values for each molecule for 3D7 was significant excepted for artesunate (p = 0.35). p value indicates the significance of the difference of geometric means of the same molecule between 2012 and 2013 IC50 50 % inhibitory concentration, IC confidence interval, Mean geometric mean, min minimum, max maximum Polymorphism assessment of pfmdr1 and pfcrt genes and haplotype of mdr1 gene analysis The 120 and 50 samples collected in Thiès were successfully genotyped. The majority of isolates had the wild type alleles N and K at codon 86 (pfmdr1) and 76 (pfcrt) with respectively 96 and 78 % in 2012 and 98 and 80 % in 2013. Mixed allele was found in 2012 in 1 % for N86Y and 2 % for K76T of proportion. The mutant allele for these codons was in proportion of 3 and 2 % in 2012 and 2 and 0 % in 2013. Concerning the 184 codon, the mutant allele F predominates both in the 2 years with 75 % for F allele (vs. 20 % for Y allele) in 2012 and 60 % for F allele (vs. 34 % for Y allele) in 2013 with a significant difference (p = 0.029). The presence of mixed allele in Thiès isolates (3 % in 2012 and 6 % in 2013) for this codon was noted. Finally, for 1246 codon, the only allele found was the wild type D1246 (Table 2).Table 2 Prevalence of single nucleotide polymorphism et haplotypes of pfmdr1 gene of isolates from Thiès pfmdr1 genotype 2012 (120) 2013 (N = 50) p value N86 97 % (84/87) 98 % (49/50) 0.63 86Y 2 % (2/87) 2 % (1/50) 0.1151 MIXTE (N86Y) 1 % (1/87) 0 % 0.44 Y184 20 % (22/119) 34 % (17/50) 0.029 184F 78 % (93/119) 60 % (30/50) 0.0155 MIXTE (Y184F) 3 % (4/119) 6 % (3/50) 0.42 D1246 100 % (119/119) 100 % (50/50) – K76 78 % (47/60) 80 % (40/50) 0.83 76T 20 % (12/60) 20 % (10/50) 1 MIXTE 2 % (1/60) 0 % 0.36 NYD 18 % (18/102) 35.85 % (18/50) 0.012 NFD 79 % (81/102) 62.26 % (31/50) 0.022 YFD 3 % (3/102) 1.89 % (1/50) 0.72 Samples containing single allele in the codons N86Y and Y184F were used to determine prevalence of the circulating pfmdr1 to reduce ambiguity from the mixed samples. The haplotypes N86Y184D1246, N86F184D1246 and Y86F184D1246 were found both in 2012 and 2013 (Table 2). A high prevalence of N86F184D1246 haplotype was found 79 % in 2012 and 62.26 % in 2013 with a significant decrease in 2013. Both the wildtype Y184 and the combined N86Y184D1246 are selected in 2013. Genotype and phenotype analysis An association analysis between 184F mutation and the ex vivo susceptibility to LUM, AMT, CQ, AMQ, and ARS was performed (Table 3). High geometric means of IC50 for LUM were found with samples having the wild allele Y184 in 2012 isolates (p = 0.0008). For the other compounds, no difference between the geometric mean of IC50 of isolates with the 184F allele and that of GM of IC50 s with the wild allele was see.Table 3 Association between the mutation 184F and the geometric means of IC50 values for each drugs Drugs Year IC50 geometric mean (nM) Y184 184F p value Amodiaquine 2012 10.51 (19) 15.02 (69) 0.0671 2013 5.1 (16) 6.277 (24) 0.1992 Chloroquine 2012 117.8 (20) 104 (89) 0.1094 2013 24.18 (15) 28.10 (27) 0.1036 Lumefantrine 2012 493.6 (15) 179.2 (69) 0.0008 2013 155.9 (15) 68.13 (23) 0.1277 Artesunate 2012 4.034 (12) 3.041 (60) 0.3808 2013 3.365 (17) 3.693 (25) 0.5729 Artemether 2012 – – – 2013 5.997 (17) 5.936 (25) 0.9387 The numbers in parentheses indicate the number of samples with wild or mutant allele Discussion Plasmodium falciparum resistance exists to all first-line anti-malarial drugs, used in both the past and present, alarmingly, even artemisinin derivatives. This resistance has been confirmed in five countries in Southeast Asia (Cambodia, The Lao People’s Democratic Republic, Myanmar, Thailand, Viet Nam) [27]. Monitoring ACT resistance worldwide is absolutely essential, as there is no other alternative drug treatment available [28]. In Senegal, ACT has been first-line treatment since 2006, and currently, AL and ASAQ are recommended as first-line treatment of uncomplicated malaria, while dihydroartemisinin-piperaquine is used as second-line [2, 19]. Both combinations (AL and ASAQ) are effective event for child and adult [29]. However, AL is used more frequently because it is better tolerated [30]. ACT treatment failure of 0.9 % for AL was observed between 2004 and 2014 and it was 0.25 % for ASAQ treatment [2]. Previous studies showed that AL, DHAPQ and ASAQ are highly effective for the treatment of uncomplicated P. falciparum malaria in Senegal [31, 32]. In Thiès (2012–2013) three recrudescent samples were observed and these did not reveal mutation in the K13 propeller region (Dieye et al. pers. comm.). The DAPI ex vivo test, that has been shown to be an excellent technique to study the chemo-sensitivity of P. falciparum [20, 25], was used to measure the ex vivo sensitivity of isolates from Thiès in 2012 and 2013 to AMQ, CQ, LUM, ARS, and AMT. Currently, novel phenotype assays (RSA) and a new molecular maker of mutations in the kelch 13 (K13) propeller region [9], to detect resistance of ART derivatives, are used and recommended [33–35]. However, in this study, the data presented was manipulated in the seasonal period of 2012 and 2013, before the RSA recommendation in December 2013. Kelch 13 sequencing was performed and no mutations known to confer resistance were observed in these samples (Deme & Ndiaye, pers. comm). To validate the result, 3D7 chloroquine sensitive strain was used. Good sensitivity (<00 nM) was found for chloroquine in both years. A significant increase of sensitivity was observed for 3D7 and isolate from Thiès and this, for all molecules except artesunate, which means the differences in drugs between years could be for technical reasons rather than biological ones. ARS and AMT exert their actions through formation of dihydroartemisinin in vivo [36]. This metabolite is often present in higher concentrations than the parent drugs. However, studies show that AMT and ARS have potent parasite killing activity in vitro [37]. This id why AMT and ARS were tested separately. Also, five single nucleotide polymorphisms in the pfmdr1 gene were associated to anti-malarial drug resistance. Studies show that the pfmdr1 gene polymorphism at codons N86Y, Y184F and D1246Y is mainly linked to AL or ASAQ drug pressure [15, 38, 39]. These facts justify the choice of the three codons of pfmdr1 gene. The resistance to AMQ has always been linked to the mutation at the 86 position of the pfmdr1 gene [10, 11]. Studies show that high ASAQ pressure on the parasite population can select Y86Y184Y1246 haplotypes [15]. The existence of cross resistance, strains resistance to both of drugs together, between AMQ and CQ was detected [40]. The result obtained in Thiès, combined with those obtained in the same region in 2010 [25] and in 2013 [20] reveal that the ex vivo sensitivity of the parasite population to AMQ and CQ has increased between 2011 and 2013. Also, as previously described in Thiès [20], a decrease of the mutation at the 86 position was observed. Studies show that the prevalence of 86Y allele increased between 2000 and 2003 on parasites from Pikine (Dakar). However, a decrease was noted between 2003 and 2009 in this locality [41]. These results reveal that sensitivity of parasite to AMQ increased drastically after the abandonment of chloroquine in 2003. The same tendency was observed in Thiès. Also, for the Pfmdr1 gene, the haplotype Y86Y184Y1246 was not found. This means that the drugs ARS and AMQ are effective on the population of P. falciparum from Thiès and any drug pressure was noted. Increase of wild-type allele K76 was also found between 2011 and 2013 in Thiès. The study of Ndiaye et al. [42] also showed this increase in the central (70.5 % in 2009 and 74.8 % in 2010) and in southern (65.4 % in 2010 and 71.0 % in 2011) Senegal. The combination AMT-LUM has been used as first-line treatment for uncomplicated malaria in Senegal since 2006 [43]. The resistance to LUM has been linked to the increase of copy number in the pfmdr1 gene and the selection of the N86 allele [10]. However, studies have shown a selection of the N86F184D1246 haplotype by a high pressure of AL [12, 16]. The high prevalence of wild allele N86, mutant allele 184F and N86F184D1246 haplotype was also noted in this study. In Thiès, Van Tyne et al. [20] demonstrated an increase of the 184F mutation between 2008 and 2011. However, a tendency to a decrease of this mutation between 2011 and 2013 was noted. This tendency can be explained by the use of the ASAQ combination in SLAP (health centre) after the unavailability of AL. This observation means that a pressure is exerted by AMT-LUM combination on the parasite population from Thiès and then this pressure decreases if the drug (AL) is not used. Conclusion The study of ex vivo sensitivity of P. falciparum to anti-malarial drugs is a powerful tool to understand parasite phenotypes and to orient the policy of monitoring therapeutic management of malaria. The results of this study show a good sensitivity of P. falciparum populations to amodiaquine, artesunate, artemether and lumefantrine. So, the high prevalence of N86F184D1246 haplotype selected by AL pressure was found. Expanded in vivo surveillance of ACT and continued monitoring of artemisinin drug resistance by using new techniques, such as the ex vivo RSA and kelch13 genotyping, should be a priority. Authors’ contributions AM, BD, YDN, ABD, MSY, AG, IMN, TN, ASB, MAD, MN, MCS, MA and AKB carried out the experiments and collected data. NS, DN, DJK, OK, DN conceived and designed the study. AM and AKB analysed the data. AM, BD, KD, ABD and YDN wrote the manuscript. All authors read and approved the final manuscript. Acknowledgements We acknowledge the International Center for Excellence in Malaria Research (ICEMR) project. We thank Cyrille Diedhiou, Nasserdine Papa Nze, Dior Diop, Younouss Diedhiou, Lamine Ndiaye, Amadou Mactar Mbaye, the SLAP patients and staff for their contribution in this study. Competing interests The authors declare that they have no competing interests. Consent for publication The participants in this study are consent for publication. Ethics approval and consent to participate The Human Subjects Committee of Tulane University and the Ethics Committee of the Senegal Ministry of Health in Dakar both approved the protocols used in these studies. Funding The work was supported by the International Centers of Excellence for Malaria Research, (ICEMR) West Africa (U19AI089696). ==== Refs References 1. WHO. Q&A on artemisinin resistance. Geneva, World Health Organization. 2013 http://who.int/malaria/media/artemisinin_resistance_qa/en/. 2. WHO. World Malaria Report. Geneva, World Health Organization. 2015. http://apps.who.int/iris/bitstream/10665/200018/1/9789241565158_eng.pdf. 3. Blount RE Management of chloroquine resistant falciparum malaria Trans Am Clin Climatol Assoc 1967 78 196 204 5339079 4. Kihamia CM Gill HS Chloroquine-resistant falciparum malaria in semi-immune native African Tanzanians Lancet 1982 2 43 10.1016/S0140-6736(82)91175-8 6123770 5. Anderson TJ Roper C The origins and spread of antimalarial drug resistance: lessons for policy makers Acta Trop 2005 94 269 280 10.1016/j.actatropica.2005.04.010 15878153 6. WHO. Briefing on malaria treatment guidelines and artemisinin monotherapies. Geneva, World Health Organization. 2006. http://apps.who.int/malaria/docs/Meeting_briefing19April.pdf. 7. Noedl H Se Y Schaecher K Smith BL Socheat D Fukuda MM Evidence of artemisinin-resistant malaria in western Cambodia N Engl J Med 2008 359 2619 2620 10.1056/NEJMc0805011 19064625 8. WHO Global report on antimalarial drug efficacy and drug resistance: 2000–2010 2010 Geneva World Health Organization 9. Ariey F Witkowski B Amaratunga C Beghain J Langlois AC Khim N Molecular marker of artemisinin-resistant Plasmodium falciparum malaria Nature 2014 505 50 55 10.1038/nature12876 24352242 10. Pradines B, Dormoi J, Briolant S, Bogreau H, Rogier C. La résistance aux antipaludiques. Revue Francophone des Laboratoires. 2010; 422. 11. Eyase FL Akala HM Ingasia L Cheruiyot A Omondi A Okudo C The role of Pfmdr1 and Pfcrt in changing chloroquine, amodiaquine, mefloquine and lumefantrine susceptibility in Western-Kenya P. falciparum samples during 2008–2011 PLoS One 2013 8 e64299 10.1371/journal.pone.0064299 23675533 12. Kavishe RA Paulo P Kaaya RD Kalinga A Van Zwetselaar M Chilongola J Surveillance of artemether-lumefantrine associated Plasmodium falciparum multidrug resistance protein-1 gene polymorphisms in Tanzania Malar J 2014 13 264 10.1186/1475-2875-13-264 25007802 13. Ashley E Dhorda M Fairhurst RM Amaratunga C Lim P Suon S Sreng S Spread of artemisinin resistance in Plasmodium falciparum malaria N Engl J Med 2014 371 411 423 10.1056/NEJMoa1314981 25075834 14. Sisowath C Petersen I Veiga MI Mårtensson A Björkman A Fidock DA Gil JP In vivo selection of Plasmodium falciparum parasites carrying the chloroquine-susceptible pfcrt K76 allele after treatment with artemether–lumefantrine in Africa J Infect Dis 2009 199 750 757 10.1086/596738 19210165 15. Baliraine FN Rosenthal PJ Prolonged selection of pfmdr1 polymorphisms after treatment of falciparum malaria with artemether-lumefantrine in Uganda J Infect Dis 2011 204 1120 1124 10.1093/infdis/jir486 21881128 16. Happi CT Gbotosho GO Folarin OA Sowunmi A Hudson T O’Neil M Selection of Plasmodium falciparum multidrug resistance gene 1 alleles in asexual stages and gametocytes by artemether–lumefantrine in Nigerian children with uncomplicated falciparum malaria Antimicrob Agents Chemother 2009 53 888 895 10.1128/AAC.00968-08 19075074 17. Humphreys GS Merinopoulos I Ahmed J Whitty CJM Mutabingwa TK Sutherland CJ Amodiaquine and artemether–lumefantrine select distinct alleles of the Plasmodium falciparum mdr1 gene in Tanzanian children treated for uncomplicated malaria Antimicrob Agents Chemother 2007 51 991 997 10.1128/AAC.00875-06 17194834 18. Jacqueline K Lekostaj L Amoah E Roepe PD A single S1034C mutation confers altered drug sensitivity to PfMDR1 ATPase activity that is characteristic of the 7G8 isoform Mol Biochem Parasitol 2008 157 107 111 10.1016/j.molbiopara.2007.09.008 18006157 19. PNLP. Directives nationales de prevention et de prise en charge du paludisme. Dakar. 2013-24. http://www.asgosenegal.org/docs/DirectivesPECVFF.pdf. 20. Van Tyne D Dieye B Valim C Daniels RF Sène PD Lukens AK Changes in drug sensitivity and anti-malarial drug resistance mutations over time among Plasmodium falciparum parasites in Senegal Malar J 2013 12 441 10.1186/1475-2875-12-441 24314037 21. Ndiaye D Dieye B Ndiaye YD Tyne DV Daniels R Bei AK Polymorphism in dhfr/dhps genes, parasite density and ex vivo response to pyrimethamine in Plasmodium falciparum malaria parasites in Thies, Senegal Int J Parasitol Drugs Drug Resist 2013 3 135 142 10.1016/j.ijpddr.2013.07.001 24533303 22. Fall B Camara C Fall M Nakoulima A Dionne P Diatta B Plasmodium falciparum susceptibility to standard and potential anti-malarial drugs in Dakar, Senegal, during the 2013–2014 malaria season Malar J. 2015 14 60 10.1186/s12936-015-0589-3 25849097 23. PNLP. Plan Stratégique National 2011–2015. Dakar. 2010-129. http://www.africanchildforum.org/clr/policypercountry/senegal/senegal_malaria_2011-2015_fr.pdf. 24. PNLP. Bulletin épidémiologique annuel du paludisme au Senegal. Dakar. 2014-24. http://www.pnlp.sn/telechargements/Rapports/Bulletin-Epidemiologique-Annuel-2014-du-Paludisme-au-Senegal.pdf. 25. Ndiaye D Patel V Demas A LeRoux M Ndir O Mboup S A non-radioactive DAPI-based high-throughput in vitro assay to assess Plasmodium falciparum responsiveness to antimalarials—increased sensitivity of P. falciparum to chloroquine in Senegal Am J Trop Med Hyg 2010 82 228 230 10.4269/ajtmh.2010.09-0470 20133997 26. Daniels R Ndiaye D Wall M McKinney J Séne PD Sabeti PC Rapid, field-deployable method for genotyping and discovery of single-nucleotide polymorphisms associated with drug resistance in Plasmodium falciparum Antimicrob Agents Chemother 2012 56 2976 2986 10.1128/AAC.05737-11 22430961 27. WHO Status report on artemisinin resistance 2014 Geneva World Health Organization 28. Ménard D Ariey F Mercereau-Puijalon O Étude de la résistance de Plasmodium falciparum aux antipaludiques au sein du réseau international des Instituts Pasteur Med Sci (Paris) 2013 29 647 655 10.1051/medsci/2013296020 23859522 29. Ndiaye JL Randrianarivelojosia M Sagara I Brasseur P Ndiaye I Faye B Randomized, multicentre assessment of the efficacy and safety of ASAQ–a fixed-dose artesunate-amodiaquine combination therapy in the treatment of uncomplicated Plasmodium falciparum malaria Malar J. 2009 8 125 10.1186/1475-2875-8-125 19505304 30. Maiteki-Sebuguzi C Jagannathan P Yau VM Clark TD Njama-Meya D Safety and tolerability of combination antimalarial therapies for uncomplicated falciparum malaria in Ugandan children Malar J 2008 7 106 10.1186/1475-2875-7-106 18547415 31. Sylla K Abiola A Tine R Faye B Sow D Ndiaye JL Monitoring the efficacy and safety of three artemisinin-based combinations therapies in Senegal: Results from two years surveillance BMC Infect Dis 2013 13 598 10.1186/1471-2334-13-598 24354627 32. Faye B Offianan AT Ndiaye JL Tine RC Touré W Djoman K Efficacy and tolerability of artesunate-amodiaquine (Camoquin plus) versus artemether-lumefantrine (Coartem) against uncomplicated Plasmodium falciparum malaria: multisite trial in Senegal and Ivory Coast Trop Med Int Health 2010 15 608 613 20214761 33. Witkowski B Amaratunga C Khim N Sreng S Chim P Kim S Novel phenotypic assays for the detection of artemisinin-resistant Plasmodium falciparum malaria in Cambodia: in vitro and ex vivo drug-response studies Lancet Infect Dis 2013 13 1043 1049 10.1016/S1473-3099(13)70252-4 24035558 34. Fandeur T. Laboratoire National de Référence pour la surveillance des Chimiorésistances du Paludisme au Niger. 2011; 1–19. 35. Witkowski B Khim N Chim P Kim S Ke S Kloeung N Reduced artemisinin susceptibility of Plasmodium falciparum ring stages in Western Cambodia Antimicrob Agents Chemother 2013 57 914 923 10.1128/AAC.01868-12 23208708 36. Brewer TG Grate SJ Peggins JO Weina PJ Petras JM Levine BS Fatal neurotoxicity of arteether and artemether Am J Trop Med Hyg 1994 51 251 259 7943542 37. Huang X Aslanian RG Case studies in modern drug discovery and development 2012 London Wiley 38. Achieng AO Muiruri P Ingasia LA Opot BH Juma DW Yeda R Temporal trends in prevalence of Plasmodium falciparum molecular markers selected for by artemether-lumefantrine treatment in pre-ACT and post-ACT parasites in Western Kenya Int J Parasitol Drugs Drug Resist. 2015 5 92 99 10.1016/j.ijpddr.2015.05.005 26236581 39. Sisowath C Ferreira PE Bustamante LY Dahlström S Mårtensson A Björkman A The role of pfmdr1 in Plasmodium falciparum tolerance to artemether-lumefantrine in Africa Trop Med Int Health. 2007 12 736 742 10.1111/j.1365-3156.2007.01843.x 17550470 40. Trape JF Tall A Sokhna C Ly AB Diagne N Ndiath O The rise and fall of malaria in a West African rural community, Dielmo, Senegal, from 1990 to 2012: a 22 year longitudinal study Lancet Infect Dis 2014 14 476 488 10.1016/S1473-3099(14)70712-1 24813159 41. Ly O Gueye PE Deme AB Dieng T Badiane AS Ahouidi AD Evolution of the pfcrt T76 and pfmdr1 Y86 markers and chloroquine susceptibility 8 years after cessation of chloroquine use in Pikine, Senegal Parasitol Res 2012 111 1541 1546 10.1007/s00436-012-2994-7 22706959 42. Ndiaye M Faye B Tine R Ndiaye JL Lo A Abiola A Assessment of the molecular marker of Plasmodium falciparum chloroquine resistance (Pfcrt) in Senegal after several years of chloroquine withdrawal Am J Trop Med Hyg 2012 87 640 645 10.4269/ajtmh.2012.11-0709 22927495 43. Mouzin E, Thior PM, Diouf MB, Samb B. Focus sur le Senegal. Geneva, Roll Back Malaria. 2010. http://www.rollbackmalaria.org/files/files/resources/report4-fr.pdf. 44. Pradines B Tall A Parzy D Spiegel A Fusai T Hienne R In-vitro activity of pyronaridine and amodiaquine against African isolates (Senegal) of Plasmodium falciparum in comparison with standard antimalarial agents J Antimicrob Chemother 1998 42 333 339 10.1093/jac/42.3.333 9786473

PMC005xxxxxx/PMC5000461.txt

==== Front TrialsTrialsTrials1745-6215BioMed Central London 151910.1186/s13063-016-1519-6Study ProtocolComparison of active treatments for impaired glucose regulation: a Salford Royal Foundation Trust and Hitachi collaboration (CATFISH): study protocol for a randomized controlled trial Coventry Peter A. peter.coventry@york.ac.uk 1Bower Peter peter.bower@manchester.ac.uk 2Blakemore Amy 2Baker Liz 2Hann Mark mark.hann@manchester.ac.uk 4Paisley Angela angela.paisley@srft.nhs.uk 5Renwick Charlotte charlotte.renwick@york.ac.uk 1Li Jinshuo jinshuo.li@york.ac.uk 1Ugajin Atushi atsushi.ugajin@hitachi-eu.com 3Gibson Martin martin.gibson@manchester.ac.uk 51 Mental Health and Addiction Research Group, Department of Health Sciences, University of York, York, YO10 5DD UK 2 NIHR School for Primary Care Research and Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PL UK 3 Information Systems Group, Hitachi Europe Limited, London, NW1 5DH UK 4 Centre for Biostatistics and Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PL UK 5 Salford Royal NHS Foundation Trust, Salford, M6 8HD UK 26 8 2016 26 8 2016 2016 17 1 4245 4 2016 22 7 2016 © Coventry et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Diabetes is highly prevalent and contributes to significant morbidity and mortality worldwide. Behaviour change interventions that target health and lifestyle factors associated with the onset of diabetes can delay progression to diabetes, but many approaches rely on intensive one-to-one contact by specialists. Health coaching is an approach based on motivational interviewing that can potentially deliver behaviour change interventions by non-specialists at a larger scale. This trial protocol describes a randomized controlled trial (CATFISH) that tests whether a web-enhanced telephone health coaching intervention (IGR3) is more acceptable and efficient than a telephone-only health coaching intervention (IGR2) for people with prediabetes (impaired glucose regulation). Methods CATFISH is a two-parallel group, single-centre individually randomized controlled trial. Eligible participants are patients aged ≥18 years with impaired glucose regulation (HbA1c concentration between 42 and 47 mmol/mol), have access to a telephone and home internet and have been referred to an existing telephone health coaching service at Salford Royal NHS Foundation Trust, Salford, UK. Participants who give written informed consent will be randomized remotely (via a clinical trials unit) to either the existing pathway (IGR2) or the new web-enhanced pathway (IGR3) for 9 months. The primary outcome measure is patient acceptability at 9 months, determined using the Client Satisfaction Questionnaire. Secondary outcome measures at 9 months are: cost of delivery of IGR2 and IGR3, mental health, quality of life, patient activation, self-management, weight (kg), HbA1c concentration, and body mass index. All outcome measures will be analyzed on an intention-to-treat basis. A qualitative process evaluation will explore the experiences of participants and providers with a focus on understanding usability of interventions, mechanisms of behaviour change, and impact of context on delivery and user acceptability. Qualitative data will be analyzed using Framework. Discussion The CATFISH trial will provide a pragmatic assessment of whether a web-based information technology platform can enhance acceptability of a telephone health coaching intervention for people with prediabetes. The data will prove critical in understanding the role of web applications to improve engagement with evidence-based approaches to preventing diabetes. Trial registration ISRCTN16534814. Registered on 7 February 2016. Electronic supplementary material The online version of this article (doi:10.1186/s13063-016-1519-6) contains supplementary material, which is available to authorized users. Hitachi Europe Ltd.issue-copyright-statement© The Author(s) 2016 ==== Body Background Diabetes is a long-term condition characterized by hyperglycaemia in the presence of defects of insulin secretion or insulin action, or both, and is a major cause of morbidity and premature mortality globally [1]. At present, 3.4 million adults in the UK are diagnosed with diabetes, the majority with type 2 diabetes [2]. The damaging effects of uncontrolled hyperglycaemia can cause macrovascular complications (coronary artery disease, peripheral arterial disease and stroke) and microvascular complications (diabetic nephropathy [kidney disease], neuropathy [nerve damage], which can lead to non-traumatic lower limb amputations, and retinopathy, which can lead to blindness) [3]. Altogether, the impact of diabetes is thus significant, with serious implications for health and quality of life, and costs to health care systems. In England, the direct cost to the National Health Service (NHS) of treating type 2 diabetes is approximately £8.8 billion annually, with a further £13 billion associated with indirect costs; these costs are estimated to rise to £15.1 and £20.5 billion, respectively, by 2035–6 [4]. Obesity, physical inactivity and diet are among key risk factors for type 2 diabetes. Weight gain and obesity are especially implicated in the onset of type 2 diabetes. Obese women are nearly 13 times more likely to develop type 2 diabetes than non-obese women; obese men are over 5 times as likely to develop type 2 diabetes [5]. Furthermore, a 1 kg/m2 increase in body mass index increases the risk of impaired fasting glucose by 9.5 % [6]. Impaired fasting glucose or impaired glucose tolerance indicate impaired glucose regulation, which is a condition where blood glucose levels are raised, but the levels are insufficient to meet current thresholds for a clinical diagnosis of type 2 diabetes. Impaired fasting glucose is associated with a raised hepatic glucose output, whereas impaired glucose tolerance is associated with peripheral insulin resistance. There is strong and consistent evidence that people with impaired fasting glucose or impaired glucose tolerance have between a 6- and 12-fold risk of developing diabetes, compared with people without, and both are risk factors for fatal and non-fatal cardiovascular events [7]. However, it is well established that lifestyle interventions that target modifiable risk factors such as weight and physical activity can prevent the onset of diabetes in people with impaired glucose regulation. A systematic review of 36 trials showed that diabetes prevention programmes that included diet or physical activity interventions can significantly reduce progression to type 2 diabetes and reduce weight and glucose at 12–18 months, compared with usual care [8]. As such, identification of people with impaired glucose regulation and intervention with lifestyle-change programmes presents significant opportunities for reducing the future incidence of type 2 diabetes. The delivery of these behaviour change interventions is central to guidance from the National Institute for Health and Care Excellence (NICE) on prevention of diabetes in high-risk groups, including people with impaired glucose regulation. However, the delivery of NICE-recommended diabetes prevention programmes is contingent on the availability of specialist staff to provide intensive interventions to relatively small numbers of people over 9 to 18 months. As articulated by the NHS National Diabetes Prevention Programme, the challenge remains to scale up and rapidly roll out evidence-based behaviour change interventions to ensure that more people at risk of diabetes can access to such interventions, but without compromising quality. Health coaching A model of care that has potential to achieve diabetes prevention at a large scale through effective behaviour change is ‘health coaching’. This is a relatively new approach and variously defined but common to this approach is an emphasis on health education and health promotion via patient-centred coaching based on motivational interviewing to improve health outcomes [9]. The increasing adoption of telephone and mobile technologies among patients, and the possibility of delivering care in efficient and flexible ways, has led to significant interest in the potential of telephone health coaching which involves:a regular series of phone calls between patient and health professional… to provide support and encouragement to the patient, and promote healthy behaviours such as treatment control, healthy diet, physical activity and mobility, rehabilitation, and good mental health [10] However, current evidence of effectiveness is mixed. A systematic review of 13 randomized controlled trials or quasi-experimental studies showed that, in 11 studies, telephone, internet or a combination of telephone, face-to-face, internet or email health coaching can effectively improve physical and mental health, promote healthy behaviours and increase social support among people with long-term conditions [11]. Other reviews have similarly identified a number of effective models, although the important ‘active ingredients’ are not clear [12, 13]. Moreover, much of the evidence is derived from trials conducted in the USA and there is uncertainty about the benefits of health coaching in the UK. A recent evaluation of the nurse-led Birmingham OwnHealth telephone health coaching service for people with long-term conditions (including diabetes) did not find reductions in health service utilization or cost over 12 months [14]. By contrast, a UK trial of telephone support from non-clinical telecare staff (backed up by diabetes specialist nurses) did show significant improvements in glycaemic control in people with type 2 diabetes, compared with usual care [15]. This intervention, now known as Diabetes Care Call, has recently been adapted for use in people with impaired glucose tolerance and impaired glucose regulation. A pilot evaluation (n = 44) of the Care Call intervention in people with impaired glucose tolerance showed reductions in weight (2.81 kg, 95 % confidence interval 1.2–4.42), body mass index (1.06 kg/m2, 95 % confidence interval 0.49–1.63), and fasting blood glucose (0.29 mmol/l, 95 % confidence interval 0.07–0.51) 1 year after the intervention [16]. Similar outcomes 12 months after the intervention were achieved in a pilot evaluation of Care Call in people with impaired glucose regulation who were offered either a telephone-only or a telephone plus group education pathway [17]. While the findings of these pilot studies are limited by the absence of a control group, they offer proof of concept that telephone health coaching can translate to people with impaired glucose regulation to promote positive and sustained lifestyle changes to prevent type 2 diabetes. The Impaired Glucose Regulation Care Call intervention has recently been enhanced, with greater use of web-based materials and electronic transfer of patient data, with a view to making the service more engaging for patients, and the provision of care more efficient for providers. The web plus telephone health coaching intervention has been developed by NorthWest EHealth in partnership with Hitachi Europe Ltd. Patient engagement is critical to the success of health promotion interventions and frequent, real-time communication and feedback are key to behaviour change and empowering patients to manage their behaviour [18, 19]. Information technology (IT) platforms, such as desktop applications, mobile short message service (SMS) and internet-based interventions are increasingly used to support and enhance patient engagement in self-management programmes. There is partial evidence that e-health interventions, described as second-generation interactive computerized interventions, can lead to positive improvements in physical activity and diet in people drawn from community and health settings [20] and can also support diabetes self-management tasks [21]. However, the evidence in favour of using IT interventions to support behaviour change is equivocal and few studies have assessed whether satisfaction and usability lead to better engagement and less costly delivery [22]. The addition of an IT platform within the Impaired Glucose Regulation Care Call service might lead to significant advantages in patient uptake and engagement, as well as freed human resources for the provider, which could ultimately improve the clinical effectiveness and cost-effectiveness of the service. However, there is a need to conduct an assessment of satisfaction, usability and cost of delivery of the new web-enabled telephone health coaching service (known as IGR3). This trial will therefore compare user experience and cost of delivery of IGR3 with the existing telephone-only health coaching service (known as IGR2). Further study into the potential impact of the IGR3 model on the clinical and cost effective aspects will then be planned. Methods/Design Trial design This trial protocol is written in accordance with standardized reporting guidance from SPIRIT (see Additional file 1) [23, 24]. This trial is a pragmatic, two-arm, patient-level randomized and controlled comparison of two health coaching services, one of which is already commissioned by Salford Clinical Commissioning Group and provided in the NHS by Salford Royal NHS Foundation Trust (i.e. IGR2). As a comparison of ‘active’ interventions, the expected differences in effectiveness are likely to be small, and the trial is not designed primarily to assess differences in clinical outcomes. Therefore, the objective of this trial is primarily to assess the acceptability of IGR3 compared with IGR2, with a secondary aim of examining whether IGR3 will result in a more efficient delivery method. This trial will test the hypothesis that a web-enhanced telephone health coaching intervention for people with impaired glucose regulation (IGR3) will be more acceptable than an existing telephone-only health coaching intervention (IGR2). We are also going to examine whether IGR3 will provide a more efficient delivery method. Primary objective To assess, quantitatively, whether a web-enhanced telephone coaching intervention (IGR3) is more acceptable than an existing telephone-only coaching intervention (IGR2) for people with impaired glucose regulation. Secondary objectives To determine whether the delivery of the IGR3 intervention is more efficient than the existing commissioned IGR2 while maintaining the quality of service on a similar level To explore the cost-effectiveness of IGR3 in comparison with IGR2 To explore and compare user and provider experience of IGR3 and IGR2 interventions qualitatively To explore the impact, if any, of IGR3 compared with IGR2 on clinical outcomes relevant to diabetes prevention in people with impaired glucose regulation Study setting This trial will be a single-centre study conducted in Salford, UK. Salford is a city in the north west of England made up of eight neighbourhoods with a population of 247,000 (34000 aged 65 and over) and ranked as the 16th most deprived local authority in England out of 326 [25]; approximately 14 % of the adult population are obese [26]. There are 47 general practices in the city, clustered in eight neighbourhoods. Interventions The intervention and control in the trial are both forms of health coaching. Figures 1 and 2 show the care pathways for IGR2 and IGR3, respectively. A comparison of the two services (highlighting their similarities and differences) is shown in Table 1. The key differences between the arms are that IGR3 provides patients with a web desktop dashboard to track progress against patient-centred goals (e.g. weight, dietary modifications) and a pedometer to monitor physical activity. Patients in the IGR3 arm also have access to educational content on the web dashboard in addition to the paper-based educational materials given to patients in the IGR2 arm.Fig. 1 Care pathway for IGR2. GP, general practitioner; IGR, impaired glucose regulation Fig. 2 Care pathway for IGR3. GP, general practitioner; IGR, impaired glucose regulation Table 1 Comparison of intervention characteristics Comparison IGR2 IGR3 Materials Patient information package Web-based patient tracking system for diabetes specialist nurse Educational materials Web-based patient information, videos and data recording SMS Patient information package, including pedometer, self-assessment link and log-in details Educational materials Providers Diabetes specialist nurse or dietician Diabetes specialist nurse or dietician Health advisor Health advisor Administrative support Administrative support Modes of delivery Telephone support Telephone support with web-based patient tracking Location of delivery Remote Remote Intervention components Triage Call from diabetes specialist nurse Call from diabetes specialist nurse Introduction call Call from health coach Call from health coach Self-assessment Not applicable Online self-assessment Action planning call Pre-call admin Pre-call admin Call to patient Call to patient Post-call admin Post-call admin Tracking Telephone Online and telephone Follow-up calls 1–6 Pre-call admin Pre-call admin Call to patient Call to patient Post-call admin Post-call admin Step-down call at 9 months As follow-up call 1 As follow-up call 1 Tailoring Content of intervention in response to patient self-evaluation Content of intervention in response to patient self-evaluation Data and outcomes Demographic and clinical characteristics Data about demographic and clinical characteristics will be entered on a case report form by the researcher at the baseline appointment. We will use sociodemographic questions from the General Practice Patient Survey [27], including sex, age, current work situation and qualifications. Ethnicity will be assessed using the 17 Census 2011 categories [28]. We will include a single-item health literacy measure, which has demonstrated good reliability and validity [29, 30], and a measure of the number and impact of long-term conditions [31]. Primary outcome measure Patient experience Patient satisfaction will be assessed using the Client Satisfaction Questionnaire (CSQ-8), which is a generic survey instrument used widely in primary care clinical trials [32]. The CSQ-8 is an eight-item self-administered questionnaire collected at the end of service delivery and scored using a four-point Likert scale. The CSQ-8 scores range from 8 to 32, with higher values indicating higher satisfaction. Secondary outcome measures Costs of intervention The costs of delivery of IGR2 and IGR3 will be determined. Hitachi Europe Ltd, with support from Salford Royal Foundation NHS Trust, will provide a detailed cost breakdown of the operation of IGR2 and IGR3, including staff and infrastructure. Data on number and length of calls for each element of the care pathway in each arm will be recorded throughout the trial period. Clinicians responsible for delivery of the intervention will log call times using a standardized activity log pro-forma. Health resources usage The usage of NHS health care and social services for participants will be determined using an adapted health resources questionnaire based on our previous COINCIDE trial [33]. We will obtain information on rates of utilization of most of the major elements of health and social care through linkage with the Salford Integrated Record. Health outcome measures HbA1c concentration Weight (kg) and body mass index Quality of life: measured using the Euroqol-5D-5 L (EQ-5D-5 L) [34]. The five-item EQ-5D-5 L is a generic measure of health-related quality of life, consisting of the EQ-5D descriptive system and the EQ Visual Analogue Scale (EQ VAS). The first part consists of five domains: mobility, self-management, usual activities, pain, anxiety and depression, with five levels of severity for each domain. A utility value can then be calculated based on a population tariff. The visual analogue scale records an individual’s self-perceived health, ranging from 0 to 100. Mental Health Inventory-5: this is a five-item scale that measures general mental health, including depression, anxiety, behavioural-emotional control and general positive affect [35]. Health experience and self-management: this will be measured by a modified version of the Summary of Diabetes Self-Care Activities. It assesses the number of days per week respondents engage in healthy and unhealthy behaviours (i.e. eating fruit and vegetable, eating red meat, undertaking exercise, drinking alcohol, and smoking) [36]. Patient activation: this will be measured by the Patient Activation Measure. Patient activation is a measurable outcome associated with higher quality of life, improved clinical outcomes and increase engagement with health or social care. The Patient Activation Measure is a self-report measure of patient knowledge, skills and confidence in self-management for long-term conditions [37]. We will use the short 13-item version [38]. Routine service level data We will extract data related to a range of processes associated with engagement with and completion of the intervention from the secure web-based intervention hosted by North West EHealth at the University of Manchester. These data will allow us to assess patient fidelity to the pre-specified service model outlined in Table 1. Specifically, we will run queries to produce aggregate data for all patients in the IGR3 arm at the end of the intervention period related to:Completeness of self-assessments Number of times patients logged in to specific pages Number of times patients used ‘contact advisor’ option for additional support Sample size The existing IGR2 service is commissioned for 500 patients per year and we anticipate with the support of Salford Royal NHS Foundation Trust, general practitioners and diabetes specialist nurses to recruit 200 of these patients in 12 months. The trial sample size has therefore been set at 100 patients per arm, based on a pragmatic decision concerning the probable recruitment window. With an estimated 15 % attrition rate, we would have 90 % power to detect an effect on a standardized measure of 0.5 on the CSQ-8, and 70 % power to detect a standardized effect size of 0.4 with a two-sided alpha of 0.05. A significant difference in CSQ-8 scores in favour of IGR3 will prove the hypothesis that the web plus telephone health coaching intervention offers patients a better care experience than the existing telephone-only health coaching intervention. As a comparison of two active treatments, where one is simply an enhanced version of the other, differences in clinical outcomes, quality of life and cost-effectiveness are expected to be relatively small. Therefore, the trial will not be powered to detect differences for secondary outcomes. Eligibility of participants Participants will be identified from referrals into the existing Impaired Glucose Regulation Care Call service provided by Salford Royal NHS Foundation Trust. Referral criteria into the Impaired Glucose Regulation Care Call service are:Moderate or high risk score on the Diabetes UK Risk score tool [39] and2. HbA1c = 42–47 mmol/mol (6.0–6.4 %) or3. Previous diagnosis of impaired glucose regulation with 1× confirmatory blood test (HbA1c within the previous 6 months). Based on these referral criteria, the eligibility criteria for the trial recruitment are as follows. Inclusion criteria Aged 18 years or older HbA1c between 42 and 47 mmol/mol (6.0–6.4 %) in previous 6 months Access to a telephone and home internet Exclusion criteria Referred to the face-to-face group impaired glucose regulation education session and does not go on to receive telephone-only support Diagnosis of type 2 diabetes: HbA1c of ≥48 mmol/mol (≥6.5 %) Diagnosis of gestational diabetes Does not read or speak English Incapable of participating as indicated by general practitioner because of dementia, learning difficulties, vision or motor skills limitations, serious and enduring mental health problems Recruitment to the trial General practice surgeries throughout Salford will be given promotional literature about Care Call (prepared by Hitachi Europe Ltd) to raise awareness among general practitioners about the availability of the service for people with impaired glucose regulation. All patients referred to the Care Call service will have a confirmed diagnosis of impaired glucose regulation and will have had an opportunity to discuss with their general practitioners the options available from the Care Call service. Eligible patients for the service and thus the trial will then be identified from routine contact with patients’ general practitioners. In addition, a rapid search and find tool designed by NorthWest EHealth, FARSITE, will be used to identify further eligible patients [40]. The FARSITE software provides a safe, convenient and effective way for general practitioners to control the recruitment of their patients into clinical research, while allowing NHS-based researchers to run complex and powerful searches over anonymized population-level health record data. Because FARSITE is hosted in a secure environment located at Salford Royal NHS Foundation Trust, confidentiality of data is preserved. General practitioner data collected and processed for FARSITE are transmitted across the NHS (N3) network, using high grade encryption, by the secured local NHS data host, the General Practitioner System Supplier or Apollo Medical Systems Ltd. Patient demographics data and pseudonymized data are stored in two separated and encrypted databases. In the CATFISH study, a research nurse employed by Hitachi Europe Ltd will run FARSITE searches from general practices in Salford to generate lists of pseudonymized patient populations. The clinical teams in practice can review the selected patients, merge patient contact details using the letter generation tool and send the letters to DocMan for print and postal fulfilment services. These letters will offer patients suspected to have impaired glucose regulation to attend for a general practitioner consultation and onward referral to Care Call. Feasibility searches using FARSITE protocols for impaired fasting glucose or impaired glucose tolerance were run in November 2014 and identified 3852 patients with suspected impaired glucose regulation. This test run showed that the FARSITE tool was capable of identifying patients with impaired glucose regulation and that there are sufficient numbers of patients with impaired glucose regulation who can be referred to the Care Call service and thus be invited to the CATFISH trial. After triage, the diabetes specialist nurse at the Care Call service will pass details of all eligible patients to the CATFISH trial administrator. The CATFISH trial administrator will call all patients and confirm personal details (email and phone number). Each patient is given a brief overview of the CATFISH trial. The administrator will confirm that each patient meets the inclusion criteria for the CATFISH trial (access to home internet and a desktop computer or laptop), and will seek permission for the University of Manchester research team to contact them. Those patients who do not wish to be approached by researchers will be redirected to the existing Care Call service (IGR2). The contact details of those patients who do agree to be contacted will be passed to the University of Manchester research team using a secure (nhs.net) email service. Within one week, a University of Manchester researcher will then contact the patient to discuss involvement in the trial in greater detail, giving them an opportunity to ask questions about the trial. Participant timeline The recruitment window runs from July 2015 to the end of June 2016. After consenting and undertaking baseline assessments, participants will enter the IGR3 or IGR2 service, where they will receive active therapeutic contacts for 6 months, followed by a step-down call at 9 months. We will collect measures at baseline, and 9 months (i.e. 3 months after the end of the core contact period; see Table 1). Recruitment flow and timelines of assessments are shown in Fig. 3 and Table 2, respectively.Fig. 3 CONSORT flow diagram. UoM, University of Manchester Table 2 SPIRIT Schedule of enrolment, interventions and assessments CSQ Client Satisfaction Measure, EQ-5D EuroQol five dimensions, HbA1c glycated haemoglobin (A1c), MHI-5 Mental Health Inventory, PAM Patient Activation Measure, SDSCA Summary of Diabetes Self-Care Activities Randomization and allocation concealment On providing consent, participants will be asked to complete baseline assessments and are then randomized using a remote and automated randomization service provided by the Manchester Academic Health Science Centre Clinical Trials Unit (MAHSC-CTU) at the Christie Hospital NHS Foundation Trust, Manchester, UK. To ensure allocation concealment, randomization will be by means of a computer-generated code implemented by a MAHSC-CTU employee and shared by telephone with the Care Call administrator following correct exchange of a password. The Care Call administrator will communicate allocations to Care Call staff (diabetes specialist nurse and health advisors). Participants will be allocated 1:1 to either IGR2 or IGR3 using minimization to ensure balance for age (<40, 40–60, >60 years) and body mass index (≤18.5, 18.6–24.9, 25.0–29.9). We will use minimization with a probability weighting of 0.75 to reduce predictability. Blinding It will not be possible to blind participants to treatments but they will not be formally told which intervention is an existing service (IGR2) and which intervention is novel (IGR3). Our researchers at the University of Manchester will be informed of the MAHSC-CTU randomization number for each participant by the Care Call administrator. The MAHSC-CTU randomization number will become the primary identifier for participants in the trial. In addition to the Care Call administrator, the principal investigator (PAC) will be unmasked to allocations in the event that participants request to be unblinded. Participants will be unblinded at the end of the follow-up period, or on withdrawal from the study. The CATFISH research team at the University of Manchester will remain blind to treatment allocation until follow-up assessments have been completed. The trial statistician will remain blind to treatment allocation. However, owing to the nature of health economic analysis, it is not possible to blind the trial health economist. Data collection At the baseline assessment visit, University of Manchester researchers will record the height and weight of participants and calculate body mass index using the NHS Choices body mass index healthy weight calculator [41]. Height will be measured using a Leicester stadiometer on a firm and even surface. Participants will be asked to remove their shoes and stand up straight with heels together, with heels, buttocks and shoulders pressed against the stadiometer. The University of Manchester researcher will take the measurement with the participant standing tall, looking straight ahead with the head upright and not tilted backwards. Where participants’ cannot stand, arm span can be used as an estimate of height, using the formula: total arm span/1.06 (women) or total arm span/1.03 (men). Arm span is measured by locating and marking the edge of the right collar bone (in the sternal notch) with a pen. Participants will each be asked to place their non-dominant arm in a horizontal position. The researcher will check that the patient’s arm is horizontal and in line with the shoulders. Using a tape measure, the researcher will measure the distance from the mark on the midline at the sternal notch to the tip of the middle finger. If the arm is flat and wrist is straight, the researcher will take a reading in centimetres and repeat the process for the dominant arm to calculate the total arm span. Weight will be measured in kilograms using Seca 875 weighing scales (Class 111 calibrated medical scales) that conform to ISO 9001:2008. Both height and weight will be recorded on a case report form. The participant’s initials is entered onto the front cover of the case report form, along with general practitioner ‘P’ code and date of completion. After height and weight have been measured, participants will be given the baseline questionnaire to complete. Researchers will be available to answer any questions the participant may have during completion. Explanation should be given without biasing the participant’s response. The researcher may also read the questions and complete the questionnaire if the participant requests this. After completing the questionnaire, the researcher will check that all questions have been attempted. At follow-up, the researcher will contact the participant by telephone to arrange a convenient time and place to meet for the follow-up assessment. During this, call the researcher will remind the participant not to tell the researcher if they were part of the telephone-only health coaching group or the web plus telephone health coaching group. At the follow-up assessment visit, the researcher will adopt the same procedures undertaken at the baseline visit to collect and record data on height and weight. The participants will be given the follow-up questionnaire to complete and the researcher will adopt the same procedure undertaken at the baseline visit to ensure that this questionnaire is completed appropriately. After completing follow-up assessments, participants will be invited to attend an appointment at the Clinical Research Facility at Salford Royal NHS Foundation Trust for a plasma glucose test to measure HbA1c. All blood tests will be conducted by nursing staff at the Barnes Clinical Research Facility, Salford Royal NHS Foundation Trust. Sample type and volume are fluoride oxalate (yellow), 1 ml; the reference range is 3.0–6.0 mmol/l. Laboratory staff will follow the Salford Royal NHS Foundation Trust protocol for prevention and management of potential exposure to blood-borne viruses, including needlestick and sharps injuries [42]. Data management After completion of blood tests and analysis, nursing staff at the Barnes Clinical Research Facility will be notified and will collect the results from the laboratory. Hard copies of the results will then be stored in a locked, secure area. A member of the CATFISH research team will visit the Barnes Clinical Research Facility at least once every two weeks to collect the results. The results will then be returned to the CATFISH office at the University of Manchester and stored securely. Once the research team has collected the HbA1c concentration results from the Clinical Research Facility, they will be screened by the CATFISH Research Nurse. If the HbA1c concentration falls outside the normal prediabetes range expected (≥48 mmol/mol), the participant’s general practitioner will be informed by letter of the result. If the concentration remains within the prediabetes range (42–47 mmol/mol) or is within the normal range (<42 mmol/mol) the general practitioner will not be routinely informed of the result. Blood samples for HbA1c testing will be automatically archived after analysis to a secure storage unit in the pathology department at Salford Royal NHS Foundation Trust and kept at 4 °C. They will be kept for a maximum of 2 days and then sent for incineration. Demographic and outcome data will be collected in an anonymized format using paper-based questionnaires administered face-to-face by the University of Manchester researchers. Additional data about engagement and delivery of the intervention will be captured by the secure and web-based system hosted by NorthWest EHealth at the University of Manchester. Patient confidentiality will be protected throughout all phases of data collection and analysis, in accordance with them UK Data Protection Act, 1998. The data management policy will adhere to Research Councils UK Common Principles on Data Policy and will be created by the principal investigator in accordance with the University of Manchester’s intellectual property policy and relevant third-party agreements. All paperwork will be transferred immediately to the University of Manchester and stored in a lockable fling cabinet. Paperwork with patient-identifiable data (consent form, case report form) should be stored separately from anonymized data (baseline and follow-up questionnaires). Names and contact details of patients who decide not to take part in the trial will be destroyed by the research team. All other data collected from questionnaires after consent is given will be anonymized. University of Manchester policy on storage of personal data is 5 years after the last publication date of the study or 10 years, whichever is the greater. Consent forms will be retained as essential documents, but items such as contact details will be deleted as soon as they are no longer needed. Statistical analysis We will report the trial and analysis according to CONSORT standards, including full details of use of the various telephone coaching components [43]. The data analyst will be masked to treatment allocation. For most outcomes, we will present descriptive data on baseline and follow-up scores, to allow assessment of change in IGR2 and IGR3 patients, as well as comparison with outcomes found in pilot evaluations [16, 17]. The focus will be on assessing whether IGR3 achieves at least as good outcomes as IGR2. This will not involve a formal assessment of equivalence. We will formally test for differences between IGR3 and IGR2 on patient experience using the CSQ-8. Analysis will follow intention-to-treat principles and a pre-specified plan. The core analysis will be via linear regression, using robust standard errors adjusted for the clustering of patients within practices. We will control for baseline values of each outcome and design factors. We will apply multiple imputation to baseline and 9 month variables with missing values by the chained equations approach using scores on all primary and secondary outcome measures (at baseline and follow-up). We will use 20 multiple imputation sets, as this will provide appropriate stability of results. Analyses will be conducted using STATA (version 14) with an alpha significance value of 5 %. We will report standardized effect sizes for all outcomes to aid comparison with published studies. Health economic analysis The health economic analysis will comprised two parts, both of which will assess the cost-effectiveness of health coaching with a web-based IT platform (IGR3) compared with health coaching alone (IGR2) among people with prediabetes. The first will be an incremental cost-effectiveness analysis from a clinical commissioning group perspective using patient satisfaction and intervention costs to derive a cost per additional unit of patient satisfaction. The second analysis will be conducted from an NHS and personal social services perspective [44]. Costs will include intervention costs and healthcare and social services resource costs. The quantity of resource use will be collected by questionnaire and a set of national average unit costs will be applied (e.g. [45]). The use of the EQ-5D-5 L will enable the estimation of quality-adjusted life years by calculating the area under the curve [46]. An incremental cost-effectiveness ratio (cost per additional quality-adjusted life year) will be used to assess cost-effectiveness of IGR3 in comparison with IGR2. Cost-effectiveness planes and cost-effectiveness acceptability curves will be constructed to reflect any uncertainty in the results and threshold. Qualitative study Process evaluations of complex interventions can be used to explain outcomes through an evaluation of how casual assumptions about how an intervention might work are related to the way it was implemented and how it produces change within particular contexts. Drawing on guidance from the Medical Research Council, a focus on understanding implementation (the what and how of intervention delivery), mechanisms of impact (pathways to change), and contextual factors can inform the design and conduct of a process evaluation [47]. However, the framework proposed by the Medical Research Council is not easily operationalized in the absence of a programme theory set out as a logic model. Programme theory articulates the hypothesized connections between the programme components and the outcomes to be assessed and is often underpinned by a theory of change [48]. Logic models offer a visual way of representing the ‘if… then…’ relationships between the resources needed to deliver the programme, the activities planned and their outputs, and the intended results of the programme. Using programme theory to drive the evaluation can help differentiate between programme theory failure, i.e. whether the intervention failed because of weaknesses in the underlying theory of change, and programme implementation failure, i.e. whether the intervention failed because of weaknesses in the way it was delivered [49]. In this trial, the theory of change presupposes that health coaching supported by web-enabled self-monitoring and feedback and education will increase patient activation, which, in turn, will result in increased patient satisfaction, reductions in the cost of service delivery and positive changes in health behaviours known to delay or prevent type 2 diabetes (Fig. 4). As such, greater effects are anticipated among participants in the web plus telephone coaching group than in the telephone-only group.Fig. 4 Theory of change model in CATFISH At the heart of this model is the concept of patient activation, which captures key ingredients known to predict patients’ capacity to engage in self-managing their health and use of healthcare: knowledge, skill and confidence [38]. Higher patient activation has been shown to predict engagement in preventive behaviours, such as attending regular check-ups, and healthy behaviours, such as regular exercise, treatment adherence and self-monitoring [50]. Moreover, activated patients are more likely to have clinical outcomes, such as HbA1c concentration and body mass index in the normal range [51]. Critically, highly activated patients are more satisfied with their care experience and have lower rates of hospital admissions and emergency room use, possibly leading to reductions in the cost of their care [52, 53]. Taking this theory of change as a starting point, Fig. 5 shows the logic model for the web plus telephone health coaching intervention tested in this trial. It is read from left to right, and includes a detailed breakdown of the resources and activities associated with delivering the intervention, along with details of the anticipated results, which include outputs, outcomes and impact over time. This logic model will facilitate qualitative evaluation of key programme vantage points related to context, implementation and outcomes [54]. While this trial is not a formal test of clinical effectiveness, qualitative evidence drawn from patient participants and also from health professionals engaged in delivery of the interventions will strengthen our understanding about user experience and impact of what was delivered, leading to greater opportunities to report about how the interventions might work in comparable and different contexts. Specific to the evaluation of IGR3, the evaluation will also be informed by evidence about dynamic factors that moderate individual acceptance of IT [55].Fig. 5 Logic model of programme components in CATFISH. DNS, domain name system Qualitative data collection Qualitative assessments using semi-structured interviews with patient participants drawn from both arms of the trial will take place after quantitative follow-up data have been collected. Semi-structured interviews offer opportunities to cover, in-depth, a range of topics relevant to the research questions, but also allow for exploration and probing of issues raised during the interview. In this trial, we will assess patient experience of IGR3 compared with IGR2, with a focus on understanding whether the web enhancements led to greater levels of activation and thus greater engagement with managing their health. We will also capture data from health professionals about the experience of implementing web or telephone health coaching in the context of impaired glucose regulation, with a focus on understanding acceptability and feasibility of using web platforms to enhance patient engagement in action planning and behaviour change. Purposeful maximum variation sampling will be used to identify patient participants sampled for age, baseline body mass index and intervention arm. All interviews will be conducted before outcome analysis is complete, to allow for a-priori exploration of user acceptance and experience of implementation. We will aim to conduct approximately 40 interviews in total, comprising approximately 20 participants drawn from both arms of the trial. Where feasible, professionals engaged in the commissioning, management and delivery of the health coaching service will also be interviewed. Up to 15 professional interviews will be conducted. Qualitative data analysis Interviews will be transcribed verbatim and analyzed thematically using standard approaches informed by Framework [56]. There are five key stages in this type of analysis:Familiarization – the transcripts will be read thoroughly by all researchers to identify key themes. Developing a thematic framework – a framework will be developed that will be applied to the transcripts. Following discussions with co-researchers, this framework will then be expanded and refined. Indexing – themes and emerging sub themes will be labelled and indexed. Charting – framework involves devising a series of thematic charts or matrices. Mapping and interpretation – the aim is to bring out the key characteristics and map and interpret the data as a whole. A benefit of using Framework analysis is that strategies and recommendations for practice and policy may be elicited at an early stage. Data monitoring The trial will be supervised independently by members of the trial steering committee. This committee will meet twice during the active recruitment period and has responsibility for monitoring progress of the trial, adherence to the protocol, patient safety and consideration of new information. Membership includes the principal investigator (PAC), the chairperson (Professor Christie Deaton, University of Cambridge, UK), and two other independent members (Dr Barbara Barett, King’s College London, UK and Dr Daniel Hind, University of Sheffield, UK). The trial statistician will attend when appropriate. At the chair’s discretion, an observer from Hitachi Europe Ltd will attend the trial steering committee. Given the nature of this trial it is unlikely that there are critical patient safety issues for a separate data monitoring and ethics committee to consider and there will be no formal stopping rules. Terms of reference of the trial steering committee are available on request from the principal investigator. Adverse event reporting An adverse event is any untoward and unexpected medical occurrence in a patient or clinical study subject. Adverse events are likely to be rare but should be reported to the principal investigator by the researcher or Care Call team. Although CATFISH is a trial of a non-investigational medicinal product, serious adverse events that are both related to the research procedures and are unexpected should be reported immediately (within 24 hours) either orally or in writing to the research sponsor (University of Manchester). This immediate report will be followed by a detailed written report sent to the NHS Research Ethics Committee that granted approval for the trial (East of England – Cambridgeshire and Hertfordshire) within 15 days of the study investigator becoming aware of the event. Research ethics The trial will be conducted in accordance with the UK Department of Health’s Research Governance Framework in health and social care and adhere to the ethical principles of the Helsinki Declaration [57]. All research staff involved in the conduct of the trial will meet the standards laid out in the ICH Harmonised Tripartite Guideline for Good Clinical Practice [58]. All participants will be offered a high street voucher worth £20 after completing baseline and the follow-up assessments. Amendments Substantial amendments will be communicated to the NHS Research Ethics Committee for the East of England (Cambridgeshire and Hertfordshire), following the process outlined by the NHS Health Research Authority. Since starting the trial one substantial amendment has been submitted and granted. This related to permission for a promotional flyer to be used in general practice to promote the Impaired Glucose Regulation Care Call service among general practitioners. This amendment also included provision for the eligibility criteria to be changed to bring the trial into line with evaluation parameters proposed by the NHS National Diabetes Prevention Programme, i.e. only patients with a HbA1c concentration between 42 and 47 mmol/mol in the previous 6 months can be referred into the Care Call service and subsequently invited to take part in the trial. Access to data and dissemination policy As the sponsor of the trial, the University of Manchester will remain the custodians of the data collected from participants during the trial and will not share data with any third party, including private companies, without the consent of the participants. Data will not be released to third parties or private companies (including the funder) before the trial has been completed and will be analyzed by an independent evaluation team at the University of Manchester. No interim analysis is planned and no interim data will be shared with the funder or third parties. In recognition of the importance of transparency and need to increase trust in clinical trial results both Hitachi Europe Ltd, and the University of Manchester will agree to data sharing in accordance with proposals outlined by the International Committee of Medical Journal Editors, which state that authors share with others the deidentified individual-patient data underlying the results presented in the trial report (including tables, figures, and appendices or supplementary material) no later than 6 months after publication [59]. Hitachi, as the funder of the trial and as owners of the technology to be tested, may wish to invoke a brief embargo (up to 3 months) on data sharing before publication in an open-access journal. Discussion Interventions that rely solely on telephone contact (with no self-monitoring of blood glucose) are no more effective than standard care in improving glycaemic control [60], signalling an opportunity to further develop and evaluate interventions that combine telephone interventions with self-monitoring and electronic transfer of data between patients and healthcare providers. Before embarking on expensive and time-consuming trial assessment of clinical effectiveness and cost-effectiveness, however, a key challenge is to understand from the patient perspective if enhancing telephone health coaching interventions with IT platforms improves acceptability and usability and thereby engagement in diabetes prevention programmes. This trial will offer important insights about whether a web-based IT platform can enhance engagement in a telephone health coaching intervention provided by health advisors for people with impaired glucose regulation. The results will have implications for the design of future definitive cost-effectiveness trials in settings where there is no existing diabetes prevention programme. The trial design is potentially limited by restrictions on participant recruitment. Currently, referral into the Care Call service at Salford Royal NHS Foundation Trust is heavily reliant on general practice and there are limited routes into the service from other sources in the community, e.g. pharmacy and public health. Participants in the CATFISH trial will therefore primarily be drawn from patients already ‘in the system’ and known to general practitioners and may have been given behaviour change advice in the past. Additionally, achieving our recruitment target may be jeopardized by only sourcing participants for the CATFISH trial from referrals into the Care Call service – recruitment into the trial will be contingent on sufficient throughput in the clinical service. However, Salford Royal NHS Foundation Trust is one of seven demonstrator sites for the NHS National Diabetes Prevention Programme in the NHS and there is an ongoing commitment to increase capacity in the Care Call service, with a likely benefit for the CATFISH trial. Furthermore, the Care Call service attracts referrals from all eight neighbourhoods across Salford, increasing opportunities to recruit participants with different socio-economic profiles. The design and recruitment strategy are thus pragmatic and thus more likely to be generalizable. Working with industry partners in health services research is novel and presents unique challenges, not least the need to maintain independence. Hitachi Europe Ltd, have invested in the Care Call service at Salford Royal NHS Foundation Trust to improve efficiencies, such as employing an administrator and a research nurse to expedite quality referrals into the service. With the support of the trial steering committee, the CATFISH trial is being run as an independent evaluation and we have ensured that sufficient safeguards are in place to preserve independence throughout all phases of the trial. This includes a commitment to open-access publication and data sharing, in keeping with policies to prevent publication and outcome reporting bias of clinical trials. Trial status Trial registration was initiated prospectively with ISRCTN on 23 April 2015. Failure of administrative functions on the part of BioMed Central who host and curate ISRCTN and the University of Manchester led to delay in payment and registration was not finalised until 1 July 2015. The recruitment started on 30 June 2015, after the initiation of public registration. Recruitment to the trial began in June 2015 and completed in May 2016. A total of 209 participants were recruited and randomized. The trial is now in follow-up and data collection will be completed at the latest in March 2017; results will be available in May 2017. Abbreviations CONSORT, Consolidated Standards of Reporting Trials; CSQ-8, Client Satisfaction Questionnaire; EQ-5D, Euroqol-5D; HbA1c, Glycated haemoglobin; IT, information technology; MAHSC-CTU, Manchester Academic Health Science Centre Clinical Trials Unit; NHS, National Health Service (UK); NICE, National Institute for Health and Care Excellence; SMS, short message service; SPIRIT, Standard Protocol Items: Recommendations for Interventional Trials Additional file Additional file 1: SPIRIT 2013 Checklist. (DOC 121 kb) Funding Hitachi Europe Ltd funded a proportion of time of PAC, PB, MH and AP to conduct the trial. AU is funded by Hitachi Europe Ltd. The funder did not design the study or contribute to the decision to submit this protocol for publication. Authors’ contributions PC and PB designed the study and drafted the manuscript. MH designed the statistical analysis plan and other statistical elements of the study. AP contributed to clinical sections of this manuscript. CR and JL contributed to the health economic evaluation section of the manuscript. AB and LB contributed to the methods section on taking anthropometric measurements and blood tests and other outcomes. MG was involved in the conception of the study. AU provided oversight about the role of Hitachi as a funder and partner in delivery of the trial protocol at the Care Call Service at SRFT. All authors approved this manuscript for publication. Competing interests PC, PB, MH, MG, AB, LB, CR, JL have no competing interests. AP receives a fee from Hitachi Europe Ltd. in her role as a clinical advisor. AU does not have any financial and non-financial competing interests associated with the CATFISH service trial nor the web-based technology used as part of the trial, aside from the salary drawn from Hitachi Europe Ltd for expertise provided to the its Healthcare Programme; he will not receive any reimbursements, fees, funding (including stock-holdings) or salary from an organisation that may gain or lose financially from the publication of the article, either now or in the future. Ethics approval and consent to participate Ethical approval was granted on 27 March 2015 by the NHS Research Ethics Committee for the East of England (Cambridgeshire and Hertfordshire) (reference no 15/EE/0117). Patients referred to the Care Call service and who agree to participate will be sent an information sheet and consent forms and asked to return the signed consent form to the University of Manchester research team. To incentivize participation in the trial, patients will be given a £20 Love to Shop voucher at the start and again at the end of the 9 month assessment period. In the consent process, patients will be provided with information about the aims and objective of the trial, including explanation of the random design. Information sheets will only explain that taking part in the study will involve being randomized to one of two types of remote health coaching interventions, but participants will not be told which group they are in – they will be given clear guidance explaining how by being randomized to either intervention their care will not be disadvantaged. We will seek full informed consent to randomize patients between the two trial arms, according to conventional procedures. Declaration of interests The trial is a collaboration between Hitachi Europe Ltd, Salford Royal Foundation NHS Trust, and NIHR CLAHRC Greater Manchester. Trial sponsor Ms Lynne McRae, University of Manchester, M13 9PL, UK. lynne.macrae@manchester.ac.uk. ==== Refs References 1. American Diabetes Association Diagnosis and classification of diabetes mellitus Diabetes Care 2009 32 Suppl 1 S62 7 10.2337/dc09-S062 19118289 2. Diabetes UK Facts and stats 2015 London Diabetes UK 3. Fowler MJ Microvascular and macrovascular complications of diabetes Clin Diabetes 2008 26 2 77 82 10.2337/diaclin.26.2.77 4. Hex N Bartlett C Wright D Taylor M Varley D Estimating the current and future costs of type 1 and type 2 diabetes in the UK, including direct health costs and indirect societal and productivity costs Diabet Med 2012 29 7 855 62 10.1111/j.1464-5491.2012.03698.x 22537247 5. Health and Social Care Information Centre Statistics on obesity, physical activity and diet: England 2014 2014 Leeds Health and Social Care Information Centre 6. Bombelli M Facchetti R Sega R Carugo S Fodri D Brambilla G Giannattasio C Grassi G Mancia G Impact of body mass index and waist circumference on the long-term risk of diabetes mellitus, hypertension, and cardiac organ damage Hypertension 2011 58 6 1029 35 10.1161/HYPERTENSIONAHA.111.175125 22025375 7. Santaguida PL BC Hunt D Morrison K Gerstein H Raina P Booker L Yazdi H Diagnosis, prognosis, and treatment of impaired glucose tolerance and impaired fasting glucose. Evidence Report/Technology Assessment No 128 2005 Rockville Agency for Healthcare Research and Quality (US) 8. Public Health England A systematic review and meta-analysis assessing the effectiveness of pragmatic lifestyle interventions for the prevention of type 2 diabetes mellitus in routine practice 2015 London Public Health England 9. Palmer S Tubbs I Whybrow A Health coaching to facilitate the promotion of healthy behaviour and achievement of health-related goals Int J Health Promot Educ 2003 41 3 91 3 10.1080/14635240.2003.10806231 10. McLean S Protti D Sheikh A Telehealthcare for long term conditions BMJ 2011 342 d120 10.1136/bmj.d120 21292710 11. Kivela K Elo S Kyngas H Kaariainen M The effects of health coaching on adult patients with chronic diseases: a systematic review Patient Educ Couns 2014 97 2 147 57 10.1016/j.pec.2014.07.026 25127667 12. McLean S Sheikh A Cresswell K Nurmatov U Mukherjee M Hemmi A Pagliari C The impact of telehealthcare on the quality and safety of care: a systematic overview PLoS One 2013 8 8 e71238 10.1371/journal.pone.0071238 23977001 13. Hutchison AJ Breckon JD A review of telephone coaching services for people with long-term conditions J Telemed Telecare 2011 17 8 451 8 10.1258/jtt.2011.110513 22025743 14. Steventon A Tunkel S Blunt I Bardsley M Effect of telephone health coaching (Birmingham OwnHealth) on hospital use and associated costs: cohort study with matched controls BMJ 2013 347 f4585 10.1136/bmj.f4585 23920348 15. Young RJ Taylor J Friede T Hollis S Mason JM Lee P Burns E Long AF Gambling T New JP Pro-active call center treatment support (PACCTS) to improve glucose control in type 2 diabetes: a randomized controlled trial Diabetes Care 2005 28 2 278 82 10.2337/diacare.28.2.278 15677779 16. Savas LA Grady K Cotterill S Summers L Boaden R Gibson JM Prioritising prevention: implementation of IGT Care Call, a telephone based service for people at risk of developing type 2 diabetes Prim Care Diabetes 2015 9 1 3 8 10.1016/j.pcd.2014.07.003 25175562 17. Savas LA, Grady K. The IGR Care Call project evaluation report. Manchester: University of Manchester; 2013. http://clahrc-gm.nihr.ac.uk/wp-content/uploads/Final-IGR-report-Jan-2014.pdf. Accessed 03 Aug 16. 18. Sundiatu DSG Thomas P Angela S Changing patient behavior: the next frontier in healthcare value Health Int 2012 12 65 73 19. Small N Bower P Chew-Graham CA Whalley D Protheroe J Patient empowerment in long-term conditions: development and preliminary testing of a new measure BMC Health Serv Res 2013 13 1 1 15 10.1186/1472-6963-13-1 23286781 20. Norman GJ Zabinski MF Adams MA Rosenberg DE Yaroch AL Atienza AA A review of eHealth interventions for physical activity and dietary behavior change Am J Prev Med 2007 33 4 336 45 10.1016/j.amepre.2007.05.007 17888860 21. El-Gayar O Timsina P Nawar N Eid W A systematic review of IT for diabetes self-management: are we there yet? Int J Med Inform 2013 82 8 637 52 10.1016/j.ijmedinf.2013.05.006 23792137 22. Sawesi S Rashrash M Phalakornkule K Carpenter JS Jones JF The impact of information technology on patient engagement and health behavior change: a systematic review of the literature JMIR Med Inform 2016 4 1 e1 10.2196/medinform.4514 26795082 23. Chan AW Tetzlaff JM Gotzsche PC Altman DG Mann H Berlin JA Dickersin K Hrobjartsson A Schulz KF Parulekar WR SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials BMJ 2013 346 e7586 10.1136/bmj.e7586 23303884 24. Chan AW Tetzlaff JM Altman DG Laupacis A Gotzsche PC Krleza-Jeric K Hrobjartsson A Mann H Dickersin K Berlin JA SPIRIT 2013 statement: defining standard protocol items for clinical trials Ann Intern Med 2013 158 3 200 7 10.7326/0003-4819-158-3-201302050-00583 23295957 25. Department for Communities and Local Government The English indices of deprivation 2015 2015 London Department for Communities and Local Government 26. Salford Primary Care Trust. Refreshed strategic plan 2009–2014. www.ibyd.co.uk/bhf/documents/Salford_PCT/StrategicPlan2009-2014.pdf. Accessed 03 Aug 16. 27. Campbell J Smith P Nissen S Bower P Elliott M Roland M The GP patient survey for use in primary care in the National Health Service in the UK – development and psychometric characteristics BMC Fam Pract 2009 10 57 10.1186/1471-2296-10-57 19698140 28. Office for National Statistics Harmonised Concepts and Questions for Social Data Sources. Primary Principles. Ethnic Group. Version 3.3 2015 London Office for National Statistics 29. Morris NS MacLean CD Chew LD Littenberg B The Single Item Literacy Screener: evaluation of a brief instrument to identify limited reading ability BMC Fam Pract 2006 7 21 10.1186/1471-2296-7-21 16563164 30. Jeppesen KM Coyle JD Miser WF Screening questions to predict limited health literacy: a cross-sectional study of patients with diabetes mellitus Ann Fam Med 2009 7 1 24 31 10.1370/afm.919 19139446 31. Bayliss EA Ellis JL Steiner JF Seniors’ self-reported multimorbidity captured biopsychosocial factors not incorporated into two other data-based morbidity measures J Clin Epidemiology 2009 62 5 e551 557 10.1016/j.jclinepi.2008.05.002 32. Attkisson CC Zwick R The Client Satisfaction Questionnaire: psychometric properties and correlations with service utilization and psychotherapy outcome Eval Program Plann 1982 5 3 233 7 10.1016/0149-7189(82)90074-X 10259963 33. Coventry P Lovell K Dickens C Bower P Chew-Graham C McElvenny D Hann M Cherrington A Garrett C Gibbons CJ Integrated primary care for patients with mental and physical multimorbidity: cluster randomised controlled trial of collaborative care for patients with depression comorbid with diabetes or cardiovascular disease BMJ 2015 350 h638 10.1136/bmj.h638 25687344 34. Herdman M Gudex C Lloyd A Janssen M Kind P Parkin D Bonsel G Badia X Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5 L) Qual Life Res 2011 20 10 1727 36 10.1007/s11136-011-9903-x 21479777 35. Berwick DM Murphy JM Goldman PA Ware JE Jr Barsky AJ Weinstein MC Performance of a five-item mental health screening test Med Care 1991 29 2 169 76 10.1097/00005650-199102000-00008 1994148 36. Toobert DJ Hampson SE Glasgow RE The summary of diabetes self-care activities measure: results from 7 studies and a revised scale Diabetes Care 2000 23 7 943 50 10.2337/diacare.23.7.943 10895844 37. Hibbard JH Stockard J Mahoney ER Tusler M Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers Health Serv Res 2004 39 4 Pt 1 1005 26 10.1111/j.1475-6773.2004.00269.x 15230939 38. Hibbard JH Mahoney ER Stockard J Tusler M Development and testing of a short form of the Patient Activation Measure Health Serv Res 2005 40 6 Pt 1 1918 30 10.1111/j.1475-6773.2005.00438.x 16336556 39. Diabetes UK. Diabetes risk score assessment tool. 2016. https://www.diabetes.org.uk/professionals/diabetes-risk-score-assessment-tool/. Accessed 03 Aug 16. 40. NorthWest EHealth. FARSITE. 2014. http://nweh.co.uk/products/farsite. Accessed 03 Aug 16. 41. NHS Choices. BMI healthy weight calculator. 2015. http://www.nhs.uk/Tools/Pages/Healthyweightcalculator.aspx. Accessed 03 Aug 16. 42. Salford Royal NHS Foundation Trust Prevention and management of potential exposure to blood borne viruses including needlestick and sharps injuries. Issue No. 4 2015 Salford Salford Royal NHS Foundation Trust 43. Schulz KF Altman DG Moher D CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials BMJ 2010 340 c332 10.1136/bmj.c332 20332509 44. National Institute for Health and Care Excellence (NICE) Guide to the methods of technology appraisal 2013 2013 Manchester National Institute for Health and Care Excellence (NICE) 45. Curtis L Unit costs of health and social care 2013 2013 Canterbury Personal Social Services Research Unit, University of Kent 46. Richardson G Manca A Calculation of quality adjusted life years in the published literature: a review of methodology and transparency Health Econ 2004 13 12 1203 10 10.1002/hec.901 15386669 47. Moore GF Audrey S Barker M Bond L Bonell C Hardeman W Moore L O’Cathain A Tinati T Wight D Process evaluation of complex interventions: Medical Research Council guidance BMJ 2015 350 h1258 10.1136/bmj.h1258 25791983 48. Knowlton LW Phillips CC The logic model guidebook. better strategies for great results 2013 Thousand Oaks Sage Publications 49. Bickman L Using program theory in evaluation 1987 San Francisco Jossey-Bass 50. Hibbard JH Gilburt H Supporting people to manage their health. An introduction to patient activation 2014 London The King’s Fund 51. Greene J Hibbard JH Why does patient activation matter? An examination of the relationships between patient activation and health-related outcomes J Gen Intern Med 2012 27 5 520 6 10.1007/s11606-011-1931-2 22127797 52. Hibbard JH Greene J What the evidence shows about patient activation: better health outcomes and care experiences; fewer data on costs Health Aff (Millwood) 2013 32 2 207 14 10.1377/hlthaff.2012.1061 23381511 53. Kinney RL Lemon SC Person SD Pagoto SL Saczynski JS The association between patient activation and medication adherence, hospitalization, and emergency room utilization in patients with chronic illnesses: a systematic review Patient Educ Couns 2015 98 5 545 52 10.1016/j.pec.2015.02.005 25744281 54. WK Kellogg Foundation Using logic models to bring together planning, evaluation, and action. Logic Model Development Guide 2004 Battle Creek WK Kellogg Foundation 55. Venkatesh VMM, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Q. 2003; n27:425–78. 56. Ritchie J Spencer L Bryman A Burgess RG Qualitative data analysis for applied policy research Analyzing qualitative data 1994 London Routledge 173 194 57. World Medical Association General Assembly World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects – Seoul amendment 2008 Ferney-Voltaire World Medical Association 58. Medical Research Council Guidelines for good clinical practice in clinical trials 1998 London Medical Research Council 59. Taichman DB Backus J Baethge C Bauchner H de Leeuw PW Drazen JM Fletcher J Frizelle FA Groves T Haileamlak A Sharing clinical trial data – a proposal from the International Committee of Medical Journal Editors N Engl J Med 2016 374 4 384 6 10.1056/NEJMe1515172 26786954 60. Suksomboon N Poolsup N Nge YL Impact of phone call intervention on glycemic control in diabetes patients: a systematic review and meta-analysis of randomized. controlled trials PLoS One 2014 9 2 e89207 10.1371/journal.pone.0089207 24586596

PMC005xxxxxx/PMC5000462.txt

==== Front BMC Evol BiolBMC Evol. BiolBMC Evolutionary Biology1471-2148BioMed Central London 72510.1186/s12862-016-0725-xErratumErratum to: Life habits, hox genes, and affinities of a 311 million-year-old holometabolan larva Haug Joachim T. joachim.haug@palaeo-evo-devo.info 1Labandeira Conrad C. labandec@si.edu 234Santiago-Blay Jorge A. BLAYJ@si.edu 25Haug Carolin carolin.haug@palaeo-evo-devo.info 1Brown Susan sjbrown@ksu.edu 61 Ludwig Maximilians University Munich, Biocenter – Department of Biology II and GeoBio-Center, Großhaderner Str. 2, Planegg-Martinsried, 82152 Germany 2 Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013 USA 3 Department of Entomology, University of Maryland, College Park, MD 20742 USA 4 College of Life Sciences, Capital Normal University, Beijing, 100048 China 5 Department of Crop and Agroenvironmental Sciences, University of Puerto Rico, Mayagüez, PR 00681 USA 6 Division of Biology, Kansas State University, Manhattan, KS 66502 USA 25 8 2016 25 8 2016 2016 16 1 16914 7 2016 19 7 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.issue-copyright-statement© The Author(s) 2016 ==== Body Erratum Following the publication of this article [1] it has been brought to the attention of the authors and the editors of BMC Evolutionary Biology that the description of the newly described genus and species Srokalarva berthei did not fully meet the criteria of availability as defined by the ICZN (International Code of Zoological Nomenclature). The species description and accompanying ZooBank identification numbers were contained in an additional file and not in the main manuscript as required under the ICZN code. This addendum is to ensure that the ICZN criteria for the availability of new names are satisfied. The following systematics section is identical to that published as part of additional file 1 of this article [1], but is republished here to ensure its full availability. The date of publication of the nomenclatural acts is the date that this addendum has been published. Systematics Insecta, rank uncertain Holometabola, rank uncertain Srokalarvidae, tax. nov. Principle suprageneric characters. Adults are unknown; the diagnostic features are based on larval characters, as detailed below. Extended synonymy. 1990 “oldest known larva” – Shear & Kukalová-Peck, p. 1827 [2]. 1990 “oldest known endopterygote larva” – Shear & Kukalová-Peck, fig. 44 [2]. 1991 “oldest known fossil larva” – Kukalová-Peck p. 151 [3]. 1991 “oldest known endopterygote larva” – Kukalová-Peck p. 171; fig. 6.26 A [3]. 1997 “first Carboniferous larva” – Kukalová-Peck, p. 204 [4] 1997 “oldest known larva” – Kukalová-Peck, p. 204 [4]. 1997 “Berthe-Traub specimen” – Kukalová-Peck, p. 204 [4]. 1997 “Berthe-Traub larva” – Kukalová-Peck, p. 204 [4]. 1997 oldest true larva – Kukalová-Peck, p. 206 [4]. 1997 “Srokalarva berthei “– Kukalová-Peck, fig. 14B.11 (first use of the Linnaean binomial) [4]. 1997 “Alleged Carboniferous endopterygote larva” – Willmann, fig. 20.5 [5]. 1997 “alleged Carboniferous larva” – Willmann, p. 276 [5]. 1997 “specimen described as Carboniferous holometabolan larva“– Willmann, p. 276 [5]. 1997 “alleged endopterygote Carboniferous larva” – Willmann, p. 277 [5]. 1997 “oldest known endopterygote larva'”– Willmann, p. 277 [5]. 2002 “alleged holometabolan larva from the Westphalian of Mazon Creek” – Rasnitsyn & Quicke, p. 157 [6]. 2002 “Srokalarva”– Labandeira & Santiago-Blay, pp. 101-102 [7]. 2005 “Srokalarva”– Grimaldi & Engel, p. 54 [8]. 2007 “alleged holometabolous larva from the Late Carboniferous” – Nel et al. p. 350 [9]. 2011 “Srokalarva berthei” – Labandeira, pp. 11, 16; tab 1 [10]. 2011 “Srokalarva”– Labandeira, pp. 11, 335 [10]. 2011 “Srokalarva berthei”– Labandeira, fig. 1G [10]. 2013 Srokalarva bertei – Nel et al. p. 259, fig. 3; (sic!) [11]. 2013 Srokalarva – Nel et al., table 3 [11]. Genus Srokalarva gen. nov. Species: berthei sp. nov. Material The fossil consists of an ironstone concretion from the Mazon Creek fossil megalocality, collected at Pit 11 near Essex, in northwestern Kankakee, Co. Illinois, U.S.A. [12, 13]. Srokalarva berthei was found in the Francis Creek Shale Member of the Carbondale Formation. The age of the fossil is the regional Upper Desmoinesian Stage of eastern North American chronostratigraphy, corresponding to the Westphalian D interval of the older European geochronology [13], and is considered of late Moscovian Age, ca. 311 Ma, based on the most recent time scale [14]. Holotype Specimen MCP-322 is deposited in the Geology Department of the Field Museum of Natural History, Chicago, Illinois, USA. This specimen previously was housed in the collections of the Mazon Creek Project of Northeastern Illinois University, in Chicago, Illinois. Remarks―The designation, Srokalarva berthei, was not validated by the fourth edition of the International Code of Zoological Nomenclature at the time that the Linnaean binomen was applied to this fossil in 1997 [4]. This lack of formal validation is attributed to (i) the absence of a valid description, (ii) a diagnosis was not offered, and (iii) a holotype specimen was not designated, thus rendering the name, Srokalarva berthei, a nomen nudum at first mention. Nevertheless, the Srokalarva berthei binomen is available and is used in this report. The formal species description of Srokalarva berthei Haug, Labandeira, Santiago-Blay, Haug and Brown is provided under the ZooBank identification number ADDB3CD0-68 F1-4591-93BB-1C56AD9F8E10. ZooBank is accessed through http://zoobank.org. The description follows the scheme for arthropods proposed by Haug et al. [15]; whereby separate descriptions are provided for each segment. For each description, there is initial concentration on dorsal organization, followed by structural details for each appendage or other specialized structure. Terminology is kept at a more general level, yet specialized terms for different groups, especially involving insect and mandibulate terminology, are given. This approach should improve comparisons to other arthropod groups and a better understanding arthropod biology for the non-expert reader. General habitus Elongate sclerotized arthropod of about 22 mm length. Body organized into 18 segments (17 externally visible, one inferred). We have used the formal taxon, Holometabola, as an unranked, supraordinal designation that encompasses all holometabolous insects. Holometabolous insects are characterized by the unique feature of complete metamorphosis, featuring a dramatic change in ontogenetic development from one major life-stage to the next, and typified by the life stages of egg to larva to pupa to adult. In addition, the larval stage has a distinctive type of wing development, the endopterygote condition, which refers to the internal formation of wings under the thoracic cuticle. The term, endopterygote, thus is restricted to this type of wing development, although we recognize that historically the term, “Endopterygota”, has been used as a synonym for Holometabola [16]. Tagmatization and dorsal body organization Head. Anterior five segments, ocular segment and post-ocular segments 1-5 (post-ocular segment 2 inferred by comparison with modern forms), dorsally forming a continuous head capsule. All these segments are head segments. Length of head about 2.9 mm. A possible suture line is apparent either between postocular segments 1 and 2 or between 2 and 3. Thorax. Post-ocular segments 6–8 subsimilar in dorsal morphology; they are recognized therefore as a separate tagma. (The Srokalarva berthei thorax is not necessarily directly homologous to the thorax in other arthropods; however, it is homologous to the pro-, meso- and metathoraces of other insects.) Postocular segment 6 (thorax segment 1, the prothorax) dorsally forming a sclerotized tergite (pronotum) of roughly rounded-rectangular in outline. Pronotum surrounded apparently by softer membrane, not directly articulating or covering posterior parts of the head or the tergite of the succeeding segment. Length of pronotum about 1.4 mm; length of membranous area anterior to tergite about 0.3 mm. Exact dorsalventral dimension difficult to assess due to a slightly tilted body embedded in matrix. Postocular segment 7 (thorax segment 2, the mesothorax) dorsally forming a sclerotized tergite (mesonotum). Mesonotum surrounded apparently by softer membrane anteriorly, not directly articulating to tergite of the preceding or succeeding segment. Length of mesonotum about 1.3 mm; length of membranous area anterior to tergite about 0.9 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but larger in dorsalventral dimension than pronotum. Postocular segment 8 (thorax segment 3, the metathorax) dorsally forming a sclerotized tergite (metanotum). Metanotum surrounded by apparently softer membrane, not directly articulating to tergite of the preceding segment. Length of mesonotum about 2.2 mm; length of membranous area anterior to tergite about 0.6 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedding, but larger in dorsalventral dimension than mesonotum. Abdomen. Postocular segments 9–18 subsimilar in dorsal morphology; they are recognized therefore as a separate tagma, the abdomen (not homologous to abdomen in other arthropods). Postocular segment 9 (abdominal segment 1) dorsally (and “laterally”) forming a sclerotized tergite. Tergite in direct contact to preceding tergite (metanotum), slightly overhanging next posterior one. Length about 1.5 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but slightly shorter in dorsalventral dimension than metanotum. Postocular segment 10 (abdominal segment 2) dorsally (and “laterally”) forming a sclerotized tergite. Tergite slightly overhanging adjacent posterior one. Length about 1.4 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but slightly shorter in dorsalventral dimension than preceding tergite. Postocular segment 11 (abdominal segment 3) dorsally (and “laterally”) forming a sclerotized tergite. Tergite slightly overhanging adjacent posterior one. Length about 1.1 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but slightly shorter in dorsalventral dimension than preceding tergite. Postocular segment 12 (abdominal segment 4) dorsally (and “laterally”) forming a sclerotized tergite. Tergite slightly overhanging adjacent posterior one. Length about 1.1 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but slightly shorter in dorsalventral dimension than preceding tergite. Post-ocular segment 13 (abdominal segment 5) dorsally (and “laterally”) forming a sclerotized tergite. Tergite slightly overhanging adjacent posterior one. Length about 1.1 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but slightly shorter in dorsalventral dimension than preceding tergite. Postocular segment 14 (abdominal segment 6) dorsally (and “laterally”) forming a sclerotized tergite. Tergite slightly overhanging adjacent posterior one. Length about 1.1 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but slightly shorter in dorsalventral dimension than preceding tergite. Postocular segment 15 (abdominal segment 7) dorsally (and “laterally”) forming a sclerotized tergite. Tergite slightly overhanging adjacent posterior one. Length about 1.0 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but slightly shorter in dorsalventral dimension than preceding tergite. Postocular segment 16 (abdominal segment 8) dorsally (and “laterally”) forming a sclerotized tergite. Tergite slightly overhanging adjacent posterior one. Length about 0.8 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but slightly shorter in dorsalventral dimension than preceding tergite. Postocular segment 17 (abdominal segment 9) dorsally (and “laterally”) forming a sclerotized tergite. Tergite slightly overhanging adjacent posterior one. Length about 1.0 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but slightly shorter in dorsalventral dimension than preceding tergite. Postocular segment 18 (abdominal segment 10) dorsally (and “laterally”) forming a sclerotized tergite. Tergite slightly overhanging adjacent posterior one. Length about 1.5 mm. Exact dorsalventral dimension difficult to assess due to slightly tilted embedment, but slightly shorter in dorsalventral dimension than preceding tergite. It remains unclear whether a possible eleventh abdominal segment is truly absent or simply not preserved. Structural details within each tagma Head. Ocular segment without traces of compound eyes. Stemmata may be present but cannot be verified. Clypeo-labral complex well developed anteriorly on the head capsule. Clypeus about 0.8 mm in proximal-distal axis; labrum about 1.5 mm in proximal-distal axis. Postocular segment 1 with a pair of well-developed appendages, antennae (antennulae in other mandibulates) inserted dorsad to the clypeus. Diameter at base about 0.4 mm; tapering distally, and stronger in the terminal third. Maximum preserved length about 4.8 mm. Preserved position indicates an original subdivision into numerous elements, yet no clear subdivisions are apparent. No details of postocular segment 2 (intercalary segment) available. Postocular segment 3 with a pair (?) of well-developed appendages, mandibles. Consisting of a single element each. Only visible in lateral view. Elements massive in appearance and of triangular outline, base of the triangle proximally, tip distally. Base of the triangle about 1.8 mm long, height of triangle about 2.3 mm. Dorsad to mandibles small structure compressed through head capsule; square-shaped in lateral view, with about 0.5 mm along one edge, possible representing the hypopharynx (possibly homologous to paragnaths in other mandibulates). Postocular segment 4 with a pair (?) of well-developed appendages, maxillae (maxillulae in other mandibulates). Preserved position indicates an original subdivision into numerous elements, with a proximal part and a distal part (palp), yet no clear subdivisions are apparent. Distal part about 0.25 mm in diameter; overall length (proximal-distal axis) about 2.6 mm. Postocular segment 5 with a presumably fused pair (?) of well-developed appendages, labium (maxillae or second maxillae in other mandibulates). Preserved position indicates an original subdivision into numerous elements, with a proximal part and a distal part (palp), yet no clear subdivisions are apparent. Distal part about 0.25 mm in diameter; overall length (proximal-distal axis) about 3.4 mm. Thorax. Postocular segment 6 (prothorax) with a pair (?) of well-developed appendages. General shape in lateral view elongate; tapering distally. Proximal-distal length about 5.5 mm. Apparently subdivided into five major elements (possibly corresponding to coxa, trochanter, femur, tibia and tarsus), all subsimilar in length, exact dimension difficult to measure, and a distal part (pretarsus?) bearing a pair of claws. Postocular segment 7 (mesothorax) with a pair (?) of well-developed appendages. General shape in lateral view elongate; tapering distally. Proximal-distal length about 6.2 mm (exact length difficult to assess). Apparently subdivided into five major elements (possibly corresponding to coxa, trochanter, femur, tibia and tarsus), all subsimilar in length, exact dimension difficult to measure; a distal part (pretarsus?) with claws is not preserved, but was most likely present. Postocular segment 8 (metathorax) with a pair of well-developed appendages. General shape in lateral view elongate; tapering distally. Proximal-distal length about 6.1 mm (exact length difficult to assess). Apparently subdivided into five major elements (possibly corresponding to coxa, trochanter, femur, tibia and tarsus), all subsimilar in length, exact dimension difficult to measure; a distal part (pretarsus?) with claws is not preserved, but was most likely present. Abdomen. Postocular segment 9 (abdominal segment 1) with a pair of well-developed appendages. General shape in lateral view elongate; tapering distally, and stronger than thoracic appendages. Proximal-distal length about 5.0 mm (exact length difficult to assess). Apparently subdivided into 7 major elements, all subsimilar in length, exact dimension difficult to measure; a distal pair of claws could not be observed. Postocular segment 10 (abdominal segment 2) with a pair (?) of well-developed appendages. General shape in lateral view elongate; tapering distally, and stronger than thoracic appendages. Proximal-distal length difficult to assess, as distal part appears to be preserved incompletely. Probably originally resembling appendage of preceding segment, i.e. subdivided into 7 major elements, all subsimilar in length; a distal pair of claws could not be observed. Postocular segment 11 (abdominal segment 3) with a pair (?) of well-developed appendages. General shape in lateral view elongate; tapering distally, and stronger than thoracic appendages. Proximal-distal length difficult to assess, as distal part appears to be preserved incompletely. Probably originally resembling appendage of preceding segment, i.e. subdivided into 7 major elements, all subsimilar in length; a distal pair of claws could not be observed. Postocular segment 12 (abdominal segment 4) with a pair (?) of well-developed appendages. General shape in lateral view elongate; tapering distally, and stronger than thoracic appendages. Proximal–distal length difficult to assess, as distal part appears to be preserved incompletely. Probably originally resembling appendage of preceding segment, i.e. subdivided into 7 major elements, all subsimilar in length; a distal pair of claws could not be observed. Postocular segment 13 (abdominal segment 5) with a pair (?) of well-developed appendages. General shape in lateral view elongate; tapering distally, and stronger than thoracic appendages. Proximal–distal length difficult to assess, but apparently about the same length as abdominal appendage 1. Probably originally resembling appendage of preceding segment, i.e. subdivided into 7 major elements, all subsimilar in length; a distal pair of claws could not be observed. Postocular segment 14 (abdominal segment 6) with a pair (?) of well-developed appendages. General shape in lateral view elongate; tapering distally, and stronger than thoracic appendages. Proximal–distal length difficult to assess, as distal part appears to be preserved incompletely. Probably originally resembling appendage of preceding segment, i.e. subdivided into 7 major elements, all subsimilar in length; a distal pair of claws could not be observed. Postocular segment 15 (abdominal segment 7) with a pair (?) of well-developed appendages. General shape in lateral view elongate; tapering distally, and stronger than thoracic appendages. Proximal–distal length difficult to assess, only a rather proximal part is preserved. Probably originally resembling appendage of preceding segment, i.e. subdivided into 7 major elements, all subsimilar in length; a distal pair of claws could not be observed. Postocular segment 16 (abdominal segment 8) possibly originally with a pair (?) of well-developed appendages, but no structure is preserved. Postocular segment 17 (abdominal segment 9) with a pair of short, conical, backward pointing appendages of slightly less than 2 mm in length. Post-ocular segment 18 (abdominal segment 10) appears to lack appendages. Taxonomic Identity of Srokalarva berthei Four possibilities exist for the possible identity of Srokalarva berthei. A first hypothesis is that Srokalarva berthei plausibly could be interpreted as an isopod or isopod-like crustacean. Division of Srokalarva berthei into three, distinctive tagma, a head, thorax and abdomen, would augur against such an affiliation. Additionally, the fivefold external organization of the head into discrete ocular, intercalary, mandibular, maxillary and labial regions, from anatomical anterior to posterior position, is a condition not seen in any crustacean. Several authors [5, 8] have indicated that Srokalarva berthei represents a myriapod. This interpretation appears based on the assumption that myriapods have a homonomous trunk tagmosis, which was reconstructed originally for Srokalarva berthei. However, myriapods do not possess a homonomous trunk tagmosis [17]. More importantly, our reinvestigation demonstrates that the trunk of Srokalarva berthei is indeed differentiated into two tagmata, a thorax with three segments and an abdomen with ten (externally visible) segments. Such a tagmosis pattern clearly indicates an insectan affinity for Srokalarva berthei. Could Srokalarva berthei represent an apterygote form instead of a larval insect? The mouthparts of Srokalarva berthei are clearly ectognathous, and an entognath affinity, typical of the Protura, Collembola and Diplura can be excluded. By virtue of its larval status, Srokalarva berthei lacks characters that would indicate an affinity to Zygentoma or Archaeognatha, or a position somewhere close to the node of Ectognatha or Pterygota. The general morphology, especially of the thorax, also does not indicate a nymphal identity, such as a hemimetabolous insect. The general morphology of Srokalarva berthei is compatible with an interpretation as an endopterygote (holometabolous) larva. Propositions that have been used to exclude an endopterygote interpretation can be shown to be misinterpretations, likely caused by fossil specimen artifacts. Major examples from publications using such features as an argument for exclusion of Srokalarva berthei from Endopterygota include the following misinterpretations and sources:There is no pronounced tagmosis into thorax and abdomen [8]. There is no sequence of leg-bearing and apodous segments [6]. There are no externally visible compound eyes or ocelli [5]. There are no claws on abdominal appendages [5]. There are no "segmented" cerci [5]. The interpretation of Srokalarva berthei as an endopterygote larva is plausible based on the alternatives to these five characters. Other features show that Srokalarva berthei is an endopterygote larva. The morphology and arrangement of the tergites demonstrate an endopterygote condition. Distinct sclerites intercalated between a larger softer, occasionally membranous, area can be seen in various endopterygote larvae, including an eruciform larva from the Early Permian of Uralian Russia [18]. Thoracic legs with few elements are indicative of the larval nature of Srokalarva berthei. We conclude that there is no character contradicting the interpretation of Srokalarva berthei as a holometabolous larva, whereas there are several characters positively and parsimoniously supporting this attribution. Given the number of details now known, Srokalarva berthei is currently the best candidate to represent a true holometabolous larva during the Middle Pennsylvanian Period. Details of Metabolarva bella also make it a plausible candidate for a holometabolous larva [10], but a detailed description of its morphology is desirable. Srokalarva berthei probably represents a late, probably ultimate, larval instar based on complete abdominal segmentation of ten evident segments, the presence of likely genital structures, and its overall size. The online version of the original article can be found under doi:10.1186/s12862-015-0428-8. Acknowledgements This is contribution 316 of the Evolution of Terrestrial Ecosystem Consortium at the Natural History, in Washington, D.C. ==== Refs References 1. Haug JT Labandeira CC Santiago-Blay JA Haug C Brown S Life habits, hox genes, and affinities of a 311 million-year-old holometabolan larva BMC Evol Biol 2015 15 208 10.1186/s12862-015-0428-8 26416251 2. Shear WA Kukalová-Peck J The ecology of Paleozoic terrestrial arthropods: the fossil evidence Can J Zool 1990 68 1807 1834 10.1139/z90-262 3. Kukalová-Peck J Naumann ID Carne PB Lawrence JF Nielsen ES Spradbery JP Taylor RW Fossil history and the evolution of hexapod structures Insects of Australia: A Textbook for Students and Research Workers 1991 2 Melbourne, Ithaca Melbourne University Press and Cornell University Press 141 179 4. Kukalová-Peck J Shabica CW Hay AA Mazon Creek insect fossils: the origin of insect wings and clues about the origin of insect metamorphosis Richardson’s Guide to the Fossil Fauna of Mazon Creek 1997 Chicago Northern Illinois University Press 194 207 5. Willmann R Fortey RA Thomas RH Advances and problems in insect phylogeny Arthropod Relationships 1997 London Chapman and Hall 270 279 6. Rasnitsyn AP Rasnitsyn AP Quick DLJ Cohors Scarabaeiformes Laicharting, 1781. The holometabolans (= Holometabola Burmeister, 1835, = Endopterygota Sharp, 1899, = Oligoneoptera Martynov, 1938) History of Insects 2002 Dordrecht Kluwer 157 254 7. Labandeira CC Santiago-Blay JA Abdominal legs of Middle Pennsylvanian Srokalarva : early expression of the Distal-less gene in holometabolous insects Geol Soc Am Abstr Prog 2002 34 6 101 102 8. Grimaldi DA Engel MS Evolution of the Insects 2005 New York Cambridge University Press 9. Nel A Roques P Nel P Prokop J Steyer JS The earliest holometabolous insect from the Carboniferous: a “crucial” innovation with delayed success (Insecta Protomeropina Protomeropidae) Ann Soc Entom France 2007 43 349 355 10.1080/00379271.2007.10697531 10. Labandeira CC Evidence for an earliest Late Carboniferous divergence time and the early larval ecology and diversification of major Holometabola lineages Entom Am 2011 117 9 21 11. Nel A Roques P Nel P Prokin AA Bourgoin T Prokop J The earliest known holometabolous insects Nature 2013 503 257 261 24132233 12. Selden PA Nudds JR Evolution of Fossil Ecosystems 2005 Chicago University of Chicago Press 13. Shabica C Hay A Richardson’s Guide to the Fossil Fauna of Mazon Creek 1997 Chicago Northern Illinois University Press 14. Walker JD Geissman JW Bowring SA Babcock LE The Geological Society of America geologic time scale Geol Soc Am Bull 2013 125 259 272 10.1130/B30712.1 15. Haug JT Briggs DEG Haug C Morphology and function in the Cambrian Burgess Shale megacheiran arthropod Leanchoilia superlata and the application of a descriptive matrix BMC Evol Biol 2012 12 art. 162 10.1186/1471-2148-12-162 16. Kristensen NP Phylogeny of the endopterygote insects, the most successful lineage of living organisms Eur J Entom 1999 96 237 253 17. Haug JT Haug C Schweigert G Sombke A The evolution of centipede venom claws – Open questions and possible answers Arthro Struc Dev 2014 43 5 16 10.1016/j.asd.2013.10.006 18. Novokshonov VG The first mecopteroids (Insecta: Papilionidea = Mecopteroidea) and the origin of scorpionflies (Panorpida = Mecoptera), with description of a legless eruciform larva from the Lower Permian of Tshekarda Paleont J 2004 38 S204 S213

PMC005xxxxxx/PMC5000463.txt

==== Front Parasit VectorsParasit VectorsParasites & Vectors1756-3305BioMed Central London 174210.1186/s13071-016-1742-8ResearchRickettsia vini n. sp. (Rickettsiaceae) infecting the tick Ixodes arboricola (Acari: Ixodidae) http://orcid.org/0000-0001-8249-4494Novakova Marketa novakova.marke@gmail.com 12Costa Francisco B. franc.borges@yahoo.com.br 3Krause Frantisek bretislavovafk@seznam.cz 4Literak Ivan literaki@vfu.cz 12Labruna Marcelo B. labruna@usp.br 31 Department of Biology and Wildlife Diseases, Faculty of Veterinary Hygiene and Ecology, University of Veterinary and Pharmaceutical Sciences Brno, Brno, Czech Republic 2 CEITEC, University of Veterinary and Pharmaceutical Sciences Brno, Brno, Czech Republic 3 Department of Preventive Veterinary Medicine and Animal Health, Faculty of Veterinary Medicine, University of São Paulo, São Paulo, Brazil 4 Breclav, Czech Republic 26 8 2016 26 8 2016 2016 9 1 46917 3 2016 5 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Recently, a new rickettsia named ‘Candidatus Rickettsia vini’ belonging to the spotted fever group has been molecularly detected in Ixodes arboricola ticks in Spain, the Czech Republic, Slovakia and Turkey, with prevalence reaching up to 100 %. The aim of this study was to isolate this rickettsia in pure culture, and to describe it as a new Rickettsia species. Methods A total of 148 ornitophilic nidicolous ticks Ixodes arboricola were collected in a forest near Breclav (Czech Republic) and examined for rickettsiae. Shell vial technique was applied to isolate rickettsiae in Vero cells. Rickettsial isolation was confirmed by optical microscopy and sequencing of partial sequences of the rickettsial genes gltA, ompA, ompB, and htrA. Laboratory guinea pigs and chickens were used for experimental infestations and infections. Animal blood sera were tested by immunofluorescence assay employing crude antigens of various rickettsiae. Results Rickettsia vini n. sp. was successfully isolated from three males of I. arboricola. Phylogenetic analysis of fragments of 1092, 590, 800, and 497 nucleotides of the gltA, ompA, ompB, and htrA genes, respectively, showed closest proximity of R. vini n. sp. to Rickettsia japonica and Rickettsia heilongjiangensis belonging to the spotted fever group. Experimental infection of guinea pigs and chickens with R. vini led to various levels of cross-reactions of R. vini-homologous antibodies with Rickettsia rickettsii, Rickettsia parkeri, ‘Candidatus Rickettsia amblyommii’, Rickettsia rhipicephali, Rickettsia bellii, and Rickettsia felis. Laboratory infestations by R. vini-infected I. arboricola larvae on chickens led to no seroconversion to R. vini n. sp., nor cross-reactions with R. rickettsii, R. parkeri, ‘Ca. R. amblyommii’, R. rhipicephali, R. bellii or R. felis. Conclusions Our results suggest that R. vini n. sp. is possibly a tick endosymbiont, not pathogenic for guinea pigs and chickens. Regarding specific phenotypic characters and significant differences of DNA sequences in comparison to the most closely related species (R. japonica and R. heilongjiangensis), we propose to classify the isolate as a new species, Rickettsia vini. Electronic supplementary material The online version of this article (doi:10.1186/s13071-016-1742-8) contains supplementary material, which is available to authorized users. Keywords TicksIxodes arboricolaTree-hole tickIxodidaeOrnitophilic ticksNidicolous ticksRickettsia viniRickettsiaeSpotted fever groupCzech Republichttp://dx.doi.org/10.13039/501100002322Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCAPES/PROEX 2327/2015Labruna Marcelo B. http://dx.doi.org/10.13039/501100006435Central European Institute of TechnologyLQ1601 2020Novakova Marketa http://dx.doi.org/10.13039/501100006435Central European Institute of TechnologyLQ1601 2020Literak Ivan issue-copyright-statement© The Author(s) 2016 ==== Body Background Rickettsiae are Gram-negative coccobacilli belonging to the family Rickettsiaceae, order Rickettsiales in the alpha subdivision of the class Proteobacteria. Rickettsia spp. have small genomes (1.1–2.1 Mb) resulted from reductive evolution caused by their obligate endosymbiotic relationship to eukaryotic cells [1]. Their host diversity is remarkably high. Although all valid species are associated with arthropods, novel genotypes have also been identified in annelids, amoebae and plants [2, 3]. A number of Rickettsia species can propagate in vertebrates, some of them cause diseases in humans and animals, to which they are transmitted by arthropod vectors such as fleas, lice, mites or ticks. Some species are considered non-pathogenic, and novel Rickettsia species reveal to be nearly cosmopolitan [4]. Originally, pathogenic rickettsiae used to be divided into two groups, the typhus group that included Rickettsia prowazekii and Rickettsia typhi, and the spotted fever group (SFG) composed by about 20 species [5]. The taxonomic position of other rickettsial species has remained unclear because of their genetic anomalies. Due to findings of intriguing variety of rickettsiae in arthropods and molecular analysis of rickettsial plasmids, the genus Rickettsia has been reclassified into SFG rickettsiae, typhus group rickettsiae, the transitional group, the Rickettsia bellii group, the Rickettsia canadensis group, and several basal groups [3, 6]. However, some authors do not support the creation of the transitional group claiming that it is not monophyletic and is unhelpful as it does not take into account epidemiological criteria [1]. Tick-borne rickettsioses are caused by rickettsiae belonging to the SFG [4]. Rapid development of molecular methods brought reversed approach to tick-borne pathogen research, when disease cases are detected years after the tick-borne microorganism was first discovered [7]. There have been species of rickettisae detected in ticks years or decades before they became associated with human illness cases, e.g. Rickettsia monacensis, Rickettsia parkeri, Rickettsia massiliae and Rickettsia slovaca [4, 8]. It is not clear if these novel tick-borne diseases were not noticed by physicians or whether they were absent. While it has been suggested that any novel described rickettsia from ticks should be considered a potential pathogen [5], many tick species just do not bite humans under natural conditions, or some rickettsial agents are just tick endosymbionts. Recently, a novel SFG rickettsia has been found by molecular methods in bird-associated ticks. It was named ‘Candidatus Rickettsia vini’ and until now it has been detected in Spain, the Czech Republic, Slovakia and Turkey [9–11]. This bacterium has been molecularly detected mainly in Ixodes arboricola ticks, in which the prevalence is high (reaching 90–100 %) [11, 12]. It has rarely been found in immature stages of Ixodes ricinus [9]. I. arboricola tick is widely distributed in the Palaearctic region. It lives in tree holes and nest boxes where it feeds on hole-breeding birds. Although this tick species does not represent a primary risk for humans, it shares several host species and overlaps in feeding period with Ixodes ricinus [13]. Therefore, tick-borne microorganisms, including ‘Ca. R. vini’, could be potentially bridged between these two tick species via co-feeding. Phylogenetic analysis based on partial sequences of four rickettsial genes (gltA, ompA, ompB, sca4) showed that ‘Ca. R. vini’ segregated closest to Rickettsia heilongjiangensis and Rickettsia japonica, supported by high bootstrap values [14]. The latter two species are causative agents of the Far East spotted fever (R. heilongjiangensis) and the Japanese spotted fever (R. japonica), and both have been reported in Asia [4]. In order to describe ‘Ca. R. vini’ as a new species, we isolated the bacterium in cell culture for the first time, and performed both molecular and phenotypical characterization of the isolates. Methods Field study in Breclav, Czech Republic Free-living I. arboricola ticks were collected manually from nest boxes during after-breeding season in Breclav, Czech Republic (48°43'N, 16°54'E, 150 m above sea level, an oak-ash flood-plain forest), an area attractive to tourists. Nesting bird species had been previously identified during the breeding season using a bird guide book [15] and confirmed according to characteristic appearance of the nest during tick collecting. Ticks were identified to species according to Nosek & Sixl [16]. Collected ticks were brought alive to the laboratory and incubated at 12 °C (relative humidity of 80 %) for 3 months and then at 24 °C (relative humidity of 80 %) for 7 days before being subjected to the hemolymph test. Hemolymph test and isolation of rickettsiae Selected individuals were tested for the presence of Rickettsia-like structures using the hemolymph test [17]. Shortly, the distal part of a tick leg was cut, then a drop of hemolymph was dried on a microscope slide and stained using Gimenez method [18]. The whole-body remnants were immediately stored at -80 °C to preserve living rickettsial organisms. Isolation of rickettsiae from the tick samples was performed according to previous protocols [19] with some modifications. Briefly, ticks were surface-sterilized by immersion in iodine-alcohol for 10 min, washed in sterile water, macerated, and resuspended in 600 μl of brain heart infusion (BHI). For each tick sample, two shell vials with a confluent monolayer of Vero cells were each inoculated with 300 μl of the BHI suspension and then centrifuged for 1 h at 700× g and 22 °C. The monolayers were washed and fed with 1 ml of minimal essential medium supplemented with 5 % of bovine calf serum (Hyclone, Logan, UT, USA) and 1 % of antibiotics and antifungal (penicillin, streptomycin and amphotericin B) and incubated at 28 °C. Every 3 days, the medium was replaced by a new medium (without antibiotics and antifungal additives), and the aspirated medium was checked for the presence of Rickettsia-like organisms by Gimenez staining. If the result was positive, the monolayer of the shell vial was harvested and inoculated into a 25 cm2 flask containing a monolayer of confluent uninfected Vero cells. Cells in the 25 cm2 flask were checked by Gimenez staining until > 90 % of them were infected, when they were harvested and inoculated into 75 cm2 flasks of Vero cells. The level of infection of cells was monitored by Gimenez staining of scraped cells from the inoculated monolayer. The rickettsial isolate was considered to be established in the laboratory after at least three passages through 75 cm2 Vero cell flasks, each achieving a proportion > 90 % of infected cells [20]. Experimental infestations and inoculations Selected larvae obtained from one egg cluster of I. arboricola were PCR-tested to confirm the presence of rickettsial DNA. Then, three tick naive chickens (denoted A, B and C) were each infested with 100 I. arboricola larvae from this cluster. Blood samples were collected from the chickens at the beginning of the infestation (day 0) and 21 days later. Two chickens (denoted D, E) and two male guinea pigs (denoted A, B), all tick naive, were each inoculated intraperitoneally with a suspension of ≈ 1 × 106 Vero cells infected with an I. arboricola rickettsial isolate derived from a fresh culture containing > 90 % infected cells. Blood samples were collected at 0 and 21 days after inoculation. The guinea pigs were examined daily for fever (if the rectal temperature was > 39.5 °C) and scrotal reactions. Serological tests Animal blood sera were individually tested by immunofluorescence assay (IFA) as described [21], employing crude antigens of five SFG rickettsiae (the I. arboricola rickettsial isolate Rv-M1A strain Breclav; Rickettsia rickettsii strain Taiaçu [22]; R. parkeri strain At24 [23]; ‘Candidatus Rickettsia amblyommii’ strain Ac37 [19]; and Rickettsia rhipicephali strain HJ5 [24]); a basal group rickettsia (R. bellii strain Mogi [22]); and one transitional group rickettsia (Rickettsia felis strain Pedreira [25]), which were prepared using whole infected Vero or C6/36 cells as previously described [21]. Sera were diluted in 2-fold increments, beginning from a 1:64 dilution, tested with fluorescein isothiocyanate-labeled rabbit anti-guinea pig IgG (Sigma-Aldrich, St. Louis, MO, USA) or anti-bird IgG-FITC conjugate (Alpha Diagnostic Intl Inc., San Antonio, TX, USA). Endpoint titers for both homologous and heterologous reactions were determined. Molecular characterization All whole-body remnants of the ticks used to inoculate shell vials and infected Vero cell 1st–4th passages were subjected to DNA extraction using the guanidine isothiocyanate technique, as described elsewhere [26], and DNA extracts were stored at -20 °C until they were used as templates for polymerase chain reaction (PCR). DNA samples were tested by a battery of PCR protocols targeting fragments of four rickettsial genes: citrate synthase gene (gltA), the 190-kDa outer membrane protein gene (ompA), the 120-kDa outer membrane protein gene (ompB), and the 17-kDa protein gene (htrA) (Table 1). Each PCR run included a negative control (2.5 μl of water) and a positive control (2.5 μl of DNA of Rickettsia parkeri strain NOD) samples. PCR products were purified by ExoSAP-IT® (USB), DNA-sequenced by Sanger dideoxy sequencing, and analyzed using BLAST [27] to determine similarities to other Rickettsia spp. available in GenBank, National Center for Biotechnology Information (NCBI) [28]. The DNA sequences obtained from the 4th passage-infected cells were submitted to the GenBank database (see below). Phylogenetic analyses were performed using the program MEGA version 6.06 in November 2015 [29]. The newly-generated partial DNA sequences (gltA, ompA, ompB, and htrA genes) were analyzed separately, and also concatenated. In both cases, nucleotides were aligned with the corresponding sequences of other Rickettsia species available in the GenBank database using MUSCLE algorithm as implemented in MEGA. The resulted alignment was checked and manually corrected. The evolutionary history was inferred using the Maximum Likelihood method based on the Tamura 3-parameter (I + G) model with 1000 replicates of random-addition taxa and tree bisection and reconnection branch swapping. All positions were weighted equally.Table 1 Primer pairs used for amplification of rickettsial genes Target gene, primer pair no., primer name Specifity Sequence Amplified fragment (nt) Reference gltA Genus Rickettsia 1 CS-78 5'-GCAAGTATCGGTGAGGATGTAAT-3' 401 [19] CS-323 5'-GCTTCCTTAAAATTCAATAAATCAGGAT-3' [19] 2 CS-239 5'-GCTCTTCTCATCCTATGGCTATTAT-3' 834 [38] CS-1069 5'-CAGGGTCTTCGTGCATTTCTT-3' [38] ompA Spotted fever group (SFG) 3 Rr190.70p 5'-ATGGCGAATATTTCTCCAAAA-3' 632 [39] 190-701 5'-GTTCCGTTAATGGCAGCATCT-3' [40] ompB Genus Rickettsia a 4 120-M59 5'-CCGCAGGGTTGGTAACTGC-3' 820 [41] 120-807 5'-CCTTTTAGATTACCGCCTAA-3' [41] htrA Genus Rickettsia 5 17k-5 5'-GCTTTACAAAATTCTAAAAACCATATA-3' 549 [38] 17k-3 5'-TGTCTATCAATTCACAACTTGCC-3' [38] aExcept for some species of basal groups (e.g. Rickettsia bellii) Morphology by light microscopy Gimenez stained hemolymph smears were examined under oil immersion (at magnification of × 1000; 10× ocular and a 100× objective). Images of Rickettsia-like structures and adjacent Vero cells were captured using Leica Microscope DM4000-B. Results Family Rickettsiaceae Pinkerton 1936 Genus Rickettsia da Rocha-Lima 1916 Rickettsia vinin. sp. Type-host: Tree-hole tick, Ixodes arboricola Schultze & Schlottke, 1930 (Acari: Ixodida: Ixodidae). Type-locality: Breclav, Czech Republic. Other localities: La Rioja, Spain; Kızılırmak Delta, Samsun, Turkey; Velky Kosir, Czech Republic; Ziar nad Hronom, Slovakia. Type-strain: The type-strain BreclavT from three I. arboricola male ticks, sampled in Breclav, Czech Republic (48°43'N, 16°54'E) in a nest box of Ficedula albicollis, is deposited at the Rickettsial Collection of the Laboratory of Parasitic Diseases of the Faculty of Veterinary Medicine, University of São Paulo, São Paulo, Brazil (culture collection codes: Rv-M1A-3P; Rv-M2B-3P; Rv-M3B-3P), and the Rickettsial Collection of the Rickettsial Zoonoses Branch of the Centers for Disease Control and Prevention (CDC), Atlanta, GA, USA (culture collection codes: Rv-M1A-2P; Rv-M2B-2P; Rv-M3B-2P). Vector: Unknown. Representative DNA sequences: GenBank: partial sequences KT187394 (gltA gene); KT326194 (ompA gene); KT187395 (ompB gene); KT187396 (htrA gene). Etymology: The name vini has been proposed by Palomar et al. [9] who first detected molecularly this bacterium at La Rioja, a vineyard region in Spain. District of Breclav, the type-locality, is also an important area of vine production in the Czech Republic. Description Rickettsia vini n. sp. is a Gram-negative, nonmotile, obligately intracellular bacterium. The organism has a typical bacillary morphology with binary fission. It grows at 28 °C on Vero cells in minimal essential medium with 5 % bovine calf serum supplement (Fig. 1). Sequencing of gltA, ompA, ompB, and htrA genes implies that this bacterium is significantly different from all recognized rickettsial species. It belongs to the SFG and is most closely related to R. japonica and R. heilongjiangensis. Rickettsia vini n. sp. is not pathogenic for chickens and guinea pigs through intraperitoneal inoculation, although it induces seroconversion in these animals (see below). The pathogenicity of this bacterium for vertebrate hosts, including humans, remains to be elucidated.Fig. 1 Vero cells infected by Rickettsia vini n. sp. strain Breclav visualized by Gimenez staining Field study A total of 35 nest boxes (32 of Ficedula albicollis, 3 of species of Paridae) were checked for the presence of ticks. One hundred forty-eight I. arboricola ticks (2 engorged nymphs, 18 males, 128 engorged females) were found in 9 (25.7 %) out of 35 nest boxes; all 9 boxes belonged to F. albicollis (arithmetic mean ± standard error: 16.4 ± 41.2 ticks per infested nest box). Although one F. albicollis nest box contained 18 male and 115 engorged female ticks, all 6 nestlings successfully fledged, which was documented during breeding season. Ixodes arboricola females were each stored in a separate tube and egg clusters were laid by 24 of them. Hundreds of larvae hatched after one month. Isolation of Rickettsia vini n. sp. All 18 male ticks were subjected to the hemolymph test; of these three were found positive for Rickettsia-like organisms within their hemocytes, and subsequently subjected to the isolation of rickettsiae by the shell vial technique. Rickettsiae were successfully isolated from all three ticks and established in Vero cell culture (Fig. 1). The three isolates were designated as Rv-M1A, Rv-M2B, and Rv-M3B. Experimental infestations, inoculations and serological tests The chickens A, B and C that were infested with R. vini-infected I. arboricola larvae remained seronegative to all seven Rickettsia species, including R. vini antigens (Table 2). A total of 15 to 17 engorged larvae were recovered from each chicken. Conversely, the chickens D, E that were inoculated with R. vini-infected Vero cells showed seroconversion for R. vini n. sp., R. rickettsii, and ‘Ca. R. amblyommii’ with titers ranging from 64 to 512 at 21 days after inoculation. Chicken E also seroconverted to R. bellii (Table 2). None of the above five chickens showed apparent signs of disease during the present study.Table 2 Homologous and heterologous endpoint titers of IgG to seven Rickettsia species in animal sera Species Chickens infested with R. vini-infected Ixodes arboricola Animals inoculated with R. vini culture Chicken A Chicken B Chicken C Chicken D Chicken E Guinea pig A Guinea pig B Rickettsia vini n. sp. –a – – 128 512 512 128 Rickettsia rickettsii – – – 64 64 512 – Rickettsia parkeri – – – – – – – ‘Ca. Rickettsia amblyommii’ – – – 128 64 256 – Rickettsia rhipicephali – – – – – – NT Rickettsia bellii – – – – 256 – – Rickettsia felis – – – – – – – a–, negative at the 1:64 serum dilution Abbreviation: NT not tested The guinea pig A showed seroconversion to R. vini, R. rickettsii and ‘Ca. R. amblyommii’ with 512, 512 and 256 endpoint titers, respectively, 21 days after intraperitoneal inoculation of R. vini-infected Vero cells. The guinea pig B seroconverted only to R. vini n. sp., with a 128 endpoint titer (Table 2). None of these guinea pigs developed fever, scrotal reactions or any other clinical alteration. Genotyping and phylogenetic analysis DNA of infected cells from the 1st to 4th rickettsial passages of all three isolates were tested by PCRs targeting the gltA, ompA, ompB, and htrA genes, and 1092, 590, 800, and 497 nucleotides (nt), respectively, of the PCR products were sequenced from each isolate. Sequences obtained from different passages of all three isolates were 100 % identical. BLAST analysis of the gltA partial sequence showed 100 % (1092/1092 nt) similarity to the corresponding sequence of two strains of R. vini from the Czech Republic and Spain (KJ626330, JF803266) [11, 14]. The ompA partial sequence revealed 100 % (590/590 nt) similarity to the corresponding sequence of R. vini from Spain (JF758828) [14]. The ompB partial sequence showed 99.3 % (764/769 nt) similarity to the corresponding sequence of Rickettsia sp. HIR/D91 (KC888953). The htrA partial sequence was 99.2 % (493/497 nt) similar to the corresponding sequence of various strains of R. rickettsii (AY281069, CP000766, CP000848, CP003305, CP003306, CP003307, CP003309, CP003311, CP003318, CP006009, CP006010, M28479) and Rickettsia philipii (CP003308). Before this study, there were no corresponding sequences of the ompB and the htrA gene fragments of R. vini in GenBank. Phylogenetic analyses were inferred from the gltA, ompA, ompB, and htrA partial sequences, with each gene analyzed separately (Additional files 1, 2, 3 and 4). Then an analysis of a concatenated dataset was carried out on an alignment that included 2979 nt (1092, 590, 800, 497 nt for the gltA, ompA, ompB, and htrA genes, respectively). In all analyses, R. vini n. sp. segregated closest to R. japonica and R. heilongjiangensis cluster, which was supported by high bootstrap values (Fig. 2).Fig. 2 Molecular phylogenetic analysis of Rickettsia vini n. sp. isolated from the tick Ixodes arboricola (Czech Republic). A total of 2979 unambiguously aligned nucleotide sites of the rickettsial genes gltA, ompA, ompB, and htrA were concatenated and subjected to analysis by the Maximum Likelihood method. The bootstrap values obtained by 1000 replicates are shown at the nodes. The tree is drawn to scale; scale-bar indicates nucleotide substitutions (%) per site. The GenBank accession numbers of the sequences included in this analysis are shown in Additional files 1, 2, 3 and 4 Discussion This study described and characterized a new species of Rickettsia, R. vini n. sp., isolated from I. arboricola ticks collected in nest-boxes in the Czech Republic. This bacterium was first detected by PCR in I. arboricola and I. ricinus immature ticks collected from birds in La Rioja, a vineyard region in Spain [9] and named ‘Ca. R. vini’ [14]. To date, this bacterium has been detected molecularly in ticks in Europe and Turkey. The Palaearctic distribution of the type-species, the tick I. arboricola predicates possibly a similar wide occurrence of R. vini n. sp. Through molecular analyses (PCR detection), infection rates of R. vini in I. arboricola ticks up to 100 % have been reported [10, 11, 14]; however, we found only three out of 18 males positive for Rickettsia-like organisms using the hemolymph test. This may be caused by higher sensitivity of PCR detection, when compared to the hemolymph test, or/and because not all R. vini-infected ticks contain rickettsiae in their hemolymph. All PCR-tested unfed larvae of I. arboricola from this study contained rickettsial DNA, indicating transovarial transmission of the rickettsial agent. All animals inoculated intraperitoneally seroconverted after 21 days, sometimes with high homologous antibody titers to R. vini n. sp. (Table 2). The guinea pig A showed cross-reactivity for R. rickettsii and ‘Ca. R. amblyommii’ antigens, while the guinea pig B reacted only to the homologous antigens. Both chickens D and E inoculated with R. vini-infected Vero cells showed homologous titers always equal or higher than heterologous titers. Cross-reactivities were observed with closely related species belonging to the SFG such as R. rickettsii and ‘Ca. R. amblyommii’, although chicken E also reacted to R. bellii, a non-SFG agent. Cross-reactivity with lower titres for heterologous antigens has also been observed in experimental studies with guinea pigs intraperitoneally inoculated by Vero cells infected with R. monteiroi, R. bellii, R. rickettsii or R. canandensis [30]. Although R. felis is phylogenetically closer than R. bellii to R. vini, no cross-reactivity with R. felis was observed. These results indicate that R. vini n. sp. possibly shares numerous antigenic constituents with other Rickettsia species, especially SFG members (Fig. 2). These findings are consistent with previous studies with mice, guinea pigs, dogs and opossums that were inoculated with different Rickettsia species [31–34]. Absence of clinical signs in R. vini-inoculated chickens D, E and guinea pigs A, B suggests that R. vini n. sp. is not pathogenic for these animals. None of the three chickens A, B, C infested by R. vini-infected larvae seroconverted, in contrary to chickens D, E that were inoculated with R. vini culture. While these results suggest a tick-symbiotical nature of R. vini, it is also possible that chickens (and guinea pigs) are just not susceptible to R. vini. If this is the case, the seroconversion of inoculated animals in the present study could be just a result of direct contact with bacterial antigens, rather than active infection. Such assumptions need to be confirmed in further studies. Finally, the non-susceptibility of chickens in the present study could be linked to the inoculation route (intraperitoneal inoculation), since other rickettsial agents were shown to cause skin lesions through intradermal inoculations of experimental animals, in contrast to no clinical alterations when the same agents were intraperitoneally inoculated [35, 36]. Moreover, our results of animal inoculations do not exclude a possible susceptibility of the bird hosts of I. arboricola to R. vini under natural conditions. The phylogenetic analyses of four rickettsial genes showed that R. vini n. sp. belongs to the SFG and is most closely related to R. japonica and R. heilongjiangensis, which is in compliance with previous studies [11, 14]. In this study, we amplified different and longer fragments of the ompB and htrA genes of R. vini that have not been previously published. R. japonica and R. heilongjiangensis are associated with various tick vectors and mammal reservoirs [4]. It has been proposed that a new Rickettsia species should not show > 99.9 %, > 99.2 %, and > 98.8 % similarity for the gltA, ompB, and ompA genes, respectively, with the most homologous validated species [37]. Similiarity values of R. vini DNA sequences with the most closely related validated species are 99.7 % for the gltA gene of R. heilongjiangensis (CP002912), 96.8 % for the ompB gene of R. japonica (AP011533), and 97.1 % for the ompA gene of R. heilongjiangensis (CP002912). These comparison values also support the recognition of R. vini as a new species. Conclusions Here we report the first isolation of ‘Ca. R. vini’ in cell culture, both molecular and morphological characterization of the isolates, experimental inoculation of laboratory guinea pigs and chickens, and experimental infestation of chickens with R. vini-infected ticks. We conclude that R. vini n. sp. is not pathogenic for chickens and guinea pigs, although direct inoculation of these animals with R. vini resulted in seroconversion. The new species described here is ecologically, geographically and molecularly distinct from any closely related validated species. Additional files Additional file 1: Maximum Likelihood phylogenetic tree based on the partial gltA gene including a sequence for Rickettsia vini n. sp. (DOCX 637 kb) Additional file 2: Maximum Likelihood phylogenetic tree based on the partial ompA gene including a sequence for Rickettsia vini n. sp. (DOCX 698 kb) Additional file 3: Maximum Likelihood phylogenetic tree based on the partial ompB gene including a sequence for Rickettsia vini n. sp. (DOCX 639 kb) Additional file 4: Maximum Likelihood phylogenetic tree based on the partial htrA gene including a sequence for Rickettsia vini n. sp. (DOCX 522 kb) We thank to Amalia Barbieri, Fernanda Nieri-Bastos and Jonas Moraes-Filho for their help with cell culture and ricketsial antigens, and Jairo Mendoza Roldan for his help with image capture. Funding Marketa Novakova and Ivan Literak were supported by project CEITEC 2020 (LQ1601) from the Czech Ministry of Education, Youth and Sports within the National Programme for Sustainability II. Marcelo B. Labruna was supported by the “Coordenação de Aperfeiçoamento de Pessoal de Nível Superior” (CAPES, Brazil). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. Availability of data and materials The datasets supporting the conclusions of this article are included within the article and its additional files. The type-strain BreclavT is deposited at the Rickettsial Collection of the Laboratory of Parasitic Diseases of the Faculty of Veterinary Medicine, University of São Paulo, São Paulo, Brazil (culture collection codes: Rv-M1A-3P; Rv-M2B-3P; Rv-M3B-3P), and the Rickettsial Collection of the Rickettsial Zoonoses Branch of the Centers for Disease Control and Prevention (CDC), Atlanta, GA, USA (culture collection codes: Rv-M1A-2P; Rv-M2B-2P; Rv-M3B-2P). Authors’ contributions MN contributed to conception of the study, collected and determined ticks used in this study, made molecular analysis of the rickettsial isolates, drafted the major part of the manuscript. FBC isolated the bacterium Rickettsia vini n. sp. from Ixodes arboricola ticks, made serologic assays, experimental animal infestations and infections, drafted significant part of the manuscript, made final approval of the version to be published. FK collected samples for this study, determined the bird species, critically revised the manuscript and provided comments and suggestions, made final approval of the version to be published. IL contributed to conception of the study, critically revised the manuscript, provided comments and suggestions and made final approval of the version to be published. MBL designed and coordinated the experiments, contributed significantly to the manuscript by editing it, providing critical comments and suggestions, made final approval of the version to be published. All authors read and approved the final version of the manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate This study was approved by the Ethics Committee on Animal Research for the Faculty of Veterinary Medicine of the University of São Paulo. ==== Refs References 1. Merhej V Raoult D Rickettsial evolution in the light of comparative genomics Biol Rev 2011 86 379 405 10.1111/j.1469-185X.2010.00151.x 20716256 2. Perlman SJ Hunter MS Zchori-Fein E The emerging diversity of Rickettsia Proc R Soc B 2006 273 2097 106 10.1098/rspb.2006.3541 16901827 3. Weinert LA Werren JH Aebi A Stone GN Jiggins FM Evolution and diversity of Rickettsia bacteria BMC Biol 2009 7 6 10.1186/1741-7007-7-6 19187530 4. Parola P Paddock CD Socolovschi C Labruna MB Mediannikov O Kernif T Update on tick-borne rickettsioses around the world: a geographic approach Clin Microbiol Rev 2013 26 657 702 10.1128/CMR.00032-13 24092850 5. Raoult D Roux V Rickettsioses as paradigms of new or emerging infectious diseases Clin Microbiol Rev 1997 10 694 719 9336669 6. Gillespie JJ Beier MS Rahman MS Ammerman NC Shallom JM Purkayastha A Plasmids and rickettsial evolution: Insight from Rickettsia felis PLoS One 2007 2 e266 10.1371/journal.pone.0000266 17342200 7. Tijsse-Klasen E Koopmans MPG Sprong H Tick-borne pathogen - reversed and conventional discovery of disease Front Public Health 2014 2 73 10.3389/fpubh.2014.00073 25072045 8. Jado I Oteo JA Aldámiz M Gil H Escudero R Ibarra V Rickettsia monacensis and human disease, Spain Emerg Infect Dis 2007 13 1405 7 10.3201/eid1309.060186 18252123 9. Palomar AM Santibáñez P Mazuelas D Roncero L Santibáñez S Portillo A Role of birds in dispersal of etiologic agents of tick-borne zoonoses, Spain, 2009 Emerg Infect Dis 2012 18 1188 91 10.3201/eid1807.111777 22709801 10. Keskin A Koprulu TK Bursali A Ozsemir AC Yavuz KE Tekin S First record of Ixodes arboricola (Ixodida: Ixodidae) from Turkey with presence of Candidatus Rickettsia vini (Rickettsiales: Rickettsiaceae) J Med Entomol 2014 51 864 7 10.1603/ME13169 25118420 11. Novakova M Bulkova A Costa FB Kristin A Krist M Krause F Molecular characterization of ‘Candidatus Rickettsia vini’ in Ixodes arboricola from the Czech Republic and Slovakia Ticks Tick Borne Dis 2015 6 330 3 10.1016/j.ttbdis.2015.02.006 25769386 12. Palomar AM Portillo A Crespo A Santibáñez S Mazuelas D Oteo JA Prevalence of ‘Candidatus Rickettsia vini’ in Ixodes arboricola ticks in the North of Spain, 2011–2013 Parasit Vectors 2015 8 110 10.1186/s13071-015-0724-6 25889739 13. Heylen DJA Van Oosten AR Devriendt N Elst J De Bruyn L Matthysen E Seasonal feeding activity of the tree-hole tick, Ixodes arboricola Parasitology 2014 141 1044 51 10.1017/S0031182014000225 24655546 14. Palomar AM Portillo A Santibáñez P Santibáñez S García-Álvarez L Oteo JA Genetic characterization of Candidatus Rickettsia vini, a new rickettsia amplified in ticks from La Rioja, Spain Ticks Tick Borne Dis 2012 3 318 20 10.1016/j.ttbdis.2012.10.025 15. Svensson L Mullarney K Zetterström D Birds of Europe 2010 2 New Jersey Princeton University Press 16. Nosek J Sixl W Central-European ticks (Ixodoidea) key for determination 1972 Graz Mitteilungen der Abteilung für Zoologie am Landesmuseum Joanneum 1972 17. Burgdorfer W Hemolymph test. A technique for detection of rickettsiae in ticks Am J Trop Med Hyg 1970 19 1010 4 4992724 18. Gimenez DF Staining rickettsiae in yolk-sac cultures Stain Technol 1964 39 135 40 10.3109/10520296409061219 14157454 19. Labruna MB Whitworth T Bouyer DH McBride J Camargo LMA Camargo EP Rickettsia bellii and Rickettsia amblyommii in Amblyomma ticks from the state of Rondônia, Western Amazon, Brazil J Med Entomol 2004 41 1073 81 10.1603/0022-2585-41.6.1073 15605647 20. Labruna MB Whitworth T Horta MC Bouyer DH McBride JW Pinter A Rickettsia species infecting Amblyomma cooperi ticks from an area in the state of São Paulo, Brazil, where Brazilian spotted fever is endemic J Clin Microbiol 2004 42 90 8 10.1128/JCM.42.1.90-98.2004 14715737 21. Horta MC Labruna MB Sangioni LA Vianna MCB Gennari SM Galvão MAM Prevalence of antibodies to spotted fever group rickettsiae in humans and domestic animals in a Brazilian spotted fever-endemic area in the state of São Paulo, Brazil: Serologic evidence for infection by Rickettsia rickettsii and another spotted fever group Rickettsia Am J Trop Med Hyg 2004 71 93 7 15238696 22. Pinter A Labruna MB Isolation of Rickettsia rickettsii and Rickettsia bellii in cell culture from the tick Amblyomma aureolatum in Brazil Ann N Y Acad Sci 2006 1078 523 30 10.1196/annals.1374.103 17114770 23. Silveira I Pacheco RC Szabó MPJ Ramos HGC Labruna MB Rickettsia parkeri in Brazil Emerg Infect Dis 2007 13 1111 3 10.3201/eid1307.061397 18214195 24. Labruna MB Pacheco RC Richtzenhain LJ Szabó MPJ Isolation of Rickettsia rhipicephali and Rickettsia bellii from Haemaphysalis juxtakochi ticks in the state of São Paulo, Brazil Appl Env Microbiol 2007 73 869 73 10.1128/AEM.02249-06 17142361 25. Horta MC Labruna MB Durigon EL Schumaker TTS Isolation of Rickettsia felis in the mosquito cell line C6/36 Appl Environ Microbiol 2006 72 1705 7 10.1128/AEM.72.2.1705-1707.2006 16461734 26. Chomkzynski P A reagent for the single-step simultaneous isolation of RNA, DNA and proteins from cell and tissue samples Biotechniques 1993 15 532 7 7692896 27. Altschul SF Gish W Miller W Myers EW Lipman DJ Basic local alignment search tool J Mol Biol 1990 215 403 10 10.1016/S0022-2836(05)80360-2 2231712 28. Geer LY Marchler-Bauer A Geer RC Han L He J He S Liu C Shi W Bryant SH The NCBI BioSystems database Nucleic Acids Res 2010 38 D492 6 10.1093/nar/gkp858 19854944 29. Tamura K Stecher G Peterson D Filipski A Kumar S MEGA6: Molecular evolutionary genetics analysis version 6.0 Mol Biol Evol 2013 30 2725 9 10.1093/molbev/mst197 24132122 30. Pacheco RC Moraes-Filho J Marcili A Richtzenhain LJ Szabó MPJ Catroxo MHB Rickettsia monteiroi sp. nov., infecting the tick Amblyomma incisum in Brazil Appl Environ Microbiol 2011 77 5207 11 10.1128/AEM.05166-11 21685169 31. Horta MC Sabatini GS Moraes-Filho J Ogrzewalska M Canal RB Pacheco RC Experimental infection of the opossum Didelphis aurita by Rickettsia felis , Rickettsia bellii , and Rickettsia parkeri and evaluation of the transmission of the infection to ticks Amblyomma cajennense and Amblyomma dubitatum Vector Borne Zoonotic Dis 2010 10 959 67 10.1089/vbz.2009.0149 20455783 32. Philip RN Casper EA Burgdorfer W Gerloff RK Hughes LE Bell EJ Serologic typing of rickettsiae of the spotted fever group by microimmunofluorescence J Immunol 1978 121 1961 8 101593 33. La Scola B Raoult D Laboratory diagnosis of rickettsioses: current approaches to diagnosis of old and new rickettsial diseases J Clin Microbiol 1997 35 2715 27 9350721 34. Piranda EM Faccini JLH Pinter A Saito TB Pacheco RC Hagiwara MK Labruna MB Experimental infection of dogs with a Brazilian strain of Rickettsia rickettsii : clinical and laboratory findings Mem Inst Oswaldo Cruz 2008 103 696 701 10.1590/S0074-02762008000700012 19057821 35. Socolovschi C Audoly G Raoult D Connection of toxin-antitoxin modules to inoculation eschar and arthropod vertical transmission in Rickettsiales Comp Immunol Microbiol Infect Dis 2013 36 199 209 10.1016/j.cimid.2013.01.001 23414774 36. La Scola B Bechah Y Lepidi H Raoult D Prediction of rickettsial skin eschars in humans using an experimental guinea pig model Microb Pathog 2009 47 128 33 10.1016/j.micpath.2009.06.004 19527779 37. Fournier PE Raoult D Current knowledge on phylogeny and taxonomy of Rickettsia spp Ann N Y Acad Sci 2009 1166 1 11 10.1111/j.1749-6632.2009.04528.x 19538259 38. Labruna MB McBride JW Bouyer DH Camargo LMA Camargo EP Walker DH Molecular evidence for a spotted fever group Rickettsia species in the tick Amblyomma longirostre in Brazil J Med Entomol 2004 41 533 7 10.1603/0022-2585-41.3.533 15185961 39. Regnery RL Spruill CL Plikaytis BD Genotypic identification of rickettsiae and estimation of intraspecies sequence divergence for portions of two rickettsial genes J Bacteriol 1991 173 1576 89 1671856 40. Roux V Fournier PE Raoult D Differentiation of spotted fever group rickettsiae by sequencing and analysis of restriction fragment length polymorphism of PCR-amplified DNA of the gene encoding the protein rOmpA J Clin Microbiol 1996 34 2058 65 8862558 41. Roux V Raoult D Phylogenetic analysis of members of the genus Rickettsia using the gene encoding the outer-membrane protein rOmpB (ompB ) Int J Syst Evol Microbiol 2000 50 1449 55 10.1099/00207713-50-4-1449 10939649

PMC005xxxxxx/PMC5000464.txt

==== Front Infect Agent CancerInfect. Agents CancerInfectious Agents and Cancer1750-9378BioMed Central London 9610.1186/s13027-016-0096-3Research ArticlePrevalence of human papillomavirus in saliva of women with HPV genital lesions http://orcid.org/0000-0002-9072-1148Visalli Giuseppa +39 090 221 3349gvisalli@unime.it 1Currò Monica monica.curro@unime.it 1Facciolà Alessio alessiof1976.af@gmail.com 1Riso Romana romy2184@yahoo.it 1Mondello Placido pmondello@virgilio.it 2Laganà Pasqualina plagana@unime.it 1Di Pietro Angela adipietr@unime.it 1Picerno Isa ipicerno@unime.it 1Spataro Pasquale pasquale.spataro@unime.it 11 Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Via C. Valeria, Gazzi, 98100 Messina, Italy 2 Riuniti Papardo Piemonte Hospital, Messina, Italy 26 8 2016 26 8 2016 2016 11 1 4813 5 2016 26 7 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The human papilloma viruses (HPVs) are DNA viruses associated with benign and malignant lesions of skin and mucous membranes. The HPVs has been implicated as the cause of virtually all cervical cancers worldwide but studies showed that these viruses can cause numerous cancers in several tissues including Oral Squamous Cell Carcinoma (OSCC). At least 90 % of HPV-positive OSCCs are associated with high-risk (or oncogenic) HPV-16 and oral infection confers an approximate 50-fold increase in risk for HPV-positive OSCC. HPV-positive OSCCs are associated with sexual behaviors in contrast to HPV-negative OSCCs that are associated with chronic tobacco and alcohol use. The aim of this study was to estimate the prevalence of HPV-DNA in saliva samples collected from women in which it has been previously established the HPV infection of the cervix with relative genotyping and, then, to study the possible correlation. Methods Saliva samples were collected from 100 women with HPV cervical lesions, aged between 22 and 52 years old, and 25 healthy women with normal cytology (control group), aged between 20 and 49 years old. PCR assay was used to detect HPV DNA. Results The prevalence of oral HPV infection in saliva samples was 24 % in women with HPV cervical lesions while in the control group was 8 %. It has been demonstrated a strong association between high grade squamous intraepithelial lesion and oral infection due to HPV16 and 18, that are the most frequently detected HPV genotypes. Conclusion This study shows that patients with genital HPV infection are at risk for oral infection and, consequently, for the development of OSCC. Keywords HPVHSILSalivaHead-neck cancerissue-copyright-statement© The Author(s) 2016 ==== Body Background The human papilloma viruses (HPVs) are DNA viruses that infect squamous epithelial cells. They constitute a group of more than 100 different genotypes associated with benign and malignant lesions of skin and mucous membranes. These viruses are divided in two groups on the basis of their epidemiological association with the development of cervical carcinoma: high-risk HPVs, that include the genotypes 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66 and 68 and low-risk HPVs such as the genotypes 6, 11, 42, 43 and 44. The HPV-DNA contains sequences that encodes two proteins with oncogenic capacity, E6 and E7, that exhibit their effect by disrupting the function of two tumor suppressor genes, p53 and pRb respectively, causing defective cell apoptosis and uncontrolled cell growth [1]. The HPVs has been implicated as the cause of virtually all cervical cancers worldwide [2] although they can infect several cell types causing various intraepithelial neoplasias [3–6]. Oral cancer holds the eighth position in the cancer incidence ranking worldwide [7]. Of all head and neck cancers, Oral Squamous Cell Carcinoma (OSCC) is the most common malignant epithelial neoplasia of oral cavity (90 %); this represent approximately 5 % in men and 2 % in women considering all malignancies [8]. At least 90 % of HPV-positive OSCCs are associated with high-risk (or oncogenic) HPV-16 [9] and oral infection confers an approximate 50-fold increase in risk for HPV-positive OSCC [3]. The incidence of OSCC has significantly increased over the last 3 decades in several countries, in particular, the incidence of HPV-positive OSCC increased by 225 % (from 0.8 per 100 000 to 2.6 per 100 000), predominantly among young individuals, and white men [10]. HPV-positive OSCCs are associated with sexual behavior in contrast to HPV-negative OSCCs that are associated with chronic tobacco and alcohol use [3]. Recently, besides the traditional risk factors for developing oropharyngeal cancer (tobacco use and heavy alcohol consumption), HPVs are identified as an independent risk factor in the onset of pre-cancerous and cancerous oropharyngeal lesions. It is likely, in fact, that HPV may modulate the malignancy process in some tobacco- and alcohol-induced oropharyngeal cancers, but may also be the primary oncogenic factor for inducing carcinogenesis in a subset of patients without these traditional risk factors [3, 4]. Of all the HPV genotypes, 24 are involved in the development of benign and malignant lesions of the oral cavity [11, 12]. In particular, HPV16, and to a lesser extent HPV18, are most commonly identified from oral biopsies [13, 14]. International studies have evaluated HPV prevalence in healthy adults using biopsy samples, revealing prevalence rates that ranged from 0 to 15 % [15, 16] and in healthy adult saliva and oral lavage samples, revealing prevalence rates between 2.8 and 25 % [13, 17, 18]. A recent systematic review of the literature showed oral HPV16 prevalence was 1.3 % among healthy individuals and appeared to differ by geographic region, although significant heterogeneity between studies due to in part to differences in specimen collection, processing and testing limited conclusive interpretation of the data [19]. There is limited information about the natural history of oral HPV infection, but since oral HPV16 infection is associated with this cancer, it is important to estimate the proportion of healthy individuals with oral HPV infection [19]. The aim of this study was to estimate the prevalence of HPV-DNA in saliva samples collected from women in which it has been previously established the HPV infection of the cervix with relative genotyping and, then, to study the possible correlation. Methods Patients This study enrolled 100 women with HPV genital lesions and 25 healthy women (control group), selected from a group of 280 women that went to the Gynaecological Unit of the Riuniti Papardo-Piemonte Hospital, in Messina, for routine gynaecological screening between July 2014-October 2015. The control group was selected on the base of negative Pap-Test from last 3 years. None of the women enrolled in the study was vaccinated for HPV. The gynaecologist, after making sure of the absence of lesions in the oral cavity, had provided to us a saliva sample and all the clinical information of patients. After having received their written informed consent, a detailed anonymous questionnaire was administered in order to collect information on age, gender, smoking, drinking and lifetime sexual activity. Sample collection and DNA isolation Participants were asked to sit comfortably in an upright position and tilt their heads down slightly to pool saliva in the mouth. The first expectoration was discarded to eliminate food debris and unwanted substances contaminating the sample that may cause analytical inaccuracy. Participants were asked, just after, to briefly (for 30 s) refrain from swallowing and expectorate however much saliva was in the mouth from a single expectoration into a pre-labelled sterile container and ~ 2 mL saliva was collected. The samples were then immediately refrigerated to minimize degradation of salivary proteins until further processing. To process, the oral rinse was centrifuged at 3,000 g for 10 min at 4 °C, the supernatant was removed and the pellet was resuspended in 10 ml of sterile normal saline; the centrifugation was repeated and the salivary pellet was stored at -80 °C until DNA purification. DNA extraction DNA was extracted from saliva cellular pellets using Puregene DNA purification system (Qiagen, Milan, Italy) according to manufacturer’s instructions. DNA concentration and quality were estimated by spectrophotometer measurements of absorbance at 260 and 280 nm and electrophoresis. Detection of HPV in the saliva sample Total saliva DNA was tested for HPV DNA by a PCR assay using the consensus primers MY09/MY11, which amplify a fragment of 450 bp within the L1 gene region of the viral genome (Table 1).Table 1 List of primers and annealing temperatures used in this study Primer name Sequence (5’ → 3’) Annealing temperature (°C) Fragment lenght (bp) MY09 CGTCCMARRGGAWACTGATC 58 450 MY11 GCMCAGGGWCATAAYAATGG HPV6f TAGTGGGCCTATGGCTCGTC 55 280 HPV6r TCCATTAGCCTCCACGGGTG HPV11f GGAATACATGCGCCATGTGG 58 360 HPV11r CGAGCAGACGTCCGTCCTCG HPV16f TGCTAGTGCTTATGCAGCAA 55 152 HPV16r ATTTACTGCAACATTGGTAC HPV18f AAGGATGCTGCACCGGCTGA 58 216 HPV18r CACGCACACGCTTGGCAGGT HPV31f ATGGTGATGTACACAACACC 55 514 HPV31r GTAGTTGCAGGACAACTGAC HPV33f ATGATAGATGATGTAACGCC 55 455 HPV33r GCACACTCCATGCGTATCAG HPV45f ATTTCACAGCATAGCTGGACAGTA 55 100 HPV45r CTATACTTGTGTTTCACTACGTCT ß-globin f GAAGAGCCAAGGACAGGTAC 57 268 ß-globin r CAACTTCATCCACGTTACC Each PCR run included a negative (sterile water substituted for DNA) and a positive (DNA sample of an HPV type 16 carrier) control to monitor contamination and overall end point sensitivity. In parallel, each sample was amplified for β-globin to control for DNA integrity. PCR reactions were carried out in a total volume of 50 μl containing purified DNA (200 ng), 1x PCR Buffer, 3 mM MgCl2, 1 U of Taq DNA polymerase, 0.2 mM of dNTP, and 0.3 μM of each primer for HPV genome (MY09/MY11) or β -globin. Amplification was performed in a Hybaid PCR sprint thermocycler with the following profile: an initial denaturation step at 94 °C for 10 min, followed by 40 cycles of denaturation at 94 °C for 1 min, primer annealing at 58 °C for 1 min, and extension at 72 °C for 1 min; finally, an extension step of 7 min at 72 °C. The PCR products were analyzed by 2 % agarose gel electrophoresis, stained with ethidium bromide and visualized with ultraviolet transilluminator. Then, HPV-positive samples were amplified with a set of seven different-HPV-type specific primers. The sequences of primers and annealing temperatures used are given in Table 1. Statistical analyses The association between HPV infection and socio-clinical variables was assessed using chi-square tests, evaluating the Odds Ratio (OR) and the 95 % Confidence Interval (CI). Significance was assessed at the p < 0.05 level. All analyses were performed using Prism 4.0 software. Results Table 2 shows information on age, gender, smoking, drinking, dietary and sexual habits obtained by anonymous questionnaire.Table 2 Behavioural factors of studied subjects Variable HPV negative HPV positive Age media at first sexual intercourse 20 17 Sexual promiscuity   Yes 0 9   No 25 91 Oral sex habit   Yes 3 15   No 22 85 Use of sex-toys   Yes 0 2   No 25 98 Smoking habit   Yes 7 38   No 18 62 Alcohol consumption   Yes 8 40   No 17 60 HPV vaccine   Yes 0 0   No 25 100 Coinfections   Yes 0 23   No 25 77 Saliva samples were collected from 100 women with HPV cervical lesions, aged between 22 and 52 years old, and 25 healthy women with normal cytology (control group), aged between 20 and 49 years old. In particular, in women with HPV cervical lesions, according to the Bethesda System Cytology Classification, on the basis of lesions, condylomas accounted for 47 % of the women, low-grade squamous intra-epithelial lesions (LSILs) for 28 % and high-grade squamous intra-epithelial lesions (HSILs) for 25 %. The information on cervical HPV genotyping supplied by gynaecologist showed that 42 samples were positive for low-risk genotypes, and the remaining 58 samples were positive for high-risk genotypes. Of all HPV cervical samples, 25 were positive for more than one HPV type. Considering single and multiple infections, HPV 16 was the most frequent type (19 samples), followed by types 6 (13 samples), 45 and 11 (8 samples each), 81 (6 samples), 18, 52 and 31 (4 samples each). The concentration of DNA isolated from all collected saliva samples was between 100 and 300 ng/μL. Absorbance measurements and A260/A280 ratio analysis confirmed the purity of the DNA isolates, which averaged between 1.7 and 2.0. The results of PCR with MY09/MY11 primers showed that the HPV positive saliva samples were 24 in women with HPV cervical lesions and 2 in the control group. Of these positive samples, the characterization of HPV genotype showed that, in women with HPV cervical lesions, 9 woman had a multiple infection (more genotypes simultaneously), 8 women were infected with one genotype while 7 women were positive for MY09/MY11 but no specific genotype between those tested was detected. In the control group, 1 woman was infected with one genotype and 1 woman was positive for MY09/MY11 but no specific genotype between those tested was detected (Fig. 1a).Fig. 1 a Women infected by multiple genotypes simultaneously, one genotype and unknown genotype in saliva samples. b Genotype characterization of most frequent HPVs in saliva of women with HPV genital lesions and in control group The Fig. 1b shows the genotype characterization, HPV 16 was the most frequent followed by the 18 and then from 45. The percentage of positivity to low-risk HPV infection (caused by HPV 6/11) was about 5.26 %. To investigate in the HPV positive cervical group a potential risk factor promoting the presence of the virus in the saliva we correlated this data with the information collected in the questionnaire. There was no statistical significance of association between the HPV positivity and patients’ age, smoking and drinking alcohol. Other social and sexual behaviors were not significantly associated with the detection of HPV DNA in saliva samples. Analyzing the data of saliva HPV positivity and cervical clinical data we revealed a correspondence of genotypes between saliva and cervix in case of infections by HPV 16 and 18 supported by a significant increase of saliva HPV positivity in women with high-grade cervical lesions (P = 0.0069; OR = 3.747; 95 % CI: 1.39–10.09) (Fig. 2).Fig. 2 Comparison of the HPV positivity frequency in oral fluid between HSIL positive and negative groups Discussion The diagnosis of cervical HPV infections generally is not accompanied by investigations in different sites such as the oral cavity, except in the presence of visible lesions. Our results show that patients with genital HPV infection are at risk for oral infection not always associated with injuries. The absence of clinical signs in the oral cavity of these patients suggests a subclinical infection, and a molecular assay might thus be necessary to diagnose it. Highly conserved regions in different parts of the viral genome have enabled the development of general or consensus PCR primer sets which allow the detection of a broad spectrum of different HPV genotypes. However, differences in malignant potential mean that it is particularly important to accurately identify infections with the high-risk HPV genotypes. After amplification with general or consensus primers, additional techniques are necessary to identify the underlying HPV genotype [20, 21]. In the present study, we performed a careful oral clinical examination of all patients; no injury was found. We chose to investigate women with cervical HPV but no visible lesions in the oral cavity in order to demonstrate the presence of the virus in saliva even in the absence of evident clinical signs. This finding indicates that oral examination alone can not exclude the possibility of oral HPV infection. A link between human papillomavirus and oropharyngeal cancer was suggested more than 20 years ago [22]. Recent studies of healthy children and adults have found an oral prevalence of high-risk HPV strains, ranging between 2.5 and 5 % [17, 19] while previous studies revealed oral-HPV in 20.7 % of women with concomitant HPV-cervical lesions [13, 23]. Our study highlights that women with a prior histopathologic diagnosis of cervical HPV are at high risk for subclinical oral HPV, as indicated by the presence of the virus in the oral cavity of 24 % of the patients. In particular, 70 % were positive to high-risk (HPV 16-18-31-33-45) and low-risk (6–11) most frequent HPV genotypes. A significant proportion (30 %) of subjects has not been characterized; we assume that the positivity could be due to infection with other less frequent genotypes. Despite the wide distribution of HPV in general population, we found a low positivity in the control used in this study. Previous studies have shown that current smoking (and intensity) is associated with oral HPV infection [24, 25]. Actually, even if we did not obtain a significative statistical correlation between smoking habit and oral infection, probably because the studied women were occasional smokers, it cannot be excluded a possible synergy between these two factors. This hypothesis is suggested by the well known oxidative damage caused by smoke that is an important risk factor for the HPV infection as previously shown [26]. Moreover, oral sexual behaviors have been associated with oral HPV infection and transmission of other viral infections, such as herpesviruses (HSV) [27]. The majority of the women examinated in our study stated that don’t have oral sexual habits but we think that this is a false finding, due to the social conditioning; this is suggested by the correlation between cervical and oral genotypes found in our study. A multicenter study revealed a percentage of the HPV detection in oral cancer specimens higher among subjects who have oral sexual habits and/or sexual promiscuity [13]. Conclusion The transmission in the oral cavity of HPV and, consequently, the risk of oral cancer is increased in women with cervical cancer and in their spouses [13, 28]; this finding suggests a cross-transmission between the oral cavity and genitals. Our results, in accordance with the cited studies, highlight the need to perform an oral screening test in the women with cervical high risk-HPV lesions. The correlation between these two anatomic sites could be consequent to genetic predisposition and/or conditions of low immune response such as HIV infection [29, 30] that probably favor the colonization and the persistence of oral HPV [31]. To prevent the cross-transmission, it could be useful focusing the attention on a correct health education to reduce the risk of oral and, in general, head and neck cancer developing. It is important, in our opinion, increase not only correct sexual behaviors but, in general, healthy lifestyle. The US Centers for Disease Control and Prevention (CDC) currently recommends routine HPV vaccination for females aged 9 to 26 years and males aged 9 to 21 years for the prevention of ano-genital warts and cancers based on demonstrated efficacy in randomized clinical trials [32, 33]. Current vaccines approved by the FDA prevent infections with HPV types 16 and 18, the two high-risk HPVs that cause about 70% of cervical cancers and the most part of the other HPV-associated cancers [10, 34]. Even if the vaccine efficacy against oral HPV infection is unknown, and therefore the vaccination cannot currently be recommended for the primary prevention of oropharyngeal cancer, this practice could be equally useful in the prevention of this kind of cancer considering that the most detected oral HPV genotypes, in our study, were HPV-16 and 18 and the strong demonstrated correlation between HSIL and oral HPV positivity. Abbreviations HPV, human papillomavirus; OSCC, oral squamous cell carcinoma; HSIL, high grade squamous intraepithelial lesion; LSIL, low grade squamous intraepithelial lesion; HSV, herpesvirus; CDC, center for disease control and prevention; FDA, Food and Drug Administration Acknowledgement None. Funding This study was supported only by Departmental funding. Availability of data and materials The data we wish sharing are already exposed in Table 2. We are not authorized to share the clinical data of the patients. Authors’ contributions GV and MC identified the endpoints analyzed and prepared the figures and tables; GV, RR and AF contributed to the acquisition, analysis and interpretation of data; PM recruited the patients and collected clinical data; IP and PS designed the study and analyzed the data; AD and PL helped to interpret the data; GV, RR and AF wrote the paper. All authors have read and approved the final version of the manuscript. Competing interests The authors declare that they have no competing interests. Ethics approval and consent to participate All tested women filled an informant consent reporting all the information about the research. ==== Refs References 1. Duensing S Münger K Mechanisms of genomic instability in human cancer: Insights from studies with human papillomavirus oncoproteins Int J Cancer 2004 109 2 157 162 10.1002/ijc.11691 14750163 2. Clifford GM Smith JS Plummer M Muñoz N Franceschi S Human papillomavirus types in invasive cervical cancer worldwide: a metaanalysis Br J Cancer 2003 88 63 73 10.1038/sj.bjc.6600688 12556961 3. Gillison ML D’Souza G Westra W Distinct risk factor profiles for human papillomavirus type 16-positive and human papillomavirus type 16-negative head and neck cancers J Natl Cancer Inst 2008 100 6 407 420 10.1093/jnci/djn025 18334711 4. Miller CS Johnstone BM Human papillomavirus as a risk factor for oral squamous cell carcinoma: a meta-analysis, 1982-1997 Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2001 91 622 635 10.1067/moe.2001.115392 11402272 5. Rezazadeh A Laber DA Ghim SJ Jenson AB Kloecker G The role of human papilloma virus in lung cancer: a review of the evidence Am J Med Sci 2009 338 1 64 67 10.1097/MAJ.0b013e3181a393ba 19593105 6. Shukla S Bharti AC Mahata S Hussain S Kumar R Hedau S Das BC Infection of human papillomaviruses in cancers of different human organ sites Indian J Med Res 2009 130 3 222 233 19901431 7. Moore MA Ariyaratne Y Badar F Bhurgri Y Datta K Mathew A Gangadharan P Cancer epidemiology in South Asia - past, present and future Asian Pac J Cancer Prev 2009 11 49 66 20553068 8. Silverman S Jr Silverman S Jr Epidemiology Oral Cancer 4th ed Hamilton 1998 Ontario, Canada BC Decker Inc 1 6 9. Kreimer AR Clifford GM Boyle P Franceschi S Human papillomavirus types in head and neck squamous cell carcinomas worldwide: a systematic review Cancer Epidemiol Biomarkers Prev 2005 14 2 467 475 10.1158/1055-9965.EPI-04-0551 15734974 10. Chaturvedi AK Engels EA Pfeiffer RM Hernandez BY Xiao W Kim E Jiang B Human papillomavirus and rising oropharyngeal cancer incidence in the United States J Clin Oncol 2011 29 32 4294 4301 10.1200/JCO.2011.36.4596 21969503 11. Boy S Van Rensburg EJ Engelbrecht S Dreyer L van Heerden M van Heerden W HPV detection in primary intra-oral squamous cell carcinomas − commensal, a etiological agent or contamination? J Oral Pathol Med 2006 35 86 90 10.1111/j.1600-0714.2006.00385.x 16430738 12. Shillitoe EJ The role of viruses in squamous cell carcinoma of the oropharyngeal mucosa Oral Oncol 2009 45 351 355 10.1016/j.oraloncology.2008.08.001 18952492 13. Herrero R Castellsagué X Pawlita M Lissowska J Kee F Balaram P Rajkumar T Human papillomavirus and oral cancer: The International Agency for Research on Cancer multicenter study J Natl Cancer I 2003 95 1772 1783 10.1093/jnci/djg107 14. Ostwald C Rutsatz K Schweder J Schmidt W Gundlach K Barten M Human papillomavirus 6/11, 16 and 18 in oral carcinomas and benign oral lesions Med Microbiol Immunol 2003 192 3 145 148 10.1007/s00430-002-0161-y 12920590 15. Bouda M Gorgoulis VG Kastrinakis NG Giannoudis A Tsoli E Danassi-Afentaki D Foukas P High risk HPV types are frequently detected in potentially malignant and malignant oral lesions, but not in normal oral mucosa Mod Pathol 2000 13 6 644 653 10.1038/modpathol.3880113 10874669 16. González JV Gutiérrez R Keszler A Colacino Mdel C Alonio LV Teyssie AR Picconi MA Human papillomavirus in oral lesions Medicina (B Aires) 2007 67 4 363 368 17891932 17. D’Souza G Kreimer AR Viscidi R Pawlita M Fakhry C Koch WM Westra WH Case-control study of human papillomavirus and oropharyngeal cancer N Engl J Med 2007 356 19 1944 1956 10.1056/NEJMoa065497 17494927 18. Seaman WT Andrews E Couch M Kojic EM Cu-Uvin S Palefsky J Deal AM Detection and quantitation of HPV in genital andoral tissues and fluids by real time PCR Virol J 2010 7 194 10.1186/1743-422X-7-194 20723234 19. Kreimer AR Bhatia RK Messeguer AL González P Herrero R Giuliano AR Oral human papillomavirus in healthy individuals: a systematic review of the literature Sex Transm Dis 2010 37 6 386 391 20081557 20. Gravitt PE Peyton CL Alessi TQ Wheeler CM Coutlée F Hildesheim A Schiffman MH Improved amplification of genital human papillomaviruses J Clin Microbiol 2000 38 357 361 10618116 21. Sasagawa T Minemoto Y Basha W Yamazaki H Nakamura M Yoshimoto H Sakaike J A new PCR-based assay amplifies the E6–E7 genes of most mucosal human papillomaviruses (HPV) Virus Res 2000 67 127 139 10.1016/S0168-1702(00)00137-4 10867192 22. Hobbs CG Sterne JA Bailey M Heyderman RS Birchall MA Thomas SJ Human papillomavirus and head and neck cancer: a systematic review and meta-analysis Clin Otolaryngol 2006 31 259 266 10.1111/j.1749-4486.2006.01246.x 16911640 23. Giraldo P Gonçalves AK Pereira SA Barros-Mazon S Gondo ML Witkin SS Human papillomavirus in the oral mucosa of women with genital human papillomavirus lesions Eur J Obstet Gynecol Reprod Biol 2006 126 104 106 10.1016/j.ejogrb.2005.09.009 16324781 24. Castellsagué X Munoz N Chapter 3: cofactors in human papillomavirus carcinogenesis: role of parity, oral contraceptives, and tobacco smoking J Natl Cancer Inst Monogr 2003 31 20 28 10.1093/oxfordjournals.jncimonographs.a003477 12807941 25. Arnson Y Shoenfeld Y Amital H Effects of tobacco smoke on immunity, inflammation and autoimmunity J Autoimmun 2010 34 3 258 265 10.1016/j.jaut.2009.12.003 26. Visalli G Riso R Facciolà A Mondello P Caruso C Picerno I Di Pietro A Higher levels of oxidative DNA damage in cervical cells are correlated with the grade of dysplasia and HPV infection J Med Virol 2016 88 2 336 344 10.1002/jmv.24327 26174792 27. Edwards S Carne C Oral sex and the transmission of viral STIs Sex Transm Infect 1998 74 6 10 10.1136/sti.74.1.6 9634307 28. Rintala M Grenman S PuranenM SS Natural history of oral papillomavirus infections in spouses: a prospective Finnish HPV family study J Clin Virol 2006 35 89 94 10.1016/j.jcv.2005.05.012 16112613 29. Termine N Giovanelli L Matranga D CalecaM BC Perino A Oral human papillomavirus infection in women with cervical HPV infection: new data from an Italian cohort and a metanalysis of the literature Oral Oncol 2011 47 244 250 10.1016/j.oraloncology.2011.02.011 21429788 30. Marais DJ Passmore JA Denny L Sampson C Allan BR Williamson AL Cervical and oral human papillomavirus types in HIV-positive and negative women with cervical disease in South Africa J Med Virol 2008 80 953 959 10.1002/jmv.21166 18428143 31. Adamopoulou M Vairaktaris E Nkenke E Avgoustidis D Karakitsos P Sioulas V Nisyrios T Prevalence of human papillomavirus in saliva and cervix of sexually active women Gynecol Oncol 2013 129 2 395 400 10.1016/j.ygyno.2013.02.015 23428459 32. Paavonen J Naud P Salmerón J Wheeler CM Chow SN Apter D Kitchener H HPV PATRICIA Study Group Efficacy of human papillomavirus (HPV)-16/18 AS04-adjuvanted vaccine against cervical infection and precancer caused by oncogenic HPV types (PATRICIA): final analysis of a double blind, randomised study in young women Lancet 2009 374 301 314 10.1016/S0140-6736(09)61248-4 19586656 33. Giuliano AR Palefsky JM Goldstone S Moreira ED Jr Penny ME Aranda C Vardas E Efficacy of quadrivalent HPV vaccine against HPV infection and disease in males N Engl J Med 2011 364 5 401 411 10.1056/NEJMoa0909537 21288094 34. Gillison ML Chaturvedi AK Lowy DR HPV prophylactic vaccines and the potential prevention of noncervical cancers in both men and women Cancer 2008 113 10 Suppl 3036 3046 10.1002/cncr.23764 18980286

PMC005xxxxxx/PMC5000466.txt

==== Front World J Surg OncolWorld J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 98210.1186/s12957-016-0982-6Case ReportInvasive ductal carcinoma of the breast with osteoclast-like giant cells and clear cell features: a case report of a novel finding and review of the literature Zagelbaum Nicole K. NicoleZagebaum@gmail.com 12Ward Michael F. IIMfwardii@gmail.com 12Okby Nader nokby@ormc.org 2Karpoff Howard hkarpoff@crystalrunhealthcare.com 21 Touro College of Osteopathic Medicine, 230 W 125th St #1, New York, NY 10027 USA 2 Orange Regional Medical Center, 707 East Main Street, Middletown, NY 10940 USA 26 8 2016 26 8 2016 2016 14 1 22711 4 2016 13 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Osteoclast-like giant cells (OLGCs) are a rare histologic finding within a tumor of the breast. Although there has been discussion as to the pathogenesis and prognosis related to this finding, our understanding of its significance remains inconclusive. Clear cells are another unique histologic finding in breast tumors and are typically associated with tumors arising in other organs such as renal cell carcinoma. Case presentation This is a case report of a 64-year-old female who presented with one tumor identified as invasive ductal carcinoma with a combination of OLGCs and clear cell features. Conclusions To our knowledge, this combination of findings has not been previously described in the literature and therefore represents another morphologic manifestation of breast carcinoma. As patients are diagnosed earlier and live longer, a growing number of these rare variants may be recognized and provide opportunities to further our understanding of the associated molecular pathways which could contribute to the possibility of therapeutic intervention. Keywords CarcinomaBreastOsteoclast-like giant cellsClear cellsissue-copyright-statement© The Author(s) 2016 ==== Body Background Breast cancer is the most commonly diagnosed noncutaneous cancer and the second leading cause of cancer death among women worldwide [1]. In the USA, the incidence of breast cancer in women increased from 105.1 per 100,000 in 1975 to 129.6 per 100,000 in 2012 [2, 3]. Simultaneously, the mortality has decreased by 30 % since the 1990s resulting in a prevalence of over 3.1 million diagnosed breast cancer cases in the USA as of 2014 [1, 4]. Breast cancer progression is a complex and multifaceted subject. Prognosis is based on a combination of factors including lymph node status, tumor size, and histology, as well as expression of hormone and growth receptors [5–7]. Histologic reports and proteomic analysis have determined that most breast malignancies arise from epithelial tissue and that ductal and lobular carcinomas make up 75 and 15 % of invasive cancers, respectively [2, 8, 9]. Several rarer subtypes including mucinous, clear cell, OLGCs, and pleomorphic carcinomas account for the remaining 10 % of all cases and continue to be relatively unexplored due to few reported cases and a lack of large statistically significant studies [10]. As the prevalence of breast cancer increases, there should be a simultaneous escalation in the number of these historically rare variants and the need to classify them appropriately as molecular pathways of varying cancers may have important implications on prognosis and treatment. Introduction to osteoclast-like giant cells OLGCs are large multinucleated cells that resemble the morphology and function of histiocytic osteoclasts found in bone [11]. They have typically been associated with several cancers including gallbladder, liver, and thyroid [12–14]. Agnatis first reported OLGCs as a component of a primary breast malignancy in 1979 [15]. They are found in only 0.5–1.2 % of all primary breast carcinomas and to date approximately 200 cases of OLGCs associated with breast malignancy have been reported [16, 17]. OLGCs have been detected mostly in association with invasive metaplastic carcinoma but may be seen with other histologic variants including lobular, tubular, mucinous, and papillary patterns [10, 16]. Introduction to clear cells Clear cells are recognized by histologic findings that result from the removal of cytoplasmic inclusions during tissue processing. Various cellular components may result in a clear appearance and histochemical staining can be used to determine the contents of the cell, although it is not routinely performed. Some common contents include lipid, mucin, or glycogen [18, 19]. Clear cells are traditionally found in carcinomas of the kidney, ovary, vagina, cervix, endometrium, and salivary glands [20–22]. Rarely, clear cells have also been identified in several types of breast carcinomas including ductal, lobular, adenocarcinoma, squamous cell carcinomas, and metastases from other organs [23, 24]. Hull first described the presence of glycogen-rich clear cells as a separate histologic category of invasive ductal carcinoma of the breast in 1981 [18]. Fewer than 150 cases have been reported in the literature as of 2014 [25]. This is a case report of a patient who presents with a previously undescribed combination of these two unique histologic categories of invasive ductal carcinoma. We also provide a review of the literature on these rare characteristics of breast carcinoma that have been previously reported in separate studies. Case presentation A 64-year-old Caucasian female with no personal or family history of breast or ovarian cancer presented for routine screening mammography. Imaging showed an irregular 4-cm mass in the upper outer quadrant of the right breast containing several pleomorphic calcifications (Fig. 1). This lesion was assigned a Breast Imaging Reporting and Data System (BIRADS) score of 4, representing a suspicious abnormality where biopsy is recommended [26]. Ultrasound (US) identified a mass with angular margins, calcifications, and hypervascularity suspicious for invasive ductal carcinoma (Fig. 2). The lesion was sampled using vacuum-assisted US-guided biopsy with a 14-gauge needle, and the biopsy was placed in 10 % neutral buffered formalin and forwarded to pathology for processing.Fig. 1 Initial MLO view mammography demonstrating an irregularly bordered mass (left, arrow). Magnified view of the right breast showing several pleomorphic microcalcifications (right, arrow) contained within the mass Fig. 2 Ultrasound image of right breast mass where several small calcifications can be seen (arrow), representing an uncommon sonographic finding Grossly, the biopsy consisted of four red yellow cylindrical fibrofatty soft tissue cores ranging from 1.5 to 1.7 cm in length. Hematoxylin and eosin (H&E) sections were microscopically examined and demonstrated invasive nests of cuboidal cells with ample amphiphilic cytoplasm. In addition, large multinucleated cells with pink cytoplasm, intracellular granular inclusions, and increased nuclear to cytoplasmic ratio were identified. Small polygonal cells with centrally located nuclei and clear cytoplasm were noted as well as areas of central necrosis and associated calcifications (Figs. 3 and 4).Fig. 3 H&E stain demonstrating invasive ductal carcinoma. a Both OLGCs (white arrows) and clear cells (black arrows) are present throughout the tumor. b Large focus of OLGCs. c Predominant clear cell features Fig. 4 H&E stain demonstrating central necrosis and associated calcifications Immunohistochemical staining demonstrated tumor cells to be positive GATA3 (Fig. 5a), confirming the lesion to be ductal cell in origin. In addition, mammaglobin was focally positive (Fig. 5b) indicating the tumor to be breast tissue and not a metastasis from another site. Smooth muscle myosin heavy chain was negative, verifying the tumor architecture to be abnormal and invasive (Fig. 5c). These overall findings were consistent with invasive ductal carcinoma with OLGCs and clear cell features. This diagnosis was corroborated by an outside, fellowship-trained breast pathologist. Further immunohistochemical staining found the sample to be positive for estrogen and progesterone receptors and negative for Human Epidermal Growth Factor Receptor 2 (HER2).Fig. 5 a Stain demonstrating positive for GATA3. b Focally positive mammaglobin stain, confirming the tumor to be breast in origin. c Stain for smooth muscle myosin heavy chain only present in arteriole walls, demonstrating neovascular changes in tumor Discussion and review of the literature Osteoclast-like giant cells OLGCs in association with breast tumors are believed to represent a fusion of several cells of monocyte lineage located in the stroma. The significance of this finding is inconclusive. The 5-year survival rate is about 70 % versus an average overall survival rate of 72 % for similarly staged breast carcinomas [3, 10]. In six cases of invasive carcinomas with OLGCs, Holland did not find an exceptionally different clinical course when compared to typical invasive carcinomas [27]. Agnantis described eight patients with similar results in terms of prognosis and outcome [15]. Other investigations have shown that the average size of an OLGC-containing breast carcinoma is 3 cm and that over one third of patients have axillary metastasis [27]. Cai reviewed 42 cases of OLGC in breast carcinoma and found a majority had a relationship to marked angiogenesis and that this finding portended a poorer prognosis [27, 28]. Much debate and speculation has gone into the origin of OLGCs and their relationship to breast cancer [15, 29]. Markopoulos hypothesized that chemotactic agents produced by the tumor may recruit histiocytes to the region, resulting in this unique histological subtype of breast carcinoma [30]. Interestingly, one study found that OLGCs isolated from an invasive breast cancer were able to digest bone directly in vitro. These were the first cells observed to resorb bone that were not directly harvested from osseous tissue. Unlike osteoclasts, which require the presence of osteoblasts to be stimulated, these OLGCs were directly activated by the presence of parathyroid hormone. Additionally, the cells were not inhibited by calcitonin, demonstrating another key distinction between OLGCs and osteoclasts [11]. These differences provide important clues into the origin of these OLGCs, and more research may be warranted to clarify the significance of these cells. Breast carcinoma with clear cell features Clear cells are a rare histologic finding in a primary breast cancer and can be seen in several tumor types. Variants reported within primary breast tumors include glycogen-rich clear cell carcinoma (GRCCC), signet-ring, lipid-filled, and secretory carcinomas. Of these, GRCCC is the most common clear cell variant in breast cancer [30]. The current diagnostic criterion for a GRCCC is debatable. One early study defined GRCCC tumors as containing greater than 50 % clear cells [31]. However, the World Health Organization (WHO) definition is a tumor in which greater than 90 % of the neoplastic cells contain clear cytoplasm filled with glycogen [10], reflecting the variability of cell composition seen in breast tumors. There is conflicting evidence regarding the survival rate of patients diagnosed with GRCCC. Some research suggests a poor prognosis. One case series found that five of its six cases had axillary lymph node involvement at the time of diagnosis and that all five of these patients succumbed to the disease within 7 years [31]. By comparison, the overall 5-year survival rate of all types of breast cancer was 89.4 % between 2005 and 2011 [32]. WHO identifies GRCCC to have a more aggressive course with axillary involvement than other ductal carcinoma variants. However, they acknowledge that prevalence is not yet sufficient to establish large multimodal studies on these relationships [10]. In contrast, Hayes matched GRCCC to other types of invasive breast carcinoma by tumor stage and grade and demonstrated no difference in outcomes [33]. Overall, the consensus is that there have not been enough reported cases to draw significant conclusions on GRCCC’s effect on patient outcomes warranting further investigation on the subject. The research in the clinical progression of GRCCC is also conflicted. A few case studies suggest low rates of recurrence following tumor excision. Hull presents a case where a patient had no axillary lymph node involved which contained any evidence of neoplasm after mastectomy [18]. Sorensen and Paulsen describe a patient without recurrence or metastasis after a follow-up period of 6 months [34]. Shirley outlines a case where no evidence of metastatic disease was found after 18 months of follow-up [35]. However, Kuroda identifies a propensity for GRCCC to metastasize in a study that aggregated over 700 cases of breast carcinoma in which 20 cases were GRCCC. In these cases, tumor size was an average of 2.6 cm and 35 % of patients had positive lymph nodes in the axillary region [36]. Other clear cell variants tend to have a more insidious progression. Signet-ring cell carcinoma of the breast contains primarily mucinous inclusions and has a 5-year survival rate of 45–60 % [37]. Lipid-rich carcinoma of the breast also has an aggressive course and poor prognosis, with a 33 % 5-year survival rate [38]. Secretory cell carcinoma of the breast has axillary lymph node metastasis in 15–30 % of all cases [19]. Overall, studies have indicated an incomplete understanding of the pathogenesis and prognosis associated with clear cell features in invasive ductal carcinoma of the breast. Additional case reports imply that underreporting as well as misdiagnosis may be prevalent. Ovanez suggests clear cell carcinoma may mimic the appearance of pseudo-lactating changes in a premenopausal female or reflect benign changes of the breast at any age [25]. Markopoulos reported a case of a woman whose mammogram revealed a 3.5-cm lobular mass which was originally misdiagnosed to be a fibroadenoma but was finally diagnosed as a clear cell carcinoma 4 years later [30]. Aboumrad identified an example where clear cells may be confused with lipid-filled macrophages in fat necrosis of the breast [39]. Metastatic clear cell carcinomas originating in other origins such as the kidney can also mimic clear cell features found in breast carcinoma [23]. Conclusions In summary, this paper outlines our current understanding of two rare variants of breast carcinoma and provides a case study involving a unique histologic finding that has not been previously reported. The significance of cytology in the clinical progression of rare tumors of the breast is incompletely understood. The literature to date suggests that certain cell types of breast cancer may correlate with a poorer prognosis. As patients are diagnosed earlier and live longer, a growing number of these rare variants may be recognized and provide opportunities to further our understanding of the associated molecular pathways which could contribute to the possibility of therapeutic intervention. We believe it is important for health practitioners to be aware of these rare tumors as they may impact the development of optimal treatment plans in the future. Abbreviations OLGCsOsteoclast-like giant cells BIRADSBreast Imaging Reporting and Data System USUltrasound H&EHematoxylin and eosin HER2Human Epidermal Growth Factor Receptor 2 GRCCCGlycogen-rich clear cell carcinoma WHOWorld Health Organization Acknowledgements Not applicable. Funding The authors received no funding for the writing of this manuscript. Availability of data and materials Not applicable. Authors’ contributions NKZ and HK participated in the conception of the paper. NKZ and MFW wrote the manuscript. NO participated in the diagnosis, processing, and interpretation of the pathological imaging. HK edited the manuscript and made revisions. All authors have read and approved the final version of the manuscript. Authors’ information NKZ is a medical student and Master of Public Health who is particularly interested in women’s health and gender disparities. Past publications include exploring factors that impact female healthcare providers’ decisions to deploy as first responders in the event of a national disaster and barriers to receiving follow-up care after diagnosis of a high-risk breast lesion. MFW is a medical student whose interests include medical education, community service and leadership. His research interests revolve around visual and multi-sensory neuroscience and functional plasticity in visuomotor regions. NO is a fellowship-trained and board-certified pathologist currently licensed to practice medicine in New York. He is the Medical Director of Tumor Sight Development, Medical Director of the Lung Cancer Tumor Site Program and Medical Director of Laboratory Services at Orange Regional Medical Center. HK is a Memorial Sloan Kettering fellowship-trained surgical oncologist. He is skilled in general and laparoscopic surgery, with a particular focus on breast surgery. He leads weekly breast oncology board meetings and is a community leader through his dedication to quality improvement and participation in the American Society of Breast Surgeons’ The Mastery of Breast Surgery Program. Competing interests The authors declare that they have no competing interests. Consent for publication Written informed consent was obtained from the patient for publication of this case report and any accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal. Ethics approval and consent to participate Not applicable. ==== Refs References 1. Cameron JL Current surgical therapy 2012 9 2. Seo P Stone JH The antineutrophil cytoplasmic antibody-associated vasculitides Am J Med 2004 117 1 39 50 10.1016/j.amjmed.2004.02.030 15210387 3. Howlader N, N.A., Krapcho M, Garshell J, Miller D, Altekruse SF, Kosary CL, Yu M, Ruhl J, Tatalovich Z,Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA. SEER Cancer Statistics Review 1975-2012. Bethesda: National Cancer Institute; 2015. 4. DeSantis CE Cancer treatment and survivorship statistics, 2014 CA Cancer J Clin 2014 64 4 252 71 10.3322/caac.21235 24890451 5. Carter CL Allen C Henson DE Relation of tumor size, lymph node status, and survival in 24,740 breast cancer cases Cancer 1989 63 1 181 7 10.1002/1097-0142(19890101)63:1<181::AID-CNCR2820630129>3.0.CO;2-H 2910416 6. van’t Veer LJ Gene expression profiling predicts clinical outcome of breast cancer Nature 2002 415 6871 530 6 10.1038/415530a 11823860 7. Elston CW Ellis IO Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up Histopathology 1991 19 5 403 10 10.1111/j.1365-2559.1991.tb00229.x 1757079 8. Society A.C. Breast cancer facts and figures 2013-2014. Atlanta: American Cancer Society Inc.; 2013. 9. Li CI Uribe DJ Daling JR Clinical characteristics of different histologic types of breast cancer Br J Cancer 2005 93 9 1046 52 10.1038/sj.bjc.6602787 16175185 10. Tavassoli FA, Devilee P. Pathology and genetics of tumours of the breast and female genital organs. Lyon: IAPS Press; 2003. Print. 11. Athanasou NA The origin and nature of stromal osteoclast-like multinucleated giant cells in breast carcinoma: implications for tumour osteolysis and macrophage biology Br J Cancer 1989 59 4 491 8 10.1038/bjc.1989.102 2713238 12. Akatsu T Gallbladder carcinoma with osteoclast-like giant cells J Gastroenterol 2006 41 1 83 7 10.1007/s00535-005-1726-5 16501862 13. Wada Y Adenocarcinoma of the liver with osteoclast-like giant cells Pathol Int 2013 63 9 476 8 10.1111/pin.12090 24200160 14. Lee JS Fine needle aspiration cytology of anaplastic carcinoma with osteoclastlike giant cells of the thyroid. A case report Acta Cytol 1996 40 6 1309 12 10.1159/000334027 8960046 15. Agnantis NT Rosen PP Mammary carcinoma with osteoclast-like giant cells. A study of eight cases with follow-up data Am J Clin Pathol 1979 72 3 383 9 10.1093/ajcp/72.3.383 474518 16. Gjerdrum LM Lauridsen MC Sorensen FB Breast carcinoma with osteoclast-like giant cells: morphological and ultrastructural studies of a case with review of the literature Breast 2001 10 3 231 6 10.1054/brst.2000.0244 14965590 17. Niu Y Breast carcinoma with osteoclastic giant cells: case report and review of the literature Int J Clin Exp Pathol 2014 7 4 1788 91 24817980 18. Hull MT Glycogen-rich clear cell carcinoma of the breast: a light and electron microscopic study Cancer 1981 48 9 2003 9 10.1002/1097-0142(19811101)48:9<2003::AID-CNCR2820480916>3.0.CO;2-Q 6271388 19. Sullivan JJ Magee HR Donald KJ Secretory (juvenile) carcinoma of the breast Pathology 1977 9 4 341 6 10.3109/00313027709094454 593733 20. Roth LM Clear-cell adenocarcinoma of the female genital tract. A light and electron microscopic study Cancer 1974 33 4 990 1001 10.1002/1097-0142(197404)33:4<990::AID-CNCR2820330414>3.0.CO;2-5 4819225 21. Silverberg SG Ultrastructure and histogenesis of clear cell carcinoma of the ovary Am J Obstet Gynecol 1973 115 3 394 400 10.1016/0002-9378(73)90596-6 4118881 22. Herbst AL Scully RE Adenocarcinoma of the vagina in adolescence. A report of 7 cases including 6 clear-cell carcinomas (so-called mesonephromas) Cancer 1970 25 4 745 57 10.1002/1097-0142(197004)25:4<745::AID-CNCR2820250402>3.0.CO;2-2 5443099 23. Hennessy BT Squamous cell carcinoma of the breast J Clin Oncol 2005 23 31 7827 35 10.1200/JCO.2004.00.9589 16258085 24. Falco G Breast metastases from a renal cell carcinoma. A case report and review of the literature Int J Surg Case Rep 2014 5 4 193 5 10.1016/j.ijscr.2014.01.019 24632302 25. Ovanez C, Crawford J, Asarian A, Xiao P. Invasive ductal carcinoma of the breast with clear cell and pseudo-lactating changes. J Surg Case Rep. 2014;2014(7):rju063. 26. Kim EK Clinical application of the BI-RADS final assessment to breast sonography in conjunction with mammography AJR Am J Roentgenol 2008 190 5 1209 15 10.2214/AJR.07.3259 18430833 27. Holland R van Haelst UJ Mammary carcinoma with osteoclast-like giant cells. Additional observations on six cases Cancer 1984 53 9 1963 73 10.1002/1097-0142(19840501)53:9<1963::AID-CNCR2820530927>3.0.CO;2-N 6704923 28. Cai G Simsir A Cangiarella J Invasive mammary carcinoma with osteoclast-like giant cells diagnosed by fine-needle aspiration biopsy: review of the cytologic literature and distinction from other mammary lesions containing giant cells Diagn Cytopathol 2004 30 6 396 400 10.1002/dc.20069 15176026 29. Shishido-Hara Y Two cases of breast carcinoma with osteoclastic giant cells: are the osteoclastic giant cells pro-tumoural differentiation of macrophages? Diagn Pathol 2010 5 55 10.1186/1746-1596-5-55 20731838 30. Markopoulos C Glycogen-rich clear cell carcinoma of the breast World J Surg Oncol 2008 6 44 10.1186/1477-7819-6-44 18442419 31. Toikkanen S Joensuu H Glycogen-rich clear-cell carcinoma of the breast: a clinicopathologic and flow cytometric study Hum Pathol 1991 22 1 81 3 10.1016/0046-8177(91)90066-X 1985082 32. Howlader N, Noone AM, Krapcho M, Miller D, Bishop K, Altekruse SF, Kosary CL, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA (eds). SEER Cancer Statistics Review, 1975-2013, National Cancer Institute. Bethesda, MD, http://seer.cancer.gov/csr/1975_2013/, based on November 2015 SEER data submission, posted to the SEER web site, April 2016. 33. Hayes MM Seidman JD Ashton MA Glycogen-rich clear cell carcinoma of the breast. A clinicopathologic study of 21 cases Am J Surg Pathol 1995 19 8 904 11 10.1097/00000478-199508000-00005 7611537 34. Sorensen FB Paulsen SM Glycogen-rich clear cell carcinoma of the breast: a solid variant with mucus. A light microscopic, immunohistochemical and ultrastructural study of a case Histopathology 1987 11 8 857 69 10.1111/j.1365-2559.1987.tb01889.x 3305289 35. Shirley SE Clear cell carcinoma of the breast with immunohistochemical evidence of divergent differentiation Ann Diagn Pathol 2002 6 4 250 6 10.1053/adpa.2002.35399 12170458 36. Kuroda H Clinical and pathological features of glycogen-rich clear cell carcinoma of the breast Breast Cancer 2005 12 3 189 95 10.2325/jbcs.12.189 16110288 37. Vahedi MH, A.-Y.R., Zabar KK. Primary signet ring cell carcinoma of the breast: a rare pathologic entity. Bahrain Med Bull. 2011;33(1):1–5. 38. Shi P Lipid-rich carcinoma of the breast. A clinicopathological study of 49 cases Tumori 2008 94 3 342 6 18705401 39. Aboumrad MH Horn RC Jr Fine G Lipid-secreting mammary carcinoma. Report of a case associated with Paget’s disease of the nipple Cancer 1963 16 521 5 10.1002/1097-0142(196304)16:4<521::AID-CNCR2820160414>3.0.CO;2-B 14010714

PMC005xxxxxx/PMC5000467.txt

==== Front BMC Public HealthBMC Public HealthBMC Public Health1471-2458BioMed Central London 355710.1186/s12889-016-3557-0Research ArticleMortality among tuberculosis patients under DOTS programme: a historical cohort study Beyene Yeshiwork dagmawit2005natnael@gmail.com 1Geresu Berhanu berhanu.grs@gmail.com 2Mulu Assefa mulubaye@gmail.com 21 Department of Nursing, College of Medicine and Health Sciences Wollo University, Dessie, Ethiopia 2 Department of Pharmacy, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia 25 8 2016 25 8 2016 2016 16 1 88326 9 2015 19 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background In high human immunodeficiency virus (HIV) prevalence population, tuberculosis (TB) is the leading cause of morbidity and mortality. HIV is driving the TB epidemic in many countries, especially those in sub-Saharan Africa. We assessed the survival time and predictors of mortality among tuberculosis patients under directly observed treatment, short course (DOTS) strategy in Dessie Referral Hospital tuberculosis clinic, Northeast Ethiopia. Method A historical cohort design was utilized to assess survival time and determinants of mortality. A total of 1260 records of patients who started ant-tuberculosis treatment from January 2006 up to December 2010 were analyzed. Survival curves were estimated using Kaplan–Meier and were compared using the Log-rank test. The Cox proportional hazard model was used to assess the relationship between baseline variables and mortality. Results Out of the 1260 registered patients, 117 (9.3 %) died over the entire follow-up period. Among those died, 113 (18 %) were HIV positive and 4 (0.6 %) were HIV negative. The 1260 patients contributed a cumulative total of 634.25 person‑years observation. Conclusion The mortality of HIV positive tuberculosis patients was higher than those of HIV negative patients and the use of cotrimoxazole preventive therapy increased the survival time of patients. Keywords MortalityTuberculosisSurvivalHIVDessie Referral Hospitalissue-copyright-statement© The Author(s) 2016 ==== Body Background Tuberculosis (TB) remains a major global health problem. It causes ill-health among millions of people each year and ranks as the second leading cause of death from an infectious disease worldwide, after HIV. In 2014, 6 million new cases of TB were reported to the World Health Organization (WHO) and TB killed 1.5 million people (1.1 million HIV-negative and 0.4 million HIV-positive). Despite the fact that nearly all cases can be cured, TB remains one of the world’s biggest threats [1]. The synergy between TB and HIV is strong; in high HIV prevalence population, TB is a leading cause of morbidity and mortality, and HIV is driving the TB epidemic in many countries, especially those in sub-Saharan Africa [2]. Ethiopia is one of the 22 high burden countries and TB remains one of the leading causes of mortality. According to the 2014 WHO report, the prevalence and incidence of all forms of TB are 211 and 224 per 100,000 of the population, respectively. Excluding HIV related deaths, in 2013 TB mortality was estimated to be 32 per 100,000 of the population. About 13 % of all new TB cases are also HIV co-infected. Moreover, Ethiopia is one of the high TB/HIV burden countries. Among TB patients with known HIV status, about 11 % were HIV co-infected [1]. In Ethiopia a standardized TB prevention and control programme, incorporating Directly Observed Treatment, Short Course (DOTS), was started in 1992. The DOTS strategy has been subsequently scaled up in the country and implemented at national level [3]. The scale of the global TB epidemic demands urgent and effective action. It is very important in TB control to detect the disease as early as possible and to ensure that those diagnosed complete their treatment and get cured [4]. In 1995, WHO set a target of 85 % treatment success among new sputum smear-positive cases [4]. Identification of factors for treatment failure is important in reducing TB spread, morbidity and mortality in affected individuals and may help in contributing to the achievement of the treatment targets. Understanding the predictors of mortality for TB-HIV co-infected patients in the local context is critical for Ethiopia to improve TB-HIV co-infected patients’ co-management. The survival time of TB patients can be affected by different factors. Studies showed that antiretroviral therapy (ART) status, cotrimoxazole preventive therapy (CPT) status and type of TB diagnosis were independent predictors of mortality. Initiation of ART and CPT as well as extra pulmonary TB type decreased risk of mortality in TB/HIV co-infected individuals [5]. In resource-poor settings limited data exist both on treatment results and on how to carry out such interventions. As a result, the existing treatment guidelines and recommendations are based on data from the developed world. Studying the survival patterns will help in identifying the risk factors for mortality in these patients and planning effective interventions to further reduce death rates. Therefore, the aim of this study was to assess the survival time and predictors of mortality among TB patients under DOTS strategy in Dessie Referral Hospital (DRH) TB clinic, Northeast Ethiopia. Methods The study was conducted in DRH TB clinic, Northeast Ethiopia from January 1–30, 2014. DRH has a catchment population of seven million and has a total bed size of 200 with 185 health professionals (13 specialists, 14 general practitioners, 3 health officers, 6 anesthetists, 99 nurses, 12 midwifes, 12 pharmacy professionals, 12 medical laboratory professionals, 5 X-ray technicians and 2 environmental health professionals. The TB clinic is one of the hospital segments serving 300 patients on average per annum. A historical cohort design was utilized to assess survival time and predictors mortality. Based on HIV status, TB patients was categorized into “HIV positive” and “HIV negative” cohorts and were retrospectively followed until the time of the outcome (death) or censoring. Survival time was measured from the date of initiation of therapy to death or to the last follow-up. Individuals who died were considered as failures, those who remained alive until the end of the treatment or dropped out were considered as censored. A total of 1260 out of 1375 patient record cards of TB patients who started ant-TB treatment from January 2006 up to December 2010 in DRH TB clinic were included and retrospectively followed for an additional one year. The independent variables were age, sex, residence, baseline weight, HIV status, type of TB, and CPT. The outcome variable was survival time. Structured questionnaire developed using standardized TB entry and follow up form employed by the TB clinic was utilized to extract the required data from patient records. The data was collected by reviewing registers, follow up form and patients’ card. Two nurses working at the TB clinic of DRH were recruited and trained about methods of data collection for two days. Data quality was controlled by designing the proper data collection materials and through continuous supervision. All completed data collection forms were examined for completeness and consistency during data management and analysis. The data was entered and cleaned by a data clerk and the principal investigator before analysis. The survival time was calculated using the time interval between the date of anti-TB initiation and the date of event (death) or censoring. The Kaplan-Meier model was used to estimate the survival probability after anti-TB initiation, and the Log-rank test was used to compare survival curves. The Cox proportional hazard model was used to assess the relationship between baseline variables and mortality. Descriptive statistics and Cox regression were conducted using SPSS version 16. Ethical clearance was obtained from College of Medicine and Health Sciences, Wollo University Institutional Review Committee (IRC), and permission was sought from DRH. Results Demographic and clinical characteristics In this retrospective document analysis from January 2006 up to December 2010, socio-demographic and medical information of 1260 registered TB patients was summarized. Out of the total study participants 781(62 %) were males and 1206 (95.7 %) were from urban areas. Half (50.1 %) of the study subjects were HIV negative, 16.4 % were smear positive pulmonary TB, 39.8 % were smear negative pulmonary TB and 43.7 % were extra pulmonary TB patients. Majority of the study participants (83.6 %) were new cases (Table 1).Table 1 Baseline characteristics of TB patients treated at DRH from January 2006 – December 2010 Variables HIV status Total Positive (n = 629) Negative (n = 631) Gender  Male 341 (54.2) 440 (69.7) 781 (62.0)  Female 288 (45.8) 191 (30.7) 479 (38.0) Age group   < 20 83 (13.2) 80 (12.7) 163 (12.9)  20–29 110 (17.5) 288 (45.6) 398 (31.6)  30–39 274 (43.6) 148 (23.5) 422 (33.5)  40–49 101 (16.1) 36 (5.7) 137 (10.9)   > 49 61 (9.7) 79 (12.5) 140 (11.1) Residence  Urban 600 (95.4) 606 (96.0) 1206 (95.7)  Rural 29 (4.6) 25 (4.0) 54 (4.3) Baseline weight   < 20 43 (6.8) 31 (4.9) 74 (5.9)  20–29 16 (2.5) 3 (0.5) 19 (1.5)  30–39 45 (7.2) 63 (10.0) 108 (8.6)  40–49 195 (31.0) 136 (21.6) 331 (26.3)   > 49 330 (52.5) 398 (63.1) 728 (57.8) CPT initiated  No 186 (29.6) 581 (92.1) 767 (60.9)  Yes 443 (70.4) 50 (7.9) 493 (39.1) ART initiated  No 348 (55.3) 631 (100) 979 (77.7)  Yes 281 (44.7) 0 (0.0) 281 (22.3) Type of TB  Smear positive 67 (10.7) 140 (22.2) 207 (16.4)  Smear negative 291 (46.3) 211 (33.4) 502 (39.8)  EPTB 271 (43.1) 280 (44.4) 551 (43.7) Treatment category  New 539 (85.7) 514 (81.5) 1053 (83.6)  Retreatment 90 (14.3) 117 (18.5) 207 (16.4) Patient status  Censored 516 (82.0) 627 (99.4) 1143 (90.7)  Died 113 (18.0) 4 (0.6) 117 (9.3) CPT Cotrimoxazole preventive therapy, ART Antiretroviral therapy, TB Tuberculosis, EPTB-Extrapulmonary TB Survival status of the study subjects Of 629 HIV positive and 631 HIV negative TB patients, 113 (18 %) of the HIV positive and 4 (0.6 %) of the HIV negative died and were treated as failure in the analysis. The remaining 516 (82.0 %) HIV positive and 627 (99.4 %) HIV negative patients became censored during the follow up period (Table 1). The 1260 patients contributed a cumulative total 634.25 person‑years observation, which gave rise to the overall mortality rate of 18.4 per 100 person-years of follow up per annum (117 died over the entire person-years of follow up). The median and the mean survival times were 210 and 183.7 days, respectively. The log-rank test was conducted to check for existence of any significant differences in survival experience among various levels of the categorical variables included in the study. The result in Fig. 1 manifest a significant (Log rank test = 112.423, p < 0.001) differences among HIV positive and HIV negative cohorts.Fig. 1 Survival curve by HIV status of TB patients (n = 1260) treated at DRH from January 2006 – December 2010. Statistical analysis was done using the Kaplan-Meier model to estimate the survival probability after anti-TB initiation, and the Log rank test was used to assess the relationship between HIV status and mortality. The result showed that the survival time in days of HIV negative cohorts was significantly (Log rank test = 112.423, p < 0.001) higher than those of HIV positive cohorts. Statistical significance was set at p < 0.05 Predictors of mortality The relationship between the main baseline variables and the risk of death was analyzed using a Cox proportional hazard regression model. The result showed that gender, age, residence, weight, CPT, type of TB and HIV status were all significantly associated with death of TB patients during the period of TB treatment (Table 2). Compared to HIV positive patients, the hazard ratio (HR) of dying from TB decreased significantly by 99 % in HIV negative TB patients; adjusted hazard ration (AHR) = 0.01, 95 % CI: [0.003, 0.027]. Mortality risk among female TB patients increases significantly by about two fold compared to males; AHR = 2.360, 95 % CI: [1.518, 3.671]. According to the result the risk of dying significantly reduced in patients receiving CPT by 76.6 % compared to those not receiving CPT; AHR = 0.234, 95 % CI: [0.145, 0.377].Table 2 Predictors of mortality among TB patients treated at DRH from January 2006 – December 2010 Variables Status Adjusted hazard ratio (95 % CI) p-value Censored Died Gender  Male 727 54 1  Female 416 63 2.360 (1.518, 3.671)a 0.000 Age group   < 20 129 34 1  20–29 366 32 1.317 (0.629, 2.755) 0.465  30–39 401 21 0.335 (0.156, 0.722)a 0.005  40–49 120 17 1.029 (0.442, 2.394) 0.948   > 49 127 13 1.687 (0.649, 4.385) 0.283 Residence  Urban 1114 92 1  Rural 29 25 4.230 (2.508, 7.136)a 0.000 Baseline weight   < 20 54 20 1  20–29 19 0 0.000 (0.000, 0.000) 0.957  30–39 99 9 1.103 (0.420, 2.894) 0.843  40–49 291 40 0.811 (0.332, 1.980) 0.646   > 49 680 48 0.389 (0.178, 0.851)a 0.018 HIV status  Positive 516 113 1  Negative 627 4 0.010 (0.003, 0.027)a 0.000 CPT initiated  No 688 79 1  Yes 455 38 0.234 (0.145, 0.377)a 0.000 ART initiated  No 891 88 1  Yes 252 29 0.694 (0.414, 1.163) 0.166 Type of TB  Smear positive 192 15 1  Smear negative 472 30 0.417 (0.207, 0.837)a 0.014  EPTB 479 72 1.149 (0.595, 2.222) 0.679 Treatment category  New 944 109 1  Retreatment 199 8 0.438 (0.191, 1.005) 0.051 CPT Cotrimoxazole preventive therapy, ART-Antiretroviral therapy, TB Tuberculosis, EPTB Extrapulmonary TB aSignificant at α = 0.05 Discussion WHO defines TB mortality as the number of TB cases dying during treatment, regardless of the cause. Death caused by TB is preventable and management can be modified at the time of highest risk for death if known [6]. It is now recognized that both TB and HIV contribute to each other’s progress. Patients co-infected with TB and HIV have higher mortality rates in comparison with those infected with one or the other. In several case series, the main predictor for survival was the prompt initiation of effective anti-tuberculosis treatment, ART, CD4 count, site of the disease, and other previous or concurrent opportunistic infections caused by immunosuppression [7–9]. Of the 1260 registered patients, 117 (9.3 %) died over the entire follow-up period. The mortality in our study was higher than the report in Addis Ababa, Ethiopia [10] and the nationwide mortality in Ethiopia [3], but lower than those reported in previous studies including 10.0 % in Gondar, Ethiopia [11], and 14 % in Vaud County, Switzerland [12]. Similarly, the study has demonstrated significant difference on the prevalence of death between HIV positive and HIV negative TB patients. Of 629 HIV positive and 631 HIV negative TB patients, 113 (18 %) of the HIV positive and 4 (0.6 %) of the HIV negative died. Similar to the current study, previous studies [13] reported higher overall death rates among HIV positive TB patients than HIV negative TB patients. HIV infection is the primary reason for the failure to meet tuberculosis control targets (at least 85 % cure rate among new sputum smear positive TB cases) in countries with high HIV infection. This is attributable to factors such as over diagnosis of sputum smear negative TB, under diagnosis of sputum smear-positive TB, low cure rates, high morbidity, mortality and default rates during treatment, and atypical clinical presentation of TB in HIV infected patients. Consequently, HIV infection leads to diagnostic challenges and delays in identifying TB that profoundly impacts treatment outcome [14]. The relationship between the main baseline variables and the risk of death was analyzed using a Cox proportional hazard regression model. In our study not initiating CPT was associated with high risk of mortality. In line with this, studies from Northwest Ethiopia [5] South India [15] and Sub-Saharan Africa [16] showed that not taking CPT was significantly associated with mortality. CPT is a simple well tolerated and cost effective intervention which can extend and improve the quality of life for people living with HIV/AIDS including those on ART. CPT is associated with a 25–46 % reduction in mortality among individuals infected with HIV in sub-Saharan Africa even in areas of high bacterial resistance to the antibiotic [17, 18]. Previous studies found that TB-HIV co-infected patients who took ART during TB treatment had a lower risk of death. They also demonstrate the positive impact of ART on the survival outcomes among TB-HIV co-infected patients, including successful immune restoration and reductions in morbidity and mortality [5, 19]. In our study we did not find any significant difference in mortality between the on ART and non-ART cohorts, which is in agreement with previous studies [13]. This might be associated with delayed initiation of ART. The optimal time to initiate ART in patients with HIV-associated tuberculosis has been the subject of intense debate. Concerns about early initiation of ART include a high pill burden, pharmacological interactions, overlapping toxicities and the immune reconstitution inflammatory syndrome (IRIS) [20]. Conversely, delayed initiation of ART may be associated with HIV disease progression and death [21]. Previous retrospective studies [22, 23] showed that delaying ART initiation until after completion of TB therapy was associated with increased mortality. Previous TB treatment and multiple drug‑resistant TB (MDR‑TB) are considered significant risk factors for decease. It is known that patients previously treated for TB have a higher risk of presenting MDR TB and of dying than new TB patients [24]. There are also reports supporting the idea that failure or relapses were not associated with an increased risk of death [25]. This study also adds to the literature that treatment category (new or retreatment) was not significantly associated with mortality in the adjusted model, this might be due to late presentation of patients to the hospital and advanced disease progress. Our study was done retrospectively to find out the common risk factors associated with mortality that was considered one of the limitations of the survey. The data have been extracted from medical records of patients who have been already visited and registered at the hospital, so it may be subjected to selection bias. The other limitation of the survey was the fact that in many TB patients, multiple causes of death may act simultaneously, so the specific cause of death may not be determined accurately. Conclusions In summary, results from this study indicate that the mortality of HIV positive TB patients was higher than those of HIV negative TB patients and use of CPT can prolong the survival time of TB patients. The decrease in mortality among TB/HIV patients requires public health interventions and the enhancement of existing control programs to improve both prevention and treatment. Interventions should be directed at modifiable risk such as treatment of opportunistic infections. Acknowledgements We are very grateful to all members working in DRH TB clinic for their assistance in this study. Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Availability of data and materials All data generated or analyzed during this study are included in this published article. Authors’ contributions All have been involved in the design and conceptual framework of the study. BG worked on analyzing the data; YB was involved in drafting the manuscript, and the role of AM was crucial in data collection and manipulation. All the authors have read and approved the final manuscript. Authors’ information None. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate The study was approved by the Institutional Review Committee (IRC) of Wollo University. ==== Refs References 1. World Health Organization Global Tuberculosis control report 2015 20 Geneva WHO 2. Federal Minister of Health Implementation Guideline for TB/HIV Collaborative Activities in Ethiopia 2007 Addis Ababa Federal Ministry of Health 3. Federal Ministry of Health Guidelines for clinical and programmatic management of TB, TB/HIV and leprosy in Ethiopia 2012 5 Addis Ababa Federal Ministry of Health 4. World Health Organization Treatment of tuberculosis: Guidelines for National Programmes 2010 4 Geneva WHO 5. Sileshi B Deyessa N Girma B Melese M Suarez P Predictors of mortality among TB-HIV Co-infected patients being treated for tuberculosis in Northwest Ethiopia: a retrospective cohort study BMC Infect Dis 2013 13 297 10.1186/1471-2334-13-297 23815342 6. World Health Organization Framework for effective tuberculosis control 1994 Geneva WHO 7. Ackah AN Coulibaly D Digbeu H Diallo K Vetter KM Coulibaly IM Greenberg AE De Cock KM Response to treatment, mortality, and CD4 lymphocyte counts in HIV-infected persons with tuberculosis in Abidjan, Cote d’Ivoire Lancet 1995 345 607 610 10.1016/S0140-6736(95)90519-7 7898177 8. Whalen C Horsburgh CR Hom D Lahart C Simberkoff M Ellner J Accelerated clinical course of HIV infection after tuberculosis Am J Respir Crit Care Med 1995 151 129 135 10.1164/ajrccm.151.1.7812542 7812542 9. Shafer RW Bloch AB Larkin C Vasudavan V Seligman S Dehovitz JD DiFerdinando G Stoneburner R Cauthen G Predictors of survival in HIV-infected tuberculosis patients AIDS 1996 10 269 272 10.1097/00002030-199603000-00005 8882666 10. Getahun B Ameni G Biadgilign S Medhin G Mortality and associated risk factors in a cohort of tuberculosis patients treated under DOTS programme in Addis Ababa, Ethiopia BMC Infect Dis 2011 11 127 10.1186/1471-2334-11-127 21575187 11. Tessema B Muche A Bekele A Reissig D Emmrich F Sack U Treatment outcome of tuberculosis patients at Gondar University Teaching Hospital, Northwest Ethiopia. A five - year retrospective study BMC Publ Health 2009 9 371 10.1186/1471-2458-9-371 12. Zellweger JP Coulon P Outcome of patients treated for tuberculosis in Vaud County, Switzerland Int J Tuberc Lung Dis 1998 2 372 377 9613632 13. Shaweno D Worku A Tuberculosis treatment survival of HIV positive TB patients on directly observed treatment short-course in Southern Ethiopia: A retrospective cohort study BMC Res Notes 2012 5 682 10.1186/1756-0500-5-682 23234241 14. Mahajan V, Verma SK. HIV-Tuberculosis co-infection. The Internet Journal of Pulmonary Medicine 2008, http://www.ispub.com Accessed Jul 12 2013. 15. Vijay S Kumar P Chauhan LS Narayan Rao SV Vaidyanathan P Treatment outcome and mortality at one and half year follow-Up of HIV infected TB patients under TB control programme in a District of South India PLoS One 2011 6 e21008 10.1371/journal.pone.0021008 21814542 16. Harries AD Zachariah R Lawn SD Providing HIV care for co-infected tuberculosis patients: a perspective from sub-Saharan Africa Int J Tuberc Lung Dis 2009 13 6 16 19105873 17. Badri M Ehrlich R Wood R Maartens G Initiating co-trimoxazole prophylaxis in HIV-infected patients in Africa: an evaluation of the provisional WHO/UNAIDS recommendations AIDS 2001 15 1143 1148 10.1097/00002030-200106150-00009 11416716 18. World Health Organization Guideline on cotrimoxazole prophylaxis for HIV related infections among children, adolescent & adults 2009 2 Geneva WHO 19. Cain KP Anekthananon T Burapat C Akksilp S Mankhatitham W Srinak C Nateniyom S Sattayawuthipong W Tasaneeyapan T Varma JK Causes of death in HIV-infected persons who have tuberculosis, Thailand Emerg Infect Dis 2009 15 258 264 10.3201/eid1502.080942 19193270 20. Stockdale AJ Nkuranga J Török ME Faragher B Lalloo DG Initiation of Antiretroviral Therapy in HIV-Infected Tuberculosis Patients in Rural Kenya: An Observational Study Trop Med Int Health 2013 18 907 914 10.1111/tmi.12110 23590229 21. Lawn SD Churchyard G Epidemiology of HIV-associated tuberculosis Curr Opin HIV AIDS 2009 4 325 333 10.1097/COH.0b013e32832c7d61 19532072 22. Manosuthi W Chottanapand S Thongyen S Chaovavanich A Sungkanuparph S Survival rate and risk factors of mortality among HIV/tuberculosis coinfected patients with and without antiretroviral therapy J Acquir Immune Defic Syndr 1999 43 42 46 10.1097/01.qai.0000230521.86964.86 16885778 23. Velasco M Castilla V Sanz J Gaspar G Condes E Barros C Cervero M Torres R Guijarro C Effect of simultaneous use of highly active antiretroviral therapy on survival of HIV patients with tuberculosis J Acquir Immune Defic Syndr 1999 50 148 152 10.1097/QAI.0b013e31819367e7 19131895 24. Tocque K Convrey RP Bellis MA Beeching NJ Davies PD Elevated mortality following diagnosis with a treatable disease: tuberculosis Int J Tuberc Lung Dis 2005 9 797 801 16013777 25. Lefebvre N Falzon D Risk factors for death among tuberculosis cases: analysis of European surveillance data Eur Respir J 2008 31 1256 1260 10.1183/09031936.00131107 18515556

PMC005xxxxxx/PMC5000468.txt

==== Front Health Qual Life OutcomesHealth Qual Life OutcomesHealth and Quality of Life Outcomes1477-7525BioMed Central London 52310.1186/s12955-016-0523-6ResearchA longitudinal study on quality of life after injury in children Schneeberg Amy amy.schneeberg@alumni.ubc.ca 123Ishikawa Takuro tishikawa@cfri.ca 23Kruse Sami samicoolwhip@hotmail.com 3Zallen Erica erica.zallen@gmail.com 3Mitton Craig craig.mitton@ubc.ca 1Bettinger Julie A. jbettinger@cfri.ca 345http://orcid.org/0000-0002-1495-816XBrussoni Mariana +1 (604) 875-3712mbrussoni@cfri.ubc.ca 12341 School of Population & Public Health, University of British Columbia, Vancouver, BC Canada 2 British Columbia Injury Research & Prevention Unit, F508 – 4480 Oak Street, Vancouver, BC V6H 3 V4 Canada 3 British Columbia Children’s Hospital, Vancouver, BC Canada 4 Department of Pediatrics, University of British Columbia, Vancouver, BC Canada 5 Vaccine Evaluation Center, BC Children’s Hospital, Vancouver, Canada 26 8 2016 26 8 2016 2016 14 1 12010 12 2015 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background In high income countries, injuries account for 40 % of all child deaths, representing the leading cause of child mortality and a major source of morbidity. The need for studies across age groups, and use of health related quality of life measures that assess functional limitations in multiple health domains, with sampling at specific post-injury time points has been identified. The objective of this study was to describe the impact of childhood injury and recovery on health related quality of life (HRQoL) for the 12 months after injury. Methods In this prospective cohort study parents of children 0-16 years old attending British Columbia Children’s Hospital for an injury were surveyed over 12 months post-injury. Surveys assessed HRQoL at four points: baseline (pre-injury), one month, four to six months and 12 months post injury. Generalized estimating equation models identified factors associated with changes in HRQoL over time. Results A total of 256 baseline surveys were completed. Response rates for follow-ups at one, four and twelve months were 74 % (186), 67 % (169) and 64 % (161), respectively. The mean age of participants was 7.9 years and 30 % were admitted to the hospital. At baseline, a retrospective measure of pre-injury health, the mean HRQoL score was 90.7. Mean HRQoL ratings at one, four and 12 months post injury were 77.8, 90.3 and 91.3, respectively. Both being older and being hospitalized were associated with a steeper slope to recovery. Conclusions Although injuries are prevalent, the long term impacts of most childhood injuries are limited. Regardless of injury severity, most injured children recuperated quickly, and had regained total baseline status by four month post-injury. However, although hospitalization did not appear to impact long term psychosocial recovery, at four and 12 months post injury a greater proportion of hospitalized children continued to have depressed physical HRQoL scores. Both older and hospitalized children reported greater impact to HRQoL at one month post injury, and both had a steeper slope to recovery and were on par with their peers by four month. Keywords PediatricsUnintentional injuryHealth related quality of lifehttp://dx.doi.org/10.13039/501100000024Canadian Institutes of Health ResearchTIR-104028http://dx.doi.org/10.13039/501100000245Michael Smith Foundation for Health Research (CA)CI-SCH-01199(07-1)issue-copyright-statement© The Author(s) 2016 ==== Body Background Injuries account for 40 % of all child deaths in high-income countries, representing the leading cause of child mortality and a major source of morbidity [1]. In the United States, each year more than 9,000 children aged 19 and under die from unintentional injuries, and another 225,000 are hospitalized [2]. Although indicative of the enormous public health problem that injuries comprise, mortality and hospitalization statistics are inadequate to fully understand the burden of injury. The World Health Organization’s definition of health includes physical, mental and social dimensions [3]. While physiologic measures of injury severity are important to clinicians, measures of functional capacity and wellbeing can be of greater importance to individuals [4]. Measuring health related quality of life (HRQoL) after injury facilitates quantifying the impact on multiple dimensions of health and the recovery process. As a multidimensional, patient centered outcome, HRQoL measures encompass a wide range of experiences to given health states, including physical and psychosocial function as well as spiritual wellbeing [5]. It is important to identify potential long-term impact of injuries on HRQoL in order to provide timely and ongoing support. Research following child injury on psychological outcomes, is currently investigating predictors and early intervention strategies, and the present study can help build towards these interventions [6–8]. Studies examining HRQoL after injuries in adult populations have found that the impacts of injury can vary in time and extent, and that injury severity is not the only predictive factor [9]. These studies typically focus on patients with severe injuries, limiting our understanding of outcomes for the majority of injuries which do not result in death or severe disability [10]. It has been estimated that for every individual who dies from an unintentional injury, there are approximately six other individuals who are hospitalized, 45 individuals with emergency department (ED) visits and 48 individuals with visits to primary healthcare providers [11]. Thus, it is important to consider the impact less severe injuries may have given the health care burden they represent. Study methods used to assess post injury HRQoL vary widely with respect to sample population, measurement instruments used, and timing of measurements, and they rarely include a baseline HRQoL measurement for comparison to pre-injury state [10]. Further, studies with pediatric samples are rare despite the fact that the impact of childhood injuries can differ substantially from adults [9, 10]. Therefore, studies across age groups, and use of HRQoL measures that assess functional limitations in multiple health domains, with sampling at specific post-injury time points are needed [10]. Pediatric studies using generic measures of HRQoL with baseline measurements of health and wellbeing are required to understand the impact injuries have on this unique population. Available studies have found that the impact of injuries on HRQoL can extend well into the year following treatment. One study that examined the health status of children in the six months following admission to hospital for injury found that general health perceptions, physical functioning, social and physical roles, behavior, parental impact including emotional and family activities all remained lower at discharge, one month, and six months post-injury relative to a population of healthy children [12]. Although this study demonstrated that the impact of injuries can remain at six months post hospital admission for both the child and parents, they did not explore less severe injuries not requiring admission to hospital, nor did they explore factors, outside of severity, that may be used to predict depressed physical and emotional functioning. Other studies that included less severe injuries not requiring hospitalization, have found that a small proportion (8 %) of children still reported functional limitations at nine months post injury and that some injured children had depressed HRQoL scores up to two years post injury [13, 14], however these studies excluded very young children (< 5 years of age). There are gaps in the literature regarding the immediate and long-term impacts of injury and recovery, particularly in pediatric populations. The objective of this research is to better understand the impact of a broad spectrum of childhood injuries of varying severity on HRQoL and to identify demographic and diagnostic variables associated with a significant relationship with HRQoL. Methods Study population This study collected data longitudinally from a sample of parents of children aged 0 to 16 years who presented with a primary injury diagnosis at the British Columbia Children’s Hospital (BCCH) ED or were admitted to the hospital wards between February 2011 and December 2013. For children 0 to 5 years old, only parents completed surveys. For all other ages, both children and parents completed surveys. For consistency, the present paper presents only parents’ reports for all participants. Data collection A research assistant recruited directly from the ED and hospital wards on different days of the week and times of day. In addition, real time hospital admissions data were reviewed twice daily during regular office hours to identify children presenting with injury for study recruitment. Because most medically attended visits for injuries do not result in hospitalization, injuries requiring hospitalization were proportionately over-sampled to ensure a mix of patients with injuries of varying severity. Thirty percent of the study sample was hospitalized relative to only 10 % of the population of all children presenting to the hospital with an injury. Before approaching parents in hospital wards, researchers gained permission from the nurse or physician responsible for the child’s care. In the ED, parents were approached in waiting rooms, after triage confirmed that the primary reason for the visit was injury. All participants gave written consent. Parents who did not speak English or did not have an address in British Columbia (BC) were excluded from the sample. Twenty four parents indicated their child suffered from a disability or long-term health problem before the injury. Since these children had relatively rare conditions that can increase risk of injury and hospitalization their parents’ data were excluded from analysis. While we did not begin the study deliberately excluding intentional injuries (e.g., self-harm, assaults), we recognized that there would be different impacts on HRQoL. Only three participants with intentional injuries agreed to participate, which was insufficient for meaningful analysis, thus, they were excluded from the analyses reported herein. See Fig. 1 for a flowchart outlining participant disposition. This study was reviewed and approved by the University of British Columbia/Children’s and Women’s Health Centre of British Columbia Research Ethics Board.Fig. 1 Study population disposition A study specific survey instrument incorporating the Pediatric Quality of Life Questionnaire (PedsQL™) was administered to parents/guardians at baseline and one, four and 12 months post injury, as per guidelines outlined by van Beeck et al. [10]. At baseline, PedsQL™ was assessed as a retrospective measure of pre-injury health and asked about the child’s HRQoL in the month prior to injury. The questionnaire was piloted among a sample of 10 parents to ensure clarity and comprehension. Components of the questionnaire had previously been validated (the PedsQL [15, 16]) however, validity and reliability were not measured for questions related to demographics and the circumstances of the injury. Parents could complete a hard copy of the questionnaire and return in a stamped self-addressed envelope, or through an online link. Research shows, mode of administration (pen and paper, online or telephone) does not influence scores [17]. At the time of recruitment and with each subsequent follow-up, parents were offered a $2 gift card to a local coffee and pastries merchant for participating in the study, irrespective of whether they completed the survey or not. Descriptive variables At baseline, the survey instrument included questions about the circumstances around the injury and demographic information including the child’s age, and sex. Hospital records were used to determine each child’s length of hospitalization Pediatric Canadian Triage and Acuity Scale (PaedCTAS) score. The PaedCTAS is a scale used to triage patients based on urgency. PaedCTAS has five ordinal categories ranging from 1 (requires resuscitation) to 5 (non-urgent), and it is assigned to all children presenting in Canadian EDs [18]. This score can be used to predict the nature and scope of care that is likely to be required. The scoring is highly standardized, as nurses assigning the score receive continuous training. Both PaedCTAS score and hospitalization status were used as independent proxies of injury severity. Research indicates the utility of the PaedCTAS as an alternate proxy of injury severity that is not as sensitive to extraneous factors that can influence hospitalization status [19]. Participants’ postal codes were used to derive a measure of socioeconomic status (neighbourhood income quintiles) using Statistics Canada’s Postal Code Conversion File Plus [20]. Health related quality of life The PedsQL™ 4.0 Generic Core and the PedsQL™ Infant Scales were developed to assess HRQoL in children, ages 2 to 18 years and 0 to 24 months, respectively. The PedsQL™ 4.0 Generic Core is a 23 item scale and includes four subscales: physical functioning, emotional functioning, social functioning and school functioning [21]. The PedsQL™ Infant Scale is an instrument composed of 45 items and five subscales: physical functioning, physical symptoms, emotional functioning, social functioning and cognitive functioning [22]. Both PedsQL™ instruments use a five point Likert response scale ranging from “never” to “almost always” to assess the extent to which different items have affected the child in the previous month. For both measures, individual item scores have been obtained by reverse scoring items and linearly transforming them to a scale of 0 to 100, with 100 representing perfect health. Total scores have been obtained by adding the sum of items and dividing them by the number of items answered. Studies that have reviewed tools for the purpose of long-term follow-up and assessing outcomes in pediatric trauma populations have identified the PedsQL™ as one of very few that is appropriate for a large age range that also has robust psychometric properties [22, 23]. A difference of 4.5 for parent proxy have been previously established as the minimal clinically meaningful difference for this tool [24]. To better understand the true burden of injury overtime both the mean HRQoL score at each time point, as well as the proportion of children who continue to report depressed HRQoL scores at each time point (prevalence of outstanding impact) has been investigated. Statistical analysis Logistic regression was used to compare the final analytic sample, the children for whom at least one follow-up survey was available (n = 204), to the entire sample of children presenting with injury to BCCH wards or ED during the study period using administrative data obtained from BCCH. BCCH administrative data included postal code, sex, age, length of stay and hospitalization status. Statistics Canada’s Postal Code Conversion File Plus was used to assign neighbourhood income quintiles. The HRQoL of study participants at baseline and follow-up points was measured using parent response to PedsQL™. The relationship between PedsQL™ score at each time point and demographic and injury related variables was explored using bivariable linear regression. To determine the proportion of children who continued to have depressed HRQoL scores relative to baseline, the “prevalence of outstanding impact”, on overall HRQoL as well as the physical and psychosocial domains independently at each time point, was defined as having a score that was at least 1 standard deviation of the baseline mean below the individual’s baseline score. The relationship between the prevalence of outstanding impact on HRQoL and injury severity was explored by investigating the relationship between “prevalence of impaired HRQoL” and hospitalization status and PaedCTAS scores using chi-square or Fisher’s exact tests, as appropriate. A Bonferroni correction was applied to determine the alpha used for statistical significance to account for multiple comparisons. Bivariable associations between demographic and injury related variables were investigated with chi square tests for categorical comparisons and t-tests or ANOVA for continuous (age) variables. If variables were identified to be potentially collinear (p < 0.10) the variable with a stronger crude relationship with recovery in HRQoL over time was brought forward for model building. Bivariable generalized estimating equation (GEE) models using an exchangeable covariance matrix were built to explore the crude impact of demographic and injury related variables on HRQoL. To explore the impact of independent variables on recovery overtime an interaction term with time was included in all models. For the purpose of model building PaedCTAS scores were collapsed into 3 categories, PaedCTAS 1 and 2, 3 and 4 and 5, because there were not enough cases in the highest and lowest categories. A multivariable GEE model was built including all variables identified to be statistically or conceptually important. The model was run with all observations in the analytic sample (n = 204). Finally, a sensitivity analysis was run to assess the impact of exclusions due to missing data on our results. The mean HRQoL scores for the analytic sample at each time point were compared to the mean scores of the entire population of children who returned any data over the study period and no clinically or statistically significant differences were identified (results not shown). Results Study population After exclusions there were 256 baseline surveys; of those individuals 204 returned at least one follow-up survey, making up the analytic sample. Table 1 provides demographic and injury information for study participants included in the analytic sample and a comparison of participants with complete data to those lost to follow-up. The analytic sample was not statistically significantly different than the sample of children who returned a baseline survey on any of the demographic of injury related variables collected (results not shown). Also, the analytic sample was not statistically different than the broader population of all injured children based on sex or age, however the children in our sample had higher odds of being hospitalized (a result of purposeful sampling) and lower odds of being in the lowest 2 income quintiles relative to all injured children presenting at the hospital during the study period (Table 2).Table 1 Baseline characteristics Attrition Total n = 204 12 Month Complete n = 149 Lost to Follow-Up n = 55 ORa (95 % CI) Baseline HRQoL  Mean (SD) 90.7 (±8.9) 91.3 (±8.3) 89.0 (±10.3) 1.0 (0.9, 1.1) Hospitalization Status n (%)  Emergency Department 144 (70.6) 108 (72.5) 35 (66.0) 0.7 (0.4, 1.4)  Hospitalized 60 (29.4) 41 (27.5) 20 (34.0) Length of Stay (days)  Median (25 %, 75 %) 2.7 (1.5, 6.8) 2.5 (1.5, 5.0) 3.8 (1.8, 10.6) 0.9 (0.8, 1.0)  Range 0.2 – 43.4 0.2 – 14.9 0.2 – 43.4 Sex n (%)  Male 127 (62.3) 96 (64.4) 31 (56.4) 1.4 (0.7, 2.6)  Female 77 (37.7) 53 (35.6) 24 (43.6) Ref Age (years)  Median (25 %, 75 %) 7.1 (3.6, 11.7) 7.3 (3.7, 11.9) 6.8 (3.0, 11.6) 1.0 (0.9, 1.1)  Range 0.1 - 16.9 0.3 – 16.9 0.1 – 16.6 Age Category n (%)  0 – 5 years 84 (41.2) 62 (41.6) 22 (40.0) 0.9 (0.4, 2.0)  6 – 10 year 66 (32.4) 46 (30.9) 20 (36.4) 0.7 (0.3, 1.6)  11 -16 years 54 (26.5) 41 (27.5) 13 (23.6) Ref PaedCTAS n (%)  1 (requires resuscitation) 11 (5.4) 8 (5.4) 3 (5.5) 0.4 (0.0, 4.6)  2 38 (18.6) 28 (18.8) 10 (18.2) 0.4 (0.0, 3.7)  3 43 (21.1) 30 (20.1) 13 (23.6) 0.3 (0.0, 3.0)  4 104 (51.0) 76 (51.0) 28 (50.9) 0.4 (0.0, 3.3)  5 (non-urgent) 8 (3.9) 7 (4.7) 1 (1.8) Ref Income Quintile n (%)  1 (lowest income quintile) 25 (12.3) 12 (8.1) 13 (23.6) 0.3 (0.1, 0.7)  2 25 (12.3) 16 (10.7) 9 (16.4) 0.5 (0.2, 1.4)  3 43 (21.1) 37 (24.8) 6 (10.9) 1.8 (0.6, 4.9)  4 39 (19.1) 28 (18.8) 11 (20.0) 0.7 (0.3, 1.8)  5 (highest income quintile) 72 (35.3) 56 (37.6) 16 (29.1) Ref Injury Type  Head injury 18 (8.8) 12 (8.1) 6 (11.3) 1.2 (0.3, 4.9)  Lower extremity fracture 25 (12.3) 15 (10.1) 10 (18.9) 0.9 (0.3, 3.3)  Major trauma 16 (7.8) 13 (8.8) 3 (5.7) 2.6 (0.5, 13.0)  Minor external injury 77 (37.7) 57 (38.5) 20 (37.7) 1.7 (0.6, 5.3)  Upper extremity fracture 49 (24.0) 41 (27.7) 8 (15.1) 3.1 (0.9, 10.9)  Otherb 18 (9) 10 (6.8) 6 (11.3) Ref  Missing 1 (0.5) 1 (1.0) 2 (2.3) aOR from logistic regression, odds of returning 12 month survey bCategories with cell size < 5 were collapsed into, other this category includes Major Burn, Hand or foot amputation, Head Trauma, Ingestion/chocking, Internal organ injury, Spinal fracture Table 2 Study population compared to all children presenting to hospital with injury during study period Study population All injuries OR (95 % CI) Sex n (%)  Male 127 (62.3) 8156 (58.3) ref  Female 77 (37.8) 5825 (41.7) 1.2 (0.9, 1.6) Income Quintile n (%)  1(lowest income quintile) 25 (12.3) 2,744 (19.8) 0.4 (0.3, 0.7)  2 25 (12.3) 2,598 (18.8) 0.4 (0.3, 0.7)  3 43 (21.1) 2,607 (18.9) 0.8 (0.5, 1.1)  4 39 (19.1) 2,586 (18.9) 0.7 (0.5, 1.0)  5(hightest income quintile) 72 (35.3) 3,305 (23.9) ref Hospitalized n (%)  ED 144 (70.6) 12,419 (88.8) ref  Admitted 60 (29.4) 1,562 (11.2) 3.3 (2.4, 4.5) Age (Mean ± SD) (range 0 – < 17 years) 7.87 ± 4.67 7.32 ± 5.02 1.0 (1.0. 1.1) The mean age of analytic sample was 7.9 years, 62.3 % were male, and 89 % of respondents indicated English was the primary, or one of the primary languages spoken at home. Almost 30 % of participants were hospitalized for their injuries. The median length of stay for children who were hospitalized was 2.7 days, ranging from < 1 day to 43 days, with 40 % being hospitalized for 2 days or less. The majority of children included in this study were previously healthy with 87 % of parents indicating that their child had zero days of ill health in the four weeks preceding the injury. Most parents indicated their child was participating in leisure/entertainment activities (32 %), or sports/exercise either at school or at a club/gym (31 %) at the time of injury. Table 3 presents HRQoL for participants based on PedsQL™ summary scores as reported by parents at each time point stratified by demographic and injury-related variables. The mean baseline total HRQoL score (representing pre-injury health) of participants was 90.66 (95 % CI (89.4, 91.9)). At one month the mean total health score dropped to 77.8 (95 % CI (75.2, 80.4)), by four months this mean returned to almost that of pre injury status (90.3 (88.9, 91.8)) and by 12 months the mean score was equal to pre injury status (91.3 (89.8, 92.8)). None of the demographic or injury related variables were statistically significantly associated with baseline or twelve month HRQoL summary scores. At one-month post injury having been hospitalized, having a lower PaedCTAS score and being over the age of 8 were all significantly associated with lower HRQoL summary scores (p < 0.001 due to Bonferroni correction). These relationships were no longer evident at four months post injury, except for age.Table 3 PedsQL total health score, parent report at each follow-up pointa,* Baseline One Month Four Months Twelve Months n mean sd n mean sd n mean sd n mean sd Sex p = 0.31 p = 0.82 p = 0.47 p = 0.44  Male 127 90.2 9.2 113 77.6 17.5 106 89.9 9.7 103 90.8 9.8  Female 77 91.5 8.3 72 78.2 18.6 63 91 9.6 58 92.1 9.5 Age Category p = 0.58 p  = 0.005 p  = 0.003 p = 0.22  0 - 5 84 91.3 8.5 74 82.8 16.0 65 92.4 7.9 62 92.2 9.6  6 -10 66 89.8 9.5 63 73.0 18.7 52 86.6 11.4 46 89.6 10.7  11-16 54 90.7 8.8 48 76.5 17.9 41 91.3 8.5 41 92.9 7.2 Hospitalization Status p = 0.77 p  < 0.001 p = 0.71 p = 0.82  ED 144 90.5 8.9 132 82.6 14.8 126 90.2 10.1 113 91.4 9.2  Hospitalized 60 90.9 8.9 53 65.9 19.6 43 90.8 8.4 48 91 10.8 PaedCTAS p = 0.15 p  < 0.001 p = 0.72 p = 0.87  1 (resuscitation required) 11 85.4 12.4 10 65.8 17 9 88 9.4 7 90.7 12  2 38 91.1 8.6 33 68.2 19.9 30 90.1 8.5 33 91 9.1  3 43 91.7 8.2 40 78 18.3 34 89.8 9.2 34 92.2 8.7  4 104 90.3 8.9 94 82 15.9 90 90.5 10.5 79 91.3 9.7  5 (non-urgent) 8 95.2 4.3 8 82 11.8 6 95 4.8 8 88.1 14.3 Income Quintile p = 0.12 p = 0.16 p = 0.44 p = 0.27  1 (lowest income quintile) 25 90.2 9.5 21 73.9 21.1 18 89 9.9 13 93 9.3  2 25 88.3 11.7 23 74.8 18.6 20 87.4 10.2 18 88.2 10.6  3 43 93 6.9 38 83.9 17.6 37 92.3 9.6 38 92.6 10.9  4 39 88.6 9.4 35 75.6 17.5 31 90.8 10.8 33 89.1 10.8  5 (highest income quintile) 72 91.4 8.1 68 77.8 16.5 63 90.2 8.9 59 92.2 7.6 Injury p = 0.89 p  < 0.001 p = 0.99 p = 0.95  Head injury 18 91.4 6.7 17 89.3 8.2 15 91.4 6.4 12 93.6 5.9  Lower extremity fracture 25 92.9 9.2 22 58.6 19.9 16 88.7 9.4 15 90.2 10.2  Major trauma 16 89.0 11.6 15 65.5 21.2 13 90.0 9.8 13 90.0 11.2  Minor external injury 77 90.8 9.4 67 84.8 15.3 60 89.2 11.6 57 91.3 10.9  Upper extremity fracture 49 89.6 8.5 46 77.9 12.2 41 91.5 8.8 41 92.6 7.3  Other* 16 90.7 6.9 15 74.8 16.9 11 90.6 5.9 10 92.0 9.1 aVariable ranges from 0-100 with 100 representing perfect health; minimal clinically important difference is a 4 point change *P values for differences in mean PedsQL scores across variables (within time points) from bivariable linear regression, < 0.001 considered significant with Bonferroni correction At 12 months post injury the prevalence of outstanding impact on total HRQoL was 8 %, 10 % and 9 % for the total summary score, physical and psychosocial domains respectively (Table 4). No injury or demographic variables were associated with the prevalence of outstanding HRQoL impact overall at 12 months.Table 4 Prevalence of impaired HRQoL (as defined > 1 standard deviation of baseline mean below baseline score) by injury severity One Month Four Months Twelve Months Total Physical Psycho-social Total Physical Psycho-social Total Physical Psycho-social Full population n (%) 90 (44.1) 113 (55.4) 58 (28.4) 23 (11.3) 28 (13.7) 18 (8.8) 13 (6.4) 16 (7.8) 15 (7.4) Hospitalization Status n (%) p  < 0.001 p  = 0.001 p  < 0.001 p = 0.91 p = 0.03 p = 0.21 p = 0.87 p = 0.05 p = 0.83  ED 49 (34.0) 69 (47.9) 30 (20.8) 16 (11.1) 15 (10.4) 15 (10.4) 11 (7.6) 11 (7.6) 13 (9.0)  Hospitalized 41 (68.3) 44 (73.3) 28 (46.7) 7 (11.7) 13 (21.7) 3 (5.0) 5 (8.3) 10 (16.7) 6 (10.0) PaedCTAS n (%) p = 0.06 p = 0.18 p = 0.03 p = 0.84 p = 0.14 p = 0.85 p = 0.12 p = 0.11 p = 0.04  1 (resuscitation required) 7 (63.6) 7 (63.6) 6 (54.5) 1 (9.1) 2 (18.2) 1 (9.1) 0 (0.0) 0 (0.0) 1 (9.1)  2 21 (55.3) 26 (68.4) 15 (39.5) 6 (15.8) 9 (23.7) 2 (5.3) 5 (13.2) 7 (18.4) 5 (13.2)  3 21 (48.8) 24 (55.8) 13 (30.2) 5 (11.6) 7 (16.3) 4 (9.3) 1 (2.3) 2 (4.7) 1 (2.3)  4 36 (34.6) 50 (48.1) 21 (20.2) 10 (9.6) 9 (8.7) 10 (9.6) 8 (7.7) 10 (9.6) 9 (8.7)  5 (non-urgent) 5 (62.5) 6 (75.0) 3 (37.5) 1 (12.5) 1 (12.5) 1 (12.5) 2 (25.0) 2 (25.0) 3 (37.5) *p values comparing prevalence of impaired HRQoL across groups from chi square test or Fisher’s where cell size < 5; < 0.001 considered significant with Bonferroni correction Table 5 presents the results of the GEE model examining predictors of HRQoL over time (from 1-12 months) the QICu of the model with only time was 98 146 and the model with all covariates the QICu was 72 322. The model demonstrates that the only significant modifiers of HRQoL recovery following injury, after controlling for baseline HRQoL, were age and hospitalization status. Children who were hospitalized had a steeper slope to recovery as demonstrated by the fact that despite having lower HRQoL at one month post injury relative to children who were not hospitalized, HRQoL for both hospitalized and un-hospitalized children returned to baseline by four months post injury (Fig. 2). The parameter estimate for the adjusted model from Table 5 for the hospitalization and time interaction term can be interpreted as follows: during the time from 1-12 months post injury, in a one month period the average change in HRQoL score for children who were not hospitalized was 0.93 points less than children who were hospitalized controlling for baseline HRQoL, age, sex and PaedCTAS. Likewise, relative to children who were one year younger, older children experienced a 0.07 point greater increase in their HRQoL score in a month period, or the slope of HRQoL over time for children who were one year older was found to be 0.07 steeper than that of younger children.Table 5 PedsQl Total score at 1, 4 and 12 months using Generalized Estimating Equation Time only Model (95 % CI) Crude Estimatea (95 % CI) Adjusted Estimateb (95 % CI) Intercept 81.47 (79.37, 83.56) 34.53 (17.88, 51.17) Time in months 0.99 (0.79, 1.19) 0.54 (–1.37, 2.46) Baseline HRQoL 0.52 (0.24, 0.79) 0.53 (0.29, 0.77) Time*Baseline 0.01 (–0.01, 0.03) 0.01 (–0.01, 0.03) Hospitalization Status 13.65 (8.38, 18.93) 11.95 (5.59, 18.30) Time*Hospitalization (ref = hosp) –1.17 (–1.67, –0.68) –0.93 (–1.58, –0.29) Age (yrs) –1.03 (–1.46, –0.59) –0.93 (–1.32, –0.54) Time*Age 0.07 (0.03, 0.12) 0.07 (0.04, 0.11) Sex (ref = Female) –0.41 (–5.06, 4.25) 2.63 (–1.25, 6.5) Time*Sex –0.10 (–0.53, 0.33) –0.29 (–0.67, 0.10) PaedCTAS 1&2 Reference PaedCTAS 3 7.51 (0.54, 14.49) –0.59 (–8.33, 7.16) PaedCTAS 4&5 11.87 (6.24, 17.51) 2.29 (–4.56, 9.16) Time*CTAS3 –0.61 (–1.25, 0.02) –0.02 (–0.73, 0.69) Time*PaedCTAS 4&5 –1.07 (–1.58, –056) –0.36 (–1.03, 0.32) a“Crude” models include the covariate, time and the interaction between time and the covariate bAdjusted for all other variables in table including interaction terms Fig. 2 GEE estimates for injuries requiring hospitalization vs ED visit*. *Holding all other variables in model constant as: female; PaedCTAS of 1 or 2; 7.1 years of age (median age of population) and baseline PedsQl of 90.7 (mean of population) Although injury severity, as measured by hospitalization, increased the rate of recovery, it did not impact the state of recovery (a child’s HRQoL score at a given timepoint) beyond one month post injury. The mean HRQoL score for children who were hospitalized was significantly lower than those who presented to ED at one month post injury (65.9 vs 82.6, p <0.001) however this difference was no longer evident at four or 12 months (Table 3). Likewise children with lower PaedCTAS scores had significantly lower HRQoL scores one month post injury, a difference that again disappeared by four and 12 months. When broken down into psychosocial and physical components of HRQoL however, we found that a greater proportion of children who were hospitalized continued to have diminished scores for the physical component of the HRQoL measurement through to 12 months post injury (16.7 % of hospitalized children vs 7.6 % of children presenting to ED, p = 0.05) although there was not a significant difference in the psychosocial domain of HRQoL at four or 12 months between these two groups (Table 4). Discussion In accordance with previous work [13, 25], we found that most children’s summary HRQoL score had returned to within one standard deviation of baseline by four months post injury. Hospitalization status and age were the only variables associated with a significant change in the rate of recovery, with children who were admitted and older children having a faster rate (steeper slope) to recovery relative to those who were seen in the ED and younger children. This finding demonstrates that children with greater impact on HRQoL at one month post injury (those hospitalized and older children) recover at an accelerated rate and by four months post injury there is no difference in HRQoL impact relative to their ED and younger peers. Hospitalized children may have experienced a greater impact on HRQoL at one month relative to children seen in the ED due to time away from school/peers, and injuries that resulted in a greater impact on activities of daily living. Older children (those > 5 years of age) may have experienced a greater impact on HRQoL at one month post injury as they are more independent relative to younger children in activities of daily living and leisure activities. Thus, their injuries may have resulted in a greater loss of independence. Our findings are consistent with the findings of the UK burden of injury multicenter study that recruited almost 300 hundred participants under 18 years of age. They found that admission status and injury severity were the only variables associated with recovery at one month post injury among 5-17 year olds, and that 91 % of participants had recovered by 12 months post injury [25]. In addition, Polinder et al., reported that less than 10 % of their study population of injured children 5-14 years had residual disability after nine months with girls and hospitalized children having higher odds of longer lasting disability [13]. Further, a 2012 systematic review on studies of children who have suffered traumatic brain injuries found that the odds of experiencing poor Quality of Life increased with more severe injuries (assessment time points ranged from three months to five years) [26]. However, even among children with TBI, a recent study found that by 18 months post injury parent ratings of children’s HRQoL returned to the normal range for most children, regardless of injury severity [27]. In the current study, at four and 12 months a higher proportion of hospitalized children, relative to their unadmitted counterparts, still had physical HRQoL scores that were at least one standard deviation lower than their baseline score while their total and psychosocial scores were on par with baseline. PaedsCTAS did not have a significant impact on recovery despite being a measure of severity. It is possible this result is due to the fact that although PaedsCTAS has been found to be associated with physical recovery, no relationship with psychosocial recovery has been observed [19]. Future analysis will explore predictors of physical and psychosocial functioning independently. The utility of providing targeted rehabilitation support, such as occupational and physical therapy, throughout recovery to injured children who were hospitalized to help diminish this impact could be investigated in future research. Variables that could be used to predict and protect the subset of children at high risk of long-term or more serious impact, outside of lengthy hospitalization and possibly severe traumatic brain injury [28, 29] have not been consistently demonstrated across studies. Some studies have found that children involved in motor vehicle accidents [30] and burn victims [31] can have more psychological and/or longer lasting sequalae relative to other injuries; the sample size of children with these mechanisms of injury in the current study was too small to investigate this further. Our findings can inform the debate regarding the tradeoff between the benefits of a physically active lifestyle versus potential impacts on HRQoL resulting from childhood injuries [32–38]. Among our sample, 63 % were engaged in leisure/physical activity at the time of their injury, highlighting the high incidence of these injuries. Our data did not include information on exposure time, however, a systematic review calculated that the injury incidence rate during leisure/physical activity was between 0.15-0.27 medically attended injuries per 1,000 h of physical activity, indicating that while they may be prevalent, they are relatively rare when accounting for exposure [39]. In those relatively rare cases when injury does occur, our findings suggest that most children recuperate quickly, with HRQoL comparable to pre-injury levels by four-months post-injury. The limitations of this study should be noted in interpreting the findings. Despite our best efforts, the study sample represents 30 % of the eligible population that was approached for study participation. Our response rates appear to be lower than other comparable longitudinal injury studies of children attending an ED or admitted to hospital for an injury. For example, Polinder et al.’s pediatric study had a response rate of 43 % [13], while Lyons et al.’s study of injured children and adults had a participation rate of 66 % [25, 40]. However, when we compared the study population to the broader population of children presenting at BCCH with an injury, we found that our sample matched all injured children, with the exception of income with our study population having a significantly lower proportion of individuals from the lowest two income quintiles. It is possible that being from a lower income bracket could be associated with a detrimental impact on HRQoL recovery, which may not have been captured in this study due to small sample size. The influence of income was not examined in Polinder et al. and Lyons et al.’s research, thus limiting our understanding of this issue. Our sensitivity analysis indicated no significant differences in HRQoL over time resulting from excluding participants due to missing data. We were successful in sampling a breadth of injuries and over-sampling injuries that required hospitalization. As with any longitudinal research, there was attrition over the course of this study. Those lost to follow-up had a lower mean baseline HRQoL score relative to those who completed the study period; however, this difference was less than the minimal clinically important difference of 4.5 points [41]. Finally, baseline health prior to injury was based on a retrospective measure and it is possible that parents under- or over-represented child health prior to injury. It has been suggested that baseline measures collected at recruitment are more appropriate than healthy population norms for the purpose of determining the impact of injury on HRQoL in an adult population [42]. No study, to our knowledge, has examined this in a pediatric population. Conclusions This study examined the longitudinal recovery of children in the year following injury. Our findings indicate that very few injuries have a long lasting impact on children’s HRQoL, demonstrating children’s resilience to physical trauma. This research contributes to, and expands upon the current literature on recovery from childhood injury by including a wide age-range of children, looking at a longer time period post-injury, and using a pediatric tool to measure HRQoL. Older and hospitalized children experienced greater short-term impact to HRQoL and a steeper slope to recovery. On average, hospitalized children continued to experience greater impact to the physical domain of their HRQoL throughout the year post-injury. On-going rehabilitation support should be considered as a mechanism to reduce physical sequalae. Overall, the rapid recovery trajectory for most injuries encourages children’s participation in active healthy lifestyles. Abbreviations BCBritish Columbia BCCHBritish Columbia children’s hospital EDEmergency department GEEGeneralized estimating equation HRQoLHealth related quality of life PaedCTASPediatric Canadian triage and acuity scale PedsQL™Pediatric quality of life questionnaire Acknowledgements The authors would like to extend their gratitude and acknowledgements to all study participants and study team members for their time and energy spent on this project. Salary support for authors was provided by the BCCH (MB, JB) and by a Michael Smith Foundation for Health Research Scholar Award (MB). Funding This study was funded by the Canadian Institutes of Health Research (Grant # TIR-104028), as well as the Michael Smith Foundation for Health Research. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Availability of data and material The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Authors’ contributions AS was involved with data collection, designed and carried out statistical analyses, drafted the initial manuscript and approved the final manuscript as submitted. MB conceptualized and designed the study, oversaw data collection, reviewed and revised the manuscript and approved the final manuscript as submitted. CM was involved with study conceptualization and design, reviewed and revised the manuscript and approved the final manuscript as submitted. JB was involved with developing the analysis plan, reviewed and revised the manuscript and approved the final manuscript as submitted. SK, TI, and EZ were involved with study implementation, data collection, reviewed and revised the manuscript and approved the final manuscript as submitted. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate This study was reviewed and approved by the University of British Columbia/Children’s and Women’s Health Centre of British Columbia Research Ethics Board, reference number H09-01627. Informed and written consents were obtained from parents of all agreed participating children and assent from all participating children aged 7 and older. Participants were informed about their freedom from refusal and any decision which they may take would not affect their healthcare services. Anonymity and confidentiality were maintained throughout the research process. ==== Refs References 1. Peden M Oyegbite K Ozanne-Smith J Hyder AA Branche C Rahman AKMF Rivara F Bartolomeos K World Report on Child Injury Prevention 2008 Geneva World Health Organization Press 2. Centers for Disease Control and Prevention. National Center for Injury Prevention and Control National Action Plan for Child Injury Prevention 2012 Atlanta CDC, NCIPC 3. Grad FP. Preable to the Constitution of the World Health Organization. B World Health Organ. 2002;80:981–84. 4. Guyatt GH Feeny DH Patrick DL Measuring health-related quality of life Ann Intern Med 1993 118 622 9 10.7326/0003-4819-118-8-199304150-00009 8452328 5. Patrick D Erickson P Walker SR Rosser RM Assessing health-related quality of life for clinical decision-making Quality of Life Assessment: Key Issues in the 1990s 1993 Dordrecht Springer Netherlands 11 64 6. Kenardy JA Spence SH Macleod AC Screening for posttraumatic stress disorder in children after accidental injury Pediatrics 2006 118 1002 9 10.1542/peds.2006-0406 16950991 7. March S Kenardy JA Cobham VE Nixon RDV McDermott B De Young A Feasibility of a Screening Program for At-Risk Children Following Accidental Injury J Trauma Stress 2015 28 34 40 10.1002/jts.21981 25703937 8. Kassam-Adams N, Bakker A, Marsac ML, Fein JA, Winston FK. Traumatic Stress, Depression, and Recovery. Pediatr Emerg Care. 2015;1. 9. Polinder S Haagsma JA Belt E Lyons RA Erasmus V Lund J Van Beeck EF A systematic review of studies measuring health-related quality of life of general injury populations BMC Public Health 2010 10 783 10.1186/1471-2458-10-783 21182775 10. van Beeck Larson CF, Lyons RA, Meerding W, Mulder S, Essink-Bot M. EF. Guidelines for the conduction of follow up studies measuring injury-related disability. J Trauma. 2007;62:534–550. 11. Polinder S Haagsma JA Toet H van Beeck EF Epidemiological burden of minor, major and fatal trauma in a national injury pyramid Br J Surg 2012 99 (Suppl 1) 121 22441865 12. Aitken ME Tilford JM Barrett KW Parker JG Simpson P Landgraf J Robbins JM Health Status of Children After Admission for Injury Pediatrics 2002 110 337 342 10.1542/peds.110.2.337 12165587 13. Polinder S Meerding WJ Toet H Mulder S Essink-Bot M-L van Beeck EF Prevalence and prognostic factors of disability after childhood injury Pediatrics 2005 116 e810 7 10.1542/peds.2005-1035 16322139 14. Davey TM Aitken LM Kassulke D Bellamy N Ambrose J Gee T Clark M Long-term outcomes of seriously injured children: a study using the Child Health Questionnaire J Paediatr Child Health 2005 41 278 83 10.1111/j.1440-1754.2005.00611.x 15953329 15. Desai AD Zhou C Stanford S Haaland W Varni JW Mangione-Smith RM Validity and responsiveness of the pediatric quality of life inventory (PedsQL) 4.0 generic core scales in the pediatric inpatient setting JAMA Pediatr 2014 168 1114 21 10.1001/jamapediatrics.2014.1600 25347549 16. Varni JW Seid M Kurtin PS PedsQL 4.0: reliability and validity of the Pediatric Quality of Life Inventory version 4.0 generic core scales in healthy and patient populations Med Care 2001 39 800 12 10.1097/00005650-200108000-00006 11468499 17. Kruse S Schneeberg A Brussoni M Construct validity and impact of mode of administration of the PedsQL™ among a pediatric injury population Health Qual Life Outcomes 2014 12 168 10.1186/s12955-014-0168-2 25433795 18. Gouin S Gravel J Amre DK Bergeron S Evaluation of the Paediatric Canadian Triage and Acuity Scale in a pediatric ED Am J Emerg Med 2005 23 243 247 10.1016/j.ajem.2004.02.046 15915392 19. Yates M, Ishikawa T, Schneeberg A, Brussoni M. Pediatric Canadian Triage and Acuity Scale (PasedsCTAS) as a Measure of Injury Severity. Int J Environ Res Public Heal. 2016;13. 20. Statistics Canada Postal Code Conversion File Plus PCCF+ Version 5 F User’s Guide 2010 Ottawa Minister of Industry. Statistics Canada Catalogue no 82-E0086-XDB 21. Varni JW Seid M Knight TS Uzark K Szer IS The PedsQLTM 4.0 Generic Core Scales: Sensitivity, Responsiveness, and Impact on Clinical Decision-Making J Behav Med 2002 25 175 193 10.1023/A:1014836921812 11977437 22. Willis Gabbe BJ, Butt W, Cameron PA. CD. Assessing outcomes in paediatric trauma populations. Inj Int J Care Inj. 2006;37:1185–96. 23. Janssens L Gorter JW Ketelaar M Kramer WLM Holtslag HR Health-related quality-of-life measures for long-term follow-up in children after major trauma Qual Life Res 2008 17 701 13 10.1007/s11136-008-9339-0 18437531 24. Varni JW, Burwinkle TM, Seid M, Skarr D. The PedsQL 4.0 as a pediatric population health measure: feasibility, reliability, and validity. Ambul Pediatr. 2003;3:329–41. 25. Kendrick D Vinogradova Y Coupland C Mulvaney CA Christie N Lyons RA Towner EL Recovery from injury: the UK burden of injury multicentre longitudinal study Inj Prev 2013 19 370 81 10.1136/injuryprev-2012-040658 23599210 26. Battista A Di, Soo C, Catroppa C, Anderson V. Quality of Life in Children and Adolescents Post-TBI: A Systematic Review and Meta-Analysis. J Neurotraum. 2012;29:1717–27. 27. Brown EA Kenardy J Chandler B Anderson V McKinlay L Le Brocque R Parent-Reported Health-Related Quality of Life in Children With Traumatic Brain Injury: A Prospective Study J Pediatr Psychol 2016 41 244 255 10.1093/jpepsy/jsv090 26395759 28. Stancin T Drotar D Taylor HG Yeates KO Wade SL Minich NM Health-Related Quality of Life of Children and Adolescents After Traumatic Brain Injury Pediatrics 2002 109 e34 10.1542/peds.109.2.e34 11826244 29. McCarthy ML MacKenzie EJ Durbin DR Aitken ME Jaffe KM Paidas CN Slomine BS Dorsch AM Christensen JR Ding R Health-related quality of life during the first year after traumatic brain injury Arch Pediatr Adolesc Med 2006 160 252 60 10.1001/archpedi.160.3.252 16520444 30. Winston FK Kassam-Adams N Vivarelli-O’Neill C Ford J Newman E Baxt C Stafford P Cnaan A Acute Stress Disorder Symptoms in Children and Their Parents After Pediatric Traffic Injury Pediatrics 2002 109 e90 10.1542/peds.109.6.e90 12042584 31. van Baar ME Polinder S Essink-Bot ML van Loey NEE Oen IMMH Dokter J Boxma H van Beeck EF Quality of life after burns in childhood (5-15 years): children experience substantial problems Burns 2011 37 930 8 10.1016/j.burns.2011.05.004 21724334 32. Langley J Cryer C A consideration of severity is sufficient to focus our prevention efforts Inj Prev 2012 18 73 4 10.1136/injuryprev-2011-040278 22294564 33. Brussoni M, Brunelle S, Pike I, Sandseter EBH, Herrington S, Turner H, Belair S, Logan L, Fuselli P, Ball DJ. Can child injury prevention include healthy risk promotion? Inj Prev. 2014;21:344-47. 34. Rivara F Counterpoint: minor injuries may not be all that minor Inj Prev 2011 17 149 50 10.1136/injuryprev-2011-040035 21507885 35. Brussoni M Olsen LL Pike I Sleet D Risky play and children’s safety: Balancing priorities for optimal child development Int J Environ Res Public Health 2012 9 3134 3138 10.3390/ijerph9093134 23202675 36. Molcho M Pickett W Some thoughts about “acceptable” and “non-acceptable” childhood injuries Inj Prev 2011 17 147 148 10.1136/ip.2010.030023 21429895 37. Tremblay MS Gray C Babcock S Barnes J Bradstreet CC Carr D Chabot G Choquette L Chorney D Collyer C Herrington S Janson K Janssen I Larouche R Pickett W Power M Sandseter EBH Simon B Brussoni M Position Statement on Active Outdoor Play Int J Environ Res Public Health 2015 12 6475 6505 10.3390/ijerph120606475 26062040 38. Brussoni M Gibbons R Gray C Ishikawa T Sandseter EBH Bienenstock A Chabot G Fuselli P Herrington S Janssen I Pickett W Power M Stanger N Sampson M Tremblay MS What is the Relationship between Risky Outdoor Play and Health in Children? A Systematic Review Int J Environ Res Public Health 2015 12 6423 6454 10.3390/ijerph120606423 26062038 39. Nauta J Martin-Diener E Martin BW van Mechelen W Verhagen E Injury risk during different physical activity behaviours in children: a systematic review with bias assessment Sports Med 2015 45 327 36 10.1007/s40279-014-0289-0 25430601 40. Lyons RA Kendrick D Towner EM Christie N Macey S Coupland C Gabbe BJ UK Burden of Injuries Study Group Measuring the population burden of injuries--implications for global and national estimates: a multi-centre prospective UK longitudinal study PLoS Med 2011 8 10.1371/journal.pmed.1001140 22162954 41. Varni JW Burwinkle TM The PedsQL as a patient-reported outcome in children and adolescents with Attention-Deficit/Hyperactivity Disorder: a population-based study Health Qual Life Outcomes 2006 4 26 36 10.1186/1477-7525-4-26 16630344 42. Watson WL Ozanne-Smith J Richardson J Retrospective baseline measurement of self-reported health status and health-related quality of life versus population norms in the evaluation of post-injury losses Inj Prev 2007 13 45 50 10.1136/ip.2005.010157 17296689

PMC005xxxxxx/PMC5000469.txt

==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3082810.1038/srep30828ArticleA Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study Haghighi Mona 1Johnson Suzanne Bennett 2Qian Xiaoning 3Lynch Kristian F. 4Vehik Kendra 4Huang Shuai a5The TEDDY Study GroupRewers Marian 6Barriga Katherine 6Baxter Judith 6Eisenbarth George 6Frank Nicole 6Gesualdo Patricia 6Hoffman Michelle 6Norris Jill 6Ide Lisa 6Robinson Jessie 6Waugh Kathleen 6She Jin-Xiong 78Schatz Desmond 78Hopkins Diane 78Steed Leigh 78Choate Angela 78Silvis Katherine 78Shankar Meena 78Huang Yi-Hua 78Yang Ping 78Wang Hong-Jie 78Leggett Jessica 78English Kim 78McIndoe Richard 78Dequesada Angela 78Haller Michael 78Anderson Stephen W. 78Ziegler Anette G. 91011Boerschmann Heike 91011Bonifacio Ezio 91011Bunk Melanie 91011Försch Johannes 91011Henneberger Lydia 91011Hummel Michael 91011Hummel Sandra 91011Joslowski Gesa 91011Kersting Mathilde 91011Knopff Annette 91011Kocher Nadja 91011Koletzko Sibylle 91011Krause Stephanie 91011Lauber Claudia 91011Mollenhauer Ulrike 91011Peplow Claudia 91011Pflüger Maren 91011Pöhlmann Daniela 91011Ramminger Claudia 91011Rash-Sur Sargol 91011Roth Roswith 91011Schenkel Julia 91011Thümer Leonore 91011Voit Katja 91011Winkler Christiane 91011Zwilling Marina 91011Simell Olli G. 1213141516171819Nanto-Salonen Kirsti 1213141516171819Ilonen Jorma 1213141516171819Knip Mikael 1213141516171819Veijola Riitta 1213141516171819Simell Tuula 1213141516171819Hyöty Heikki 1213141516171819Virtanen Suvi M. 1213141516171819Kronberg-Kippilä Carina 1213141516171819Torma Maija 1213141516171819Simell Barbara 1213141516171819Ruohonen Eeva 1213141516171819Romo Minna 1213141516171819Mantymaki Elina 1213141516171819Schroderus Heidi 1213141516171819Nyblom Mia 1213141516171819Stenius Aino 1213141516171819Lernmark Åke 20Agardh Daniel 20Almgren Peter 20Andersson Eva 20Andrén-Aronsson Carin 20Ask Maria 20Karlsson Ulla-Marie 20Cilio Corrado 20Bremer Jenny 20Ericson-Hallström Emilie 20Gard Thomas 20Gerardsson Joanna 20Gustavsson Ulrika 20Hansson Gertie 20Hansen Monica 20Hyberg Susanne 20Håkansson Rasmus 20Ivarsson Sten 20Johansen Fredrik 20Larsson Helena 20Lernmark Barbro 20Markan Maria 20Massadakis Theodosia 20Melin Jessica 20Månsson-Martinez Maria 20Nilsson Anita 20Nilsson Emma 20Rahmati Kobra 20Rang Sara 20Järvirova Monica Sedig 20Sibthorpe Sara 20Sjöberg Birgitta 20Törn Carina 20Wallin Anne 20Wimar Åsa 20Hagopian William A. 21Yan Xiang 21Killian Michael 21Crouch Claire Cowen 21Hay Kristen M. 21Ayres Stephen 21Adams Carissa 21Bratrude Brandi 21Fowler Greer 21Franco Czarina 21Hammar Carla 21Heaney Diana 21Marcus Patrick 21Meyer Arlene 21Mulenga Denise 21Scott Elizabeth 21Skidmore Jennifer 21Small Erin 21Stabbert Joshua 21Stepitova Viktoria 21Becker Dorothy 22Franciscus Margaret 22Dalmagro-Elias Smith MaryEllen 22Daftary Ashi 22Krischer Jeffrey P. 4Abbondondolo Michael 4Ballard Lori 4Brown Rasheedah 4Cuthbertson David 4Eberhard Christopher 4Gowda Veena 4Lee Hye-Seung 4Liu Shu 4Malloy Jamie 4McCarthy Cristina 4McLeod Wendy 4Smith Laura 4Smith Stephen 4Smith Susan 4Uusitalo Ulla 4Yang Jimin 4Akolkar Beena 23Briese Thomas 24Erlich Henry 25Oberste Steve 26 1 Department of Industrial and Management Systems Engineering, University of South Florida, Tampa, Florida, USA2 Department of Behavioral Sciences and Social Medicine, College of Medicine, Florida State University, Tallahassee, Florida, USA3 Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, USA4 Health Informatics Institute, University of South Florida, Tampa, Florida, USA5 Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington, USA6 University of Colorado, Anschutz Medical Campus, Barbara Davis Center for Childhood Diabetes, Aurora, Colorado, United States7 University of Florida, Gainesville, Florida, United States8 Pediatric Endocrine Associates, Atlanta, Georgia, United States9 Diabetes Research Institute, Center for Regenerative Therapies, TU Dresden, Institute of Psychology, University of Graz, Austria10 Von Hauner Children´s Hospital, Department of Gastroenterology, Ludwig Maximillians University Munich, Germany11 Research Institute for Child Nutrition, Dortmund, Germany12 University of Turku, Turku, Finland13 Turku University Hospital, Hospital District of Southwest Finland, Turku, Finland14 University of Tampere, Tempere, Finland15 Tampere University Hospital, Tempere, Finland16 University of Kuopio, Kuopio, Finland17 Oulu University Hospital, Oulu, Finland18 University of Oulu, Oulu, Finland19 National Institute for Health and Welfare, Helsinki, Finland20 Lund University, Lund, Sweden21 Pacific Northwest Diabetes Research Institute, Seattle, Washington, United States22 Children’s Hospital of Pittsburgh of UPMC, Pittsburgh, Pennsylvania, United States23 National Institutes of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, United States24 Columbia University, New York, United States25 Children’s Hospital Oakland Research Institute, California, United States26 Centers for Disease Control and Prevention, Atlanta, Georgia, United States.a shuai.huang.ie@gmail.com* A comprehensive list of consortium members appears at the end of the paper 26 08 2016 2016 6 3082807 04 2016 11 07 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions. ==== Body Understanding the factors associated with the risk of individuals withdrawing from a study is an important first step towards identifying the eventual health needs of different individuals within a population1. This lays the foundation to develop and deliver appropriate resources to the right targets, called “tailored health interventions”. Evidence suggests that individuals prefer tailored care to a standardized care that is designated for the average population2345. Therefore, health professionals need to identify the subgroups of individuals characterized by different patterns of risk factors. However, rather than identifying subgroups, traditional intervention studies often focus on identification of risk factors that are associated with the outcome of interest for the population as a whole167. One commonly adopted approach is to use logistic regression to identify factors associated with study withdrawal8910. However, this approach only models the average effects of the risk factors. Consequently, it is likely that the interventions developed from regression models will be geared toward the average member of the population, with less consideration of the special needs of different subgroups11. The aim of the present study is to illustrate the use of the rule-based analysis121314 as an exploratory technique in an epidemiologic context. The rule-based analysis121314 is particularly useful for identifying the subgroups embedded in a dataset—whose members share similar risk patterns—that influence the outcome of interest. A rule describes the range of values on one or more risk factors that are associated with either an increase or decrease in risk for withdrawal in a subset of individuals. Thus, rules provide a natural semantics to define the risk pattern of subsets of individuals while each rule may indicate a specific unmet health need or warning signal for study withdrawal. By identifying the unknown rules from observational studies, a comprehensive set of risk-predictive rules can be considered as a set of sensors, providing us personalized risk estimation by looking into the risk patterns endorsed by each individual. Specifically, we used a recently developed rule-discovery algorithm for the rule-based analysis, the RuleFit method14, which is one example from a huge array of rule-based methods that are promising for epidemiologic research. The RuleFit method has an advantage over logistic regression because it relies on a nonparametric model with fewer modeling assumptions, random forest13, which is capable of identifying the risk predictive rules. There is no need to explicitly include covariate interactions or transformations into the model because of the recursive splitting structure used in generating the random forest. Also, the rule-based analysis permits an individual’s risk to be predicted on the basis of only one, or at most a few, risk factors, whereas scores derived from regression models require that all covariates be available. We demonstrate the rule-based analysis using data from a large multinational epidemiological natural history study of type 1 diabetes mellitus (T1DM), the Environmental Determinants of Diabetes in the Young (TEDDY) study15. Specifically, we use the rule-based analysis for predicting study withdrawal during the first year of the TEDDY study, by effectively integrating the psychosocial, demographic, and behavioral risk factors collected at study inception. We compare the rule-based analysis with a previous analysis that was conducted on the same data10. The previous analysis used traditional logistic regression methods to identify factors collected at study inception that were strongly associated with study withdrawal during the first year of TEDDY10. However, the way these factors interact with each other and the way these interactions might define subgroups in the study population with different risk levels remain unknown. Therefore, we tested the hypothesis that the rule-based analysis can identify the risk-predictive rules useful for stratifying the study population into different subgroups with different risk levels for study withdrawal in the first year of TEDDY. The previous analysis10 provided us an opportunity for critically evaluating the potential added value of a rule-based analysis over that provided by traditional logistic regression methods. Also, we considered how the rule-based method could lead to more informed intervention strategies or prioritization of the intervention allocation to the study participants. By conducting this comparison, we also hoped to identify some practical guidelines for when we should use rule-based methods and when regressions model would be more preferable, enriching the analytic toolbox of today’s epidemiologists to address the emerging data challenges. Materials and Methods The TEDDY study TEDDY is a natural history study that seeks to identify the environmental triggers of autoimmunity and T1DM onset in genetically at-risk children identified at three centers in the United States (Colorado, Washington, and Georgia/Florida) and three centers in Europe (Finland, Germany, and Sweden). Infants from the general population with no immediate family history of T1DM, as well as infants who have a first degree relative with T1DM, are screened for genetic risk at birth using human leukocyte antigen genotyping. Parents with infants at increased genetic risk for T1DM are invited to participate in TEDDY. Parents are fully informed of the child’s increased genetic risk and the protocol requirements of the TEDDY study, including the requirement that eligible infants must join TEDDY before the infant is 4.5 months of age. The TEDDY protocol is demanding with study visits for blood draws and other data and sample collection scheduled every three months during the first four years of the child’s life and biannually thereafter. Parents are also asked to keep detailed records of the child’s diet, illnesses, life stresses and other environmental exposures. TEDDY obtains written consent from the parents shortly after child’s birth for obtaining genetic and other samples from the infant and also parents. Detailed study design and methods have been previously published15. The study methods have been carried out in accordance with the approved guidelines by local Institutional Review or Ethics Boards and monitored by an External Evaluation Committee formed by the National Institutes of Health. The experimental protocols of the study were approved by the National Institute of Health. Study sample This analysis focused on two groups of families from the general population used in the previous logistic regression study10: 2,994 families who had been active in TEDDY for ≥1 year and 763 families who withdrew from TEDDY during the first year. Both the prior and current analyses were limited to general population families because study withdrawal among the first degree relatives population was rare. Study variables Study variables were selected from data collected on the screening form at the time of the child’s birth and from interview and questionnaire data collected at the baby’s first TEDDY visit. These variables included: demographic characteristics—TEDDY country (Finland, Germany, Sweden, United States); mother’s age (in years); child’s gender; maternal health during pregnancy‒number of illnesses, gestational diabetes or type 2 diabetes (yes/no); mother’s lifestyle behaviors during pregnancy—smoked at any time during pregnancy (yes/no), alcohol consumption (no alcohol, 1–2 times per month, ≥3 times per month during each trimester), employment status (worked during all 3 trimesters/did not work at all or reduced work hours); baby’s health status‒birth complications (yes/no), health problems since birth (yes/no), hospitalizations after birth (yes/no); number of stressful life events during and after pregnancy; mother’s emotional status including worry and sadness during pregnancy (rated on 5 point scales), anxiety about the child’s risk of developing diabetes measured by a six-item scale adapted from the State component of the State-Trait Anxiety Inventory234; the accuracy of the mother’s perception of the child’s risk for developing diabetes (accurate: indicating the child’s T1DM risk was higher or much higher than other children’s T1DM risk; inaccurate: indicating the child’s T1DM risk was the same, somewhat lower or much lower than other children’s T1DM risk); and whether the child’s father completed the initial study questionnaire (yes/no). Previous logistic regression results Multiple logistic regression models were used to identify significant predictors of early withdrawal from TEDDY. Variables were entered in blocks in the following order: demographic variables (country of residence, child’s gender, mother’s age); pregnancy/birth variables (maternal diabetes, illness in mother or child, birth complications, maternal smoking; maternal drinking; maternal employment outside the home, maternal worry or sadness during pregnancy, number of stressful life events occurring during pregnancy or after the child’s birth); father’s participation in TEDDY defined by father’s completion of a brief questionnaire; and mother’s reactions to the baby’s increased T1DM risk (anxiety and accuracy of mother’s perception of the child’s T1DM risk). Nine percent of the study sample (N = 326) had missing data on one or more variables. As expected, those subjects who had difficulty in complying with all data collection (35%) were more likely to withdraw than those with high data collection compliance (19%). While it is unknown what is the underlying mechanism that could explain this association, we suspect that this could indicate that the percentage of missing data is a good indicator that suggests a need for TEDDY study to better communicate with participant families and remove any possible difficulties for them to participate in the study. The analysis was first completed for those with no missing data and then rerun for the full sample using multiple imputation methods to generate appropriate parameter estimates for missing data using the Proc MI and Proc MIANALYZE procedures available from SAS 9.15. Table 1 provides the results of the final logistic regression model for the sample of 3,431 TEDDY participants with no missing data. The model was highly significant (Chi-Square  = 264.87 (12), p < 0001) and accurately placed 81.6% of the sample into their respective group (Actives versus Withdrawals). The data in Table 1 also provides the final logistic regression model for the total sample, with multiple imputation methods used to replace missing data. Because the early withdrawal rate was higher among participants with missing data, we added a variable to the imputed model, >1 missing data point (yes/no). The presence of >1 missing data points predicted early drop-out over and above all other variables in the model. The descriptive information for each of the significant predictors is provided in Table 2. Statistical methods Basic idea of the RuleFit method We use RuleFit14 to discover the hidden rules that may be predictive of the risk of early withdrawal in subsets of TEDDY individuals. A rule consists of several interacting risk factors and their ranges. We are interested in the rules by which the subjects can be stratified by distinct risk levels. For example, a rule consisting of State Anxiety Inventory Score >45 and Dad Participation = NO would be useful if the subjects who can be characterized by this rule have a higher risk of early withdrawal. RuleFit is a computational algorithm that can scale up for high-dimensional applications (e.g., with a large number of variables) for rule discovery, which is capable of exhaustively searching for potential rules on a large number of candidate risk factors. It has two phases, the “rule generation phase” and “rule pruning phase”. Rule generation At this stage, random forest13 is used to exhaustively search for candidate rules over the potential risk factors. Random forest is a high-dimensional rule discovery approach that extends traditional decision tree models12. Specifically, a random forest estimates a number of trees, with each tree being estimated on a relatively homogenous subpopulation generated by bootstrapping the original dataset. Since each tree employs a set of rules to characterize a subpopulation, the random forest is actually a comprehensive collection of rules that are able to characterize the whole dataset. Rule pruning As a heuristic and exhaustive search approach, the random forest may produce a large number of rules that can be redundant or irrelevant to predicting early withdrawal due to overfitting. To address this, the sparse regression model1617 can be applied to select a minimum set of risk-predictive rules, by using all the potential rules as predictors and the withdrawal status as the outcome. The sparse regression model is a high-dimensional variable selection model that can be applied on a large number of variables, and has been widely used in bioinformatics and systems biology1819. In what follows, we illustrate the details of how the RuleFit method uses the three models, the decision tree, random forest, and sparse linear regression models, in the rule generation stage and the rule pruning stage: Stage 1 of RuleFit - Rule generation Rule generation is computationally challenging, since the number of potential rules grows exponentially in relationship to the number of risk factors. Given such a large number of potential rules, an intelligent rule generator is needed to narrow down the search by effectively detecting high-quality risk-predictive rules. Decision tree learning method provides such an intelligent rule generator. A decision tree is a technique for segmenting the population into different subgroups using a set of rules. For example, we use the decision tree model for analyzing the TEDDY dataset to divide the population into homogeneous subgroups based on the percentage of study withdrawals in each subgroup. The decision tree model is a nonparametric method that automatically explores the given risk factors and their interactions for a tree that has high accuracy in predicting study withdrawal. In our analysis, as shown in Fig. 1, three subgroups with distinct risk levels are identified and can be characterized by rules defined by maternal age, smoking status, number of missing data, and a geographical indicator for Finland. For example, the leftmost node characterizes a subgroup of subjects, in which all of them have Maternal age <27.5 and Finland = NO. The risk of study withdraw in this subgroup is 0.38. This analysis demonstrates that the decision tree model is a powerful tool for detecting the subgroups that can be characterized by rules. Note that, the cut-off value of each factor used in Fig. 1 is automatically determined by the Recursive Partitioning Algorithm (RPA). One limitation of the decision tree is that only exclusive rules can be identified. For instance, the decision tree in Fig. 1 implies that each participant can only be characterized by one single rule, which doesn’t consider the possibility that a participant may have multiple risk patterns characterized by different factors or different interactions between factors. As a remedy, random forest13 is a high-dimensional rule discovery approach that extends traditional decision tree models. It estimates a number of trees: in each iteration, we estimate a decision tree on a bootstrapped sample of the training set, and this process iterates until the pre-specified number of trees is achieved13. To understand the random forest, it is worth mentioning that the essence of this iterative procedure is to generate a large number of substantially different trees, since the more similar the trees are, the less advantage estimating multiple trees has. In order to achieve this goal, randomization methods are used, which is the reason for the name “random forest”. Specifically, in estimating each tree, the bootstrap technique is used for generating a different training sample by randomly reweighting the original dataset. Subsequently, in the estimation of each tree, a subset of risk factors is randomly selected for estimating the tree. Therefore, as each tree is built for a sub-population using a subset of risk factors, the heterogeneity of the participants is well addressed in the random forest model, increasing the likelihood of detecting meaningful risk-predictive rules for different subgroups13. As each tree can be decomposed to a number of rules, e.g., in Fig. 1, we could extract at least five rules while each rule corresponds to a leaf node in the tree, with random forest we could collect many rules. Stage 2 of RuleFit - Rule pruning Rule pruning is essentially a procedure of selecting a subset of rules out of a pool of q candidate rules, denoted as R = [R1, R2, …, Rq], which are predictive to the output variable Y. This problem is particularly challenging in high-dimensional settings where we have a large number of generated rules and q is large. One solution to select the most critical rules is to adopt the Least Absolute Shrinkage Selection Operator (LASSO)16, which is a sparse linear regression model that is capable of identifying a subset of relevant variables out of a huge list of candidate variables. Specifically, the formulation of LASSO is Here, the square error term, is used to measure the model fit. The L1-norm penalty term ||β||1 (16), defined as the sum of the absolute values of all elements in β, is used to measure the complexity of the regression model. The user-specified penalty parameter, λ, aims to achieve an optimal balance between the model fitness and model complexity – larger λ will result in sparser estimate for β. It has been shown that LASSO is consistent on variable selection both from theoretical research16 and empirical studies17181920. Efficient algorithms have been developed to solve the optimization problem, such as the shooting algorithm16, proximal gradient algorithms17, etc. Through LASSO, we expect that the rules with critical risk factor patterns will be identified with controlled redundancy. In our study, since the output variable Y, i.e., the withdrawal status, is a binary variable, the sparse logistic regression17 is a better choice than linear regression, which can be readily implemented in the R package of RuleFit14. In summary, RuleFit is computationally efficient since efficient algorithms have been developed for both Random Forest and sparse linear regression models. RuleFit has an automated cross-validation procedure for tuning its parameters, such as the number of trees, the size of the trees and the penalty parameter λ in LASSO, which can be used to obtain a set of high-quality rules. More details about RuleFit can be found in14. Figure 2 also provides a schematic description of the Rulefit algorithm. Results Identified risk-predictive rules Table 3 provides the risk-predictive rules identified by the RuleFit algorithm for the Active and Withdrawn families used in the previous logistic regression analysis10. The risk factors identified in the risk-predictive rules are the same as those identified in the previous logistic regression analysis: demographic factors including maternal age and country, maternal lifestyle factors during pregnancy including as smoking, drinking, and working outside the home, psychosocial factors including the mother’s perception of the child’s risk and her anxiety about the child’s risk, dad participation, and the number of missing data points. In addition, the interaction between the state anxiety inventory score with the risk perception accuracy found in the previous study, which further validated in the rule-based analysis (see Table 1 and Table 3). However, the rule-based analysis was more powerful at detecting the interactions between the risk factors. In addition, the rule-based approach identified the number of negative life events as a risk factor, a variable that was not significant in the prior logistic regression analysis. And the rule-based approach found no significant role for child gender, which had a weak effect in the prior analysis (see Table 3). Note that the rules shown in Table 3 were identified by LASSO from more than 2000 candidate rules generated by random forest. Investigation of the risk levels of endorsing the risk patterns We next investigated the risk level of endorsing each of the rules by computing the study withdrawal rate for each subgroup that endorsed a rule. Figure 3 illustrates the withdrawal rates of each of the eight identified rules as well as the overall withdrawal rate of the whole study population. The number of subjects in each subgroup is also shown in the figure. It is clear that endorsing any of the first four rules will boost the risk of early withdrawal dramatically, while endorsing any of the later four rules will help decrease the risk significantly. Approximately 10 percent of the study population did not fall into any subgroup and their withdrawal rates were relatively high. It could be possible that there are other important subgroups that were not detectable with the available measures. It could also be possible that for this small group the RuleFit is not powerful enough to detect any significant rules, indicating the need for more powerful rule methods. Moreover, it is possible that because the dropout mechanism could be very complicated and involves many aspects such as socioeconomic and psychological factors, the existence of this subgroup indicates a certain level of unpredictability for some cases. Investigation of the redundancy of the rules One important technical issue in the rule-based analysis is the control of redundancy of the rules. Two rules are redundant if a participant endorses one rule, this participant will endorse the other rule. Obviously, it is less desirable to have two rules that largely overlap with each other. We investigated the redundancy of the 8 rules and presented the results in Fig. 4. Figure 4 can be read in this way: the pie graph on row i (corresponds to rule i) and column j (corresponds to rule j) records the proportion of the participants endorsing rule i who also endorse rule j. It can be seen that, the overall redundancy of the rules is slight, although there are some correlations between some rules, such as rule 1 and rule 4, rule 5 and rule 7. The reason for a correlation between two rules may be that both rules share some common risk factors, e.g., both rule 1 and rule 4 involve maternal age < 27.5 in their definitions. Discussion In this article, the rule-base analysis14 has been proposed to enrich the toolbox of epidemiological intervention studies that have been relying on regression models. We used data from the TEDDY study and demonstrated that the rule-based analysis can effectively identify risk-predictive rules from the psychosocial, demographic, and behavioral risk factors. The 8 identified rules are found predictive of early withdrawal during the first year of the TEDDY study. The 8 rules involve different sets of risk factors, highlighting the different nature of the withdrawal risk for each of these subgroups. Note that these 8 rules are not exclusive, giving the flexibility that an individual can show multiple risk patterns simultaneously. We also compared the rule-based analysis with the previous analysis that was conducted on the same data10. We found that both methods detected almost the same suite of risk factors, providing validation of our rule-base analysis. Note that the previous analysis only identified the average effects of these risk factors across the whole population, without considering how these risk factors interact with each other in determining the risk of early withdrawal. Although it identified the interaction between the mother’s state anxiety inventory score and her risk perception accuracy, many other interactions remained undetected. The rule-based analysis was superior at detecting multiple interactions between the risk factors, in addition to the interaction between the mother’s state anxiety inventory score and her risk perception accuracy. As each rule characterizes a distinct risk pattern that consists of different risk factors, a further investigation of the particular characteristics of each rule may help identify the special health needs of the subgroup whose members endorse this rule, leading to tailored interventions. For example, as revealed in rule 3, for mothers who are highly anxious about their child’s T1D risk with a state anxiety inventory score >45, the lack of participation of the father increases the risk of study withdrawal. In an effort to tailor an intervention to this specific subgroup, a study nurse might be assigned to the family having this risk pattern to enhance the psychological support for the mother and encourage the participation of the father. On the other hand, the rules are also helpful for developing general-purpose interventions. For instance, as smoking during pregnancy was important in multiple rules, investigations may be conducted to understand why this behavior is related to the risk of study withdrawal. If smoking during pregnancy was found to be an indicator of less health-conscious attitudes, a tailored intervention might be developed for mothers who smoked during pregnancy to increase their health consciousness in an effort to reduce her risk of study withdrawal. As tailored interventions are developed and deployed, it is also important to evaluate the efficacy of these interventions for the subgroups separately, in order to identify the best intervention strategy for each subgroup. The rule-based analysis also identified the negative life events as a risk factor of the early withdrawal, which was not detected by the logistic regression model used in the previous study10. Previous studies have linked negative life events with immune system functioning2122 and the onset of T1DM2324. While the mechanism underlying the linkage between the negative life events and study withdrawal remains unknown, it is reasonable to expect that mothers experiencing numerous negative life stresses may not have the personal resources to remain in the study. Certainly tailoring an intervention to this subgroup of individuals seems warranted. The rule-based method has a number of advantages when handling complex datasets. It can be used with a mix of nominal, ordinal, count or continuous variables and it can combine a mixture of variables—demographic, biological, psychological—without interpretation difficulty. Also, as rules are scale independent, data do not need to be standardized. Finally, the rules will permit some individuals to be classified on the basis of only one, or at most a few, risk factors, whereas risk scores derived from regression models require that all the risk factors are available. There are limitations of the rule-based approach for epidemiologic studies. First, it is not suitable for studying the overall impact of a single independent variable on the outcome variable. This is because a single independent variable may play a role in multiple rules, which results in difficulty to investigate its overall effect on the whole population. Also, domain insight is very important in the identification of the rules using RuleFit. Due to the automatic nature of the rule-based approach, it is tempting to simply enter all the possible candidate variables into the program without justification of which independent variables should be considered. It has been recommended in the literature25 that the prior knowledge regarding the relationship between the independent and dependent variables should be incorporated with the rule-based models. One of the reasons the rule-based approach yielded remarkably similar findings to the logistic regression approach in terms of identifying risk factors per se, is that considerable thought was put into variable selection and measurement. Rule-based models should not be used for blind exploration of large data sets and should benefit from domain experts’ supervision. We agree that a general guidance to use machine learning models for analyzing complex dataset such as TEDDY data is that the new tool should be appropriate to the research question. This is actually one main motivation for our study. As with most observational studies, a significant amount of variation exists among TEDDY subjects. Conventional models such as the logistic regression model cannot sufficiently characterize these variations, since logistic regression model essentially aims to characterize the average effects of the risk factors on a homogeneous population. It is reasonable to suspect that TEDDY population consists of a mix of heterogeneous subpopulations while interactions between variables are essential to define and understand these subpopulations. Thus, the main motivation of this study is to demonstrate the utility of the rule-based approach for analyzing complex datasets such as TEDDY data. Moreover, TEDDY data exhibits some other significant challenges to conventional models that the rule-based method can easily handle as we have articulated above. Through this study, one of our co-authors (who has been a pediatric psychiatrist for many years and led the previous study on the same dataset using logistic regression model10) found that the rule-based method could be a valuable new tool to augment conventional hypothesis-driven research, particularly when theory-driven researchers have limited insight or detailed knowledge about the dataset to be analyzed (e.g., this is very likely as contemporary epidemiologists need to analyze datasets with a diverse set of variables that include traditional epidemiological variables as well as genetic variables (such as SNP variants), virus exposures, omics variables, etc.). Together with the fact that the current study has demonstrated that the rule-based approach could identify risk factors that are consistent with the previous hypothesis-driven research, our study implies that, for those complex datasets, the rule-based method could be used to initiate the analysis process to identify unknown but informative patterns from the dataset that may help theory-driven researchers to generate new hypothesis and better formulate their studies. To facilitate this role, we draw the following practical guidance for how to integrate the rule-based analysis methods into the existing epidemiological toolbox. If there is a strong premise that multiple subgroups may exist in the dataset, the rule-based method could be a very useful approach. On the other hand, subgroups may vary from dataset to dataset, and the rules (and the risk factors involved in these subgroups) identified by the rule-based method may vary from dataset to dataset as well. It is important to understand that the rule-based method is a customized method that is tailored for analyzing an individual dataset, so whether or not the results identified from one dataset could be generalized to another dataset depends on the subgroup structure of the new dataset. While flexibility of an analytic method usually comes with risk of overfitting, a customized method also needs customized expertise or solid domain knowledge of the dataset. Finally, rule-based methods can be considered as opportunistic methods that aim to discover positive patterns, but the results identified by rule-based methods are not necessary exclusive. For example, it is possible that there are more rules besides the eight rules identified from TEDDY cohort by the RuleFit. In summary, we believe that the rule-based approach will be useful in many epidemiologic studies, particularly with heterogeneous populations consisting of subgroups of individuals. The distinct risk factors that define each subgroup could also reflect a different mechanism of withdrawing from the study, leading to development of different intervention strategies. Besides the utility in designing tailored intervention, it can also help with the prioritization of the intervention targets, e.g., we could choose eliminate a particularly high-risk subgroup at the beginning of a clinical study. Note that the RuleFit algorithm introduced here is one example from a huge array of the rule-based methods that are promising for epidemiologic research in general. How to properly adopt them for addressing the increasing analytic challenges in epidemiologic studies will be an important future research topic. Also, we will investigate how to build predictive models based on the discovered rules, and further validate its predictive performance on another validation dataset that is being collected at TEDDY study. Additional Information How to cite this article: Haghighi, M. et al. A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study. Sci. Rep. 6, 30828; doi: 10.1038/srep30828 (2016). This work was funded by U01 DK63829, U01 DK63861, U01 DK63821, U01 DK63865, U01 DK63863, U01 DK63836, U01 DK63790, UC4 DK63829, UC4 DK63861, UC4 DK63821, UC4 DK63865, UC4 DK63863, UC4 DK63836, UC4 DK95300, and UC4 DK100238, and Contract No. HHSN267200700014C from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Allergy and Infectious Diseases (NIAID), National Institute of Child Health and Human Development (NICHD), National Institute of Environmental Health Sciences (NIEHS), Juvenile Diabetes Research Foundation (JDRF), and Centers for Disease Control and Prevention (CDC). This work supported in part by the NIH/NCATS Clinical and Translational Science Awards to the University of Florida (UL1 TR000064) and the University of Colorado (UL1 TR001082). The authors thank the funding for this project provided by JDRF (1-PNF-2014-151-A-V). Author Contributions S.B.J. provided the manuscript that served as a basis of the study; she provided the idea for the analysis. S.H. did the design of the paper and wrote the manuscript, he mentored the graduate student in the analysis. M.H. carried out programming and running statistical analysis of data, interpreting the results and preparing the manuscript. X.Q. contributed in the design, analysis and drafting the manuscript. K.F.L. and K.V. provided the concept and design of the study, and did the critical review. TEDDY approved the study and provided the data. Figure 1 A decision tree learned from the TEDDY data. Figure 2 Flow diagram of the RuleFit algorithm. Figure 3 Proportion of early withdrawal of the eight rules and the overall population. Figure 4 Investigation of the redundancy of the 8 rules. The pie graph on row (corresponds to rule) and column (corresponds to rule j) records the proportion of the participants endorsing rule i who also endorse rule. Table 1 Previous logistic regression results for the sample with no missing data and the total sample with missing data imputed: Variables associated with study withdrawal in the first year of TEDDY. (Reprinted from Johnson, S. B. et al.10 with permission from John Wiley and Sons Inc). Predictor variable   Sample with No Missing Data (N=3431) Sample with missing data imputed (N = 3757) Estimate SE P-value OR 95% Confidence Interval β SE P-value Intercept 1.126 0.424 0.008       0.982 0.400 0.014  Country United States ref ref Finland −0.420 0.130 0.001 0.657 0.509 0.848 −0.431 0.123 0.0004 Germany 0.278 0.222 0.211 1.321 0.854 2.042 0.154 0.218 0.481 Sweden −0.342 0.110 0.002 0.711 0.572 0.882 −0.346 0.104 0.002  Child sex female No ref               Yes 0.160 0.092 0.081 2.316 1.840 2.915 0.217 0.086 0.012  Maternal age (years) −0.058 0.009 <0.0001 0.944 0.927 0.961 −0.053 0.009 <0.0001 Maternal Lifestyle Behaviors during Pregnancy  Smoked No ref ref Yes 0.841 0.117 <0.0001 2.318 1.841 2.918 0.803 0.117 <0.0001  Alcohol consumption in last trimester None ref       1–2 times/month −0.343 0.148 0.020 0.709 0.531 0.948 −0.280 0.140 0.045 >2 times/month −0.424 0.319 0.183 0.654 0.350 1.222 −0.401 0.299 0.180  Worked all trimesters No ref ref Yes −0.396 0.095 <0.0001 0.673 0.559 0.811 −0.364 0.090 <0.0001  Dad participation No ref ref Yes −0.569 0.162 0.0005 0.566 0.412 0.778 −0.608 0.146 <0.0001  Risk perception Underestimate ref ref Accurate −1.257 0.375 0.0008 0.284 0.137 0.593 −1.032 0.354 0.004  State Anxiety Inventory score 0.001 0.006 0.835 1.001 0.989 1.014 0.001 0.006 0.825  State Anxiety Inventory score x risk perception 0.023 0.009 0.011 1.023 1.005 1.041 0.018 0.009 0.039  >1 missing data points             1.321 0.464 0.007 Table 2 Characteristics of TEDDY Actives and Withdrawals. (Reprinted from Johnson, S. B. et al.10 with permission from John Wiley and Sons Inc). Characteristic Actives (n = 2994) Withdrawals (n = 763) Total Sample (n = 3757) Country N (%) N (%) N  Finland 747(84%) 140(16%) 887  Germany 106(75%) 36(25%) 142  Sweden 1052(82%) 231(18%) 1283  United States 1089(75%) 356(25%) 1445 Child sex N (%) N (%) N  Male 1538 (81%) 352 (19%) 1890  Female 1456 (78%) 411 (22%) 1867 Maternal age (years) M (SD) M (SD) M (SD)   30.8 (5.0) 28.5 (5.7) 30.4(5.2) Maternal Lifestyle Behaviors During Pregnancy  Smoking N (%) N (%) N   Smoked 296(63%) 171(37%) 467   Did not smoke 2602(84%) 510(16%) 3112   Data missing 96(54%) 82(46%) 178  Alcohol consumption at 3rd trimester N (%) N (%) N   Alcohol 1-2 times per month 474(87%) 72(13%) 546   Alcohol ≥ 3 time per month 105(89%) 13(11%) 118   No alcohol 2359(79%) 609(21%) 2968   Data missing 56(45%) 69(55%) 125  Employment status N (%) N (%) N   Worked all 3 trimesters 1418(85%) 251(15%) 1669   Reduced work, quit, or did not work at all 1426(77%) 417(23%) 1843   Data missing 150(61%) 95(39%) 245 Dad Participation in TEDDY N (%) N (%) N  Participated 2813(82%) 624(18%) 3437  Did Not Participate 181(57%) 139(43%) 320 Maternal Reactions to Child’s Increased TIDM Risk  Risk perception N (%) N (%) N   Accurate 1809(84%) 355(16%) 2164   Underestimate 1132(77%) 343(23%) 1475   Data missing 53(45%) 65(55%) 118  State Anxiety Inventory score M (SD) M (SD) M (SD)   Total Sample 38.7(9.7) 40.8(10.6) 39.1(9.9)   Risk Perception: Accurate 38.8(10.2) 41.7(10.4) 39.3(9.6)   Risk Perception: Underestimate 38.4(10.2) 39.9(10.8) 38.8(10.4)   N (%) N (%) N   Data missing 46 (42%) 63 (58%) 109 Missing Data N (%) N (%) N  ≤1missing data points 2944 (81%) 695 (19%) 3639  >1 missing data points 50 (42%) 68 (58%) 118 Table 3 The 8 rules identified by the RuleFit method. Rule 1 (risk increasing rule) Rule 2 (risk increasing rule) Maternal age <27.5 Finland = NO Smoker during pregnancy = YES Accurate risk perception = NO State anxiety inventory score >45 Rule 3 (risk increasing rule) Rule 4 (risk increasing rule) State anxiety inventory score >45 Dad participation = NO Maternal age <27.5 Accurate risk perception = NO Alcohol consumption in last trimester <2 times per month Rule 5 (risk decreasing rule) Rule 6 (risk decreasing rule) Worked all trimesters = YES Smoker during pregnancy = NO Finland = NO Alcohol consumption in last trimester >0 Number of negative events <2 Rule 7 (risk decreasing rule) Rule 8 (risk decreasing rule) Smoker during pregnancy = NO State anxiety inventory score < 45 Number of missing data points < = 1 Maternal age > 27.5 Smoker during pregnancy = NO Number of missing data points < = 1 ==== Refs Greenland S. , Gago-Dominguez M. & Castelao J. E. The value of risk-factor (“black-box”) epidemiology . Epidemiology 15 , 529 –535 (2004 ).15308951 Evans L. K. Knowing the patient: the route to individualized care . J. Gerontol. Nurs. 22 , 15 –19 ; quiz 52 (1996 ).8698966 Radwin L. & Alster K. Individualized nursing care: an empirically generated definition . Int. Nurs. Rev. 49 , 54 –63 (2002 ).11928937 Ryan P. & Lauver D. R. The efficacy of tailored interventions . Journal of Nursing Scholarship 34 , 331 –337 (2002 ).12501736 Whittemore R. Consequences of Not” Knowing the Patient” . Clinical Nurse Specialist 14 , 75 –81 (2000 ).11188452 Susser M. Does risk factor epidemiology put epidemiology at risk? Peering into the future . J. Epidemiol. Community Health 52 , 608 –611 (1998 ).10023453 Skrabanek P. Risk factor epidemiology: Science or non-science . Social Affairs Unit, Health, Lifestyle and Environment: Countering the Panic, London: Social Affairs Unit (1991 ). Seigel D. G. & Greenhouse S. W. Multiple relative risk functions in case-control studies . Am. J. Epidemiol. 97 , 324 –331 (1973 ).4701676 Petronis K. R. , Samuels J. , Moscicki E. K. & Anthony J. C. An epidemiologic investigation of potential risk factors for suicide attempts . Soc. Psychiatry Psychiatr. Epidemiol. 25 , 193 –199 (1990 ).2399476 Johnson S. B. et al. The Environmental Determinants of Diabetes in the Young (TEDDY) study: predictors of early study withdrawal among participants with no family history of type 1 diabetes . Pediatric diabetes 12 , 165 –171 (2011 ).21029290 Johnson S. B. et al. At high risk for early withdrawal: using a cumulative risk model to increase retention in the first year of the TEDDY study . J. Clin. Epidemiol. 67 , 609 –611 (2014 ).24725640 Rokach L. & Maimon O. Data mining with decision trees: theory and applications (World Scientific, 2008 ). Breiman L. Random forests . Mach. Learning 45 , 5 –32 (2001 ). Friedman J. H. & Popescu B. E. Predictive learning via rule ensembles . The Annals of Applied Statistics , 916 –954 (2008 ). TEDDY Study Group. The Environmental Determinants of Diabetes in the Young (TEDDY) study: study design . Pediatr. Diabetes 8 , 286 –298 (2007 ).17850472 Tibshirani R. Regression shrinkage and selection via the lasso . Journal of the Royal Statistical Society.Series B (Methodological) 267 –288 (1996 ). Liu J. , Chen J. & Ye J. Large-scale sparse logistic regression (Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, ACM, 2009). Wu T. T. , Chen Y. F. , Hastie T. , Sobel E. & Lange K. Genome-wide association analysis by lasso penalized logistic regression . Bioinformatics 25 , 714 –721 (2009 ).19176549 Kim S. , Sohn K. A. & Xing E. P. A multivariate regression approach to association analysis of a quantitative trait network . Bioinformatics 25 , i204 –i212 (2009 ).19477989 Ma S. , Song X. & Huang J. Supervised group Lasso with applications to microarray data analysis . BMC Bioinformatics 8 , 60 (2007 ).17316436 Leclere J. & Weryha G. Stress and auto-immune endocrine diseases . Hormone Research in Paediatrics 31 , 90 –93 (1989 ). Saravia-Fernandez F. , Durant S. , Hasnaoui A. E. , Dardenne M. & Homo-Delarche F. Environmental and experimental procedures leading to variations in the incidence of diabetes in the nonobese diabetic (NOD) mouse . Autoimmunity 24 , 113 –121 (1996 ).8986323 Slawson P. F. , Flynn W. R. & Kollar E. J. Psychological factors associated with the onset of diabetes mellitus . JAMA 185 , 166 –170 (1963 ).13989201 Thernlund G. M. et al. Psychological stress and the onset of IDDM in children . Diabetes Care 18 , 1323 –1329 (1995 ).8721932 Marshall R. J. The use of classification and regression trees in clinical epidemiology . J. Clin. Epidemiol. 54 , 603 –609 (2001 ).11377121

PMC005xxxxxx/PMC5000470.txt

==== Front BMC Complement Altern MedBMC Complement Altern MedBMC Complementary and Alternative Medicine1472-6882BioMed Central London 129610.1186/s12906-016-1296-5Research ArticleOptimization of extraction parameters of PTP1β (protein tyrosine phosphatase 1β), inhibitory polyphenols, and anthocyanins from Zea mays L. using response surface methodology (RSM) Hwang Seung Hwan 1Kwon Shin Hwa 2Wang Zhiqiang 1Kim Tae Hyun 1Kang Young-Hee 1Lee Jae-Yong 23Lim Soon Sung +82-33-248-2133limss@hallym.ac.kr 121 Department of Food Science and Nutrition, Hallym University, 1 Hallymdeahak-gil, Chuncheon, 24252 Republic of Korea 2 Department of Natural Medicine, Hallym University, 1 Hallymdeahak-gil, Chuncheon, 24252 Republic of Korea 3 Department of Biochemistry, School of Medicine, Hallym University, 1 Hallymdeahak-gil, Chuncheon, 24252 Republic of Korea 26 8 2016 26 8 2016 2016 16 1 3175 5 2016 17 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Protein tyrosine phosphatase expressed in insulin-sensitive tissues (such as liver, muscle, and adipose tissue) has a key role in the regulation of insulin signaling and pathway activation, making protein tyrosine phosphatase a promising target for the treatment of type 2 diabetes mellitus and obesity and response surface methodology (RSM) is an effective statistical technique for optimizing complex processes using a multi-variant approach. Methods In this study, Zea mays L. (Purple corn kernel, PCK) and its constituents were investigated for protein tyrosine phosphatase 1β (PTP1β) inhibitory activity including enzyme kinetic study and to improve total yields of anthocyanins and polyphenols, four extraction parameters, including temperature, time, solid-liquid ratio, and solvent volume, were optimized by RSM. Results Isolation of seven polyphenols and five anthocyanins was achieved by PTP1β assay. Among them, cyanidin-3-(6”malonylglucoside) and 3′-methoxyhirsutrin showed the highest PTP1β inhibition with IC50 values of 54.06 and 64.04 μM, respectively and 4.52 mg gallic acid equivalent/g (GAE/g) of total polyphenol content (TPC) and 43.02 mg cyanidin-3-glucoside equivalent/100 g (C3GE/100g) of total anthocyanin content (TAC) were extracted at 40 °C for 8 h with a 33 % solid-liquid ratio and a 1:15 solvent volume. Yields were similar to predictions of 4.58 mg GAE/g of TPC and 42.28 mg C3GE/100 g of TAC. Conclusion These results indicated that PCK and 3′-methoxyhirsutrin and cyanidin-3-(6”malonylglucoside) might be active natural compounds and could be apply by optimizing of extraction process using response surface methodology. Keywords Zea mays L.Protein tyrosine phosphatase 1βResponse surface methodologyAnthocyaninPolyphenolhttp://dx.doi.org/10.13039/501100003624Ministry of Agriculture, Food and Rural Affairs109163-3Lim Soon Sung http://dx.doi.org/10.13039/501100003725National Research Foundation of Korea2015R1D11A01059199Lim Soon Sung http://dx.doi.org/10.13039/501100002632Hallym UniversityHRF-201602-011Lim Soon Sung issue-copyright-statement© The Author(s) 2016 ==== Body Background Zea mays L. (Purple corn, PC) has a variety of kernel colors, such as white, yellow, red, purple, brown, green, and blue. PC has been cultivated in Latin America, mainly in Peru, and Peruvian people have been utilizing PC for centuries. Anthocyanin (ATC), a source of color in PC, is approved in Japan as an extract, and is listed in the “Existing Food Additive List” as PC color. ATC reportedly has various biological activities, such as antioxidant [1], anti-mutagenic [2], and anti-cancer activities [3]. Numerous studies have identified and characterized the possible bioactivities of phenolic compounds from PC. Previous phytochemical investigations of PC studied cyanidin-3-glucoside, pelargonidin-3-glucoside, and peonidin-3-glu-coside by HPLC-MS [4]. Prior work by Pascual-Teresa et al. also identified cyanidin-3-(6-malon-glucoside), pelargonidin-3-(6-malon-glucoside) and peonidin-3-(6-malon-glucoside) [5]. Recently, phenolic constituents were isolated from a 35 % ethanol extract of purple corn kernel (PCK). Among the isolated compounds, hirstrin, 3′-methoxyhirstrin, cyanidin-3-(6”-malonylglucoside), ferulic acid, p-hydroxycinnamic acid, and 2,4,6-trihydroxybenzoic acid, exhibited strong inhibitory effects on aldose reductase and galactitol accumulation in rat lenses and erythrocytes, and on mesangial fibrosis and inflammation, with the added effects of slowed diabetes-associated glomerulosclerosis and displayed anti-diabetic [6–8]. Protein tyrosine phosphatase (PTP) expressed in insulin-sensitive tissues (such as liver, muscle, and adipose tissue) has a key role in the regulation of insulin signaling and pathway activation [9], making PTP a promising target for the treatment of type 2 diabetes mellitus (T2DM) and obesity [10]. Although several PTPs, such as PTP-α, leukocyte antigen-related tyrosine phosphatase (LAR), and SH2-domain-containing phosphotyrosine phosphatase (SHP2), have been implicated in the regulation of insulin signaling, there is substantial evidence supporting PTP1β as the critical PTP controlling the insulin signaling pathway. PTP1β can interact with and dephosphorylate activated insulin receptors (IR), as well as insulin receptor substrate (IRS) proteins [11]. For this reason, researchers are focused on finding safe, potent, non-toxic PTP1β inhibitors from natural and synthetic sources. Polyphenols isolated from the fruit of Phellinus linteus and Prunella vulgaris L. are reported to inhibit PTP1β and confer anti-diabetic effects [12]. Response surface methodology (RSM) is an effective statistical technique for optimizing complex processes using a multi-variant approach [13]. Before applying the RSM, it is necessary to choose an experimental design that defines which experiments should be performed in a given study. The main advantage of this technology is that fewer experimental trials are needed to evaluate multiple factors and their interactions, making it less laborious and time-consuming than other optimization techniques (e.g., the “one-variable-at-a-time” optimization). RSM has been successfully used for extract optimization of phenolic compounds and antioxidant of grape peel [14]. Recently, Pedro et al. optimized the total flavonoid, polyphenol, and anthocyanins of black rice using RSM coupled with central composite design (CCD), allowing rapid screening of a wide range of conditions while also indicating the role of each factor [15]. To date, no data have been published on the inhibitory effects of PCK extracts on PTP1β regulation. Therefore, the inhibitory effects of compounds isolated from PCK on PTP1β activity were investigated to evaluate potential treatments of diabetic complications. Optimization of various conditions, such as extraction temperature, extraction time, solid-liquid ratio, and solvent volume, for were studied to assess potential development of PTP1β inhibitors and to maximize the extract yield (EY), total polyphenol content (TPC), and total anthocyanin content (TAC) from PCK using by RSM. Methods Plant materials and reagents Commercially grown PCK was obtained from Gangwon-do agricultural research and extension services in Korea (April, 2014). The plants were identified by Emeritus Professor H.J. Chi at Seoul National University, and voucher specimens were deposited in the Center for Efficacy Assessment and Development of Functional Foods and Drugs, Hallym University in with voucher number RIC-2014-NP-0415. Fresh PCK was dried at 45 °C in a drying oven and then stored at room temperature. A PTP1β (human, recombinant) drug discovery kit was purchased from BIOMOL® International LP (Plymouth meeting, PA). Sodium chloride, p-nitrophenyl phosphate (pNPP), and dithiothreitol were obtained from Sigma–Aldrich Co. (St. Louis, MO, USA) for use as synthetic substrates. All other chemicals and reagents used were of analytical grade. Extraction, fractionation and isolation Dried PCK (1.0 kg) was ground and extracted with 35 % ethanol for 8 h at room temperature. The total filtrate was concentrated to dryness in vacuo at 40 °C. The PCK 35 % ethanol extract powder (500 g) was applied to an open glass column packed with Diaion HP-20 and eluted with water to wash any sugars or impure components. The packing was then suspended in water and partitioned sequentially with n-Hexane, CH2Cl2, EtOAc, and n-BuOH, leaving a residual aqueous fraction. The EtOAc fraction showed inhibitory activity on PTP1β, hence 5.5 g of extract was subjected to C18 gel column chromatography eluted with water and increasing methanol in an H2O-MeOH gradient system (95:5 → 0:50, v/v) to obtain 7 compounds. Also, the n-BuOH fraction (1.0 g) was subjected to high speed counter current chromatography (HSCCC). The HSCCC system employed in the present study was a Model TBE-1000A HSCCC (Shanghai Tauto Bio technique, Shanghai, China) with 3 multilayer coil columns connected in series and was equipped with a 50-mL sample loop. The inner diameter of the PTFE tubing was 1.8 mm, and the total volume capacity was 1000 mL. The b-value of the preparative column varied from 0.42 at the internal layer to 0.63 at the external layer. The rotation speed of the apparatus was regulated using a speed controller in the range of 0-600 rpm. The HSCCC system was equipped with a Model Hitachi L-6200 intelligent pump (Hitachi, Tokyo, Japan), Model TOPAZ dual UV monitor operating at 520 nm, and Model ECOMAC-ECOM Acquisition and Control (version 0.97). The upper phase, consisting of a mixture of n-BuOH:acetic acid:water (4:1:5, v/v/v) was used as the stationary phase, while the lower phase was used as the mobile phase. The mobile phase was pumped at 2.5 mL/min, while centrifugation was carried out at 400 rpm. As a result, 12 compounds were isolated and identified by 1H & 13C NMR spectra (COSY, HMBC, HMQC and DEPT) and LC-MS/MS. Assay method of PTP1β inhibitory activity A PTP1β (human, recombinant) drug discovery kit was purchased from BIOMOL® International LP (Plymouth meeting, PA). Enzymatic activity was measured using pNPP, as described previously. To each of the 96-wells in a microtiter plate (final volume: 100 μL) was added 2 mM pNPP and PTP1β (0.05-0.1 ng/well) in a buffer containing 50 mM citrate (pH 6.0), 0.1 M sodium chloride, 1 mM EDTA, and 1 mM dithiothreitol, with or without test compounds. Following incubation at 37 °C for 30 min, the reaction was terminated with 10 M sodium hydroxide. The amount of p-nitrophenol produced was estimated by measuring the absorbance at 405 nm. The non-enzymatic hydrolysis of 2 mM pNPP was corrected by measuring the increase in absorbance at 405 nm obtained in the absence of PTP1β enzyme. Kinetics of PTP1β by active compounds Inhibition kinetics studies were carried out in the absence and presence of active compounds with various concentrations of pNPP (0.1, 0.5 and 1.0 mM) as substrate. The initial rate was determined on the basis of the rate of increase in absorbance at 405 nm. The Michaelis-Menten constant (Km) and maximal velocity (Vmax) of PTP1β were determined by Lineweaver-Burk Plot analysis for competitive inhibition, and the intercept on the vertical axis for noncompetitive inhibition [16]. Extraction process The dried PCK (1.0 g) was accurately weighed and placed in a capped tube and mixed with 10 mL of 35 % ethanol. After wetting the plant material, the tube containing the suspension was immersed at 37 °C in a water bath and irradiated for the predetermined for 30 min. After extraction, the sample was centrifuged at 3000 rpm for 3 min. The supernatant was collected and diluted with eluent. All samples were filtered through 0.45 μm syringe filter. Experimental design for RSM The effects of the four independent processing parameters (extraction temperature (X1, °C), extraction time (X2, hour), solid-liquid ratio (X3, %), and solvent volume (X4, 1:X)), on the dependent variables were investigated using RSM. The CCD for RSM required only five levels, coded as -2, -1, 0, +1, +2. The total number of experiments designed was 27 based on the five levels and a four-factor experimental design, with five replicates at the central conditions of the design for estimation of a pure error sum of squares. The dependent variables were TPC (Y1), TAC (Y2), and EY (Y3). The model equation for the response (Y) to the three independent variables (X1, X2, X3 and X4) is given in the following equation: Y=β0+∑i=12βiXi+∑i=12βiiXi2+∑i∑j=i+1βijXiXj Total polyphenol content determination Total polyphenol content (TPC) was determined according to the Folin Denis Method with a slight modification. The extract was double-diluted and 100 μL of the diluted sample was mixed with 50 μL Folin Ciocalteu’ reagent and 300 μL of 2 % (w/v) sodium carbonate. After incubating the samples at room temperature for 1 h, 1 mL water was added before measuring the absorbance at 750 nm. The calibration curve was obtained using gallic acid in the same manner as done for the sample (R2 = 0.999). Results were expressed as mg of gallic acid equivalent (GAE) per g of dried weight. Total anthocyanin content determination Total anthocyanin (TAC) was used to indicate the contents of anthocyanin extracted from PCK. TAC was determined using a pH differential method. Absorbencies were read at 530 and 700 nm. Pigment content was calculated as cyanidin-3-glucoside (C3G) using an extinction coefficient (ε) of 26,900 and a molecular weight of 449.2 and expressed as mg cyanidin-3-glucoside equivalent (C3GE) per 100 g of dried weight [17]. Determination of extraction yield The PCK extracts were concentrated in an efficient centrifugal concentration system (EZ-2 plus, Genevac and UK) and the difference in weight corresponds to the soluble solid (total extract yield) of the dried PCK. Data analysis All calculations and analyses were performed using statistical analysis system (SAS, SAS Institude Inc., NC, USA, version 9.1) software and Sigma plot (Systat Software Inc., USA, version 11). Inhibition rates were calculated as percentages (%) with respect to the control value and IC50 value was estimated from the least-squares regression line of the logarithmic concentration plotted against inhibitory activity. Result PTP1β inhibitory compounds from Zea mays L The present study was carried out to obtain new potential PTP1β inhibitors from PCK. In order to identify the active compounds from PCK, its extract was systematically divided into 5 fractions, which were then tested for PTP1β inhibitory activity. Among them, the EtOAc fraction was found to have moderate PTP1β inhibitory activity with a mean IC50 value of 26.12 μg/mL, whereas the positive control suramin showed an IC50 value of 7.51 μg/mL (Table 1). This suggested the presence of PTP1β inhibition in the EtOAc fraction.Table 1 Inhibitory effect of the crude extract and fractions of Zea mays L. on protein tyrosine phosphatase 1β Extract and fractions Concentration (μg/mL) Inhibition (%) IC50 b (μg/mL) Suramina 12.97 61.88 6.49 40.62 7.51 3.21 10.69 EtOH ext. 100 43.99 - n-Hex fr. 100 25.54 - CH2Cl2 fr. 100 28.12 - EtOAc fr. 100 83.88 50 57.23 26.12 10 44.77 n-BuOH fr. 100 70.89 50 45.09 58.20 10 26.87 - Water fr. 100 47.50 - aSuramin was used as positive control bThe IC50 value was defined as the half-maximal inhibitory concentration and mean of 3 duplicate analyses of each sample Isolation of the compounds from active EtOAc fraction The active EtOAc fraction (IC50 = 26.12 μg/mL) was subjected to repeated chromatography on a reversed phase C-18 gel chromatography column, yielding protocatechuic acid (1) (5.1 mg), vanillic acid (2) (12.6 mg), 2,4,6-trihydroxy benzoic acid (3) (6.5 mg), p-4-hydroxycinnamic acid (4) (15.0 mg), ferulic acid (5) (5.5 mg), hirsutrin (6) (21.0 mg), and 3′-methoxyhirsutrin (7) (20.0 mg). Also, the n-BuOH fraction (IC50 = 58.20 μg/mL) was subjected to HSCCC, yielding cyanidin-3-glucoside (8) (6.8 mg), pelargonidin-3-glucoside (9) (1.7 mg), peonidin-3-glucoside (10) (1.7 mg), cyanidin-3-(6”-malonylglucoside) (11) (7.6 mg), and pelargonidin-3-(6”-malonylglucoside) (12) (5.4 mg) in Fig. 1. The inhibitory activities of compounds 1-12 were assayed against PTP1β, and the results are presented in Table 2. The known PTP1β inhibitor, suramin (IC50 = 2.76 μM), was used as a positive control. Among the extracts, compounds 5, 7, 9 and 11 exhibited moderate activity with IC50 values of 185.41, 64.04, 210.81, and 54.06 μM, respectively. This suggests that addition of a methyl group to the phenolic acid skeleton may be responsible for a loss of in vitro activity. Addition of malonylglucoside to the cyanidin skeleton may also be responsible for loss of in vitro activity. In a previous study of anti-diabetic compounds from PCK extract, it was demonstrated that the anthocyanins isolated from PCK could inhibit renal fibrosis for mesangial inflammation specific therapies in a high-glucose-induced diabetic nephropathy model [7]. Moreover, compounds 6, 7, and 11 from PCK showed significant inhibitory activities on rat lenses and human recombinant aldose reductase [6], indicating that PCK extract exerted anti-diabetic effects through protection of pancreatic β-cells, increase of insulin secretion, and AMPK activation in the liver of C57BL/KsJ db/db mice [8].Fig. 1 Chemical structures of compounds 1–12 isolated from Zea mays L Table 2 Inhibitory effect of the isolated compounds from Zea mays L. on protein tyrosine phosphatase 1β Compounds Concentration (μg/mL) Inhibition (%) IC50 b (μg/ml) IC50 (μM) Suramina 5 64.32 2.76 2.5 46.46 3.94 1 10.69 Protochtechuic acid (1) 100 <50.0 - - Vanillic acid (2) 100 <50.0 - - 2,4,6-Trihydroxybenzoic acid (3) 100 < 50.0 - - p-Hydroxycinnamic acid (4) 100 < 50.0 - - Ferulic acid (5) 100 96.09 185.41 50 64.53 35.97 10 28.33 Hirsutrin (6) 100 < 50.0 - - 3′-Methoxyhirsutrin (7) 50 85.89 64.04 25 36.84 30.61 10 15.02 Cyanidin-3-glucoside (8) 100 < 50.0 - - Pelargonidin-3-glucoside (9) 100 55.05 210.81 50 13.35 91.36 10 1.09 Peonidin-3-glucoside (10) 100 < 50.0 - - Cyanidin-3-(6”-malonylglucoside) (11) 50 91.73 54.06 25 36.24 28.95 10 18.54 Peonidin-3-(6”-malonylglucoside) (12) 100 < 50.0 - - aSuramin was used as positive control bThe IC50 value was defined as the half-maximal inhibitory concentration and mean of 3 duplication analyses of each sample Kinetics of PTP1β inhibition by the active compounds A kinetic study using pNPP as a substrate at a concentration range of 0.2-1.0 mM was performed to determine the type of inhibition compounds 7 and 11 exhibited. A kinetic analysis of PTP1β inhibition by compounds 7 and 11 using Lineweaver-Burk plots of 1/velocity and 1/concentration of substrate is shown in Fig. 2. When the concentration of the substrate pNPP was changed, the slopes obtained with the uninhibited enzyme and the three different concentrations of each compound were found to be parallel. The results showed that the inhibition of PTP1β by compound 11 was mixed. However, compound 7 yielded a noncompetitive inhibition pattern against PTP1β. In this study, polyphenol derivatives, including anthocyanins isolated from PCK, exhibited PTP1β inhibitory activities. These compounds may be potential lead compounds for further development as a functional food source for the prevention of diabetes.Fig. 2 Lineweaver-Burk plots of the inhibitory effect of compounds on PTP1β -catalyzed hydrolysis of pNPP, respectively. Data are expressed as the mean substrate concentration of compound 7 (a) and 11 (b) Optimization of extraction conditions to maximize total content of polyphenol, anthocyanin content, and extraction yield In this study, four independent parameters were used. The 27 designed experiments for optimizing the four individual parameters in the current CCD are shown in Table 3. The regression equations for response surface are listed in Table 4. The replicates (runs 23–27) at the center of the design were estimated by a pure error sum of squares. Joglekar and Ma suggested that, for a good fit of a model, R2 should be at least 0.800, where a value lower than 0.800 indicating the model is inappropriate for explaining the relationships between variables. RSM has been successfully used to optimize biochemical and biotechnological processes related to the food industry [18]. The main advantage of RSM is the reduced the number of experimental trials needed to evaluate multiple parameters and their interactions. Therefore, RSM is less laborious and time-consuming compared to other approaches to process optimization. The optimization of extraction parameters for TPC and TAC from PCK, will provide information and we will give a foundation for the development and utilization of PCK resources by RSM.Table 3 Experimental range and values of the independent variables in the central composite design for optimization of extraction conditions No. Independent Response variables X1 a X2 X3 X4 Y1 b Y2 Y3 1 30 (-1) 6 (-1) 25 (-1) 12 (-1) 5.91 55.16 6.00 2 50 (1) 6 (-1) 25 (-1) 12 (-1) 3.40 32.06 7.65 3 30 (-1) 10 (1) 25 (-1) 12 (-1) 6.55 65.20 6.00 4 50 (1) 10 (1) 25 (-1) 12 (-1) 5.47 47.47 6.70 5 30 (-1) 6 (-1) 35 (1) 12 (-1) 6.32 66.17 5.85 6 50 (1) 6 (-1) 35 (1) 12 (-1) 2.04 16.61 8.50 7 30 (-1) 10 (1) 35 (1) 12 (-1) 8.08 77.94 6.15 8 50 (1) 10 (1) 35 (1) 12 (-1) 3.70 34.71 7.30 9 30 (-1) 6 (-1) 25 (-1) 12 (-1) 4.42 41.02 6.30 10 50 (1) 6 (-1) 25 (-1) 20 (1) 6.64 67.21 7.75 11 30 (-1) 10 (1) 25 (-1) 20 (1) 6.33 63.36 6.25 12 50 (1) 10 (1) 25 (-1) 20 (1) 6.47 65.81 7.10 13 30 (-1) 6 (-1) 35 (1) 20 (1) 5.75 58.94 6.35 14 50 (1) 6 (-1) 35 (1) 20 (1) 3.62 70.81 9.25 15 30 (-1) 10 (1) 35 (1) 20 (1) 6.30 64.96 6.35 16 50 (1) 10 (1) 35 (1) 20 (1) 4.67 69.92 9.00 17 20 (-2) 8 (0) 30 (0) 16 (0) 3.41 20.63 5.75 18 60 (2) 8 (0) 30 (0) 16 (0) 3.80 24.07 9.10 19 40 (0) 4 (-2) 30 (0) 16 (0) 4.64 40.02 5.95 20 40 (0) 12 (2) 30 (0) 16 (0) 4.63 37.48 6.00 21 40 (0) 8 (0) 20 (-2) 16 (0) 6.22 52.90 6.40 22 40 (0) 8 (0) 40 (2) 16 (0) 4.92 71.46 5.75 23 40 (0) 8 (0) 30 (0) 8 (-2) 6.63 60.04 2.70 24 40 (0) 8 (0) 30 (0) 24 (+2) 5.72 56.32 6.35 25 40 (0) 8 (0) 30 (0) 16 (0) 4.95 45.34 5.75 26 40 (0) 8 (0) 30 (0) 16 (0) 4.34 35.13 5.78 27 40 (0) 8 (0) 30 (0) 16 (0) 4.28 40.88 5.73 aX1, extraction temperature (°C); X2, extraction time (hour); X3, solid-liquid ratio (%); X4, solvent volume (1:X) bY1, total polyphenol content (mg GAE/g); Y2, total anthocyanin content (mg C3GE/100 g) Y3, extraction yield (%) Table 4 Polynomial equations calculated using the RSM program for extraction conditions of Zea mays L. Response variables Second order polynomial equationsa R2 p-value Total polyphenol content (mg GAE/g) YTPC = 12.967917 + 0.236917X1 + 0.119583X2-0.184667X3-1.221042X4-0.001699X12-0.000781X1X2 + 0.021901X2 2-0.013988X1X3 + 0.003563 X2X3 + 0.012854X3 2 + 0.16953X1X4 2-0.021797X2X4-0.007281X3X4+ 0.029538X4 2 0.935 0.0001 Total anthocyanin content (mg C3GE/100 g) YTAC = 412.389167 + 0.248000X1 + 4.349167X2-14.648667X3-23.737500X4-0.027356X12-0.058562X1X2 + 0.341094X2 2-0.079975X1X3-0.072875X2X3 + 0.288875X3 2 + 0.279406X1X4 2-0.230156X2X4 + 0.099687X3X4 + 0.388867X4 2 0.917 0.0001 Extraction yield (%) YEY = 29.279167-0.538500X1-0.842500X2-0.823000X3-0.010833X4 + 0.006002X12-0.007188X1X2 + 0.059427X2 2 + 0.004625X1X3-0.003125X2X3 + 0.010508X3 2 + 0.004219X1X4 2 + 0.014844X2X4 + 0.003437X3X4-0.0077997X4 2 0.887 0.0001 aX1, extraction temperature (°C); X2, extraction time (hour); X3, solid-liquid ratio (%); X4, solvent volume (1:X) Optimization of total polyphenol contents (TPC) The regression equation of changes in TPC calculated by the RSM program for various extraction conditions is shown in Table 4 with an R2 of 0.935 with less than 5 % significance level recognized. TPC was at the maximum level of 7.89 mg GAE/g with conditions at 29.29 °C (X1), 8.99 h (X2), 33.67 % (X3) and 1:10.25 (X4), respectively (Table 5). The four-dimensional response surface and contour plot shown in Fig. 3 illustrates the variation of TPC extraction efficiency relative to changes in X1, X2, X2 and X4. The response surface of TPC indicated that TPC increased as X1 and X3 decreased and X2 and X4 increased (Table 6). Results showed that higher TPC (>8.3 mg GAE/g) could be obtained when the extraction occurred at higher X2 (>10 h) and X4 (>1:20) and lower X1 (20–25 °C) in comparison with higher temperature and higher solid-liquid ratio. TPC should increase with longer extraction time and higher solvent volume.Table 5 Predicted levels of extraction condition for the maximum response of extraction conditions by the ridge analysis in Zea mays L. Response variables Optimum extraction conditionsa Maximum Morphology X1 X2 X3 X4 Total polyphenol content (mg GAE/g) 29.02 8.99 33.67 10.25 7.89 Saddle point Total anthocyanin content (mg C3GE/100 g) 45.22 7.85 34.14 22.97 82.44 Saddle point Extraction yield (%) 58.87 7.53 32.31 17.65 10.33 Saddle point aX1, extraction temperature (°C); X2, extraction time (hour); X3, solid-liquid ratio (%); X4, solvent volume (1:X) Fig. 3 Response surface plot for the effects of extraction temperature, extraction time, solvent-liquid ratio, and solvent volume on total polyphenol content of extract. (X1, extraction temperature (°C); X2, extraction time (hour); X3, Solid-liquid ratio (%); X4, solvent volume (1:X); Y2, total polyphenol content (mg GAE/g)) Table 6 Regression analysis for regression model of physiochemical properties in extraction condition of Zea mays L. Response variables F-radioa X1 X2 X3 X4 Total polyphenol content (mg GAE/g) 3.76 2.60 3.12 3.15 Total anthocyanin content (mg C3GE/100 g) 1.90 4.29 2.83 2.98 Extraction yield (%) 8.09 3.34 0.40 3.44 aX1, extraction temperature (°C); X2, extraction time (hour); X3, solid-liquid ratio (%); X4, solvent volume (1:X) Optimization of total anthocyanin contents (TAC) In the case of TAC, the X2 and X4 were the most influential factor extraction conditions. TAC extraction from PCK under various conditions is presented in Table 3, while Fig. 4 shows the four-dimensional response surface for TAC. A significance level of less than 5 % was calculated for TAC extraction from PCK with an R2 of 0.917 (Table 4). The maximum TAC predicted extraction was 82.44 mg C3GE/100 g when X1, X2, X2 and X4 volume were 45.22 °C, 7.85 h, 34.14 %, and 1:22.97, respectively (Table 5). In the present study, the effect of extraction time on TAC was investigated. As shown in Fig. 4, the amount of TAC extracted increased with increased of X2 up to 11 h, resulting in a maximum of TAC (77.94 mg/L) at 10 h. TAC was greatly affected by X2, higher X3, and higher X4, while X1 was less significant. This information was used to test the accuracy of the model’s prediction of optimum response values by comparing it with the optimum levels obtained by the RSM optimization. Under the optimal conditions, the experimental extraction of TAC was 43.02 mg C3GE/100 g; half to the predicted value in Table 7.Fig. 4 Response surface plot for the effects of extraction temperature, extraction time, solvent-liquid ratio, and solvent volume on total anthocyanin content of extract. (X1, extraction temperature (°C); X2, extraction time (hour); X3, Solid-liquid ratio (%); X4, solvent volume (1:X); Y3, total anthocyanins content (mg C3GE/100 g)) Table 7 Predicted values of response variables at a given conditiona within the range of optimum extraction conditions Response variables Predicted values Experimental values Total polyphenol content (mg GAE/g) 4.58 4.52 Total anthocyanin content (mg C3GE/100 g) 42.28 43.02 Extraction yield (%) 5.76 5.87 aGiven conditions: 40 °C extraction temperature, 8 h extraction time, 33 % in solid-liquid ratio, and 1:15 in solvent volume in conditions Optimization of extraction yield (EY) R2 for the regression equation of EY was 0.887 with a significance of less than 5 % calculated (Table 4). The predicted peak point led to the highest yield of 10.33 % with corresponding independent parameters being X1 of 58.87 °C, X2 of 7.53 h, X3 of 32.31 % and X4 of 1:17.65 (Table 5). The four-dimensional response surface plot obtained for yields as influenced by each extraction condition is shown in Fig. 5, indicating the yield should increase with increases of X1 and X4. Overall, larger content of EY was observed with increasing X1 and X4. Table 7 shows the predicted value are close to the experimental values, with the predicted peak point led to an optimization content 5.76 % of EY with the corresponding independent parameters being X1 (30–50 °C), X2 (7.5–9.0 h), X2 (32–34 %) and X4 (1:10–20). This information was used to test the accuracy of the model’s prediction of optimum response values by comparing it with the optimum levels obtained by the RSM optimization. Under the optimal conditions, the experimental EY was 5.3 %; close to the predicted value.Fig. 5 Response surface plot for the effects of extraction temperature, extraction time, solvent-liquid ratio, and solvent volume on extract yield. (X1, extraction temperature (°C); X2, extraction time (hour); X3, Solid-liquid ratio (%); X4, solvent volume (1:X); Y1, extract yield (%)) Discussion The TPC can be influenced significantly by the solvent type, concentration, temperature, and time. In the case of high temperature, some polyphenols would be degraded and their yields would be reduced, causing a decrease in the antioxidant activity. The total phenolic compounds antioxidant activity increased with increased TPC recovery. Low temperature was ineffective in the extraction process due to diminished ability to release polyphenols from fruit tissues. Also, a similar curved surface plot effect would be produced by extraction time as solvent volume in the medium and higher region. Hammi et al. reported that the yields of total phenols from Tunisian Zizyphus lotus fruits and its antioxidant activity have been significantly improved by using a 50 % ethanol concentration, 63 °C temperature, and 25 min extraction time during conventional solvent extraction [19]. In the present study, TPC obtained at the higher time and solvent volume is similar with the previous reports for the extracts of grape cane and leaves [20, 21]. Pedro et al. have reported that the yield of ATC from black rice would be influenced by the temperature and solvent ratio [15]. At longer extraction time and higher solvent volume, the extraction of ATC may reach a maxima, which may suggest the highest antioxidant activity. Moreover, Fan et al. demonstrated that the main parameter influencing ATC extraction yield from purple sweet potato was temperature [22]. The concentration gradient would be increased by raising the proportion of solvent, increasing the diffusion of solid compounds. The diffusion coefficient and the solubility of the compounds could be controlled by temperature, higher yield was obtained with increased temperature. However, anthocyanins can be damaged when temperatures are over 50 °C [23]. The temperature is an important factor for EY. Mkaouar et al. also reported the similar result [24]. The extraction efficiency critical parameter is the solubility of solutes in solvent. The viscosities of the water will decrease with the temperature increase, thereby its ability to wet the matrix and solubilize the solutes is increased. Recently, Zheng et al. reported an increased extraction rate of anthocyanin with increasing extraction temperature and static time [25]. Thus, temperature and static time have a significant effect contact time between the two phases is significantly longer, and higher extraction rates are obtained. Conclusion In conclusion, we have investigated whether phenolic compounds inhibit PTP1β activity or not, and have identified phenolic compounds from PCK that possess PTP1β inhibitory activity. From the twelve isolated compounds, 3′-methoxyhirsutrin and cyanidin-3-(6”malonylglucoside) showed the potent inhibition with IC50 values of 64.04 and 54.06 μM for PTP1β, respectively. In addition, an extraction method has been developed for the extraction of total polyphenol and anthocyanin from PCK by RSM. The present results would contribute to the research about of PCK dietary supplements for diabetes treatment and optimization of extraction method. Abbreviations ATCAnthocyanin CCDCentral composite design EYExtract yield HSCCCHigh speed counter current chromatography IRInsulin receptors IRSInsulin receptor substrate PCPurple corn PCKPurple corn kernel pNPPN p-nitrophenyl phosphate PTP1βProtein tyrosine phosphatase 1β RSMResponse surface methodology SHP2SH2-domain-containing phosphotyrosine phosphatase TACTotal anthocyanin content T2DMType 2 diabetes mellitus TPCTotal polyphenol content Acknowledgements Thanks for Jin-Kyu Kim in Biocenter, Gyeonggi Institute of Science & Technology Promotion in Suwon supporting us in this research. Funding This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through (High Value-added Food Technology Development Program), funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (109163-3) and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2015R1D1A1A01059199), Hallym University Research Fund (HRF-201602-011). Availability of data and materials All data generated or analyzed during this study are included in this published article. Authors’ contributions SHK and ZQW conducted the PTP1β inhibitory activity and analyzed the data. HSH and THK prepared the product to be tested by RSM. JYL, YHK and SSL participated in design of the study and preparation of the manuscript. All the authors read and approved the final manuscript. Competing of interests The authors declare that they have no competing interests. Consent for publication Not Applicable. Ethics approval and consent to participate Not Applicable. ==== Refs References 1. Tsuda T Shiga K Ohshima K Kawakishi S Osawa T Inhibition of lipid peroxidation and active oxygen radical scavenging effect of anthocyanin pigments isolated from Phaseolus vulgaris L Biochem Pharmacol 1996 52 1033 1039 10.1016/0006-2952(96)00421-2 8831722 2. Yoshimoto M Okuno S Yoshinaga M Yamakawa O Yamaguchi M Yamada J Antimutagenicity of sweetpotato (Ipomoea batatas) roots Biosci Biotech Bioch 1999 63 537 541 10.1271/bbb.63.537 3. Koide T Hashimoto Y Kamei H Kojima T Hasegawa M Terabe K Antitumor effect of anthocyanin fractions extracted from red soybeans and red beans in vitro and in vivo Cancer Biother Radiopharm 1997 12 277 280 10.1089/cbr.1997.12.111 10851476 4. Yang Z Chen Z Yuan S Zhai W Piao X Piao X Extraction and identification of anthocyanin from purple corn (Zea mays L.) Int J Food Sci Tech 2009 44 2485 2492 10.1111/j.1365-2621.2009.02045.x 5. Pascual-Teresa SD Santos-Buelga C Rivas-Gonzalo JC LC-MS analysis of anthocyanins from purple corn cob J Sci Food Agr 2002 82 1003 1006 10.1002/jsfa.1143 6. Kim TH, Kim JK, Kang YH, Lee JY, Kang IJ, Lim SS. Aldose reductase inhibitory activity of compounds from Zea mays L. BioMed Res Int. 2013;2013:8–15. 7. Li Z Lim SS Lee JY Kim JK Kang SW Kim JL Kang YH Purple corn anthocyanins dampened high-glucose-induced mesangial fibrosis and inflammation: possible renoprotective role in diabetic nephropathy J Nutr Biochem 2012 23 320 331 10.1016/j.jnutbio.2010.12.008 21543205 8. Huang B Wang ZQ Park JH Ryu OH Choi MK Lee JY Kang YH Lim SS Anti-diabetic effect of purple corn extract on C57BL/KsJ db/db mice Nutr Rer Pract 2015 9 22 29 10.4162/nrp.2015.9.1.22 9. Schultz LD Schweitzer PA Rajan TV Yi T Ihle JN Matthews RJ Thomas ML Beier DR Mutations at the murine motheaten locus are within the hematopoietic cell protein tyrosine Phosphatase (Hcph) gene Cell 1993 73 1445 1454 10.1016/0092-8674(93)90369-2 8324828 10. Bialy L Waldmann H Inhibitors of protein tyrosine phosphatase: Next-generation drugs? Angew Chem Int Edit 2005 44 3814 3839 10.1002/anie.200461517 11. Asante-Appiah E Kennedy BP Protein tyrosine phosphatase: the quest for negative regulators of insulin action Am J Physiol 2003 284 663 670 12. Lee YS Kang IJ Won MH Kim JK Lim SS Inhibition of protein tyrosine phosphatase 1beta by hispidin derivatives isolated from the fruiting body of Phellinus linteus Nat Prod Commun 2010 5 1927 1930 21299122 13. Bezerra MA Santelli RE Oliveira EP Villar LS Escaleira LA Response surface methodology (RSM) as a tool for optimization in analytical chemistry Talanta 2008 284 965 977 10.1016/j.talanta.2008.05.019 18761143 14. Ghafoor K Choi YH Optimization of ultrasound assisted extraction of phenolic compounds and antioxidants from grape peel through response surface methodology J Korean Soc Appl Bl 2009 52 295 300 10.3839/jksabc.2009.052 15. Pedro AC Granato D Rosso ND Extraction of anthocyanins and polyphenols from black rice (Oryza sativa L.) by modeling and assessing their reversibility and stability Food Chem 2016 191 12 20 10.1016/j.foodchem.2015.02.045 26258696 16. Li HM Hwang SH Kang BG Hong JS Lim SS Inhibitory effects of Colocasia esculenta (L.) Schott constituents on aldose reductase Molecules 2014 19 13212 13224 10.3390/molecules190913212 25255750 17. Rodrigues S Fabiano AN Fernandes A Brito ESD Sousa AD Narain N Ultrasound extraction of phenolics and anthocyanins from jabuticaba peel Ind Crop Prod 2015 69 400 407 10.1016/j.indcrop.2015.02.059 18. Joglekar AM May AT Product excellence through design of experiment Cereal Food World 1987 32 857 868 19. Hammi KM Jdey A Abdelly C Majdoub H Ksouri R Optimization of ultrasound-assisted extraction of antioxidant compounds from Tunisian Zizyphus lotus fruits using response surface methodology Food Chem 2015 184 80 89 10.1016/j.foodchem.2015.03.047 25872429 20. Karacabey E Mazza G Optimisation of antioxidant activity of grape cane extracts using response surface methodology Food Chem 2010 119 343 348 10.1016/j.foodchem.2009.06.029 21. Prasad K Nath N Mathematical modeling and optimisation of sugarcane juice level in grape beverage using response surface methodology (RSM) J Dairy Foods Home Sci 2011 30 278 284 22. Fan G Han Y Gu Z Chen D Optimizing conditions for anthocyanins extraction from purple sweet potato using response surface methodology (RSM) LWT-Food Sci Tech 2008 41 155 160 10.1016/j.lwt.2007.01.019 23. Cacace JE Mazz G Optimization of extraction of anthocyanins from black currants with aqueous ethanol J Food Sci 2003 68 240 248 10.1111/j.1365-2621.2003.tb14146.x 24. Mkaouar S Bahloul N Gelicus A Allaf K Kechaou N Instant controlled pressure drop texturing for intensifying ethanol solvent extraction of olive (Olea europaea) leaf polyphenols Sep Purif Technol 2016 145 12 20 25. Zheng X Xu X Liu C Sun Y Lin Z Liu H Extraction characteristics and optimal parameters of anthocyanin from blueberry powder under microwave-assisted extraction conditions Sep Purif Technol 2013 104 17 25 10.1016/j.seppur.2012.11.011

PMC005xxxxxx/PMC5000471.txt

==== Front Virol JVirol. JVirology Journal1743-422XBioMed Central London 59910.1186/s12985-016-0599-yResearchCodon optimization of antigen coding sequences improves the immune potential of DNA vaccines against avian influenza virus H5N1 in mice and chickens Stachyra Anna 1Redkiewicz Patrycja 1Kosson Piotr 2Protasiuk Anna 1Góra-Sochacka Anna 1Kudla Grzegorz 3http://orcid.org/0000-0002-5205-2924Sirko Agnieszka +48 225925748asirko@ibb.waw.pl 11 Institute of Biochemistry and Biophysics, Polish Academy of Sciences, ul., Pawinskiego 5A, 02-106 Warsaw, Poland 2 Mossakowski Medical Research Centre Polish Academy of Sciences, ul., Pawinskiego 5, 02-106 Warsaw, Poland 3 MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU Scotland UK 26 8 2016 26 8 2016 2016 13 1 1439 6 2016 12 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Highly pathogenic avian influenza viruses are a serious threat to domestic poultry and can be a source of new human pandemic and annual influenza strains. Vaccination is the main strategy of protection against influenza, thus new generation vaccines, including DNA vaccines, are needed. One promising approach for enhancing the immunogenicity of a DNA vaccine is to maximize its expression in the immunized host. Methods The immunogenicity of three variants of a DNA vaccine encoding hemagglutinin (HA) from the avian influenza virus A/swan/Poland/305-135V08/2006 (H5N1) was compared in two animal models, mice (BALB/c) and chickens (broilers and layers). One variant encoded the wild type HA while the other two encoded HA without proteolytic site between HA1 and HA2 subunits and differed in usage of synonymous codons. One of them was enriched for codons preferentially used in chicken genes, while in the other modified variant the third position of codons was occupied in almost 100 % by G or C nucleotides. Results The variant of the DNA vaccine containing almost 100 % of the GC content in the third position of codons stimulated strongest immune response in two animal models, mice and chickens. These results indicate that such modification can improve not only gene expression but also immunogenicity of DNA vaccine. Conclusion Enhancement of the GC content in the third position of the codon might be a good strategy for development of a variant of a DNA vaccine against influenza that could be highly effective in distant hosts, such as birds and mammals, including humans. Electronic supplementary material The online version of this article (doi:10.1186/s12985-016-0599-y) contains supplementary material, which is available to authorized users. Keywords ChickensDNA vaccineGC contentH5N1InfluenzaMicehttp://dx.doi.org/10.13039/501100005632Narodowe Centrum Bada i RozwojuWND-POIG.01.01.02-00-007/08PBS2/A7/14/2014Sirko Agnieszka http://dx.doi.org/10.13039/100004440Wellcome Trust097383Kudla Grzegorz http://dx.doi.org/10.13039/501100000265Medical Research Councilissue-copyright-statement© The Author(s) 2016 ==== Body Background Vaccines against influenza are traditionally produced from viruses propagated in chicken embryos, however the first formulations with antigens produced in cell lines are also available, for example Flucelvax®. The traditional techniques have a number of disadvantages: (i) the process is slow and inflexible, which hinders a fast reaction in the case of new outbreaks, (ii) capacity is too small to produce enough doses, (iii) workers are exposed to the dangerous live pathogen and (iv) the virus can mutate during propagation. Moreover, highly pathogenic strains are difficult to propagate in eggs in sufficient amounts, due to their harmful effect on the host, and have to be reassorted or genetically engineered. Problematic are also traces of chicken proteins present in formulation, which are common allergens [1, 2]. The DNA vaccines seem to be a very promising alternative with multiple advantages. They are relatively easy and economical in production due to the lack of long-lasting and complicated procedures of antigen multiplication and purification. They can be quickly re-designed and re-constructed in case of sudden new disease outbreaks. They guarantee antigens with native structure, identical with those within infection, containing all posttranslational modifications, since they are produced in vivo in host cells. Moreover, they are safe and no infective form of the pathogen is needed at any step. DNA itself is also more stable in storage and transport than proteins. DNA vaccines induce both humoral and cellular immunological responses, stimulating T cells, antigen presenting cells and antibodies production, ensure broad, long lasting and protective response [3, 4]. Thus, it is not surprising that several clinical trials of DNA vaccines against influenza are now ongoing (http://clinicaltrials.gov/) [5, 6]. The expression level of cDNA encoding an antigen in the cells of immunized host is an important factor influencing the immunological potential of DNA-based vaccines. Manipulations within the coding sequence, such as replacing the rare codons with the synonymous codons preferred by the host organism and avoidance of RNA secondary structures motifs or others unprofitable features have been applied to improve the effectiveness of DNA vaccines against influenza [7]. For example, codon optimization of DNA vaccine based on HAs from A/New Caledonia/20/99 (H1N1) and A/Panama/2007/99 (H3N2) not only enhanced its immunogenicity but also might lead to the reduction of the number of required doses [8]. Similar results were also reported for DNA vaccine based on HA derived from the swine influenza virus A/Texas/05/2009 (H1N1) [9]. These authors demonstrated that optimization of the codon bias of HA from H1N1 resulted in stimulation of CD8+ (determined by the high levels of TNF, IFNγ and IL-2) and in elevated level of antibody production. Recently, also immunization of ponies (mixed breeds of Shetland blood, Welsh blood, Florida swamp pony blood) with monovalent or trivalent DNA vaccines (with mammalian preferred codons) encoding HAs from different strains of H3N8 equine influenza was reported [10]. The vaccine was administered to ponies that were subsequently challenged with the homologues virus. The degree of protection, virus shedding and clinical symptoms after infection were significantly reduced in all immunized groups compared to the negative control. Moreover, a moderate level of cross response was obtained in the group that received the trivalent formulation. Avian influenza is a serious and highly infectious disease of poultry and other bird species, caused by influenza viruses which can be also transmitted to humans causing high mortality [11, 12]. Therefore, development of effective vaccines against avian influenza is very important. In birds, higher effectiveness of the DNA vaccine based on the HA variant with codons optimized for chicken usage, where the optimized gene shared about 75 % nucleotides with the wild type gene, has been reported by several independent research groups. The examples include chicken [13] and Japanese quails [14] immunization by different variants of H5 HA. The authors mentioned several possible reasons of the observed superiority of the modified plasmid, such as increased expression due to usage of the chicken optimized codons, increased mRNA stability due to increased GC content and increased level of CpG motifs that could act as an adjuvant of immunological responses [13]. In contrast, no significant seroconversion differences between the groups immunized with the optimized and non-optimized variants were observed in the case of the DNA vaccine based on HA from the low pathogenic H6N2 virus [15]. The authors observed high inter-individual variation, possibly due to poor efficiency of the delivery method and/or the huge biological variation of individual responses. The H5 HA variants optimized for human preferred codons were also tested. For example, a large set of different HA optimized for human preferred codons was tested in mice and chickens and proven to elicit robust protective immune responses against a broad range of H5 influenza strains [16]. Animals received several multivalent combinations of DNA vaccines. Responses were tested by HI and virus microneutralization tests with homologous and heterologous antigens, as well as by the challenge experiment. The obtained results indicated protection against heterologous strains of highly pathogenic avian influenza H5N1 after vaccination with two doses of DNA vaccine. Another interesting approach was applied by the researchers who used the consensus sequence of H5 HA based on the sequences from 467 different H5 strains, optimized it for mammalian expression (using human preferred codons) and observed not only its high expression level but also strong protective immune response in vaccinated laboratory animals [17]. Most above-mentioned studies confirmed that codon optimization to the codon bias of the host improves the efficacy of DNA vaccine. However, several studies in mammalian cells suggest that increasing the GC content provides better mRNA stability, processing and nucleocytoplasmic transport [18–21]. Because the distribution of GC content among genes is similar in mammals and birds (Additional file 1: Figure S1), we hypothesized that GC content optimization might also lead to improved expression and immunogenicity in birds. The DNA vaccine prepared according to such criterion could be effective in many types of hosts, its design would be simplified and the obtained effects more universal. Therefore, the goal of this study was to evaluate the immunogenicity of the variant of DNA vaccine containing nearly 100 % of codons with GC at the third position in two model animals, mice and chickens, and comparing it to the other vaccine variants. All tested vaccine variants were based on HA from the highly pathogenic avian influenza virus A/swan/Poland/305-135V08/2006 (H5N1). Methods Plasmids used for DNA vaccination The HAw/pCI, K3/pCI and GK/pCI plasmids were used for DNA vaccination. The HAw/pCI plasmid contains the nucleotide sequence identical to the region encoding the full-length HA from A/swan/Poland/305-135V08/2006 (H5N1). The K3/pCI and GK/pCI plasmids contain two different nucleotide sequences encoding the same H5 HA protein as HAw/pCI (with the leader peptide) but without the proteolytic cleavage site (341-RRRKKRR-347) between HA1 and HA2 subunits. The sequence encoding HA, present in K3/pCI, was optimized for domestic chicken (Gallus gallus) and the codon adaptation index (CAI) reached 0.91. In contrast, the sequence encoding HA, present in GK/pCI was not optimized to any codon bias but it was was modified by changing the nucleotides present in the third positions of the codons to either guanine (G) or cytosine (C). The cDNA of K3 and GK were synthesized by GeneScript (USA; http://www.genscript.com/). Comparison of the HA sequences is shown in Additional file 2: Figure S2. The inserts were cloned into MluI and SalI restriction sites of the pCI expression vector (Promega, Wisconsin, USA) downstream of the cytomegalovirus (CMV) promoter and upstream of the SV40 late polyadenylation signal. Plasmids were propagated in DH5α strain of Escherichia coli and isolated using NucleoBond® PC 10000 EF Giga-scale purification kit (Macherey-Nagel, Düren, Germany). Transfection of mammalian cells The mouse myoblast cells (2x105 cells; C2C12 line) were transfected with 2 μg of HAw/pCI, K3/pCI, GK/pCI or pCI using Lipofectamine® 3000 Reagent (ThermoFisher Scientific, Waltham, USA) as described by the manufacturer. After 48h the cells were scraped off into the RIPA buffer (ThermoFisher Scientific, Waltham, USA), transferred to the 1.5 ml tubes and frozen in liquid nitrogen, following thawing at 37 °C (three times). The homogenates were centrifuged at 10 000× g for 8 min at 4 °C and the equal amounts of protein extract were analyzed by SDS-PAGE (Nu-Page™ 4-12 % Bis-Tris gel, Invitrogen™, Basel, Switzerland) and Western blotting. The nitrocellulose membranes were blocked in 5 % milk in 1× TBS buffer (50 mM Tris, pH 8, 150 mM NaCl, 1 % Tween 80) and incubated for 1.5h with primary antibody anti – HA (H5) (1:500, ImmuneTechnology, USA), or anti- GAPDH (1:20000, Sigma, St. Louis, USA) and for 1h with secondary antibody (anti-rabbit or anti-mouse IgG (whole molecule) − alkaline phosphatase antibody; Sigma, St. Louise, USA). The enzymatic color reaction was generated using NBT/BCIP Stock Solution (Roche, Switzerland). The bands intensity was compared using the Image J (https://imagej.nih.gov/ij/). Immunization of animals Vaccine doses were prepared by mixing plasmid DNA (suspended in PBS, pH 7.4) with Lipofectin® (Invitrogen™, Basel, Switzerland) in ratio 6:1 as described earlier [22]. Our previous results indicated that the DNA vaccination was more effective when plasmid was used with a lipid carrier (Additional file 3: Figure S3 and [22]). Schemes of the immunization experiments are presented in Fig. 1 and the number of animals and DNA doses used in each experiment is indicated in Table 1. Specific-pathogen free BALB/c female mice (5–6 weeks of age) were maintained in standard conditions with free access to water and standard mouse diet at the experimental facility in Mossakowski Medical Research Centre Polish Academy of Sciences. Mice were immunized intramuscularly (in quadriceps of left thigh; one spot) and obtained two 50-μl doses of the vaccine, on days 35 and 49 (days of life). Several doses of plasmid DNA were tested in order to choose the most convenient dose for the comparison of the vaccine variants. The blood samples were collected three-fold: two weeks after the first immunization (day 49), one week (day 56) and two weeks (day 63) after the second immunization. Broiler chickens (Ross 308) and layer chickens (Rosa 1) were purchased from commercial brooder on the hatching day and maintained in standard bedding conditions at experimental poultry house. Birds were immunized intramuscularly (in breast muscle, one spot) on days 7 and 21 (day of life) using 60 μg of plasmid DNA mixed with Lipofectin® in a final volume of 100 μl. The dose was chosen as optimal for the purposes of this study based on our previous experiment with chickens immunization [22, 23]. The blood samples were collected from the wing vein on days 21, 28 and 35 in Experiment 1 and on days 21 and 35 in Experiment 2.Fig. 1 Schedule of mice (a) and chickens (b) experiments Table 1 Number of animals used in immunization experiments DNA dose Number of animals per group HAw/pCI K3/pCI GK/pCI pCI Mice Experiment 1 20 μg 7 6 - 6 Experiment 2 10 μg - 6 7 - 50 μg - 6 6 2 Experiment 3 10 μg - 6 5 2 Experiment 4 20 μg - 6 6 2 Chickens Experiment 1 (Broilers) 60 μg 8 8 - 5 Experiment 2 (Layers) 60 μg - 6 6 2 Experiment 3 (Broilers) 60 μg - 10 9 4 All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. The experiments of mice immunization were approved by the Fourth Local Ethical Committee for Animal Experiments at the National Medicines Institutes, Permit Number 03/2014. The experiments with chickens were approved by the Second Local Ethical Committee for Animal Experiments at the Medical University of Warsaw, Permit Number 17/2009. Elisa Mice: 96-well flat-bottom plates (MaxiSorp Surface, Nunc, UK) were coated with 300 ng of purified recombinant H5 HA (A/swan/Poland/305-135V08/2006, H5N1) (derived from a baculovirus system (Oxford Expression Technologies, UK) at 2–8 °C overnight. After removing the coating buffer, the plates were washed three times with 1× PBST (phosphate buffered saline with 0,05 % of Tween-20) and blocked with 2 % of BSA-PBST at 37 °C for 90 min. After 2 washes, the 100-fold in Experiment 1, Experiment 3 and Experiment 4 and the 50-fold (49d) or 200-fold (56d and 63d) in Experiment 2 diluted sera samples were added and incubated at 2–8 °C overnight. Next day, after 4 washes, plates was incubated for 1h at 37 °C with alkaline phosphatase-conjugated goat anti-mouse IgG (Sigma Aldrich, St. Louise, USA). The enzymatic color reaction was performed using alkaline phosphatase yellow (pNPP) liquid substrate (Sigma, St.LouiseUSA), stopped with 3M NaOH and measured (OD405) using a Synergy/HT microplate reader (BioTek Instruments, Inc.). Chickens: 96-well flat-bottom plates (MediSorp Surface, Nunc, UK) were coated with the same antigen as above. After removing the coating buffer, the plates were washed four times with 1× PBST and blocked with 2 % of BSA-PBST at 37 °C for 90 min. Following 2 washes, the 200-fold diluted sera samples were added and incubated at 2–8 °C overnight. Next day, after 5 washes plates were incubated for 1h at 37 °C with peroxidase-conjugated goat anti-chicken IgY (Life Technologies, USA). The enzymatic color reaction was generated using TMB substrate (Sigma, St.Louise, USA), stopped with 0.5M H2SO4 and measured (OD450) as above. Antibody endpoint titers For determination of IgY endpoint titers two-fold serial dilutions of chicken sera collected on day 35 (in range from 10−3 to 10−6) were made and analyzed using the ELISA protocol. Based on OD450 values the absorption curves were made and the endpoint titers were determined using Gen5 Data Analysis Software (BioTek Instruments, Inc.). Hemagglutination inhibition (HI) HI tests were performed according to the OIE standard procedures using the commercially available hemagglutinating antigen prepared from low pathogenic H5N2 strain A/chicken/Belgium/150/1999 (DG Deventer, Netherlands) with 96 % protein sequence similarity to the vaccine antigen. For the HI test, serum to be tested was serially two-fold diluted (1:8 to 1:512) in 25 μl of PBS in V-bottom microtiter plates and an equal volume of HA antigen containing 4 HA units was added. After incubation at room temperature (RT) for 25 min, 25 μl of a 1 % suspension of hens’ red blood cells was added and incubated for 25 min at RT. HI titers are shown as the reciprocal of the highest dilution of sera that completely inhibited hemagglutination. Cytokine production assay Immunized and control mice were euthanized two weeks after boost dose (day 63) and their spleens were harvested. The spleen cell suspensions from the pooled two spleens (from two randomly selected mice from the same group) were washed in RPMI-1640 medium (Sigma, USA) and treated for 5 min with the Lysis buffer (BD, Franklin Lakes, USA) in order to clear red blood cells. To determine the amount of cytokines in culture supernatants, splenocytes (2x106 per well) were incubated in 96-well plates (Corning, Corning, USA) with complete RPMI-1640 with 10 μg/ml of recombinant H5 HA protein purified from the baculovirus system (Oxford Expression Technologies, England), 5 μg/ml Concavaline A (Con A) or medium alone (see above). Cells were incubated for 72h (37 °C, 5 % CO2) and centrifuged (10 min, 1000 rpm, 4 °C). The level of cytokines was quantified in the collected supernatants using Cytometric Bead Array Mouse Th1/Th2/Th17 Cytokine Kit (BD, Franklin Lakes, USA) according to the manufacturer’s instructions and the FASCCalibur™ flow cytometer (BD, Franklin Lakes, USA). Statistical analysis Non-parametric tests, such as Kruskal-Wallis (for comparison of multiple groups) or Wald-Wolfowitz, Kolmogorov-Smirnov and Mann-Whitney U (for comparison of two groups) that are components of Statistica 12 (StatSoft, Poland) were used to evaluate the statistical differences. The groups were considered significantly different if at last one of the test was positive (p < 0.05). Results Verification of the HA expression cassettes in mammalian cells The HAw/pCI, K3/pCI and GK/pCI plasmids, containing the variants of H5 HA from A/swan/Poland/305-135V08/2006 (H5N1), were transiently transfected into the mammalian cells and the level of H5 HA protein produced by the transfected cells was monitored (Fig. 2). The cells transfected with GK/pCI usually produced about 15–30 % more HA than the cells transfected with K3/pCI, while the HA protein in cells transfected with HAw/pCI was hardly detectable. These results indicated that enriching nucleotide sequence encoding HA with GC in the third positions of the codons improves the functionality of the HA cassette in mice cells in comparison to the variant optimized for chicken codon bias.Fig. 2 Expression of H5 HA in the C2C12 cell line (mouse myoblasts) transfected with the indicated plasmids: HAw/pCI, K3/pCI, GK/pCI and empty pCI as a negative control. About 200 ng of recombinant H5 HA [A/Bar-Headed Goose/Qinghai/12/05 (H5N1)] was used as a positive control (HA). GAPDH (Glyceraldehyde-3-phosphate dehydrogenase) represents the product of an intrinsic gene, was used as a loading control. Data are representative of at least three independent experiments. L – Page Ruler™Prestaned Protein Ladder with the size of protein bands indicated Comparison of the effectiveness of HAw/pCI and K3/pCI in two animal models The effectiveness of two DNA vaccines, the wild type (HAw/pCI) and the variant optimized for chicken codon bias (K3/pCI), was compared in two model animals, mice and chickens (broilers). The DNA doses and the number of animals vaccinated with the compared variants is shown as Experiment 1 for either mice or chickens in Table 1. The level of anti-H5 HA antibodies in sera collected from the immunized mice and chickens are shown in Fig. 3a and b, respectively. Both vaccine plasmids stimulated anti-H5 HA humoral response with apparently better parameters in the case of K3/pCI groups, however the differences between K3/pCI and HAw/pCI failed to pass the statistical significance test. In both immunized organisms the geometric means and/or medians of the K3/pCI groups were usually higher than of the respective HAw/pCI groups, especially in sera collected one week after the booster (day 56) for mice and one and two weeks after the booster (days 28 and 35) for chickens. Results of this experiment failed to indicate significant differences between HAw/pCI and K3/pCI, however they might suggest that HAw/pCI is slightly inferior in comparison to K3/pCI in both animal models.Fig. 3 Comparison of humoral responses in animals immunized with two variants of the DNA vaccine. The mice (a) and chickens (b) sera was tested for the presence of the anti-H5 HA antibodies after immunization with the variant containing the wild type H5 HA (HAw/pCI) and the variant containing H5 HA optimized to the chicken codon bias (K3/pCI). The results of one-dilution ELISA for individuals, medians and the 10th and 90th percentiles are shown for each group. The number of individuals was as indicated in Table 1, in Experiment 1 for mice and chickens, respectively. The values in the brackets are the geometric means calculated for the K3/pCI and GK/pCI groups Mice response to the optimized variants of DNA vaccine The subsequent mice immunizations have been conducted according to the same general scheme (Fig. 1a) in three independent experiments, labeled as Experiment 2, 3 and 4. The results of one-dilution ELISA, detecting presence of specific anti-H5 HA antibodies in mice sera are shown in Fig. 4. The used doses of DNA and the number of animals in each group are indicated in Table 1. The lowest dose of the DNA (10 μg) was used two times, once in Experiment 2 and once in Experiment 3 but the statistically significant differences between K3/pCI and GK/pCI groups were observed only in Experiment 3, on days 49 and 56. Each of the higher doses of DNA, 50 μg and 20 μg, were tested only once, in Experiment 2 and 4, respectively. The statistically significant differences between the K3/pCI and GK/pCI groups were observed only in case of 50μg dose on days 49 and 63 (Fig. 4).Fig. 4 Comparison of humoral responses in mice immunized with two optimized variants of DNA vaccine. The presence of anti H5 HA antibodies was monitored in sera collected from the animals on the indicated days in three independent experiments, Experiments 2, 3 and 4 (see also Table 1). The results for individuals, medians and the 10th and 90th percentiles are shown for each group. Statistically significant differences between groups K3/pCI and GK/pCI (p < 0.05) are marked by asterisks. The arrows show from which individuals the spleens have been harvested. The values in the brackets are the geometric means calculated for the K3/pCI and GK/pCI groups The supernatants of liquid cultures of stimulated splenocytes from the spleens isolated at the end of the Experiment 4 (day 63) from two individuals per group were used to measure the levels of interleukin 2 (IL-2), interleukin 4 (IL-4), interleukin 6 (IL-6), interferon-γ (IFN-γ), tumor necrosis factor (TNF), interleukin 17A (IL-17A), and interleukin 10 (IL-10) in a single sample (Fig. 5). The IL-4 and IL-17A were not detected in the tested supernatants. No secretion of TNF, IL-6 and IL-2 or very low secretion IFN-γ was observed in the case of activated splenocytes collected from the control group vaccinated with the empty pCI vector (data not shown). Interestingly, the level of IL-2 and IL-10 was several-fold higher in the case of K3/pCI than GK/pCI, while the levels of IFN-γ, TNF and IL-6 were higher in the case of GK/pCI.Fig. 5 Levels of selected cytokines produced by H5 HA-stimulated splenocytes. The assay was performed with the splenocytes isolated from two pulled down spleens (from two individuals from the same group, indicated by arrows in Fig. 4) collected at the end of experiment (day 63) Chickens response to the optimized variants of DNA vaccine The optimized variants (K3/pCI and GK/pCI) of DNA vaccine were used for immunization of layers and broilers in two independent chicken experiments, labeled as Experiment 2 and 3, respectively. The humoral responses were first evaluated by one-dilution ELISA using the standard 200-fold dilutions of sera (Fig. 6a,b). The medians were always higher in GK/pCI groups than in the respective K3/pCI groups, however only in broilers in sera collected on day 21 (two weeks after the first dose) the differences passed the applied statistical significance test (Fig. 6b).Fig. 6 Comparison of humoral responses in sera of chickens immunized with two optimized variants of DNA vaccine. The results for individuals, medians and the 10th and 90th percentiles are shown for K3/pCI and GK/pCI groups of layers (a) and broilers (b). The percentage distribution of IgY endpoint titers into four categories within the groups and the HI titers are presented in panels (c) and (d), respectively. The number of individuals was as indicated in Table 1, in Experiment 2 and Experiment 3 for layers and broilers, respectively. The values in the brackets are the geometric means calculated for the K3/pCI and GK/pCI groups Next, the endpoint titers of anti-H5 HA in the sera collected two weeks after the booster (on day 35) were assayed and, in order to facilitate the interpretation of data, they were arbitrarily divided into four categories: high (>105), medium (104-105), low (103-104) and very low (<103) (Fig. 6c). In layers, none of the probes from the K3/pCI group reached the end-point titer above 105 and 33 % of probes did not exceed the titer above 103, in contrast to the 33 and 17 % of such probes, respectively, in the case of GK/pCI group. The highest titer of layers’ sera from K3/pCI and GK/pCI group was 7 × 104 and 4 × 105, respectively. The endpoint titers of the broilers’ sera indicated less variability within the groups and the highest titers were more similar (both about 2 × 105). In broilers, 40 % of the probes from the K3/pCI group had titers above 105 and all of them were above 103, while all sera from the GK/pCI group had titers above 104, including 33 % with the titer above 105. The results of hemagglutination inhibitions (HI) test seem to confirm a slightly better performance of the GK/pCI vaccine over the K3/pCI vaccine in both chicken experiments, however the differences are not statistically significant (Fig. 6d). Discussion DNA vaccines containing the optimized variants of H5 HA gene induced strong and specific immune responses in mice and chickens. In both animal models the slight superiority of GK/pCI over K3/pCI was observed. The observed differences were frequently statistically significant. Changes within GK did not regard the codon usage preference in any particular organism but the key was maximization of the GC content at the third coding position of HA (43, 65 and 99.8 % in HAw/pCI, K3/pCI and GK/pCI, respectively). This study was inspired by the previous reports indicating that an increased GC content provides better mRNA stability, processing and nucleocytoplasmic transport [18, 20]. In fact, our results can be explained and are in full agreement with the above literature data. We started with verification of the modified cassettes by monitoring of the level of HA protein produced in mouse muscle cells (C2C12) transfected with K3/pCI and GK/pCI. Indeed, about 15–30 % higher level of HA protein production was observed in cells transfected with GK/pCI than with K3/pCI, which corresponds well with apparently higher immune responses to GK/pCI than to K3/pCI in the immunized animals. The correlation between in vitro expression in transfected cells and immunogenicity of DNA vaccine was also observed by others [24, 25]. Little is known about the timing of cytokine production after immunization. We investigated the profiles of cytokines in the supernatants from the cultured, stimulated with H5 HA for 72h, mice splenocytes that were isolated from the spleens of the immunized animals. In the supernatants we confirmed the presence of five of seven tested cytokines. The levels of IFN-γ, TNF and IL-6 were higher in the group immunized with GK/pCI than with K3/pCI. This result suggests that codon optimization affects both branches of immune responses, humoral (IL-6) and cellular (IFN-γ, TNF) what was previously reported in studies with HIV and HPV DNA vaccine [26, 27]. The lower levels of IL-2 and IL-10 in GK/pCI than K3/pCI group is unclear and need further investigation. The lower level of IL-2 was also observed by Tenbusch et al. in stimulated CD4+ from mice immunized with DNA vaccine containing the optimized sequence for the HA from H1N1 [9]. We did not detect IL-4 nor IL-17A. The lack of IL-17A might be explained by the high concentration of IFN-γ negatively regulating the induction of Th17 cells [28]. The lack of IL-4 might be explained by the conditions of the assay and splenocytes cultivation (and induction) which were optimal for IFN-γ but not IL-4 detection due to the short half-life of the letter [29]. Additional analysis of mice sera (data not shown) indicated that although the level of IgG2a (one of two major isotypes of antibodies) was rather similar in both groups, the level of IgG1 was slightly higher in GK/pCI than in K3/pCI. This result might suggest that the elevation of immune response in GK/pCI group concerned mostly the elevation of Th2 type, however these aspects of the response to the vaccine variants require more studies. Better efficacy of GK/pCI than K3/pCI observed in chickens is in contrast with the results by Rao et al. [30] who reported that in chicken genome the GC content at the third coding position is negatively correlated with the expression level and that it is not correlated with the maximum expression level. Based on their own analysis, the authors stated that the GC content in genes (general, not only in the third codon positions) could explain only approximately 10 % of the variation in gene expression. According to Kudla at al. [20] the efficient transcription or mRNA processing is responsible for the high expression of GC-rich gene, while other researchers (for example [31, 32]) assumed that the increased expression of codon–optimized genes was caused by the more efficient translational mechanism. The high effectiveness of the variant with nearly 100 % codons with GC at the third position in both model animals (regardless of the codon usage preferences) suggests that the first hypothesis might be correct. Interestingly, the immunization was generally more effective in broilers than in layers. The results of ELISA test, as well as of HI test were less variable within the broiler groups (70–88 % positives). Immunization of the layers type chickens gave slightly lower and more variable antibody levels and slightly worse results in the HI test (Fig. 5c). On average, the endpoint titers were lower in layers than in broilers, particularly in K3/pCI groups. Many factors can disturb the effectiveness of immunization and the chickens might respond in a very individual way, as observed by others, too [15]. DNA uptake by the target cells, preceded by penetration of sufficient area of tissue after injection seems to be crucial. It is worth to emphasize that the dose chosen for chickens’ immunization was suboptimal for better visualization of the expected differences in immune response. Differences in the strength and dynamic of broilers’ and layers’ responses can be linked to the different genetic background of two used chicken types, differences in their metabolism, growth and development which are results of intensive genetic selection [33]. Chickens are not so popular animal model as mice in immunological studies, still considerable number of publications about chicken immunization with DNA vaccine, especially with avian influenza antigens are available [7]. Most of such experiments were performed with specific pathogen free White Leghorn chickens. In this study we used birds, which are popularly used in Poland for the commercial purposes: the broiler line Ross 308 and the layer line Rosa 1 (a hybrid of Rhode Island and Sussex) and kept them in standard commercial conditions, which allow us to observe natural reactions to the immunizations. Moreover, to our knowledge this is the first report on comparison of the layers’ and the broilers’ humoral responses to the DNA vaccine. Some papers comparing immunological responses of broiler and layer types are available [34–36], however in these experiments conventional vaccines against Salmonella sp. were used, or synthetic peptide antigen, not originated from any poultry disease. Similarly to our results, differences in responses between broilers and layers have been previously reported. Conclusion In summary, our results strongly suggest that the enhancement of GC content in the third positions of the codons is a promising strategy for development of DNA vaccine that could be highly effective in a broad range of target species, such as birds and mammals, including humans. Additional files Additional file 1: The mean GC content of the genes in Homo sapiens, Mus musculus, Gallus gallus and Influenza A virus. (PPT 132 kb) Additional file 2: Alignment of sequences encoding H5 HA included in HAw/pCI, K3/pCI and GK/pCI. (DOCX 58 kb) Additional file 3: Serum humoral response in individual mice and chickens after DNA immunization with and without lipofectin. (PPT 157 kb) We dedicate this work to the memory of Professor Włodzimierz Zagórski-Ostoja, who was actively involved in its initial stages. Funding This study was funded by the National Center for Research and Development (EC Innovative Economy Program POIG.01.01.02-00-007/08) and in part by Grant No. PBS2/A7/14/2014 from the National Centre for Research and Development. GK was supported by the Wellcome Trust (097383) and by the Medical Research Council. Authors’ contribution ASt and AP conducted the chicken experiments, PR and PK conducted the mice experiments, ASi, AG-S and GK participated in study design and data analysis. All authors participated in manuscript and figures preparation, have read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Part of presented results is a subject of pending patent application P-411230 (Poland). Ethics approval and consent to participate All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. The experiments of mouse immunization were approved by the Fourth Local Ethical Committee for Animal Experiments at the National Medicines Institutes, Permit Number 03/2014. The experiments with chickens were approved by the Second Local Ethical Committee for Animal Experiments at the Medical University of Warsaw, Permit Number 17/2009. ==== Refs References 1. Wong SS Webby RJ Traditional and new influenza vaccines Clin Microbiol Rev 2013 26 476 492 10.1128/CMR.00097-12 23824369 2. Gerdil C The annual production cycle for influenza vaccine Vaccine 2003 21 1776 1779 10.1016/S0264-410X(03)00071-9 12686093 3. Khan KH DNA vaccines: roles against diseases Germs 2013 3 26 35 10.11599/germs.2013.1034 24432284 4. Trovato M Berardinis PD Novel antigen delivery systems World J Virol 2015 4 156 168 10.5501/wjv.v4.i3.156 26279977 5. Ledgerwood JE, Hu Z, Costner P, Yamshchikov G, Enama ME, Plummer S, Hendel CS, Holman L, Larkin B, Gordon I, et al. Phase I Clinical Evaluation of Seasonal Influenza Hemagglutinin (HA) DNA Vaccine Prime Followed by Trivalent Influenza Inactivated Vaccine (IIV3) Boost. Contemp Clin Trials. 2015;44:112-18. 6. Kibuuka H Berkowitz NM Millard M Enama ME Tindikahwa A Sekiziyivu AB Costner P Sitar S Glover D Hu Z Safety and immunogenicity of ebola virus and marburg virus glycoprotein DNA vaccines assessed separately and concomitantly in healthy ugandan adults: a phase 1b, randomised, double-blind, placebo-controlled clinical trial Lancet 2015 385 1545 1554 10.1016/S0140-6736(14)62385-0 25540891 7. Stachyra A Góra-Sochacka A Sirko A DNA vaccines against influenza Acta Biochim Pol 2014 61 515 522 25210719 8. Wang S Taaffe J Parker C Solorzano A Cao H Garcia-Sastre A Lu S Hemagglutinin (HA) proteins from H1 and H3 serotypes of influenza a viruses require different antigen designs for the induction of optimal protective antibody responses as studied by codon-optimized HA DNA vaccines J Virol 2006 80 11628 11637 10.1128/JVI.01065-06 16987975 9. Tenbusch M Grunwald T Niezold T Storcksdieck Genannt Bonsmann M Hannaman D Norley S Uberla K Codon-optimization of the hemagglutinin gene from the novel swine origin H1N1 influenza virus has differential effects on CD4(+) T-cell responses and immune effector mechanisms following DNA electroporation in mice Vaccine 2010 28 3273 3277 10.1016/j.vaccine.2010.02.090 20206668 10. Ault A Zajac AM Kong WP Gorres JP Royals M Wei CJ Bao S Yang ZY Reedy SE Sturgill TL Immunogenicity and clinical protection against equine influenza by DNA vaccination of ponies Vaccine 2012 30 3965 3974 10.1016/j.vaccine.2012.03.026 22449425 11. Sonnberg S Webby RJ Webster RG Natural history of highly pathogenic avian influenza H5N1 Virus Res 2013 178 63 77 10.1016/j.virusres.2013.05.009 23735535 12. Palese P Influenza: old and new threats Nat Med 2004 10 S82 S87 10.1038/nm1141 15577936 13. Jiang Y Yu K Zhang H Zhang P Li C Tian G Li Y Wang X Ge J Bu Z Chen H Enhanced protective efficacy of H5 subtype avian influenza DNA vaccine with codon optimized HA gene in a pCAGGS plasmid vector Antiviral Res 2007 75 234 241 10.1016/j.antiviral.2007.03.009 17451817 14. Li JP Jiang YP Zhao SC Chang XF Liu JX Zeng XY Li YB Chen HL Protective efficacy of an H5N1 DNA vaccine against challenge with a lethal H5N1 virus in quail Avian Dis 2012 56 937 939 10.1637/10150-040812-ResNote.1 23402115 15. Shan S Jiang Y Bu Z Ellis T Zeng X Edwards J Tian G Li Y Ge J Chen H Fenwick S Strategies for improving the efficacy of a H6 subtype avian influenza DNA vaccine in chickens J Virol Methods 2011 173 220 226 10.1016/j.jviromet.2011.02.008 21333689 16. Rao S Kong WP Wei CJ Yang ZY Nason M Styles D DeTolla LJ Panda A Sorrell EM Song H Multivalent HA DNA vaccination protects against highly pathogenic H5N1 avian influenza infection in chickens and mice PLoS One 2008 3 e2432 10.1371/journal.pone.0002432 19293944 17. Chen MW Cheng TJ Huang Y Jan JT Ma SH Yu AL Wong CH Ho DD A consensus-hemagglutinin-based DNA vaccine that protects mice against divergent H5N1 influenza viruses Proc Natl Acad Sci U S A 2008 105 13538 13543 10.1073/pnas.0806901105 18765801 18. Goetz RM Fuglsang A Correlation of codon bias measures with mRNA levels: analysis of transcriptome data from escherichia coli Biochem Biophys Res Commun 2005 327 4 7 10.1016/j.bbrc.2004.11.134 15629421 19. Han JS Boeke JD A highly active synthetic mammalian retrotransposon Nature 2004 429 314 318 10.1038/nature02535 15152256 20. Kudla G Lipinski L Caffin F Helwak A Zylicz M High guanine and cytosine content increases mRNA levels in mammalian cells PLoS Biol 2006 4 e180 10.1371/journal.pbio.0040180 16700628 21. Nguyen KL Llano M Akari H Miyagi E Poeschla EM Strebel K Bour S Codon optimization of the HIV-1 vpu and vif genes stabilizes their mRNA and allows for highly efficient Rev-independent expression Virology 2004 319 163 175 10.1016/j.virol.2003.11.021 15015498 22. Stachyra A Góra-Sochacka A Sawicka R Florys K Sączyńska V Olszewska M Pikuła A Śmietanka K Minta Z Szewczyk B Highly immunogenic prime–boost DNA vaccination protects chickens against challenge with homologous and heterologous H5N1 virus Trials Vaccinology 2014 3 40 46 10.1016/j.trivac.2014.02.002 23. Stachyra A Gora-Sochacka A Zagorski-Ostoja W Krol E Sirko A Antibody response to DNA vaccine against H5N1 avian influenza virus in broilers immunized according to three schedules Acta Biochim Pol 2014 61 593 596 25180224 24. Shan S Ellis T Edwards J Fenwick S Robertson I Comparison of five expression vectors for the Ha gene in constructing a DNA vaccine for H6N2 influenza virus in chickens Adv Microbiol 2016 6 310 319 10.4236/aim.2016.64030 25. Uchijima M Yoshida A Nagata T Koide Y Optimization of codon usage of plasmid DNA vaccine is required for the effective MHC class I-restricted T cell responses against an intracellular bacterium J Immunol 1998 161 5594 5599 9820537 26. Deml L Bojak A Steck S Graf M Wild J Schirmbeck R Wolf H Wagner R Multiple effects of codon usage optimization on expression and immunogenicity of DNA candidate vaccines encoding the human immunodeficiency virus type 1 Gag protein J Virol 2001 75 10991 11001 10.1128/JVI.75.22.10991-11001.2001 11602739 27. Siegismund CS Hohn O Kurth R Norley S Enhanced T- and B-cell responses to simian immunodeficiency virus (SIV)agm, SIVmac and human immunodeficiency virus type 1 Gag DNA immunization and identification of novel T-cell epitopes in mice via codon optimization J Gen Virol 2009 90 2513 2518 10.1099/vir.0.013730-0 19587137 28. Harrington LE Hatton RD Mangan PR Turner H Murphy TL Murphy KM Weaver CT Interleukin 17-producing CD4+ effector T cells develop via a lineage distinct from the T helper type 1 and 2 lineages Nat Immunol 2005 6 1123 1132 10.1038/ni1254 16200070 29. Conlon PJ Tyler S Grabstein KH Morrissey P Interleukin-4 (B-cell stimulatory factor-1) augments the in vivo generation of cytotoxic cells in immunosuppressed animals Biotechnol Ther 1989 1 31 41 2562642 30. Rao YS Chai XW Wang ZF Nie QH Zhang XQ Impact of GC content on gene expression pattern in chicken Genet Sel Evol 2013 45 9 10.1186/1297-9686-45-9 23557030 31. Andre S Seed B Eberle J Schraut W Bultmann A Haas J Increased immune response elicited by DNA vaccination with a synthetic gp120 sequence with optimized codon usage J Virol 1998 72 1497 1503 9445053 32. Zolotukhin S Potter M Hauswirth WW Guy J Muzyczka N A “humanized” green fluorescent protein cDNA adapted for high-level expression in mammalian cells J Virol 1996 70 4646 4654 8676491 33. Buzała M Janicki B Czarnecki R Consequences of different growth rates in broiler breeder and layer hens on embryogenesis, metabolism and metabolic rate: a review Poult Sci 2015 94 728 733 10.3382/ps/pev015 25691756 34. Groves PJ Sharpe SM Cox JM Response of layer and broiler strain chickens to parenteral administration of a live salmonella typhimurium vaccine Poult Sci 2015 94 1512 1520 10.3382/ps/pev127 26009756 35. Penha Filho RA de Paiva JB Arguello YM da Silva MD Gardin Y Resende F Berchieri Junior AB Sesti L Efficacy of several vaccination programmes in commercial layer and broiler breeder hens against experimental challenge with salmonella enterica serovar enteritidis Avian Pathol 2009 38 367 375 10.1080/03079450903183645 19937524 36. Koenen ME Boonstra-Blom AG Jeurissen SH Immunological differences between layer- and broiler-type chickens Vet Immunol Immunopathol 2002 89 47 56 10.1016/S0165-2427(02)00169-1 12208050

PMC005xxxxxx/PMC5000472.txt

==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3248310.1038/srep32483ArticleGene–culture interaction and the evolution of the human sense of fairness Liu Tru-Gin a1Lu Yao 121 National Sun Yat-sen University, Institute of Economics, Kaohsiung, 80424, Taiwan2 Wuhan University, Dong Fureng School of Economic and Social Development, Beijing, 100010, Chinaa trugin@mail.nsysu.edu.tw26 08 2016 2016 6 3248309 05 2016 08 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/How Darwinian evolution would produce creatures with the proclivity of Darwinian generosity, most of them voluntarily giving up the immediate benefit for themselves or their genes, remains a puzzle. This study targets a problem, the origin of human sense of fairness, and uses fairness-related genes and the social manipulation of Darwinian generosity as the key variables underlying the human sense of fairness, inequity aversion, as well as their relationships within cooperation, and the anticipation foresight of the way relationships are affected by resource division, given the assumption of randomly matched partners. Here we suggest a model in which phenotype will gradually converge towards the perfect sense of fairness along with the prospect of cooperation. Later, the sense of fairness will decrease but it is never extinct. Where social manipulation of Darwinian generosity overshadows genetics, the sense of fairness could be acute to the degree of social manipulation. Above all, there still exists a threshold in the degree of social manipulation, beyond which altruism dominates selfishness in human cooperation. Finally, we propose three new directions toward more realistic scenarios stimulated by recent development of the synergy between statistical physics, network science and evolutionary game theory. ==== Body The sense of fairness remains unknown how it arose, especially Darwinian generosity, observed only in chimpanzees and humans12. It argues that the human response to unfairness evolved in order to support long-term cooperation1. Gene–culture coevolution is key for explaining important patterns within the sense of fairness3. Neuroeconomists, recently, have been particularly interested in assessing the way allocation decisions are made while interacting with others, pointing towards how the sense of fairness emerges and works24. Evidence shows that negative effects on altruistic cooperation are caused by economic incentives in the case when they come in the form of sanctions or are associated with selfish intentions3. Because the identification of fairness-related genes escapes measurement, while genetic group selection is unlikely to occur empirically56, simulation experiments are focusing potential evolutionary patterns of fairness-related genes. Here we show that there exists a critical value in the degree of social manipulation, beyond which altruism dominates the perfect sense of fairness, and vice versa. Second, the emergence of the perfect sense of fairness is not necessarily reliant on continued intra-generational cooperation1. The increasing prospect for cooperation across generations is sufficient enough for its emergence. In contrast with the intra-generation version wherein reputation is important, the sense of fairness evolves intergenerationally as well7. Third, the sense of fairness, the first degree inequity aversion (IA1), and the second degree inequity aversion (IA2) are not mutually independent even without continued cooperation1. Furthermore, most results of the ultimate game experiments2891011121314151617 are consistent with the fairness-norm hypothesis18. In the more general context, social manipulation is a device, overshadowing the genetics system to associate people together wherever applicable. From a broader perspective, this device has far-reaching implications for the evolution of human sense of fairness in the near future. Is sense of fairness innate or something developed in social life? The answer relates to what fairness is defined as in terms of evolution. The argument that vampire bats have their own way of sharing blood with nonkin can be made in complete analogy with our way of sharing, i.e., “fairness”19. Following this thought, how our current fairness norms operate is indivisible from how they evolve, since each sheds light on the other. Although, only a small portion of mammals have ever demonstrated a sense of fairness or unfairness among all, a few primates and almost all breeds of apes do have this sense with the levels of IA varying upon the group of mammals. In most cases, they belong to IA1, negative reactions to inequity to the detriment of the actor8. Human’s economic incentives mainly cause negative effects on altruistic cooperation, if they come in the form of sanctions and are associated with greedy or selfish intentions3. IA2, also known as Darwinian generosity, refers to negative reactions to inequity that benefits the actor or overcompensator2. It requires advanced cognition and emotional control, only observed in chimpanzees and humans thus far. IA1 is reported to be more pronounced than IA220, while IA1 emerged earlier as well21. In neuroeconomics, there recently has been a surge of interest in assessing the way allocation decisions are made while interacting with others, especially how the sense of fairness emerges and works4. This is the foundation of the full-blown human sense of fairness. Although fairness is essential to humans, how it arose remains unknown, especially, IA2. Scientists believe that the emergence of the sense of fairness is in close relation with cooperation, despite presenting an evolutionary puzzle for its negative impact on the short-term interests of at least some parties. Theoretical and experimental studies on various guises of cooperation and a wide range of animal species suggest four paths to cooperation: reciprocal altruism, kinship, group-selected cooperation, and byproduct mutualism. Each can be transformed directly from the cooperator’s dilemma game with slight changes in the payoffs. Cooperation in a particular case may follow a single path or contain at least two elements22. Hence, the human sense of fairness should associate four dimensions, each with at least one path to cooperation. In addition, many studies emphasize that culture and social learning are substantially important in its formation2324. It argues that the human response to unfairness evolves from the sake of supporting long-term cooperation, otherwise the latter would not have sustained without appropriate channels to ensure the sharing of payoffs1. One wonders whether such channels are more associated with social environmental evolution or was already embedded within our genes. Scholars believe that experimental results drawing from the pure ultimatum game (UG), wherein haggling is impossible, people do not get to know each other, the total sum disappears if not split on the first attempt, and the game plays just once, are helpful to uncover the fundamental principles governing human’s decision-making mechanisms2. In most studies on UG experiments undertaken in typical Western-type civilisations, the majority of proposers offer 40% to 50% of the total sum, and about half of all responders reject offers below 20%28910111213141516. While the former is far from what rational analysis would dictate for selfish players, the latter has often been attributed to negative feelings toward perceived inequity4. In marked contrast to general reports, the findings from 15 small-scale societies across 4 continents show sizable variations in the offer. For example, the mean offer within the Machiguenga tribe in the Amazon was only 26%, but many members of the Au tribe in Papua New Guinea offered more than 50% although the Au tended to reject offers either excessively generous or miserly. Despite these variations, most people worldwide reveal a high value on fair outcomes25. Rejecting low offers is exorbitant, and whether behaviour changes along with all stake levels is an inescapable question. It reports that stakes do not matter while low offers up to 10% to 20% have rarely been observed2627. In contrast, some evidence shows that sufficiently high stakes lead responder behaviour to converge toward full acceptance of low offers even without learning when stakes calibration have been treated beforehand28. Various elements have been added to UG to suit for numerous situations so as to explore the causes of the emotional behaviour inconsistency thus elicited. For instance, in the cases where the competition for being a proposer is intense, inequity can be justified, or in other words, people get to know each other, which then lowers the amount of routine offers thus getting accepted much easier229. Nonetheless, these outcomes are far from what rational analysis would dictate for Homo economicus if only offers do not converge toward zero. On the other hand, rejecting a dismal offer involves an immediate cost, which may be offset by gains in future encounters from reputation acquired through an internal device, self-esteem. A repeated UG shows that fairness can evolve intra-generationally if associated with reputation7. One of the modified UG experiments reports that neither the apes nor the 3~5-year-old human children consistently refused offers, but behavioural protest did occur1. It suggests that decision making in a socioemotional context relates to cognitive or affective processes. Research findings demonstrate that the influence of emotion on decision making deepens upon age30. This makes UG particularly valuable for assessing age differences in financial decision making, since emotion has its value over the share in a repeated game. Experimental results reveal that older adults divided the money more generously than young adults whom rejected more unfair offers proposed by young adults compared to older adults. Moreover, both participating age groups reported to be displeased at unfair offers proposed by young adults compared to receiving the same offer from an older adult31. As well, prosocial sentiments may be evident in the decisions of older responders, due to the previous noted self-serving motivation while accepting an unfair offer and the increasing recognition in age concerning the social goals of fairness and generosity32. The findings from various variants of UG experiments suggest that real people are a complicated hybrid species of Homo economicus and Homo emoticus. The major challenge is to theorize how Darwinian evolution would produce creatures with the proclivity of Darwinian generosity. One class of experiments that comes close to UG is the dictator game. In one set of the experiment, dictators gave 1/3 of the total sum to the paired anonymous student17. Similarly, in “gangster” experiments, the gangster students took away “only” 3/4 of the total sum3334. These findings inspire us to look to the potential link between social and genetic inheritances. Among the three classes of experiments, both the dictator game and the gangster game did not require cooperation between two randomly paired individuals. In the sort of UG, however, this cooperation is necessary to materialize the total sum. Therefore, insights drawing from UG experiments are valuable as far as the evolution of the human response to unfairness is concerned. The sense of fairness is by itself a reflection of cognition. Recently, neuroscientists have attempted to unravel neural genes in the areas of the brain implicated with cognition. Current studies can only verify a handful of neural genes, all of which relating to behaviours more at an elementary level, not mentioning more abstract or advanced cognition. If the sense of fairness is not innate, then it can only be acquired from social inheritances. In this case, fairness-related genes should be overlooked since social cultural environment is partly extrasomatic. However, if the sense of fairness is innate, one would wonder how fairness-related genes will evolve. Will they converge over infinite gene-culture coevolution? Because the identification of fairness-related genes escapes measurement, it is difficult to conduct empirical tests that distinguish among various arguments. Hence, simulation experiments are conducive to demonstrate the evolution of fairness-related genes in the context of various patterns of gene-culture interactions. Our controlled simulation experiments are carried out in an imaginary isolated island with a constant environment carrying a capacity of N individuals of each generation. Assume that N is evenly split between the male and female gender, and the costs of help and reciprocal exchange are identical among kin versus nonkin, so that there are no differences between reciprocal altruism and kinship in terms of the path to cooperation. The life of each individual must go through the stages of birth, preying, reproduction, and death. When an ovum meets a sperm, two strands of genes will crossover normally or mutate with a low probability to determine the unique phenotype of the fertilized ovum, which can be considered as an observable behavioural mode. In the second stage, an individual preys either alone or cooperatively with others. In the third stage, individuals with higher degree of fitness will have more offspring than others thus forming a dominant group in the population in the long run. During the hunting period, each individual goes out as predators to find prey for M times totally. For each time’s outing for preying, an individual can realise a certain constant payoff, π0 > 0, if hunting singly. To cooperate with someone is the other alternative. Assume that individuals seeking for cooperation are repeatedly randomly matched in pairs. Assume further that the probability an individual is matched with the same opponent more than once is negligible, and it is not necessary for an individual to establish reputation or to give up an immediate benefit to stabilize a long-term valuable cooperative relationship. Suppose that perfect cooperation in the absence of IA will bring with the total net reward of π1 to be divided among participants. Without loss of generality, cooperation among three or more individuals are excluded, assume that π1 > 2π0 holds true to allow for positive net gain from perfect cooperation. All individuals are assumed to make less optimal decisions and are programmed with a mixed behavioural mode, which is not considered as a conscious choice. As a result, an individual sometimes cooperates with someone to hunt, instead of preying alone constantly. To operate on this idea, assume that there are m times, m ≤ M, an individual will look for cooperation opportunities while capable of hunting. The tendency how m evolves across generations, t, becomes critical in justifying the argument that the sense of fairness relates to cooperation. For each generation, an individual i is assumed to be reproduced by random mating. The genotypes of i’s fairness-related genes are denoted by (Bi, Γi, Θi), with each operator in parentheses representing the genotypes of the sense of fairness, the IA1-discount factor, and genetic IA2 respectively. Unless otherwise noted, each genotype is a binary string of length 4. The phenotypes of Bi and Γi, denoted as bi and γi, are simply the products of three genetic operators: reproduction, crossovers, and mutations. In addition, the phenotype of Θi, denoted as θi, is the product of gene-culture interaction. Denote the parameter α ∈ [0, 1] as the degree of social manipulation. The bijection from a gene-culture profile to the profile of phenotypes is set as (bi, γi, θi) = (Bi × Φ, Γi × Φ, λ α + (1 − λ)Θi × Φ), where bi, γi, θi, α ∈ [0, 1], λ ∈ {0, 1}, and Φ = (20, 21, 22, 23)T/(24 − 1). Since the human sense of fairness is the focal point, only bi is termed as the phenotype hereafter, which is further classified into five categories: pure altruism (bi = 0), strong sense of fairness (0 < bi < 0.5), perfect sense of fairness (bi = 0.5), weak sense of fairness (0.5 < bi < 1), and pure egoism (bi = 1). The Methods section will detail the connections among the profile of (bi, γi, θi), the magnitude and the division of total payoffs, each individual’s lifetime payoffs, as well as the realised genotype of the next generation. The following summarizes only the elements with direct bearings on the experiments undertaken. Let βi = bi/(bi + bj) and βj = 1 − βi. Denote Πi as individual i’s payoff in each random encounter with j, which equals [βi − θi(βi − βj)/2] γjπ1 if bi + bj ≤ 1 and bi > bj both hold; [βi + θj(βj − βi)/2] γiπ1 if bi + bj ≤ 1 and bi < bj both hold; 0.5 π1 if bi = bj = 0.5 holds; π0 if otherwise, for all i ≠ j, i, j = 1, ..., N. Thus, the lifetime payoffs of individual i of the tth generation can then be calculated, denoted as Assume that the ability to transmit one’s own genotypes is proportional to lifetime payoffs. Given N, the probability a priori of any individual i of the tth generation transmitting her (his) own genotypes to the next generation can be determined, denoted as Pi,t+1 =  It helps determine the realised genotypes of the next generation through the operators of genetic reproduction, crossover, or mutation. Let x ∈ [0, 1] and y ∈ [0, 1] be the probabilities of crossover and mutation for each element of the inherited genes respectively. Six controlled experiments of gene-culture algorithm simulations up to 10,000 generations are conducted, either with or without the social manipulation of IA2 to explore how the sense of fairness embedded in the phenotype evolves through genes alone or within gene-culture interactions. The first two experiments do not involve IA, aiming to examine whether the distribution of the phenotype is sensitive to changes in the prospect of cooperation upon convergence. The other four experiments are linked to IA1 or IA2 in various aspects, either with or without social manipulation of IA2, aiming to evaluate potential influences that different degrees of social manipulation of IA2 may bring about on the phenotype upon convergence. Note also that Bi is extended to a binary string of a length of 8 to allow for more variants within population in the experiments where IA is absent or genetic IA2 is overshadowed by social manipulations. Results All experiments have the common set of parameters: π0 = 0.01, π1 = 1, N = 1,000, M = 100, x = 0.5, and y = 0.01. To capture stakes effect, π1 is set at the value 100 times of π0. As well, m = t/100 except in the second experiment where m = max {100 − t, 0}. Two experiments without IA The first experiment simulates the evolution of the phenotype in the absence of IA while the number of cooperation opportunities is increasing over time. Assume that the phenotype starts from the mass range of [0.9, 1], corresponding to nearly pure egoism. As a result, the phenotype demonstrates a tendency to converge towards the perfect sense of fairness, see Fig. 1. The second experiment simulates the evolution of the phenotype without IA while the amount of cooperation opportunities is non-increasing over time. The initial distribution of the phenotype is reproduced from Panel (d) of Fig. 1. Figure 2 shows the results, suggesting that the phenotype is degenerating gradually. The results of the first two experiments suggest that the phenotype demonstrates a tendency of converging towards the perfect sense of fairness without IA while the prospect of cooperation is increasing over time, but degenerating towards even distribution while the prospect of cooperation is decreasing. An experiment without IA2 The third experiment simulates the evolution of the phenotype in the absence of IA2 while the number of cooperation opportunities is increasing over time. Assume that the phenotype and γ both start from the mass range of [0.9, 1]. The latter corresponds to very low levels of IA1. Figure 3 shows the results. The results show that the phenotype evolves towards the perfect sense of fairness. With endogenous IA1, it is interesting to see how γ evolves though not figured. It starts from the mass range of [0.9, 1]. At t = 100, it has scattered unevenly across the whole range. At t = 1,000, its distribution has been skewing left, over 60% of population falling on [0.7, 1] within which half population fall on [0.9, 1]. This pattern persists at t = 10,000. Thus far, the results show that the phenotype converges towards the perfect sense of fairness without IA2, regardless of whether IA1 is present or not. Second, the left-skewness in the distribution of γ upon the convergence of the phenotype suggests that individuals with higher degrees of IA1 will gradually lose their fitness in the long term. An experiment with genetic IA2 The fourth experiment simulates the evolution of the phenotype with genetic IA2 while the number of cooperation opportunities is increasing over time. It corresponds to the case where λ = 0 so that the degree of IA2 is completely dominated by genetics. Assume that both the phenotype and γ fall on [0.9, 1] while θ falls on [0, 0.1] initially, the latter of which corresponds to low levels of IA2. The simulation results are shown in Fig. 4. As Fig. 4 shows, in the context where IA2 is dominated by genetics, the phenotype converges towards the perfect sense of fairness when the prospect of cooperation is increasing over time. Where γ is concerned, it evolves from the mass range of [0.9, 1] towards an even distribution. From t = 0 to t = 100, it spreads out unevenly, but slightly skewed left, with the mode falling on [0.9, 1], accounting for just over 30% of population. At t = 1,000, it becomes less skewed, nearly 80% of population are evenly distributed on [0.5, 0.6] and [0.7, 1]. At t = 10,000, it is more evenly distributed. Where θ is concerned, it evolves from the mass range of [0, 0.1] to right skewness. At t = 100, it has scattered unevenly across the whole range, slightly left skewed. At t = 1,000, it forms a bimodal distribution with two modes falling on [0, 0.1] and [0.5, 0.6]. At t = 10,000, it is skewed right with the mode falling on [0, 0.1], accounting for nearly 25% of the population. As well, less than 30% of the population fall on [0.6, 1]. These observations suggest that γ and θ are not mutually independent, even if a long-term valuable cooperative relationship does not exist between two partners. This implication is consistent with the hypothesis that IA2 requires anticipation of IA1 in the partner and its negative impact on the relationship1. Second, the distribution of θ is more skewed right when γ is more evenly distributed. To be precise, the degree of IA2 is converging towards [0, 0.1] when γ is more evenly distributed over the whole range. It supports, at least partially, the argument that sufficiently high stakes lead responder behaviour to converge towards full acceptance of low offers, even in the absence of learning28. Otherwise, θ would not converge towards [0, 0.1]. Thirdly, the results constitute a sharp contrast to the general observations from most studies on UG experiments where the majority of proposers offer 40% to 50% of the total sum, corresponding to θ’s range of [0.8, 1]. This contrast suggests that the human IA2 may be substantially influenced by social manipulation, instead of genetics alone. An experiment with cultural IA2 = 2/3 The fifth experiment examines the evolutionary pattern of the phenotype in the context of social manipulation dominance of IA2 given by θi = θj = 2/3. Under this setting, the disadvantaged partner will receive 1/3 to 1/2 of the total sum when both bi + bj ≤ 1 and bi ≠ bj hold. This setting is consonant with many experimental studies on UG24121314151617181929. Hence, the results will be highly illuminative in exploring why people redistribute voluntarily. Assume that both the phenotype andγ fall on [0.9, 1] initially. The simulation results are shown in Fig. 5. With θ = 2/3, the phenotype converges towards the mass range of [0.4, 0.5], suggesting that people redistribute voluntarily to satisfy fairness norms, the perfect sense of fairness35. Where γ is concerned, it demonstrates the tendency of convergence towards the right end, the lowest level of IA1. At t = 100, it scatters unevenly across the whole range. At t = 1,000, nearly 40% (80%) of population fall on the range of [0.9, 1] ([0.7, 1]). The pattern has been persisting ever since. In contrast to the fourth experiment where γ is distributed more or less uniformly at t = 10,000, this result suggests that holding θ at 2/3 can effectively constrain the variation of IA1, thus increase the size of benefits from cooperation in the long term. The larger is the degree of social manipulation, the faster IA1 (γ) is converging towards zero (unity). An experiment with cultural IA2 = 1 The final experiment examines the evolution of the phenotype in the context of the perfect social manipulation dominance of IA2, θi = θj = 1. Nash proposed axioms which implies that the right way to divide the pie is the allocation that maximizes the product of the differences from the status quo subject to the feasibility constraint36. Consider a society where Nash’s axioms serve as a guiding principle or an ethical code of conduct in the division of the total sum. The outcome of Nash bargaining equilibrium indeed corresponds to θi = θj = 1 in our setting, since the profile,(π0, π0), can be viewed as the status quo. Hence, the experimental simulation given θi = θj = 1 corresponds to one of the modified versions of Nash’s bargaining problem. Assume that the phenotype falls on [0.9, 1] initially. Figure 6 shows the simulation results. As Fig. 6 shows, the phenotype converges towards pure altruism under the perfect social manipulation dominance of IA2. This observation is in sharp contrast to those obtained under genetic dominance of IA2 or cultural dominance of IA2 = 2/3, suggesting that there exists a threshold of cultural IA2, beyond which the phenotype will not converge towards the perfect sense of fairness anymore. Instead, it is altruism which would prevail. Where γ is concerned, it converges towards low degree of IA1. At t = 100, it scatters unevenly across the whole range. At t = 1,000, over 70% (90%) of population fall on the range of [0.9, 1] ([0.7, 1]). This pattern of distribution has been persisting ever since. Our results demonstrate that, in a society following Nash’s axioms in the division of the total sum, the phenotype will converge towards pure altruism, while IA1 will converge towards the low end when the prospect of cooperation is increasing over time. The tendencies of convergence towards pure altruism (or strong sense of fairness) and low degrees of IA1 will increase not only the probability a prior of a successful cooperation between two actors at each encounter, but also the expected benefit from cooperation. Summary and Discussion with Comments We target a problem, the origin of human sense of fairness, and suggest a model in which phenotype will gradually converge towards the perfect sense of fairness along with the prospect of cooperation. Once the prospect of cooperation stops increasing, the sense of fairness will degenerate gradually, but it is never extinct. To some extent, the findings can justify partially the hypothesis that the human response to unfairness evolved for the sake of supporting long-term cooperation involving intra-generational cooperation and cooperation passing on the generation both11. In the environment where social manipulation of Darwinian generosity overshadows genetics, the sense of fairness could be acute to the degree of social manipulation. This is because that the higher this degree, the higher the probability a prior of a successful cooperation and the larger the expected benefit from cooperation will prevail, and consequently, the higher fitness will result. Furthermore, there may exist a threshold in the degree of social manipulation of Darwinian generosity, beyond which the phenotype will converge towards altruism rather than the perfect sense of fairness. However, the evidences presented here are not convincingly supporting the above remarks if viewed from a broader perspective. Above all, the current setting is far from the reality since any topology of gene manipulation is not well mixed. Meanwhile, albeit the time course could be familiar for human societies, there is a relevant shortage of the present model. Namely, it assumes random partnership, which is just a narrow sense of cooperative relationships. As far as the gene-culture approach is concerned, in retrospect, recent development in this topic will certainly shed light on the following three new directions toward more realistic situations. The first direction associates with the implications of the choice of discrete or continuous sets of phenotypes (or strategies). Where fairness is concerned, theoretical works mainly focus on the division strategy of UG73738. Along with the shift in the focus to discrete or continuous sets of strategies, it shows that discrete set of strategies could lead to rich dynamical behaviours in the spatial UG39, followed by the finding that fine-grained strategy intervals promote the evolution of fairness40. To be precise, for the whole set of N2 coarse-grained strategies where N is a small natural number, the two strategies coexistent in the stationary state are always the two most rational strategies with the lowest possible acceptance level. As N becomes larger, the dominant strategy, by contrast, is both fair and empathetic. Secondly, where the types of players and spatiality both are considered simultaneously, the scenario of the evolution of fairness becomes much more complicated. Within the context of either empathetic, pragmatic or independent players, in terms of the roles as the proposal or the respondent, compounded further by different topologies of either a homogeneous number of neighbors or scale-free networks, and selection rules of either natural selection or social penalty in the form of collateral punishment up to the first neighbors of the less fit players, the rejection of low offers arises in the context of natural selection regardless of the underlying topology. In the context of social punishment, however, the dynamical behaviour of the system changes radically due to the fact that the players have to consider the fitness of their neighbors in addition to their own benefit. It shows that players can adapt their offers and acceptance thresholds independently. Moreover, the dynamical equilibria of both typologies converge to the setting of pragmatic players, the framework where full altruistic behaviour is observed. Notwithstanding, it should be emphasised that the abundance of highly generous individuals observed when social penalty is at work arises from a purely scale-free effect combined with a social enforcement of altruism41. Experimentally, similar findings out of data collecting from nearly 200 dictators across various treatments suggest that agents do not ubiquitously choose the most selfish outcome in dictator games, implying institutions do matter substantially in reality42. And lastly but most importantly, pairwise social interactions have dominated the interpretation of many biological data, though far from reality, above all in the public goods game with many players. When many players are involved, decision-making becomes more complicated for the potential increase in the number of equilibria. Group interactions can hardly be treated as the corresponding sum of pairwise interactions. As a consequence, the public goods game with many players would probably be well interpreted in terms of group interactions for their inherent irreducibility43. Indeed, this perspective has been applied to study the emergence of fairness in repeated group interactions, in which individuals engage in an iterated N-person prisoner’s dilemma44. Recently, the synergy between statistical physics, network science and evolutionary game theory has made considerable advances in the study of evolutionary dynamics of group interactions on top of structured populations, including lattices, complex networks (involving social heterogeneity, bipartite graphs, hierarchical social structure, and populations of mobile agents), and coevolutionary models4546474849. As a matter of fact, it has been reviewed that the effect of spatiality could play a decisive role in general on the evolution of fairness in group interactions on structured populations49. The current framework can be extended accordingly to examine gene-culture coevolution wherein migration in combination with within-group selection against altruists is a much stronger force than selection between groups. Hopefully, it will probably stimulate the interest of another scientific community. Methods Bargaining over a prey may involve issues of haggling, information, game structure, reputation, and trust in cooperation process365051525354. Additionally, even if an agreement a priori were made, one would suspect how the deal goes ahead in the absence of explicit contracts and regulatory institutions. It is plausible that an altruistic individual is likely to be sanctioned by her selfish partner, and consequently resulting in detrimental effects on the cooperation itself. These negative effects have been overlooked by the prevailing self-interest approach for long. Indeed, whether trust will emerge from individuals paired by a random encounter is not only a fundamental problem in the behavioural sciences, but also reliant on the degree of fairness-based altruism. The trust game, which assesses the amount one player invests with another in order to potentially increase total investment income with default risk, has been considered as an appropriate experimental candidate to find the properties of trust. In one class of the trust game experiments, players have revealed the preference of placing trust in members of their own age group35. Other studies also confirm that in-group members are evaluated more favorably than out-group members55. These research findings suggest that trust discrimination exists at least on the grounds of group. An experimental study which attempts to capture the relationship among trust, sanctions, and altruistic cooperation demonstrates that fairness-based altruism matters for human cooperation3. In light of the above discussion, we believe that fairness-based altruism is a powerful source of human cooperation, and should be reflected in our modelling. We follow Nash’s two-person cooperative game for simplicity36. Assume that both players simultaneously formulate their demands before action, say bi, bj ∈ [0, 1]. If (bi, bj) is feasible, each player at least gets what he demanded. Specifically, we assume that the constraint set is binding, such that the share player i gets, βi, is proportional to what he demanded, i.e., βi = bi/(bi + bj). If it is infeasible, they both will prey alone in the end for that specific encounter. Suppose that each individual is programmed to follow a certain mode of behaviour in formulating his demand. Denote bi,t as the share formulated by individual i of the tth generation, which is considered as a phenotype serving as a measure of the human sense of fairness. Suppress the subscript t temporarily for brevity. Let di ∈ [0, 1] be individual i’s degree of IA1, which can be interpreted as a measure of sanctions against revealed selfish or greedy intentions of the opponent, and is detrimental to altruistic cooperation if di > 0. Thus, fairness-based altruism is linked to human cooperation. Define γi ≡ 1 − di as the IA1-discount factor, and θi ∈ [0, 1] as the degree of IA2. Assume that (bi, γi) is solely determined by individual i’s genes, (Bi, Γi) where Bi and Γi are all binary strings of length 4. In the case where IA is absent, Bi is extended to a binary string of length 8 to allow for more variants within population. The condition, bi + bj ≤ 1, is the prerequisite that two individuals agree to hunt cooperatively. Each individual does not know the true value of γ of her partner before action. The IA1-discount factor of the disadvantaged actor, either γi or γj, will be triggered during the process of cooperation, and thus causes negative reactions to inequity to the detriment of the actor. Assume that the total net reward is deflated by the IA1-discount factor of the disadvantaged actor. Where θi is concerned, it matters only on occasions of inequity benefiting one individual or overcompensation. The fact that IA2 has only been observed in chimpanzees and humans suggests that IA2 requires more advanced cognition and emotional control than IA1 does. Social learning or culture (social manipulation) may be of substantial importance in the determination of θi. Assume that θi is determined by the interplay of two inheritance systems: genetics and social manipulation6. The former is a bijection from Θi, a binary string of length 4, while the latter, summarized by the social manipulation index, α ∈ [0, 1], reflects social norms regulating a portion of overcompensation to be transferred from the advantaged actor to the disadvantaged one. Conceptually, α mirrors social order3 or a measure of evolution of ideas, wisdom devices, or memes, the latter of which refers to behaviours and ideas copied from person to person by imitation56. Assume that the value of α is common knowledge, but the IA2-related genetic inheritance index is a private information before one-shot partnering relationship ends. For simplicity, assume that the interplay between both inheritance systems has only two potential outcomes, dominated by either genetics or social manipulation. When both conditions, bi + bj ≤ 1 and bi ≠ bj, meet, either θi or θj will initiate. Once initiate, the advantaged actor will make non-negative transfers perceived as fair by herself or her society to her opponent. Assume that, wherever applicable, the larger θi or θj is, the larger is the portion of overcompensation to be transferred without reducing the total net reward. The bijection from gene-culture to phenotypes is expressed as (bi, γi, θi) = (Bi × Φ, Γi × Φ, λ α + (1 − λ) Θi × Φ), where bi, γi, θi, α ∈ [0, 1], λ ∈ {0, 1}, and Φ =  (20, 21, 22, 23)T/(24 − 1). It is clear that λ is a dummy variable. In case where social manipulation dominates, λ = 1 and θi = α. Otherwise, it will be determined by genetics. Denote Πi as individual i’s payoff in each random encounter with j. Then, Πi will equal [βi − θi(βi − βj)/2] γjπ1 if bi + bj ≤ 1 and bi > bj hold, or [βi + θj(βj − βi)/2] γiπ1 if bi + bj ≤ 1 and bi < bj hold, or 0.5 π1 if bi = bj = 0.5 holds, or π0 if otherwise, for all i ≠ j, i, j = 1, ..., N. Given the setting, the number of successful cooperation during a lifetime is endogenous while subject to perturbations. Assume that the time discount factor is unity. Thus, the lifetime payoffs of individual i of the tth generation, denoted as will equal At the third stage of each generation, all individuals begin to breed. Assume that the ability to transmit one’s own genotype is proportional to his own lifetime payoffs. As a result, given N, the probability a priori of any individual i of the tth generation transmitting her (his) own genotype to the next generation can be calculated, denoted as Pi,t+1, i.e. Denote (Bi,t, Γi,t, Θi,t) as the reproduced genes of individual i of the tth generation, a binary string of length 12. After all of the N reproduced genes have been generated across individuals, they randomly match in pairs which would give births to the realised genes of next generation, (Bi,t+1, Γi,t+1, Θi,t+1). Using the standard doctrine in evolutionary biology, assume that the realised genes come from two sources: genetic inheritance with high probability as well as mutation with low but positive probability. For each individual fertilized ovum, its inherited genes will have its origin from either maternal side or paternal side, or both. The former two cases occur through the genetic operator of reproduction, while the later occurs through the operator of crossover. Assume that the probability of crossover for each element of the inherited genes is x, x ∈ [0, 1]. Assume further that, for each element of the inherited genes, there is a probability of mutation, y ∈ [0, 1]. Therefore, each realised gene has to go through all the operators to materialize. It is necessary to clarify at the outset that our simulations might be inconsistent with the evolutionarily stable strategy (ESS) in the short term. Stability does not necessarily coincide with the ESS or (in some cases) any of the ESS when the dynamical system is subjected to small but non-vanishing perturbations57. Thus, the concept of stochastic stability will be useful in considering the meaning of convergence across generations, a concept this study has heavily relied upon. Additional Information How to cite this article: Liu, T.-G. and Lu, Y. Gene–culture interaction and the evolution of the human sense of fairness. Sci. Rep. 6, 32483; doi: 10.1038/srep32483 (2016). Supplementary Material Supplementary Information The authors are grateful to Prof Sheng Hua (Wuhan University), Feny Chinghui Chen (National Central University), and Hsiao-Pu Chen (Universität Hamburg) for helpful discussions and assistance. Author Contributions T.-G.L. and Y.L. planned the study and performed the data analysis. T.-G.L. conducted the Methods section and Y.L. wrote the computing programs. T.-G.L. and Y.L. contributed to the research. T.-G.L. contributed to writing the paper. Figure 1 The phenotype evolves towards the perfect sense of fairness without inequity aversion while the amount of cooperation opportunities is increasing over time. It starts from the mass range of [0.9, 1], corresponding to nearly pure egoism, Panel (a). At t = 100, Panel (b), it spreads out more or less evenly. At t = 1,000, Panel (c), over 80% of population fall on the range of [0.4, 0.5]. At t = 10,000, Panel (d), it converges to the mass range of [0.4, 0.5], 90% of total population. Figure 2 The phenotype becomes more evenly distributed without inequity aversion while the amount of cooperation opportunities is non-increasing over time. Panel (a) reproduces Panel (d) of Fig. 1. At t = 100, when there have been not any opportunities of cooperation for the first time, the perfect sense of fairness still dominates, over 70% of population falling on [0.4, 0.5], Panel (b). This is because that cooperation opportunities have been a scarce good for 100 generations. At t = 200, Panel (c), the phenotype spreads out, but is more concentrated on the left. At t = 1,000, Panel (d), it becomes more evenly distributed. Figure 3 The phenotype evolves towards the perfect sense of fairness without the second degree inequity aversion while the amount of cooperation opportunities is increasing over time. It starts from the mass range of [0.9, 1], Panel (a), corresponding to nearly pure egoism. At t = 100, it has scattered unevenly across the whole range, Panel (b). At t = 1,000, Panel (c), over 80% of population concentrate on [0.4, 0.5]. It converges towards the mass range of [0.4, 0.5] at t = 10,000, accounting for over 90% of population, Panel (d). Figure 4 Assume that both the phenotype and IA1 discount factor fall on [0.9, 1], and IA2 falls on [0, 0.1] initially. The phenotype evolves towards the perfect sense of fairness while the amount of cooperation opportunities is increasing over time. It starts from the mass range of [0.9, 1], Panel (a). At t = 100, it has scattered across the whole range, Panel (b). At t = 1,000, Panel (c), it is highly concentrated on [0.4, 0.5], over 80% of population. It converges towards [0.4, 0.5] at t = 10,000, 90% of population, Panel (d). Figure 5 The phenotype converges towards the perfect sense of fairness when the second degree of inequity aversion is set at 2/3 while the amount of cooperation opportunities is increasing over time. The phenotype distributes evenly within [0.9, 1] at t = 0, Panel (a). It scatters unevenly across the whole range at t = 100, Panel (b). At t = 1,000, nearly 80% of population fall on [04, 0.5], Panel (c). At t = 10,000, nearly 90% of population fall on the mass range of [0.4, 0.5], Panel (d). Figure 6 The phenotype demonstrates the tendency of convergence towards pure altruism under the perfect social manipulation dominance of the second degree inequity aversion while the amount of cooperation opportunities is increasing over time. The phenotype is evenly distributed within [0.9, 1] at t = 0, Panel (a). It scatters unevenly across the whole range at t = 100, Panel (b). At t = 1,000, over 50% (80%) of population fall on [0, 0.1] ([0, 0.3]), Panel (c). Its distribution is more skewed right at t = 10,000, over 60% (nearly 90%) of population falling on the mass range of [0, 0.1] ([0, 0.3]), Panel (d). ==== Refs Brosnan S. F. & de Waal F. B. Evolution of responses to (un)fairness . Science 346 , 1251776 (2014 ).25324394 Sigmund K. , Fehr E. & Nowak M. A. The economics of fair play . Sci. Am. 286 , 82 –87 (2002 ).11799620 Fehr E. & Rockenbach B. Detrimental effects of sanctions on human altruism . Nature 422 , 137 –140 (2003 ).12634778 Sanfey A. G. Social decision-making: insights from game theory and neuroscience . Science 318 , 598 –602 (2007 ).17962552 Fehr E. & Fischbacher U. The nature of human altruism . Nature 425 , 785 –791 (2003 ).14574401 Aoki M. A condition for group selection to prevail over counteracting individual selection . Evolution 36 , 832 –842 (1982 ). Nowak M. A. , Page K. M. & Sigmund K. Fairness versus reason in the ultimatum game . Science 289 , 1773 –1775 (2000 ).10976075 Fehr E. & Schmidt K. M. A theory of fairness, competition, and cooperation . Q. J. Econ. 114 , 817 –868 (1999 ). Güth W. , Schmittberger R. & Schwarze B. An experimental analysis of ultimatum bargaining . J. Econ. Behav. Organ. 3 , 367 –388 (1982 ). Thaler R. H. Anomalies: the ultimatum game . J. Econ. Perspect. 2 , 195 –206 (1988 ). Güth W. & Tietze R. Ultimatum bargaining behavior: a survey and comparison of experimental results . J. Econ. Psychol. 11 , 417 –449 (1990 ). Fehr E. & Gächter S. Homo Reciprocans and Human Cooperation (Working Paper, Institute for Empirical Economic Research, Univ. Zurich, 1999 ). Bolton G. E. & Zwick R. Anonymity versus punishment in ultimatum bargaining . Game Econ. Behav. 10 , 95 –121 (1995 ). Roth A. E. In Handbook of Experimental Economics (eds Kagel J. H. & Roth A. E. ) 253 –348 (Princeton Univ. Press, Princeton, 1995 ). Roth A. E. , Prasnikar V. , Okuno-Fujiwara M. & Zamir S. Bargaining and market behavior in Jerusalem, Ljubljana, Pittsburgh and Tokyo: an experimental study . Am. Econ. Rev. 81 , 1068 –1095 (1991 ). Camerer C. F. Behavioral Game Theory: Experiments in Strategic Interaction (Princeton Univ. Press, Princeton, 2003 ). Eichenberger R. & Oberholzer-Gee F. Rational moralists: The role of fairness in democratic economic politics . Public Choice 94 , 191 –210 (1998 ). Mueller D. C. Public Choice III (Cambridge Univ. Press, New York, 2003 ). Binmore K. The Origins of Fair Play: Papers on Economics & Evolution (No. 614, Max Planck Inst. of Economics, MPI Jena, 2006 ). Loewenstein G. F. , Thompson L. & Bazerman M. H. Social utility and decision making in interpersonal contexts . J. Pers. Soc. Psychol. 57 , 426 –441 (1989 ). Blake P. R. & McAuliffe K. I had so much it didn’t seem fair: eight-year-olds reject two forms of inequity . Cognition 120 , 215 –224 (2011 ).21616483 Dugatkin L. A. Cooperation among Animals: An Evolutionary Perspective (Oxford Univ. Press, New York, 1997 ). Cavalli-Sforza L. L. & Feldman M. W. Cultural Transmission and Evolution: A Quantitative Approach (Princeton Univ. Press, Princeton, 1981 ). Flinn M. V. Culture and the evolution of social learning . Evol. Hum. Behav. 18 , 23 –67 (1997 ). Henrich J. . In search of Homo economicus: Behavioral experiments in 15 small-scale societies . Am. Econ. Rev. 91 , 73 –78 (2001 ). Cameron L. A. Raising the stakes in the ultimatum game: Experimental evidence from Indonesia . Econ. Inq. 37 , 47 –59 (1999 ). Slonim R. & Roth A. E. Learning in high stakes ultimatum games: An experiment in the Slovak Republic . Econometrica 66 , 569 –596 (1998 ). Andersen S. , Ertaç S. , Gneezy U. , Hoffman M. & List J. A. 2011 . Stakes matter in ultimatum games . Am. Econ. Rev. 101 , 3427 –3439 (2011 ). Levitt S. D. & Dubner S. J. SuperFreakonomics: Global Cooling, Patriotic Prostitutes, and Why Suicide Bombers Should Buy Life Insurance (William Morrow Publisher, New York, 2009 ). Weierich M. R. . Older and wiser? An affective science perspective on age-related challenges in financial decision making . Soc. Cogn. Affect. Neurosci. 6 , 195 –206 (2011 ).20587596 Bailey P. E. , Ruffman T. & Rendell P. G. Age-related differences in social economic decision making: The ultimatum game.” J. Gerontol. B. Psychol. Sci. Soc. Sci. 68 , 356 –363 (2013 ).22929390 Kirman A. & Teschl M. Selfish or selfless? The role of empathy in economics . Philos. Trans. R. Soc. Lond. B. Biol. Sci. 365 , 303 –317 (2010 ).20026468 Kahneman D. , Knetsch J. L. & Thaler R. H. Fairness and the assumptions of economics . J. Bus. 59 , S285 –300 (1986 ). Davis D. D. & Holt C. A. Experimental Economics (Princeton Univ. Press, Princeton, 1993 ). Holm H. & Nystedt P. Intra-generational trust - A semi-experimental study of trust among different generations . J. Econ. Behav. Organ. 58 , 403 –419 (2005 ). Nash J. F. Jr. Two-person cooperative game . Econometrica 21 , 128 –140 (1953 ). Page K. M. & Nowak M. A. A generalized adaptive dynamics framework can describe the evolutionary ultimatum game . J. Theor. Biol. 209 , 173 –179 (2001 ).11401459 Dishon-Berkovits M. & Berkovits R. The ultimatum game: discrete vs. continuous offers . Physica A 409 , 53 –60 (2014 ). Szolnoki A. , Perc M. & Szabó G. Defense mechanisms of empathetic players in the spatial ultimatum game . Phys. Rev. Lett. 109 , 078701 (2012 ).23006406 Szolnoki A. , Perc M. & Szabó G. Accuracy in strategy imitations promotes the evolution of fairness in the spatial ultimatum game . Europhys. Lett. 100 , 28005 (2012 ). Sinatra R. . The Ultimatum Game in complex networks . J. Stat. Mech. 9 , P09012 (2009 ). List J. On the interpretation of giving in dictator games . J. Polit. Econ. 3 , 482 –493 (2007 ). Archetti M. & Scheuring I. Review: game theory of public goods in one-shot social dilemmas without assortment . J. Theor. Biol. 299 , 9 –20 (2012 ).21723299 Van Segbroeck S. , Pacheco J. M. , Lenaerts T. & Santos F. C. Emergence of fairness in repeated group interactions . Phys. Rev. Lett. 108 , 158104 (2012 ).22587290 Perc M. , Gómez-Gardeñes J. , Szolnoki A. , Floría L. M. & Moreno Y. Evolutionary dynamics of group interactions on structured populations: a review . J. R. Soc. Interface 10 , 20120997 (2013 ).23303223 Xia C. , Meloni S. , Perc M. & Moreno Y. Dynamic instability of cooperation due to diverse activity patterns in evolutionary social dilemmas . Europhys. Lett. 109 , 58002 (2015 ). Xia C. , Meng X. & Wang Z. Heterogeneous coupling between interdependent lattices promotes the cooperation in the prisoner’s dilemma game . PLoS ONE 10 , e0129542 (2015 ).26102082 Xia C. , Miao Q. , Wang J. & Ding S. Evolution of cooperation in the traveler’s dilemma game on two coupled lattices . Appl. Math. Comput. 246 , 389 –398 (2014 ). Perc M. & Szolnoki A. Coevolutionary games - a mini review . BioSystems 99 , 109 –125 (2010 ).19837129 Nash J. F. Jr. The bargaining problem . Econometrica 18 , 155 –162 (1950 ). Rubinstein A. Perfect equilibrium in a bargaining model . Econometrica 50 , 97 –109 (1982 ). Ochs J. & Roth A. E. An experimental study of sequential bargaining . Am. Econ. Rev. 79 , 355 –384 (1989 ). Osborne M. J. & Rubinstein A. Bargaining and Markets (Academic Press, San Diego, 1990 ). Park E.-S. Reputation effects in bargaining games . Southern Econ. J. 66 , 186 –192 (1999 ). Brewer M. B. In-group bias in the minimal intergroup situation: A cognitive-motivational analysis . Psychol. Bull. 86 , 307 –324 (1979 ). Blackmore S. The power of memes . Sci. Am. 283 , 52 –61 (2000 ).11103459 Foster D. & Young P. Stochastic evolutionary game dynamics . Theor. Popul. Biol. 38 , 19 –32 (1990 ).

PMC005xxxxxx/PMC5000473.txt

==== Front BMC GeriatrBMC GeriatrBMC Geriatrics1471-2318BioMed Central London 33110.1186/s12877-016-0331-1Research ArticleThe impact of intravenous thrombolysis on outcome of patients with acute ischemic stroke after 90 years old Sagnier S. sharmilas@hotmail.fr 1Galli P. paola_g17@hotmail.com 12Poli M. mathilde.poli@chu-bordeaux.fr 1Debruxelles S. sabrina.debruxelles@chu-bordeaux.fr 1Renou P. pauline.renou@chu-bordeaux.fr 1Olindo S. stephane.olindo@chu-bordeaux.fr 1Rouanet F. francois.rouanet@chu-bordeaux.fr 1Sibon I. 33-5-56-79-55-20igor.sibon@chu-bordeaux.fr 121 Unité Neuro-vasculaire, Pôle de Neurosciences Cliniques, Hôpital Pellegrin, CHU Bordeaux, UnitéBordeaux Segalen, 33076, Bordeaux, France 2 Université Bordeaux Segalen, Bordeaux, France 25 8 2016 25 8 2016 2016 16 1 15613 5 2016 20 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Age increases the risk of mortality and poor prognosis following stroke. The benefit of intravenous thrombolysis in very old patients remains uncertain. The purpose of the study was to evaluate the efficacy and safety of thrombolysis in very old patients considering their perfusion-imaging profile. Methods We conducted a retrospective study including patients older than 90 y.o. admitted for an acute ischemic stroke. A computed tomography perfusion-imaging (CTP) was performed in patients who received thrombolysis. Primary outcome was the functional status at 3 months, assessed by the modified Rankin scale (mRS). Secondary outcomes were the rate of hemorrhagic transformations, duration of hospitalization and the rate of death in the first 7 days. Patients receiving thrombolysis were compared with an age-matched group of non-thrombolysed patients. Results 78 patients were included (31 % male, aged 92 ± 1.7 y.o). 37 patients received thrombolysis and among them, 30 had CTP with a mismatch. The three months mRS was not significantly different in the two groups (mRS 0–2: 5 % and 7 % in the thrombolysed and non-thrombolysed group, respectively). Hemorrhagic transformations were more frequent in the thrombolysed group (54 % versus 12 %, p = 0.002) and symptomatic intracranial hemorrhage tended to be associated with mRS at three months and death in the first 7 days. Duration of hospitalization was longer in the thrombolysed group (10 days ± 12 versus 7 days ± 9, p = 0.046). Conclusions Patients who received thrombolysis did not have a better functional prognosis than non-thrombolysed patients. Electronic supplementary material The online version of this article (doi:10.1186/s12877-016-0331-1) contains supplementary material, which is available to authorized users. Keywords Intravenous thrombolysisVery old patientsMismatchFunctional prognosisHemorrhagic transformationPost-stroke complicationsissue-copyright-statement© The Author(s) 2016 ==== Body Background Stroke care in older people is becoming a public health problem given the increased ageing of the population [1]. Indeed, the incidence of stroke increases with age and about 30 % of stroke patients are older than 80 years old [2]. It is widely admitted that oldest patients have a worse post-stroke functional outcome and a higher rate of death [3, 4]. Mortality at three months increases by 72 % whereas probability of good outcome decreases by 25 % every ten years [5]. The benefit of intravenous thrombolysis (IV-tPA) in ischemic stroke (IS) patients has been widely demonstrated [6, 7] but most of the studies excluded patients older than 80, therefore potentially limiting thrombolysis in this population. Several observational studies found that, compared to younger patients, tPA infusion to patients older than 80 y.o. was associated with higher functional dependency [3, 4, 8, 9]. While no significant increase of hemorrhagic transformation was observed in these older patients, this worse functional outcome seemed to be related to a worse pre-stroke functional status, a higher clinical severity at baseline, and more frequent post-stroke complications during the acute (pneumonia, heart failure). Despite the less favorable outcome of older patients, recent studies have suggested that IV-tPA could improve the functional prognosis of patients aged between 80 and 90 y.o. [10, 11]. However, old age remains a limitation for using IV-tPA for many physicians [12, 13]. That is even more true in the subgroup of very old patients, those aged over 90 y.o., for whom available data are scarce. In this population, few studies [4, 10] failed to identify a benefit of IV-tPA on functional outcome or mortality at three months. None of these studies have evaluated the potential benefit of IV-tPA depending on the neuroradiological imaging pattern at baseline. While still a matter of debate, some studies have suggested that a perfusion mismatch was associated with a better post-stroke functional prognosis among patients receiving IV-tPA [14]. The aim of our study was to evaluate the influence of IV-tPA on the three months functional outcome in a population of patients aged over 90 y.o., considering their perfusion-imaging profile. Methods Study design and patients Patients older than 90 y.o. admitted in the emergency department of the Bordeaux University hospital for an acute IS between October 2012 and June 2015 were retrospectively included. IS was diagnosed by a stroke neurologist based on clinical and imaging data. Inclusion criteria were an admission in the first twelve hours following symptoms onset, a pre-stroke modified Rankin scale (mRS) < 4, an absence of pre-stroke severe cognitive impairment, an available computerized neurovascular medical record and a set of brain images including a computed tomography (CT) and angio-CT of the cervical and intracranial arteries at baseline and a follow-up brain imaging (brain magnetic resonance imaging [MRI] or CT-scan in case of MRI contraindication) within 72 h, confirming the IS. Moreover, for patients receiving IV-tPA, a CT-perfusion (CTP) imaging at baseline had to be available. IV-tPA was administered according to the ESO guidelines [15] at the dose of 0.9 mg/kg until 4.5 h after symptoms onset in absence of usual contraindications. Patients admitted after the first 4.5 h were not thrombolysed and CTP were not performed. They formed a non-thrombolysed age-matched group for comparisons with the thrombolysed group. Patients with transient ischemic attack were excluded from the study. Demographic and clinical data Demographic and clinical data were recorded for each patient from their computerized medical record. Pre-stroke functional and cognitive status were evaluated using the pre-stroke mRS [16] and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) [17]. Stroke severity at baseline and at 24 h was evaluated by a stroke neurologist using the NIHSS [18]. The delay between symptom onset and IV-tPA administration, the duration of hospitalization and post-stroke in-hospital complications (delirium, mood disorders, swallowing disorders, seizure, acute coronary syndrome, pulmonary and urinary tract infection) were recorded. Stroke subtypes were defined according to the TOAST classification (Trial of Org 10172 in Acute Stroke Treatment) [19]. A clinical assessment was realized at three months post-stroke by a neurologist or a geriatrist and functional outcome was evaluated using the mRS. A three months mRS ranged 0 to 2 (i.e. alive and independent) indicated favorable outcome. The destination at the end of hospitalization (home, rehabilitation center, other medical department or nursing home) was also recorded. Imaging acquisition and analysis Images were acquired at the Bordeaux University hospital on a 64-slice CT (General Electric Optima 660). Analysis was performed by two neurologists who had experience in CT and MRI examination (GP and SS). CTP source images were loaded on an Advantage workstation Volume Share 5 (General Electric Healthcare). Perfusion maps were automatically generated including mean transit time (MTT), cerebral blood volume (CBV) and cerebral blood flow (CBF) maps, using CT Perfusion 4 (General Electric Healthcare), a commercially available software based on a delay-insensitive algorithm that is unaffected by delay between arterial input and tissue curves. A mismatch was visually defined by a MTT – CBV difference greater than 20 % [20]. The Alberta Stroke Program Early CT score (ASPECTS) [21] was calculated on the non-contrast CT. ASPECTS is a score ranged from 0 to 10 and reflects the infarct burden (a low score meaning a more severe infarct). The presence and location of intracranial arterial occlusion were identified on CT-angiography of cervical and intracranial arteries. Hemorrhagic transformation was assessed on follow-up brain imaging according to the radiological criteria of ECASS I [7]: hemorrhagic infarction (HI 1 and 2) or parenchymal hemorrhage (PH 1 and 2). Symptomatic intracranial hemorrhage was defined by the presence of a hemorrhagic transformation accompanied by neurological deterioration reflected by a worsening of the NIHSS at 24 h of at least two points. Microbleeds were assessed on T2* MRI sequences according to the STRIVE criteria [22] and were classified depending on their number: absence, between 1 and 5, and > 5. Outcomes Primary outcome was the mRS at three months. Secondary outcomes were the presence of a hemorrhagic transformation on the follow-up brain imaging, duration of hospitalization and death in the first 7 days. Statistical analysis Qualitative variables were expressed as numbers and percentages, and quantitative variables as means and standard deviations (SD). Comparisons of quantitative variables were assessed using a t-test or a Wilcoxon test after verifying the conditions of application, and comparisons of qualitative variables were assessed using a Chi2 test. Variables associated with thrombolysis were included in a bivariate analysis with primary and secondary outcomes as dependent variables, using a linear regression model. A multivariate analysis was performed for each outcome using multiple linear regressions, and including all variables with p < 0.1 in the bivariate analysis. A p-value < 0.05 was considered significant. Statistical analysis were performed with R software version 3.2.2. Results Patients Seventy -eight patients were included (Fig. 1), 35 % male, aged 91.9 ± 1.7 (mean ± SD) y.o. Demographic data are described in Table 1. 37 patients received IV-tPA. Among them, 30 patients had perfusion maps of sufficient quality to be analyzed and all of them had a mismatch. 41 patients did not receive IV-tPA. All of the patients were hospitalized in an intensive care unit, and those who did not receive IV-tPA had a 250 mg bolus of Aspirin in the first twelve hours. Patients who were taking anticoagulants before stroke also received aspirin as blood biological tests showed no efficacy of their treatment. The two groups were similar in terms of age, pre-stroke functional and cognitive status. Patients who received IV-tPA had significantly more history of hypercholesterolemia (41 % versus 20 %, p = 0.04) and more statins as current treatment (32 % versus 10 %, p = 0.01). Their mean total cholesterol level at baseline did not differ (1.9 g/L ± SD 0.3 versus 1.9 g/L ± SD 0.4, p = 0.7, in the thrombolysed and non-thrombolysed group, respectively).Fig. 1 Patient’s flow chart Table 1 Demographic data Thrombolysed Non-thrombolysed p N = 37 N = 41 Male, n (%) 17 (46) 10 (24) 0.05 Age, mean (SD) 91.7 (1.5) 92 (1.8) NS Vascular risk factors, n (%)  Hypertension 33 (89) 35 (85) NS  Hypercholesterolemia 15 (41) 8 (20) 0.04  Diabetes mellitus 5 (14) 4 (10) NS  Current smoking 1 (3) 0 NS Medical history, n (%)  Atrial fibrillation 12 (32) 9 (22) NS  Ischemic heart disease 3 (8) 3 (7) NS  Heart failure 3 (8) 5 (12) NS  Stroke or transient ischemic attack 6 (16) 10 (24) NS Current treatment, n (%)  Antiplatelets 19 (51) 20 (49) NS  Oral anticoagulants 2 (5) 6 (15) NS  Antihypertensive drugs 28 (76) 28 (68) NS  Statins 12 (32) 4 (10) 0.01  Antidepressant drugs 6 (16) 3 (7) NS Pre-stroke status  IQCODE, mean (SD) 3.2 (0.7) 3.3 (0.5) NS  mRS > 1, n (%) 14 (38) 19 (46) NS  At home, n (%) 32 (87) 29 (71) NS  Nursing home, n (%) 5 (14) 12 (29) NS SD Standard deviation, IQCODE Informant Questionnaire on Cognitive Decline in the Elderly, mRS modified Rankin Scale, NS Non-significant Clinical and radiological data at baseline are presented in Table 2. Stroke severity was not significantly different between the two groups (mean NIHSS 16 ± SD 7 in the thrombolysed group versus 13 ± 6 in the non-thrombolysed group, p = 0.06). The ASPECTS measured on non-contrast CT was similar in the two groups. Intracranial occlusion was significantly more frequent in the thrombolysed group (73 % versus 34 %, p = 0.002) with a predominance of M1 and M2 occlusion of the middle cerebral artery.Table 2 Acute clinical and radiological status, post-stroke outcome and stroke mechanisms Thrombolysed Non-thrombolysed p N = 37 N = 41 Acute clinical status, mean (SD)  NIHSS at baseline 16 (7) 13 (6) 0.06  NIHSS at 24 h 15 (8) 12 (7) NS  Systolic blood pressure (mmHg) 151 (28) 164 (25) 0.03  Diastolic blood pressure (mmHg) 79 (18) 85 (22) NS  Temperature (Celsius degree) 36.4 (0.6) 36.6 (0.6) NS  Capillary blood glucose level (g/L) 1.2 (0.3) 1.2 (0.4) NS Onset to needle time, mean (SD) 168 min (48) - -  Imaging parameters   Mismatch, n (%) 30 (81) - -   Non-contrast CT ASPECTS, mean (SD) 8.3 (2.2) 8.4 (3.3) NS   Intracranial occlusion, n (%) 27 (73) 14 (34) 0.002    M1 12 (45) 7 (50) NS    M2 10 (37) 3 (22) 0.02    M3 2 (7) 1 (7) NS    ACA 1 (4) 1 (7) NS    PCA 2 (7) 1 (7) NS    VB 0 1 (7) NS   Microbleeds, n (%) (n = 25) (n = 24)    1 – 5 6 (24) 6 (25) NS    >5 1 (4) 0 NS  Post-stroke complications, n (%)   Delirium 11 (30) 3 (7) 0.01   Mood disorder 3 (8) 2 (5) NS   Swallowing disorder 14 (38) 4 (10) 0.003   Seizure 0 1 (2) NS   Ischemic heart attack 1 (3) 3 (7) NS   Pulmonary infection 12 (32) 6 (15) NS   Urinary infection 3 (8) 1 (2) NS  Hemorrhagic transformation, n (%) 20 (54) 5 (12) 0.002   HI 1 and 2 8 (40) 4 (80) NS   PH 1 and 2 12 (60) 1 (20) 0.003  Symptomatic intracranial hemorrhage, n (%) 8 (22) 0 0.08  Duration of hospitalization, mean (SD) 10 days (12) 7 days (9) 0.046  mRS 0–2 at 3 months, n (%) 2 (5) 3 (7) NS  Post-stroke outcome, n (%)   Death ≤ 7 days 8 (22) 4 (10) NS   Death > 7 days 6 (16) 6 (15) NS   Return to home 5 (14) 7 (17) NS   Rehabilitation center 10 (39) 7 (17) NS   Other medical department 8 (22) 15 (37) NS   Nursing home 3 (8) 10 (24) NS  Stroke subtypes (TOAST), n (%)   Large artery atherosclerosis 3 (8) 10 (24) NS   Cardioembolic (AF) 27 (73) 24 (59) NS   Small vessel disease 0 0 -   Other 0 1 (2) NS   Undetermined 7 (19) 6 (15) NS NIHSS National Institute of Health Stroke Scale, ASPECTS Alberta Stroke Program Early CT score, M1 - M2 - M3 segments of middle cerebral artery, ACA anterior cerebral artery, PCA posterior cerebral artery, VB vertebral-basilar arteries, HI hemorrhagic infarction, PH, parenchymal hemorrhage, AF atrial fibrillation, NS non-significant Post-stroke outcomes and complications Primary and secondary outcomes are described in Table 2. The functional prognosis at three months was poor but similar in the two groups (7 % and 14 % mRS ≤ 2 at three months in the thrombolysed and non-thrombolysed group, respectively). Duration of hospitalization tended to be longer in the thrombolysed group (10 days ± 12 versus 7 days ± 9, p = 0.046). The mortality rate in the first seven days was higher in patients receiving IV-tPA but not significantly different from the other group (22 % versus 10 %). The most frequent post-stroke complications were swallowing disorders (38 %), pulmonary infections (32 %) and delirium (30 %). The rates of swallowing disorders and delirium were significantly higher in patients receiving IV-tPA (p = 0.003 and 0.01, respectively). The rate of hemorrhagic transformations was also higher in the thrombolysed group (54 % versus 17 %, p = 0.002), with a predominance of parenchymal hemorrhages and a trend to more symptomatic intracranial hemorrhage (40 % in the thromboysed group and no symptomatic intracranial hemorrhage in the non-thrombolysed group, p = 0.08). In bivariate analyses (Table 3), hemorrhagic transformation was associated with NIHSS at baseline and at 24 h (β = 0.02, p = 0.01 and β = 0.03, p = 0.003, respectively), presence of an intracranial occlusion (β = 0.4, p = 0.002) and thrombolysis (β = 0.4, p = 0.002). mRS at three months was also associated with NIHSS at baseline (β = 0.08, p = 0.008) and at 24 h (β = 0.09, p < .001), presence of an intracranial occlusion (β = 1.04, p = 0.01), together with hemorrhagic transformation (β = 0.8, p = 0.04) and symptomatic intracranial hemorrhage (β = 1, p = 0.03). Death in the first seven days was also associated with symptomatic intracranial hemorrhage (β = 0.6, p < .001) together with NIHSS at baseline and at 24 h. There was no significant association with duration of hospitalization. Additional bivariate analyses were performed with swallowing disorders and delirium as dependent variables. Swallowing disorders were associated with NIHSS at 24 h (β = 0.02, p = 0.02), and thrombolysis (β = 0.3, p = 0.003). Delirium was also associated with thrombolysis (β = 0.2, p = 0.01) and the presence of an intracranial occlusion (β = 0.2, p = 0.047).Table 3 Bivariate analyses of associations between pre-stroke and stroke characteristics and outcomes (linear regressions) mRS at three months Hemorrhagic transformation Duration of hospitalization Death ≤ 7 days Estimate β (SE) p Estimate β (SE) p Estimate β (SE) p Estimate β (SE) p Age −0.01 (0.1) 0.9 0.02 (0.04) 0.6 0.9 (0.7) 0.2 −0.03 (0.02) 0.3 Male −0.05 (0.05) 0.9 0.03 (0.1) 0.8 3.4 (2.5) 0.2 −0.1 (0.09) 0.1 Hypercholesterolemia −1.1 (0.4) 0.009 0.003 (0.1) 0.9 −1.9 (2.6) 0.5 −0.2 (0.09) 0.02 Statins −1 (0.5) 0.06 −0.06 (0.1) 0.7 −0.1 (3) 0.9 −0.1 (0.1) 0.3 Systolic blood pressure at baseline −0.0004 (0.008) 0.9 −0.003 (0.002) 0.2 −0.0003 (0.05) 0.9 −0.003 (0.002) 0.07 NIHSS at baseline 0.08 (0.03) 0.008 0.02 (0.009) 0.01 0.2 (0.2) 0.4 0.02 (0.006) 0.002 NIHSS at 24 h 0.09 (0.02) <.001 0.03 (0.008) 0.003 0.07 (0.2) 0.7 0.03 (0.005) <.001 Intracranial occlusion 1.04 (0.4) 0.01 0.4 (0.1) 0.002 2.9 (2.5) 0.2 0.03 (0.08) 0.7 Thrombolysis 0.2 (0.4) 0.6 0.4 (0.1) 0.002 2.7 (2.4) 0.3 0.1 (0.08) 0.2 Hemorrhagic transformation 0.8 (0.4) 0.04 - - 2.3 (2.8) 0.4 0.1 (0.09) 0.1 Symptomatic intracranial hemorrhage 1 (0.4) 0.03 - - −5.2 (6.4) 0.4 0.6 (0.2) <.001 Cardioembolic stroke subtype (AF) 0.9 (0.4) 0.053 −0.03 (0.1) 0.8 4.6 (2.5) 0.07 0.07 (0.09) 0.4 Large artery atherosclerosis stroke subtype −0.09 (0.6) 0.9 −0.05 (0.2) 0.8 −4.8 (3.2) 0.1 −0.09 (0.1) 0.4 SE standard error, AF atrial fibrillation In multivariate analyses (Table 4), only the NIHSS at 24 h (β = 0.03, p = 0.006) and the presence of an intracranial occlusion (β = 0.3, p = 0.02) remained associated with hemorrhagic transformation. No significant association persisted with mRS at three month, death in the first seven days (see Additional file 1), swallowing disorders and delirium.Table 4 Predictors of hemorrhagic transformation in multivariate analysis (multiple linear regressions) Hemorrhagic transformation Estimate β (SE) p NIHSS at baseline −0.002 (0.01) 0.8 NIHSS at 24 h 0.03 (0.01) 0.006 Intracranial occlusion 0.3 (0.1) 0.02 Thrombolysis 0.03 (0.1) 0.8 Discussion The main result of this study is the absence of significant difference on functional outcome at three months between patients older than 90 y.o. receiving and not receiving IV-tPA for an acute IS. In line with previous studies, this result suggests poor outcome in this very elderly population treated with IV-tPA for acute IS [4, 10]. However, a recent sub-group analysis of the Third International Stroke Trial (IST-3) reported a good outcome in 111 patients > 90 y.o. treated with alteplase versus 98 control patients, and this good outcome was not significantly different from the other groups [23]. Our different results might be explained by the lack of power of our study. Interestingly, our results were observed despite a favorable neuroimaging pattern on CTP imaging with the presence of a MTT-CBV mismatch in all available perfusion maps of the patients receiving IV-tPA and presence of a high ASPECT score [24, 25]. The impact of CTP imaging profile in patients receiving IV-tPA is not clearly established in the literature. This result suggests that even with the presence of a favorable perfusion profile, the response to thrombolysis in terms of efficacy and safety in the sub-population of very old patients was not improved. A worse collateral supply in older compared to younger patients could partly explain this result. Indeed, the long term exposure to vascular risk factors could have reduced the permeability of collateral vessels [26]. Patients included in the present study had relatively high NIHSS at baseline, which, in combination with the old age could have increased the risk of poor prognosis. This result is in accordance with previous reports which suggested that a positive SPAN-100 (patient age + NIHSS at baseline ≥ 100) could predict no significant benefit of thrombolysis [27]. Unfortunately, the use of CTP parameters did not seem to modify this cut-off. Swallowing disorders and delirium were significantly more frequent in the thrombolysed group. Swallowing disorders appeared to be related to stroke severity, and delirium to a side-effect of IV-tPA combined with the effect of age. Delirium could also have been favored by the cognitive frailty of these very elderly patients. In addition, the decubitus often imposed in the acute phase given the presence of a proximal intracranial occlusion probably increased these disorders. The trend to more frequent pulmonary infections in the thrombolysed group might have been the consequence of swallowing disorders in addition of agitation and altered awareness, with the risk of getting in a vicious circle. These factors might have contributed to impair the functional prognosis, increase mortality and interfere with the potential benefit of thrombolysis. The high rate of hemorrhagic transformation observed in our population receiving IV-tPA (53 %) is in accordance with the rate predicted by the SPAN-100 [27]. Hemorrhagic transformation and symptomatic intracranial hemorrhage might also partly explain the absence of IV-tPA benefit in the present study as we showed that symptomatic intracranial hemorrhage tended to be associated with the mRS at three months and death in the first 7 days. However, in IST-3, symptomatic intracranial hemorrhage did not affect clearly the outcome at six months [23], and while thrombolysis was found to be associated with hemorrhagic transformation in bivariate analysis, it did not remain significant in multivariate analysis. Conversely, intracranial occlusion and stroke severity at 24 h were independent predictors of hemorrhagic transformation. The association between intracranial occlusion and hemorrhagic transformation has already been described [28] and might be related to the larger infarct size observed in this condition. The results of this study should be interpreted cautiously due to several limitations. First, the retrospective design and the small sample size limits the power of statistical analysis. But the characteristics of our population are in line with previous studies and support the validity of our sample. Second, IV-tPA was administered until 4.5 h while some recommendations limit the use of this treatment to 3 h post-stroke onset in patients older than 80 y.o. [21]. However, treatment was initiated early in our sample (mean 168 ± SD 48 min) which might have limited the influence of the delay. Third, CTP imaging was not performed in non-thrombolysed patients, which did not allow direct comparisons between groups. Finally, the absence of evaluation of recanalization and/or reperfusion and final infarct size also limits the interpretation of results. Conclusion IV-tPA administered early after IS onset in our sample of patients aged over 90 y.o. did not influence the functional prognosis whereas most of them had a favorable neuroimaging pattern. Moreover, hemorrhagic transformation and post-stroke complications were more frequent in thrombolysed patients, and symptomatic intracranial hemorrhage tended to worsen the functional outcome at three months and increase the rate of death in the first 7 days. While the identification of additional predictors could be useful to improve the selection of patients suitable for IV-tPA, other revascularization techniques such as mechanical thrombectomy might be considered in this frail population in order to reduce hemorrhagic transformation, early clinical worsening, the vicious circle of post-stroke complications and extended duration of hospitalization. Further studies are needed to confirm those results. Additional file Additional file 1: Table S1. Multivariate analysis of associations between pre-stroke and stroke characteristics, mRS at three months and death in the first 7 days (multiple linear regressions). (DOCX 22 kb) Abbreviations ACAAnterior cerebral artery AFAtrial fibrillation ASPECTSAlberta Stroke Program Early CT score CBFCerebral blood flow CBVCerebral blood volume CTComputed tomography CTPCT-perfusion HIHemorrhagic infarction IQCODEInformant Questionnaire on Cognitive Decline in the Elderly ISIschemic stroke IV-tPAIntravenous thrombolysis M1M2, M3, Segments of middle cerebral artery mRSModified Rankin scale MRIMagnetic resonance imaging MTTMean transit time NIHSSNational Institute of Health Stroke Score PCAPosterior cerebral artery PHParenchymal hemorrhage SDStandard deviation TOASTTrial of Org 10172 in Acute Stroke Treatment VBVertebral-basilar arteries Acknowledgements The authors acknowledge Sylvain Ledure who provided a technical help. Funding None. Availability of data and materials All data generated or analyzed during this study are included in this published article and its additional information file. Authors’ contributions SS, GP and MP analyzed and interpreted clinical and radiological data, and contributed to write the manuscript. SD, PR, SO and FR participated in the acquisition of data, and revised the manuscript. IS conceived the study and has been involved in the interpretation of data, drafting the manuscript and critical revision. All authors read and approved the final manuscript. Competing interest The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate Our study was a non-interventional retrospective study and did not need formal ethics approval, nor written consent, in accordance with national regulations (see first part of the Public Health Code, Book I, Title II, article L1121-1). In addition, according to law 2012–300 of March 5, 2012, relative to research involving humans, a formal oral or written consent is not required for non-interventional studies, but a non-opposition of patients is needed, i.e. the absence of written opposition. All patients were part of a local stroke registry and had a written and explicit information indicating that their data could be used for research purposes. None of them expressed written opposition. ==== Refs References 1. Green Paper—Faced with demographic change, a new solidarity between the generations. Communication from the European Commission, COM. 2005;94. Available at: http://ec.europa.eu/employment_social/social_situation/green_paper_en.html. Accessed 4 Oct 2005. 2. Russo T Felzani G Marini C Stroke in the very old: a systematic review of studies on incidence, outcome, and resource use J Aging Res 2011 2011 108785 10.4061/2011/108785 21876804 3. Boulouis G Dumont F Cordonnier C Bodenant M Leys D Hénon H Intravenous thrombolysis for acute cerebral ischaemia in old stroke patients ≥ 80 years of age J Neurol 2012 259 1461 7 10.1007/s00415-011-6359-4 22183776 4. Bray BD Campbell J Hoffman A Tyrrell PJ Wolfe CDA Rudd AG Stroke thrombolysis in England: an age stratified analysis of practice and outcome Age Ageing 2013 42 240 5 10.1093/ageing/afs167 23174425 5. Berrouschot J Röther J Glahn J Kucinski T Fiehler J Thomalla G Outcome and severe hemorrhagic complications of intravenous thrombolysis with tissue plasminogen activator in very old (> or =80 years) stroke patients Stroke 2005 36 2421 5 10.1161/01.STR.0000185696.73938.e0 16210554 6. Wahlgren N Ahmed N Dávalos A Hacke W Millán M Muir K Thrombolysis with alteplase 3–4.5 h after acute ischaemic stroke (SITS-ISTR): an observational study Lancet 2008 372 1303 09 10.1016/S0140-6736(08)61339-2 18790527 7. Hacke W Kaste M Fieschi C Toni D Lesaffre E von Kummer R Intravenous thrombolysis with recombinant tissue plasminogen activator for acute hemispheric stroke. The European Cooperative Acute Stroke Study (ECASS) JAMA 1995 274 1017 25 10.1001/jama.1995.03530130023023 7563451 8. Engelter ST Bonati LH Lyrer PA Intravenous thrombolysis in stroke patients of > or = 80 versus < 80 years of age--a systematic review across cohort studies Age Ageing 2006 35 572 80 10.1093/ageing/afl104 17047006 9. Simon JE Sandler DL Pexman JHW Hill MD Buchan AM Calgary Stroke Programme Is intravenous recombinant tissue plasminogen activator (rt-PA) safe for use in patients over 80 years old with acute ischaemic stroke? - The Calgary experience Age Ageing 2004 33 143 9 10.1093/ageing/afh031 14960429 10. Mishra NK Ahmed N Andersen G Egido JA Lindsberg PJ Ringleb PA Thrombolysis in very elderly people: controlled comparison of SITS International Stroke Thrombolysis Registry and Virtual International Stroke Trials Archive BMJ 2010 341 c6046 10.1136/bmj.c6046 21098614 11. Emberson J Lees KR Lyden P Blackwell L Albers G Bluhmki E Effect of treatment delay, age, and stroke severity on the effects of intravenous thrombolysis with alteplase for acute ischaemic stroke: a meta-analysis of individual patient data from randomised trials Lancet 2014 384 1929 35 10.1016/S0140-6736(14)60584-5 25106063 12. Shamy MCF Jaigobin CS The complexities of acute stroke decision-making: a survey of neurologists Neurology 2013 81 1130 3 10.1212/WNL.0b013e3182a55ec7 23946306 13. Liu Y, Zhao H, Zhou J, Wang Q, Chen Z, Luo N. Mild stroke and advanced age are the major reasons for exclusion from thrombolysis in stroke patients admitted within 4.5 hours. J Stroke Cerebrovasc Dis Off J Natl Stroke Assoc. 2014;23:1571–6 14. Ogata T Christensen S Nagakane Y Ma H Campbell BC Churilov L The effects of alteplase 3 to 6 h after stroke in the EPITHET-DEFUSE combined dataset: post hoc case–control study Stroke 2013 44 87 93 10.1161/STROKEAHA.112.668301 23250996 15. The European Stroke Organisation (ESO) executive committee and the ESO writing committee. Guidelines for management of ischaemic stroke and transient ischaemic attack 2008. Cerebrovasc Dis. 2008;25:457–507. 16. Van Swieten JC Koudstaal PJ Visser MC Schouten HJ van Gijn J Interobserver agreement for the assessment of handicap in stroke patients Stroke J Cereb Circ 1988 19 604 7 10.1161/01.STR.19.5.604 17. Jorm AF Jacomb PA The Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE): socio-demographic correlates, reliability, validity and some norms Psychol Med 1989 19 1015 22 10.1017/S0033291700005742 2594878 18. Brott T Adams HP Olinger CP Marler JR Barsan WG Biller J Measurements of acute cerebral infarction: a clinical examination scale Stroke J Cereb Circ 1989 20 864 70 10.1161/01.STR.20.7.864 19. Adams HP Bendixen BH Kappelle LJ Biller J Love BB Gordon DL Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment Stroke J Cereb Circ 1993 24 35 41 10.1161/01.STR.24.1.35 20. Lin K Rapalino O Lee B Do KG Sussmann AR Law M Correlation of volumetric mismatch and mismatch of AlbertaStroke Program Early CT Scores on CT perfusion maps Neuroradiology 2009 51 17 23 10.1007/s00234-008-0454-y 18787815 21. Barber PA Demchuk AM Zhang J Buchan AM Validity and reliability of a quantitative computed tomography score in predicting outcome of hyperacute stroke before thrombolytic therapy. ASPECTS Study Group. Alberta Stroke Programme Early CT Score Lancet 2000 355 1670 4 10.1016/S0140-6736(00)02237-6 10905241 22. Wardlaw JM Smith EE Biessels GJ Cordonnier C Fazekas F Frayne R Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration Lancet Neurol 2013 12 822 38 10.1016/S1474-4422(13)70124-8 23867200 23. Lindley RI Wardlaw JM Whiteley WN Cohen G Blackwell L Murray GD Alteplase for acute ischemic stroke: outcomes by clinically important subgroups in the Third International Stroke Trial Stroke 2015 46 746 56 10.1161/STROKEAHA.114.006573 25613308 24. Sillanpaa N Saarinen JT Rusanen H Hakomaki J Lahteela A Numminen H CT Perfusion ASPECTS in the evaluation of acute ischemic stroke: thrombolytic therapy perspective Cerebrovasc Dis Extra 2011 1 6 16 10.1159/000324324 22566978 25. Wintermark M Flanders AE Velthuis B Meuli R van Leeuwen M Goldsher D Perfusion-CT assessment of infarct core and penumbra: receiving operating characteristic curve analysis of 130 patients suspected of acute hemispheric stroke Stroke 2006 37 979 85 10.1161/01.STR.0000209238.61459.39 16514093 26. Liebeskind DS Collateral circulation Stroke 2003 34 2279 2284 10.1161/01.STR.0000086465.41263.06 12881609 27. Saposnik G Guzik AK Reeves M Ovbiagele B Johnston SC Stroke Prognostication using Age and NIH Stroke Scale: SPAN-100 Neurology 2013 80 21 8 10.1212/WNL.0b013e31827b1ace 23175723 28. The IST-3 collaborative group Association between brain imaging signs, early and late outcomes, and response to intravenous alteplase after acute ischaemic stroke in the third International Stroke Trial (IST-3): secondary analysis of a randomised controlled trial Lancet Neurol 2015 14 485 96 10.1016/S1474-4422(15)00012-5 25819484

PMC005xxxxxx/PMC5000474.txt

==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3208310.1038/srep32083ArticleDiscovery of a Carbazole-Derived Lead Drug for Human African Trypanosomiasis Thomas Sarah M. 1Purmal Andrei 2Pollastri Michael 3Mensa-Wilmot Kojo a11 Department of Cellular Biology, Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, Georgia 30602, USA2 Cleveland BioLabs, Inc., Buffalo, New York 14203, USA3 Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, USA.a mensawil@uga.edu26 08 2016 2016 6 3208311 11 2015 02 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/The protozoan parasite Trypanosoma brucei causes the fatal illness human African trypanosomiasis (HAT). Standard of care medications currently used to treat HAT have severe limitations, and there is a need to find new chemical entities that are active against infections of T. brucei. Following a “drug repurposing” approach, we tested anti-trypanosomal effects of carbazole-derived compounds called “Curaxins”. In vitro screening of 26 compounds revealed 22 with nanomolar potency against axenically cultured bloodstream trypanosomes. In a murine model of HAT, oral administration of compound 1 cured the disease. These studies established 1 as a lead for development of drugs against HAT. Pharmacological time-course studies revealed the primary effect of 1 to be concurrent inhibition of mitosis coupled with aberrant licensing of S-phase entry. Consequently, polyploid trypanosomes containing 8C equivalent of DNA per nucleus and three or four kinetoplasts were produced. These effects of 1 on the trypanosome are reminiscent of “mitotic slippage” or endoreplication observed in some other eukaryotes. ==== Body Human African trypanosomiasis (HAT) is a disease endemic to regions of sub-Saharan Africa, and is caused by the protozoan parasite Trypanosoma brucei. Nearly 70 million people are at risk of contracting HAT1. Drug therapy is necessary to cure this otherwise fatal infectious disease2. The five drugs currently registered to treat HAT are suramin, pentamidine, melarsoprol, eflornithine and nifurtimox. Except for nifurtimox (administered orally, but only in combination with the injectable drug eflornithine), none are orally bioavailable. Thus, an entirely orally bioavailable treatment regimen does not exist for treatment of HAT. Other problems relating to safety have led to renewed calls for safe and orally bioavailable anti-HAT drugs, even as clinical trials for two leads (Fexinidazole3 and SCYX-71584) are ongoing (reviewed in refs 1, 5 and 6). There are several strategies for discovering drugs against neglected human diseases such as HAT78910. In this study we utilize a “drug repurposing” approach7 in which drugs developed for one indication are tested for efficacy against a different disease. Chemical scaffolds of drugs that are active against parasites in vitro and in a mouse model of HAT could be subsequently optimized through medicinal chemistry efforts to create novel anti-trypanosome compounds1011. Carbazole scaffolds are found in some marketed drugs or are “hits” in development for treatment of chronic disease. For example, carprofen, a non-steroidal anti-inflammatory analgesic is a carbazole derivative12. N-alkyl carbazoles as well as aminopropyl-carbazoles are under investigation as lead drugs to treat Alzheimer’s and Parkinson’s diseases13141516. As part of a drug discovery initiative, Cleveland BioLabs, Inc. synthesized a class of carbazole derivatives termed “Curaxins”. Some Curaxins can intercalate into DNA, though they are non-genotoxic in that they do not induce DNA damage17 and influence activity of the “facilitates chromatin transcription” (FACT) complex in some human cancer cells1718. We tested this class of compounds against T. brucei for several reasons. First, several of them were orally bioavailable and had excellent in vivo toxicology properties17. Moreover, CBL0137 (1, Fig. 1a) has completed phase I clinical trials for treatment of advanced solid tumors and lymphomas19. Finally, methods for synthesis of this family of compounds were available, enabling production of new analogs based on evolving phenotypic structure-activity relationship data20. We report here that many representatives of this class of compounds inhibited proliferation of bloodstream T. brucei in vitro at nanomolar concentrations. CBL0137 (1), CBL0159 (2) and CBL0176 (3) were tested in a mouse model of HAT. Administered orally, they increased survival of infected mice compared to control untreated animals. Compound 1 cured 100% of infected mice, qualifying it as a lead drug worthy of pre-clinical evaluation studies according to guidelines on tropical diseases set forth by the World Health Organization21. In “mode of action” studies, we found that 1 inhibits mitosis and re-licenses entry into S-phase of the cell division cycle, leading to emergence of polyploid T. brucei. Materials and Methods Drugs Samples of compounds (>95% pure) including CBL0137 (lot #10-106-88-30) were provided by Cleveland BioLabs, Inc. (Buffalo, NY). For in vitro studies, 10 mM stock solutions of the compounds were prepared in dimethylsulfoxide (DMSO). For oral gavage of mice, the compounds were formulated in 0.2% hydroxypropyl methylcellulose (HPMC). Cell culture Bloodstream form (BSF) Trypanosoma brucei was maintained at densities below 106 cells/mL at 37 °C, 5% CO2 in HMI-9 medium supplemented with 10% fetal bovine serum (Atlanta Biologicals; Atlanta, GA), 10% SERUM PLUSTM (Sigma; St. Louis, MO), and 1% antibiotic-antimycotic Solution (Corning cellgro®; Corning NY)22. T. brucei brucei RUMP52823, and T. brucei rhodesiense KETRI 248224 (a gift from Stephen Hajduk, University of Georgia), were used for these studies. All trypanosome experiments were performed using T. b. brucei unless otherwise specified. Human HeLa cells were grown in 75 cm2 vented cap culture flasks (Corning) at 37 °C, 5% CO2 in Dulbecco’s modified Eagle’s medium (DMEM) (Corning cellgro®) containing 10% FBS, and 1% antibiotic-antimycotic Solution25. Cultures were maintained at up to 80% confluency. Trypanosome and HeLa cell-based proliferation inhibition assays T. brucei and HeLa cells were cultured as described9 with modifications. T. brucei T. brucei (brucei or rhodesiense) were seeded at 4 × 103 cells/mL in 24-well plates (0.5 or 1 mL of culture per well). Cells were incubated for 48 h with 1 or 2 μL of DMSO (vehicle control) or compound in DMSO. Compounds were initially tested at 10 nM, 100 nM or 1 μM, to define a range where cell density responded to drug concentrations. Then, at least five drug concentrations26 covering this range was used for subsequent assays. Each concentration was tested in duplicate. Cell density was determined with a Neubauer Bright-Line hemocytometer (Sigma) after 48 h. Cells were counted only if they were motile. Mean cell counts were plotted against compound concentration and the GI50 (compound concentration that inhibits T. brucei proliferation by 50%) was determined by linear interpolation using Excel for Mac 2011 (Microsoft)27. Final mean GI50 values were calculated based on two independent experiments, each with at least five data points performed in duplicate. HeLa cells HeLa cells were seeded to 1 × 105 cells/mL in 24-well plates (1 mL of culture per well) and incubated drug-free for 24 h at 37 °C, 5% CO2. DMSO or stock inhibitor concentration (5 μL) was added to obtain the specified final concentrations. Cells were incubated for 24 h2829 at 37 °C, 5% CO2. Next, cells were trypsinized and cell density was determined with a Neubauer Bright-line hemocytometer as described9. GI50 for each compound was calculated by plotting data for the cell counts in Excel as described for T. brucei above. Data were obtained from two independent experiments, four separate biological replicates. High throughput trypanosome proliferation inhibition assay T. brucei were seeded at 4 × 103 cells/mL and dispensed into wells of a 384-well black plate (Greiner; Frickenhausen, Germany). Wells in two columns per plate were filled with 50 μL of HMI-9 medium using a Multidrop Combi (Thermo Scientific; Waltham, MA) to serve as a background control. Fifty microliters of trypanosome suspension was added to separate columns using a Multidrop Combi. Lastly, an additional 50 μL of cell resuspension was added to only the top row of wells that contained cells (row A, labeled by Greiner), using an Xplorer multichannel pipette (Eppendorf; Hamburg-Eppendorf, Germany) bringing final volumes of cell-containing wells in the top row to 100 μL. Prior to their addition to assay plates, DMSO or compounds in DMSO were diluted 1:4 (v/v) with HMI-9 medium in 0.2 mL tubes (MidSci; St. Louis, MO). A microliter of DMSO (25%) or diluted drug was added to wells containing cells of the top row using an Xplorer multichannel pipette. Each concentration was tested in duplicate. Cells and DMSO/drug were mixed and serially diluted 1:2 down the rows of the plate. Plates were incubated for 48 h at 37 °C and 5% CO2 and loaded into a Fluoroskan Ascent Microplate Fluorometer (Thermo Scientific). Cells were lysed by addition of 15 μL of SYBR Green I (Invitrogen; Carlsbad, CA) in lysis solution30 (5X SYBR Green I, 30 mM Tris pH 7.5, 7.5 mM EDTA, 0.012% saponin and 0.12% Triton X-100) to each well. Plates were agitated at 1200 rpm for 45 s, incubated in the dark for 1 h at room temperature, and fluorescence was detected (ex: 485 nm, em: 538 nm) using 100 ms integration time. Data collected was exported to Excel from Ascent Software (Thermo Scientific). Base-line corrected non-linear regression graphs were generated and GI50 values determined using GraphPad Prism (GraphPad Software; La Jolla, CA). Final mean GI50 values were calculated based on four separate biological replicates. Infection of mice with T. brucei brucei Cultured T. brucei were pelleted and resuspended in cold phosphate buffered saline (PBS) containing 1% glucose at 1 × 105 cells/mL. Female Swiss-Webster mice (8–10 weeks old, 20–25 g, n = 4 per group) (Harlan; Indianapolis, IN) were infected intraperitoneally (i.p.) with 104 bloodstream trypanosomes in 100 μL of PBS using 26G needles. To avoid damage to T. brucei cells, mechanical stress during administration was minimized by avoiding repeated pulling and pushing movements of cell resuspension through the syringe needle. Starting 48 h post-infection, and every 1–8 days thereafter, parasitemia was monitored by collecting 3 μL of blood from the tail vein of mice. Blood samples were supplemented with 21 μL of RBC Lysis Solution (Qiagen; Valencia, CA) and incubated at room temperature for 15–45 min. prior to observing for parasites using a Neubauer Bright-line hemocytometer. Mice with parasitemia greater than 2 × 108 trypanosomes/mL were euthanized. Mice were considered cured if they lived more than 30 days after experimental treatment ended and had no detectable parasites in the blood at that time3132. To compare animal survival in treatment and vehicle control groups, Student’s t-test was performed in Excel to generate p-values. All animal experiments were conducted with the approval of the Institutional Animal Care and Use Committee (IACUC) at the University of Georgia. All experimental protocols involving animals were carried out in accordance with the approved guidelines of the IACUC at the University of Georgia. Drug administration and determination of parasitemia in mice Formulated compounds or vehicle control (0.2% HPMC) were administered by oral gavage starting 24 h after mouse infection with T. brucei3334. Animals were weighed before each compound administration, and dose volume was adjusted based on body weight (10 mL/kg) to deliver accurate doses of test compounds. The treatment was ceased for animals when normalized body weight (NBW) loss exceeded 20%, and resumed after NBW recovery above 90%. Compounds 1–3 were administered orally once per day of treatment 24 h post-infection as follows. 1: 30 mg/kg or 40 mg/kg, treatment regimen of “4 days on/2 days off” for a total of 14 doses; 2: 20 mg/kg (days 2–5), 10 mg/kg (day 7), 5 mg/kg (days 8–9), no drug (day 6, days 10–13); 3: 25 mg/kg (days 2–5), 12.5 mg/kg (day 7), 6.25 mg/kg (days 8–10), no drug (day 6, days 11–13). Scheduled euthanasia by CO2 overdose followed by incision to form a bilateral pneumothorax was conducted on mice considered cured 30 days after the end of experimental treatment (see previous section). Mice with parasitemia greater than 2 × 108 trypanosomes/mL or NBW losses ≥30% were subjected to unscheduled euthanasia. Effects of ethidium bromide and compound 1 on kinetoplast duplication and nucleus mitosis Thirty-hour compound 1 treatment of trypanosomes T. brucei were seeded at 1 × 105 cells/mL in 175 cm2 vented cap culture flasks containing 100 mL of HMI-9 medium and incubated at 37 °C, 5% CO2 for 30 h with 1 (200 nM), ethidium bromide (EtBr, 200 nM), sterile deionized H2O or DMSO (0.1%). At stated times trypanosome density was determined using a Z2 Coulter Counter (Beckman). A 10 mL aliquot of cell culture per sample (1 × 106–2 × 107 cells total) was collected every 6 h and analyzed using fluorescence microscopy as described below. At the same time-points a 5 mL aliquot (5 × 105–1 × 107 cells total) was collected and analyzed by flow cytometry as described below. All data reported were obtained from three independent experiments. Fluorescence microscopy HMI-9 medium (5–10 mL) containing 1 × 105–2 × 106 cells/mL of T. brucei was centrifuged (5 min, 3000 × g at room temperature) to pellet the cells. After supernatant removal cells were resuspended in 1 mL of PBS containing 4% paraformaldehyde (Affymetrix; Santa Clara, CA) and incubated for either 1 min at room temperature or up to two weeks at 4 °C. Fixed cells were adhered to poly-L-lysine coated coverslips for 15 min at room temperature. Coverslips were washed with approximately 0.1–1 mL of PBS, air dried, then mounted on 2 μL of DAPI (1.5 μM) in Vectashield (Vector Labs; Burlingame, CA). For quantitation, 150 cells per sample were counted for each independent experiment using an EVOS® FL inverted fluorescence microscope (Life Technologies; Grand Island, NY). Images for figures were captured on an Applied Precision DeltaVision microscope system (GE Healthcare; Issaquah, WA) using an Olympus IX-71 inverted microscope (Olympus; Center Valley, PA) at 60X, ex: 435 nm, em: 448 nm. To compare effects on organelle DNA duplication by drug treatment and vehicle control groups, Student’s t-test was performed in Excel to generate p-values. Flow cytometry T. brucei (between 5 × 105 cells to 1 × 107 cells) in 5 mL of culture medium were centrifuged (3 min, 3000 × g at room temperature) to pellet cells and washed once with 1 mL of PBS containing 10 mM glucose. Cells were fixed in 1 mL of 70% methanol supplemented by PBS at 4 °C for up to two weeks, centrifuged (3 min, 2000 × g at room temperature), and resuspended at 5 × 105 cells/mL in 1X PBS. RNase A and propidium iodide (PI) were added to each sample to final concentrations of 500 μg/mL and 7.5 μM, respectively, and the suspension was protected from light during incubation for 1 h at 37 °C35. Samples were placed on ice for 15 min and data was immediately collected on a CyAn ADP Analyzer (Beckman Coulter; Hialeah, FL). During analysis with FlowJo software (FlowJo, LLC; Ashland, OR), trypanosomes were gated from background debris by plotting “events” as forward scatter vs. side scatter (both on the logarithmic scale). Single trypanosomes were gated for cell cycle analysis from cells stuck together (“doublets”) by plotting trypanosome events as PI fluorescence vs. pulse width. Distribution of trypanosomes into groups containing different amounts of chromosomal DNA was performed using Watson-Pragmatic algorithm in FlowJo. DNA distribution values from independent experiments were averaged with error bars generated and graphed in Excel. To compare effects of drug treatment on DNA content of experimental and vehicle control groups, Student’s t-test was performed in Excel to generate p-values. “Delayed killing” effects after 6-h exposure of cells to compound 1 T. brucei cells T. brucei were seeded at 5 × 105 cells/mL in 25 cm2 vented cap culture flasks containing 5 mL of HMI-9 medium and incubated 6 h with 1 (1 μM) or DMSO (0.1%). Cells were centrifuged (3000 × g, 5 min, room temperature), washed twice with HMI-9 medium and resuspended at 1 × 105 cells/mL in 5 mL of HMI-9 medium. Trypanosomes were incubated at 37 °C, 5% CO2 for 48 h. Cell density was determined with a Neubauer Bright-line hemocytometer as described for cell proliferation assays. Data were obtained from two independent experiments, four separate biological replicates. HeLa cells HeLa cells were seeded to 1 × 105 cells/mL in 24-well plates (1 mL of culture per well) and incubated drug-free for 24 h at 37 °C, 5% CO2. Next, 1 (1 μM) or DMSO (0.1%) was added and cells were treated for 6 h. Cells were washed, trypsinized, and resuspended in equivalent volumes of HMI-9 medium9. Cell density was determined using a Neubauer Bright-line hemocytometer as described in the cell-based proliferation assays. Samples were resuspended in HMI-9 medium to 5 × 104 cells/mL and incubated for 48 h. Cells were counted by hemocytometer, and resuspended to 5 × 104 cells/mL every 48 h for 8 days (192 h) post-treatment. Data were obtained from two independent experiments, four separate biological replicates. Results Effect of compounds on trypanosome proliferation: Preliminary structure-activity relationship (SAR) Twenty-six compounds were screened for their effects on trypanosome proliferation in vitro, by culturing bloodstream T. brucei in different concentrations of each compound. Test compound concentrations causing 50% inhibition of trypanosome proliferation (GI50) were calculated (Fig. 1, Supplementary Fig. S1). Compounds with GI50 less than 100 nM were classified as “hits”36. Most compounds were categorized into one of three classes according to the R1 and R2 substituents on the carbazole scaffold (Fig. 1a,b). The most potent inhibitors belonged to Class 3, containing two cyclopentanone rings fused with the carbazole. Most of these inhibitors displayed a GI50 between 0.7–3 nM. Class 2 compounds (with one fused cyclopentanone ring and one acetyl group) had GI50 between 2–10 nM. Class 1 compounds (diacetyl-substituted on the carbazole) had GI50 between 25–300 nM. We could hypothesize a few reasons why this conformational restraint may be relevant. First, this ring restraint could reinforce presentation of the hydrogen bond acceptor carbonyl(s) in a vector that made more favorable interactions with its target(s) of action. Second, the enhanced planarity compared to the acyclic acetyl groups could enhance DNA intercalation. Lastly, we do not rule out a possibility that this structural feature affects other properties that contributed to the potency of Class 3 inhibitors against the parasite. Work is ongoing to test these hypotheses. Other compounds that did not cleanly fit into the classification system above were tested (Fig. 1c). These compounds all presented H-bond acceptor moieties that could potentially mimic the cyclopentanone carbonyl oxygen, however only one, CBL0167 (6), had appreciable activity with GI50 less than 25 nM (Fig. 1c). With the exception of CBL0149 (Fig. 1a), the N-linked side chain of each compound tested contained either a basic secondary or tertiary amine. Within the Class 1 compounds, increasing chain length and steric bulk around the amine generally reduced potency. For example, extension of the chain from two to three carbons (1 vs. CBL0127, Fig. 1a) resulted in a 3-fold reduction in potency. In another example, increasing the steric bulk on the linker (CBL0100Q versus CBL0100, Fig. 1a) led to a nearly 250-fold potency loss. Lastly, we noted that hydroxylation of the carbazole core was tolerated in three examples (such as compound 2, Fig. 1b). This initial SAR was instructive with regards to the first round of medicinal chemistry optimization, which will be reported in due course. Selection of compounds for testing in a mouse model of HAT To explore anti-trypanosomal effects of the compounds in mice, we selected representatives of each class as defined in Fig. 1. Compound 1 was the best Class 1 candidate to test in vivo because it is well-tolerated in mice following oral administration17, and it had a low GI50 of 55 nM against T. brucei (Fig. 1a). Compounds 2 (Class 2) and 3 (Class 3) were chosen because they were also orally bioavailable (Cleveland BioLabs, unpublished data) and they had low GI50’s of 7.4 nM and 2.2 nM respectively. Furthermore, compounds 1–3 were potent against the human-infective subspecies T. brucei rhodesiense (Table 1). Prior to performing drug efficacy studies in a mouse model of HAT, we sought to identify overtly toxic compounds, by determining the GI50 of compounds 1–3 against HeLa cells in vitro (Table 1). The selectivity index (SI) for each compound was calculated as a ratio between HeLa and T. brucei GI50 values. Because 1 is well-tolerated in mice17, it’s SI (38-fold) was used as a threshold for compound selection. Both 2 and 3 had SI values greater than that of 1 (SI = 78 and 236-fold, respectively), indicating less general toxicity by these criteria. Therefore, 1 (Class 1), 2 (Class 2) and 3 (Class 3) were selected for testing in a mouse model of HAT. Compound 2 and Compound 3 extend life of mice infected with T. brucei Following infection with trypanosomes, mice from the vehicle (i.e., untreated) control group survived 5 days on average. Mice treated orally with 2 or 3 had a 2-fold increase in average survival (Fig. 2a). From days two to five a full dose (at the repeated maximum tolerated dose) of either 2 or 3 was orally administered to mice (20 mg/kg and 25 mg/kg respectively). At day six, both compounds reduced parasitemia 100-fold (Fig. 2b,c). However, weight loss exceeding 10% of normal body weight (NBW) was observed in both treatment groups (Supplementary Fig. S2b,c). As a result, over the next several days, doses of both compounds were reduced to limit weight loss. After treatment with 2 and 3 ended (day 10), parasitemia rose and all mice were euthanized for humane reasons because of high parasitemia (>2 × 108 cells/mL) (Fig. 2b,c). Compound 1 cures T. brucei infection in a mouse model of HAT Compound 1 was administered to T. brucei-infected mice once per day of treatment (4-on, 2-off) at 30 mg/kg or 40 mg/kg for a total of 14 doses. Little or no weight loss was observed during treatment with 1 (Supplementary Fig. S2a). Vehicle control mice were euthanized for humane reasons by day five because their parasitemia was greater than the 2 × 108 parasites/mL threshold. All mice treated with 1 were alive on day five. A 30 mg/kg dose of 1 cured 50% of trypanosome-infected mice. Following administration of 40 mg/kg, 100% of trypanosome-infected mice were cured of infection (Fig. 3a). Trypanosomes were not observed in peripheral blood of infected mice at either dose level (Fig. 3b,c). Of the two mice that died during the 30 mg/kg treatment, one had no parasitemia and may have died of other causes, whereas the second mouse died following recrudescence observed on day 27 post-infection (Fig. 3b). Overall, this data demonstrated efficacy of 1 in a mouse model of HAT, and established 1 as a lead for T. brucei drug development. Compound 1 affects DNA replication and mitosis Following discovery of 1 as a lead, we explored that drug’s mode of action by examining its effect on trypanosome cell division. Trypanosomes have chromosomal DNA in the nucleus, and their mitochondrial DNA (kinetoplast DNA (kDNA)) is found in a nucleoid termed the kinetoplast within the mitochondrion. Because compound 1 binds DNA in HeLa cells17 we compared its effects on trypanosome biology to that of ethidium bromide (EtBr), a well-known DNA binding agent that is also anti-trypanosomal37. A 30 h time-course of ethidium bromide (EtBr, 200 nM) and 1 (200 nM) treatment was performed with their appropriate vehicle controls under conditions reported to cause dyskinetoplastic formation during EtBr treatment37. Cell density and effects on DNA “karyotype” (i.e., number of nuclei and kinetoplasts per cells) and DNA content were determined from samples collected every 6 h (Figs 4, 5, 6 and 7, Supplementary Figs S4–S8). Both compounds blocked trypanosome proliferation, with only 1.5-fold and 2.5-fold increases in cell density during 30 h treatment with 1 or ethidium bromide (Supplementary Fig. S4). Generally, effects on DNA karyotype/content by either drug reached maximum effect by 24 h (Figs 4 and 6). Therefore, representative microscopy images presented were taken only from trypanosomes obtained at this time-point (Fig. 5 and Supplementary Fig. S6). Ethidium bromide (200 nM) produced dyskinetoplastic trypanosomes (i.e., cells that lack a kinetoplast but contain a nucleus, 0K1N) within 6 h (Fig. 4d). Proportions of dyskinetoplastic trypanosomes increased whereas proportions of cells with one kinetoplast one nucleus (1K1N) and cells with two kinetoplasts and one nucleus (2K1N) decreased during the 30 h treatment (Figs 4d and 5c,d). Compound 1 (200 nM) failed to generate dyskinetoplastic trypanosomes. Instead, 1 increased the fraction of 2K1N cells while decreasing the proportion of 1K1N cells. Furthermore, 1 caused the formation of XK1N trypanosomes containing three or four kinetoplasts and one nucleus (Figs 4c and 5a,b and Supplementary Fig. S6). These observations indicated that 1 inhibits mitosis, but did not affect kinetoplast biogenesis. These differences in the biological effects of EtBr and 1 suggested that the targets of the two compounds are different. Effects of 30 h treatment with 1 (200 nM) or EtBr (200 nM) on trypanosome DNA content were analyzed (Figs 6 and 7 and Supplementary Figs S7 and S8). For 1, most treated cells contained 4C DNA and a significant fraction (~30%) were polyploid with 8C DNA (Figs 6c and 7a,b and Supplementary Fig. S7). These data indicated that although 1-treated trypanosomes failed mitosis they could, surprisingly, re-enter S-phase of the cell division cycle. Ethidium bromide caused little or no effect on nuclear DNA content compared to the H2O (vehicle) control (Figs 6d and 7c,d and Supplementary Fig. S8). Compound 1 has a “delayed killing” effect on T. brucei Compound 1 cured trypanosome infection in the mouse model of acute HAT (Fig. 3) whereas 30 h incubation with 200 nM of the drug arrested proliferation of T. brucei in vitro (Supplementary Fig. S4). To explain these data, we hypothesized that exposure of trypanosomes to 1 could lead to “delayed killing” of the cells after removal of drug from culture medium. To test this theory, an experiment was designed to best mimic conditions of detectable parasitemia and reasonable drug exposure in a mouse infection. We used 5 × 105 trypanosomes/mL and 1 μM of compound 1, because the maximum concentration of 1 observed in mouse blood plasma (Cmax) was 2.25 μM after a single oral dose of 30 mg/kg (Supplementary Fig. S3 and Supplementary Table S1). Trypanosomes were treated with 1 (1 μM) for 6 h after which the drug was washed off, trypanosomes were seeded in fresh medium and incubated for 48 h, eight division cycles (Fig. 8). Following 6 h compound 1 treatment, wash off, and 48 h incubation in drug-free medium, control cells treated with DMSO proliferated, whereas all 1-treated trypanosomes died (Fig. 8b,c). We concluded that trypanosomes are damaged irreversibly within hours of exposure to 1. Delayed killing effects were restricted to trypanosomes because no such effects on HeLa proliferation were observed under similar experimental conditions (Supplementary Fig. S9). Discussion Drugs currently used to treat HAT are in great need of improvement1. Unfortunately, because HAT is a disease of poverty, discovering better drugs against the disease is not suited for expensive research by major pharmaceutical companies38. In this study, we employed a “drug repurposing” strategy78 to establish 1 as a lead for anti-trypanosome drug discovery. By comparing compounds with matching substituents at R3, R4, and/or R5 we observed that replacing cyclopentanones with acetyl groups or other chemical structures at R1 or R2 always reduced the anti-trypanosomal activity of the compound (e.g. compare 5 to CBL0252 to 1, Fig. 1a). Overall, these observations supported the significance of a rotationally-restricted cyclopentanone ring in enhancing anti-trypanosomal features. Cyclopentanone rings provided an electron-withdrawing effect, a hydrogen-bond acceptor, hydrophobicity, and steric restriction. Restraint of the rotation posed by the cyclopentanone ring may have placed the carbonyl group oxygen atom(s) at an ideal orientation for better interaction with the compound’s target(s) of action, when compared to the Class 1 and 2 analogs. Finally, the importance of R1 and R2 on drug potency was illustrated best by CBL0139 and CBL0144 (Fig. 1c). Both compounds contained a nitrogen within the carbazole ring system with no attached substituent, and they were both inactive (GI50 > 10 μM) against T. brucei. The use of proliferation inhibition assays for hit discovery (Supplementary Fig. S1) is standard for identifying anti-trypanosomal compounds263039. Moreover, there has been a recent emphasis on identifying compounds that kill T. brucei rather than inhibit proliferation40. However, as our work suggests, proliferation inhibition is not always the best indicator of drug efficacy in the mouse model of HAT. For example, 2 and 3 had excellent GI50 values that were less than 10 nM (Table 1). However, 2 and 3 failed to cure T. brucei infection in mice (Fig. 2). Conversely, 1 had relatively less impressive anti-proliferative activity (Table 1). Yet it was 1 that cured a trypanosome infection in mice (Fig. 3). One possible explanation for these results is that varying toxicity of different analogs in mice limits how much drug can be administered to clear the infection without killing the mouse (Supplementary Fig. S2). Studies investigating the mode of action of our lead compound, 1, revealed that the principal biological effect was inhibition of mitosis (Figs 4 and 5, Supplementary Figs S5 and S6). However, it is not possible to completely exclude other effects contributing to trypanosome death. Compound 1 treatment led to a build-up of 2K1N and XK1N cells (Fig. 4c) and blocked trypanosome proliferation (Supplementary Fig. S4). The population of cells with 2C DNA was depleted, and instead most trypanosomes had 4C and 8C DNA (Fig. 6c). Together, these data indicated that trypanosomes were unable to execute mitosis, failed to undergo cytokinesis and they re-entered S-phase marked by (i) synthesis of chromosomal DNA, and (ii) production of new kinetoplasts. Consistent with these concepts, detection of trypanosomes with 8C DNA content was concurrent with appearance of XK1N at 18 h (Figs 4c and 6c). Mitosis inhibition accompanied by ongoing DNA synthesis (both nuclear and mitochondrial) has been reported in bloodstream form (BSF) T. brucei following knockdown of select protein kinases or cyclins4142. Although compound 1 is a non-genotoxic DNA intercalator in a human cell17, we failed to detect it in trypanosome nuclei using the published conditions. However, the ability to inhibit mitosis and not DNA replication argues against compound 1 principally acting as a DNA intercalator in T. brucei. Instead, compound 1 could target proteins. Compound 1 is a carbazole, some of which bind proteins121617184344454647484950. So it is possible that compound 1 has a protein target in trypanosomes. Three protein kinases (Cdc-2 related kinase 3 (CRK3), Aurora kinase 1 (AUK1) and tousled-like kinase 1 (TLK1)) are of interest as possible targets of 1 because they regulate both nuclear DNA replication and mitosis. Knockdown of CRK351, AUK152 or TLK153 in bloodstream T. brucei results in build-up of 2K1N cells with 4C DNA content. Most strikingly, sustained knockdown of AUK1 led to an accumulation of trypanosomes with 8C DNA content, a single enlarged nucleus, and multiple kinetoplasts similar to the XK1N trypanosomes observed after 1 treatment (Supplementary Fig. S6). CRK3 and TLK1 knockdown also produced an XK1N population, however, effects on DNA content above 4C were not reported. Mitotic arrest preceding overreplication of DNA has been observed in select vertebrate cells either as a natural process (i.e., differentiation) or induced by drug treatment. In (i) “mitotic slippage” or (ii) endoreplication, human glioma cells treated with nocodazole54, or megakaryocytes undergoing endoreplication55565758, arrest at mitosis but continue to synthesize DNA. In summary, we have found that the carbazole compound 1 is an orally bioavailable lead for anti-trypanosome drug discovery, and established its mode of action: it blocks mitosis but allows licensing of chromosomal and kinetoplast DNA replication. Carbazoles such as carprofen and other carbazole derivatives are being evaluated as leads for drugs to treat human neurodegenerative disorders1213141516. Additionally, some carbazole derivatives are active against other protozoan parasites, such as Leishmania donovani59, and Plasmodium falciparum6061. Thus, carbazoles are a promising chemical scaffold for “repurposing” in an effort to discover new and better anti-trypanosomal drugs. Additional Information How to cite this article: Thomas, S. M. et al. Discovery of a Carbazole-Derived Lead Drug for Human African Trypanosomiasis. Sci. Rep. 6, 32083; doi: 10.1038/srep32083 (2016). Supplementary Material Supplementary Information We thank Alex Adjei (Mayo Clinic) who initiated the collaboration between the Mensa-Wilmot laboratory and Cleveland BioLabs, Inc. We thank Julie Nelson (University of Georgia, UGA) and Justin Wiedeman (UGA) for invaluable technical support for data collection/analysis. We thank Paul Guyett (UGA) and Catherine Sullenberger (UGA) for helpful discussion and advice. Incuron, LLC (Moscow, Russian Federation) performed the pharmacokinetic analysis. Work in the Mensa-Wilmot lab was supported by grant R21AI098998 from the National Institute of Health. Dedicated to the memory of Martin John Rogers (1960–2014). John inspired drug discovery in academia through his enthusiasm and commitment to excellence as a program officer for Tropical Diseases at NIAID (National Institutes of Health). John, you are missed greatly: we will continue your legacy and make you proud. Author Contributions Conceived and designed the experiments: S.M.T., A.P. and K.M.-W. Performed the experiments: S.M.T. Analyzed the data: S.M.T., M.P., A.P. and K.M.-W. Wrote the paper: S.M.T., M.P. and K.M.-W. Figure 1 Inhibition of T. brucei proliferation: Exploratory Structure-Activity Relationship (SAR). T. brucei (4 × 103 cells/mL) in 24-well or 96-well plates were incubated with DMSO or compound (various concentrations) for 48 h. The amount of drug that inhibits trypanosome proliferation 50% (GI50) was determined for each compound. Mean GI50 were determined from two independent experiments (totaling four separate biological replicates) within +/− standard deviation. (a) SAR of Class 1 (R1 and R2 = acetyl groups), Class 2 (R1 = acetyl group, R2 = cyclopentanone), and Class 3 (R1 and R2 = cyclopentanone). (b) Class 1, 2 or 3 structures with hydroxyls at R4 and/or R5. (c) Other compounds not qualified as Class 1, 2 or 3. *For CBL0209 we do not know which E/Z isomers were tested. Figure 2 Compounds 2 and 3 reduce trypanosome proliferation in mice. Mice (n = 4 per group) were infected intraperitoneally with 1 × 104 bloodstream T. brucei. Compound 2, 3 and vehicle were administered orally as indicated in graphs. Doses administered of compound 2: 5 mg/kg, 10 mg/kg and 20 mg/kg. Doses administered of compound 3: 6.25 mg/kg, 12.5 mg/kg and 25 mg/kg (a) Mean survival of vehicle and compound treated mice. Horizontal lines indicate mean survival (days). Student’s t-test was used to compare survival of vehicle to drug-treated mice. *P < 0.0007. (b,c) Parasitemia of 2 (b) or 3 (c) treated mice compared to vehicle. Individual mice are represented by different symbol shapes. Horizontal lines indicate median parasitemia. Figure 3 Compound 1 cures T. b. brucei infection in a mouse model of HAT. Mice (n = 4 per group) were infected intraperitoneally with 1 × 104 bloodstream T. brucei. Compound 1 (30 mg/kg or 40 mg/kg) and vehicle were administered orally once per day of treatment for a total of 14 doses. (a) Number of mice alive post-infection. *All remaining mice were cured of trypanosome infection. (b,c) Parasitemia in mice dosed with vehicle or 30 mg/kg of compound 1 (b) or 40 mg/kg of compound 1 (c). Individual mice are represented by different symbol shapes. Horizontal lines indicate median parasitemia. UND = parasitemia undetectable. Mouse (♦) died on day 16 post-infection, no parasitemia observed prior to death (data not presented). *All remaining mice were cured of trypanosome infection. Figure 4 Summary of effects of compound 1 and ethidium bromide on trypanosome nucleus and kinetoplast copy number. Results summarized from Supplementary Fig. S5. (a) DMSO-treated, (b) H2O-treated, (c) 1-treated, (d) ethidium bromide-treated. Mean percentage of cells +/− standard deviation were determined from three independent experiments. Figure 5 Effects of 24 h compound 1 treatment on trypanosome nucleus and kinetoplast copy number. T. brucei (1 × 105 cells/mL) were treated with 1 (200 nM), ethidium bromide (200 nM), H2O, or DMSO (0.1% vol/vol) for 24 h as part of a 30 h time-course in HMI-9 medium (Supplementary Fig. S5). Cells were fixed with paraformaldehyde (4% in PBS) and DNA was stained with DAPI (1.5 μM). (a,c) Representative images of 24 h treated cells. Panels = Left: DIC (differential interference contrast), middle: DAPI (red), right: Merge. Bar = 10 μm. (b,d) Nuclei (N) and kinetoplasts (K) were counted from 150 cells for each sample. 1K1N, trypanosomes with one kinetoplast/one nucleus; 2K1N, trypanosomes with two kinetoplasts/one nucleus; 2K2N, trypanosomes with two kinetoplasts/two nuclei; 0K1N, trypanosomes without visible kinetoplasts/one nucleus; XK1N, trypanosomes with more than two kinetoplasts/one nucleus. Mean percentage of cells +/− standard deviation were determined from three independent experiments. Student’s t-test was used to compare organelle copy number distribution of vehicle (DMSO or H2O) to drug-treated trypanosomes. *P < 0.05, determined by Student’s t-test. Figure 6 Summary of effects of compound 1 and ethidium bromide on nuclear DNA content. Results summarized from Supplementary Figs S7 and S8. (a) DMSO-treated, (b) H2O-treated, (c) 1-treated, (d) ethidium bromide-treated. Mean percentage of cells +/− standard deviation were determined from three independent experiments. Figure 7 Effects of 24 h compound 1 treatment on nuclear DNA content. T. brucei (105 cells/mL) were treated with 1 (200 nM), ethidium bromide (200 nM), H2O, or DMSO (0.1% vol/vol) for 24 h as part of a 30 h time-course in HMI-9 medium (Supplementary Figs S7 and S8). Cells were fixed with PBS containing 70% methanol, treated with RNase A (500 μg/mL) and DNA was stained with propidium iodide (7.5 μM). (a,c) Histograms of DNA content per cell. 10,000 trypanosomes were analyzed per sample. Chromosomal content (e.g. “2C”) is indicated for each peak. (b,d) Proportion of cells with DNA content from 2C–8C. Mean percentage of cells +/− standard deviation were determined from three independent experiments. *P < 0.05, determined by Student’s t-test comparing DNA content of vehicle (DMSO or H2O) to drug-treated trypanosomes. Figure 8 Delayed killing effects of Compound 1 on T. brucei. T. brucei (5 × 105 cells/mL) were treated with 1 (1 μM) or DMSO (0.1% vol/vol) for 6 h. Cells were washed twice with HMI-9 medium, resuspended at 1 × 105 cells/mL, and cultured for 48 h. Trypanosome densities were determined with a hemocytometer. (a) Flow chart summarizing trypanosome treatment and recovery protocol prior to analysis. (b) Cell density before (“Start”) and after 6 h treatment with DMSO or 1 (1 μM). (c) Cell density after wash and resuspension at 1 × 105 cell/mL (“Start”) and after 48 h incubation in drug-free medium. Mean cell density (values above each bar) ± standard deviation is presented from two independent experiments, four separate biological replicates. “” indicates no cells observed. Table 1 Selectivity Index of hits. Cmpd Growth inhibition (GI50) ± SD (nM) Selectivity Index T. b. rhodesiense T. b. brucei HeLa HL GI50/Tbb GI50 1 58 ± 3 55 ± 7 2100 ± 50 38 2 13 ± 3 7.4 ± 0.2 580 ± 100 78 3 3.6 ± 0.3 2.2 ± 0.1 520 ± 40 236 Proliferation inhibition of compounds against T. b. brucei, T. b. rhodesiense and human HeLa (HL) cells. T. brucei (4 × 103 cells/mL) in 24-well plates were incubated with DMSO (0.1% vol/vol) or compound (various concentrations) for 48 h. The amount of drug that inhibits trypanosome proliferation 50% (GI50) was determined for each compound. Mean GI50 ± standard deviation was determined from two independent experiments, four separate biological replicates. ==== Refs WHO. Control and surveillance of human African trypanosomiasis . WHO Technical Report Series 984 , 1 –237 (2013 ).24552089 Brun R. , Blum J. , Chappuis F. & Burri C. Human African trypanosomiasis . Lancet 375 , 148 –159 , 10.1016/s0140-6736(09)60829-1 (2010 ).19833383 Kaiser M. . Antitrypanosomal activity of fexinidazole, a new oral nitroimidazole drug candidate for treatment of sleeping sickness . Antimicrob Agents Chemother 55 , 5602 –5608 , 10.1128/aac.00246-11 (2011 ).21911566 Jacobs R. T. . SCYX-7158, an orally-active benzoxaborole for the treatment of stage 2 human African trypanosomiasis . PLoS Negl Trop Dis 5 , e1151 , 10.1371/journal.pntd.0001151 (2011 ).21738803 Jannin J. & Cattand P. Treatment and control of human African trypanosomiasis . Curr Opin Infect Dis 17 , 565 –571 (2004 ).15640711 Maser P. . Antiparasitic agents: new drugs on the horizon . Curr Opin Pharmacol 12 , 562 –566 , 10.1016/j.coph.2012.05.001 (2012 ).22652215 Gelb M. H. . Protein farnesyl and N-myristoyl transferases: piggy-back medicinal chemistry targets for the development of antitrypanosomatid and antimalarial therapeutics . Mol Biochem Parasitol 126 , 155 –163 (2003 ).12615314 Ashburn T. T. & Thor K. B. Drug repositioning: identifying and developing new uses for existing drugs . Nat Rev Drug Discov 3 , 673 –683 , 10.1038/nrd1468 (2004 ).15286734 Behera R. , Thomas S. M. & Mensa-Wilmot K. New Chemical Scaffolds for Human African Trypanosomiasis Lead Discovery from a Screen of Tyrosine Kinase Inhibitor Drugs . Antimicrob Agents Chemother 58 , 2202 –2210 , 10.1128/aac.01691-13 (2014 ).24468788 Pollastri M. P. & Campbell R. K. Target repurposing for neglected diseases . Future medicinal chemistry 3 , 1307 –1315 , 10.4155/fmc.11.92 (2011 ).21859304 Patel G. . Kinase scaffold repurposing for neglected disease drug discovery: discovery of an efficacious, lapatinib-derived lead compound for trypanosomiasis . J Med Chem 56 , 3820 –3832 , 10.1021/jm400349k (2013 ).23597080 Favia A. D. . Identification and characterization of carprofen as a multitarget fatty acid amide hydrolase/cyclooxygenase inhibitor . J Med Chem 55 , 8807 –8826 , 10.1021/jm3011146 (2012 ).23043222 De Jesus-Cortes H. . Neuroprotective efficacy of aminopropyl carbazoles in a mouse model of Parkinson disease . Proc Natl Acad Sci USA 109 , 17010 –17015 , 10.1073/pnas.1213956109 (2012 ).23027934 Yoon H. J. . Aminopropyl carbazole analogues as potent enhancers of neurogenesis . Bioorg Med Chem 21 , 7165 –7174 , 10.1016/j.bmc.2013.08.066 (2013 ).24095011 Pieper A. A. , McKnight S. L. & Ready J. M. P7C3 and an unbiased approach to drug discovery for neurodegenerative diseases . Chem Soc Rev 43 , 6716 –6726 , 10.1039/c3cs60448a (2014 ).24514864 Saturnino C. . N-alkyl carbazole derivatives as new tools for Alzheimer’s disease: preliminary studies . Molecules 19 , 9307 –9317 , 10.3390/molecules19079307 (2014 ).24991761 Gasparian A. V. . Curaxins: anticancer compounds that simultaneously suppress NF-kappaB and activate p53 by targeting FACT . Science translational medicine 3 , 95 –74 , 10.1126/scitranslmed.3002530 (2011 ). Carter D. R. . Therapeutic targeting of the MYC signal by inhibition of histone chaperone FACT in neuroblastoma . Science translational medicine 7 , 312ra176 , 10.1126/scitranslmed.aab1803 (2015 ). Incuron. A Phase I Trial of CBL0137 in Patients With Metastatic or Unresectable Advanced Solid Neoplasm or Refractory Lymphomas. http://clinicaltrials.gov/show/NCT01905228. Date of Access: 2015 Dec 15 (2013). Tucker J. . Inventors; Cleveland BioLabs, Inc., assignee. Carbazole compounds and therapeutic uses of the compounds. World Patent WO 2010/042445 A1. Apr 15 2010. Nwaka S. & Hudson A. Innovative lead discovery strategies for tropical diseases . Nature reviews. Drug discovery 5 , 941 –955 (2006 ).17080030 Hirumi H. & Hirumi K. Axenic culture of African trypanosome bloodstream forms . Parasitology Today 10 , 80 –84 , 10.1016/0169-4758(94)90402-2 (1994 ).15275508 Leal S. . Virulence of Trypanosoma brucei strain 427 is not affected by the absence of glycosylphosphatidylinositol phospholipase C . Mol Biochem Parasitol 114 , 245 –247 (2001 ).11378204 Bacchi C. J. . Differential susceptibility to DL-alpha-difluoromethylornithine in clinical isolates of Trypanosoma brucei rhodesiense . Antimicrob Agents Chemother 34 , 1183 –1188 (1990 ).2118325 Katiyar S. . Lapatinib-binding protein kinases in the african trypanosome: identification of cellular targets for kinase-directed chemical scaffolds . PloS one 8 , e56150 , 10.1371/journal.pone.0056150 (2013 ).23437089 Kaminsky R. & Brun R. In vitro assays to determine drug sensitivities of African trypanosomes: a review . Acta Tropica 54 , 279 –289 , 10.1016/0001-706x(93)90100-p (1993 ).7902665 Huber W. & Koella J. C. A comparison of three methods of estimating EC50 in studies of drug resistance of malaria parasites . Acta Tropica 55 , 257 –261 (1993 ).8147282 Kaba S. I. & Egorova E. M. In vitro studies of the toxic effects of silver nanoparticles on HeLa and U937 cells . Nanotechnology, science and applications 8 , 19 –29 , 10.2147/nsa.s78134 (2015 ). Ekwall B. & Johansson A. Preliminary studies on the validity of in vitro measurement of drug toxicity using HeLa cells. I. Comparative in vitro cytotoxicity of 27 drugs . Toxicology letters 5 , 299 –307 (1980 ).7385251 Faria J. . Drug discovery for human African trypanosomiasis: identification of novel scaffolds by the newly developed HTS SYBR Green assay for Trypanosoma brucei . Journal of biomolecular screening 20 , 70 –81 , 10.1177/1087057114556236 (2015 ).25342146 Bacchi C. J. . Cure of murine Trypanosoma brucei rhodesiense infections with an S-adenosylmethionine decarboxylase inhibitor . Antimicrob Agents Chemother 36 , 2736 –2740 (1992 ).1482141 Nare B. . Discovery of Novel Orally Bioavailable Oxaborole 6-Carboxamides That Demonstrate Cure in a Murine Model of Late-Stage Central Nervous System African Trypanosomiasis . Antimicrob. Agents Chemother. 54 , 4379 –4388 , 10.1128/aac.00498-10 (2010 ).20660666 Magez S. , Radwanska M. , Beschin A. , Sekikawa K. & De Baetselier P. Tumor necrosis factor alpha is a key mediator in the regulation of experimental Trypanosoma brucei infections . Infect Immun 67 , 3128 –3132 (1999 ).10338530 Bouteille B. . Effect of megazol on Trypanosoma brucei brucei acute and subacute infections in Swiss mice . Acta Trop 60 , 73 –80 (1995 ).8610542 Worthen C. , Jensen B. C. & Parsons M. Diverse effects on mitochondrial and nuclear functions elicited by drugs and genetic knockdowns in bloodstream stage Trypanosoma brucei . PLoS Negl Trop Dis 4 , e678 , 10.1371/journal.pntd.0000678 (2010 ).20454560 Nwaka S. . Advancing drug innovation for neglected diseases-criteria for lead progression . PLoS Negl Trop Dis 3 , e440 , 10.1371/journal.pntd.0000440 (2009 ).19707561 Roy Chowdhury A. . The killing of African trypanosomes by ethidium bromide . PLoS Pathog 6 , e1001226 , 10.1371/journal.ppat.1001226 (2010 ).21187912 DiMasi J. A. , Hansen R. W. & Grabowski H. G. The price of innovation: new estimates of drug development costs . Journal of health economics 22 , 151 –185 , 10.1016/s0167-6296(02)00126-1 (2003 ).12606142 Bowling T. , Mercer L. , Don R. , Jacobs R. & Nare B. Application of a resazurin-based high-throughput screening assay for the identification and progression of new treatments for human African trypanosomiasis . International journal for parasitology. Drugs and drug resistance 2 , 262 –270 , 10.1016/j.ijpddr.2012.02.002 (2012 ).24533287 De Rycker M. . A Static-Cidal Assay for Trypanosoma brucei to Aid Hit Prioritisation for Progression into Drug Discovery Programmes . PLoS Negl Trop Dis 6 , e1932 , 10.1371/journal.pntd.0001932 (2012 ).23209868 Hammarton T. C. Cell cycle regulation in Trypanosoma brucei . Mol Biochem Parasitol 153 , 1 –8 , 10.1016/j.molbiopara.2007.01.017 (2007 ).17335918 Li Z. Regulation of the cell division cycle in Trypanosoma brucei . Eukaryotic cell 11 , 1180 –1190 , 10.1128/ec.00145-12 (2012 ).22865501 Bertolacci L. . A binding site for nonsteroidal anti-inflammatory drugs in fatty acid amide hydrolase . Journal of the American Chemical Society 135 , 22 –25 , 10.1021/ja308733u (2013 ).23240907 Boeckler F. M. . Targeted rescue of a destabilized mutant of p53 by an in silico screened drug . Proc Natl Acad Sci USA 105 , 10360 –10365 , 10.1073/pnas.0805326105 (2008 ).18650397 Koman I. E. . Targeting FACT complex suppresses mammary tumorigenesis in Her2/neu transgenic mice . Cancer prevention research (Philadelphia, Pa.) 5 , 1025 –1035 , 10.1158/1940-6207.capr-11-0529 (2012 ). Nakamura K. . Antitumor activity of ER-37328, a novel carbazole topoisomerase II inhibitor . Mol Cancer Ther 1 , 169 –175 (2002 ).12467211 Shapiro B. A. , Ray S. , Jung E. , Allred W. T. & Bollag W. B. Putative conventional protein kinase C inhibitor Godecke 6976 [12-(2-cyanoethyl)-6,7,12,13-tetrahydro-13-methyl-5-oxo-5H-indolo(2,3-a)pyrrolo(3.4-c)-carbazole] stimulates transglutaminase activity in primary mouse epidermal keratinocytes . The Journal of pharmacology and experimental therapeutics 302 , 352 –358 (2002 ).12065737 Smaill J. B. . Synthesis and structure-activity relationships of N-6 substituted analogues of 9-hydroxy-4-phenylpyrrolo[3,4-c]carbazole-1,3(2H,6H)-diones as inhibitors of Wee1 and Chk1 checkpoint kinases . European journal of medicinal chemistry 43 , 1276 –1296 , 10.1016/j.ejmech.2007.07.016 (2008 ).17869387 Wang G. . P7C3 neuroprotective chemicals function by activating the rate-limiting enzyme in NAD salvage . Cell 158 , 1324 –1334 , 10.1016/j.cell.2014.07.040 (2014 ).25215490 Yin Z. . DNA replication is the target for the antibacterial effects of nonsteroidal anti-inflammatory drugs . Chemistry & biology 21 , 481 –487 , 10.1016/j.chembiol.2014.02.009 (2014 ).24631121 Tu X. & Wang C. C. The involvement of two cdc2-related kinases (CRKs) in Trypanosoma brucei cell cycle regulation and the distinctive stage-specific phenotypes caused by CRK3 depletion . J Biol Chem 279 , 20519 –20528 , 10.1074/jbc.M312862200 (2004 ).15010459 Jetton N. . The cell cycle as a therapeutic target against Trypanosoma brucei: Hesperadin inhibits Aurora kinase-1 and blocks mitotic progression in bloodstream forms . Mol Microbiol 72 , 442 –458 , 10.1111/j.1365-2958.2009.06657.x (2009 ).19320832 Lindsay M. E. , Gluenz E. , Gull K. & Englund P. T. A new function of Trypanosoma brucei mitochondrial topoisomerase II is to maintain kinetoplast DNA network topology . Mol Microbiol 70 , 1465 –1476 , 10.1111/j.1365-2958.2008.06493.x (2008 ).19019151 Tsuiki H. . Mechanism of hyperploid cell formation induced by microtubule inhibiting drug in glioma cell lines . Oncogene 20 , 420 –429 , 10.1038/sj.onc.1204126 (2001 ).11313973 De Veylder L. , Larkin J. C. & Schnittger A. Molecular control and function of endoreplication in development and physiology . Trends in plant science 16 , 624 –634 , 10.1016/j.tplants.2011.07.001 (2011 ).21889902 Zanet J. . A mitosis block links active cell cycle with human epidermal differentiation and results in endoreplication . PloS One 5 , e15701 , 10.1371/journal.pone.0015701 (2010 ).21187932 Geddis A. E. & Kaushansky K. Megakaryocytes express functional Aurora-B kinase in endomitosis . Blood 104 , 1017 –1024 , 10.1182/blood-2004-02-0419 (2004 ).15130946 Vitrat N. . Endomitosis of human megakaryocytes are due to abortive mitosis . Blood 91 , 3711 –3723 (1998 ).9573008 Brendle J. J. . Antileishmanial activities of several classes of aromatic dications . Antimicrobial agents and chemotherapy 46 , 797 –807 (2002 ).11850264 Molette J. . Identification and optimization of an aminoalcohol-carbazole series with antimalarial properties . ACS medicinal chemistry letters 4 , 1037 –1041 , 10.1021/ml400015f (2013 ).24900603 Erath J. . Small-molecule xenomycins inhibit all stages of the Plasmodium life cycle . Antimicrob Agents Chemother 59 , 1427 –1434 , 10.1128/aac.04704-14 (2015 ).25512429

PMC005xxxxxx/PMC5000475.txt

==== Front BMC Public HealthBMC Public HealthBMC Public Health1471-2458BioMed Central London 356610.1186/s12889-016-3566-zResearch ArticleDeterminants of timely initiation of complementary feeding among mothers with children aged 6–23 months in Lalibela District, Northeast Ethiopia, 2015 Sisay Wondimu womsisay@gmail.com 1Edris Melkie melkiey2004@yahoo.com 2Tariku Amare amaretariku15@yahoo.com 21 Department of Reproductive and Child Health, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia 2 Department of Human Nutrition, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia 25 8 2016 25 8 2016 2016 16 1 88427 10 2015 20 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Optimal complementary feeding alone prevents six percent of child mortality, but it has continued to be considered as sub-optimal in Ethiopia. Therefore, this study aimed to assess timely initiation of complementary feeding and associated factors among mothers with children aged 6–23 months in Lalibela District. Methods A community-based cross-sectional study was conducted from March 01 to April 29, 2015. Four hundred twenty-one mother-child pairs were selected by the systematic random sampling technique. An interviewer-administered questionnaire was used to collect data. A multivariable logistic regression analysis was employed to identify factors associated with timely initiation of complementary feeding. The Adjusted Odds Ratio (AOR) with a 95 % Confidence Interval (CI) was computed to assess the strength of association, and variables with a P-value of <0.05 were considered as statistically significant in the multivariable analysis. Results The study demonstrated that, the prevalence of timely initiation of complementary feeding was 63 %. In addition, mother’s education [AOR = 4.33, 95 % CI: 1.99, 9.40], antenatal care follow up [AOR = 5.90, 95 % CI: 2.45, 14.21], and institutional delivery [AOR = 2.54, 95 % CI: 1.33, 4.82] were found key determinants of timely initiation of complementary feeding. Conclusion In this community, timely initiation of complementary feeding was lower than the World Health Organization cut-off point for good practice of complementary feeding. Therefore, intensifying utilization of antenatal care and institutional delivery helps to improve the coverage of timely initiation of complementary feeding. Furthermore, the focus needs to be on uneducated women. Keywords Complementary feedingChildren aged 6–23 monthsDeterminantsNortheast Ethiopiaissue-copyright-statement© The Author(s) 2016 ==== Body Background Around the age of 6 months, infant needs for energy and micronutrients start to exceed what is provided by breast milk. They are developmentally ready to initiate additional (complementary) food, which is necessary to meet their extra energy and micronutrient requirement [1]. In addition, the transition period (6 months to 2 years) is part of the ‘critical window of opportunity’ to enhance the survival and optimal growth of the child [2]. Thus, the World Health Organization (WHO) recommends that mothers should initiate soft, semi-solid, or solid food to their infants at the age of 6 months [3]. Infants and young children bear the heaviest burden of undernutrition and continue to suffer from disability and death associated with it [4]. Globally, undernutrition results in 3 million child deaths annually and this amounts to 45 % of all causes of mortality. Over two-thirds of these deaths are often associated with inappropriate feeding practice and occur during the first year of life [5, 6]. Sub-optimal breastfeeding results in more than 800,000 deaths annually [6] and is also a significant determinant of childhood undernutrition [7, 8]. On the other hand, optimal breastfeeding prevents 13 % of the deaths occurring in children under five, and appropriate complementary feeding results in an additional six percent reduction [9]. Nevertheless, global complementary feeding practice has been sub-optimal. Among South Asian countries, the rate of timely initiation of complementary feeding is lower than the WHO recommendation for good practice (80–94 %) [10]. In this regard, about 71 %, 70 %, 55 %, and 39 % of the infants in Bangladesh, Nepal, India, and Pakistan, respectively, are reported to have timely initiation of complementary feeding [8, 10–12]. On the other hand, there is a low rate of timely initiation of complementary feeding in Africa [1, 13]. In Ethiopia, more than half (57 %) of the child mortality occurs mainly due to undernutrition [14], and the majority of the children have had sub-optimal feeding practices. Only51% of the infants aged 6–9 months receive complementary food [15]. Furthermore, studies from different regions of the country show a low rate of timely initiation of complementary feeding (52.8–62.8 %) [16–18]. The determinants of timely initiation of complementary feeding vary between settings mainly depending on the level of health care utilization and socio-demographic characteristics. Reports from different countries reveal that, child sex, mothers wealth status, marital status, maternal and paternal education, maternal age (≥30 years), exposure to media, and knowledge about the right time for initiation of complementary feeding [11, 18–23], Antenatal Care (ANC) follow up, postnatal care, and institutional delivery [8, 11, 18, 20, 21, 23] are the commonly reported determinants of timely initiation of complementary feeding. In order to reduce the high burden of child malnutrition and mortality in Ethiopia [15], ensuring appropriate Infant and Young Child Feeding (IYCF) practices is of vital importance. The country has implemented the IYCF strategy for a decade [24], so, studies showing complementary feeding practices have a paramount significance in evaluating the progress of interventions aiming to address inappropriate child feeding practices. However, such studies are scarce in Ethiopia, particularly in the northeastern part of the country. Therefore, this study aimed to assess the timely initiation of complementary feeding and its determinants among mothers with children aged 6–23 months in Lalibela District, northeast Ethiopia. Methods Study design and setting A community-based cross-sectional study was conducted from March 01 to April 29, 2015, in Lalibela District, northeast Ethiopia. The district is one of the historical tourist destinations registered by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) as a world wonder site. Lalibela District, which is 700 km from Addis Ababa, the capital city of Ethiopia, has two urban and one rural kebeles (smallest administration units in Ethiopia). According to the 2014/15 District Finance and Economic Development Office annual statistical report, the total population of the district was 31,491, of which children aged 6–23 months comprised 4.39 % (1065). The total number of households in the district was estimated at 7323. At the moment, one district hospital, one health center, two urban and one rural health posts were providing health services to the community. Sample size and sampling procedure All mothers with children aged 6–23 months and have lived in the three kebeles of Lalibela District for at least 6 months were eligible for the study. The sample size was determined using single population proportion formula by considering the following assumptions: 52.8 % as a proportion of mothers practicing timely initiation of complementary feeding [18]; 5 % margin of error, and 95 % confidence level. In addition, a 10 % non-response rate which gives the final sample size of 421was anticipated. Information regarding the total number of households with eligible children was obtained from the District Health Office. The number of households sampled from the three kebeles of the district was proportionate-to-population size. A systematic random sampling technique was used to select individual households with eligible children. A sampling interval was calculated by dividing the total number of mothers who had children aged 6–23 months during the study period by the allocated sample size. For households with multiple children, one child was selected using the lottery method. Data collection tools and procedures A structured interviewer-administered questionnaire was used to collect data. To maintain consistency, the questionnaire was first translated from English to Amharic (the native language of the study area) and was back-translated to English by professional translators. Six female clinical nurses and two health officers who were not working in the actual study area were recruited as data collectors and supervisors, respectively. Training was given to data collectors and supervisors for 2 days on basic skills of interview, ways of obtaining consent, and on how to maintain confidentiality of information. The investigators oversaw all data collection activities. The completion, accuracy, and clarity of the collected data were checked carefully on daily basis. A pre-test was administered on 5 % (21) of the sample out of the study area. During the pre-test, the acceptability and applicability of the procedures and tools were evaluated, but the result of the pre-test was not included for analysis. Complementary feeding practices were assessed according to the key indicators recommended by WHO [3]. Accordingly, the outcome variable (timely initiation of complementary feeding) was confirmed by asking the mothers to recall the age at which they initiated additional food to [child’s name], and were asked “When did you first introduce any solid, semi-solid, or fluid to [child’s name] in addition to breast milk”. Then, if the mother answered “at the sixth month”, it was categorized as timely initiation of complementary feeding and coded as “1”, but if she had initiated beyond (before or after) the sixth month, it was considered as untimely initiation of complementary feeding and was coded as “0”. In addition, a single visit was made to gather data regarding complementary feeding practices and other characteristics. For a few mothers who faced difficulties in remembering the right time of initiation of complementary feeding, data collectors carried out different probing mechanisms to help them recall, thereby minimizing recall bias. Relating the time of initiation to known public events, occurrences of common childhood developmental milestones, and immunization schedules were some of the probing techniques used by data collectors. Moreover, to minimize the social desirability bias, data collectors created a conducive environment by keeping mothers apart and making them comfortable during data collection. The standardized Dietary Diversity Score (DDS) tool with a 24 h recall was used to qualitatively assess the dietary intake of children. Mothers were asked to list the food items consumed by the children in the previous 24 h preceding the date of survey. The food items were categorized into seven food groups, such as starchy staples (grains, roots, and tubers), legumes and nuts, dairy products, flesh food (meat, fish, poultry, and organ meat), egg, vitamin-A rich fruits and vegetables, and other fruits and vegetables. By considering the minimum acceptable DDS, a child having a DDS of ≥4 was categorized as good dietary diversity, but if it had a DDS of <4, it was considered as poor dietary diversity [3]. The independent variables included in the study were mainly related to the parents’ socio-demographic and economic characteristics (age, education, employment, household wealth, religion, household size, and marital status), and health-care related information (ANC, place of delivery, postnatal care, frequency of health extension visits, and mothers’ knowledge and source of information about the right time for initiation of complementary feeding). Accordingly, to determine their knowledge about the right time for initiation of complementary feeding, the mothers were asked such a key question as “What is the appropriate time to start additional food for a child in addition to breastfeeding?”. If the mother said “at the sixth month”, she was considered as having accurate information about the right time for initiation of complementary feeding; otherwise, she was deemed to have inaccurate information. The Household Wealth Index was computed using a composite indicator by considering properties, such as livestock ownership, selected household assets, and size of agricultural land. Principal Component Analysis was performed to categorize household wealth status into poor, medium, and rich. Data analysis The collected data were entered into the EPI-Info version 7 software, and transferred, cleaned, coded, and analyzed using Statistical package for Social Science (SPSS) version 20. Descriptive statistics, including frequencies, proportions, means, and standard deviations were used to summarize the variables. A binary logistic regression was used to identify the determinants of timely initiation of complementary feeding. A bivariable analysis was done to show the crude effect of each independent variable on the outcome variable. Variables with a P-value of <0.2 in the bivariable analysis were entered to a multivariable logistic regression analysis. Stepwise backward Likelihood Ratio (LR) was used for multivariable logistic regression. The Adjusted Odds Ratio (AOR) with a 95 % Confidence Interval (CI) was computed to assess the strength of association, and a P-value of <0.05 was used to declare the statistical significance in the multivariable analysis. Results Socio-demographic and economic characteristics A total of 421 mother-child pairs were included in the study. The mean age (±Standard Deviation, SD) of the children was 14.87(±4.73) months. The majority of the respondents (95.2 %) were Orthodox Christians and 83.4 % of them were married. All of the participants were Amhara by ethnicity. More than half (52.3 %) of the children were male, and nearly one-third (27.8 %) were in the age range of 6 to 11 months. About 28.5 % of the mothers had no formal education, and more than half (59.9 %) were housewives (Table 1).Table 1 Socio-demographic and economic characteristics of mothers with children aged 6-23 months in Lalibela District, northeast Ethiopia, 2015 Variables Frequency Percent Child age in months  6–11 117 27.8  12–17 150 35.6  18–23 154 36.6 Sex of child  Female 201 47.7  Male 220 52.3 Relationship of care giver to the child  Mother 413 98.1  Other a 8 1.9 Maternal age  15–24 120 28.5  25–34 216 51.3   > 34 85 20.2 Maternal religion  Orthodox 401 95.2  Other b 20 4.8 Maternal marital status  Currently married 351 83.4  Currently unmarried c 70 16.6 Maternal education  Uneducated 120 28.5  Primary school 106 25.2  Secondary school and above 195 46.3 Maternal occupation  Employed d 70 16.6  Housewife 252 59.9  Others e 99 23.5 Paternal education  Uneducated 105 30.0  Primary school 51 14.5  Secondary school and above 195 55.5 Paternal occupation  Employed 163 38.7  Merchant 58 13.8  Farmer 51 12.1  Unemployed 79 18.8 Family size  2–3 155 36.8  4–6 245 58.2   > 6 21 5.0 Possession of microfinance bank account  Yes 251 59.6  No 170 40.4 Wealth status  Poor 139 33.0  Medium 189 44.9  Rich 93 22.1 a Grandmother and sister b Muslim and protestant c Single, divorced, widowed d Governmental and non-governmental employees e Student, farmer, unemployed, merchant, daily laborer Maternal health care related characteristics Nearly three-fourths (74.1 %) of the mothers had at least one ANC visit for the index child, of which about 81.7 % had 3 to 4 visits. Nearly two-thirds (63.4 %) of them gave birth at health institutions, and about one-quarter (25.4 %) had postnatal care (Table 2).Table 2 Maternal health care and child feeding practices in Lalibela District, northeast Ethiopia, 2015 Variables Frequency Percent Antenatal care (413)  Yes 306 74.1  No 107 25.9 Frequency of antenatal care visits  1–2 times 30 9.8  3–4 times 250 81.7   ≥ 5 times 26 8.5 Place of delivery (413)  Health facility 262 63.4  Home 151 36.6 Postnatal visit (413)  Yes 105 25.4  No 308 74.6 Frequency of feeding per day (n = 411)  1–2 times 94 22.3  3 times 190 45.1   ≥ 4 times 127 30.2 Dietary diversity score (n = 411)  Poor 360 87.6  Good 51 12.4 Type of food at first time of weaning  Gruel 385 91.4  Porridge 364 86.5  Cow milk 112 26.6  Powder milk 50 11.9  Others a 12 3.3 Information on TICF b  Accurate information 248 58.9  Inaccurate information 173 41.1 Source of information on TICF  Health extension workers 350 83.1  Health care professionals 302 71.7  Television and radio 151 35.8  Community health worker 23 5.5 Since ten children didn’t initiate complementary feeding until the date of survey, the total number of children within variables for feeding frequency and dietary diversity is not 421 a Tea, sugar water and juice b Time for initiation of complementary feeding Complementary feeding practices The prevalence of timely initiation of complementary feeding was 63 % [95 % Cl: 58.0, 67.5 %]. One hundred eighteen children (28.0 %) started complementary feeding after sixth months, while twenty-eight (6.7 %) were initiated before they reached the sixth month. In addition, ten children (2.3 %) were offered no additional food since they have been born. Nearly two-thirds (58.9 %) of the mothers had accurate information about the right time of initiation of complementary feeding. The majority (87.6 %) of the children had poor dietary diversity, and below half (45.1 %) ate three times a day (Table 2). Factors associated with timely initiation of complementary feeding In the bivariable analysis, maternal education, occupation, marital status, wealth status, paternal education and occupation, possession of television, ANC follow up, place of delivery, postnatal care, and health extension visits in the past 6 months were significantly associated with timely initiation of complementary feeding. However, the result of the multivariable analysis showed that maternal educational status, ANC follow-up, and place of delivery were significantly and independently associated with timely initiation of complementary feeding. Accordingly, the likelihood of timely initiation of complementary feeding among children whose mothers attended primary school [AOR = 3.39, 95 % CI: 1.52, 7.54] and secondary school and above [AOR = 4.33, 95 % CI: 1.99, 9.40] was higher compared to that of uneducated mothers. Moreover, increased odds of timely initiation of complementary feeding were noted among mothers who had ANC follow up [AOR = 5.90, 95 % CI: 2.45, 14.21] compared to those had no ANC follow up. Similarly, the odds of timely initiation of complementary feeding were higher among mothers who gave birth at health facilities [AOR = 2.54, 95 % CI: 1.33, 4.82] as compared to those who gave birth at home (Table 3).Table 3 Factors associated with timely initiation of complementary feeding among mothers with children aged 6–23 months in Lalibela District, northeast Ethiopia, 2015 Variables Timely initiation of complementary feeding COR c(95 % CI) AOR d(95 % CI) Yes# No# Maternal age  25–34 140 76 0.92(0.58,1.48)   > 34 45 40 0.56 (0.32,0.99)  15–24 80 40 1 Maternal marital status  Currently married 228 123 1.65(0.99,2.78)  Currently unmarried 37 33 1 Maternal education  Illiterate 41 79 1  Primary school 63 43 2.82(1.64,4.85) 3.39(1.52,7.54) b  Secondary school and above 161 34 9.12(5.38,15.48) 4.33 (1.99, 9.40) b Maternal occupation  Employed 55 15 2.3 (1.25, 4.36)  Others 56 43 0.83 (0.57, 1.32)  Housewife 154 98 1 Wealth status  Poor 71 68 1  Medium 145 44 3.16 (1.97,5.07)  Rich 49 44 1.07 (0.63,1.80) Paternal education  Illiterate 45 60 1  Primary school 31 20 2.07(1.05, 4.09)  Secondary school and above 152 43 4.71(2.82, 7.88) Paternal occupation  Employed 121 42 2.55(1.59, 4.11)  Merchant 40 18 1.97(1.04, 3.74)  Farmer 25 26 0.85(0.45, 1.61)  Unemployed 79 70 1 Owning television  Yes 141 45 2.81(1.84, 4.28)  No 124 111 1 Antenatal care  Yes 245 61 21.26(11.80,38.33) 5.9(2.45,14.21) b  No 17 90 1 1 Place of delivery  Yes 206 56 6.24 (4.01,9.72) 2.54(1.33,4.82) b  No 56 95 1 1 Postnatal care  Yes 80 25 2.22(1.34,3.67)  No 182 126 1 Health extension visits a  No visit 10 21 1  1–2 times 85 69 2.59 (1.14,5.86)  3–4 times 147 60 5.15 (2.29,11.57)   ≥ 5 times 23 6 8.05 (2.49,25.99) a health extension visits were determined based on the number of visits made during the past 6 months preceding the date of survey b significant at a P-vale of <0.05 c Crude Odds Ratio d Adjusted Odds Ratio Discussion The result of this study revealed that the prevalence of timely initiation of complementary feeding was 63 %. This finding was lower than the WHO cut-off point (80 % to 94 %) for good practice of complementary feeding [10]. Similarly, it was lower than the reports from Abyi-Adi, Ethiopia (79.7 %) [25], India (77.5 %) [26], and Bangladesh (71 %) [27]. The higher prevalence of timely initiation of complementary feeding in the latter study areas could be related to the improvements in utilization of ANC and institutional delivery. Hence, nutrition education and counseling are components of maternal health care services; a higher utilization of these services will bring an added benefit to improve mothers’ awareness on appropriate child feeding practices [25]. However, our finding was higher than that of the 2011 Ethiopian Demographic Health Survey report (51 %) [15] and the report from northern Ethiopia (52.8 %) [18]. This is probably related to the current improvements in the implementation of the Health Extension Program. Health extension workers are making home to home visits on regular bases to support families in accessing basic health services and to give home-based health education as well as other promotion services, including promotion of appropriate IYCF. Compared to the current finding, a lower prevalence of timely initiation of complementary feeding was reported from Nigeria (41 %) [13] and India (55.7 %) [12]. This discrepancy could be attributed to differences in sample sizes between the two study areas, as more mothers were surveyed in India than in this study. Though the sample size was lower in Nigeria, a lower practice of timely initiation of complementary feeding could be related to the variation in mothers’ working environments; in Nigeria, most of the mothers were working outside the home, while most mothers were housewives in Ethiopia. It was affirmed that mothers working outside their home were more likely to return to work before they exclusively breastfed their infants for the recommended duration, 6 months [28–30]. As a result, they would be forced to initiate complementary feeding to their infants earlier than housewife mothers. The result of the adjusted analysis showed that the odds of timely initiation of complementary feeding were higher among educated mothers as compared to their uneducated counterparts. Parallel findings were reported by studies elsewhere [16–18, 25, 31]. This could be due to the fact that education has an immense benefit in promoting the optimal maternal nutrition and health seeking behavior [15]. In addition, other studies persistently claimed that mothers’ education has a profound effect on children’s nutritional status and caring practice [15, 32–34]. Higher odds of timely initiation of complementary feeding were observed among mothers who visited ANC as compared to those who did not. This finding was in agreement with other reports in Ethiopia [16–18, 25]. Obviously, pregnancy has been considered as an important window of opportunity to deliver nutrition counseling and education on IYCF [35]. Nutrition education and counseling have a pivotal role in enhancing mothers’ IYCF knowledge and practice and maternal self-efficacy in child care [36–38]. Mothers who delivered at health institutions were more likely to initiate complementary feeding at the right time (sixth month) as compared to those who gave birth at home. The finding was supported by reports elsewhere [16–28]. Mothers who give birth at health institutions have a better opportunity to access appropriate child feeding information, which ultimately improves their capacity to challenge unfavorable attitudes of the community [35, 39]. The previous reports also claimed that institutional delivery was found to increase the likelihood of exclusive breastfeeding for 6 months, indicating timely initiation of complementary feeding [28, 40, 41]. On the other hand, home birthing is associated with inappropriate neonatal feeding practices, such as discarding colostrum and giving prelacteal feeds [42–44]. The investigators made a lot of effort to maintain the quality of the data, mainly through a pretest, frequent field supervisions, and training of data collectors. However, the study was not free from some limitations. First, since the estimation of some of the variables, including health extension visits, was made through recall (with the longest recall period of 6 months), there might have been a risk of recall bias. Secondly, the study did not consider the measurement of some of the independent variables, like type of nutrition services received during ANC and postnatal care visits, and mothers’ attitude towards appropriate breastfeeding and complementary feeding which might confound the result of the study. Thirdly, the study was not free from the pitfalls of a cross-sectional study design. Conclusion This study revealed that, the prevalence of timely initiation of complementary feeding was low; it was by far lower than the WHO cut-off point for good practice of complementary feeding. Mother’s educational status, ANC follow up, and institutional delivery were significantly associated with timely initiation of complementary feeding. Therefore, current efforts should be strengthened to improve optimal complementary feeding practices by stepping-up the utilization of ANC and institutional delivery. The focus needs to be on uneducated women. Furthermore, future studies should emphasize mixed methods, such as triangulating with a qualitative study design and prospective study designs to identify key barriers of timely initiation of complementary feeding. Abbreviations AORAdjusted Odds Ratio CORCrude Odds Ratio WHOWorld Health Organization ANCAntenatal care CIConfidence interval IYCFInfant and young child feeding DDSDietary Diversity Score SDStandard deviation UNESCOUnited Nations Educational, Scientific, and Cultural Organization Acknowledgements Authors would like to thank all respondents for their willingness to participate in the study. They are also grateful to the Lalibela District Health Office and the University of Gondar for material and financial support, respectively. Finally, authors’ appreciation goes to Mr. Demeke Dessu for his unreserved professional contribution in copyediting the document. Funding This study was funded by Lalibela District Health Office and the University of Gondar. The views presented in the article are of the author and not necessarily express the views of the funding organization. Lalibela District Health Office and the University of Gondar were not involved in the design of the study, data collection, analysis and interpretation. Availability of data and materials Data will be available upon request from the corresponding authors. Authors’ contribution WS conceived the study, coordinated the overall activity, and carried out the statistical analysis. ME participated in the design of the study, and drafted the manuscript. AT participated in the design of the study, performed the statistical analysis, and drafted the manuscript. All authors read and approved the final manuscript. Competing interest Authors declare that they have no conflict of interest. Consent for publication Not applicable. Ethics approval and consent to participate Ethical clearance was obtained from the Ethical Review Board of the University of Gondar. A letter of permission was secured from the Lalibela District Health Office prior to the actual data collection. All mothers were informed about the purpose of the study, and interview was held only with those who agreed to give verbal consent to participate. The right of a participant to withdraw from the study at any time, without any precondition was disclosed unequivocally. Moreover, the confidentiality of information obtained was guaranteed by all data collectors and investigators by using code numbers rather than personal identifiers and by keeping the questionnaire locked. ==== Refs References 1. WHO Indicators for assessing infant and young child feeding practices PArt 3 Country Profiles 2010 2. Khanal V Sauer K Zhao Y Determinants of complementary feeding practices among Nepalese children aged 6–23 months: findings from demographic and health survey 2011 BMC Pediatr 2013 13 1 1 10.1186/1471-2431-13-131 23281628 3. World Health Organization Indicators for assessing infant and young child feeding practices: part 1: definitions: conclusions of a consensus meeting held 6-8 November 2007 in Washington DC, USA 2008 4. UNICEF WHO Planning guide for national implementation of the Global Strategy for Infant and Young Child Feeding 2007 5. WHO, UNICEF: Global strategy for infant and young child feeding. Geneva: World Health Organization; Geneva, Switzerland. 2003. 6. Black R, Alderman H, Bhutta Z, Gillespie S, Haddad L, Horton S: Executive Summary of The Lancet Maternal and Child Nutrition Series. Maternal and Child Nutrition Study Group (eds), Maternal and Child Nutrition 2013:1-12. 7. UNICEF WHO Strengthening action to improve feeding of infants and young children 6-23 months of age in nutrition and child health programmes: report of proceedings, Geneva 2008 8. Khan ME Donnay F Tarigopula UK Aruldas K Shaping demand and practices to improve family health outcomes: findings from a quantitative survey 2013 New Delhi Population Council 9. Jones G Steketee RW Black RE Bhutta ZA Morris SS Group BCSS How many child deaths can we prevent this year? Lancet 2003 362 9377 65 71 10.1016/S0140-6736(03)13811-1 12853204 10. WHO A tool for assessing national practices, policies and programmes Infant and Young Child Feeding 2003 11. Saleh F Ferdous Ara M Hoque A Alam MS Complementary feeding practices among mothers in selected slums of Dhaka city: a descriptive study J Health Popul Nutr 2014 32 1 89 24847597 12. Sinhababu A Mukhopadhyay DK Panja TK Saren AB Mandal NK Biswas AB Infant-and young child-feeding practices in Bankura district, West Bengal, India J Health Popul Nutr 2010 28 3 294 299 20635641 13. Ogunlesi T Ayeni V Adekanmbi A Fetuga B Determinants of timely initiation of complementary feeding among children aged 6‑24 months in Sagamu, Nigeria Niger J Clin Pract 2015 17 6 785 790 10.4103/1119-3077.144399 25385920 14. Save the children Ethiopia Ethiopia national nutrition strategy, review and analysis of progress and gaps: one year on 2009 15. Ethiopia CSA, Macro I: Ethiopia demographic and health survey 2011. Addis Ababa, Ethiopia and Calverton, Maryland, USA: Central Statistical Agency (Ethiopia) and ICF International 2012. 16. Semahegn A Tesfaye G Bogale A Complementary feeding practice of mothers and associated factors in Hiwot Fana Specialized Hospital, Eastern Ethiopia Pan Afr Med J 2014 18 143 10.11604/pamj.2014.18.143.3496 25419281 17. Shumey A Demissie M Berhane Y Timely initiation of complementary feeding and associated factors among children aged 6 to 12 months in Northern Ethiopia: an institution-based cross-sectional study BMC Public Health 2013 13 1 1050 10.1186/1471-2458-13-1050 24195592 18. Yemane S Awoke T Gebreslassie M Timely initiation of complementary feeding practice and associated factors among mothers of children aged from 6 to 24 months in Axum town, north Ethiopia Int J Nutr Food Sci 2014 3 5 438 442 10.11648/j.ijnfs.20140305.21 19. Agedew E, Demissie M, Misker D, Haftu D: Early Initiation of Complementary Feeding and Associated Factors among 6 Months to 2 Years Young Children, in Kamba Woreda, South West Ethiopia: A Community–Based Cross-Sectional Study. J Nutr Food Sci. 2014;4(6):314. doi:10.4172/2155-9600.1000314. 20. Kimani-Murage EW Madise NJ Fotso J-C Kyobutungi C Mutua MK Gitau TM Yatich N Patterns and determinants of breastfeeding and complementary feeding practices in urban informal settlements, Nairobi Kenya BMC Public Health 2011 11 1 1 10.1186/1471-2458-11-396 21199570 21. Mihrshahi S Kabir I Roy S Agho KE Senarath U Dibley MJ Network SAIFR Determinants of infant and young child feeding practices in Bangladesh: secondary data analysis of Demographic and Health Survey 2004 Food Nutr Bull 2010 31 2 295 313 10.1177/156482651003100220 20707235 22. Senarath U Agho KE Akram De S Godakandage SS Hazir T Jayawickrama H Joshi N Kabir I Khanam M Patel A Comparisons of complementary feeding indicators and associated factors in children aged 6–23 months across five South Asian countries Matern Child Nutr 2012 8 s1 89 106 10.1111/j.1740-8709.2011.00370.x 22168521 23. Khanal V Sauer K Zhao Y Exclusive breastfeeding practices in relation to social and health determinants: a comparison of the 2006 and 2011 Nepal Demographic and Health Surveys BMC Public Health 2013 13 1 1 10.1186/1471-2458-13-958 24. Federal Ministry of Health Ethiopian National Strategy on infant and young child feeding 2004 25. Mekbib E Shumey A Ferede S Haile F Magnitude and factors associated with appropriate complementary feeding among mothers having children 6–23 months-of-age in Northern Ethiopia; A Community-Based Cross-Sectional Study J Food Nutr Sci 2014 2 2 36 26. Rao S Swathi P Unnikrishnan B Hegde A Study of complementary feeding practices among mothers of children aged six months to two years—a study from coastal south India Australas Med J 2011 4 5 252 257 10.4066/AMJ.2011.607 23393516 27. Kabir I Khanam M Agho KE Mihrshahi S Dibley MJ Roy SK Determinants of inappropriate complementary feeding practices in infant and young children in Bangladesh: secondary data analysis of Demographic Health Survey 2007 Matern Child Nutr 2012 8 s1 11 27 10.1111/j.1740-8709.2011.00379.x 22168516 28. Seid AM Yesuf ME Koye DN Prevalence of Exclusive Breastfeeding Practices and associated factors among mothers in Bahir Dar city, Northwest Ethiopia: a community based cross-sectional study Int Breastfeed J 2013 8 1 1 10.1186/1746-4358-8-14 23497501 29. Rez-Escamilla RP Lãoetter C Segall AM Rivera A Trevino-Siller S Sanghvf T Exclusive breast-feeding duration is associated with attitudinal, socioeconomic and biocultural determinants in three Latin American Countries J Nutr 1995 125 12 2972 84 7500175 30. Ogunba BO Effect of maternal employment on infant feeding practices in Southwestern Nigeria Food Nutr Sci 2015 6 07 597 10.4236/fns.2015.67063 31. Adnan N Muniandy ND The relationship between mothers’ educational level and feeding practices among children in Selected Kindergartens in Selangor, Malaysia: A Cross-sectional Study Asian J Clin Nutr 2012 4 2 39 10.3923/ajcn.2012.39.52 32. Tromp II Briede S Kiefte-de Jong J Renders C Jaddoe V Franco O Hofman A Raat H Moll H Factors associated with the timing of introduction of complementary feeding: the Generation R Study Eur J Clin Nutr 2013 67 6 625 630 10.1038/ejcn.2013.50 23462942 33. Liaqat P Rizvi MA Qayyum A Ahmed H Ishtiaq N Maternal education and complementary feeding Pak J Nutr 2006 5 6 563 568 10.3923/pjn.2006.563.568 34. Abuya BA Ciera J Kimani-Murage E Effect of mother’s education on child’s nutritional status in the slums of Nairobi BMC Pediatr 2012 12 1 1 10.1186/1471-2431-12-80 22208358 35. Wu Q Scherpbier RW van Velthoven MH Chen L Wang W Li Y Zhang Y Car J Poor infant and young child feeding practices and sources of caregivers’ feeding knowledge in rural Hebei Province, China: findings from a cross-sectional survey BMJ open 2014 4 7 e005108 10.1136/bmjopen-2014-005108 25079931 36. Manikyamba D Vidya D Satyavani A Prasad AK Deepthi KT Impact of nutritional education on the knowledge of mothers regarding infant and young child feeding practices Scholars J Appl Med Sci 2015 3 3A 1074 1078 37. Hackett KM Mukta US Jalal CS Sellen DW A qualitative study exploring perceived barriers to infant feeding and caregiving among adolescent girls and young women in rural Bangladesh BMC Public Health 2015 15 1 771 10.1186/s12889-015-2115-5 26259575 38. Kushwaha KP Sankar J Sankar MJ Gupta A Dadhich J Gupta Y Bhatt GC Ansari DA Sharma B Effect of peer counselling by mother support groups on infant and young child feeding practices: the Lalitpur experience PLoS One 2014 9 11 e109181 10.1371/journal.pone.0109181 25369452 39. Bahemuka GJ Munyanshongore C Birungi F Knowledge, attitudes and practices of exclusive breast-feeding of infants aged 0-6 months by Urban refugee women in Kigali 2013 40. Biks GA Tariku A Tessema GA Effects of antenatal care and institutional delivery on exclusive breastfeeding practice in northwest Ethiopia: a nested case–control study Int Breastfeed J 2015 10 1 1 10.1186/s13006-015-0055-4 25635183 41. Aidam BA Perez-Escamilla R Lartey A Aidam J Factors associated with exclusive breastfeeding in Accra, Ghana Eur J Clin Nutr 2005 59 6 789 96 10.1038/sj.ejcn.1602144 15870819 42. Bekele Y Mengistie B Mesfine F Prelacteal feeding practice and associated factors among mothers attending immunization clinic in Harari Region public health facilities, Eastern Ethiopia Open J Prev Med 2014 4 529 534 10.4236/ojpm.2014.47063 43. Legesse M Demena M Mesfin F Haile D Prelacteal feeding practices and associated factors among mothers of children aged less than 24 months in Raya Kobo district, North Eastern Ethiopia: a cross-sectional study Int Breastfeed J 2014 9 1 1 10.1186/s13006-014-0025-2 24422991 44. Legesse M Demena M Mesfin F Haile D Factors associated with colostrum avoidance among mothers of children aged less than 24 months in Raya Kobo district, North-eastern Ethiopia: community-based cross-sectional study J Trop Pediatr 2015 61 5 357 63 10.1093/tropej/fmv039 26141533

PMC005xxxxxx/PMC5000476.txt

==== Front BMC CancerBMC CancerBMC Cancer1471-2407BioMed Central London 271510.1186/s12885-016-2715-1Case ReportDermatomyositis with anti-TIF-1γ antibodies as a presenting symptom of underlying triple-negative breast cancer: a case report Kubeček Ondřej okubec@gmail.com 1Soukup Tomáš tomas.soukup@fnhk.cz 2Paulík Adam adam.paulik@fnhk.cz 1Kopecký Jindřich jindrich.kopecky@fnhk.cz 11 Department of Oncology and Radiotherapy, Charles University in Prague, Faculty of Medicine and University Hospital in Hradec Králové, Sokolská 581, 500 05 Hradec Králové, Czech Republic 2 2nd Department of Internal Medicine – Gastroenterology, Charles University in Prague, Faculty of Medicine and University Hospital in Hradec Králové, Sokolská 581, 500 05 Hradec Králové, Czech Republic 25 8 2016 25 8 2016 2016 16 1 68418 2 2016 11 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Dermatomyositis is an autoimmune myopathy characterized by proximal muscle weakness, muscle inflammation, and typical skin findings. It is a rare disease with an incidence of ~1/100 000. About 15–30 % of adult-onset cases are caused by underlying malignancy and dermatomyositis can be the first symptom of undiagnosed cancer, mainly in the case of anti-transcription intermediary factor 1γ (anti-TIF-1γ) antibodies presence. TIF-1γ is a transcriptional cofactor which is implicated in TGFβ signaling pathway that controls cell proliferation, differentiation, apoptosis, and tumorigenesis. Its expression was shown to be associated with younger age, higher tumor grade, more estrogen receptor negativity, tumors larger than 2 cm, and tendency towards poor outcome in early breast cancer. No association between anti-TIF-1γ antibodies and prognosis has been proposed yet. Case presentation We report a case of a 43-year-old premenopausal woman presenting with the symptoms of systemic rheumatic disease, the most prominent being a typical skin rash and muscle pain. After a series of investigations, the patient was diagnosed with anti-TIF-1γ positive dermatomyositis and concurrent triple-negative breast cancer (cT1c N3c M0) as an underlying cause. Immediate intravenous corticosteroid therapy relieved the symptoms and enabled anticancer therapy to be commenced. Considering the tumor stage, neoadjuvant therapy with 4 courses of AC (Doxorubicin/Cyclophosphamide) followed by 4 courses of Paclitaxel/Carboplatin was administered. However, no tumor regression was documented and radiotherapy was chosen as the definitive treatment. Conclusion Early detection of anti-TIF-1γ autoantibodies can contribute to a rapid diagnosis of tumor-associated dermatomyositis and enable immediate anticancer treatment. We demonstrate the emerging role of anti-TIF-1γ antibodies in the diagnostics of tumor-associated dermatomyositis. Furthermore, we propose a potential role of anti-TIF-1γ antibodies as a prognostic marker in early breast cancer patients. Keywords AutoantibodiesBreast cancerDermatomyositisParaneoplasticCase reportCharles University, Faculty of Medicine in Hradec Králové grant PRVOUK 37/06issue-copyright-statement© The Author(s) 2016 ==== Body Background Dermatomyositis (DM) together with polymyositis and inclusion body myositis belong to a group of acquired skeletal muscle diseases known as idiopathic inflammatory myopathies [1]. DM is considered an autoimmune disease. It may present with variously expressed clinical signs, the most prominent being characteristic rash and muscle weakness. The skin manifestations include heliotrope rash on the upper eye lids, erythematous rash localized on the face, neck, anterior chest, back, and large joints [2]. Gottron rash refers to violaceous rash or papules localized typically in metacarpophalangeal, and proximal or distal interphalangeal joints. Together with heliotrope rash, it is considered a specific cutaneous feature of the disease. Proximal muscle weakness usually develops slowly over weeks or months [3]. DM is associated with presence of specific autoantibodies which are usually divided into myositis specific autoantibodies (including anti-Mi-2, anti-CADM-140, anti-SAE, anti-p155/140 (anti-TIF-1γ), anti-MJ, anti-t-RNA synthetase, and anti-PMS1 antibodies) and myositis associated autoantibodies (including anti-Ro/SSA, anti-U1RNP, anti PM/Scl, and Anti-Ku antibodies) [4]. Recently, a remarkable association between several antibodies and specific clinical presentations have been found [5]. The majority of cases are idiopathic. However, in ~15–30 % of adult-onset cases, DM is associated with malignancy. Cancer may occur before, at the same time, or following the diagnosis of DM. DM that develops as a consequence of the tumor presence in the body is classified as paraneoplastic. The mechanism how malignancy induces DM is not clear yet. However, several possible mechanisms have been proposed. It has been demonstrated that some tumors, including breast adenocarcinoma, express high levels of myositis autoantigens [6]. These antigens can also be found in regenerating myoblasts in affected muscles from myositis patients. It is therefore possible that immune response directed against cancer cells cross-reacts with regenerating muscle cells and could therefore be responsible for the pathogenesis of DM [6]. The most common tumor types associated with DM include gynecological tumors (mainly ovarian cancer), lung, pancreatic, gastric, colorectal cancer, and non-Hodgkin’s lymphoma [7]. The most common tumor sites in men are lung, prostate, and stomach. This contrasts with DM in women, which is most frequently associated with tumors of breast, ovary, and uterus [8]. The spectrum of tumor types varies greatly across different regions. DM in Asian populations is, for example, more frequently associated with a nasopharyngeal cancer [9]. The first case of DM associated with breast cancer was reported in 1916 [10]. According to published population-based studies, breast cancer is diagnosed in ~10–20 % of malignancy-associated DM cases [8]. Triple-negative cancer is an intrinsic subtype of breast cancer. It is defined by the absence of estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor 2 (HER2) overexpression and/or gene amplification [11]. It accounts for 15–20 % of newly diagnosed breast cancer cases [12]. Typical features include younger age at diagnosis, poorer prognosis, and association with BRCA 1/2 mutations [12]. No data regarding the incidence of anti-TIF-1γ autoantibodies in triple-negative breast cancer has been published so far. Case presentation A forty-three-year-old premenopausal caucasian woman with no relevant medical history presented with intermittent fever, fatigue, myalgia, dysphagia, and erythematous rash lasting over 1 month. The nonpruritic macular rash was initially localized on the back of patient’s hands and was followed by eruption of erythema over patient’s face after 1 week. The onset of pruritic macular rash on lateral sites of patient’s thighs and upper part of back followed. The patient presented first to her dermatologist who treated her with topical steroids for 2 weeks. However, no clinical effect was observed. Considering the skin manifestation and other symptoms suspicious of a systemic rheumatic disease, the patient was referred to a rheumatologist. She was later admitted to a hospital to establish a diagnosis and commence treatment. The skin examination revealed a slight periorbital edema (Heliotrope rash) and erythematous rash localized over her cheeks and nasal bridge omitting the nasolabial sulcus. It was therefore resembling a typical malar rash in lupus erythematosus (Fig. 1). Erythematous hyperpigmented papules were found over the proximal and distal interphalangeal joints (Gottron’s sign). The pruritic maculopapular rash was also present on lateral sites of patient’s thighs and back (Figs. 2 and 3). V-sign, a typical distribution of macular exanthema on the front site of patient’s chest, was found (Fig. 4). The physical examination also revealed enlarged lymph nodes in her left axilla and supraclavicular region, which was further confirmed by ultrasound (Fig. 5), and painful swelling and enlargement of the whole left mammary gland.Fig. 1 Erythematous rash localized over the cheeks and nasal bridge omitting the nasolabial sulcus resembling a typical malar rash in lupus erythematosus Fig. 2 Maculopapular rash on lateral sites of patient’s thighs Fig. 3 Maculopapular rash on patient’s back Fig. 4 V-sign (macular exanthema on the front site of patient’s chest) Fig. 5 Ultrasound image of enlarged lymph node in the left axilla Blood investigations revealed raised erythrocyte sedimentation rate (ESR, 34 mm/h). C-reactive protein (CRP) was slightly elevated (12.4 mg/L). Serum muscle enzyme concentrations were also elevated - alanine aminotransferase (0.71 μkat/L), aspartate aminotransferase (1.38 μkat/L), creatine kinase (CK, 26.24 μkat/L), and myoglobin (267 μg/L). Electromyography revealed no pathological findings. Skin biopsy from the affected area was performed with negative lupus band test (direct immunofluorescence test for lupus erythematosus). The whole panel of autoantibodies was examined using immunoblot technique (Euroimmun, Euroline Autoimmune Inflammatory Myopathies 16 Ag) with only anti-TIF-1γ antibodies being positive. The probability of DM was evaluated > 90 % using the IMCCP (The International Myositis Classification Criteria Project) criteria [13]. Muscle biopsy is not mandatory in the presence of typical skin manifestations according to these criteria. Considering the high probability of DM, further supported by the presence of anti-TIF-1γ, a muscle biopsy was omitted. Because of the patient’s complains of dysphagia gastro-duodenoscopy was performed to exclude the upper gastrointestinal tract involvement. The finding was consistent with erosive antral gastritis with negative rapid urease test (rapid diagnostic test for Helicobacter pylori infection). Series of investigations were performed to exclude an extra-muscular involvement - ophthalmologic, otorhinolaryngologic, neurologic, cardiac and renal - all with negative findings. Tumor markers including CEA, CA 15–3, CA 125, and CA 19–9 were negative. Mammography was performed to exclude breast cancer as an underlying condition. The result, however, was equivocal (sporadic microcalcifications without any obvious tumor mass). Neither ultrasound of the abdomen nor chest x-ray showed any abnormality. Since the conventional investigations were not conclusive, a whole body PET/CT scan was performed to exclude malignancy. The scan showed FDG-avid lesion 19 × 14 mm in the left mammary gland, and multiple FDG-avid lymph nodes in the left axilla and under the pectoralis major muscle (Figs. 6 and 7).Fig. 6 PET/CT showing FDG-avid lesion 19 × 14 mm in the left mammary gland Fig. 7 PET/CT showing multiple FDG-avid lymph nodes in the left axilla and under the pectoralis major muscle Direct core cut biopsy was not feasible since there was no evident mass within the breast according to mammography. Extirpation of the left supraclavicular lymph node was therefore performed to obtain the histopathological specimen and confirm the diagnosis. Metastasis of poorly differentiated adenocarcinoma was reported (Fig. 8). Immunohistochemical assessment of steroid hormone status was performed. The expression of the estrogen and progesteron receptors, and HER-2/neu protein were all negative. Additional in situ hybridization (ISH) found no HER-2/neu amplification, thus confirming the diagnosis of the triple-negative breast cancer. The disease was staged as cT1c N3c M0. Genetic testing to exclude BRCA 1/2 mutation was advised, considering the patient’s age and histological type of breast cancer (triple-negative).Fig. 8 Light microscope image of lymph node infiltrated with metastasis of poorly differentiated adenocarcinoma (Haematoxylin and Eosin stain) The treatment of DM was initiated with intravenous pulse corticosteroid therapy (methylprednisolone 5 × 1000 mg alternate days), followed by oral corticosteroids. Initial daily dose of 32 mg of methylprednisolone was reduced by 8 mg every week to the maintenance dose of 8 mg/day. The muscle strength tended to deteriorate during the deescalation phase. This prompted the contemporary discontinuation of dose reduction, until muscle weakness improved (CK 1.03 μkat/L, myoglobin 25.5 μg/L). The symptoms of dysphagia and skin manifestation were promptly managed, enabling the anti-cancer therapy to be commenced. Considering both disease burden and histologic features, neoadjuvant chemotherapy was decided to be the option. The regimen containing 4 courses of doxorubicin 60 mg/m2 + cyclophosphamide 600 mg/m2 q3w followed by 4 courses paclitaxel 175 mg/m2 + carboplatin AUC 5 q3w was chosen. The patient continued with a maintenance dose of corticosteroids during the chemotherapy, which was well tolerated. However, the investigations following the last dose of chemotherapy (mammography, ultrasound of the breast and regional lymph nodes), did not show any signs of tumor regression. Surgery was still not feasible because of the supraclavicular and axillary lymph node persistence. Radiotherapy was therefore decided to be the option by the multidisciplinary board (including oncologist, breast surgeon and radiologist) in order to achieve local control. Primary chemoresistance of the tumor was an additional reason to support this approach. Discussion Cancer should always be considered as an underlaying cause of DM. Several risk factors have been proposed to be related with increased risk of malignancy in DM patients. An extensive meta-analysis of clinical trials found older age, male sex, dysphagia, cutaneous necrosis, cutaneous vasculitis, rapid onset (<4 weeks), elevated CK, higher ESR, and higher CRP as factors to be associated with higher risk [14]. Considering the high incidence of cancer in DM patients, it is the author’s opinion that every patient with DM should be thoroughly investigated to exclude the malignancy with an extra effort in patients bearing one or more of above named risk factors. The diagnosis of DM is traditionally based on five criteria published by Bohan and Peter in 1975: 1) Symmetric proximal muscle weakness, 2) Muscle biopsy evidence of myositis, 3) Increase in serum skeletal muscle enzymes, 4) Characteristic electromyographic patterns, and 5) Typical rash of dermatomyositis. Two of these criteria were present together with typical skin manifestation which made the diagnosis of DM probable in presented case [15]. However, these criteria seem to be inadequate in several aspect (e.g. including patients with some forms of muscle dystrophy). Novel criteria suitable to be used within clinical trials have therefore been proposed recently [13]. Using the IMCCP criteria (The International Myositis Classification Criteria Project) in our patient, the probability of DM was evaluated > 90 %. Anti-TIF-1γ antibodies were positive while anti-NXP-2 (anti-nuclear matrix protein NXP-2) antibodies were negative in presented patient. It has been shown that the presence of anti-TIF-1γ and anti-NXP-2 antibodies is frequent in DM patients [5]. These autoantibodies are present in most patients with cancer-associated DM (found in 83 % cases - 31 % anti-NXP-2 and 52 % anti-TIF-γ), which could make them a useful tool to identify patients with malignancy alongside the DM [5]. Furthermore, it was observed that these antibodies are almost exclusively non-overlapping and that the vast majority of individuals with positivity of either antibody is negative in other DM-specific or myositis-specific antibodies as observed in our patient [5]. Thus, the involvement of these antibodies in the primary diagnostics of DM could identify patients with otherwise negative autoantibodies. TIF-1γ is a transcriptional cofactor which is implicated in TGFβ signaling pathway that controls cell proliferation, differentiation, apoptosis and tumorigenesis [16]. Results of a study evaluating the role of TIF-1γ and its interaction with TGFβ1/SMAD4 signaling pathway as a prognostic factor in operable breast cancer have been published recently [17]. TIF-1γ expression was shown to be associated with younger age, higher tumor grade, more estrogen receptor (ER) negativity, and tumors larger than 2 cm [17]. Furthermore, TIF1γ expression showed tendency towards poor outcome. The subgroup of patients expressing both TGFβ1 and TIF1γ showed the poorest outcome in the studied population [17]. We propose that if the correlation of serum anti-TIF-1γ antibodies and TIF-1γ expression in the tumor was found, the anti-TIF-1γ antibodies might serve as a potential prognostic marker in early breast cancer patients. DM is considered a potentially treatable disease. Systemic corticosteroids remain a mainstay in therapy. Oral prednisone at initial dose of 0.5–1 mg/kg/day should be given as initial therapy, followed by a slow progressive dose reduction not earlier than 6 weeks after the myositis has become inactive (clinically and enzymatically) [18]. In severe cases, intravenous methylprednisolone is the treatment option [19]. Some patients, however, do not respond to corticosteroids or develop serious side effects. In such cases, introduction of immunosuppressive agents is recommended. The most widely used drugs include methotrexate, azathioprine, cyclophosphamide or cyclosporin A [3]. The surgical removal of the tumor or anti-cancer treatment may itself result in disappearance or reduction of the paraneoplastic symptoms [20]. Methylprednisolone pulse therapy seems to relieve dysphagia in DM patients [21]. This finding together with urgency to achieve a rapid response was the reason to choose the initial pulse corticotherapy. The symptoms of the disease were managed soon after making the diagnosis and the patient was ready to begin the anti-cancer treatment without undue delay. Conclusions DM can be the first symptom of previously undiagnosed malignancy. When confirming the diagnosis of DM, malignancy should always be excluded. The anti-TIF-1γ and anti-NXP-2 antibodies may play an essential role in rapid diagnosis of malignancy associated DM, especially in patients bearing several risk factors known to be associated with malignancy. Considering the fact that individuals with positivity of either of these antibodies are very frequently negative in other DM-specific and myositis-specific antibodies, their assessment within primary diagnostics might be beneficial to identify patients with otherwise negative antibodies. Proper management of DM, including the use of intravenous corticosteroids, is essential to enable early cancer treatment. Maintenance corticosteroid therapy does not interfere with chemotherapy administration and can provide control of the rheumatic disease during cancer treatment. Furthermore, we propose that anti-TIF-1γ antibodies might serve as a prognostic marker of worse clinical outcome in early breast cancer provided correlation between serum anti-TIF-1γ antibodies and TIF-1γ expression in the tumor is found. Abbreviations AUCArea under the curve CEACarcinoembryonic antigen CKCreatine kinase CRPC-reactive protein DMDermatomyositis EREstrogen receptor ESRErythrocyte sedimentation rate FDGFluorodeoxyglucose HER2Human epidermal growth factor receptor 2 IMCCPThe International Myositis Classification Criteria Project ISHIn situ hybridization pCRPathologic complete response PET/CTPositron emission tomography-computed tomography PgRProgesteron receptor TGFβTransforming growth factor β TIF-1γTranscription intermediary factor 1γ Acknowledgements We thank Dr. Tomáš Rozkoš, The Fingerland Department of Pathology, University Hospital Hradec Králové, Hradec Králové, CZ, for providing the histopathological study of the patient’s lymph node infiltrated with the adenocarcinoma. Funding This work was supported by the Charles University Faculty of Medicine in Hradec Králové grant PRVOUK 37/06. Availability of data and materials The data supporting the conclusions of this article will not be shared publicly provided they include confidential information related to the patient. All data are stored within the Hospital Information System of the Hradec Králové University Hospital and their faithfulness can be verified upon request. Authors’ contributions OK and TS collected clinical data and drafted the manuscript. OK, TS, AP and JK participated in the interpretation of data and provided comments to the manuscript. All authors have read and approved the manuscript of this case report. Competing interests The authors declare that they have no competing interests. Consent for publication Written informed consent was obtained from the patient for publication of this Case report and any accompanying images. A copy of the written consent is available for review by the Editor of this journal. Ethics approval and consent to participate Not applicable. ==== Refs References 1. Dalakas MC Polymyositis, dermatomyositis and inclusion-body myositis N Engl J Med 1991 325 21 1487 1498 10.1056/NEJM199111213252107 1658649 2. Dalakas MC Hohlfeld R Polymyositis and dermatomyositis Lancet 2003 362 9388 971 982 10.1016/S0140-6736(03)14368-1 14511932 3. Callen JP Wortmann RL Dermatomyositis Clin Dermatol 2006 24 5 363 373 10.1016/j.clindermatol.2006.07.001 16966018 4. Iaccarino L Ghirardello A Bettio S Zen M Gatto M Punzi L Doria A The clinical features, diagnosis and classification of dermatomyositis J Autoimmun 2014 48–49 122 127 10.1016/j.jaut.2013.11.005 24467910 5. Fiorentino DF Chung LS Christopher-Stine L Zaba L Li S Mammen AL Rosen A Casciola-Rosen L Most patients with cancer-associated dermatomyositis have antibodies to nuclear matrix protein NXP-2 or transcription intermediary factor 1gamma Arthritis Rheum 2013 65 11 2954 2962 10.1002/art.38093 24037894 6. Casciola-Rosen L Nagaraju K Plotz P Wang K Levine S Gabrielson E Corse A Rosen A Enhanced autoantigen expression in regenerating muscle cells in idiopathic inflammatory myopathy J Exp Med 2005 201 4 591 601 10.1084/jem.20041367 15728237 7. Hill CL Zhang Y Sigurgeirsson B Pukkala E Mellemkjaer L Airio A Evans SR Felson DT Frequency of specific cancer types in dermatomyositis and polymyositis: a population-based study Lancet 2001 357 9250 96 100 10.1016/S0140-6736(00)03540-6 11197446 8. Barnes BE Mawr B Dermatomyositis and malignancy. A review of the literature Ann Intern Med 1976 84 1 68 76 10.7326/0003-4819-84-1-68 1106291 9. Peng JC Sheen TS Hsu MM Nasopharyngeal carcinoma with dermatomyositis. Analysis of 12 cases Arch Otolaryngol Head Neck Surg 1995 121 11 1298 1301 10.1001/archotol.1995.01890110072013 7576478 10. Kankeleit H Über primäre nichteitrige Polymyositis Dtsch Arch Klin Med 1916 120 335 349 11. Reis-Filho JS Tutt AN Triple negative tumours: a critical review Histopathology 2008 52 1 108 118 10.1111/j.1365-2559.2007.02889.x 18171422 12. Bauer KR Brown M Cress RD Parise CA Caggiano V Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: a population-based study from the California cancer Registry Cancer 2007 109 9 1721 1728 10.1002/cncr.22618 17387718 13. Pilkington C Tjärnlund A, Bottai M, Werth V, Visser M, Alfredsson L, Amato A, Barohn RJ, Liang M, Singh J et al.: Progress report on development of classification criteria for adult and juvenile idiopathic inflammatory myopathies. Pediatric Rheumatology 2014 12 Suppl 1 94 14. Lu X Yang H Shu X Chen F Zhang Y Zhang S Peng Q Tian X Wang G Factors predicting malignancy in patients with polymyositis and dermatomyostis: a systematic review and meta-analysis PLoS One 2014 9 4 e94128 10.1371/journal.pone.0094128 24713868 15. Bohan A Peter JB Polymyositis and dermatomyositis (first of two parts) N Engl J Med 1975 292 7 344 347 10.1056/NEJM197502132920706 1090839 16. Wakefield LM Piek E Bottinger EP TGF-beta signaling in mammary gland development and tumorigenesis J Mammary Gland Biol Neoplasia 2001 6 1 67 82 10.1023/A:1009568532177 11467453 17. Kassem L Deygas M Fattet L Lopez J Goulvent T Lavergne E Chabaud S Carrabin N Chopin N Bachelot T TIF1gamma interferes with TGFbeta1/SMAD4 signaling to promote poor outcome in operable breast cancer patients BMC Cancer 2015 15 453 10.1186/s12885-015-1471-y 26040677 18. Oddis CV Therapy of inflammatory myopathy Rheum Dis Clin North Am 1994 20 4 899 918 7855328 19. Marie I Mouthon L Therapy of polymyositis and dermatomyositis Autoimmun Rev 2011 11 1 6 13 10.1016/j.autrev.2011.06.007 21740984 20. Racanelli V Prete M Minoia C Favoino E Perosa F Rheumatic disorders as paraneoplastic syndromes Autoimmun Rev 2008 7 5 352 358 10.1016/j.autrev.2008.02.001 18486921 21. Hrncir Z Favorable effect of methylprednisolone pulse therapy in dysphagia and primary idiopathic polymyositis/dermatomyositis Cas Lek Cesk 1992 131 13 399 401 1504995

PMC005xxxxxx/PMC5000477.txt

==== Front BMC Pregnancy ChildbirthBMC Pregnancy ChildbirthBMC Pregnancy and Childbirth1471-2393BioMed Central London 103810.1186/s12884-016-1038-1Research ArticleThis baby is not for turning: Women’s experiences of attempted external cephalic version Watts N. P. nicole.watts@uts.edu.au 1Petrovska K. karolina.petrovska@student.uts.edu.au 1Bisits A. Andrew.bisits@sesiahs.health.nsw.gov.au 2http://orcid.org/0000-0001-7352-2879Catling C. christine.catling@uts.edu.au 1Homer C. S. E. caroline.homer@uts.edu.au 11 Centre for Midwifery, Child and Family Health, Faculty of Health, University of Technology Sydney, Sydney, Australia 2 Royal Hospital for Women, Sydney, Australia 26 8 2016 26 8 2016 2016 16 1 24810 12 2015 11 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Existing studies regarding women’s experiences surrounding an External Cephalic Version (ECV) report on women who have a persistent breech post ECV and give birth by caesarean section, or on women who had successful ECVs and plan for a vaginal birth. There is a paucity of understanding about the experience of women who attempt an ECV then plan a vaginal breech birth when their baby remains breech. The aim of this study was to examine women’s experience of an ECV which resulted in a persistent breech presentation. Methods A qualitative descriptive exploratory design was undertaken. In-depth semi-structured interviews were conducted and analysed thematically. Results Twenty two (n = 22) women who attempted an ECV and subsequently planned a vaginal breech birth participated. Twelve women had a vaginal breech birth (55 %) and 10 (45 %) gave birth by caesarean section. In relation to the ECV, there were five main themes identified: ‘seeking an alternative’, ‘needing information’, ‘recounting the ECV experience’, ‘reacting to the unsuccessful ECV’ and, ‘reflecting on the value of an ECV’. Conclusions ECV should form part of a range of options provided to women, rather than a default procedure for management of the term breech. For motivated women who fit the safe criteria for vaginal breech birth, not being subjected to a painful experience (ECV) may be optimal. Women should be supported to access services that support vaginal breech birth if this is their choice, and continuity of care should be standard practice. Keywords External cephalic versionBreech presentationPregnancyQualitative researchCaesarean sectionThe study was supported by a small scholarship grant from the Australian College of Midwives, New South Wales branch.issue-copyright-statement© The Author(s) 2016 ==== Body Background The optimal mode of birth for women who have a baby in the breech position at term is controversial. Since the Term Breech Trial [1], the availability of planned vaginal breech birth has diminished [2]. In Australia, in 2012, 87 % babies in the breech position were born by caesarean section (CS) [3]. In an attempt to reduce the need for CS for breech, external cephalic version (ECV) has become a popular, safe practice and is recommended for women who have a straightforward pregnancy with a breech presentation near term [4–8]. The procedure is offered to women from around 36 weeks gestation with success at early or late gestation being equivocal [9]. Success rates for ECVs are reported between 40 and 60 % [10]. As such, an ECV has been identified as a potential way to reduce CS rates [11] although consideration of the subsequent care for women whose babies remain breech is important. There are few studies about a woman’s experience surrounding an ECV and her subsequent preference for mode of birth [12–14]. These report on the experiences of women who have a persistent breech post ECV and then gave birth by CS, or on women who had successful ECVs that resulted in plans for a vaginal birth. There is a paucity of understanding about the experience of women who attempt an ECV then choose to plan a vaginal breech birth when their baby remains breech. Therefore, the aim of this study was to examine women’s experience of an ECV that resulted in a persistent breech presentation. This is part of a wider program of research exploring the experiences of women who choose a vaginal breech birth and the midwives and doctors who cared for them [15–17]. Methods A qualitative descriptive study was undertaken [18, 19]. This approach was selected to enable an accounting of events from the participants of the study in order to better understand their experiences. The participants were the women who had experienced an ECV and while their stories are described and explored, the findings seek to interpret meanings and actions from those stories. This study received approval from the Human Research Ethics Committee-Northern sector, South Eastern Sydney Local Health District, New South Wales Health. Reference: HREC 12/072 (HREC/12/POWH/163). Recruitment took place between March and October 2013 from two hospitals in New South Wales that supported planned vaginal breech birth. English-speaking women, who after an unsuccessful ECV planned a vaginal breech birth for a singleton pregnancy in the past 7 years regardless of their eventual mode of birth, were recruited in 2013. Women were identified from two Australian public maternity units in urban/metropolitan areas that supported women to have a vaginal breech birth. A review of the hospitals’ database that recorded women who planned a vaginal breech birth was undertaken to identify eligible women. In total, 32 women were invited to participate with 22 (69 % response rate) willing to be interviewed. Two members of the research team conducted all the interviews. These took place in women’s homes as that was identified as the most convenient. Appointments were made with women at a time most suitable to them and usually family members or partners cared for the children while the interview took place. A series of open-ended questions were asked during interview, which lasted around 60 min. Each were recorded with a digital voice recorder and transcribed by a professional transcription service. Data collection ended when no new information arose from the interviews and it was agreed by the research team that data saturation had been achieved. We used a similar process to that reported in our previous paper [15]. An inductive thematic analysis was used to identify, describe, and analyse themes and patterns within the data [20]. The process meant that transcriptions were initially read and re-read by three members of the research team and codes were identified. The codes were then examined for patterns and the underlying meaning of the issues identified were analysed within and between transcripts. The codes were refined and then grouped according to commonalities which gave themes. These were shared with the research group again and then cross-reviewed with the data, carefully considering counterexamples or negative cases to ensure that the similarity and diversity of experiences were identified [21]. The themes are illustrated with quotes from the data. At the end of each quote is a code indicating the interview number and whether they had a caesarean section (CS) or a vaginal birth (VB). Results Twenty-two women were interviewed, of which three quarters were primiparous (n = 16; 73 %). All were Caucasian, and the majority were educated to tertiary level. Most women were interviewed in the 3 years since their breech birth. At the time of the ECV, most (n = 16; 73 %) women were attending a hospital that did not support vaginal breech birth. After the breech presentation persisted, these women were informed that they would need a CS and all decided to actively seek different carers to facilitate vaginal breech birth. The other six (27 %) women were receiving care at a hospital that supported vaginal breech birth and continued with this care. Overall outcomes of birth were that twelve (55 %) women achieved a vaginal breech birth and 10 (45 %) gave birth by CS after labour had commenced (see Fig. 1).Fig. 1 Participants outcomes Five main themes were identified. These were ‘seeking an alternative’, ‘needing information’, ‘recounting the ECV experience’, ‘reacting to the unsuccessful ECV’ and, ‘reflecting on the value of an ECV’. Seeking an alternative Most women sought out other means to turn the baby and viewed the ECV as their last resort. Most tried more than one alternative therapy prior to attempting an ECV, some of which consisted of acupuncture, chiropractic, hypnotherapy, moxibustion, maternal positioning and yoga. This was motivated by the desire to avoid a medical procedure (ECV) and ultimately to avoid a CS birth. One woman said:“So I thought the whole breeching thing - I’ll fix that easy. It’s not a problem. I just do acupuncture, I do chiropractic, I do my exercises, he’s going to turn’. That was my attitude. And I thought he was going to turn all the way up to, the D-Day but…yeah. That didn’t happen.” CS3 Needing information Women needed detailed individualised information to assist their decision-making to have an ECV. The way information was presented by clinicians made a difference to the way women felt about attempting an ECV. For example:“When he offered the option he did it in such a way that it was so welcoming, it didn’t feel like it was a procedure and he assured me it would be up to the point that he felt the most pressure that he felt would be safe for the baby. So that was a different way in which the ECV was painted and so I agreed to do the ECV.” CS15 Despite this positive comment, many other women believed they were given insufficient information by their clinicians about the risks and benefits of an ECV. One woman expressed this by saying:“I felt that I wasn’t adequately educated as to what it was going to be like. I think I would have preferred a more complete understanding of the process before I made the choice more than just being told ‘it’s not pleasant’.” VB10 Many women sought additional information from the internet, social media and their friends and family regarding ECV. Information on the internet was mostly reported as negative. This clouded the perception of the value of attempting an ECV. One woman said:“I stupidly Googled it before I went and I find that people only want to share their stories when they are horrific.” VB11 Some women felt they were not given a choice to opt out of an ECV, but that it was an expected step in the course of management for a breech baby. One woman expressed this lack of choice saying:“I don’t think it was really presented as an option it was just presented as the next step.” VB17 Recounting the ECV experience When asked how they felt about the experience of having the ECV performed, the majority of women responded that the procedure caused them physical pain. Because of the subjective nature of the experience of pain, some of the women compared it to other painful events in their life, like childbirth. For example:“I can do pain. I didn’t have drugs for my first labour and I didn’t have drugs for my second labour.. but that was, incredibly painful.” VB1 Some women continued to have pain for some time after the procedure. One woman said:“I remember going to bed afterwards and trying to sleep ‘cause I was just in so much pain. And it really felt like someone had pummelled me, I had been through an absolute wringer.” VB22 Reacting to an unsuccessful ECV The reaction to a persistently breech baby was mixed. Most women had a strong emotional response, but reactions varied dependent upon where the ECV was attempted. For women who were already in a hospital supportive of vaginal breech birth, the significance of an unsuccessful ECV was negligible as the option of vaginal birth was already in place prior to the procedure. For the women who were not given this option, disappointment and distress were reported. The availability of vaginal breech birth for these women was crucial to how they felt about the outcome of the ECV. These women expressed feelings of disappointment, devastation and unacceptance of the consequence of having a baby remaining in the breech position. For example:“I definitely didn’t accept it. And I remember when I came home from the ECV that had failed and I was, you know, again, wailing and crying. Just absolutely devastated.” VB17 Women, cared for in hospitals that did not support vaginal breech birth, hinged their hopes on a successful ECV as they felt it was the last resort to be able to continue along their path of planning a vaginal birth. One women woman said:“It was awful. I was quite traumatised after that [ECV]. I think also knowing that this was my last chance, if he didn’t turn that I would have to have a caesarean.” VB14 In comparison, women who were aware of the option of vaginal breech birth prior to ECV were not as concerned when the procedure did not turn the baby. For example:“We walked away from that and I think at that point I began to accept that she wasn’t going to turn back. And that I was going to be delivering her breech [vaginally].” CS5 Reflecting on the value of ECV Almost half of the women (46 %) said they would not attempt an ECV in a future pregnancy. Reasons for this were three-fold. Firstly, the experience caused physical pain. This was expressed by one woman as:“So they’re pushing your stomach around and it’s just bloody excruciating… it just didn’t feel good… Never, never, never, again will I ever, ever, do that, never.” VB10 Secondly, ECV was seen as a procedure that introduced excessive risk to the baby that the women considered unnecessary, and some felt guilty for this. For example:“felt really guilty that I’d possibly brought a little bit of distress to my baby in utero.. would never attempt an ECV if I was breech second time around.” VB2 Thirdly, the option and availability of a planned vaginal breech birth meant the women who were already in a hospital supportive of vaginal birth did not appreciate that an ECV to promote cephalic presentation was worthwhile because the fetal presentation was inconsequential for their pregnancy and birth. Many women who sought out the option of vaginal breech birth commented that if the option of vaginal breech birth had have been presented and available prior to attempting an ECV then they may not have chosen to attempt it. One woman said:“I think I wish I’d had more information about the ECV and that it’s not necessarily something that you need to do.. so from what I know now, I wouldn’t necessarily make that choice.” VB8 Discussion This study describes Australian women’s experiences who underwent an ECV which resulted in a baby who remained a breech presentation. Other studies have described women’s experiences of having a breech presenting baby [22–24] and ECV [13, 14, 25–27]. Our findings add to the understanding of women’s experiences with a breech-presenting baby in the late third trimester of pregnancy as many women are offered an ECV, It was common for women to seek out a variety of complementary therapies for the relief of pregnancy-related complaints and symptoms [28], and this included turning babies [23]. This study showed that women used alternative therapies to attempt spontaneous cephalic version. However, few were reported in the literature as having any major effect on turning babies, although moxibustion (a Chinese herbal medical intervention that stimulates acupuncture points) may have some effect in reducing CS rates when used in conjunction with positional therapies [29, 30]. Alternative therapies can also be used to reduce the discomfort of an ECV. Women were not given analgesia during the ECV in this study, although methods to reduce discomfort can include hypnosis [31], inhalation analgesia, [32], injectable analgesia, and regional anaesthesia [33]. However, pain levels vary in women and women’s perception and recollection of pain are important. Vlemmix et al. [25] concluded that a woman’s willingness to agree to undergo an ECV is influenced by her perception of the pain and the likely success of converting her baby to a cephalic presentation. Women’s recollection of pain can also be diminished if their ECV was successful [26]. This may explain why the majority of women in this study reported it as a painful experience, as they all had an unsuccessful ECV, although this memory may have been compounded by the distress three quarters of them felt when they were told to expect a CS. The way information and options for birth were presented was important. The timing, manner and content of the information were central to women’s levels of anxiety. Discussions with health professionals surrounding myths (predominately found on the internet) and risks and benefits for ECV, vaginal breech birth and caesarean section were appreciated. In particular, risks and benefits are useful when articulated in a clear, easy to understand format especially the success rates. ECV success rates of 40–60 % have been reported [10], however it is pertinent to reveal local rates to women as well as discuss rates for women’s individual breech-positioned baby (eg. frank, footling). For example, footling breech babies have 2.77-times more likelihood of remaining cephalic after ECV than babies in a frank breech position [34]. Information to aid decision-making can also be facilitated through a decision-making tool. For example, a small study in Canada using an audio-guided workbook for women with a breech presentation was found to be helpful, although self-rated anxiety levels were not lowered significantly after using the decision aid [35]. Breech positions have long been seen as ‘malpositions’ of the fetus. It could be argued that there is a place for respecting women’s choice to refuse ECV and try for a vaginal breech birth. Other countries, such as Finland, where one in three women with breech babies are eligible and willing to try for a vaginal birth have this attitude towards breech-positioned babies [36]. Furthermore, another study by the same authors suggested that a trial of vaginal breech birth is as positive as a vertex birth experience for women [22]. Considering this, it may be time to move away from the approach of women being told their babies are in the ‘wrong’ position, and that turning them to a cephalic presentation is the only desirable option. This study included a selective group of women because they were highly motivated to pursue a vaginal breech birth. This may not reflect the general population of women, many of whom consent to a caesarean section when their baby is persistently breech. Despite this, these women provide a unique opportunity to understand the experience of women who have an ECV that does not turn their baby. Qualitative studies such as this provide a window into the experience for these women and could be reflective of other women’s experiences. Conclusion Understanding women’s experiences is important for doctors and midwives who provide care for women with a baby in the breech presentation late in pregnancy. ECV should form part of a range of options provided to women, rather than a default procedure for management of the term breech. For motivated women who fit the safe criteria for vaginal breech birth, not being subjected to a painful experience (ECV) is optimal. Given many women reported that they would not attempt an ECV in a future pregnancy, access services that support vaginal breech birth needs to be made available. Acknowledgements We would like to acknowledge the women who freely gave their time to be interviewed for this study Funding The study was supported by a small scholarship grant from the Australian College of Midwives, New South Wales Branch. Availability of data and materials The data will not be shared. This is because there is identifying information within the files. Authors’ contributions The contribution to authorship is: CC contributed to writing and editing, NW interviewed the women, analysed the data and contributed to the writing, KP interviewed the women and, AB contributed to the conception, design and protocol, CH coordinated the study, contributed to the protocol, design and writing, and approved the final draft. All were involved in revision and final approval. Competing interests There are no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate This study received approval from the Human Research Ethics Committee-Northern sector, South Eastern Sydney Local Health District, New South Wales Health. Reference: HREC 12/072 (HREC/12/POWH/163). ==== Refs References 1. Hannah ME Hannah WJ Hewson SA Hodnett ED Saigal S Willan AR Planned caesarean section versus planned vaginal birth for breech presentation at term: a randomised multicentre trial Lancet 2000 356 9239 1375 1383 10.1016/S0140-6736(00)02840-3 11052579 2. Daviss B-A Johnson KC Lalonde AB Evolving evidence since the term breech trial: Canadian response, European dissent, and potential solutions J Obstet Gynaecol Can 2010 32 3 217 224 10.1016/S1701-2163(16)34447-4 20500965 3. Australian Institute of Health and Welfare Mothers and Babies Report, 2012 2014 Canberra AIHW 4. The Royal Australian and New Zealand College of Obstetricians and Gynaecologists. Management of Breech Presentation at Term. Melbourne: RANZCOG; 2013. 5. Royal College of Obstetricians and Gynaecologists. External cephalic version and reducing the incidence of breech presentation Guideline no. 20a. London: RCOG; 2010. 6. Nassar N Roberts CL Barratt A Bell JC Olive EC Peat B Systematic review of adverse outcomes of external cephalic version and persisting breech presentation at term Paediatr Perinatal Epidemiol 2006 20 2 163 171 10.1111/j.1365-3016.2006.00702.x 7. Hutton EK, Hofmeyr G. External cephalic version for breech presentation before term. Cochrane Database of Systematic Reviews 2006 (Issue 1. Art. No.: CD000084. DOI: 10.1002/14651858.CD000084.pub2). 8. Grootscholten K Kok M Oei SG Mol BWJ van der Post JA External Cephalic Version–Related Risks: A Meta-analysis Obstet Gynecol 2008 112 5 1143 1151 10.1097/AOG.0b013e31818b4ade 18978117 9. Hutton EK Hannah ME Ross SJ Delisle MF Carson GD Windrim R The Early External Cephalic Version (ECV) 2 Trial: an international multicentre randomised controlled trial of timing of ECV for breech pregnancies BJOG: IntJ Obstetr Gynaecol 2011 118 5 564 577 10.1111/j.1471-0528.2010.02837.x 10. Hofmeyr G, Kulier R, West H. External cephalic version for breech presentation at term. . Cochrane Database of Systematic Reviews 2015 (Issue 4. Art. No.: CD000083. DOI: 10.1002/14651858.CD000083.pub3). 11. Cho L Lau W Lo T Tang H Leung W Predictors of successful outcomes after external cephalic version in singleton term breech pregnancies: a 9-year historical cohort study Hong Kong Med J 2012 18 1 11 19 22302905 12. Menakaya UA Trivedi A Qualitative assessment of women’s experiences with ECV Women Birth 2013 26 1 e41 e44 10.1016/j.wombi.2012.09.001 23062234 13. Rijnders M Offerhaus P van Dommelen P Wiegers T Buitendijk S Prevalence, Outcome, and Women’s Experiences of External Cephalic Version in a Low-Risk Population Birth: Issues in Perinatal Care 2010 37 2 124 133 10.1111/j.1523-536X.2010.00392.x 14. Say R Thomson R Robson S Exley C A qualitative interview study exploring pregnant women’s and health professionals’ attitudes to external cephalic version BMC Pregnancy Childbirth 2013 13 1 1 9 10.1186/1471-2393-13-4 23324161 15. Homer CS Watts NP Petrovska K Sjostedt CM Bisits A Women’s experiences of planning a vaginal breech birth in Australia BMC Pregnancy Childbirth 2015 15 89 10.1186/s12884-015-0521-4 25885035 16. Catling C Petrovska K Watts N Bisits A Homer C Barriers and facilitators for vaginal breech births in Australia: Clinician’s experiences Women Birth 2016 29 138 143 10.1016/j.wombi.2015.09.004 26472624 17. Catling C Petrovska K Watts N Bisits A Homer C Care during the decision-making phase for women who want a vaginal breech birth: Experiences from the field Midwifery 2016 34 111 116 10.1016/j.midw.2015.12.008 26795725 18. Sandelowski M Whatever happened to qualitative description? Res Nurs Health 2000 23 334 340 10.1002/1098-240X(200008)23:4<334::AID-NUR9>3.0.CO;2-G 10940958 19. Sandelowski M What’s in a name? Qualitative description revisited Res Nurs Health 2010 33 1 77 84 20014004 20. Liamputtong P Qualitative Research Methods 2005 Melbourne Oxford University Press 21. Taylor B Kermode S Roberts K Research in Nursing and Health Care: Evidence for Practice 2006 3 Nelson Thomson Learning 22. Toivonen E Palomaki O Huhtala H Uotila J Maternal experiences of vaginal breech delivery Birth 2014 41 4 316 322 10.1111/birt.12119 24935907 23. Guittier M-J Bonnet J Jarabo G Boulvain M Irion O Hudelson P Breech presentation and choice of mode of childbirth: A qualitative study of women’s experiences Midwifery 2011 27 6 e208 e213 10.1016/j.midw.2010.08.008 21051127 24. Glasø AH Sandstad IM Vanky E Breech delivery—what influences on the mother’s choice? Acta Obstetricia Et Gynecologica Scandinavica 2013 92 9 1057 1062 10.1111/aogs.12183 23710781 25. Vlemmix F Kuitert M Bais J Opmeer B van der Post J Mol BW Patient’s willingness to opt for external cephalic version J Psychosom Obstetr Gynaecol 2013 34 1 15 21 10.3109/0167482X.2012.760540 26. Bogner G Hammer BE Schausberger C Fischer T Reisenberger K Jacobs V Patient satisfaction with childbirth after external cephalic version Arch Gynecol Obstetr 2014 289 3 523 531 10.1007/s00404-013-3007-5 27. Truijens SEM van der Zalm M Pop VJM Kuppens SMI Determinants of pain perception after external cephalic version in pregnant women Midwifery 2014 30 3 e102 e107 10.1016/j.midw.2013.11.005 24332750 28. Adams J Sibbritt D Lui CW The use of complementary and alternative medicine during pregnancy: a longitudinal study of Australian women Birth 2011 38 3 200 206 10.1111/j.1523-536X.2011.00480.x 21884228 29. Zhang Q-H, Yue J-H, Liu M, Sun Z-R, Sun Q, Han C, et al. Moxibustion for the correction of nonvertex presentation: a systematic review and meta-analysis of randomized controlled trials. Evid Based Complement Alternat Med. 2013;2013:241027. 30. Coyle M, Smith C, Peat B. Cephalic version by moxibustion for breech presentation. Cochrane Database of Systematic Reviews 2005 (Issue 2. Art. No.: CD003928. DOI: 10.1002/14651858.CD003928.pub2.). 31. Guittier M-J Guillemin F Brandao Farinelli E Irion O Boulvain M de Tejada BM Hypnosis for the Control of Pain Associated with External Cephalic Version: A Comparative Study J Altern Complement Med 2013 19 10 820 825 10.1089/acm.2012.0945 23461523 32. Burgos J Cobos P Osuna C de Mar CM Fernández-Llebrez L Astorquiza TM Nitrous oxide for analgesia in external cephalic version at term: prospective comparative study J Perinatal Med 2013 41 6 719 723 10.1515/jpm-2013-0046 33. Weiniger CF Ginosar Y Elchalal U Sela HY Weissman C Ezra Y Randomized controlled trial of external cephalic version in term multiparae with or without spinal analgesia Br J Anaesth 2010 104 5 613 618 10.1093/bja/aeq053 20338954 34. Burgos J Melchor JC Pijoán JI Cobos P Fernández-Llebrez L Martínez-Astorquiza T A prospective study of the factors associated with the success rate of external cephalic version for breech presentation at term Int J Gynecol Obstet 2011 112 1 48 51 10.1016/j.ijgo.2010.07.023 35. Nassar N Roberts CL Raynes-Greenow CH Barratt A Development and pilot-testing of a decision aid for women with a breech-presenting baby Midwifery 2007 23 1 38 47 10.1016/j.midw.2005.09.003 16843575 36. Toivonen E Palomäki O Huhtala H Uotila J Selective vaginal breech delivery at term—still an option Acta Obstetricia Et Gynecologica Scandinavica 2012 91 10 1177 1183 10.1111/j.1600-0412.2012.01488.x 22708506

PMC005xxxxxx/PMC5000478.txt

==== Front Parasit VectorsParasit VectorsParasites & Vectors1756-3305BioMed Central London 176210.1186/s13071-016-1762-4ResearchHow do biting disease vectors behaviourally respond to host availability? http://orcid.org/0000-0001-8639-4511Yakob Laith laith.yakob@lshtm.ac.uk Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT UK 25 8 2016 25 8 2016 2016 9 1 46820 4 2016 17 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Ecological theory predicts a diverse range of functional responses of species to resource availability; but in the context of human blood consumption by disease vectors, a simplistic, linear response is ubiquitously assumed. A simple and flexible model formulation is presented that extends the Holling’s Types to account for a wider range of qualitatively distinct behaviours, and used to examine the impact of different vector responses to the relative availability of multiple blood-host species. Results Epidemiological models of falciparum malaria, Chagas disease and Lyme disease demonstrate that the standard, often implicit, assumption of a linear functional response can lead to spurious under- or over-estimates in disease transmission potential, across a full range of pathogen life-cycles. It is shown how the functional response in vector biting can augment disease intervention outcomes. Interactions between vector biting behaviour and uneven pathogen transmission probabilities between alternative hosts, as is the case for Chagas disease, can render infection more resilient to control. Conclusions Both the novel response formula and the nested vector-borne disease structure offer a flexible framework that can be applied to other vector-borne diseases in assessing the role of this newly identified aspect of biting behavioural ecology. Keywords Behaviour ecologyFunctional responseVector-borne diseaseMalariaChagas diseaseLyme diseasehttp://dx.doi.org/10.13039/501100000265Medical Research Council Newton Fundhttp://dx.doi.org/10.13039/100004440Wellcome Trustissue-copyright-statement© The Author(s) 2016 ==== Body Background How species respond to availability in resources is highly variable and has fostered considerable interest among ecologists for decades. Seminal papers written by Holling describe the different forms of functional response that predators exhibit to prey density [1–3]. A term first coined by Solomon [4], ‘functional response’ refers to the influence of resource availability on the rate of its consumption. Three qualitatively distinct functional responses were originally described: Type I responses depict resource consumption as a linear function of availability; Type II responses depict resource consumption as a decelerating function of availability (convex-up); and Type III responses depict resource consumption as an initially accelerating but then decelerating function of availability (s-shaped curve). Although Holling initially drew strong delineation between the types of predator species and the functional responses that they exhibit (e.g. invertebrates are Type II whereas mammals are Type III), subsequent ecological studies have generalised this phenomenon beyond predator-prey interactions (to account for all manner of resource consumption) and recast various species across a continuous spectrum of Types [5]. Real [6] devised a general formula that enabled flexible characterisation of a Hollings Type I, II or III response. This constituted an important contribution because different response Types could be assessed simply through re-parameterisation of the same underlying model, and this type of nesting is an advantage in direct comparison between models in estimating best fit to data [7]. The formulation proposed by Real [6] is as follows: 1 C=αNβ1+αwNβ where, C is the resource consumption rate, N is the density (or availability) of the resource, w is the handling time of the resource (i.e. the amount of time taken between identifying the prey and consuming it), and α and β are shape parameters. In the case that w = 0 and β = 1, C = αN (a linear Type I response); in the case that w > 0 and β = 1, a formulation which is equivalent to the Michaelis-Menten equation of enzyme kinetics results and is characterised by a decelerating consumption that eventually saturates (Type II); in the case that w > 0 and β > 1, a sigmoidal relationship results (Type III). However, the extent of analogous developments in the context of vector-borne diseases is very limited. Many disease vectors are obligatorily haematophagous, meaning blood is a critical resource for survival and/or reproduction [8]. An important distinction to make here is that host death would rarely be expected as a direct consequence of blood-feeding by a vector (an exception being neurotoxin-mediated tick paralysis), but instead may result from coincident pathogen transmission. Thus the bidirectional effects on both consumer and resource species population dynamics implicit to predator/prey (and parasitoid/host) systems do not necessarily hold here. A further necessary consideration for systems of haematophagous disease vectors is that, as a rule, blood can be (and is) sourced from multiple host species. Even the most discerning of vector species thrive on the blood of multiple hosts [9, 10]. For example, Anopheles gambiae (sensu stricto) famously shows extreme preference for human blood [11] but adapts to environments with low human availability by sourcing blood from alternative mammals [12] with reportedly little-to-no effect on its resulting fecundity [13]. This is in stark contrast to parasitoid systems which are typically highly specialised and to most predator-prey theoretical and empirical studies (although, see multi-species models of Abrams & Matsuda [14] and Rueffler et al. [15]). To avoid conflation, the biting response of disease vectors to host availability shall be referred to as ‘behavioural’ instead of ‘functional’. Development in the understanding of behavioural responses in disease vector biting is timely as this field is anticipated to accelerate rapidly following recent advances in molecular approaches; novel biological fingerprinting methods allow for the inexpensive, rapid and sensitive identification of host species from vector blood meals [16]. In the context of human disease control, there has been a recently rekindled interest in targeting vectors that bite alternative (often domestic) host species [17–19]. However, the full potential of these advances in informing vector-borne disease epidemiology will only be realised with their appropriate interpretation through a more developed ecological theory. Of the few ecological and epidemiological studies that consider host preference among vectors, linearity between alternative host availability and vector response is typically assumed [17, 20, 21]. In other words, a doubling in the availability of a particular host species relative to all potential hosts doubles the proportion of bites taken on that species. Here, the behavioural response of haematophagous arthropod disease vectors to the availability of alternative hosts and the resulting consequences for vector-borne disease transmission are explored. Methods Modelling the behavioural response in biting disease vectors The proportion of blood-meals taken from the host species of interest (here, humans) compared to alternative hosts is generally assumed to increase as a direct proportion of increasing relative human availability. A model was sought to relax this key assumption of a century’s worth of vector-borne disease (VBD) models in order to explore the epidemiological impact of non-linear vector biting behavioural responses to host availabilities. While the nested model of Real (1977) (Equation 1) offers a concise and flexible framework for exploring different qualitative responses, there were VBD-specific scenarios that could not be resolved using this existing framework. For example, in the case of a zoonotic VBD which has spilled over into a local human population, a vector with strong zoophilic speciation may only opportunistically bite humans when their preferred host becomes vanishingly rare - this is the entomological/ epidemiological situation reported in Louisiana, USA, where the local kissing bugs (Triatoma sanguisuga) were observed to only start biting humans and infecting them with Trypanosoma cruzi when the local armadillo population collapsed [22]. This behaviour is not described by a Type I, II or III response. A new, flexible formula was developed to account for a wider range of vector responses to host availability: 2 p=QQ+α1−Qβ where, p is the proportion of all blood meals that are derived from the species of interest, for humans, this metric has been termed the ‘human blood index’ (HBI) [20]; Q is the availability of the host species of interest relative to all potential hosts; α and β are parameters that shape the behavioural response. Figure 1 demonstrates the effects that α and β have on the functional response with this new formulation. In addition to a linear (Type I), convex-up (Type II) and sigmoidal (Type III) response, the new formula also allows for responses that are convex-down (hereon referred to as ‘Type IV’) and atypical sigmoidal (classic s-shape reflected in the y = x, ‘Type V’). The qualitatively distinct feeding behaviours which can be characterised as combinations of intrinsic (genetic) host preferences and vector phenotypic response to local conditions [23] are described in Table 1.Fig. 1 The behavioural response in human blood index of a disease vector to varying levels of human host availability (relative to all potential blood sources). Distinct qualitative forms (denoted ‘I’ to ‘V’) are shaped by parameters α and β as described in Equation 2 Table 1 The qualitatively different behavioural responses (parameterisation and associated vector behaviours) described by the new formula Response type Ecological equivalent Parametric conditions Vector behaviour Type I Analogous to Holling’s Type I α = 1 β = 1 Indiscriminate; or vector biting that is consistent (proportionate) across relative availabilities of alternative hosts. Type II Analogous to Holling’s Type II α < 1 β ≥ 1 The HBI of an anthropophilic vector saturates whereby even when humans and non-humans have similar availability, almost all blood meals are secured from humans. Type III Analogous to Holling’s Type III α ≥ 1 β > 1 Similar to a Type II response, the HBI saturates, but at low levels of human availability vectors are uninclined to bite them. Corresponding with the analogous Holling’s Type, this could be associated with a learned behaviour with an increased rate of human encounters. Type IV Inversion of Holling’s Type II α > 1 β ≤ 1 A zoophilic vector is uninclined to bite humans until they constitute all but the only available blood source. Type V Inversion of Holling’s Type III α ≤ 1 β < 1 HBI saturates and becomes relatively invariant when humans and non-human hosts are at similar availability. This is analogous to ‘negative prey switching’ whereby the ‘predator’ consumes disproportionately less of the more available ‘prey’ [41]. Eventually, when non-humans become vanishingly rare, the HBI is forced to increase sharply to unity. The impact of these qualitatively distinct behavioural responses are assessed for different classes of VBDs. Infectious disease agents can be categorised across a spectrum according to their transmission potential to humans relative to non-human species [24]; and a natural, human-centric stratification is to consider the transmission potential to humans of pathogens that are either strict-anthroponotic (where non-human species are incompetent reservoirs), generalist (where humans and non-human species are both competent reservoirs) or strict-zoonotic (where humans are incompetent reservoirs). To exemplify the epidemiological impact of vector biting responses, these three strata are respectively represented by models of falciparum malaria, Chagas disease and Lyme disease. Nested ecological-epidemiological models The transmission dynamics of falciparum malaria, Chagas disease and Lyme disease are all nested within the following general VBD framework: 3 dSdt=γI+τR−pHmbHSZ 4 dIdt=pHmbHSZ−γ+ε+πI 5 dRdt=εI+κA−τ+θpHmbHZR 6 dAdt=πI+θpHmbHZR−κA 7 dXdt=μV−pHbVHI+σA+1−pHbVNIN+σNANX−μX 8 dYdt=pHbVHI+σA+1−pHbVNIN+σNANX−ζ+μY 9 dZdt=ζY−μZ 10 dSNdt=γNIN+τNRN−1−pHmbNSNZ 11 dINdt=1−pHmbNSNZ−γN+εN+πNIN 12 dRNdt=εNIN+κNAN−τN+θN1−pHmbNZRN 13 dANdt=πNIN+θN1−pHmbNZRN−κNAN The epidemiological categories of the vector population and the populations of different host species (subscript H refers to humans; N refers to non-human hosts) are tracked as proportions. Disease transmission is assumed frequency-dependent to maintain convention with almost all VBD models. Susceptible hosts (S) become infected (I) following a bite from an infectious vector (Z). Infected hosts can either revert to susceptible at rate γ, or they can benefit from temporary (τ > 0 and/or θ > 0) or permanent (τ = θ = 0) immunity. Alternatively, hosts can become asymptomatically infected (A) directly progressing from symptomatic infection (π > 0) or following on from recovery and subsequent reinfection (θ > 0). Asymptomatic infection may have the same transmission potential to vectors as symptomatic infections (σ = 1) or different transmission potential to vectors (σ ≠ 1), and can either be lifelong (κ = 0) or the pathogen can be completely cleared and hosts recover at rate κ. Susceptible vectors (X) become infected (Y) following a bite from an infectious host, and after the extrinsic incubation period, become infectious (Z). Total vectors V = X+Y+Z. Vectors typically outnumber hosts and, following convention, the ratio of vector-to-hosts (all blood-source host species) is denoted m. Typically, they also live shorter lives than hosts and so the relatively long extrinsic incubation period is explicitly included, as are vector demographics. Here, a stable vector population is assumed whereby births are set to balance deaths (μ). The impact of biting behaviour is assessed for pathogens with markedly different aetiologies through the following specifications and parameterisations. Model specification Humans are considered the only intermediate host for Plasmodium falciparum (c.f. knowlesi malaria for which mixed-host species models now exist [25]). Therefore, transmission terms between vectors and non-human hosts are assumed to equal zero. Following convention of previously published malaria models, host recovery without imparting some level of immunity does not occur; nor does asymptomatic chronicity following initial infection and so γ and π equal zero respectively [26]. The resulting compartmental framework is equivalent to an SIRS model but with possibility of maintained asymptomatic infection status following temporally proximal sequential infections [27]. Trypanosoma cruzi is a more generalist pathogen, infecting marsupials, primates, bats, armadillos and rodents, among other species [28]. In highly endemic human communities of Latin America, domestic animals are the key infection source and dogs are the primary parasite reservoir [29]. Infection dynamics are therefore tracked between dogs, the kissing bug vector and humans. (However, Equations 3–13 can be extended to greater numbers of blood-hosts and this will constitute important future work). Similarly for dogs and humans, infection is not cleared and acute infection invariably leads to chronic, asymptomatic infection. Hence, ε, γ, τ, θ and κ equal zero and the transitions are described by an SIA model. A key difference between these two blood-hosts is that while asymptomatically infected dogs can continue to transmit the parasite to vectors (σN > 0), chronically infected humans do not constitute parasite reservoirs [30]. Humans are dead-end hosts of Lyme disease. Therefore, human host transmission to the vector (bVH) equals zero. No temporary or lasting immunity has been documented for humans and so dynamics are described by an SIS model; whereas infection is generally chronic and symptomless in amplification host species (e.g. white-footed field mice, deer) and described by an SIA model [31]. These substructures can be achieved as with the other disease examples by setting the redundant rates to zero. Rates of change between the remaining epidemiological categories for all infection models are described in full in Table 2.Table 2 Parameterisation for vector-borne disease models Definition Plasmodium falciparum Trypanosoma cruzi Borrelia burgdorferi b i Transmission coefficient (vectors→hosts) = bite rate x transmission probability 0.1 = 1/3 × 0.3 (humans) [42]; 0 (non-humans) 2 × 10-5 = ¼ × 8 × 10-5 (humans) [43, 44]; 2.5 × 10-4 = ¼ × 0.001 (non-humans) [45] 0.003=1365×1.0humansandnon‐humans [46] b Vi Transmission coefficient (hosts→vectors) = bite rate x transmission probability 0.007=13×0.02humans [47]; 0(non-humans) 0.015 = ½ × 0.03 (humans); 0.25 = ½ × 0.49 (non-humans) [48] 0(humans); 0.003=1365×1.0non‐humans [46] γ Recovery rate (no immunity) 0 (humans and non-humans) 0 (humans and non-humans) 1/28 (humans)a; 0 (non-humans) [31] ε Clearance rate of symptomatic infection 1/200 (humans) [49]; 0 (non-humans) 0 (humans and non-humans) 0 (humans and non-humans) κ Clearance rate of asymptomatic infection 1/200 (humans) [49]; 0 (non-humans) 0 (humans and non-humans) 0 (humans and non-humans) π Asymptomatic primary infection rate 0 (humans and non-humans) 1/40 (humans and non-humans) [50, 51] 0 (humans); 1/28 (non-humans) [31] θ Asymptomatic secondary infection rate 0.5 (assumed for humans); 0 (non-humans) 0 (humans and non-humans) 0 (humans and non-humans) τ Full susceptibility reversion rate 1/1000 (humans) [52]; 0 (non-humans) 0 (humans and non-humans) 0 (humans and non-humans) μ Birth (or maturation) and death rate of vectors (i.e. stable population) 1/10 [53] 1/365 [54] 1/365 [55] σ Adjustment factor for asymptomatic transmissibility to vector 0.25 (humans) [56]; 0 (non-humans) ≈0 humans [30]; ≈1 non-humans [57]b 0 (humans); ≈1 (non-humans) ζ Rate of parasite development within vector 1/10 [58] 1/10 [59] 1/365 [60]c aClassically, Lyme disease infection dynamics are of an SIS form whereby the pathogen is assumed to be cleared by the host’s immune system. However, Nadelman & Wormser [31] review several studies demonstrating that an SIA form is more appropriate for non-human hosts bA longitudinal study of domestic dogs (a principal Chagas disease reservoir) demonstrated persistent infectiousness but it was unclear whether this was a result of repeat infections cParasite development is assumed to correspond with the developmental delays between life stages of the tick (whereby the tick will take its blood-meal from a different host species) Results Control strategies focusing on reducing vector biting rates were simulated for models representing each of the three pathogen life-cycle strata. Specifically, the impact on control of different behavioural responses in vector biting behaviour was assessed separately for falciparum malaria, Chagas disease and Lyme disease (Fig. 2). Due to their long duration, rates of chronic infection with vector-borne diseases are slow to change following control and so results are presented in terms of the impact of vector behavioural response on rates of acute (symptomatic) infections which better characterise disease incidence.Fig. 2 Disease control efficacy is contingent on the behavioural response of biting vectors to the availability of alternative blood-hosts. The parameters α and β determine the shape of the behavioural response as described in Equation 2. The human proportion of all blood-hosts is indicated in the top-right of each plot. For Plasmodium falciparum (top row), the region above the contours corresponds with controlled transmission, but for Trypanosoma cruzi (middle row) and Borrelia burgdorferi (bottom row), the regions below the contours correspond with controlled transmission. A special case is shown in the left plot for T. cruzi whereby the high α/ low β region (above broken line) delimits a second parameter space for controlled transmission (see text). The contour labels correspond with the percentage reduction in bite rate required to achieve control. (These models are all deterministic and so a 90 % reduction in the acute infections relative to the maximum level in the absence of control is used to infer controlled transmission) Intuitively, acute malaria infection was easier to control when vectors had strong zoophilic preference across a wide range of host availabilities (high α, low β, i.e. Type IV) and most resilient to control when vectors were highly anthropophilic across a wide range of host availabilities (low α, high β i.e. Type II). Also expected for this parasite that requires passage through humans for its propagation, was the result that when humans constituted a larger proportion of the total blood-host availability, infection was more difficult to control (from left to right on top row of Fig. 2). Acute human infection with both Lyme and Chagas disease had qualitatively similar relationships with the vectors’ behavioural response. Control was easiest when vectors were highly anthropophilic (low α, high β, i.e. Type II), and hardest when vectors were zoophilic (high α, low β i.e. Type IV). While this was an expected result for Lyme disease (whereby humans are dead-end hosts and thereby detract from the pathogen transmission cycle), the qualitatively similar result for Chagas was less intuitive and arose from the disproportionately high contribution of non-human hosts to the force of infection (dogs not only remain infectious for much longer than humans but are substantially more infectious to the vectors, Table 2). Host preference that was weighted against humans (high α, low β, i.e. Type IV) was most resilient to human infection control for all Lyme and Chagas disease scenarios, with one exception. For a generalist pathogen (T. cruzi), there are some circumstances when a more intermediate biting behaviour (less definitively anthropophilic/zoophilic) can give rise to a human infection that is less amenable to control (left subplot, middle row of Fig. 2). Here, a Type II response (low α, high β) reduces the proportion of bites on the more competent host (dogs), in turn reducing the prevalence of disease and subsequent force of infection on humans. However, when humans only constitute a minority of available blood-hosts, the exaggerated proportion of bites on dogs under a Type IV response (high α, low β) depletes the opportunities for pathogen spread to humans more than the reduced prevalence of disease that would result for a less zoophilic vector. Therefore, both extremes of vector biting behaviour are more conducive to control. Discussion Models of diseases spread by haematophagous arthropods are increasingly popular tools for understanding the spread of vector-borne diseases and strategizing their control. Persisting among even the most complex of contemporary models is the widespread assumption that vector bites are distributed in a directly proportionate manner on alternative hosts according to their relative availability, sometimes adjusted according to a constant intrinsic host preference as described by Bailey [32]. Critically, a linear (Type I) functional response is not only atypical for arthropods, it is without precedent [33]. Unfortunately, examples of studies that account for non-linear effects of human host availability on vector biting behaviour are scant. While parallel advances have been made in the context of predator-prey [34] and host-parasitoid systems [35], these have not translated to corresponding developments in VBD understanding. Antonovics et al. [36] used a general Type II model to simulate VBD transmission and described how a vector that is highly restricted in its movement could well have its bite rate limited by low host density (invalidating the general assumption of frequency-dependence); and, frequency-dependence and density-dependence are well known to generate markedly different transmission dynamics [37]. This concept has been recently built upon by Kershenbaum et al. [38] who showed in a one-vector two-host (one competent, one incompetent) model that parameter spaces exist whereby a reduction in competent host availability risks exacerbating disease prevalence through attenuated competition for limited vector feeding sites. The current study does not account for this potential transmission bottleneck; and a unified approach to account for not only the proportional distribution of bites across different alternative host availabilities but also a vector biting rate that can be influenced by host densities constitutes an important future endeavour. A further aspect of the current work that justifies future development is the exploration of how different behavioural responses might impact pathogen transmission dilution and amplification [39]. Miller & Huppert [40] also used a Type II formulation to describe vector bites split between multiple host species and showed disease transmission is intensified (or ‘amplified’) when more host species are included in a system if the vector prefers the host with the highest transmission ability; otherwise, the addition of more host species dilutes transmission [40]. Although the current study is restricted to a vector shared between only two alternative hosts, the methods described are easily adaptable to more hosts for the analysis of species diversity and pathogen persistence. Conclusions This study makes the following contributions: it provides a new, two-parameter function that can be used to understand functional response ecology and that extends the qualitative Types achievable with earlier (three-parameter) models of Holling and Real; it introduces a general framework into which this vector behaviour can be incorporated to explore its consequences on infectious diseases with diverse epidemiology; it highlights an aspect of vector behaviour that is almost completely neglected; and demonstrates how this response of the vector to alternative host availabilities can drastically alter efforts to mitigate transmission. Data derived from laboratory or semi-field conditions (where the relative availabilities of alternative blood hosts can more easily be manipulated) are a high research priority in the field of vector-borne disease. Diverse aetiologies and idiosyncratic epidemiology severely limit opportunities for scientific discoveries that can potentially impact the whole gamut of vector-borne diseases. The ecology of this behaviour in biting disease vectors potentially offers one of the last largely unexplored avenues of generally applicable vector-borne disease research. Abbreviations HBIHuman blood index SIASusceptible-infected-asymptomatic SIRSSusceptible-infected-recovered-susceptible SISSusceptible-infected-susceptible VBDVector-borne disease Acknowledgements I thank Ian Baldwin and the anonymous reviewers for their insightful feedback and suggestions. Funding Funding is provided by the European Union through Horizon2020 as well as the UK Medical Research Council, The Newton Fund and The Wellcome Trust. Availability of data and material Not applicable. Authors’ contributions Not applicable. Competing interests The author declares that he has no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate Not applicable. ==== Refs References 1. Holling CS The components of predation as revealed by a study of small mammal predation of the European pine sawfly Can Entomol 1959 91 293 320 10.4039/Ent91293-5 2. Holling CS Some characteristics of simple types of predation and parasitism Can Entomol 1959 91 385 398 10.4039/Ent91385-7 3. Holling CS The functional response of predators to prey density and its role in mimicry and population regulation Mem Entomol Soc Can 1965 45 5 60 10.4039/entm9745fv 4. Solomon ME The natural control of animal populations J Anim Ecol 1949 18 1 35 10.2307/1578 5. Lafferty KD DeLeo G Briggs CJ Dobson AP Gross T Kuris AM A general consumer-resource population model Science 2015 349 6250 854 857 10.1126/science.aaa6224 26293960 6. Real LA The kinetics of functional response Am Nat 1977 111 289 300 10.1086/283161 7. McCallum H Preditor-prey, host-parasitoid and plant-herbivore models Population parameters: estimation for ecological models 2000 Oxford Blackwell Sciences Ltd 244 283 8. Lehane MJ The Biology of Blood-Sucking in Insects 2005 2 Cambridge Cambridge University Press 9. Chaves LF Harrington LC Keogh CL Nguyen AM Kitron UD Blood feeding patterns of mosquitoes: random or structured? Front Zool 2010 7 1 1 11 10.1186/1742-9994-7-3 20148101 10. Rabinovich JE Kitron UD Obed Y Yoshioka M Gottdenker N Chaves LF Ecological patterns of blood-feeding by kissing-bugs (Hemiptera: Reduviidae: Triatominae) Mem I Oswaldo Cruz 2011 106 479 494 10.1590/S0074-02762011000400016 11. Pates HV Takken W Stuke K Curtis CF Differential behaviour of Anopheles gambiae sensu stricto (Diptera: Culicidae) to human and cow odours in the laboratory B Entomol Res 2001 91 289 296 10.1079/BER200198 12. White GB Magayuka SA Boreham PFL Comparative studies on sibling species of the Anopheles gambiae Giles complex (Dipt., Culicidae): bionomics and vectorial activity of species A and species B at Segera, Tanzania B Entomol Res 1972 62 295 317 10.1017/S0007485300047738 13. Lyimo IN Keegan SP Ranford-Cartwright LC Ferguson HM The impact of uniform and mixed species blood meals on the fitness of the mosquito vector Anopheles gambiae s.s: Does a specialist pay for diversifying its host species diet? J Evolution Biol 2012 25 452 460 10.1111/j.1420-9101.2011.02442.x 14. Abrams PA Matsuda H Population dynamical consequences of reduced predator switching at low total prey densities Popul Ecol 2003 45 175 185 10.1007/s10144-003-0159-3 15. Rueffler C VanDooren TJM Metz JAJ Adaptive walks on changing landscapes: Levins’ approach extended Theor Popul Biol 2004 65 165 178 10.1016/j.tpb.2003.10.001 14766190 16. Önder Ö Shao W Lam H Brisson D Tracking the sources of blood meals of parasitic arthropods using shotgun proteomics and unidentified tandem mass spectral libraries Nat Protocols 2014 9 4 842 850 10.1038/nprot.2014.048 24625782 17. Saul A Zooprophylaxis or zoopotentiation: the outcome of introducing animals on vector transmission is highly dependent on the mosquito mortality while searching Malaria J 2003 2 1 1 18 10.1186/1475-2875-2-32 18. Iwashita H Dida GO Sonye GO Sunahara T Futami K Njenga SM Chaves LF Minakawa N Push by a net, pull by a cow: can zooprophylaxis enhance the impact of insecticide treated bed nets on malaria control? Parasit Vectors 2014 7 1 1 15 10.1186/1756-3305-7-52 24411014 19. Yakob L Endectocide-treated cattle for malaria control: A coupled entomological-epidemiological model Parasite Epidemiol Control 2016 1 1 2 9 10.1016/j.parepi.2015.12.001 20. Garrett-Jones C The human blood index of malaria vectors in relation to epidemiological assessment B World Health Organ 1964 30 241 261 21. Killeen GF Chitnis N Moore SJ Okumu FO Target product profile choices for intra-domiciliary malaria vector control pesticide products: repel or kill? Malaria J 2011 10 1 1 22 10.1186/1475-2875-10-207 22. Dorn PL Perniciaro L Yabsley MJ Roellig DM Balsamo G Diaz J Wesson D Autochthonous transmission of Trypanosoma cruzi , Louisiana Emerg Infect Dis 2007 13 605 607 10.3201/eid1304.061002 17553277 23. Lefèvre T Gouagna L-C Dabiré KR Elguero E Fontenille D Renaud F Beyond Nature and Nurture: Phenotypic plasticity in blood-feeding behavior of Anopheles gambiae s.s. when humans are not readily accessible Am J Trop Med Hyg 2009 81 6 1023 1029 10.4269/ajtmh.2009.09-0124 19996432 24. Wolfe ND Dunavan CP Diamond J Origins of major human infectious diseases Nature 2007 447 7142 279 283 10.1038/nature05775 17507975 25. Yakob L Bonsall MB Yan G Modelling knowlesi malaria transmission in humans: vector preference and host competence Malaria J 2010 9 329 10.1186/1475-2875-9-329 26. Mandal S Sarkar RR Sinha S Mathematical models of malaria - a review Malaria J 2011 10 202 10.1186/1475-2875-10-202 27. Artzy-Randrup Y Dobson AP Pascual M Synergistic and antagonistic interactions between bednets and vaccines in the control of malaria Proc Natl Acad Sci U S A 2015 112 10 3014 3019 10.1073/pnas.1409467112 25605894 28. Noireau F Diosque P Jansen AM Trypanosoma cruzi : adaptation to its vectors and its hosts Vet Res 2009 40 26 10.1051/vetres/2009009 19250627 29. Gurtler RE Cecere MC Lauricella MA Cardinal MV Kitron U Cohen JE Domestic dogs and cats as sources of Trypanosoma cruzi infection in rural northwestern Argentina Parasitol 2007 134 01 69 82 10.1017/S0031182006001259 30. Añez N Martens ML Romero M Crisante G Trypanosoma cruzi primary infection prevents severe re-infection in mice Bol Mal Salud Ambiental 2011 51 177 186 31. Nadelman RB Wormser GP Reinfection in patients with Lyme disease Clin Infect Dis 2007 45 8 1032 1038 10.1086/521256 17879922 32. Bailey NTJ The Biomathematics of Malaria 1982 London Charles Griffin & Co. 33. Jeschke JM Kopp M Tollrian R Consumer-food systems: why type I functional responses are exclusive to filter feeders Biol Rev 2004 79 2 337 349 10.1017/S1464793103006286 15191227 34. Oaten A Murdoch WW Switching, functional response, and stability in predator-prey systems Am Nat 1975 109 299 318 10.1086/282999 35. Hassell MP The dynamics of arthropod predator-prey systems 1978 Princeton Princeton University Press 36. Antonovics J Iwasa Y Hassell MP A generalized model of parasitoid, venereal, and vector-based transmission processes Am Nat 1995 145 661 675 10.1086/285761 37. Getz WM Pickering J Epidemic models: thresholds and population regulation Am Nat 1983 121 892 898 10.1086/284112 38. Kershenbaum A Stone L Ostfeld RS Blaustein L Modelling transmission of vector-borne pathogens shows complex dynamics when vector feeding sites are limited PLoS One 2012 7 5 e36730 10.1371/journal.pone.0036730 22590597 39. Randolph SE Dobson ADM Pangloss revisited: a critique of the dilution effect and the biodiversity-buffers-disease paradigm Parasitol 2012 139 847 863 10.1017/S0031182012000200 40. Miller E Huppert A The effects of host diversity on vector-borne disease: The conditions under which diversity will amplify or dilute the disease risk PLoS One 2013 8 11 e80279 10.1371/journal.pone.0080279 24303003 41. Abrams PA Matsuda H Harada Y Evolutionarily unstable fitness maxima and stable fitness minima of continuous traits Evol Ecol 1993 7 465 487 10.1007/BF01237642 42. Rickman L Jones TR Long GW Paparello S Schneider I Paul CF Plasmodium falciparum -infected Anopheles stephensi inconsistently transmit malaria to humans Am J Trop Med Hyg 1990 43 441 445 2240371 43. Coffield DJ Jr Spagnuolo AM Shillor M Mema E Pell B Pruzinsky A Zetye A A Model for Chagas disease with oral and congenital transmission PLoS One 2013 8 6 e67267 10.1371/journal.pone.0067267 23840647 44. Catalá S The biting rate of Triatoma infestans in Argentina Med Vet Entemol 1991 5 325 333 10.1111/j.1365-2915.1991.tb00558.x 45. Cohen JE Gürtler RE Modeling household transmission of American trypanosomiasis Science 2001 293 694 698 10.1126/science.1060638 11474111 46. Piesman J Mather TN Sinsky RJ Spielman A Duration of tick attachment and Borrelia burgdorferi transmission J Clin Microbiol 1987 25 557 558 3571459 47. Bonnet S Gouagna LC Paul RE Safeukui I Meunier JY Boudin C Estimation of malaria transmission from humans to mosquitoes in two neighbouring villages in south Cameroon: evaluation and comparison of several indices T Roy Soc Trop Med H 2003 97 53 59 10.1016/S0035-9203(03)90022-8 48. Gurtler RE Cecere MC Castanera MB Canale D Lauricella MA Chuit R Segura EL Probability of infection with Trypanosoma cruzi of the vector Triatoma infestans fed on infected humans and dogs in northwest Argentina Am J Trop Med Hyg 1996 55 24 31 8702018 49. Falk N Maire N Sama W Owusu-Agyei S Smith T Beck H Felger I Comparison of PCR-RFLP and Genescan-based genotyping for analyzing infection dynamics of Plasmodium falciparum Am J Trop Med Hyg 2006 74 6 944 950 16760501 50. Gomes ML Toledo MJO Nakamura CV Bittencourt NLR Chiari E Araújo SM Trypanosoma cruzi : genetic group with peculiar biochemical and biological behavior Mem I Oswaldo Cruz 2003 98 649 654 10.1590/S0074-02762003000500011 51. Teixeira ARL Hecht MM Guimaro MC Sousa AO Nitz N Pathogenesis of Chagas' disease: Parasite persistence and autoimmunity Clin Microbiol Rev 2011 24 3 592 630 10.1128/CMR.00063-10 21734249 52. Doolan DL Dobaño C Baird JK Acquired immunity to malaria Clin Microbiol Rev 2009 22 1 13 36 10.1128/CMR.00025-08 19136431 53. Ermert V Fink A Jones A Morse A Development of a new version of the Liverpool Malaria Model. I. Refining the parameter settings and mathematical formulation of basic processes based on a literature review Malaria J 2011 10 1 35 10.1186/1475-2875-10-35 54. Chaves LF Hernandez M-J Revilla TA Rodríguez DJ Rabinovich JE Mortality profiles of Rhodnius prolixus (Heteroptera: Reduviidae), vector of Chagas disease Acta Trop 2004 92 2 119 125 10.1016/j.actatropica.2004.06.005 15350863 55. Apanaskevich DA Oliver JH Sonenshine DE Roe RM Life cycles and natural history of ticks Biology of Ticks 2014 New York Oxford University Press 56. Okell LC Bousema T Griffin JT Ouedraogo AL Ghani AC Drakeley CJ Factors determining the occurrence of submicroscopic malaria infections and their relevance for control Nat Commun 2012 3 1237 10.1038/ncomms2241 23212366 57. Gürtler RE Lauricelia M Solakz ND Bujas MA Wisnivesky-Colli C Dynamics of transmission of Trypanosoma cruzi in a rural area of Argentina. I The dog reservoir: an epidemiological profile Rev I Med Trop São Paulo 1986 28 28 35 10.1590/S0036-46651986000100006 58. Blanford JI, Blanford S, Crane RG, Mann ME, Paaijmans KP, Schreiber KV, Thomas MB. Implications of temperature variation for malaria parasite development across Africa. Sci Rep. 2013;3:1300. 59. Paniker CJ Medical Parasitology 1988 New Delhi Jaypee Brothers Medical Publishers Ltd 60. Kurtenbach K Hanincová K Tsao JI Margos G Fish D Ogden NH Fundamental processes in the evolutionary ecology of Lyme borreliosis Nat Rev Micro 2006 4 9 660 669 10.1038/nrmicro1475

PMC005xxxxxx/PMC5000479.txt

==== Front J Venom Anim Toxins Incl Trop DisJ Venom Anim Toxins Incl Trop DisThe Journal of Venomous Animals and Toxins Including Tropical Diseases1678-9199BioMed Central London 7910.1186/s40409-016-0079-2ResearchScorpionism by Tityus silvestris in eastern Brazilian Amazon Coelho Johne Souza johne@ufpa.br 12Ishikawa Edna Aoba Yassui ishikawa@ufpa.br 2dos Santos Paulo Roberto Silva Garcez paulogarcez@hotmail.com.br 2Pardal Pedro Pereira de Oliveira pepardal@ufpa.br 21 Postgraduate Program in Tropical Diseases, Center of Tropical Medicine, Federal University of Pará (UFPA), Belém, PA Brazil 2 Laboratory of Medical Entomology and Venomous Animals, Center of Tropical Medicine, Federal University of Pará (UFPA), Av. Generalíssimo Deodoro, 92, Umarizal, Belém, 66055-240 Pará Brazil 26 8 2016 26 8 2016 2016 22 1 2429 1 2016 1 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Scorpionism is a serious public health problem in Brazil. Although cases of envenomation by scorpions are frequent in Brazil, Tityus silvestris – found throughout the Amazon region – is considered of minor medical significance and with only a few descriptions in the literature. This article aims to describe for the first time the epidemiological characteristics and clinical manifestations of scorpion stings by T. silvestris that occurred in eastern Brazilian Amazon. Methods A prospective and observational study was carried out on 13 confirmed cases of T. silvestris envenomation registered from 2007 to 2011 in the cities of Belém and Ananindeua, Pará state, Brazil. Results The stings occurred mainly during daytime, at domiciliary environment, and the scorpions were found in clothing, fruits or vegetables. Envenomation was more frequent in the age group between 21 and 30 years old, upper limbs were more affected and medical aid was usually provided within two hours. Men and women were equally affected. Regarding severity, ten patients were classified as Class I and three patients as Class II according to the Scorpion Consensus Expert Group. Local manifestations were present in all patients, being pain the most common symptom. Mild systemic manifestations including nausea, vomiting, somnolence, malaise and prostration were observed in three victims. Symptomatic treatment of pain was offered to all patients, and only one received specific antivenom. All victims had a favorable outcome. Conclusions To the best of our knowledge, this study is the first to report the systemic symptomatology of envenomation by T. silvestris in the Brazilian Amazon, highlighting the medical relevance of the species in this region. Further research on the venom and clinical manifestations of envenomation by T. silvestris should be conducted in order to verify the relevance of this species to public health. Keywords Scorpion stingScorpionismTityus silvestrisEnvenomationEastern Brazilian Amazonissue-copyright-statement© The Author(s) 2016 ==== Body Background Scorpion envenomation was considered by the World Health Organization a neglected public health issue [1]. According to Chippaux and Goyffon [2], there are about one million and two hundred thousand cases of envenomation worldwide annually. In Brazil, it constitutes a public health problem [3]. Scorpion stings are among the most frequent causes of envenomation in Brazil, responsible for 30 % of the deaths by this cause in the country [4]. Although in Brazil there are about 160 scorpion species described, only Tityus serrulatus, T. bahiensis, T. stigmurus and T. obscurus are considered medically important. Therefore, the species from the Amazon region T. metuendus, T. silvestris and Rhopalurus are of minor medical significance [5]. T. silvestris are among the small scorpions of the family Buthidae in Brazil. They are yellow with scattered dark spots and their body size (in adult specimens) reaches 25 to 45 mm. These scorpions present distinct sexual dimorphism and broad distribution in French Guiana and in the Brazilian Amazon (mainly Amazonas and Pará states) [6]. The symptomatology and severity of scorpion envenomation depends on the species, the amount of inoculated venom and the chemical mediators released. A classification of clinical consequences of scorpion stings was created by an international group of experts [7]. However, studies on the envenomation by T. silvestris are still scarce. For example, Martins et al. [8] reported four cases and Asano et al. [9] only two, all of them classified as Class I of severity [7]. Because of this lack of information, the present study aims to describe, for the first time, the epidemiological characteristics and the clinical manifestations of scorpionism by T. silvestris that occurred in Pará state, eastern Brazilian Amazon. Methods The present study consisted of a prospective and observational analysis based on the records, from 2007 to 2011, of patients envenomed by T. silvestris in the cities of Belém (01° 27' 21" S e 48° 30' 16" W) and Ananindeua (01° 21’ 58”S e 48° 22’ 22” W), Pará state, eastern Amazon (Fig. 1). Belém is capital of the state with an area of 1,059.402 km2 and 1,432.844 inhabitants. Ananindeua is located at Belém metropolitan area, with an area of 190,452 km2 and 499,776 inhabitants [10]. Both cities are surrounded by tropical forests. The climate in these areas is hot and humid, with average annual temperature ranging between 22 ° C and 34 ° C.Fig. 1 Study areas in Pará state, northern Brazil: Belém (green) and Ananindeua (red) cities Patients Thirteen victims of T. silvestris were part of this study. All of them voluntarily sought hospital care and confirmed the envenomation providing the specimens to the medical staff. The animals were identified at the Laboratory of Medical Entomology and Venomous Animals, which is part of the Center of Tropical Medicine, Federal University of Pará, Brazil. Among the available variables, the present study took into account the following data related to the stings: gender and age of the victim, time to medical care, sting site, local and systemic symptoms, severity of envenomation and treatment. The severity of the scorpion stings was organized based on the classification developed by the Scorpion Consensus Expert Group [7]:Class 0 – dry sting or asymptomatic patients. Class I – envenomation with manifestations only at the bite site. Class II – envenomation with minor systemic manifestations, not life threatening. Class III – severe manifestations in which life is threatened, whose symptoms involve cardiogenic, respiratory and/or neurological failure. Results Of the patients who were envenomed, seven (53.8 %) received medical assistance in Belém and six (46.2 %) in Ananindeua. The scorpions collected by the victims were identified as T. silvestris (Fig. 2), according to the taxonomic key of Lourenço [6]. All the scorpions were fixed with ethanol 70 % and are stored at the Laboratory of Medical Entomology and Venomous Animals in the Federal University of Pará.Fig. 2 Tityus silvestris collected in the eastern Brazilian Amazon The reported circumstances of the stings included: time of the day, environment and probable scorpion shelter (Table 1). In addition, other information considered relevant are shown in Table 2, including demographic data, age, gender, time elapsed from the envenomation to medical care and affected area of the body. In Table 3, local and systemic symptoms, severity parameters, clinical severity and treatment are presented.Table 1 Circumstances of scorpionism by T. silvestris in Pará state, eastern Amazon, Brazil Circumstances No. Percent Time of the day  Morning 8 61.6  Afternoon 3 23  Night 2 15.4 Environment  Domiciliary 10 77  Extra-domiciliary 3 23 Scorpion shelter  Garments 7 53.8  Fruits and vegetables 4 30.8  Debris 2 15.4 Table 2 Demographic profile of victims, elapsed time from envenomation to medical care and affected area of the body by T. silvestris stings in Pará state, eastern Amazon, Brazil Variable No. Percent Age group (years) 13 100.0  0-10 1 7.7  11-20 2 15.4  21-30 5 38.4  31-40 2 15.4  41-50 2 15.4  51-60 1 7.7  Md(IQR)a 30(22–40) Gender 13 100.0  Male 7 53.8  Female 6 46.2 Time to medical care 13 100.0  ≤2 h 10 77  2 h to 6 h 3 23 Sting site 13 100.0  Upper limbs 8 61.6  Lower limbs 3 23  Trunk 2 15.4 aMedian and interquartle interval Table 3 Clinical parameters of envenomation in victims of T. silvestris in Pará state, eastern Amazon, Brazil Parameters No. Percent Local symptoms ᅟPain 13 100.0 ᅟParesthesia 5 38.5 ᅟErythema 4 30.8 ᅟEdema 4 30.8 Systemic symptoms ᅟMalaise 1 7.7 ᅟNausea 2 15.4 ᅟVomiting 1 7.7 ᅟProstration 1 7.7 ᅟSomnolence 1 7.7 Severity of symptoms ᅟLocal manifestations 13 100.0 ᅟSystemic manifestations 3 23 Clinical severity ᅟClass I 10 77 ᅟClass II 3 23 Treatment ᅟAnalgesics 13 100.0 ᅟAntivenom 1 7.7 All patients with local manifestations were treated with analgesics and under clinical observation for 3 to 6 h. Out of the three Class II severity patients, only the one with malaise, nausea and prostration was treated with two ampoules of specific antivenom. Hematologic and biochemical assessments were not carried out and the clinical outcome of all patients were favorable. Each vial of antivenom contained 5 mL of product, and 1 mL of it neutralizes 1 mg of T. serrulatus venom in mice. This F(ab’)2 polyspecific hyperimmune equine antivenom was raised against T. serrulatus venom and produced by the Ezequiel Dias Foundation in Minas Gerais state, Brazil. Discussion Epidemiological research conducted in the present study area indicate Belém and Ananindeua as the municipalities with the highest incidence of scorpionism in Pará state, being T. obscurus the main causative agent followed by T. silvestris [8, 9, 11, 12]. These two cities are the most populous of Pará state. The population density of Belém is 1,315 inhabitants/km2 whereas Ananindeua presents 2,477 inhabitants/km2 [10]. Since the number of confirmed envenomation provoked by T. silvestris was small in the present analysis, it is suggested a lower incidence of this species in the geographical areas of the study. The species identified as T. silvestris (according to taxonomic features) belongs to the genus Tityus and the subgenus Archaeotityus [13]. It differs from other Tityus by its small body with scattered dark spots. In this species, there is distinct sexual dimorphism. Epidemiological reports of this species are only described by Asano et al. [9] and Martins et al. [8] in the studied region. Envenomation by other species of this subgenus, such as T. pusillus, were observed in Pernambuco state, Brazil [14]. Scorpionism was more frequent during daytime, corroborating the study Pardal et al. [12] in Pará state, which differs from the observation by Ribeiro et al. [15] in São Paulo state that did not find a period of the day with significant prevalence. Regarding the circumstances of envenomation, Maestri Neto et al. [11], in an epidemiological survey condeucted in Pará state, showed that the domiciliary environment had a higher incidence, which corroborates with the results of the present work. However, Santos et al. [16] in Minas Gerais, Brazil, showed that the work environment was the most affected. It is known that scorpions are found in many different environments [5, 17]. The involved animals of the present study were found mostly in garments and vegetable leaves such as lettuce (Lactuca sativa) and fruits in clusters, such as peach palm (Bactris gasipaes), which when manipulated expose the scorpion to the person handling the plant. Scorpions have specific requirements regarding their habitat and the environmental conditions. Therefore, they can be found in modified environments, especially in urban areas [5]. Possani [17] stated that in Mexican cities scorpions are often found in public markets among fruits and vegetables. According to the age of the victims, young adults were the group most affected by T. silvestris stings. The age range was 9–57 years old, with a median of 30 and interquartile range of 22–40 years. This variable was found in the Brazilian literature, with the age range between 20 and 49 years in the northern region of the country, in the states of Amazonas and Pará [4, 11, 18]. Regarding gender, men were slightly more prevailing. The elapsed time between envenomation and hospital admission found in this study corroborates the findings of other studies in the Amazon region by Pardal et al. [12] and Queiroz et al. [18]. However, these observations did not agree with those of Chippaux [4], who described a longer time in the north than in other parts of Brazil. Probably the fastest hospital admission in the present case is due to the ease of transportation and better equipping of the health network in Belém and Ananindeua. In this study, the upper limbs were the body area most affected by scorpion stings, which agrees with previous Brazilian studies concerning other scorpion species [4, 12, 18, 19]. This fact is probably associated with the use of the upper limbs for handling objects and execution of daily tasks. Among the local symptoms of T. silvestris envenomation, pain at the sting site was the most common, followed by paresthesia, erythema and edema. These results are similar to those described for other Brazilian scorpions, both for the species of minor medical relevance – such as T. pusillus [14] and Rhopalurus amazonicus [20] – and the ones important to public health – as T. obscurus, T. serrulatus, T. bahiensis and T. stigmurus [12, 14, 20–23]. Systemic manifestations were reported in three victims of envenomation by T. silvestris aged between 22 and 57 years, classified in Class II of severity. A 22-year-old patient presented malaise, nausea and prostration. The other, a 48-year-old victim, had only one episode of vomiting, whereas the eldest patient, a 57-year-old person, had nausea and somnolence. These findings corroborate those found in the Brazilian literature, in which more severe envenomation usually affects patients younger than 15 years [24]. According to Reckziegel and Pinto [3], patients younger than 9 years have a higher risk of mortality. T. silvestris is widely distributed in the Amazon region and responsible for mild cases of envenomation, particularly in Pará [5, 6]. To the best of our knowledge, this is the first report of systemic symptoms of envenomation by this species, which may indicate a potential aggressiveness of the venom. Previous reports by Martins et al. [8] and Asano et al. [9] in the same area describe cases of envenomation by scorpions in general, four and two cases, respectively, are attributable to T. silvestris with symptoms only at the sting site [8, 9]. Of the 13 cases of envenomation of the current study, only three were classified in Class II of severity. However, they showed symptoms of mild intensity. Of these, only the patient who developed symptoms of malaise, nausea and prostration received the specific antivenom, while the others were treated with symptomatic medications and life support. All patients had clinical improvement and were discharged from the hospital within six hours of admission. In Brazil, the treatment recommended by the Brazilian Ministry of Health for patients stung by scorpions depends on the severity of the case. For cases with signs and symptoms only at the sting site, symptomatic treatment and medical observation for 6 to 12 h is recommended, whereas Class II and Class III patients should receive specific antivenom [24]. Conclusions This study is the first to report the systemic symptomatology of envenomation by T. silvestris in the Brazilian Amazon, highlighting the medical relevance of this species in this region, whose systemic manifestations were of small magnitude, classified as Class II of severity. Research on the venom and clinical manifestations of the envenomation by the species should be performed to verify its real relevance to public health. Acknowledgements We thank the researcher Denise Candido, Butantan Institute, for the identification of specimens in this study and Regina Dórea for reviewing the manuscript. Authors’ contributions All the authors observed the reported case and contributed to the design of the study and revision of the manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Written informed consent was obtained from the patients or legal guardians for publication of this study. Ethics approval and consent to participate This manuscript was approved by the Research Ethics Committee of the Tropical Medicine Center of the Federal University of Pará, document number 030/2010. ==== Refs References 1. World Health Organization Rabies and envenomings: a neglected public health issue: report of a consultative meeting 2007 Geneva World Health Organization 2. Chippaux JP Goyffon M Epidemiology of scorpionism: a global appraisal Acta Trop 2008 107 2 71 9 10.1016/j.actatropica.2008.05.021 18579104 3. Reckziegel GC Pinto VL Scorpionism in Brazil in the years 2000 to 2012 J Venom Anim Toxins incl Trop Dis 2014 20 46 10.1186/1678-9199-20-46 25873937 4. Chippaux JP Epidemiology of envenomations by terrestrial venomous animals in Brazil based on case reporting: from obvious facts to contingencies J Venom Anim Toxins incl Trop Dis 2015 21 13 10.1186/s40409-015-0011-1 26042152 5. Secretaria de Vigilância em Saúde Departamento de Vigilância Epidemiológica: Manual de Controle de Escorpiões, Série B 2009 Brasília Ministério da Saúde 6. Lourenço WR Scorpions of Brazil 2002 Paris Les Éditions de I’lf 7. Khattabi A Soulaymani-Bencheikh R Achour S Salmi LR Scorpion consensus expert group. Classification of clinical consequences of scorpion stings: consensus development Trans R Soc Trop Med Hyg 2011 105 7 364 9 10.1016/j.trstmh.2011.03.007 21601228 8. Martins MA Barradas L Silva RHV Pardal PPO Estudo clínico e epidemiológico dos acidentes por escorpião atendidos no Hospital Universitário João de Barros Barreto período de janeiro a dezembro de 1996 Rev Para Med 2002 16 1 34 8 9. Asano ME Arnund RM Lopes FOB Pardal JSO Pardal PPO Estudo clínico e epidemiológico de 12 acidentes por escorpiões atendidos no Hospital Universitário João de Barros Barreto, Belém-Pará, no período de 1992–1995 Rev Soc Bras Med Trop 1996 29 Suppl.1 243 10. Instituto Brasileiro de Geografia e Estatística. Cidades: Pará Belém e Ananindeua; 2015. [http://cidades.ibge.gov.br/xtras/perfil.php?lang = &codmun = 150080&search = para|ananindeua]. Accessed on September 07, 2015. 11. Maestri Neto A Guedes AB Carmo SF Chalkidis HM Coelho JS Pardal PPO Aspectos do escorpionismo no Estado do Pará – Brasil Rev Para Med 2008 22 1 49 55 12. Pardal PP Ishikawa EA Vieira JL Coelho JS Dórea RC Abati PA Clinical aspects of envenomation caused by Tityus obscurus (Gervais, 1843) in two distinct regions of Pará state, Brazilian Amazon basin: a prospective case series J Venom Anim Toxins incl Trop Dis 2014 20 1 3 10.1186/1678-9199-20-3 24517181 13. Lourenço WR Nouvelle proposition de découpage sous-générique du genre Tityus C. L. Koch, 1836 (Scorpiones, Buthidae) Bol SEA 2006 39 55 67 14. Albuquerque CMR Porto TJ Amorim MLP Santana Neto PL Escorpionismo por Tityus pusillus Pocock, 1893 (Scorpiones; Buthidae) no Estado de Pernambuco Rev Soc Bras Med Trop 2009 42 2 206 8 10.1590/S0037-86822009000200023 19448944 15. Ribeiro AL Rodrigues L Jorge MT Aspectos clínicos e epidemiológicos do envenenamento por escorpiões em São Paulo e municípios próximos Rev Patol Trop 2001 30 1 83 92 16. Santos PLC Martins FJ Vieira RCPA Ribeiro LC Barreto BB Leite ICG Características dos acidentes escorpiônicos em Juiz de Fora-MG Rev APS 2010 13 2 164 9 17. Possani LD El alacrán y su piquete 2005 18. Queiroz AM, Sampaio VS, Mendonça I, Fé NF, Sachett J, Ferreira LCL, et al. Severity of scorpion stings in the Western Brazilian Amazon: a case–control study. Plos One. 2015;1–14. 19. Guerra CMN Carvalho LFA Colosimo EA Freire HBM Analysis of variables related to fatal outcomes of scorpion envenomation in children and adolescents in the State of Minas Gerais State, Brazil, from 2001 to 2005 J Pediatr 2008 84 6 509 15 20. Fuentes-Silva D Santos-Jr AP Oliveira JS Envenomation caused by Rhopalurus amazonicus Lourenço, 1986 (Scorpiones, Buthidae) in Pará State, Brazil J Venom Anim Toxins incl Trop Dis 2014 20 52 10.1186/1678-9199-20-52 25873941 21. Torrez PP Quiroga MM Abati PA Mascheretti M Costa WS Campos LP Acute cerebellar dysfunction with neuromuscular manifestations after scorpionism presumably caused by Tityus obscurus in Santarém, Pará/Brazil Toxicon 2015 96 68 73 10.1016/j.toxicon.2014.12.012 25549940 22. Bucaretchi F Baracat ECE Nogueira RJN Chaves A Zambrone FAD Fonseca MRCC A comparative study of severe scorpion envenomation in children caused by Tityus bahiensis and Tityus serrulatus Rev Inst Med Trop São Paulo 1995 37 4 331 6 10.1590/S0036-46651995000400008 8599062 23. Lira-da-Silva RM Amorim AM Brazil TK Envenenamento por Tityus stigmurus (Scorpiones; Buthidae) no Estado da Bahia, Brasil Rev Soc Bras Med Trop 2000 33 3 239 45 10.1590/S0037-86822000000300001 10967591 24. Fundação Nacional de Saúde (BR) Manual de diagnóstico e tratamento de acidentes por animais peçonhentos 2001 2 Brasília Ministério da Saúde

PMC005xxxxxx/PMC5000481.txt

==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3213610.1038/srep32136ArticleParticle Size Controls on Water Adsorption and Condensation Regimes at Mineral Surfaces Yeşilbaş Merve 1Boily Jean-François a11 Department of Chemistry, Umeå University, SE-901 87 Umeå, Swedena jean-francois.boily@chem.umu.se26 08 2016 2016 6 3213625 02 2016 03 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Atmospheric water vapour interacting with hydrophilic mineral surfaces can produce water films of various thicknesses and structures. In this work we show that mineral particle size controls water loadings achieved by water vapour deposition on 21 contrasting mineral samples exposed to atmospheres of up to ~16 Torr water (70% relative humidity at 25 °C). Submicrometer-sized particles hosted up to ~5 monolayers of water, while micrometer-sized particles up to several thousand monolayers. All films exhibited vibrational spectroscopic signals akin to liquid water, yet with a disrupted network of hydrogen bonds. Water adsorption isotherms were predicted using models (1- or 2- term Freundlich and Do-Do models) describing an adsorption and a condensation regime, respectively pertaining to the binding of water onto mineral surfaces and water film growth by water-water interactions. The Hygroscopic Growth Theory could also account for the particle size dependence on condensable water loadings under the premise that larger particles have a greater propensity of exhibiting of surface regions and interparticle spacings facilitating water condensation reactions. Our work should impact our ability to predict water film formation at mineral surfaces of contrasting particle sizes, and should thus contribute to our understanding of water adsorption and condensation reactions occuring in nature. ==== Body Mineral surfaces exposed to water vapour can stabilise thin water films (Fig. 1) of various degrees of organisation and thicknesses123, and their mechanisms of formation and growth are the object of an incessantly growing body of literature4. These films are of widespread occurence in nature, and play key roles in atmospheric, terrestrial and astronomical processes5678. In the atmosphere, water films bound to mineral particle (dust) surfaces can impact cloud formation and activity910 as well as scattering and absorption of solar radiation111213141516171819. In fact, while minerals represent only a fraction of all aerosols present in the atmosphere, they can be the prime nucleation sites upon which water and ice grow19. Water and ice films are also of strong relevance to aquatic and terrestrial environments, and even those of the Cryosphere where freeze-thaw cycles impact the fate of nutrients and contaminants, water cycling, as well as gaseous exchanges between terrestrial and atmospheric systems20. These interactions can even be of especial importance in the study of soil microorganisms inhabiting these films21. In outer-space, water and ice films are strongly relevant to the availability of water on planet Mars519, as well as to the catalytic transformations of gases (e.g., CO2) in other planetary and cosmic bodies. Still, an ongoing challenge for all of these settings is to identify the mechanisms triggering water formation, growth and stability. Given the importance of these mechanisms in nature, water binding is the object of extensive field and laborary investigations on environmentally and atmospherically relevant minerals (e.g. clays, quartz, feldspars, carbonates, Arizona Test Dust, volcanic ash)471822232425262728. A recent review by Tang et al.4 provides a comprehensive view of this vast literature, and notably compares the ability of adsorption models at predicting water vapour binding in unsaturated and supersaturated atmospheres of water vapour. From a molecular view, we can regard water binding at hydrophilic surfaces of low-solubility minerals as a two-stage process. The first stage (adsorption) pertains to the attachment of water molecules to mineral surface functional groups via hydrogen bonding (Fig. 1), and should therefore strongly be controlled by mineral surface structural controls. Work with synthetic or purified natural samples is strongly beneficial in this regard, as we have demonstrated in the case of iron (oxyhydr)oxide minerals22930, and revealed the strong impact of crystallographic orientation on the properties of thin nanometric water films. The second stage (condensation) is, in contrast, dominated by water-water interactions at mineral surfaces, and is a distinct process to homogenous water condensation. This can include growth and coalesence of water (nano)droplets and growth multiple layers of liquid water-like overlayers (Fig. 1). It also can occur at open surfaces or promoted within capillaries, in the interlayer of sheet minerals or interspaces of aggregated particles (Fig. 1). This stage should thus be largely independent of the identity of the mineral, but should obey the well-known Kelvin effect31 can be accounting the energetic contributions of water condensation at curved surfaces. In an effort to attempt to generalise these concepts to a wide range of minerals of atmospheric and terrestrial relevance, we explored water vapour binding and condensation reactions on 21 samples of contrasting (i) mineral structure and (ii) composition, (iii) solubility, (iv) particle morphology/crystal habit (v) surface charge, and (vi) particle size/specific surface area (Supplementary Table 1). Minerals considered for this study (Fig. 2) were selected based on their importance in atmospheric and terrestrial systems32 and include (i) a suite of synthetic iron (oxyhydr)oxides of varied structure and particle habits and sizes, (ii) tectosilicates (quartz, microcline), (iii) a nesosilicate (olivine), (iv) expandable (montmorillonite) and non-expandable (kaolinite, illite) phyllosilicates, (v) calcium-magnesium carbonate, (vi) volcanic ash, and finally (vii) the widely-used Arizona Test Dust (ATD) for ice nucleation studies1823272833. In this work we explored the water-binding capabilities of these different minerals under ambient conditions using the Dynamic Vapour Sorption (DVS) technique. Quartz crystal microbalance (QCM) measurements of mineral particles exposed to water vapour revealed that particle size is the key parameter controlling water loadings deposited by condensation reactions. FTIR spectroscopy provided, at the same time, new insight into the hydrogen bonding environments adapted by thin water films in submicron- in relation to micron-sized minerals. These latter efforts notably build upon a recent study in our group focused on the properties of thin ice films formed in the same 21 mineral samples used of this study34. In this current study, we demonstrate the applicability of Hygroscopic Growth Theory (HGT)35 to account for the size dependence on water vapour binding in the 21 minerals under study, and discuss the implications and limitations of this and competing models in accurately accounting for molecular and thermodynamics aspects of the adsorption and condensation regimes. Results and Discussions The water vapour pressure (pw) dependence on water loadings achieved by minerals at 25 °C was first monitored by QCM (Fig. 3). Our results readily revealed contrasting results between submicron and micron-sized particles. Submicron-sized particles clearly revealed adsorption and condensation regimes, expressed as Type II adsorption isotherms36. The adsorption regime can be seen mostly below ~12 Torr H2O where maximal loadings typically lie in the ~5–15 H2O/nm2 range. These loadings are comparable to crystallographic densities of reactive (hydr)oxo groups with which water vapour molecules form hydrogen bonds, and correspond to about one monolayer of water (i.e. 13–15 H2O/nm2 and ~0.28 nm thick, on a geometric basis). In contrast, the condensation regime is predominantly manifested at pw where no more than 70 H2O/nm2, namely ~5 monolayers, are stabilised. The data do not reveal any clear contributions from differences in crystal habit, microporosity or surface (ζ) potential (Table S1). We also note that the largest water loadings achieved in submicron-sized particles occur in (1) ferrihydrite (a high specific surface area iron oxyhydroxide), (2) the bulk of akaganéite (β-FeOOH phase with the hollandite structure with nano-sized (4 × 4 Å) channels running along the length of particles), and in (3) the interlayer spacing of montmorillonites (expandable phyllosilicate minerals). In contrast, larger particles achieved more variable maximal loadings of the order of 1800–30000 H2O/nm2, namely about 120–2300 monolayers (Fig. 3d–f). As none of these loadings can be explained by filling of micropores — estimated by N2(g) adsorption/desorption isotherms (Supplementary Table 1) — these excess water molecules must reside at particle surfaces and even in the spacing between packed particles on the QCM electrodes which could catalyse condensation reactions. In fact, the method of deposition (i.e. heterogeneous coating by rash deposition vs. homogeneous coating by spray deposition, cf. Methods Section and Fig. 1) appear to affect water loadings as, for instance, seen in the case of kaolinite (Fig. 3d,e). Still, we must emphasise that loadings achieved by these contrasting deposition strategies in micron-sized particles remain at least one order of magnitude larger than those acquired on submicron-sized particles (Fig. 3a–c). We also note (i) the strongly contrasting loadings achieved by submicron-sized hematite (10 nm and 50 nm; Fig. 3b) compared to micron-sized hematite (4 μm and 5 μm; Fig. 3e), (ii) the congruent water loadings achieved by lepidocrocite (γ-FeOOH) particles of contrasting shapes (Fig. 3b), (iii) the contrasting loadings achieved in aluminosilicate minerals (montmorillonite, illite, kaolinite) shaped as platelets and with strongly-expressed basal faces, and (iv) a possibly larger water uptake in the K-feldspar-bearing kaolinite (Fluka) than in the purer kaolinite (CMS-KGa-1b) preparations. From these results we can thus largely discard the impact of (i) mineral structure, (ii) composition, (iii) particle morphology/crystal habit and (iv) surface potential (namely ζ-Potential as could be acquired in aqueous media) as major factors driving the water loadings measured by DVS (Supplementary Table 1). FTIR spectroscopy revealed additional insight into the nature of the mineral-bound water films under study (Fig. 4). In all cases did the micrometer-sized particles exhibit highly comparable distributions of O-H stretching frequencies, namely with an intense band at ~3400 cm−1 and a relatively attenuated band at ~3200 cm−1. These spectra can be used to suggest that mineral-bound water molecules form a smaller number and weaker hydrogen bonds than in liquid water. This result can be explained by the relatively thin (e.g. ~1.4 nm for 5 and ~277 nm for 1000 evenly spread monolayers) water films formed at these surfaces, whose structure are less amenable to water-water interactions than in liquid water. In particular thin water (1–3 monolayer) films embedded in the intralayers of montmorillonite exhibit these features. At the same time, the nearly symmetric bending region at ~1610–1640 cm−1 (not shown) is generally comparable to that of liquid water. Thus, the general spectral features of water films adopted by the large particles are comparable with one another, yet not entirely comparable with liquid water or hexagonal ice (Ih)37. The smaller submicron-sized particles exhibited more unique spectral features tailored by the intricate hydrogen bonding interactions between mineral surface (hydr)oxo groups and waters (Fig. 4), as well as discrete bands resulting from surface hydroxo groups. While more detailed discussions on these specific features are best achieved in communications dedicated to these issues, such as in our previous work in iron (oxyhydr)oxides22930, we note that the weaker intensities at the lower O-H stretching frequencies (e.g. ~3200 cm−1) denote smaller extents of water-water interactions in these thinner films. The strongest relationship that could be umambiguously identified between the physicochemical properties of the minerals (Supplementary Table 1), and DVS data (Fig. 3) pertains to particle size (Fig. 5). This relationship is shown for the larger fractions of particles that could be imaged by electron microscopy, and is exponential-like over 3–4 orders of magnitude of values. A log-log10 plot of these values (Fig. 5a) underscores the clear impact of particle size to water loadings especially at pressures exceeding 4 Torr H2O (~17% RH, relative humidity). This finding thus falls in line with current pratices in the atmospheric modelling community38 considering particle size as a parameter for modelling cloud droplet size, aerosol growth and transformation processes38. A formulation of the Hygroscopic Growth Theory (HGT)35 previously developed to undersaturated conditions can readily account for this relation (Fig. 5a). HGT describes water loadings (Θ; e.g. H2O/nm2) in terms of differences in the diameter of wet (D) in relation to dry (Dd) particles39: through a so-called growth factor defined as GF = D/Dd, and assuming a given diameter Dw for a single water molecule (e.g. 0.277 nm for a monolayer density of 13 H2O/nm2). At the base of the calculation of GF is the equation predicting the impact that the particle plays on the activity of water (aw) through the unitless hygroscopic parameter κ: expressed by the ratios of the particulate matter (Vs) and water (Vw) volumes. The introduction of particulate matter to a fixed volume of water should thus decrease aw because mineral-water interactions perturb the structure and hydrogen bond populations and dynamics of interfacially-bound water molecules, and even possibly the energetics (cf. surface tension) of the air/water interface40. GF in HGT developed for unsaturated conditions, and for a given geometric relationship between D and V, is obtained through: where psat is the saturation pressure at a given temperature, and pw/psat = aw is relative humidity expressed as a fraction. This function also accounts for the Kelvin effect on the energetics of water condensation at curved surfaces ( where σs is surface tension (0.072 J ·m−2 at 25 °C), MW is molecular weight and ρw the density water), which is namely effective in particles below ~100 nm in diameter. Because many of the minerals under study are of only negligible to low solubility, only a fraction of the particulate matter actually interacts with mineral surfaces, thus potentially raising uncertainties as to how the Vs/Vw ratio in Eq. 2 relates to the ability of minerals in altering aw, as will be discussed in the latter part of this article. Still, the HGT provides a very reasonable description of the QCM-derived DVS adsorption data (Fig. 5a) with a value of κ≈1 over the different pw values explored in this work. It could, as such, be a recommended value for modelling water condensation at clean mineral surfaces of varied particle size, structure, composition and even surface charge. Certainly, this approach makes the most sense for field-based applications (e.g. atmospheric aerosol chemistry, vadose zone biogeochemistry) involving heterogeneous mixtures of minerals. Although the HGT provides a means at approximately predicting the condensation regime in the larger-sized particles, it does not accurately predict Type II36 adsorption isotherms of the smaller particles as a function of water vapour pressure, where both adsorption and condensation regimes are clearly expressed (e.g. Fig. 6). One possibility that arose during our modelling attempts is to make use of exceeding large κ (e.g. 10–1000) and to scale the resulting Θ values to fit the data. Still, concerns may readily be raised as to how this paramerisation relates to the physicochemical reality of water condensation. Comparison with more classical formulations (cf. Brunauer-Emmett-Teller41, Freundlich42, Frenkel-Halsey-Hill434445), and that were notably recently reviewed by Tang et al.4 (cf. Supplementary information for a synopsis), reveal the strong predictive capability of 2-term Freundlich42 model in predicting both the adsorption and condensation regimes. In addition to this, we value the predictive capability of the Do-Do46 model in describing these regimes in a framework that relates to plausible molecular-scale processes. Although this latter model was originally intended to predict water vapour uptake in microporous carbon, it can be readily adapted to the case of binding onto mineral surfaces (cf. Fig. 3a for gibbsite) in the following manner. In the Do-Do46 formulation: the adsorption (left-hand) and condensation (right-hand) terms are explicitely taken into account with parameters including water-binding sites densities (So, Cμs), association constant (Kf, Kμ) and hydration numbers (β, α). In this approach the adsorption regime is predicted with So values contrained to crystallographic densities of surface (hydr)oxo groups (e.g. 10–15 nm−2) and with a hydration number fixed to β≈2 (or any other estimate) to denote the number of hydrogen bonds involved with first layer water molecules, as often suggested by molecular modelling40. The condensation regime occurs at a pw where water nanoclusters of a given population (e.g. α≈6)46 is achieved. Cμs values derived from this model provide an effective means at summarising the water condensation loadings achieved in the 21 mineral samples under study (Fig. 7). We first note that these values are strongly congruent with particle size (Fig. 7). They can also be roughly predicted, very much like the raw data of Fig. 5, by HGT with κ = 1 when expressed as a function of the larger-sized particles (Fig. 7a) but much not for the smaller size fractions (Supplementary Table 1). An even stronger correlation can be made by expressing these values as a function of specific surface area (ss), and notably where a steep dependence with particles below ~10 m2/g (Fig. 7b) reinforces further the idea that condensation reactions are disfavored in the submicron-sized particles. This even raises even further the importance of recognising that the smallest dimensions of anisotropically-shaped particles (e.g. acicular FeOOH minerals of 5–20 nm in width and a few hundred nm in length) could be the parameter needed to evaluate the extent to which the Kelvin31 effect applies to these surfaces. These observations bring us back to how GF of Eq. 3 is related to the physicochemical reality of the mineral/water interface. As most of the minerals under study are of only negligible to low solubility, release of soluble ions that could potentially decrease the enery barrier for water condensation and/or alteration of surface tension are, in our view, largely limited. In the great majority of the minerals under study only a fraction of the particulate matter actually interacts with mineral surfaces. It is consequently only this fraction, and not the embedded atoms composing the bulk, that influences interfacial water structure, hydrogen bonding populations and dynamics that are collectively affecting water activity. The Dd term could consequently be a proxy comensurating with the propensity of physicochemical features promoting water condensation in micron-sized particles. These features would include nano- to micron-scale surface roughness (e.g. steps, hillocks, crevasses, pores)47 and interparticle spacing (e.g. in aggregated particles, kaolinite booklets, etc.) in aggregated materials, but that have yet to be unambiguously measured and/or observed (e.g. via microscopy). An empirical approach based on the experimental data of this study involves predicting condensable densities of water through: and with values of ss (m2/g) related to particle diameter (Dd in m), through the data shown in Supplementary Figure 1, with: GF can then be generated from pw/psat using Dd in Eq. 3. Still, a future reformulation48495051 of the HGT relating the occurence of sites or regions promoting water condensation to particle size could be a viable strategy for bridging this theory to (molecular-based) adsorption isotherm models. This would represent a much needed step for securing our ability at predicting water condensation at mineral surfaces and their aggregates. Conclusions This study confirms further the notion that water loadings achieved by vapour condensation is strongly controlled by particle size. Micron-sized particles with specific surface area less than ~10 m2/g promote water condensation while submicron-sized particles stabilise water films formed by adsorption. Submicron-sized particles cannot promote condensation reactions due the relative paucity of surface regions of interparticle spaces promoting condensation reactions, and due to the otherwise expected Kelvin effect. Water adsorption isotherms in all 21 mineral under study are best described using (1–2 term) Freundlich and Do-Do models, and the particle size dependence by the HGT model. These findings should consequently help constrain further efforts in advancing knowledge water vapour condensation reactions at surfaces, as well as in evaluating the impact that co-existing solids (e.g. sea sprays), overcoatings (e.g. salts) or even reactive gases (e.g. NOx, SOx, CO2) play in this regard. In particular, we anticipate that these results should be strongly relevant to advancing our knowledge of atmospheric cloud formation processes via condensation reactions of cloud droplets on aerosol particles even under supersaturated conditions4385253. Activation of these so-called cloud condensation nuclei are the object of intense field and laboratory studies, and could be strongly related to particle size, as notably emphasised in a number of studies4385354, and surface defects (e.g pores, kinks, roughness)754, but much less so to the composition of insoluble minerals. This being said, we can anticipate strong departures from this statement for mixed systems containing dissolvable salts (e.g. metal oxide-sea spray salts), or under conditions of photo-, proton- and/or ligand-promoted mineral dissolution55. Additionally, the impact of particle aggregation on water vapour condensation, such as in the lines of our DVS data with particle deposited by spray vs. rash deposition (Fig. 1), warrants further investigations. These possibilities should consequently be more explicitely addressed in future studies with the goal of refining the impact of particle size and chemical composition in the accurate prediction of water adsorption and condensation isotherms such as those presented in this study. Methods Minerals and Characterization All metal (oxyhydr)oxides were synthetised in our laboratory using well-established methods for goethite56 (α-FeOOH), rod- and lath-shaped lepidocrocite56 (γ-FeOOH), akaganéite (β-FeOOH)57, ferrihydrite56 (e.g. Fe8.2O8.5(OH)7.4 + 3 H2O), gibbsite58 (γ-Al(OH3)), as well as nano-sized56 and micron-sized59 hematite (α-Fe2O3). Quartz (α-SiO2), olivine ((Fe,Mg)2SiO4) were taken from the mineral collection of Umeå University and ground to a fine powder with an agate mortar and pestle. Powdered forms of microcline (KAlSi3O8) were obtained from Technical University Darmstadt, and kaolinite (Al2Si2O5(OH)4) were obtained from Fluka (Sigma Aldrich) and from the Clay Mineral Society (KGa-1b). Illite-rich (K,H3O)(Al,Mg,Fe)2(Si,Al)4O10[(OH)2,(H2O)] powder was obtained from Arginotec (B + M Nottenkämper), while Na-montmorillonite was obtained (Ca0.52Na0.14K0.01)(Al3.23Fe3+0.42Mn0.01Mg0.56)(Si7.89Al0.11)O10(OH)2; (SWy-2) from the Clay Mineral Repository, an a portion was Ca-exchanged. Calcium carbonate was obtained from KEBO Lab AB, Arizona Test Dust (ATD) from (Ultrafine Test Dust, Powder Technology Inc.), and volcanic ash from Eyjafjallajökull (Iceland). Salient physical and chemical properties of these minerals are presented in Supplementary Table 1. Phases made in the laboratory were confirmed by our own powder X-ray diffraction (Bruker d8 Advance working in θ−θ mode with Cu Kα radiation) measurements. Those that were acquired were already characterised for phase purity and crystallinity, when applicable, by our providers. All mineral surfaces were tested for surface elemental composition using X-ray photoelectron spectroscopy (Kratos Axis Ultra DLD electron spectrometer). The results of these XPS analyses (Supplementary Table 1) notably show that surfaces are strongly representative of their bulk composition and contain little organic impurities (not shown). Particle sizes were estimated by imaging using Scanning Electron Microscopy (SEM; Zeiss Merlin, GmbH) or Transmission Electron Microscopy (TEM; JE-1230 (JEOL)) (Fig. 1). Up to 5 different particles in each of 3 to 7 different images, and at various magnifications where needed, were investigated to collect information on the distribution of particles sizes, the results of which are presented in Supplementary Table 1. Specific B.E.T. specific surface area and B.J.H. micropore volumes were obtained by 90-point N2(g) gas adsorption/desorption isotherms (Micromiretics) at LN2. Micropore volumes were used to estimate maximal levels of pore water. Supplementary Figure 1 also shows a correlation between B.E.T. specific surface area and particle size estimated by imaging and predicted via Eq. 6. Finally, surface (ζ) potentials of mineral particles were determined at their natural pH of suspension at 25 °C by electrophoresis (Zetasizer, Malvern). Dynamic Vapour Sorption Water vapour uptake by minerals was measured by Quartz Crystal Microbalance (QCM; eQCM 10M, Gamry Instruments Inc.), using with the DVS method at 25 °C. The serial resonance frequency (fs) of a 10 MHz gold-coated quartz resonator was first determined by measurements under a constant total flow rate of 200 standard cubic centimeters per minute (sccm) of dry N2(g). A mass flow controller (MKS, 179A) was used to control this gas flow. The crystal was then coated by pipetting or spraying a dilute aqueous suspension of minerals over the gold area, then drying under a stream of 200 sccm dry N2(g). Montmorillonite samples were dried overnight to remove the interlayer waters. The crystal was then emplaced back into the measurement cell and equilibrated under 200 sccm N2(g) for at least 1 h, after which time fs was determined to obtain the dry, time-independent, weight of the mineral sample. The parallel resonance frequency (fp) was tracked to monitor the viscosity of the mineral films on the quartz resonator. Correlated fp and fs values resulted from thin homogeneous films (Fig. 1e, left) and were observed for FeOOH minerals, gibbsite and illite deposited by pipetting, as well as micron-sized minerals deposited by spraying. Uncorrelated fp and fs values resulted from thicker heterogeneous films (Fig. 1e, right) produced by pipetting of micron-sized particles. This was confirmed further by optical microscopy. Water vapour adsorption isotherms were then collected by monitoring the frequency of the mineral-coated QCM crystal exposed to a steady stream of 200 sccm N2(g) + H2O(g) in the 0–18 Torr H2O range. Water partial pressure was generated by blending streams of dry and water-saturated N2(g) using mass-flow controllers, and monitored with a calibrated Non Dispersible Infrared device (LI-7000, Licor Inc.). This device was also used to ensure that the gases were free of CO2(g). The samples were equilibrated to a fixed partial pressure of water for a 20 to 30 min period to ensure that fs values were time-independent. The Sauerbrey equation was used to convert fs values of the QCM crystal to masses of samples (3.5–41 μg) under N2(g) conditions, and water loadings. Additionally, thin film rigidity was tracked with the parallel resonator frequency (fp) to ensure that the viscocity on water vapour sorbed film is sufficiently large for the measurements to be feasible. FTIR spectra of water vapour sorption at mineral surfaces were collected using an Attenuated Total Reflectance (ATR) accessory (Golden Gate, Specac). Aqueous suspensions of the minerals were centrifuged at their natural pH and then dried directly on the single-bound diamond ATR cell under a stream of N2(g). Samples were then covered with a flow-through cell and exposed to partial pressures of water vapour using the same experimental protocol as in the QCM experiments. All spectra were collected in-situ using a Bruker Vertex 70/V FTIR spectrometer, equipped with a DLaTGS detector, in a room kept at 25 °C. The spectra were collected in the 600–4000 cm−1 spectral range at 4 cm−1 resolution, and with a forward/reverse scanning rate of 10 Hz. Background spectra were collected with the help of gas flow under 200 sccm N2(g). We used the Blackman–Harris three-term apodisation function with 16 cm−1 phase resolution and the Mertz phase correction algorithm. Each spectrum was obtained from 100 scans, each collected over a 89 sec period. A chemometric analysis of the resulting spectra (cf. Fig. S2 for an example with illite) involved the multivariate curve resolution method60 extracting representative spectral components of mineral-bound water films. This method was especially employed for submicron-sized particles, and the spectra shown in Fig. 4 are representative of films at ~8 Torr H2O(g). Additional Information How to cite this article: Yeşilbaş, M. and Boily, J.-F. Particle Size Controls on Water Adsorption and Condensation Regimes at Mineral Surfaces. Sci. Rep. 6, 32136; doi: 10.1038/srep32136 (2016). Supplementary Material Supplementary Information This work was supported by the Swedish Research Council (2012-2976). The authors wish to thank Heike Wex (Leibniz Institute for Tropospheric Research) for providing the kaolinites, illite, microcline and ATD. Eugene Ilton and Odeta Qafoku (Pacific Northwest National Laboratory) are thanked for providing the montmorillonites. Andrei Shchukarev is also thanked for performing XPS analyses. The authors acknowledge the facilities and technical assistance of the Umeå Core Facility Electron Microscopy (UCEM) at the Chemical Biological Centre (KBC), Umeå University. Author Contributions M.Y. performed all of the experiments, analysed the data and co-write the paper. J.-F.B. designed the experiments, analysed data and co-wrote the paper. Figure 1 Schematic representation of water vapour binding at mineral surfaces.(a) The adsorption regime, also involving formation of water clusters. (b) Completion of the adsorption regime involving a monolayer. (c) The condensation regime dominated by water-water interactions. (d) Condensation of water in capillaries/pores of mineral surfaces. (e) Interparticle condensation of water in homogeneous (e.g. spray deposition) and heterogeneous (e.g. by rash deposition) of particles on a substrate. Figure 2 SEM and TEM images of minerals under this study. Figure 3 DVS (25 °C) results of mineral under study. (a) Gibbsite and Do-Do (Equation 4) modelling showing concurrent adsorption and condensation regimes. (a–c) Results for submicron-sized minerals, including expandable montmorillonite (c). (d–f) Results for micron-sized minerals. Figure 4 Representative FTIR spectra of thin water films at mineral surfaces at 25 °C. See example of water vapour binding experiment for the case of illite in Fig. S1. The symbols “*” in goethite, lath lepidocrocite, rod lepidocrocite and akaganéite denote losses in surface22930 (and bulk in akaganéite, cf. Song and Boily57) OH groups caused by water binding. Figure 5 Water loading dependence on (a) particle size and (b) specific surface area of the 21 minerals under study. The Hygroscopic Growth Theory using κ = 1 provides a general description of the condensable water loadings achieved at mineral particles (Equations 1, 2, 3) log10. Figure 6 Best-fits of five dominant models describing water binding on solid surfaces. Fits were obtained by non-linear least square optimisation of model parameters. Equations for the Do-Do (Equation 4), BET, Freundlich, FHH and HGT (Equations 1, 2, 3) are briefly discussed in the Supplementary Section. Figure 7 Condensation saturation densities obtained by fitting of DVS data (Fig. 3) with the Do-Do model (Equation 4) as a function of lower and upper ranges of particle size (a) and specific surface area (b). These latter data can be modeled using the function log(H2O/nm2) = −0.29 (log(ss))2 – 0.76 log(ss) + 4.36, where ss is specific surface area in m2/g. The dashed lines show the model predictions within ~1σ. ‘aka’ is the abbreviation for ‘akaganéite’ and ‘ferri’ for ‘ferrihydrite’. These two FeOOH-like minerals have slightly larger water loadings due to the incorporation of water in the bulk structure of akaganéite57 and possible condensation in aggregated nano-sized ferrihydrite particles log10. ==== Refs Ewing G. E. Ambient Thin Film Water on Insulator Surfaces . Chem. Rev. 106 , 1511 –1526 (2006 ).16608189 Song X. & Boily J. F. Water vapor interactions with FeOOH particle surfaces . Chem. Phys. Lett. 560 , 1 –9 (2013 ). Freedman M. A. Potential Sites for Ice Nucleation on Aluminosilicate Clay Minerals and Related Materials . J. Phys. Chem. Lett. 6 , 3850 –3858 (2015 ).26722881 Tang M. , Cziczo D. J. & Grassian V. H. Interactions of Water with Mineral Dust Aerosol: Water Adsorption, Hygroscopicity, Cloud Condensation, and Ice Nucleation . Chem. Rev. 116 , 4205 –4259 (2016 ).27015126 George C. , Ammann M. , D’Anna B. , Donaldson D. J. & Nizkorodov S. A. Heterogeneous Photochemistry in the Atmosphere . Chem. Rev. 115 , 4218 –4258 (2015 ).25775235 Andreae M. O. & Rosenfeld D. Aerosol-cloud-precipitation interactions. Part 1. The nature and sources of cloud-active aerosols . Earth-Science Reviews 89 , 13 –41 (2008 ). Hoose C. & Möhler O. Heterogeneous ice nucleation on atmospheric aerosols: a review of results from laboratory experiments . Atmos. Chem. Phys. 12 , 9817 –9854 (2012 ). Ehlmann B. L. . Geochemical Consequences of Widespread Clay Mineral Formation in Mars’ Ancient Crust . Space Science Reviews 174 , 329 –364 (2013 ). Rosenfeld D. Suppression of Rain and Snow by Urban and Industrial Air Pollution . Science 287 , 1793 –1796 (2000 ).10710302 Clement A. C. , Burgman R. & Norris J. R. In Science Vol. 325 460 –464 (2009 ).19628865 Rubasinghege G. & Grassian V. H. Role(s) of adsorbed water in the surface chemistry of environmental interfaces . Chem. Commun. 49 , 3071 –3094 (2013 ). Schuttlefield J. D. , Cox D. & Grassian V. H. An investigation of water uptake on clays minerals using ATR-FTIR spectroscopy coupled with quartz crystal microbalance measurements . J. Geophys. Res.-Atmos. 112 , 14 (2007 ). Lohmann U. & Feichter J. Global indirect aerosol effects: a review . Atmos. Chem. Phys. 5 , 715 –737 (2005 ). Phillips V. T. J. , DeMott P. J. & Andronache C. An Empirical Parameterization of Heterogeneous Ice Nucleation for Multiple Chemical Species of Aerosol . J. Atmos. Sci. 65 , 2757 –2783 (2008 ). Archuleta C. M. , DeMott P. J. & Kreidenweis S. M. Ice nucleation by surrogates for atmospheric mineral dust and mineral dust/sulfate particles at cirrus temperatures . Atmos. Chem. Phys. 5 , 2617 –2634 (2005 ). DeMott P. J. . Predicting global atmospheric ice nuclei distrubitions and their impacts on climate . Proc. Natl. Acad. Sci. USA 107 , 11217 –11222 (2010 ).20534566 Frinak E. K. , Mashburn C. D. , Tolbert M. A. & Toon O. B. Infrared characterization of water uptake by low-temperature Na-montmorillonite: Implications for Earth and Mars . J. Geophys. Res.-Atmos. 110 , 7 (2005 ). Zolles T. . Identification of Ice Nucleation Active Sites on Feldspar Dust Particles . J. Phys. Chem. A 119 , 2692 –2700 (2015 ).25584435 Cziczo D. J. . Clarifying the Dominant Sources and Mechanisms of Cirrus Cloud Formation . Science 340 , 1320 –1324 (2013 ).23661645 Dobinski W. The cryosphere and glacial permafrost as its integral component . Central Eur. J. Geosci. 4 , 623 –640 (2012 ). Tecon R. & Or D. Bacterial flagellar motility on hydrated rough surfaces controlled by aqueous film thickness and connectedness . Sci. Rep. 6 , 19409 (2016 ).26757676 Kulkarni G. , Sanders C. , Zhang K. , Liu X. H. & Zhao C. Ice nucleation of bare and sulfuric acid-coated mineral dust particles and implication for cloud properties . J. Geophys. Res.-Atmos. 119 , 9993 –10011 (2014 ). Augustin-Bauditz S. . The immersion mode ice nucleation behavior of mineral dusts: A comparison of different pure and surface modified dusts . Geophys. Res. Lett. 41 , 7375 –7382 (2014 ). Chernoff D. I. & Bertram A. K. Effects of sulfate coatings on the ice nucleation properties of a biological ice nucleus and several types of minerals . J. Geophys. Res.-Atmos. 115 (2010 ). Hoffer T. E. A Laboratory investigatino of droplet freezing . Journal of Meteorology 18 , 766 –778 (1961 ). Kanji Z. A. , Florea O. & Abbatt J. P. D. Ice formation via deposition nucleation on mineral dust and organics: dependence of onset relative humidity on total particulate surface area . Environ. Res. Lett. 3 , 7 (2008 ). Welti A. , Luond F. , Stetzer O. & Lohmann U. Influence of particle size on the ice nucleating ability of mineral dusts . Atmos. Chem. Phys. 9 , 6705 –6715 (2009 ). Zimmermann F. . Ice nucleation properties of the most abundant mineral dust phases . J. Geophys. Res.-Atmos. 113 , 11 (2008 ). Boily J. F. . Thin Water Films at Multifaceted Hematite Particle Surfaces . Langmuir 31 , 13127 –13137 (2015 ).26559158 Song X. & Boily J. F. Water vapor adsorption on goethite . Environ. Sci. Technol. 47 , 7171 –7177 (2013 ).23721420 Thomson W. On the equilibrium of vapour at a curved surface of liquid . Philosophical Magazine, series 4 42 , 448 –452 (1871 ). Wheeler M. J. . Immersion Freezing of Supermicron Mineral Dust Particles: Freezing Results, Testing Different Schemes for Describing Ice Nucleation, and Ice Nucleation Active Site Densities . J. Phys. Chem. A 119 , 4358 –4372 (2015 ).25345526 Steinke I. . Ice nucleation properties of fine ash particles from the Eyjafjallajokull eruption in April 2010 . Atmos. Chem. Phys. 11 , 12945 –12958 (2011 ). Yeşilbaş M. & Boily J.-F. Thin Ice Films at Mineral Surfaces . J. Phys. Chem. Lett. 7 , 2849 –2855 (2016 ).27377606 Petters M. D. & Kreidenweis S. M. A single parameter representation of hygroscopic growth and cloud condensation nucleus activity . Atmos. Chem. Phys. 7 , 1961 –1971 (2007 ). Sing K. S. W. . Reporting physisorption data for gas solid systems with special reference to the determination of surface-area and porosity (Recommendations 1984) . Pure App. Chem. 57 , 603 –619 (1985 ). Maréchal Y. The Hydrogen Bond and the Water Molecule. (Elsevier B. V., 2007 ). Dusek U. . Size matters more than chemistry for cloud-nucleating ability of aerosol particles . Science 312 , 1375 –1378 (2006 ).16741120 Sorjamaa R. & Laaksonen A. The effect of H2O adsorption on cloud drop activation of insoluble particles: a theoretical framework . Atmos. Chem. Phys. 7 , 6175 –6180 (2007 ). Boily J. F. Water structure and hydrogen bonding at goethite/water interfaces: implications for proton affinities . J. Phys. Chem. C 116 , 4714 –4724 (2012 ). Brunauer S. , Emmet P. H. & Teller A. Adsorption of gases in multimolecular layers . J. Am. Chem. Soc. 60 , 309 –319 (1938 ). HMF F. Ûber die Adsorption in Lösnungen . Z. Phys. Chem. 57 , 385 –470 (1906 ). J. F. Kinetic Theory of Liquids. (Oxford University Press, 1946 ). Halsey G. Physical Adsorption on Non‐Uniform Surfaces . J Chem Phys 16 , 931 –937 (1948 ). Hill T. L. Extension of Fowler’s Treatment of Surface Tension to Physical Adsorption . J. Chem. Phys. 17 , 668 –669 (1949 ). Do D. D. & Do H. D. A model for water adsorption in activated carbon . Carbon 38 , 767 –773 (2000 ). Lehmann P. & Or D. Effect of wetness patchiness on evaporation dynamics from drying porous surfaces . Water Resource Res. 49 , 8250 –8262 (2013 ). Petters M. D. & Kreidenweis S. M. A single parameter representation of hygroscopic growth and cloud condensation nucleus activity–Part 2: Including solubility . Atmos. Chem. Phys. 8 , 6273 –6279 (2008 ). Petters M. D. & Kreidenweis S. M. A single parameter representation of hygroscopic growth and cloud condensation nucleus activity–Part 3: Including surfactant partitioning . Atmos. Chem. Phys. 13 , 1081 –1091 (2013 ). Petters M. D. . Role of molecular size in cloud droplet activation . Geophy.s Res. Lett. 36 (2009 ). Henson B. F. An adsorption model of insoluble particle activation: Application to black carbon . J. Geophys. Res. 112 (2007 ). Noziere B. CLOUDS Don’t forget the surface . Science 351 , 1396 –1397 (2016 ).27013716 Wu Z. J. . Some insights into the condensing vapors driving new particle growth to CCN sizes on the basis of hygroscopicity measurements . Atmos. Chem. Phys. 15 , 13071 –13083 (2015 ). Fitzner M. , Sosso G. C. , Cox S. J. & Michaelides A. The Many Faces of Heterogeneous Ice Nucleation: Interplay Between Surface Morphology and Hydrophobicity . J. Am. Chem. Soc. 137 , 13658 –13669 (2015 ).26434775 Rubasinghege G. , Lentz R. W. , Scherer M. M. & Grassian V. H. Simulated atmospheric processing of iron oxyhydroxide minerals at low pH: roles of particle size and acid anion in iron dissolution . Proc. Natl. Acad. Sci. USA 107 , 6628 –6633 (2010 ).20360560 Schwertmann U. & Cornell R. M. The iron oxides: structure, properties, reactions, occurrences and uses. (Wiley-VCH, 2003 ). Song X. & Boily J. F. Water vapor diffusion into a nanostructured iron oxyhydroxide . Inorg. Chem. 52 , 7107 –7113 (2013 ).23701490 Harrington L. F. , Cooper E. M. & Vasudevan D. Fluoride sorption and associated aluminum release in variable charge soils . J. Colloid Interface Sci. 267 , 302 –313 (2003 ).14583205 Shchukarev A. , Boily J. F. & Felmy A. R. XPS of fast-frozen hematite colloids in NaCl aqueous solutions: I. Evidence for the formation of multiple layers of hydrated sodium and chloride ions induced by the {001} basal plane . J. Phys. Chem. C 111 , 18307 –18316 (2007 ). Jaumot J. , Gargallo R. , de Juan A. & Tauler R. A graphical user-friendly interface for MCR-ALS: a new tool for multivariate curve resolution in MATLAB . Chem. Int. Lab. Sys. 76 , 101 –110 (2005 ).

PMC005xxxxxx/PMC5000482.txt

==== Front Sci RepSci RepScientific Reports2045-2322Nature Publishing Group srep3226510.1038/srep32265ArticleThe functional and predictive roles of miR-210 in cryptorchidism Duan Zhengzheng 1Huang Helong 1Sun Fei a121 Department of Cell and Developmental Biology, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230027, China2 Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026, Chinaa feisun@ustc.edu.cn26 08 2016 2016 6 3226522 03 2016 04 08 2016 Copyright © 2016, The Author(s)2016The Author(s)This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Idiopathic diseases of the reproductive system are important factors leading to male infertility. Many studies have shown that microRNAs (miRNAs) regulate the expression of multiple genes that play a significant role in spermatogenesis and development. We previously showed that microRNA-210 (miR-210) is one of the markedly upregulated microRNAs in the testes of sterile males with maturation arrest (MA). However, the role of miR-210 in spermatogenesis remains unknown. In this study, we found that miR-210 is highly expressed not only in patients with MA but also in patients with cryptorchidism. In addition, miR-210 inhibits the expression of Nuclear Receptor Subfamily 1, Group D, Member 2 (NR1D2) both in vitro and in vivo, particularly in cryptorchidic tissues. To facilitate further research, we established a mouse model of cryptorchidism and were surprised to discover that the miR-210 expression pattern was in accordance with that of patients with cryptorchidism. Thus, we propose that miR-210 may serve as a biomarker of cryptorchidism in clinical tests. ==== Body Infertility occurs at a rate of 10–15% among couples of childbearing age, and half of these cases are thought to be due to male infertility1. Furthermore, patients with unexplained non-obstructive azoospermia (NOA), particularly men with maturation arrest (MA, a cause of NOA), usually exhibit a significantly lower sperm retrieval rate and their sperm leads to a lower clinical pregnancy rate. In addition to a variety of external factors, some common conditions, such as cryptorchidism (also known as undescended testes) and varicocele, affect spermatogenesis and are significant causes of male infertility234. During normal development, a testis descends from the waist to the scrotum via the retroperitoneal space. When this migration fails or remains incomplete, the scrotum will have no or at most one testis. This phenomenon is called cryptorchidism or undescended testis456. Cryptorchidism is a common congenital disease of the genitourinary system that negatively affects male infants. The incidence of cryptorchidism is approximately 2 to 4%; however, 30% of premature male infants are affected4. Although there are several hypotheses to explain cryptorchidism, the underlying pathological basis is not yet known. Cryptorchidism has profound influences, particularly on normal spermatogenesis and fertility potential. Additionally, one of the current perspectives holds that cryptorchidism influences testicular function and increases the risk of testicular cancer78. Recently, many studies have suggested that microRNAs (miRNAs) play an important role in spermatogenesis, and their dysregulation has been implicated in various diseases that lead to infertility91011. MicroRNAs are short noncoding RNA molecules (typically 19–23 nucleotides in length) that regulate the post-transcriptional and translational efficiency of target mRNAs through base pairing with their 3′-untranslated regions (3′-UTRs)12. Our previous analyses of microRNA arrays showed that microRNA-210 (miR-210) expression is upregulated in the testes of infertile men with maturation arrest (MA)13. miR-210 is an established target of hypoxia-inducible factors, and its upregulation is a characteristic of hypoxic conditions. Because hypoxia is an essential characteristic in the neoplastic microenvironment, the consistent upregulation of miR-210 under hypoxic conditions is a signature characteristic of solid tumours14. Currently, most investigations of miR-210 function have focused on its relationship with various types of cancer, including pancreatic cancer15 and lung cancer1617. In addition, miR-210 expression has been evaluated as a prognostic factor in breast cancer18. Clinical research involving miR-210 has focused on cancer diagnoses; thus, its expression and function in the reproductive system remains unknown. Here, we characterized the expression of miR-210 in the reproduction system and demonstrated that NR1D2 (Nuclear Receptor Subfamily 1, Group D, Member 2) is a specific target gene of miR-210. To investigate the potential role of miR-210 in spermatogenesis and cryptorchidism, we studied the correlation between miR-210 and NR1D2 in the testicular embryonic carcinoma cell line NTERA-2 (NT-2) and explored potential targets of miR-210 that may participate in testis development. Materials and Methods Tissue samples Human testicular tissue samples from control individuals and patients with MA were obtained from the First Affiliated Hospital of Anhui Medical University (Hefei, China). All patients signed informed consent documents approving the use of their tissues for research purposes. Written informed consent, which conformed to the tenets of the Declaration of Helsinki, was obtained from each participant prior to the study. This study received ethical approval from the institutional review boards of the University of Science and Technology of China and Anhui Medical University. All of the methods strictly abided by the ethical review organizations’ guidelines. Animals Mice were purchased from the Shanghai Laboratory Animal Center (SLAC) and maintained in a specific pathogen-free (SPF) animal facility. The mice were kept at 22 °C with a 14 h light/10 h dark light cycle; they were provided food and water ad libitum. The surgeries were performed while mice were narcotized. Testicular tissues were obtained after the mice were sacrificed by cervical dislocation. All mouse experiments were performed in accordance with the relevant guidelines and regulations. This study received ethical approval from the institutional review board of the University of Science and Technology of China. Cell culture and transfection microRNAs, siRNAs and plasmids NTera-2 (NT-2) cells are derived from human embryonic carcinomas. Cells (NT-2 and HEK293T) were cultured in Dulbecco’s modified Eagle’s medium (DMEM), supplemented with 1% antibiotics (100 U/ml penicillin and 100 mg/ml streptomycin, Life Technologies Inc., Grand Island, NY, USA) and 10% (v/v) foetal bovine serum (Life Technologies Inc.). The cells were cultured at 37 °C in a humidified incubator with 5% carbon dioxide. We used Lipofectamine RNAiMAX (Invitrogen, Carlsbad, CA, USA) and X-tremeGENE HP DNA Transfection Reagent (Roche) to transfect NT-2 cells with oligonucleotides and plasmids. Lipofectamine 2000 Reagent (Invitrogen) was used to transfect 293T cells. All transfection procedures were performed following the manufacturer’s instructions. Shanghai Gene-Pharma Co. (Shanghai, China) synthesized and optimized duplex miR-210 mimics and a miR-210 inhibitor as well as a negative control (NC) and an NC inhibitor. The inhibitor of miR-210 is single-stranded, sequence-specific, and chemically modified to specifically target and knock down miR-210 molecules. NR1D2 siRNA (si.NR1D2) was also designed and synthesized by Shanghai Gene-Pharma Co. The si.NR1D2 sequences were as follows: sense, 5′-GCAUGGUUCUGUGUAATT-3′; antisense, 5′-UUACACAGAACCAUGCTT-3′. The psiCHECK-2 dual-luciferase reporter plasmid was provided by Biliang Zhang (Guangzhou Institute of Biomedicine and Health, Chinese Academy of Sciences, China), and the p3XFLAG-myc-CMV™-24 expression vector was purchased from Sigma. The pEGFP-C1 vector was purchased from BD Biosciences Clontech. Wild-type (WT) plasmids of the NR1D2 3′-UTR were constructed by amplifying a 580-bp 3′-UTR fragment of NR1D2 mRNA and 2258-bp CDS plus 3′-UTR fragment of NR1D2 mRNA harbouring the miR-210 binding site predicted by miRanda (http://www.microrna.org) and DNAman, whereas mutated (MT) NR1D2 3′-UTR was generated by PCR-based site-directed mutagenesis. The WT and MT NR1D2 3′-UTR fragments were fused with the psiCHECK-2 reporter vector at the NotI and XhoI sites. The primers were as follows: WT NR1D2 3′-UTR Forward primer: 5′-TGCCTCGAGCTTCAGATGATTAGACGT-3′ Reverse primer: 5′-ATTGCGGCCGCCATATGGCAGGAACCCTGAA-3′ MT NR1D2 3′-UTR Forward primer: 5′-CAATATAACCGTCAATCACAAG -3′ Reverse primer: 5′-CTTGTGATTGACGGTTATATTG -3′ WT NR1D2 CDS plus 3′-UTR in p3XFLAG vector Forward primer: 5′-ATTGAATTCTATGAAAACAAGCAAATCGAG -3′ Reverse primer: 5′-TGCGTCGACCATATGGCAGGAACCCTGAA-3′ WT NR1D2 CDS plus 3′-UTR in pEGFP vector Forward primer: 5′-ATTGAATTCTATGAAAACAAGCAAATCGAG -3′ Reverse primer: 5′-TGCGTCGACTTAAGGGTGAACTTTAAAGGC -3′ Luciferase reporter assay Luciferase activity was detected using the Dual Luciferase Reporter Assay System (Promega Biotech Co., Ltd, Beijing) after incubating transfected cells for 30 h to allow for the expression of transfected DNA. Renilla luciferase activity was normalized to the firefly luciferase activity in each well. All experiments were repeated in triplicate. Either 40 nM of miR-210 mimic or miR-210 inhibitor were co-transfected with 200 ng of psiCHECK-2 vectors into 293T cells in 24-well plates. Western blotting Cells were lysed in RIPA buffer (50 mM Tris-HCl, pH 7.4, 150 mM, NaCl, 1% Triton X-100, 1% sodium dodecyl sulfate, 1% sodium deoxycholate, and 1 mM EDTA) containing a completely EDTA-free protease inhibitor cocktail (Roche), 1 mM phenylmethylsulfonyl fluoride (PMSF) and phosphatase inhibitors (5 mM sodium orthovanadate). Protein lysates were loaded on SDS-PAGE gels and electroblotted onto nitrocellulose membranes (Amersham Biosciences). The nitrocellulose membranes were blocked for 1 h in 5% non-fat milk in TBST (10 mM Tris, pH 7.5, 200 mM NaCl, and 0.2% Tween 20), followed by incubation with primary antibodies. The antibodies used for Western blotting analysis were anti-NR1D2 (Proteintech Group, Inc.) and anti-Actin (Abcam, Cambridge, MA, USA). In situ hybridization ISH was performed on 10-mm frozen tissue sections using LNA-modified DNA probes. The probe sequences are listed in Supplementary Table 2. Briefly, 10-mm testis biopsy sections obtained from normal controls and NOA patients were fixed with 4% paraformaldehyde for 15 min at room temperature. To block endogenous alkaline phosphatase activity, the slides were immersed and stirred gently in 0.1 M ethanolamine and 2.5% acetic anhydride for 10 min, followed by treatment with 5 mg/ml proteinase K for 3 min after extensive washing with PBS. Prehybridizations were performed for 6 h in a hybridization oven between 21 and 23 °C, which is below the reported melting temperature of the LNAs (57 °C), with 700 ml of prehybridization buffer [50% formamide, 5 × SSC, 5 × Denhardt’s, 200 mg/ml yeast RNA, 500 mg/ml salmon sperm DNA, 2% Roche blocking reagents (Roche, Basel, Switzerland) and DEPC-treated water]. A probe (1 pmol) was added to 150 ml of denaturing hybridization buffer (50% formamide, 5 × SSC, 5 × Denhardt’s, 200 mg/ml yeast RNA, 500 mg/ml salmon sperm DNA, 2% Roche blocking reagents, 0.25% CHAPS, 0.1% Tween and DEPC-treated water). After denaturing at 80 °C for 5 min, hybridization occurred overnight on the prehybridization temperature-covered glass coverslips. To remove the coverslips, the slides were soaked in pre-warmed 60 °C 5 × SSC. After incubation in 0.2 × SSC at 60 °C for 1 h, the sections were washed in B1 solution (0.1 M Tris pH 7.5/0.15 M NaCl) at room temperature for 10 min. After blocking for 1 h in 20% sheep serum (Santa Cruz Biotechnology Inc.) diluted with B1 solution, the sections were incubated overnight at 4 °C in 10% sheep serum containing anti-Digoxigenin-AP FAB fragments (Roche; 1:250). After washing three times for 5 min each in the B1 solution at room temperature and equilibrating for 10 min in B3 solution (0.1 M Tris pH 9.5/0.1 M NaCl/50 mM MgCl2), the sections were stained with NBT/BCIP (Roche) overnight at room temperature. When each probe yielded a strong signal or the NCs began to show background signal, the reactions were stopped by washing with PBS. The signals were visualized by standard light microscopy. Histological analysis and immunohistochemistry (IHC) IHC was conducted to localize the NR1D2 protein in human testicular tissues. Human testes were dissected into pieces, fixed with 4% PFA, embedded in paraffin, and sectioned at 4 um. To confirm the specific infertility syndrome, sections were stained with haematoxylin and eosin following a standard protocol. Initially, slides with testicular tissue sections were heated in 10 mM sodium citrate buffer (pH 6.0) for 10 min, after deparaffinization in a microwave oven. The sections were then dipped into PBS containing 3% H2O2 and 0.1% Triton X-100 to quench endogenous peroxidase activity. After treatment with 10% normal donkey serum (Jackson ImmunoResearch Labs Inc., West Grove, PA, USA) to block non-specific binding signals, the slides were incubated with NR1D2-specific antibody (Proteintech Group, Inc.) overnight at 4 °C and then incubated with a mouse biotinylated secondary antibody (Abcam, Cambridge, MA, USA) for 2 h at room temperature. Immunoreactivity with NR1D2 was visualized using streptavidin-peroxidase and 3,3′-diaminobenzidine (Maixin Bio, Fuzhou, China). RNA extraction and real-time PCR RNA was extracted from cells and subjected to real-time PCR. Briefly, RNA was extracted following a standard TRIzol protocol, and real-time PCR was performed with the ABI Step One System (Applied Biosystems, Foster City, CA, USA) using the SYBR Premix Ex Taq II kit (TaKaRa Bio, Inc.). To detect the relative expression of NR1D2 mRNA and mature miR-210, their expression levels were normalized to β-actin and U6 snRNA, respectively. The qRT-PCR primers are listed in Supplementary Table 1. ELISA The IL-6 concentration was measured with a RayBio Human IL-6 ELISA Kit (RayBio Inc.). Statistical analysis All experiments in this study were performed independently at least three times. Data are shown as the means plus standard errors of the mean (SEMs). A P-value < 0.05 was considered significant. Results MicroRNA-210 is upregulated in NOA patients and expressed in early testicular germ cells, with particularly high expression in testes with cryptorchidism Our previous microRNA array analyses have shown that miR-210 expression is upregulated in the testes of infertile men with MA13. To confirm this finding, we used real-time PCR to detect miR-210 expression in 7 normal controls, 7 SPG arrest samples, 6 SPC samples and 7 hypospermatogenesis samples. We observed a significant upregulation of miR-210 expression in testes obtained from all NOA patients compared with that in normal controls, using real-time PCR (Fig. 1A). In addition, in mouse seminiferous tubules that displayed normal spermatogenesis, miR-210 expression was readily detectable in the spermatogonia and spermatocytes (Fig. 1D). In agreement with the microRNA microarray results, miR-210 was significantly upregulated in testicular specimens displaying MA, such as spermatogonia arrest and spermatocyte arrest. This upregulation may not be exclusive to these patients because miR-210 expression was altered in infertile patients with hypospermatogenesis. Moreover, miR-210 was highly upregulated in patients with cryptorchidism (Fig. 1B). Real-time PCR analysis revealed that miR-210 expression increased significantly in 6 testes with cryptorchidism compared with that of 22 normal controls. Simultaneously, miR-210 expression decreased from the testes of new-born mice to those of adult mice. In testes from new-born mice, miR-210 expression was ten times greater than that in testes from adult mice (Fig. 1C). These data suggest that miR-210 is involved in spermatogenesis or the development of cryptorchidism. NR1D2 is located in spermatogonia and declines in patients with cryptorchidism NR1D2 encodes a member of the nuclear hormone receptor family, specifically the NR1 subfamily of receptors. The encoded protein functions as a transcriptional repressor and plays a role in circadian rhythms and carbohydrate and lipid metabolism1920. Our previous studies found changes in the expression of immune-related genes in patients with cryptorchidism, including the interleukin family and related nuclear receptor family (Figure S2). NR1D2 has not been reported to exhibit any relationship with reproduction. Therefore, the location and expression of NR1D2 in the testis are still unknown. Thus, we explored whether NR1D2 is expressed in spermatogonia or spermatocytes in the testis. Immunohistochemical analyses showed that NR1D2 was in the spermatogonia in the mouse testis (Fig. 2A) and in patients with MA (Fig. 2B), consistent with the localization of miR-210 in human testicular tissues. Additionally, real-time PCR showed that NR1D2 expression was lower in 30 MA patient samples than in 19 normal controls (Fig. 2C). Moreover, NR1D2 expression was significantly downregulated in 7 cryptorchidism samples relative to 8 normal controls (Fig. 2D). NR1D2 is directly targeted by miR-210 To investigate the function of miR-210 in cryptorchidism, we used the microRNA target prediction algorithm miRanda to predict potential targets of miR-210. This analysis revealed that the 3′-UTR of NR1D2 mRNA contains one presumptive miR-210 binding site (positions 309–315) (Fig. 3A). As described above, NR1D2 was upregulated in patients with cryptorchidism. NR1D2 is a transcriptional factor that participates in circadian rhythms, inflammation, carbohydrate and lipid metabolism192122. To determine whether NR1D2 is an authentic target of miR-210, miR-210 mimics/negative control or inhibitor of miR-210/inhibitor control were transfected into NT-2 cells. There was a significant reduction in NR1D2 mRNA levels in miR-210-transfected NT-2 cells (Fig. 3D). In addition, miR-210 downregulated the NR1D2 protein level in NT-2 cells (Fig. 3C). These data indicate that miR-210 modulates NR1D2 expression at the transcriptional and translational levels. To determine whether NR1D2 is a direct target of miR-210, we constructed Renilla luciferase reporters containing either the wild-type full-length NR1D2 3′-UTR or the mutant form of its seeding sites. We analysed 293T cells transfected with constructs carrying the luciferase gene fused with the 3′-UTR of NR1D2 or cells co-transfected with the parent luciferase expression vector and miR-210 mimics or negative control mimics. This resulted in an approximately 37% reduction in luciferase activity, whereas the inhibition of miR-210 expression led to the recovery of luciferase activity. Mutation of the predicted binding site of miR-210 within the 3′-UTR of NR1D2 (MT-NR1D2-3′-UTR) abolished the silencing effect of miR-210 on luciferase activity (Fig. 3B). The results above demonstrate that miR-210 negatively modulates the expression of NR1D2 by directly binding to the seed sequence of the NR1D2 3′-UTR. miR-210 regulates IL-6 by targeting NR1D2 NR1D2 plays a role in circadian rhythms, inflammation, and carbohydrate and lipid metabolism192122. Additionally, the encoded protein functions as a transcriptional repressor23. Because NR1D2 may be involved in the expression of inflammatory factors, we investigated whether cytokines are regulated by NR1D2. Among the numerous inflammatory cytokines, interleukin-6 (IL-6) showed NR1D2-specific regulation. To verify whether NR1D2 is involved in IL-6 regulation, we specifically silenced NR1D2 (si.NR1D2) in NT-2 cells by RNA interference (RNAi). Transfection of NT-2 cells with si.NR1D2 caused a significant decrease in IL-6 at both the transcription (Fig. 4A) and secretion (Fig. 4E) levels. The over-expression of NR1D2 by fusion of the CDS and 3′-UTR (740 bp adjacent to CDS, including the seed sequence) region of NR1D2 with the vector p3XFLAG in NT-2 cells increased transcription and secretion (Fig. 4B,C). In contrast, IL-6 expression was significantly downregulated in NT-2 cells co-transfected with miR-210 and p3XFLAG-NR1D2 compared with in NT-2 cells separately transfected with p3XFLAG-NR1D2 (Fig. 4B,D). miR-210 expression increases in the mouse model of cryptorchidism To determine the expression of miR-210 at different stages of cryptorchidism, we established a mouse model of cryptorchidism. Mice were divided into four groups of 12 mice each. In each group, only 6 mice were treated with surgery; the remaining 6 mice were kept as controls. When mice were under anaesthesia, the testis on one side was fixed to the abdominal cavity using the fat pad near the testis for suturing (Fig. 5A). After surgery, the 4 groups of mice were kept in an SPF-level animal facility for 3, 7, 14 or 21 days. After the corresponding number of days, mouse testis samples were obtained, and the image contrast and testicular weight were analysed. The testes with cryptorchidism decreased significantly in size and weight; by the third day, they increased slightly in size and weight, possibly due to oedema (Fig. 5B). At each time point, the testis contralateral to the operation side did not change significantly in size or weight (Fig. 5B). Correspondingly, the testis index (ratio = (testis weight/body weight) *100%) of the testes with cryptorchidism was downregulated compared with that of controls and untreated testes at 7, 14 and 21 days after surgery. Mutations in the genes insulin-like 3 (Insl3) and relaxin/insulin-like family peptide receptor 2 (also known as LGR8) are associated with cryptorchidism in humans, and changes in their expression have been observed in this model24 (Figure S1). A morphological comparison of the mature sperm from HE-stained testes from the affected and contralateral sides 3 days after surgery showed no differences from those of normal mice (Fig. 5C). By 7 days after surgery, the testes with cryptorchidism showed internal morphological damage and an absence of mature sperm (Fig. 5C). By 14 days after surgery, cavitation was observed in the testes with cryptorchidism in addition to a damaged morphology and lack of mature sperm (Fig. 5C). By 21 days after surgery, the morphology of sperm from the testes with cryptorchidism was completely destroyed, with no internal structure remaining in all levels of germ cells and mature sperm. At the same time, spermatogenesis did not change significantly in the untreated testes compared to the control mice (Fig. 5C). Both the appearance and internal structure of cryptorchidic testes were destroyed; therefore, the testes could not generate mature sperm, which led to infertility. Next, the mRNA expression levels of the relevant molecules were analysed. Except for a slight decline 7 days after surgery, miR-210 expression increased significantly at 14 and 21 days after surgery (Fig. 6A). These results are consistent with the analysis of testis tissue from patients with cryptorchidism. Real-time PCR analysis showed an increase in the expression of NR1D2 and IL-6 (Fig. 6B,C), which was not exactly consistent with the results of the in vitro experiments. Discussion The absence of one or both testes in the scrotum, defined as cryptorchidism, is a very common birth defect of the male genitourinary system. In special cases, cryptorchidism can develop as late as during young adulthood. Approximately 3% of full-term and 30% of premature infant boys are born with at least one undescended testis8. However, approximately 80% of testes with cryptorchidism have descended by the first year of life (the majority within three months), resulting in an overall incidence of cryptorchidism of 1%. Cryptorchidism is distinct from monorchism, the condition of having only one testicle. In recent decades, several studies have focused on microRNA functions during spermatogenesis, but only a few microRNA studies have concentrated on idiopathic diseases of the genitourinary system, including cryptorchidism. In this study, we observed aberrant increases in miR-210 in nonobstructive azoospermia patients and cryptorchidic patients. However, miR-210 is located in the spermatogonia and spermatocytes in human testicular tissues. This pattern suggests that the aberrant increase in miR-210 in the early stage of spermatogenesis is associated with azoospermia and cryptorchidism. Furthermore, NR1D2 was aberrantly expressed in patients with MA or cryptorchidism in this study. NR1D2, also called Rev-erbβ, is very similar to NR1D1 (nuclear receptor family 1 member 1). The major known function of NR1D2, together with NR1D1, is regulating circadian rhythm and metabolism25. NR1D1 and NR1D2 cooperate in regulating core clock function and mediating the interplay between the circadian rhythm and metabolism26. NR1D1 and NR1D2 repress the positive (Bmal1) and negative (Cry1 and NR1D1) limbs of the core clock27. Additionally, NR1D1 and NR1D2 mediate the interaction between the cellular clock and metabolism with BMAL1 and CLOCK/NPAS2 28. However, few reports address the expression of NR1D2 and its function in reproduction. Herein, we report that NR1D2 was localized in spermatogonia and spermatocytes and was downregulated in MA patients and those with cryptorchidism. This result reveals that NR1D2 plays a role in spermatogenesis and affects the occurrence of cryptorchidism. To validate whether these abnormal changes are connected, we performed a series of experiments and demonstrated that miR-210 negatively modulates NR1D2 expression by directly binding to the seed sequence of the NR1D2 3′-UTR. Thus, the aberrant downregulation of NR1D2 in patients with MA and cryptorchidism may be caused by the aberrant increase in miR-210. Furthermore, changes in immune parameters with the disruption of circadian rhythms have been linked to inflammatory pathologies19. Thus, there is compelling evidence that NR1D1 affects immunity. NR1D1 may negatively regulate an unidentified inhibitor(s) that blocks NF- κB activation and thereby induce IL-6 expression2930. Because the NR1D2 protein in mice is ~96% identical to the NR1D1 protein, NR1D2 may be associated with IL-6 expression. Real-time PCR and ELISA experiments were performed to verify that NR1D2 can promote IL-6 expression and secretion as proposed. Additionally, miR-210 reverses these changes in IL-6 by inhibiting NR1D2 expression. To confirm the mechanism that underlies the role of miR-210 in cryptorchidism, we mimicked the effect of cryptorchidism using a surgical procedure in mice. miR-210 expression increased significantly in this cryptorchidism model. However, there was a concomitant increase in NR1D2 expression. Further analysis is required to confirm whether the observed NR1D2 upregulation resulted from the inflammatory response in the model system. In this model, many genes related to inflammation changed significantly (Figure S5). Cryptorchidism caused a stress response and inflammatory reaction. Nevertheless, significant increases in miR-210 expression were demonstrated in tissues derived from both patients with cryptorchidism and mouse testes subjected to experimental cryptorchidism. In summary, a significant increase in miR-210 was observed in the testes of NOA patients, particularly in cryptorchidism. We demonstrated that miR-210 acts as an upstream regulator of NR1D2 function in human cryptorchidism. The mouse model of cryptorchidism verified that miR-210 expression was correlated with cryptorchidism. Our current preliminary research partially revealed the function of NR1D2 and established the regulatory relationship between miR-210 and NR1D2. Even more importantly, this study is the first to confirm the relationship between miR-210 and cryptorchidism. miR-210 may serve as a biological marker of cryptorchidism in clinical tests and may be used to predict the occurrence of cryptorchidism. Additional Information How to cite this article: Duan, Z. et al. The functional and predictive roles of miR-210 in cryptorchidism. Sci. Rep. 6, 32265; doi: 10.1038/srep32265 (2016). Supplementary Material Supplementary Information We thank Dr. Mian Wu for providing the HEK293T cell line. This work was supported by the National Natural Science Foundation of China Grants 81430027 (to F.S.), the National Basic Research Program of China (2014CB943100) (to F.S.) and the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (No. 20152531) (to F.S.). Author Contributions This study was conceived and designed by F.S., Z.D. and H.H. performed the experiments. All authors analysed the data and discussed the results. F.S. wrote the paper, and the other authors commented on the manuscript. Figure 1 MicroRNA-210 is upregulated in NOA patients and expressed in early testicular germ cells, with particularly high expression in testes with cryptorchidism. (A) The expression of miR-210 in the testes of normal controls (OA) and patients with MA (SPG arrest, SPC arrest or hypospermatogenesis) was examined by real-time PCR. (B) The expression of miR-210 in the testes of normal controls (OA) and patients with cryptorchidism, as determined by real-time PCR. (C) The expression of miR-210 in the testes of mice at various experimental time points, as determined by real-time PCR. (D) Localization of miR-210 in the testes of adult mice by LNA-based miRNA in situ hybridization. Representative haematoxylin and eosin staining; hybridization signals (purple) for miR-210 and negative controls are shown. NC, normal controls; SPG, spermatogonia; SPC, spermatocyte. Scale bar = 50 μm. All data are presented as the means ± SEMs from at least three independent experiments. *p < 0.05, ***p < 0.001. Figure 2 NR1D2 is located in spermatogonia and declines in cryptorchidism. (A) Immunohistochemical analysis of the NR1D2 protein in mouse testicular tissue. (B) Immunohistochemical analysis of the NR1D2 protein in human testicular tissue from patients with maturation arrest. SPG, spermatogonia; scale bar = 50 μm for all images. (C) NR1D2 mRNA levels in the testes of normal controls (OA) and patients with maturation arrest, as detected by real-time PCR. (D) NR1D2 mRNA levels in the testes of normal controls (OA) and patients with cryptorchidism, as detected by real-time PCR. *p < 0.05, **p < 0.01. Figure 3 NR1D2 is directly targeted by miR-210. (A) Putative binding sites for human miR-210 were predicted in the 3′-UTR of NR1D2 mRNA. The mutated bases of predicted miR-210 binding sites are underlined, namely MT-NR1D2 3′-UTR. (B) miR-210 targeted the 3′-UTR of NR1D2. Luciferase reporters containing either miR-210 putative binding sites from the wild-type NR1D2 3′-UTR (WT NR1D2-3′-UTR) or mutated NR1D2 3′-UTR (MT NR1D2-3′-UTR) were co-transfected with the indicated microRNA mimics into 293T cells. Luciferase activity was measured 30 h after transfection. (C) The NR1D2 protein was quantified by Western blotting. NT-2 cells were harvested 48 h after transfection with RIPA lysis buffer. Gels were run under the same experimental conditions (120 V for 90 mins). (D) NR1D2 mRNA expression was evaluated by real-time PCR. Total RNA was extracted 48 h after transfection using a standard TRIzol protocol. WT: wild-type, MT: mutant, MNC: normal control mimics, M210: miR-210 mimics, INC: normal control inhibitors, I210: miR-210 inhibitors. All data are presented as the means ± SEMs from at least three independent experiments. *p < 0.05, **p < 0.01. Figure 4 miR-210 regulates IL-6 by targeting NR1D2. (A,E) Silencing of NR1D2 resulted in downregulated IL-6 mRNA and secretion levels. NR1D2 siRNA (si.NR1D2) or negative control (si.NC) were transfected into NT-2 cells at 200 nM and harvested 48 h after transfection. (C) Upregulated IL-6 secretion levels in association with NR1D2 overexpression. (B,D) miR-210 reversed NR1D2-induced IL-6 mRNA expression and secretion. Flag-NR1D2 and miR-210 mimics were co-transfected into NT-2 cells. Cells were harvested 48 h after transfection. MNC: normal control mimics, M210: miR-210 mimics. All data are presented as the means ± SEMs from at least three independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001. Figure 5 The mouse cryptorchidism model. (A) The normal (black circle) and cryptorchid (red circle) mouse testes. (B) Photographs of the testes of mice with cryptorchidism (the top panel) and the corresponding testis index (the bottom panel). The testis samples were obtained at 3, 7, 14, 21 days after the cryptorchidism surgery on mice. The testis index was expressed as (testis weight/body weight) *100%. Con: control, UT: Untreated side, T: Treated side. (C) HE analysis of the testes of mice with cryptorchidism. The testis sections were obtained at 3, 7, 14, 21 days after the cryptorchidism surgery on mice. The testes from the treated and untreated sides 3 days after surgery showed no differences from those of control mice. By 7 days after surgery, the testes with cryptorchidism showed internal morphological damage and an absence of mature sperm. By 14 days after surgery, cavitation was observed in the testes with cryptorchidism in addition to a damaged morphology and lack of mature sperm. By 21 days after surgery, the morphology of sperm from the testes with cryptorchidism was completely destroyed, with no internal structure remaining in all levels of germ cells and mature sperm. At the same time, spermatogenesis did not change significantly in the untreated testes compared to the control mice. Bar = 50 μm for all images. *p < 0.05. Figure 6 miR-210, NR1D2 and IL-6 expression in mice with cryptorchidism. (A) miR-210 expression in mice with cryptorchidism. (B) NR1D2 expression in mice with cryptorchidism. (C) IL-6 expression in mice with cryptorchidism. Tissue RNA was extracted with TRIzol and examined by real-time PCR. All data are presented as the means ± SEMs from at least three independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001. ==== Refs Matzuk M. M. & Lamb D. J. Genetic dissection of mammalian fertility pathways . Nat Cell Biol. 4 Suppl, s41 –s49 (2002 ).12479614 Virtanen H. E. & Toppari J. Cryptorchidism and Fertility . Endocrinol Metab Clin North Am. 44 , 751 –760 (2015 ).26568490 Guerrero-Bosagna C. & Skinner M. K. Environmentally induced epigenetic transgenerational inheritance of male infertility . Curr Opin Genet Dev. 26 , 79 –88 (2014 ).25104619 Fantasia J. , Aidlen J. , Lathrop W. & Ellsworth P. Undescended Testes: A Clinical and Surgical Review . Urol Nurs. 35 , 117 –126 (2015 ).26298946 Hanerhoff B. L. & Welliver C. Does early orchidopexy improve fertility? Transl Androl Urol. 3 , 370 –376 (2014 ).26816793 Hollowell J. G. Undescended testis and infertility-Is hormonal therapy indicated? Transl Androl Urol. 3 , 377 –381 (2014 ).26814848 Cobellis G. . Spermatogenesis and cryptorchidism . Front Endocrinol (Lausanne) 5 , 63 (2014 ).24829558 Banks K. . Cryptorchidism and testicular germ cell tumors: comprehensive meta-analysis reveals that association between these conditions diminished over time and is modified by clinical characteristics . Front Endocrinol (Lausanne) 3 , 182 (2012 ). Yao C. . MicroRNAs and DNA methylation as epigenetic regulators of mitosis, meiosis and spermiogenesis . Reproduction 150 , R25 –R34 (2015 ).25852155 Tian H. . The targeting and functions of miRNA-383 are mediated by FMRP during spermatogenesis . Cell Death Dis. 4 , e617 (2013 ).23640459 Yuan S. . mir-34b/c and mir-449a/b/c are required for spermatogenesis, but not for the first cleavage division in mice . Biol Open 4 , 212 –223 (2015 ).25617420 Bartel D. P. MicroRNAs: genomics, biogenesis, mechanism, and function . Cell 116 , 281 –297 (2004 ).14744438 Lian J. . Altered microRNA expression in patients with non-obstructive azoospermia . Reprod Biol Endocrinol. 7 , 13 (2009 ).19210773 Huang X. , Le Q. T. & Giaccia A. J. MiR-210–micromanager of the hypoxia pathway . Trends Mol Med. 16 , 230 –237 (2010 ).20434954 Wang J. . MicroRNAs in plasma of pancreatic ductal adenocarcinoma patients as novel blood-based biomarkers of disease . Cancer Prev Res (Phila) 2 , 807 –813 (2009 ).19723895 Anjuman N. , Li N. , Guarnera M. , Stass S. A. & Jiang F. Evaluation of lung flute in sputum samples for molecular analysis of lung cancer . Clin Transl Med. 2 , 15 (2013 ).24053570 Lu J. . Potential Role of MicroRNA-210 as Biomarker in Human Cancers Detection: A Meta-Analysis . Biomed Res Int. 2015 , 303987 (2015 ).26446394 Li Y. . microRNA-210 as a prognostic factor in patients with breast cancer: meta-analysis . Cancer Biomark 13 , 471 –481 (2013 ).24595085 Curtis A. M. , Bellet M. M. , Sassone-Corsi P. & O’Neill L. A. Circadian clock proteins and immunity . Immunity 40 , 178 –186 (2014 ).24560196 Koh Y. S. & Moore D. D. Linkage of the nuclear hormone receptor genes NR1D2, THRB, and RARB: evidence for an ancient, large-scale duplication . Genomics 57 , 289 –292 (1999 ).10198169 Palmieri O. . Systematic analysis of circadian genes using genome-wide cDNA microarrays in the inflammatory bowel disease transcriptome . Chronobiol Int. 32 , 903 –916 (2015 ).26172092 Laing E. E. . Exploiting human and mouse transcriptomic data: Identification of circadian genes and pathways influencing health . Bioessays 37 , 544 –556 (2015 ).25772847 De Mei C. . Dual inhibition of REV-ERBbeta and autophagy as a novel pharmacological approach to induce cytotoxicity in cancer cells . Oncogene 34 , 2597 –2608 (2015 ).25023698 Ferlin A. . The INSL3-LGR8/GREAT ligand-receptor pair in human cryptorchidism . J Clin Endocrinol Metab 88 , 4273 –4279 (2003 ).12970298 Ramakrishnan S. N. , Lau P. , Burke L. J. & Muscat G. E. Rev-erbbeta regulates the expression of genes involved in lipid absorption in skeletal muscle cells: evidence for cross-talk between orphan nuclear receptors and myokines . J Biol Chem. 280 , 8651 –8659 (2005 ).15623503 Yin L. . Rev-erbalpha, a heme sensor that coordinates metabolic and circadian pathways . Science 318 , 1786 –1789 (2007 ).18006707 Rudic R. D. . BMAL1 and CLOCK, two essential components of the circadian clock, are involved in glucose homeostasis . PloS Biol. 2 , e377 (2004 ).15523558 Bugge A. . Rev-erbalpha and Rev-erbbeta coordinately protect the circadian clock and normal metabolic function . Genes Dev. 26 , 657 –667 (2012 ).22474260 Migita H. , Morser J. & Kawai K. Rev-erbalpha upregulates NF-kappaB-responsive genes in vascular smooth muscle cells . FEBS Lett. 561 , 69 –74 (2004 ).15013753 Sato S. . Direct and indirect suppression of interleukin-6 gene expression in murine macrophages by nuclear orphan receptor REV-ERBalpha . Scientific World Journal 2014 , 685854 (2014 ).25401152

PMC005xxxxxx/PMC5000483.txt

==== Front BMC CancerBMC CancerBMC Cancer1471-2407BioMed Central London 270410.1186/s12885-016-2704-4Study ProtocolTailored Beta-catenin mutational approach in extra-abdominal sporadic desmoid tumor patients without therapeutic intervention van Broekhoven Danique L.M. +31-10-7041223d.vanbroekhoven@erasmusmc.nl 1Grünhagenl Dirk J. d.grunhagen@erasmusmc.nl 1van Dalen Thijs tvdalen@diakhuis.nl 2van Coevorden Frits f.v.coevorden@nki.nl 3Bonenkamp Han J. han.bonenkamp@radboudumc.nl 4Been Lukas B. l.b.been@umcg.nl 5Bemelmans Marc H.A. m.bemelmans@mumc.nl 6Dijkstra Sander D.S. p.d.s.dijkstra@lumc.nl 7Colombo Chiara Chiara.Colombo@istitutotumori.mi.it 8Gronchi Alessandro alessandro.gronchi@istitutotumori.mi.it 8Verhoef Cornelis c.verhoef@erasmusmc.nl 11 Erasmus MC Cancer Institute, Rotterdam, The Netherlands 2 University Medical Center Utrecht, Utrecht, The Netherlands 3 Netherlands Cancer Institute, Amsterdam, The Netherlands 4 Radboud University Medical Center, Nijmegen, The Netherlands 5 University Medical Center Groningen, Groningen, The Netherlands 6 Maastricht University Medical Center, Maastricht, The Netherlands 7 Leiden University Medical Center, Leiden, The Netherlands 8 Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy 26 8 2016 26 8 2016 2016 16 1 68619 11 2015 10 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The efficacy of the classical treatment modalities surgery and radiotherapy in the treatment of aggressive fibromatosis is presently disputed and there is a shift towards a more conservative approach. The aim of the present study is to objectify tumor growth in patients with extra-abdominal or abdominal wall aggressive fibromatosis, while adhering to a “watchful waiting” policy. Other objectives are to investigate quality of life and to identify factors associated with tumor growth, in particular the relation with the presence of a CTNNB1-gene mutation in the tumor. Design and methods GRAFITI is a nationwide, multicenter, prospective registration trial. All patients with extra-abdominal or abdominal wall aggressive fibromatosis are eligible for inclusion in the study. Main exclusion criteria are: history of familiar adenomatous polyposis, severe pain, functional impairment, life/limb threating situations in case of progressive disease. Patients included in the study will be treated with a watchful waiting policy during a period of 5 years. Imaging studies with ultrasound and magnetic resonance imaging scan will be performed during follow-up to monitor possible growth: the first years every 3 months, the second year twice and the yearly. In addition patients will be asked to complete a quality of life questionnaire on specific follow-up moments. The primary endpoint is the rate of progression per year, defined by the Response Evaluation Criteria In Solid Tumors (RECIST). Secondary endpoints are quality of life and the rate of influence on tumor progression for several factors, such as CTNNB1-mutations, age and localization. Discussion This study will provide insight in tumor behavior, the effect on quality of life and clinicopathological factors predictive of tumor progression. Trial registration The GRAFITI trial is registered in the Netherlands National Trial Register (NTR), number 4714. Keywords Aggressive fibromatosisDesmoidDesmoid-type fibromatosisWatchful waitingWait-and-seeGrowthProgressionissue-copyright-statement© The Author(s) 2016 ==== Body Background Biological behavior Desmoid-type fibromatoses are rare, non-metastasizing, locally aggressive soft tissue tumors. Aggressive fibromatoses can be located in every part of the body and are classified as extra-abdominal, abdominal wall or intra-abdominal [1, 2]. The abdominal wall is a predilection site in women of reproductive age [3]. Sporadic onset of the tumor is common, but an association with familiar adenomatous polyposis (FAP) has been documented, in particular in intra-abdominally localized aggressive fibromatoses [4]. The course of the disease is unpredictable and varies between relatively indolent, i.e. stabilization of the tumor, and progressive growth, which may halt spontaneously [5]. The reported frequency of recurrence following local treatment ranges from 5 to 63 % [6]. Genetic markers in tumor tissue have been analyzed, in particular the CTNNB1-gene. CTNNB1-gene encodes beta-catenin, a proto-oncogene involved in cell adhesion and cell transcription. Beta-catenin is a key factor in the Wnt-APC-beta-catenin pathway. On a cellular level the beta-catenin protein level is elevated in these tumors, implicating beta-catenin stabilization as a key factor in the pathogenesis of aggressive fibromatosis [7, 8]. Nuclear overexpression of beta-catenin is a histological condition used in a diagnostic. The diagnostic value is sensitive, but not specific [8–10]. Research on the CTNNB1-gene revealed 3 specific mutations, namely T41A, S45F and 45P [8, 10]. While it is yet unclear how these mutations precisely affect the aforementioned pathway in these tumors, a role in biologic behavior seems natural according to their role in pathogenesis. Several groups have analyzed CTNNB1-mutation and these mutations appear to have a prognostic value in determining the risk of recurrence in retrospective series of surgically treated patients [11–15]. Although Mullen et al. did not find a statistical significant prognostic [15], several other groups reported a higher risk of recurrence for patients with an S45F-mutation [11–13], even in multivariate analysis [12]. In addition, (surgical) trauma and hormones presumably play a role in the genesis of this tumor, as aggressive fibromatosis is known to arise in scars and in fertile females [16]. Treatment Treatment of aggressive fibromatosis classically involves surgery, combined with radiotherapy on indication. Literature on the effects of surgery and radiotherapy on the rate of recurrence is conflicting [17–19]. While these effects are still being questioned, treatment policies have recently turned towards a more conservative approach. Nowadays, a watchful waiting approach is being advocated by various authors and is currently the standard in European care [20–25]. Retrospective studies showed that progression usually occurs within 2 years of diagnosis. Fiore et al. [22] reported a median time till progression of 14 months, with 89 % of progression observed within 2 years, while Salas et al. [18] described a median time till progression of 20 months. In addition, these studies have also reported spontaneous regression in up to 18.5 % of the patients [18, 22]. The ability to predict tumor behavior would enable tailoring individual patient treatment. Little is known about tumor growth. Available literature is dated and descriptive, without objective measurements [16]. Study aim The GRAFITI study will evaluate a watchful waiting approach as an initial treatment for patients with extra-abdominal or abdominal wall aggressive fibromatosis. The primary objective is to assess tumor progression using the Response Evaluation Criteria In Solid Tumors (RECIST) [26]. We will attempt to identify patient-and tumor characteristics related to growth. A twin study is ongoing in Milan, Italy (NCT02547831). The present study proposal was designed in collaboration with the Italian study group, to facilitate a possible future merger of data. Design and methods Study design GRAFITI was designed in collaboration with experts in sarcoma care throughout the Netherlands as a nationwide prospective observational study. All patients with extra-abdominal or abdominal wall aggressive fibromatosis are eligible for participation. Inclusion and exclusion criteria are discussed below. If not included, treatment options will be discussed by the local multidisciplinary teams. Treatment modalities include systemic treatment, surgery and radiotherapy, and individualized treatment will be chosen based on patient characteristics, tumor localization and predicted outcome. Patients will be treated by a watchful waiting policy and asked to complete quality of life questionnaires. During follow-up, imaging studies will be performed to monitor tumor growth. In case of growth, all treatment options will be evaluated, including continuation of watchful waiting. A switch in treatment strategy will be monitored and reasons for this switch documented (see Fig. 1).Fig. 1 Flowchart Primary objective The primary objective is to assess tumor progression in terms of objectifying and monitoring growth during watchful waiting policy as an initial treatment. Ultrasound and MRI imaging will be used to determine tumor size. Tumor behavior will be scored using RECIST. Primary endpoint is the rate of progression per year, which will be measured after 5 years of follow-up. Secondary objectives The secondary objective is to investigate the effect of treatment on the quality of life. During the study period, patients will be asked to complete the EORTC QLQ-C30 questionnaire five times: at inclusion and after 6,12,24 and 60 months. After a switch to active treatment, patients will remain on-study for the questionnaires. The scores will be evaluated and related to treatment policy. Other objectives are to analyze the value of clinicopathological factors, including CTNNB1-gene mutation, in predicting progression. The reasons and considerations for active treatment will be analyzed in relation to the applicability of a watchful waiting policy. Study population The study will take place in the Netherlands. All patients with extra-abdominal or abdominal wall aggressive fibromatosis are eligible for inclusion in the study. Primary and recurrent disease will be included, stratification will be done for analyses. Inclusion criteria Histological evidence of aggressive fibromatosis. Capable to undergo MRI-scans and ultrasounds. Capable to understand and sign informed consent. Exclusion criteria Age <18 years. Personal or family history of FAP. Intra-abdominal tumor localization. Previous treatment for the current manifestation (recurrent lesions without previous treatment are included). Severe pain or functional impairment due to the tumor (as indicated by the patient. The use of painkillers is not an exclusion criterion). Tumor progression leading to mutilation or life/limb-threatening situations, as assessed by the attending physician. Sample size Based on the incidence of sporadic aggressive fibromatosis and tumor localization, we expect to include 20 patients annually, we aim to include 100 patients in 5 years. Loss to follow-up or death is not to be expected. Under the most adverse conditions, a progression rate of 50 % would result in a 95 % confidence interval (95 % CI) of 40–60 %. A progression rate of 25 % would result in a 95 % CI of 18–34 %. We consider the presented 95 % CI to be acceptable for the study. Methods Participation in the study implies that the work-up does not deviate from present common practice. A contrast enhanced MRI-scan (T1 and T2 weighted) is used to determine the precise localization, size and involved structures. Subsequently, and also in line with national guidelines, the patient will undergo an ultrasound-guided, histological needle-biopsy of the soft tissue tumor, with a 14 G needle. Preferably 3 biopsies will be obtained. During the ultrasound, tumor size will be measured in three dimensions. In addition, as part of this study a quality of life questionnaire is completed by the patient. The follow-up schedule is set for 9 outpatient-clinic visits (see Table 1). During each visit imaging studies will be performed to monitor possible growth. In addition, patients will be asked to complete a questionnaire during 5 follow-up visits. The radiology report of the ultrasound or MRI-scan will specify the maximum diameter in all 3 dimensions and the growth in relation to previous radiological examinations. When ultrasonography suggests tumor progression, an MRI-scan is additionally made as standard care and considered as the golden standard for detecting changes within the tumor.Table 1 Follow-up schedule Assessment Enrollment Year 1 Year 2 Year 3–5 Month 3 6 9 12 18 24 36 48 60 History and Physical examination x x x x x x x x x x MRI-scan x x x x x Ultrasound x x x x x x QoL questionnaire x x x x x In case of tumor progression, the patient will be re-evaluated. If the patient is still eligible, watchful waiting policy will be continued. If not, local or systemic treatment will be started and considerations to switch treatment strategies will be documented. After inclusion of all patients, pathology specimens will be collected by one pathology laboratory and CTNNB1-gene analysis will be performed for all patients. If CTNNB1-mutation status is already known, this procedure will not be repeated. Statistical considerations Statistical analysis will be carried out using IBM SPSS Statistics 21. Radiological measurements will be registered as a continuous variable at ratio. The average progression rate per year will be analyzed using data of all patients. The progression rate per year, defined as increase in size per tumor, using RECIST criteria, with the associated range and confidence interval, will be registered as the primary outcome. The QLQ-C30 questionnaire results in a score to classify the quality of life. This score will be registered as discrete data at ratio scale. If a score cannot be rewarded, the data of the questionnaire will be regarded as missing data. If a score is missing, but later registered scores are available, the later scores will be used in assessment of the quality of life. The overall quality of life will be calculated using data of all patients at the end of follow-up. The median value will be extracted with the associated range. The possible influence of patient and tumor related factors on the progression rate and the quality of life are analyzed using the Kaplan-Meier method and univariable Cox-regression. Associations between variables will be explored by Chi-square analysis. Multivariate analysis will be performed if possible by means of Cox-regression. Those factors which prove to have statistical significance in univariate analyses, will be included in the multivariate analysis. The considerations for treatment will be categorized and analysis will show the occurrence of specific considerations. The interim analysis of both primary and secondary parameters will be done after one year of follow-up on 20 patients. The analyses will be the same as described above and will be performed by the principal investigator. For all analyses, two-sided P < 0.050 is considered statistically significant. Discussion During the last decade, there has been a shift in treatment strategy for aggressive fibromatosis from aggressive to conservative modalities. A watchful waiting policy is currently advised for extra-abdominal and abdominal wall aggressive fibromatosis [25]. Research validating the efficacy and applicability of a watchful waiting policy is limited. Mitchell et al. were the first to describe a stable phase for aggressive fibromatosis [5]. In a retrospective study of 17 patients under medical observation, all experienced at least one period of stable disease for over 6 months. A larger study by Fiore et al. evaluated 142 patients with primary and recurrent aggressive fibromatosis, treated with initial conservative treatment retrospectively [22]. Approximately 50 % of the patients did not have tumor progression after 1 year. Spontaneous regression has been reported by Salas et al. [18]. In a retrospective study analyzing 426 patients with aggressive fibromatosis, 27 patients were treated with a watchful waiting policy. Five of these patients had spontaneous remission, 16 patients stable disease and 6 patients had progressive disease. The median time to progression was 19.7 months. A recent study by Colombo et al. reported 216 patients with primary extra-abdominal (n = 188) and intra-abdominal (n = 28) disease undergoing a diversity of treatments [24]. Initial wait-and-see policy was applied in 70 patients (60 extra-abdominal) and continued till the end of follow-up in 60 %. Progression occurred in 16 of the 70 patients, mostly treated with systemic modalities. These results demonstrate the potential safety of a watchful waiting policy. Current knowledge on predictive factors is mostly based on surgical cohorts. Age, tumor localization and tumor size have been reported as predictive factors for the risk of recurrence following surgery. A nomogram was proposed by Crago et al. [27] using all these factors in a postoperative setting. In addition, CTNNB1-mutations are found to be a predictive factor for the risk of recurrence following surgery [12–14, 16]. The value of these factors in a postoperative setting cannot be extrapolated to a watchful waiting setting. The present study was designed to evaluate the role of these factors in relation to the progression rate in a watchful waiting setting. This information would help in determining which patients can safely undergo a watchful waiting policy, and which patients would benefit most from active treatment. The ability to predict tumor behavior would enable tailoring individual patient treatment and prevent over-or undertreatment. The low incidence of aggressive fibromatosis presents a challenge for quality research. Collaborations between specialized institutions is essential. The prospective evaluation of predictive factors in a watchful waiting setting has been initiated by two other research groups. In France, Bonvalot et al. are conducting a similar study (ClinicalTrials.gov identifier NCT01801176). They have finished the inclusion process and are now conducting the final follow-up. In Italy, a similar study is coordinated by Colombo et al. (ClinicalTrials.gov identifier NCT02547831). This study is still open and we encourage inclusion. The present study was designed to resemble the French and Italian study, to facilitate a possible merging of the data if the inclusion rate in the studies would be disappointing. Main inclusion and exclusion criteria match for all three studies, though our study also includes patients presenting with recurrent disease. The occurrence of aggressive fibromatosis has been related to hormonal influences and pregnancy by Häyry and Reitamo et al. [16, 28]. Although hormonal levels and receptors on the tumor have not been investigated, the occurrence of disease among fertile females is very suggestive. A recent study by van Broekhoven et al. evaluated time trends in the Dutch population [29]. Their analysis between incidence and hormonal influences did not show a positive correlation. In an attempt to evaluate the hormonal influence, data on the use of hormonal medication and history of pregnancy will be collected during the present study. Intra-abdominal tumor depositions and personal or family history of FAP are among the exclusion criteria for the presented study. Intra-abdominal desmoid tumors are associated with FAP [30]. This association is suggestive of a different tumor biology compared to sporadic disease. In addition, intra-abdominal disease is related to a high mortality among FAP-patients and as such treated differently. To limit the risks associated with the present study, these patients are excluded from participation. The occurrence of progression does not necessitate a switch to active treatment. In case the safety of the patient is compromised, for example due to organ involvement or increased pressure, a switch to active treatment will be recommended. In order to minimize the risk of compromised abilities due to tumor growth, the follow-up schedule allows for timely detection of tumor progression and patients with vital structures at risk will not be included in the study. The exclusion criteria prevent life threaten of functional impairment in case of tumor growth. Severe pain is considered to require continuous pain medication. Active treatment does not guarantee pain relief. As such, a watchful waiting policy should be considered and discussed in patients experiencing degrees of pain. During the study period, we will monitor the considerations in switching treatment strategies. An interim analysis will be performed after 1 year follow-up from the first 20 patients. This analysis is designed to validate the safety of the study. If too many patients deviate from the watchful waiting policy, this policy should be questioned. Due to the benign nature of this disease, we consider it safe if over 50 % of the patients is still undergoing watchful waiting after 1 year of follow-up. This study will provide insight in tumor behavior and clinicopathological factors predictive of tumor progression. The ability to predict tumor behavior would enable tailoring individual patient treatment. Abbreviations FAPFamilial adenomatous polyposis METCMedical research ethics committee in Dutch: Medisch Ethische Toetsing Commissie (METC) MRIMagnetic resonance imaging QoLQuality of life RECISTResponse evaluation criteria in solid tumors Acknowledgements We thank prof. dr. Hans de Wilt, dr. Robert J. van Ginkel and dr. Henk Hartgrink for their contribution to the study protocol as part of the writing committee and involvement in initiating the study at the Radboud University Medical Center, University Medical Center Groningen and Leiden University Medical Center respectively. Funding No funding was available for the study. Availability of data and materials Information on the study can be found on www.grafiti-trial.nl (Dutch website). The datasets obtained during the study are available from the corresponding author on reasonable request. Authors’ contributions A writing committee was formed for this study, to ensure a nationwide acceptance of the protocol and to facilitate implementation of the results. Specialists were asked to participate based on their role of expert in the Dutch sarcoma centers. They have given approval of the final study protocol before evaluation by the ethics committee. Three specialists will not act as principal investigator at their center and are mentioned under “Acknowledgements”. CV is the project leader. DG, TvD and FvC were part of the writing committee and are principal investigators. HB, LB, SD and MD are principal investigators. CC and AG have contributed to the study outline and are the principal investigator and project leader for the twin study in Milan. DvB is responsible for data collection and analysis. All authors have been involved in facilitating participation of the sarcoma centers. All read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Ethical approval and consent to participate The study has ethical approval from the Erasmus MC medical-ethical committee. Analysis of the manuscript was performed and approval for participation in the study was given by each center, based on either ethical approval or other guidelines in the specific centes. The study will be conducted in accordance with the ethical principles of the Declaration of Helsinki. The local investigator is responsible for the proper conduct of the study at the study site. Informed consent will be obtained for each participant at inclusion. ==== Refs References 1. Fletcher CDMBJA Hogendoorn P Mertens F WHO Classification of Tumours of Soft Tissue and Bone 2013 Fourth 468 2. Benson LS Williams CS Kahle M Dupuytren’s contracture J Am Acad Orthop Surg 1998 6 1 24 35 10.5435/00124635-199801000-00003 9692938 3. Reitamo JJ Hayry P Nykyri E Saxen E The desmoid tumor. I. Incidence, sex-, age-and anatomical distribution in the Finnish population Am J Clin Pathol 1982 77 6 665 673 10.1093/ajcp/77.6.665 7091046 4. Nieuwenhuis MH Lefevre JH Bulow S Jarvinen H Bertario L Kerneis S Family history, surgery, and APC mutation are risk factors for desmoid tumors in familial adenomatous polyposis: an international cohort study Dis Colon Rectum 2011 54 10 1229 1234 10.1097/DCR.0b013e318227e4e8 21904137 5. Mitchell G Thomas JM Harmer CL Aggressive fibromatosis: evidence for a stable phase Sarcoma 1998 2 3–4 149 154 10.1080/13577149877902 18521247 6. Baumert BG Spahr MO Von Hochstetter A Beauvois S Landmann C Fridrich K The impact of radiotherapy in the treatment of desmoid tumours. An international survey of 110 patients. A study of the Rare Cancer Network Radiat Oncol 2007 2 12 10.1186/1748-717X-2-12 17343751 7. Tejpar S Nollet F Li C Predominance of beta-catenin mutations and beta-catenin dysregulation in sporadic aggressive fibromatosis (desmoid tumor) Oncogene 1999 18 6615 6620 10.1038/sj.onc.1203041 10597266 8. Alman BA Li C Pajerski ME Diaz-Cano S Wolfe HJ Increased beta-catenin protein and somatic APC mutations in sporadic aggressive fibromatoses (desmoid tumors) Am J Pathol 1997 151 2 329 334 9250146 9. Amary MF Pauwels P Meulemans E Roemen GM Islam L Idowu B Detection of beta-catenin mutations in paraffin-embedded sporadic desmoid-type fibromatosis by mutation-specific restriction enzyme digestion (MSRED): an ancillary diagnostic tool Am J Surg Pathol 2007 31 9 1299 1309 10.1097/PAS.0b013e31802f581a 17721184 10. Miyoshi Y Iwao K Nawa G Yoshikawa H Ochi T Nakamura Y Frequent mutations in the beta-catenin gene in desmoid tumors from patients without familial adenomatous polyposis Oncol Res 1998 10 11–12 591 594 10367940 11. Domont J Salas S Lacroix L Brouste V Saulnier P Terrier P High frequency of beta-catenin heterozygous mutations in extra-abdominal fibromatosis: a potential molecular tool for disease management Br J Cancer 2010 102 6 1032 1036 10.1038/sj.bjc.6605557 20197769 12. Lazar AJ Tuvin D Hajibashi S Habeeb S Bolshakov S Mayordomo-Aranda E Specific mutations in the beta-catenin gene (CTNNB1) correlate with local recurrence in sporadic desmoid tumors Am J Pathol 2008 173 5 1518 1527 10.2353/ajpath.2008.080475 18832571 13. Colombo C Miceli R Lazar AJ Perrone F Pollock RE Le Cesne A CTNNB1 45F mutation is a molecular prognosticator of increased postoperative primary desmoid tumor recurrence: An independent, multicenter validation study Cancer 2013 119 3696 3702 10.1002/cncr.28271 23913621 14. Van Broekhoven DL Verhoef C Grunhagen DJ Van Gorp JM Den Bakker MA Hinrichs JW Prognostic Value of CTNNB1 Gene Mutation in Primary Sporadic Aggressive Fibromatosis Ann Surg Oncol 2015 22 5 1464 1470 10.1245/s10434-014-4156-x 25341748 15. Mullen JT DeLaney TF Rosenberg AE B-catenin mutation status and outcomes in sporadic desmoid tumors Oncologist 2013 18 9 1043 1049 10.1634/theoncologist.2012-0449 23960186 16. Hayry P Reitamo JJ Totterman S Hopfner-Hallikainen D Sivula A The desmoid tumor. II. Analysis of factors possibly contributing to the etiology and growth behavior Am J Clin Pathol 1982 77 6 674 680 10.1093/ajcp/77.6.674 7091047 17. Huang K Fu H Shi YQ Zhou Y Du CY Prognostic factors for extra-abdominal and abdominal wall desmoids: a 20-year experience at a single institution J Surg Oncol 2009 100 7 563 569 10.1002/jso.21384 19722232 18. Salas S Dufresne A Bui B Blay JY Terrier P Ranchere-Vince D Prognostic factors influencing progression-free survival determined from a series of sporadic desmoid tumors: a wait-and-see policy according to tumor presentation J Clin Oncol Off J Am Soc Clin Oncol 2011 29 26 3553 3558 10.1200/JCO.2010.33.5489 19. Keus RB Nout RA Blay JY De Jong JM Hennig I Saran F Results of a phase II pilot study of moderate dose radiotherapy for inoperable desmoid-type fibromatosis--an EORTC STBSG and ROG study (EORTC 62991–22998) Ann Oncol 2013 24 2672 2676 10.1093/annonc/mdt254 23868907 20. Bonvalot S Eldweny H Haddad V Rimareix F Missenard G Oberlin O Extra-abdominal primary fibromatosis: Aggressive management could be avoided in a subgroup of patients Eur J Surg Oncol 2008 34 4 462 468 10.1016/j.ejso.2007.06.006 17709227 21. Bonvalot S Desai A Coppola S Le Pechoux C Terrier P Domont J The treatment of desmoid tumors: a stepwise clinical approach Ann Oncol 2012 23 10 158 166 10.1093/annonc/mds298 22. Fiore M Rimareix F Mariani L Domont J Collini P Le Pechoux C Desmoid-type fibromatosis: a front-line conservative approach to select patients for surgical treatment Ann Surg Oncol 2009 16 9 2587 2593 10.1245/s10434-009-0586-2 19568815 23. Assad WA Nori D Hilaris BS Shiu MH Hajdu SI Role of brachytherapy in the management of desmoid tumors Int J Radiat Oncol Biol Phys 1986 12 6 901 906 10.1016/0360-3016(86)90383-4 2424881 24. Colombo C Miceli R Le Pechoux C Palassini E Honore C Stacchiotti S Sporadic extra abdominal wall desmoid-type fibromatosis: surgical resection can be safely limited to a minority of patients Eur J Cancer 2015 51 2 186 192 10.1016/j.ejca.2014.11.019 25500145 25. Kasper B Baumgarten C Bonvalot S Haas R Haller F Hohenberger P Management of sporadic desmoid-type fibromatosis: a European consensus approach based on patients’ and professionals’ expertise - a sarcoma patients EuroNet and European Organisation for Research and Treatment of Cancer/Soft Tissue and Bone Sarcoma Group initiative Eur J Cancer 2015 51 2 127 136 10.1016/j.ejca.2014.11.005 25434922 26. Eisenhauer EA Therasse P Bogaerts J Schwartz LH Sargent D Ford R New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1) Eur J Cancer 2009 45 2 228 247 10.1016/j.ejca.2008.10.026 19097774 27. Crago AM Denton B Salas S Dufresne A Mezhir JJ Hameed M A prognostic nomogram for prediction of recurrence in desmoid fibromatosis Ann Surg 2013 258 2 347 353 10.1097/SLA.0b013e31828c8a30 23532110 28. Reitamo JJ Scheinin TM Hayry P The desmoid syndrome. New aspects in the cause, pathogenesis and treatment of the desmoid tumor Am J Surg 1986 151 2 230 237 10.1016/0002-9610(86)90076-0 3946757 29. Van Broekhoven DL, Grunhagen DJ, Den Bakker MA, Van Dalen T, Verhoef C. Time Trends in the Incidence and Treatment of Extra-Abdominal and Abdominal Aggressive Fibromatosis: A Population-Based Study. Ann Surg Oncol. 2015. 30. Nieuwenhuis MH Casparie M Mathus-Vliegen LM Dekkers OM Hogendoorn PC Vasen HF A nation-wide study comparing sporadic and familial adenomatous polyposis-related desmoid-type fibromatoses Int J Cancer 2011 129 1 256 261 10.1002/ijc.25664 20830713

PMC005xxxxxx/PMC5000484.txt

==== Front BMC Health Serv ResBMC Health Serv ResBMC Health Services Research1472-6963BioMed Central London 169110.1186/s12913-016-1691-0Research ArticleSocial media use in healthcare: A systematic review of effects on patients and on their relationship with healthcare professionals Smailhodzic Edin e.smailhodzic@rug.nl 1Hooijsma Wyanda w.a.hooijsma@alumnus.rug.nl 1Boonstra Albert albert.boonstra@rug.nl 1Langley David J. d.j.langley@rug.nl 121 Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands 2 TNO, Netherlands Organization for Applied Scientific Research, Groningen, The Netherlands 26 8 2016 26 8 2016 2016 16 1 44217 11 2015 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Since the emergence of social media in 2004, a growing percentage of patients use this technology for health related reasons. To reflect on the alleged beneficial and potentially harmful effects of social media use by patients, the aim of this paper is to provide an overview of the extant literature on the effects of social media use for health related reasons on patients and their relationship with healthcare professionals. Methods We conducted a systematic literature review on empirical research regarding the effects of social media use by patients for health related reasons. The papers we included met the following selection criteria: (1) published in a peer-reviewed journal, (2) written in English, (3) full text available to the researcher, (4) contain primary empirical data, (5) the users of social media are patients, (6) the effects of patients using social media are clearly stated, (7) satisfy established quality criteria. Results Initially, a total of 1,743 articles were identified from which 22 were included in the study. From these articles six categories of patients’ use of social media were identified, namely: emotional, information, esteem, network support, social comparison and emotional expression. The types of use were found to lead to seven identified types of effects on patients, namely improved self-management and control, enhanced psychological well-being, and enhanced subjective well-being, diminished subjective well-being, addiction to social media, loss of privacy, and being targeted for promotion. Social media use by patients was found to affect the healthcare professional and patient relationship, by leading to more equal communication between the patient and healthcare professional, increased switching of doctors, harmonious relationships, and suboptimal interaction between the patient and healthcare professional. Conclusions Our review provides insights into the emerging utilization of social media in healthcare. In particular, it identifies types of use by patients as well as the effects of such use, which may differ between patients and doctors. Accordingly, our results framework and propositions can serve to guide future research, and they also have practical implications for healthcare providers and policy makers. Electronic supplementary material The online version of this article (doi:10.1186/s12913-016-1691-0) contains supplementary material, which is available to authorized users. Keywords Social mediaHealthPatientsHealthcare professionalsissue-copyright-statement© The Author(s) 2016 ==== Body Background Previous studies on social media use in healthcare identified different effects of social media use by patients for health related reasons within the healthcare system. Social media can serve as an aid to patients. For example, it fosters their autonomy by complementing the information provided by healthcare professionals [1] and by providing psychosocial support [2]. Social media use by patients can also be an aid to healthcare professionals by providing a tool to strengthen the organization’s market position [3, 4] and stimulating conversation for brand building and improved service delivery [4, 5]. In fact, social media may have effects on both patients, and on the wider healthcare system [6]. In particular, it allows patients to receive support [1], and to complement offline information [2], which may lead to enhancing the empowerment of patients [6]. However, social media use by patients does not only provide beneficial effects. It may also constitute a challenge within the healthcare system to both patients and healthcare professionals. Since everybody with access to social media can post “advice” on how to deal with a certain health condition, it is important to create reliable online communication channels to prevent health problems being exacerbated [7]. For example, one misguided idea on Twitter urged Nigerians to drink excessive amounts of salt water to combat Ebola. However, this may have led to two deaths and more than 12 admissions to hospital [7]. Thus, many healthcare professionals fear that social media use by patients for health related purposes often spreads misinformation among patients [1]. Use of social media by patients for health related reasons provides different effects, which can result in both benefits and challenges. It is important to identify these effects of social media for the healthcare system, as “a growing percentage of patients use social media for health-related reasons, so health professionals will have to reflect on the alleged beneficial effects and the potential harmful effects of social media use by patients in healthcare” [8]. Hence, the review of these effects will contribute to a better understanding of potential benefits and challenges for both patients and healthcare professionals, but also other healthcare actors such as policy makers. Therefore, this paper provides a systematic literature review of empirical studies on the effects of social media use by patients for health related reasons on patients and on their relationships with healthcare professionals. To our knowledge no other systematic research on this topic has been performed to date. Such review also provides the opportunity to extract general findings from the studies. Subsequently, healthcare professionals can learn from these findings about the effects of social media use by patients and share this knowledge with other patients and use it to their own advantage. We aim to answer the following question:According to recent empirical research, what are the effects of social media use by patients for health related reasons on patients and on their relationships with healthcare professionals? To answer this question, the paper will address the following: (1) the types of social media use by patients (2) the identified effects of social media use by patient on patients (3) the identified effects on the relationship between patients and their healthcare professionals and (4) the relationship between the effects on patients and healthcare professionals. By addressing the issue (4), we attempt to bring together our findings from the issues (2) and (3) and explore linking mechanisms between the effects patients experience and their subsequent link to the effects they experience in relationship with the healthcare professionals. Study aim and terminology The aim of this paper is to gain insights in the benefits and challenges of the effects of social media use by patients within the healthcare system and especially the effects on patients and on their relationships with healthcare professionals. The effects we focus on in this paper can be both causal and reciprocal, but always start with the use of social media by patients. Despite the popularity of social media, there is a confusion about what is exactly meant by the term social media. Therefore, in this paper we use the definition provided in the highly cited paper by Kaplan and Haenlein [9]. They describe social media as “a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content”. The internet-based applications refer to the different categories of social media, which are blogs, content communities, social networking sites, collaborative projects, virtual game worlds and virtual social worlds. These types of social media are accessible to users to utilize for, among other things, health related reasons. The term “users of social media in healthcare” in this paper refer to the patients and their family members. Patients are treated as any person who self-proclaims to be suffering from a certain condition, whether officially diagnosed by a healthcare professional or not. We define healthcare professionals as those who study, advise on or provide preventive, curative, rehabilitative and promotional health services based on an extensive body of theoretical and factual knowledge in diagnosis and treatment of conditions and other health problems [10]. Methods In order to provide an overview of the different effects of social media use by patients for health related reasons on patients and on their relationships with healthcare professionals, we conducted systematic literature review. To identify the articles, we employed a search strategy consisting of three terms as follows a) “social media” or blog* or “content communit*” or “social networking site*” or “online social network*” or “virtual world*” or “online communit*” or “online forum*” or Facebook or Twitter or Wikipedia or IMVU or “second life” or YouTube b) “Patient*” and c) “health* provider*” or “health* professional*” or “physician*” or “doctor*” or “hospital*”. The full search string is also included in the Appendix A (see Additional file 1). Additionally, as suggested by the referees of this paper, we also used the term “client*” instead of “patient*”, together with the other two original categories of terms. To perform this literature review, we followed the guidelines on conducting a systematic literature review as prescribed by the Preferred Reporting Items for Systematic Literature Reviews and Meta-Analyses (PRISMA) [11]. To conduct the search, we chose relevant databases of Web of Science and EBSCOhost COMPLETE. By focusing on EBSCOhostCOMPLETE, we made sure that the healthcare databases are included such as “PsycINFO”, “CINAHL” and “MEDLINE”. We also included the databases such “Business source premier” to include findings with a business perspective. Search options were slightly different for each database. For EBSCO the irrelevant databases were excluded first and no specific search field was selected for one of the three terms. The list of databases is presented in the Appendix B (See Additional file 2). Additionally, the option to search only in scholarly (peer reviewed) journals was used and the publication dates were selected to be after 2004. In the year 2004 the term Web 2.0 was used for the first time, which marks the start of the social media era [9]. On the other hand, we selected topic for all three terms in the Web of Science, which included the titles, abstracts, author keywords, and keywords plus fields of the articles. Selection criteria For an article to be included in the study it had to meet several selection criteria as follows: (1) published in a peer-reviewed journal, (2) written in English, (3) full text available to the researcher, (4) contain primary empirical data, (5) the users of social media are patients, (6) the effects of patients using social media are clearly stated, (7) satisfy established quality criteria. The articles were assessed on their quality by using the standard quality assessment criteria as identified by [12]. Prior to final screening and selection of the papers, first and second author agreed to independently read 100 abstracts and select the articles that would be included in the study based on the selection criteria. Afterwards, the selected articles by the two authors were compared and there was complete concurrence on the category “yes, this one will be included”. For some of the articles that were marked as “maybe”, first and second author had a brief discussion to reach a consensus. This helped to reach higher reliability for the inclusion of the articles. Further in the process, the second author consulted the first author whenever there was a doubt whether to include or exclude the article. In addition, regular meetings with the third author also contributed to the overall process of the selection. Data analysis The resulting papers were characterized by the research aim and the type of research, which is reflected in the Table 1. The papers were further categorized according to the focus of the research question and data. Each paper’s empirical findings were categorized by looking at data and making first notes inductively. Following this, we looked at our notes on topics that emerged from analysed articles and compared them to earlier literature. In this way, concepts from prior literature helped us to make the sense of data from different articles and categorize them. A good example for that is the concept of social support, which we used to classify types of use. After analysing the articles in this way, we formulated propositions in the discussion section.Table 1 Overview of included studies in the literature review Year Author(s) - Article no. Journal Main objective of study Type of research Data collection Participants (sample) 2005 [13] Journal of Sociology To explore the experiences of, and attitudes towards, online support groups Qualitative Interviews 33 Australian men with prostate cancer and 18 specialists 2008 [22] Journal of Medical Internet Research To explore whether lurkers in online patient support groups profit to the same extent as posters do Quantitative Online survey 528 members of Dutch online support groups for patients with breast cancer, fibromyalgia, and arthritis 2008 [28] Journal of Medical Internet Research To identify and analyse how users of the platform PatientsLikeMe reference personal health information within patient-to-patient dialogues Qualitative Analysis of comments 123 comments posted within the ALS community 2010 [15] New Review of Hypermedia & Multimedia To understand why and how people use health-related sites Quantitative Online survey 33 Patients with a medical condition (patients) 2010 [27] Pedriatic Transplantation To investigate the feasibility and safety of an online virtual community as a potential psychosocial intervention for post-transplant adolescents Qualitative and Quantitative Data analysis of the Zora system logs and interviews 22 patients with solid organ transplants aged between 11-15 years 2010 [35] Journal of Psychosomatic Obstetrics & Gynecology To focus on investigating the perceived disadvantages of online infertility support communities from the perspective of those who access and participate in them Qualitative and Quantitative Online survey 295 participants coping with fertility problems 2010 [36]. Journal of Medical Internet Research To describe the potential benefits of PatientsLikeMe in terms of treatment decisions, symptom management, clinical management, and outcomes Quantitative Online survey 1323 members from six PatientsLikeMe communities (ALS, MS, Parkinson’s Disease, HIV, fibromyalgia, and mood disorders) 2011 [23] Patient Education and Counseling To investigate the potential of online support groups to foster empowerment and how membership might affect the patient/health professional relationship Quantitative Online survey 246 individuals from 33 chronic conditions online support groups 2011 [26] Journal of Medical Internet Research To explore the differences in peer support received by lurkers and posters in online breast cancer communities Quantitative Online survey 253 members of four Japanese online breast cancer communities 2012 [16] Journal of Medical Internet research To explore the motivations and challenges faced by patients who share videos about their health and experiences on YouTube Qualitative Analysis of videos Videos uploaded by 4 patients with a chronic condition 2012 [30] Health Communication To examine the indirect effect of Computer Mediated Social Support on doctor–patient communication through utilizing the sense of empowerment Quantitative Online survey 464 Korean patients with diabetes 2012 [38] Information Research To examine the use of an online health forum by married Korean women living in the USA who sought help for health and medical issues Qualitative Content analysis of posts 1000 messages posted to a health forum MissyUSA 2013 [14] International Journal of Medical Informatics To investigate whether communication in online patient support groups is a source of individual as well as collective empowerment or to be understood within the tradition of compliance Qualitative Analysis of posts 4301 posts from two online communities, one for patients with COPD and one for women with pregnancy problems 2013 [24] Journal of Health Psychology To explore how cancer patients’ writing and reading on the Internet play a role in their conditions experience Qualitative Focus-group interviews 34 Cancer patients 2013 [25] JRSM short reports To explore how participation in an online support community may impact upon the experience of inflammatory bowel disease Qualitative and Quantitative Online survey 249 patients living with either Crohn’s Disease (65.9 %) or Ulcerative Colitis (26.1 %) or awaiting formal diagnosis (8 %) 2013 [34] Nordic Journal of Psychiatry To evaluate if and how online self-help forums are used by patients with bipolar disorders, their relatives and treating professionals Qualitative and Quantitative Content analysis of posts 2400 postings of 218 users (Patients with Bipolar Disorder (94 %), Relatives (4 %), or Professionals (2 %)) 2014 [1] Patient Education & Counseling To explore how individuals use online health community content in clinical discussions and how healthcare providers react to it Qualitative Focus groups 89 members of an online health community 2014 [17] Obstetrics & Gynecology To determine whether social media, specifically Facebook, is an effective tool for improving contraceptive knowledge Quantitative Survey 143 Patients who had scheduled a routine visit to a gynaecologist 2014 [21] Indian Journal of Psychological Medicine To explore the potentials of social networking sites as an adjunctive treatment modality for initiating treatment contact as well as for managing psychological problems Qualitative and Quantitative Interviews and an online survey 28 patients with any of the depressive or anxiety spectrum disorder 2014 [37] Reproductive Health To use the online platform of blogs to explore whether the framing effect of information content, situated learning of information content, and health knowledge involvement would affect health communication between doctors and patients and further explore whether this would increase patient willingness to seek treatment Quantitative Online survey 278 participants who were seeking medical treatment in a clinic or hospital in Taiwan 2014 [39] Journal of the American Medical Informatics Association To describe adults who use Twitter during a weight loss attempt and to compare the positive and negative social influences they experience from their offline friends, online friends, and family members Qualitative and Quantitative Survey 100 participants trying to lose weight 2016 [40] Counselling Psychology Quarterly To test for differences between offline and online psychological disclosure in case of young adults Quantitative Survey 128 young adults attending individual psychotherapy. Results Search results The searches were carried out in the period ending on March 17th, 2015. The application of the search strategy to the two search engines resulted initially in a total of 1,743 articles. Within the 1,743 articles many duplicates were found as well within the search engines as between the search engines. By removing duplicates the first found article was kept. In this way, we identified and removed 468 duplicates leaving us with 1,275 articles. The remaining 1,275 articles were screened on title and abstract with regards to the selection criteria. Whenever we had doubts if an article is relevant or when title and abstract were not clear, we inspected the paper in more details by accessing full article. An article was removed when, for example, it became clear that the user of social media was not a patient but another user, like the hospital, a regular “healthy” person or healthcare professional. Additionally, several articles referred to internet use by patients for health related reasons and their effects, but did not specify the effects of social media. Therefore, such articles were removed. Moreover, articles that were written in a language other than English as well as articles that did not comprise primary data or did not elaborate on an effect of patients using social media. This left us with 22 articles that met our criteria. In addition, as a result of the referees’ suggestion to include term “client”, we identified one additional article, making the entire list of 23 articles for the quality assessment. Quality of the articles was assessed by using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers by [12] as presented in the Appendix C (See Additional file 3). This assessment tool distinguishes between qualitative and quantitative research and provides different quality assessment criteria for each type of research. The criteria are rated on their presence in the respective article and are either completely addressed in the article (resulting in 2 points), partly addressed (resulting in 1 point), or not addressed (resulting in 0 points). In case an article scored below the threshold of a 50 % score of the total amount of points possible, the article is assumed to be of low quality and removed from this paper. This cut-off point for inclusion is relatively liberal according to the authors of the assessment tool [12]. One article had a quality score below the 50 % cut-point and was excluded, which left us with the total of 22 articles for analysis. The article selection process is shown in Fig. 1.Fig. 1 Flowchart of study selection process Overview of the articles The Table 1 provides an overview of 22 articles included in the study. All studies except for three were published in or after 2010. Moreover, 19 articles were published in journals that are related to the medical field, whereas only three articles are published in journal that do not have a specific connection to medicine: Journal of Sociology, New Review of Hypermedia & Multimedia, and Information Research. Only two out of the 22 articles use a theory or a model to build their research on, namely the concept of masculinity [13] and the actant model [14]. The group of articles consists of nine quantitative, seven qualitative and six mixed methods studies. The analysis of articles with regard to the type of social media and conditions is presented in the Appendix D (See Additional file 4), which shows that the 12 articles studied online support communities and most focused on chronic conditions. Other types of social media platforms and conditions were spread among the remaining articles. Analysis of results This section presents findings from 22 articles we included in our study. First of all, an overview of the extracted findings is presented regarding the types of social media use by patients. Following this, we present the effects of social media use on patients. Subsequently, an overview of the extracted findings regarding effects of social media use by patients on the relationship between patients and healthcare professionals are presented, discussed, and categorized. Types of social media use by patients for health related reasons Our analysis starts with the type of use and motivation for their use of social media. When analysing all articles it becomes clear that patients do not use social media to circumvent healthcare professionals, but rather use it as a complement to healthcare professional services to fulfil the patients’ needs that cannot be met by the healthcare professional. The relationship between patients and healthcare professionals is viewed by the patients as a more clinical one, where healthcare professionals provide expert knowledge about the condition and recommend treatment based on their medical knowledge, but not on their first-hand experience [15]. Additionally, doctors often have difficulty expressing empathy and that they filter information for the patient, where the patient would rather be informed about all options. Patients also believe that doctors might not be aware of the latest breakthroughs [15]. Moreover, one of the the main reasons for patients to join online health communities is their dissatisfaction with their healthcare professional’s inability to meet the patients’ emotional and informational needs [1]. Another reason for patients to use social media was to bridge the gap between traditional health information about their condition and everyday life [16]. In particular, Facebook is seen as an important addition to traditional in-office counselling in improving patient knowledge [17]. Therefore, the types of social media use by patients as identified in this paper refer to the way in which patients use social media intended to meet an unfulfilled need. These are identified in the articles are categorized as shown in Table 2 and explained below. Categories represent social support, consisting of emotional, esteem, informational, and network support [18], and other types of use, which are emotional expression and social comparison.Table 2 Types of use of social media by patients for health related purposes by article Type of use Article no. Social support Emotional support [1, 13, 16, 21–23, 25, 26, 30, 34–36, 40] Esteem support [14, 16, 23–25, 30, 39] Information support All articles Network support [1, 14–16, 21, 24–28, 34, 36, 39] Other types of use Emotional expression [13–15, 21, 24–26, 38] Social comparison [23, 25, 35, 39] Social support The most common type of social media use by patients for health related reasons that we found is social support. Social support is defined as “the process of interaction in relationships which is intended to improve coping, esteem, belonging, and competence through actual or perceived exchanges of psychosocial resources” [19]. Social support is represented through five different categories and four of these categories were found to be common types of social media use by patients for health related purposes [18]. These four types, namely emotional support, esteem support, information support, and network support are explained below. Emotional support. Emotional support is defined as “communication that meets an individual’s emotional or affective needs” [20]. It refers to support gained through expressions of care and concern, which serve to improve an individual’s mood. Emotional support helps patients to meet their emotional or affective needs. The use of social media by patients for emotional support was identified in 13 articles. Examples of emotional support are “sharing of emotional difficulties” [21], “encountering support that feels like a warm blanket wrapped around you” [22], and “share emotions with other people who are coping with similar problems” [23]. Esteem support. Esteem support refers to “communication that bolsters an individual’s self-esteem or beliefs in their ability to handle a problem or perform a needed task” [20]. The aim of this type of support is to encourage individuals to take the actions needed to successfully live with their condition. The use of social media by patients for esteem support was identified in seven articles. Examples of esteem support include “getting support from other patient’s encouragement” [24], “share experiences about a new treatment to find encouragement before starting it” [25], and “rituals of confirming each other’s endeavours to follow health instructions” [14]. Information support. Information support is “communication that provides useful or needed information” [20]. In particular, newly diagnosed patients are in a need for a lot of information about their condition and treatment options, which can be provided by patients who have already dealt with the condition for a longer period [20]. The use of social media by patients for information support was identified in all articles. Examples of information support are “receiving advice about treatments” [26], “help fellow sufferers by sharing experiences and relevant information about the disease” [24], and “ask questions about the condition” [25]. Network support. Network support is defined as “communication that affirms an individual’s belonging to a network or reminds him/her of support available from the network” [20]. Hence, network support is support that reminds people that no matter what situation they are facing, they are not alone. The use of social media by patients for network support was identified in 13 articles. Examples of network support include “meeting other patients who had gone through similar experiences” [27], “a means to connect with others in similar situations” [15], and “fostering relationships based on shared attributes” [28]. Other types of use In addition to the social support, we also identified two other types of use, which could not be directly placed under one of the subcategories of social support. These are emotional expression and social comparison. Emotional expression. Emotional expression refers to the unique opportunity provided by social media for patients (and other users) to express their emotions freely without having to be concerned about the immediate feelings or reactions of those who stand close to them. As noted in one of the articles, “online communities provide the potential to allow patients to open up and reduce the inhibitions felt in sharing experiences in face to face situations”, e.g. hurting other people’s feelings [13]. Therefore, patients can use social media as a place to express their emotions freely, like, releasing negative emotions [24]. In contrast to emotional support, which is defined as patients interacting in and receiving communication to meet their affective needs, emotional expression refers to patients expressing their emotions regardless of whether someone will respond. The use of social media by patients for emotional expression was identified in 8 articles. Examples include “a place to vent about the illness” [25] and “an outlet for expressing your emotions freely” [15]. Social comparison. Patients use social media to compare themselves with other patients to see how “bad” their condition is or to find out how the treatments work. This social comparison can seem to overlap with social support, for instance, when patients compare themselves to peers to recognize that they are not the only person in this situation (network support) or when patients compare themselves to peers to find out how other people suffer from or cope with the condition (esteem support, emotional support, or information support). However, social comparison was categorized separately as within the articles the authors presented it as a different type of use without specifying the details. The use of social media by patients for social comparison was identified in four articles. Examples include “upward social comparison” [25] and “comparison with other members [23]. Effects of the different types of social media use by patients on patients In this section the effects of the use of social media by patients for health related reasons are analysed and presented. The most common effect of patients using social media for health related reasons is patient empowerment, which is represented through three categories: enhanced subjective well-being, enhanced psychological well-being, and improved self-management and control. We also identified four other types of effects, which are less common in our literature review. These are: diminished subjective well-being, loss of privacy, addiction to social media, and being targeted for promotion. Identified categories are presented in Table 3 and explained below.Table 3 Effects of social media use by patients for health related reasons by article Effect Article no. Patient empowerment Enhanced subjective well-being [13, 15, 21–27, 30, 36, 39] Enhanced psychological well-being [13–16, 21–25, 27, 28, 34, 39, 40] Improved self-management and control [14–17, 22–26, 28, 30, 34, 36–38] Other types of effects Diminished subjective well-being [13, 16, 25, 26, 35, 36] Loss of privacy [16] Being targeted for promotion [16] Addiction to social media [35] Patient empowerment In current literature, the concept of empowerment is defined as “an individual trait, characterized by an emphasis on increased individual control over the aspects of one’s life” [29]. We argue that the patient empowerment refers to “the discovery and development of one’s inherent capacity to be responsible for one’s own life. Hence, patients are empowered when they are in possession of the knowledge, skills, and self-awareness necessary to identify and attain their own goals” [14]. Information support, esteem support, and emotional support were significant predictors of a patient’s sense of empowerment [30]. Informational support was the strongest predictor of increased sense of empowerment followed by esteem support and emotional support. The three subcategories of empowerment, namely enhanced subjective well-being, enhanced psychological well-being, and improved self-management and control, are discussed below. Enhanced subjective well-being. Subjective well-being refers to “what people think and how they feel about their lives in positive ways” [31]. In this paper, enhanced subjective well-being mainly refers to the pleasant emotions patients experience due to their social media use for health related reasons. “People experience enhanced subjective well-being when they feel many pleasant and few unpleasant emotions” [31]. Consequently, enhanced subjective well-being refers to an increase in the experience of pleasant emotions, which in turn heightens people’s feeling of empowerment. The effect enhanced subjective well-being was identified in 12 articles. Examples from the articles concerning enhanced subjective well-being are “increased optimism” [22], “increased acceptance of the illness” [23], “decrease anxiety” [26] and “increased sense of normalcy” [27]. Enhanced psychological well-being. Psychological well-being is defined in the literature as “focusing on eudemonic well-being, which is the fulfilment of human potential and a meaningful life” [32]. One of the components affecting psychological well-being is the experience of positive relations with others. It is argued that a central component of mental health is to be in warm, trusting, interpersonal relations [33]. Moreover, “self-actualizers are described as having strong feelings of empathy and affection for all human beings and as being capable of greater love, deeper friendship, and more complete identification with others” [33]. Therefore, enhanced psychological well-being refers to an increase in the patient’s experience of positive relations with others through the use social media. The effect enhanced psychological well-being was identified in 14 articles. Examples from the articles include “feeling of being connected to other people” [34], “increased social network online as well as offline” [27], and “promotion of deep relationships” [15]. Improved self-management and control. Improved self-management and sense of control refers to the improvement in the capability of patients to better handle their condition. As patients feel better informed, their ability to make decisions on their own improves, which fosters self-management and perceived control over the condition. Ability to deal with the day-to-day life with the condition also increases, for example due to learning about coping strategies, which also fosters improved self-management and perceived control. The effect of improved self-management and sense of control was identified in 14 articles. Examples from the articles include “increase patient’s self-management” [34], “improvement in the ability to manage the disease” [16], and “fostering insight and universality” [26]. Other types of effects In addition to the patient empowerment, several other types of effects of social media use by patients on patients were identified. These are diminished subjective well-being, loss of privacy, being targeted for promotion, and addiction to social media. Diminished subjective well-being. Diminished subjective well-being is opposite of enhanced subjective well-being and indicates an increase in the experience of negative emotions due to the use of social media, such as an increase in feelings of worry and anxiety. It was identified in six articles. Diminished subjective well-being was the most common found effect of patients using social media for health related reasons. Examples include “demoralization” [25], “hurt feelings due to negative feedback” [16], and “increased feelings of anxiety” [35]. Loss of privacy. Loss of privacy was mentioned in only one article [16]. It refers to the finding that the patients lose their privacy when they post personal videos on YouTube. Being targeted for promotion. Being targeted for promotion was also mentioned in only one article by [16]. It refers to the finding that patients who post videos on YouTube can be targets product promotions. Addiction to social media. Addiction was an effect identified in one article by [35]. It refers to the finding that sometimes patients experience their social media use for health related reasons to be addictive. As such, it often took the time that they usually spent doing other tasks. Effects of social media use by patients on the relationship between patients and healthcare professionals The use of social media by patients for health related reasons does not only affect the patients themselves or other patients, but also the relationship between patients and healthcare professionals. In total, nine articles discussed the effects of social media use by patients on the relationship between patients and healthcare professionals, although six out of these nine articles only touch very briefly upon this subject. The effects of social media use by patients for health related reasons on the relationship between patients and healthcare professionals that have been extracted from the articles are presented in Table 4 and discussed below.Table 4 Effects of social media use by patients on the healthcare professional – patient relationship Effect Article no. Healthcare professional-patient relationship More equal communication [22, 23, 30, 36, 37] Switching of doctors [1, 36] Harmonious relationship [14, 24] Suboptimal interaction [1, 13] The findings presented in Table 4 are divided into categories representing the effects on the relationship between patients and healthcare professionals. These categories are more equal communication between the patient and healthcare professional, increased switching of doctors, harmonious relationships, and suboptimal interaction between the patient and healthcare professional. The categories are discussed below. More equal communication between the patient and healthcare professional Social media use by patients for health related reasons can lead to more equal communication between the patient and healthcare professional. This effect refers to patients feeling more confident in their relationship with the healthcare professional. In total, five articles referred to this effect. With the information from the social media platforms, patients can increase their knowledge about treatment options. Consequently, they are better able to communicate with the healthcare professional as they can better understand their condition [36]. Hence, patients may feel more confident in their relationship with their physician [22, 23]. Patients feel that they are better prepared for consultations as they are more informed about their condition and know better what questions to ask [23]. Social support received through the use of social media eventually increases the likeliness to form an intention to actively communicate with the doctor during a medical consultation [30]. Moreover, the use of social media provides the opportunity to learn and increase health communication, which may lead to an increase in the patients’ willingness to seek medical attention [37]. Hence, these findings suggest that the use of social media for health related purposes can increase a patient’s confidence and active communication in their relationship with healthcare. Increased switching of doctors Social media use by patients for health related reasons can lead to shorter relationships between healthcare professionals and patients. Patients may change doctor due to online discussions about physicians or due to negative reactions from doctors about the patients’ treatments supervised by their regular physicians. Two articles found that patients changed physician because of those patients’ use of social media. For example, negative reactions from physicians to the mentions of social media use by patients made the patients to look for second opinion and even change their doctor [1]. On the other hand, some patients changed their doctor as a result of online discussion with other patients [36]. Harmonious relationships Harmonious relationships between healthcare professionals and patients can be established as social media provide a place for patients to release negative emotions. However, the effect of harmonious relationships also comprises the fact that social media might empower individuals to follow doctor’s recommendations, which reduces discussions during clinical interaction. The effect of harmonious relationships was identified in two articles. Social media provide a place for patients to express their emotions and maintain harmony in the relationship between healthcare professional and patient in offline consultations, which focuses on non-emotional aspects of the disease [24]. On the other hand, social media were empowering individual users to comply with doctors’ recommendations as a group, which affects the healthcare professional patient relationship by potentially reducing discussions during clinical interactions as patients stick to the recommended treatment [14]. However, it can also be viewed as a missed opportunity, as patients do not empower each other to find alternative treatments [14]. Suboptimal interaction between the patient and healthcare professional As patients use social media for health related reasons, this can affect the patient and healthcare professional relationship by leading to suboptimal interaction between the patient and healthcare professional. When patients bring social media content to the consultation, this can lead to increased processes of sorting information, transforming the potential risk to the healthcare professional, and challenging the healthcare professional’s expertise [13]. Additionally, if the healthcare professional reacts negatively to what patient learned from social media, this might decrease the patient’s subjective well-being [1]. The effect of suboptimal interaction between the patient and healthcare professional was identified in two articles. Discussion of the information from social media during the consultation was experienced as a threat by the physician [13]. Furthermore, healthcare professionals reacted negatively to online health community content raised during clinical interactions, which made patients feel disempowered, but it did not change their online behaviour [1]. Relationship between effects on patients and effects on the patient healthcare professional relationship In the section about the effect of “more equal communication between the patient and healthcare professional”, we already mentioned that increased communication during a consultation on behalf of the patient can be caused by patient empowerment. Patient empowerment refers to “the inherent capacity to be responsible for one’s own life” [14]. In regards to the relationship between patients and healthcare professionals, the patients took more responsibility for their own condition. Five articles find that the patient empowerment indeed affects the patients’ confidence, ability and willingness to actively participate in clinical interactions. Patients increased their sense of empowerment through their intention to actively communicate with the doctor [30]. Additionally, the patient empowerment was associated with an increased confidence in dealing with the physician [23]. Moreover, the convenience of social media use by patients is that it reduces the information gap between healthcare professionals and patients and patients have a better understanding of the healthcare professional during consultations [37]. Social media can empower patients by giving them access to information and opportunities for discussions, which increases the patient’s involvement in clinical interactions [15]. Finally, the patient empowerment increases the ability of patients to communicate with the healthcare professionals [22]. Hence, we argue that the patient empowerment contributes to more equal communication between the patient and the healthcare professional. Discussion This review provides an insight into the current body of knowledge on the effects of social media use by patients for health related reasons and the effects on patients and on their relationship with healthcare professionals. All of the studies were published in the past 10 years, with only three articles published before 2010. This can be explained by a recent increase in the use of social media by patients for health related reasons. We categorized articles into different types of use and effects. We identified that the most common type of use was social support, namely emotional support, esteem support, information support, and network support. The types of social media use were most often found to affect patients by empowering them through enhanced subjective well-being, enhanced psychological well-being, and improved self-management and control. However, the types of social media use by patients were also found to affect patients through addiction to social media, diminished subjective well-being, being targeted for promotion, and loss of privacy. Moreover, the identified types of social media use by patients for health related reasons was also found to affect the relationship between patients and healthcare professionals as it can result in more equal communication between the patient and healthcare professional, shorter relationships, harmonious relationships, and suboptimal interaction between the patient and healthcare professional. Based on these findings, we made three propositions. Relationship between use and effect: Network support and enhanced psychological well-being When patients are diagnosed with a certain condition that nobody in their close (offline) network has experienced before, patients can feel very lonely [27]. As a diabetic patient states “I literally felt like the only diabetic on the planet” [16]. However, social media provide an opportunity to easily connect with others and reduce this feeling of loneliness. Consequently, patients using social media for network support enhanced their psychological well-being. For example, social media provide means to connect with others in similar situations and this can break a patient’s loneliness [15]. This is in line with earlier studies that have shown how the existence of network support contributes to a better well-being of the patients [41, 42]. Interestingly, [41] suggest that the network support may not only benefit the patients themselves, but also their families who care for them. Yet, the relationship between the network support and psychological well-being may depend on the level of self-esteem. For example, college students with low self-esteem profited more from online social networking sites for bridging social capital and starting relationships than college students with high self-esteem [43]. In line with that, social networking sites provides the unique opportunity for patients to be able to talk about the sensitive aspects of the condition, as online communities provide the potential to reduce inhibitions felt in sharing experiences face to face [13]. Such an inhibition could reflect low self-esteem in terms of a reluctance to talk about the condition in face to face conversations. Proposition 1: Social media use by patients for network support leads to enhanced psychological well-being. This effect is stronger for people with low self-esteem than for the people with high self-esteem. Relationship between content and effect: Reading other people’s stories, improved self-management and control and enhanced subjective well-being Not all patients that make use of social media use it actively. Sometimes patients only use social media to read about other people’s stories, without actively contributing themselves. These people are called lurkers. The lurking behaviour may be related to the level of privacy concerns and computer anxiety [44]. In particular, anxiety leads to increase in lurking. Two articles in our sample were focused on the effects of patients using social media merely by reading other people’s stories. From the two articles, it becomes clear that the effects experienced by reading other people’s stories are being better informed [22, 26]. Additionally, by reading other people’s stories anxiety was found to significantly decrease [26]. Consequently, these findings suggest that reading other people’s stories on social media can lead to enhanced subjective well-being and improved self-management and control. However, [22] and [26] do not elaborate on the content of the stories read. Contrasting findings were found in other articles regarding how content affects the effects of reading other people’s stories. For example, cancer patients who read other people’s stories enhanced their subjective well-being [24]. Reading about success stories was found to enhance confidence to fight the condition, whereas reading about bad experiences prepared the patient mentally for difficult times ahead. On the other hand, the patients suffering from an inflammatory bowel disease who read other people’s stories about a bad experience suffered from diminished subjective well-being [25]. This is in line with earlier findings showing that the lack of sharing and feedback on this sharing may threaten the need for belonging [45]. Finally, patients suffering from infertility experienced diminished subjective well-being as the result of reading other people’s stories [35]. Reading stories about successful pregnancies led to increased feelings of jealousy, pain and a sense of alienation, whereas reading about bad experiences led to increased feelings of worry, anxiety and decreased optimism. Thus, this may lead to diminished subjective well-being. On the other hand, one study in our sample shows that this actually may enhance subjective-well-being [24]. In particular, this paper focused on blogs whereas other studies focused on online support groups [24]. Among other uses, blogs can be used as personals diaries to express thoughts, feelings, and stories [9]. Level of distress actually decreases when people blog about their emotional difficulties [46]. Proposition 2: Reading other people’s stories about a negative experience leads to diminished subjective well-being. This effect is weaker for patients who blog about their experiences than for those who do not. Relationship between patients and healthcare professionals: shift in power balance and increased quality of decision making The effects of social media use by patients for health related reasons show that social media use by patients can lead to patient empowerment. Patient empowerment is an established concept in the medical research and has been promoted to foster patient autonomy [47]. As a result of the patient empowerment, patients may increasingly interact with their healthcare professional and get more involved in the decision making process [15]. In this case, social media can be seen as a “new” technology adopted by patients, which may shift the power balance between the healthcare professional and the patient. The use of new technologies in healthcare has been suggested as a way to empower end-consumers by enabling speed and convenience in accessing health related information [48]. In this line, the patients are able to actively participate in the interactions with healthcare professionals. On the other hand, the healthcare professionals may experience a decrease in power in the decision making process. According to the political variant of the interaction theory [49], “a product of the interaction of system features with the intra-organizational distribution of power, defined either objectively, in terms of horizontal or vertical power dimensions, or subjectively, in terms of symbolism can be resistance to the system”. Hence, redistribution of power between patients and healthcare professionals may cause the resistance from healthcare professionals. Yet, the role of health professionals has to change because embracing patient empowerment in healthcare means making a change, which sometimes seem difficult due to traditional approach, which is embedded in their current training [50]. However, increased patient involvement in the clinical interaction could potentially increase the risk placed on the healthcare professionals [13]. Healthcare professional may not be in complete control of the information used during decision making as the patient also has a voice, but the healthcare professional bears full responsibility for the decision taken. When patients bring in the information from social media to the consultation, this could lead to unnecessary processes of sorting relevant information from irrelevant information and can be experienced as challenging the healthcare professional’s expertise [1, 13]. Hence, based on these findings it is possible for healthcare professionals to resist this shift in the balance of power. However, increased equalization of the healthcare professional and patient communication can be a positive and desired effect. In particular, healthcare professionals may become more patient-centred, thus complementing the patient empowerment [51]. As a consequence of patient empowerment, we propose that the quality of clinical decision making may be enhanced. According to the concept of bounded rationality [52], not all information can be gained on all available treatment options by healthcare professionals, as the human mind has a limited capacity to process the available information and often time is limited as well. Hence, healthcare professionals are unable to know all the information regarding treatment options and the newest developments, which affects their decision making. Thus, patients can extend this information base of the healthcare professional by specializing themselves in their own condition. This could provide an opportunity to increase the quality of the treatment decisions. Proposition 3: As a result of patient empowerment due to patients using social media for health related reasons, the power balance between healthcare professionals and patients becomes more equalized, leading to increased quality of clinical decisions making. Notwithstanding the interesting results described above, this research has some limitations which, along with the three propositions, suggest opportunities for further research. It is possible that we missed some articles that could have used different terminology. Consequently, the results of this paper might not be generalizable for all social media platforms. For practical reasons, we excluded non-English papers. Finally, a limitation of every literature review is that the authors of the included articles will have had different objectives and used different methods and means of interpretation in reaching their conclusions. In this paper, we highlighted the most important findings on our topic of study and we categorized the key effects of social media use on patients and on their relationships with healthcare professionals. Conclusions The use of social media by patients for health related reasons is growing. This systematic literature review reflects on beneficial and potentially harmful effects of social media use by patients for health related. The findings show that patients use social media mainly for social support, which is represented through information support, emotional support, esteem support, and network support. Other identified types of social media use by patients have found to be emotional expression and social comparison. These types of social media use by patients were found to most commonly lead to patient empowerment. Other effects of social media use by patients we identified were diminished subjective well-being, addiction to social media, being targeted for promotion, and loss of privacy. The types of social media use by patients were also found to affect the healthcare professional and patient relationship by stimulating more equal communication between the patient and healthcare professional, shorter relationships, harmonious relationships, suboptimal interaction between the patient and healthcare professional. Whereas some of the articles discussed the effects of patients’ use of social media on relationship between patients and healthcare professionals briefly, we encourage future research to tackle this issue. We developed three propositions, which may also stimulate further research in this respect. Additional files Additional file 1: Appendix A-Search string. (DOCX 14 kb) Additional file 2: Appendix B-List of databases. (DOCX 14 kb) Additional file 3: Appendix C-Quality assessment [53]. (DOCX 21 kb) Additional file 4: Appendix D-Summary of articles per social media category. (DOCX 14 kb) We thank Eveline Hage for providing insightful feedback in the course of manuscript preparation. Funding We have not received any funding for conducting this study. Availability of data and materials Materials and data used in this literature review may be obtained from the first author. Authors’ contributions ES was responsible for the research design, significantly contributed to the selection and analysis of included papers and reworked an earlier draft of the manuscript. WH contributed with the paper selection and analysis and wrote a preliminary draft of the manuscript. AB made significant contributions to the framework for analysis, interpretation of selected papers and writing the manuscript. DJL made significant contribution to interpretation of the studies and participated in writing the final version of the manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate Not applicable. ==== Refs References 1. Rupert DJ Moultrie RR Read JG Amoozegar JB Bornkessel AS Donoghue AC Sullivan HW Perceived healthcare provider reactions to patient and caregiver use of online health communities Patient Educ Couns 2014 96 3 320 326 10.1016/j.pec.2014.05.015 24923652 2. Ho YX O’Connor BH Mulvaney SA Features of online health communities for adolescents with type 1 diabetes West J Nurs Res 2014 36 9 1183 1198 10.1177/0193945913520414 24473058 3. McCaughey D Baumgardner C Gaudes A LaRochelle D Jiaxin K Wu KJ Raichura T Best practices in social media: Utilizing a value matrix to assess social media’s impact on health care Soc Sci Comput Rev 2014 32 5 575 589 10.1177/0894439314525332 4. Williams J A new roadmap for healthcare business success J Healthc Financ Manage Assoc 2011 65 5 62 69 5. Li C Bernoff J Groundswell: Winning in a world transformed by social technologies 2008 Boston Harvard Business School Press 6. Hawn C Take two aspirin and tweet me in the morning: How Twitter, Facebook, and other social media are reshaping health care Health Aff 2009 28 2 361 368 10.1377/hlthaff.28.2.361 7. Carter M. Medicine and the media: How Twitter may have helped Nigeria contain Ebola. Br Med J. 2014;349. 8. Antheunis ML Tates K Nieboer TE Patients’ and health professionals’ use of social media in health care: Motives, barriers and expectations Patient Educ Couns 2013 92 3 426 431 10.1016/j.pec.2013.06.020 23899831 9. Kaplan AM Haenlein M Users of the world, unite! The challenges and opportunities of Social Media Bus Horiz 2010 53 59 68 10.1016/j.bushor.2009.09.003 10. WHO Classifying health workers: Mapping occupations to the international standard classification 2010 11. Moher D Liberati A Tetzlaff J Altman DG The PRISMA Group Preferred reporting items for systematic reviews and meta-analyses: The PRISMA Statement Open Med 2009 3 3 123 130 12. Kmet LM Lee RC Cook LS Standard quality assessment criteria for evaluating primary research papers from a variety of fields Alberta Herit Found Med Res 2004 13 1 22 13. Broom A The eMale: Prostate cancer, masculinity, and online support as a challenge to medical expertise J Sociol 2005 41 1 87 104 10.1177/1440783305050965 14. Wentzer HS Bygholm A Narratives of empowerment and compliance: Studies of communication in online patient support groups Int J Med Inform 2013 82 12 386 10.1016/j.ijmedinf.2013.01.008 15. Colineau N Paris C Talking about your health to strangers: understanding the use of online social networks by patients New Rev Hypermed Multimed 2010 16 1 141 160 10.1080/13614568.2010.496131 16. Gómez-Zúñiga B Fernandez-Luque L Pousada M Hernández-Encuentra E Armayones M ePatients on YouTube: Analysis of four experiences from the patients’ perspective J Med Internet Res 2012 14 2 26 10.2196/jmir.1968 17. Kofinas JD Varrey A Sapra KJ Kanj RV Chervenak FA Asfaw T Adjunctive social media for more effective contraceptive counseling Obstet Gynecol 2014 123 4 763 770 10.1097/AOG.0000000000000172 24785602 18. Schaefer C Coyne JC Lazarus RS The health-related functions of social support J Behav Med 1981 4 4 381 406 10.1007/BF00846149 7338894 19. Cohen S Underwood LG Gottlieb BH Social support measurement and intervention: a guide for health and social scientists 2000 New York Oxford 20. Mattson M Hall JG Health as communication nexus: A service-learning approach 2011 Dubuque Kendall Hunt 21. Menon IS Sharma MK Chandra PS Thennarasu K Social networking sites: An adjunctive treatment modality for psychological problems Indian J Psychol Med 2014 36 3 260 263 10.4103/0253-7176.135374 25035548 22. Van Uden-Kraan CF Drossaert CHC Taal E Seydel ER Van de Laar M Self-reported differences in empowerment between lurkers and posters in online patient support groups J Med Internet Res 2008 10 2 18 10.2196/jmir.992 23. Bartlett YK Coulson NS An investigation into the empowerment effects of using online support groups and how this affects health professional/patient communication Patient Educ Couns 2011 83 1 113 119 10.1016/j.pec.2010.05.029 20599338 24. Chiu YC Hsieh YL Communication online with fellow cancer patients: Writing to be remembered, gain strength, and find survivors J Health Psychol 2013 18 12 1572 1581 10.1177/1359105312465915 23221492 25. Coulson NS How do online patient support communities affect the experience of inflammatory bowel disease? An online survey JRSM Short Reports 2013 4 1 8 10.1177/2042533313478004 26. Setoyama Y Yamazaki Y Namayama K Benefits of peer support in online Japanese breast cancer communities: Differences between lurkers and posters J Med Internet Res 2011 13 4 122 10.2196/jmir.1696 27. Bers MU Beals LM Chau C Satoh K Blume ED DeMaso DR Gonzalez-Heydrich J Use of a virtual community as a psychosocial support system in pediatric transplantation Pediatr Transplant 2010 14 2 261 267 10.1111/j.1399-3046.2010.01271.x 20470360 28. Frost JH Massagli MP Social uses of personal health information within PatientsLikeMe, an online patient community: What can happen when patients have access to one another’s data J Med Internet Res 2008 10 3 15 10.2196/jmir.1053 29. Gutschoven K Van den Bulck J Towards the measurement of psychological health empowerment in the general public 2006 30. Oh HJ Lee B The effect of computer-mediated social support in online communities on patient empowerment and doctor–patient communication Health Commun 2012 27 1 30 41 10.1080/10410236.2011.567449 21797714 31. Sahoo FM Mohapatra L Psychological well-Being in professional groups J Indian Acad Appl Psychol 2009 35 2 211 217 32. Chen FF Jing Y Hayes A Lee JM Two concepts or two approaches? A bifactor analysis of psychological and subjective well-being J Happiness Stud 2013 14 3 1033 1068 10.1007/s10902-012-9367-x 33. Ryff CD Happiness is everything, or is it? Explorations on the meaning of psychological well-being J Pers Soc Psychol 1989 57 6 1069 1081 10.1037/0022-3514.57.6.1069 34. Bauer R Bauer M Spiessl H Kagerbauer T Cyber-support: An analysis of online self-help forums (online self-help forums in bipolar disorder) Nordic J Psychiatry 2013 67 3 185 190 10.3109/08039488.2012.700734 35. Malik S Coulson NS ‘They all supported me but I felt like I suddenly didn’t belong anymore’: An exploration of perceived disadvantages to online support seeking J Psychosom Obstet Gynecol 2010 31 3 140 149 10.3109/0167482X.2010.504870 36. Wicks P Massagli M Frost J Brownstein C Okun S Vaughan T Bradley R Heywood J Sharing health data for better outcomes on PatientsLikeMe J Med Internet Res 2010 12 2 19 10.2196/jmir.1549 37. Lee YC Wu WL The effects of situated learning and health knowledge involvement on health communications Reprod Health 2014 11 1 220 233 10.1186/1742-4755-11-93 38. Kim S Yoon JW The use of an online forum for health information by married Korean women in the United States Inf Res 2012 17 2 514 39. Pagoto S Schneider KL Evans M Waring ME Appelhans B Busch AM Whited MC Thind H Ziedonis M Tweeting it off: Characteristics of adults who tweet about a weight loss attempt J Am Med Infor Assoc 2014 21 6 1032 1037 10.1136/amiajnl-2014-002652 40. Farber BA Nitzburg GC Young adult self-disclosures in psychotherapy and on Facebook Couns Psychol Q 2015 29 1 1 14 41. Magliano L Marasco C Fiorillo A Malangone C Guarneri M Maj M The impact of professional and social network support on the burden of families of patients with schizophrenia in Italy Acta Psychiatr Scand 2002 106 4 291 298 10.1034/j.1600-0447.2002.02223.x 12225496 42. Blickem C Kennedy A Vassilev I Morris R Brooks H Jariwala P Blakeman T Rogers A “Linking people with long‐term health conditions to healthy community activities: development of Patient‐Led Assessment for Network Support (PLANS) Health Expect 2013 16 3 48 59 10.1111/hex.12088 43. Steinfeld C Ellison NB Lampe C Social capital, self-esteem, and use of online social network sites: A longitudinal analysis J Appl Dev Psychol 2008 29 6 434 445 10.1016/j.appdev.2008.07.002 44. Osatuyi B Is lurking an anxiety-masking strategy on social media sites? The effects of lurking and computer anxiety on explaining information privacy concern on social media platforms Comput Hum Behav 2015 49 324 332 10.1016/j.chb.2015.02.062 45. Tobin SJ Vanman EJ Verreynne M Saeri AK Threats to belonging on Facebook: Lurking and ostracism Soc Influ 2015 10 1 31 42 10.1080/15534510.2014.893924 46. Boniel-Nissim M Barak A The therapeutic value of adolescents’ blogging about social–emotional difficulties Psychol Serv 2013 10 3 333 341 10.1037/a0026664 23937092 47. Feste C Anderson RM Empowerment: from philosophy to practice Patient Educ Couns 1995 26 1 139 44 10.1016/0738-3991(95)00730-N 7494713 48. Angaran DM Telemedicine and telepharmacy: current status and future implications Am J Health Syst Pharm 1999 56 14 1405 26 10428449 49. Markus ML Power, politics, and MIS implementation Commun ACM 1983 26 6 430 444 10.1145/358141.358148 50. Anderson RM Funnell MM Patient empowerment: myths and misconceptions Patient Educ Couns 2010 79 3 277 82 10.1016/j.pec.2009.07.025 19682830 51. Holmström I Röing M The relation between patient-centeredness and patient empowerment: a discussion on concepts Patient Educ Couns 2010 79 2 167 72 10.1016/j.pec.2009.08.008 19748203 52. Simon HA Decision and organization 1972 Amsterdam North-Holland Publishing 53. Bletsos K Alexias G Tsekeris C Towards a fourth cosmology of doctor-patient relationship: a reflection on the virtual patient community PatientsLikeMe Open Access J Glob Sustain Infor Soc 2013 11 1 136 144

PMC005xxxxxx/PMC5000485.txt

==== Front Stem Cell Res TherStem Cell Res TherStem Cell Research & Therapy1757-6512BioMed Central London 37510.1186/s13287-016-0375-3ResearchTGFβ-induced switch from adipogenic to osteogenic differentiation of human mesenchymal stem cells: identification of drug targets for prevention of fat cell differentiation van Zoelen Everardus J. +31-24-3652844jovazo@wxs.nl 12Duarte Isabel isabel.duarte@gmail.com 123Hendriks José M. josehendriks@gmail.com 124van der Woning Sebastian P. BvanderWoning@argenx.com 1251 Department of Cell and Applied Biology, Faculty of Science, Radboud University Nijmegen, PO Box 9010, 6500 GL Nijmegen, The Netherlands 2 Present Address: Department of Cell and Applied Biology, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands 3 Present Address: Systems Biology and Bioinformatics Laboratory (SysBioLab), University of Algarve, Faro, Portugal 4 Present Address: Department of Physical Organic Chemistry, Radboud University Nijmegen, Nijmegen, The Netherlands 5 Present Address: ARGENX BVBA, Technologiepark 30, B-9052 Zwijnaarde, Belgium 26 8 2016 26 8 2016 2016 7 1 1237 1 2016 12 7 2016 25 7 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Patients suffering from osteoporosis show an increased number of adipocytes in their bone marrow, concomitant with a reduction in the pool of human mesenchymal stem cells (hMSCs) that are able to differentiate into osteoblasts, thus leading to suppressed osteogenesis. Methods In order to be able to interfere with this process, we have investigated in-vitro culture conditions whereby adipogenic differentiation of hMSCs is impaired and osteogenic differentiation is promoted. By means of gene expression microarray analysis, we have investigated genes which are potential targets for prevention of fat cell differentiation. Results Our data show that BMP2 promotes both adipogenic and osteogenic differentiation of hMSCs, while transforming growth factor beta (TGFβ) inhibits differentiation into both lineages. However, when cells are cultured under adipogenic differentiation conditions, which contain cAMP-enhancing agents such as IBMX of PGE2, TGFβ promotes osteogenic differentiation, while at the same time inhibiting adipogenic differentiation. Gene expression and immunoblot analysis indicated that IBMX-induced suppression of HDAC5 levels plays an important role in the inhibitory effect of TGFβ on osteogenic differentiation. By means of gene expression microarray analysis, we have investigated genes which are downregulated by TGFβ under adipogenic differentiation conditions and may therefore be potential targets for prevention of fat cell differentiation. We thus identified nine genes for which FDA-approved drugs are available. Our results show that drugs directed against the nuclear hormone receptor PPARG, the metalloproteinase ADAMTS5, and the aldo-keto reductase AKR1B10 inhibit adipogenic differentiation in a dose-dependent manner, although in contrast to TGFβ they do not appear to promote osteogenic differentiation. Conclusions The approach chosen in this study has resulted in the identification of new targets for inhibition of fat cell differentiation, which may not only be relevant for prevention of osteoporosis, but also of obesity. Keywords Mesenchymal stem cellAdipogenesisOsteogenesisOsteoporosisBone marrowHistone deacetylaseMetalloproteinaseAldo-keto reductasehttp://dx.doi.org/10.13039/501100001826ZonMw90201174van Zoelen Everardus J. issue-copyright-statement© The Author(s) 2016 ==== Body Background Human mesenchymal stem cells (hMSCs) from bone marrow have the ability to differentiate into cells from multiple lineages, including osteoblasts and adipocytes. The commitment of hMSCs towards either the osteogenic or adipogenic lineage depends on the local availability of growth factors and hormones, which are able to activate lineage-specific transcriptional regulators [1]. Patients suffering from osteoporosis show an increased number of adipocytes in their bone marrow, concomitant with a reduction in the pool of hMSCs that are able to differentiate into osteoblasts, thus leading to suppressed osteogenesis [2, 3]. It is still unclear to what extent this age-related increase in differentiation of hMSCs towards adipocytes results from intrinsic changes in the stem cells or from alterations in the microenvironment of the bone marrow [1, 4]. These observations have recently stirred increasing interest in anabolic therapies for osteoporosis, whereby osteogenic differentiation of hMSCs is stimulated by preventing adipogenic differentiation [5, 6]. Most information about the signaling pathways that are required for osteogenic and adipogenic differentiation of hMSCs has come from in-vitro studies, whereby cells are treated with specific combinations of growth factors and hormones [7]. Differentiation into both lineages requires treatment of monolayer cells with dexamethasone (DEX) and is enhanced by the presence of bone morphogenetic proteins (BMPs). Osteogenic differentiation is obtained by the additional presence of ascorbate and β-glycerophosphate, whereas adipogenic differentiation requires treatment with insulin, 3-isobutyl-1-methylxanthine (IBMX), and the PPARG activator rosiglitazone. Our previous data have indicated that under these experimental conditions at least 75 % of the hMSCs differentiate into either osteoblasts or adipocytes [7]. Activation of the RUNX2 nuclear transcription factor appears to be essential for the osteogenic pathway of hMSCs, while the adipogenic pathway requires the transcriptional activity of the PPARG nuclear hormone receptor [1]. Evidence has been presented that transcriptional regulators promoting differentiation into one of these lineages actively suppress differentiation into the other lineage [8]. It has therefore been postulated that a reciprocal relationship exists between the osteogenic and adipogenic pathways, implying that impaired adipogenic differentiation of hMSCs may result in enhanced osteogenic differentiation [3]. Multiple regulators are known that affect the choice between the osteogenic and adipogenic lineage. Most notably, activation of the WNT/β-catenin pathway promotes osteogenic differentiation and inhibits adipogenic differentiation of hMSCs [9]. BMP enhances the outgrowth of both osteoblasts and adipocytes, while the related cytokine transforming growth factor beta (TGFβ) inhibits both osteogenic and adipogenic differentiation, at least when tested under these in-vitro conditions [10, 11]. Moreover, Kim et al. [12] have shown that cAMP-activated protein kinases regulate the differentiation choice of hMSCs between osteogenesis and adipogenesis. In order to find drugs affecting the choice between osteogenic and adipogenic differentiation of hMSCs, we have optimized the adipogenic culture conditions in such a way that, within the same culture, a fraction of the cells differentiates into osteoblasts and another fraction into adipocytes. Our results show that addition of TGFβ to these cultures fully blocks adipogenic differentiation but, surprisingly, enhances osteogenic differentiation. Analysis of the individual components in the culture medium showed that the presence of the phosphodiesterase inhibitor IBMX, which stabilizes cAMP levels in the cell, converted TGFβ from an inhibitor to an enhancer of osteogenic differentiation. Based on these observations we have set up a gene expression microarray experiment to identity genes that under these optimized adipogenic culture conditions are downregulated by TGFβ. The genes identified in this way seem to play an important role in adipogenesis, since inhibitors of the corresponding proteins were found to be able to block adipogenic differentiation of hMSCs. Some of these inhibitors have already received FDA approval for the treatment of various diseases, and may therefore be good candidates for therapeutic drug repurposing in order to treat patients suffering from such diseases as obesity and osteoporosis. Methods Culture and differentiation of hMSCs hMSCs harvested from normal human bone marrow were purchased from Lonza (Walkersville, MD, USA) at passage 2. Cells were expanded for no more than five passages in “mesenchymal stem cell growth medium” (MSCGM; Lonza) at 37 °C in a humidified atmosphere containing 7.5 % CO2. Studies were performed with hMSCs from three different donors, encoded 5F0138, 6F4085, and 7F3458. For differentiation experiments, 4.0 × 104 cells per cm2 were seeded in high-glucose-containing Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10 % fetal bovine serum (a selected lot from Lonza), 100 U/ml penicillin, and 100 μg/ml streptomycin. This medium will be further referred to as “proliferation medium” (PM). The next day, cells were switched to either osteogenic or adipogenic differentiation medium. Cells treated with PM were used as negative controls. Osteogenic differentiation medium (ODM) was composed of PM supplemented with 10−7 M DEX, 0.2 mM ascorbate, and 10 mM β-glycerophosphate. Adipogenic differentiation medium (ADM) was composed of PM supplemented with 10−6 M DEX, 10 μg/ml insulin (R&D Systems, Minneapolis, MN, USA), 10−7 M rosiglitazone (Sigma-Aldrich, St. Louis, MO, USA), and 500 μM IBMX (Sigma-Aldrich). Unless indicated otherwise, recombinant human TGFβ1 and BMP2 (both from R&D Systems) were used at concentrations of 2 ng/ml and 125 ng/ml, respectively. Prostaglandin E2 (PGE2), Batimastat, and Zopolrestat (Sigma-Aldrich) were used at the indicated concentrations. Media were refreshed every 3–4 days. Alkaline phosphatase assays To quantify alkaline phosphatase (ALP) enzymatic activity as a measure of osteogenic differentiation, hMSCs were seeded in 96-well tissue culture plates as already described, after which cells were differentiated for 7 days in osteogenic differentiation medium. ALP enzymatic activity was quantified by measuring the formation of p-nitrophenol from p-nitrophenyl phosphate (PNPP; Sigma-Aldrich), as described previously [13]. ALP enzymatic activity was corrected for differences in cell number, as determined by a Neutral Red assay. Cells were incubated with Neutral Red dye diluted in PBS for 1 hour at 37 °C. After washing with PBS, the dye was extracted from the cells using 0.05 M NaH2PO4 in 50 % EtOH, after which the absorbance was measured at 540 nm. For histochemical analysis of ALP activity, cells were seeded in 48-well tissue culture plates and differentiated for 7 days in osteogenic differentiation medium. Subsequently, cells were fixed in 3.7 % formaldehyde/PBS for 10 min at 22 °C. After washing with PBS, cells were incubated for 1 hour at 37 °C in a mixture of 0.1 mg/ml naphtol AS-MX phosphate (Sigma-Aldrich), 0.5 % N,N-dimethylformamide, 2 mM MgCl2, and 0.6 mg/ml Fast Blue BB salt (Sigma-Aldrich) in 0.1 M Tris–HCl, pH 8.5. Mineralization assay To measure calcium deposition in the extracellular matrix, hMSCs were seeded in 24-well tissue culture plates and cultured for 13 days under osteogenic or adipogenic differentiation conditions, as indicated. Cells were subsequently washed twice with PBS after which calcium was extracted from the extracellular matrix by treatment with 150 μl of 0.5 M HCl. Calcium concentrations were measured in a colorimetric assay using o-cresolphtalein complexone as a chromogenic agent, according to the protocol provided by the manufacturer (Sigma-Aldrich). Oil Red O staining and Triglyceride assay To quantify adipogenic differentiation, lipid droplets were stained in mature adipocytes obtained after treatment of hMSCs for 9 days in adipogenic differentiation medium. Cells were first washed twice with PBS, fixed for 30 min with 1 % formaldehyde in PBS, and then washed once with water and twice with 60 % isopropanol. Cells were then stained for 1 hour with 0.3 % w/v Oil Red O (Sigma-Aldrich) in 60 % isopropanol. Subsequently, cells were washed once with 60 % isopropanol and twice with distilled water. For quantification of Oil Red O staining, samples were treated with 100 % isopropanol and absorbance was measured at 530 nm. The amount of triglycerides stored in lipid droplets of mature adipocytes was quantified after treatment of hMSCs for 9 days in adipogenic differentiation medium. Cells in 96-well tissue culture plates were washed twice with PBS. Triglycerides were extracted from the lipid droplets by freezing the cells in 50 μl of a buffer containing 25 mM Tris–HCl (pH 7.5) and 1 mM EDTA, followed by addition of 40 μl tert-butanol and 10 μl methanol. Samples were heat-dried at 55 °C, after which they were resuspended in Triglycerides LiquiColor® mono reagents (HUMAN GmbH, Wiesbaden, Germany). Triglycerides were quantified by measuring the absorbance at 490 nm. RNA isolation and real-time quantitative RT-PCR RNA was isolated as described by Piek et al. [13]. For cDNA synthesis, 1 μg of total RNA was reverse transcribed using random hexamer primers and SUPERSCRIPT™ II reverse transcriptase (Invitrogen, Carlsbad, CA, USA). Subsequently, cDNA was amplified in a quantitative real-time PCR, performed using Power SYBR Green® PCR Mastermix (Applied Biosystems, Foster City, CA, USA) on an Applied Biosystems 7500 Real-time Fast PCR System. For each gene, PCR was carried out in duplicate and mean expression values were calculated relative to the mean expression level of the housekeeping gene RPS27A (ribosomal protein S27a). Human gene-specific PCR primers used included the following:Histone deacetylase 5 (HDAC5)-FW: 5′-ATGACAACGGGAACTTCTTTCC-3′. Histone deacetylase 5 (HDAC5)-RV: 5′-CCATGCCACGTTCACATTGTA-3′. Adiponectin (ADIPOQ)-FW: 5′-CCCAAAGAGGAGAGAGGAAGC-3′. Adiponectin (ADIPOQ)-RV: 5′-GCCAGAGCAATGAGATGCAA-3′. Alkaline phosphatase (ALPL)-FW: 5′-GATGGACAAGTTCCCCTTCGT-3′. Alkaline phosphatase (ALPL)-RV: 5′-GGACCTGGGCATTGGTGTT-3′. Ribosomal protein S27a (RPS27A)-FW: 5′-GTTAAGCTGGCTGTCCTGAAA-3′. Ribosomal protein S27a (RPS27A)-RV: 5′-CATCAGAAGGGCACTCTCG-3′. Immunoblotting hMSCs were seeded at 4.0 × 104 cells per cm2 in six-well plates and cultured for 24 hours in the indicated differentiation media. Cells were then lysed in 250 μl of RIPA lysis buffer per well. Then 5 μl of reducing sample buffer was added to 25 μl of lysate, heated to 95 °C, and subsequently loaded onto an 8 % SDS-PAGE gel. HDAC5 was detected on blots using a goat polyclonal anti-HDAC5 antibody (G-18, 1/200 dilution) raised against the N-terminus of human HDAC5 (sc-5250; Santa Cruz Biotechnology, Dallas, TX, USA), followed by an HRP-labeled polyclonal secondary antibody. Antibodies against α-tubulin (Sigma) served as a loading control. Gene expression microarray analysis To identify genes that are regulated during osteogenic and adipogenic differentiation of hMSCs, a total of 54 samples (each containing 800,000 cells/ 20 cm2) were seeded in PM and grown for 24 hours. Subsequently the medium was exchanged for differentiation medium, now consisting of PM with 10−6 M DEX, 10 μg/ml insulin, 10−7 M rosiglitazone, and 50 ng/ml BMP2 (B). In addition, either 5 ng/ml TGFβ (BT), or 250 μM IBMX (BI), or 5 ng/ml TGFβ and 250 μM IBMX (BTI) were added. Samples were incubated for either 0, 1, 2, 3, or 7 days. Experiments for each group and time point were carried out as three biological replicates, while the untreated control group (time 0) consisted of six samples. RNA was isolated as already described, and hybridized onto Affymetrix HGU 133 plus 2.0 microarrays according to existing protocols [13]. Microarray data were analyzed with the R language for statistical computing using appropriate Bioconductor packages (http://bioconductor.org/) for reading, normalizing, and statistically evaluating the data, followed by annotation of the gene sets and integration of parallel data sources. Briefly, the analysis started with a careful quality assessment of the dataset using the automatic R pipeline AffymetrixQC [14], which was customized and run locally. All 54 microarrays passed the quality control and were included in the analysis, consisting of robust microarray analysis (RMA) normalization [15], followed by statistical analysis to find differentially expressed genes using Linear Models for Microarray Data (LIMMA) [16], and subsequent functional annotation and enrichment analysis using the online resource Database for Annotation, Visualization and Integrated Discovery (DAVID) [17, 18]. Finally, the list of differentially expressed genes for the contrasts of interest was crossed with the information from the DrugBank database [19] in order to derive the final list of candidate genes for experimental testing. All R scripts used for this analysis are available upon request. Current microarray data have been deposited in NCBI’s Gene Expression Omnibus [GEO:GSE84500] (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84500). Statistical analysis Student’s t test was used for statistical comparisons. Numeric data are represented as mean ± standard deviation of triplicate experiments, unless stated otherwise. Results TGFβ induces hMSCs to switch from adipogenic to osteogenic differentiation BMPs have been described as positive regulators of both osteogenesis and adipogenesis [8, 10]. In order to study the effect of BMP2 on differentiation of hMSCs in more detail, we cultured these cells in either osteogenic differentiation medium or adipogenic differentiation medium in the absence and presence of BMP2. Figure 1a shows that addition of BMP2 has only a small stimulatory effect on adipogenic differentiation of hMSCs, as measured by the amount of the triglyceride production. On the other hand, BMP2 strongly enhanced osteogenic differentiation, as indicated by increased ALP activity (Fig. 1b).Fig. 1 Effect of TGFβ on adipogenic and osteogenic differentiation of hMSCs. a Triglyceride production by hMSCs, 9 days after incubation with adipogenic differentiation medium in the absence (white shading) and presence (black shading) of 125 ng/ml BMP2 and increasing concentrations of TGFβ1. The enhancing effect of BMP2 is not significant, while the inhibitory effect of TGFβ is significant (p < 0.01) above 1 ng/ml. b Alkaline phosphatase (ALP) activity of hMSCs, 7 days after incubation with osteogenic differentiation medium in the absence (white shading) and presence (black shading) of 125 ng/ml BMP2 and increasing concentrations of TGFβ1. Enhancing effect of BMP2 is significant (p < 0.01) at all data points, while the inhibitory effect of TGFβ is significant (p < 0.01) above 1 ng/ml. c TGFβ-induced switch from adipogenic to osteogenic differentiation. ALP staining (after 7 days) and Oil Red O (ORO) staining (after 9 days) following incubation of hMSCs in adipogenic differentiation medium containing 125 ng/ml BMP2 and the indicated concentrations of TGFβ1. BMP bone morphogenetic protein, TGFβ transforming growth factor beta The role of TGFβ in adipogenic and osteogenic differentiation of hMSCs is still unclear. Figure 1a also shows that adding TGFβ to adipogenic differentiation medium blocks adipogenic differentiation of hMSCs in a dose-dependent manner, both in the absence and additional presence of BMP2. Figure 1b shows that addition of TGFβ to osteogenic differentiation medium results in a similar inhibition of osteogenic differentiation, both in agreement with previous data [10, 11]. However, when hMSCs are treated with adipogenic differentiation medium (which contains a 10-fold higher concentration of DEX than osteogenic differentiation medium) in combination with BMP2, a fraction of the cells will differentiate into bone cells and a fraction into fat cells within the same well, as shown in Fig. 1c by histological staining. Addition of TGFβ under these conditions resulted is a dose-dependent increase in the number of ALP-positive bone cells, with a concomitant reduction in Oil Red O-positive fat cells. These data show that TGFβ blocks bone cell differentiation under osteogenic differentiation conditions, but enhances bone cell differentiation under adipogenic differentiation conditions. It can therefore be concluded that, under the experimental conditions used in Fig. 1c, TGFβ induces a switch from adipogenic to osteogenic differentiation. IBMX is a critical component in the TGFβ-mediated switch in cell fate In order to investigate which component of the adipogenic differentiation medium allows osteogenic differentiation in the presence of TGFβ, we added the adipogenic differentiation medium components insulin, IBMX, and rosiglitazone successively to hMSCs grown in osteogenic differentiation medium with BMP2 and TGFβ. Figure 2a shows that the inhibition of osteogenic differentiation by TGFβ could not be prevented by insulin or rosiglitazone, but was largely overcome upon addition of IBMX. A parallel experiment showed that omission of IBMX from adipogenic differentiation medium was sufficient to prevent the TGFβ-induced enhancement of osteogenic differentiation, while removal of insulin or rosiglitazone was without effect (Fig. 2b).Fig. 2 cAMP regulators control TGFβ-induced osteogenic differentiation of hMSCs. Osteogenic differentiation was measured by ALP activity and corrected for the level of Neutral Red uptake as a measure for the number of cells present in the well. a Osteogenic differentiation of hMSCs in osteogenic differentiation medium supplemented with or without 125 ng/ml BMP2, 2 ng/ml TGFβ1, 10 μg/ml insulin, 500 μM IBMX, or 10−7 M rosiglitazone. ALP activity is significantly higher (p < 0.001) in medium with BMP2 and TGFβ in the presence of IBMX than in the absence of IBMX. b Osteogenic differentiation of hMSCs in adipogenic differentiation medium supplemented with or without 125 ng/ml BMP2 and 2 ng/ml TGFβ1, and following omission of 10 μg/ml insulin, 500 μM IBMX, or 10−7 M rosiglitazone. ALP activity is significantly higher (p < 0.01) in medium with all supplements than in the absence of IBMX. c Effect of PGE2, added at the indicated nanomolar concentrations, on osteogenic differentiation of hMSCs in osteogenic differentiation medium. A comparison is made with the effects of BMP2 (125 ng/ml), TGFβ (2 ng/ml), and IBMX (500 μM). Enhancement of ALP activity is significant (p < 0.05) at concentrations of 10 nM PGE2 and above. d Effect of BMP2 (125 ng/ml) and TGFβ (2 ng/ml) on total Ca2+ deposition (μg) in a six-well plate well (10 cm2) by hMSCs, cultured for 13 days in either osteogenic or adipogenic differentiation medium. Ca2+ deposition is significantly enhanced by BMP2 alone in osteogenic differentiation medium (p < 0.01) and by BMP2 + TGFβ in adipogenic differentiation medium (p < 0.05). ALP alkaline phosphatase, BMP bone morphogenetic protein, IBMX 3-isobutyl-1-methylxanthine, PGE2 prostaglandin E2, TGFβ transforming growth factor beta IBMX is a phosphodiesterase inhibitor, which prevents degradation of cAMP. In order to show that enhanced cAMP levels play a role in the TGFβ-mediated switch in cell fate, we tested the effect of PGE2, a known activator of adenylate cyclase. Figure 2c shows that PGE2 is able to overcome TGFβ-induced inhibition of osteogenic differentiation of hMSCs in a dose-dependent manner, to a similar extent as IBMX. Osteogenic differentiation requires not only matrix maturation, as indicated by alkaline phosphatase expression, but also matrix mineralization, as indicated by calcium deposition. Figure 2d shows that under osteogenic differentiation conditions BMP is required for calcium deposition by hMSCs, while both BMP and TGFβ are required under adipogenic differentiation. These data show TGFβ is able to induce fully differentiated, mineralized osteoblasts under adipogenic differentiation conditions. IBMX suppresses HDAC5 expression Previous studies [20] have shown that TGFβ-mediated inhibition of osteogenic differentiation can be overcome by trichostatin A, an inhibitor of class I and II mammalian histone deacetylases (HDACs). We confirmed this observation upon incubating hMSCs in osteogenic differentiation medium with BMP2 and TGFβ (data not shown). Kang et al. [20] have presented evidence that HDAC4/5 can interact with TGFβ-activated SMAD3, resulting in a complex that represses transcription of the bone marker gene osteocalcin (BGLAP). In human adipose-derived mesenchymal stem cells, trichostatin A impaired PPARG activity, at least under osteogenic differentiation conditions [21]. Still, the role of HDACs in adipogenesis is far from clear, since HDAC inhibitors may either enhance or inhibit adipogenic differentiation [22]. We have studied the expression of HDAC5 under conditions that TGFβ enhances osteogenic differentiation of hMSCs. Figure 3a shows that HDAC5 mRNA levels are slightly upregulated 24–48 hours after addition of osteogenic differentiation medium, particularly in the presence of BMP2 and TGFβ (OBT). A strong reduction in HDAC5 gene expression was observed when IBMX was added to the medium (OBTI), however, thus creating conditions under which adipogenic differentiation is prevented and osteogenic differentiation is promoted. Less reduction in HDAC5 mRNA levels was observed in adipogenic differentiation medium alone. We could not detect mRNA expression of HDAC4 in these cells.Fig. 3 IBMX controls HDAC5 expression levels in hMSCs. a HDAC5 mRNA levels, relative to that of the housekeeping gene RSP27A, of hMSCs incubated for 24 hours (white shading) or 48 hours (black shading) in proliferation medium (C), adipogenic differentiation medium (A), osteogenic differentiation medium (O), osteogenic differentiation medium supplemented with 125 ng/ml BMP2 and 2 ng/ml TGFβ (OBT), and osteogenic differentiation medium supplemented with 125 ng/ml BMP2, 2 ng/ml TGFβ, and 500 μM IBMX (OBTI). Data expressed as percentage of the expression levels at time zero. Results represent the mean and standard deviation of duplicate experiments. Indicated significance levels are relative to expression in control samples (C) at 24 or 48 hours, respectively. b Immunoblot for protein expression of HDAC5 in hMSCs, 5 days after incubation in the indicated media. Expression of α-tubulin was used as a loading control. *p < 0.05; **p < 0.01; ***p < 0.001. HDAC histone deacetylase Figure 3b shows that HDAC5 levels are similarly regulated at the protein level. Western blot analysis revealed the highest expression level in hMSCs treated with osteogenic differentiation medium containing BMP2 and TGFβ (OBT), whereas almost no protein was detected in the additional presence of IBMX (OBTI). These data indicate that under conditions whereby TGFβ enhances osteogenic differentiation, no HDAC5 is available to prevent expression of bone specific genes. Altered gene expression during TGFβ-mediated switch in cell fate The presented data show that, upon incubation of hMSCs in adipogenic differentiation medium containing BMP2 and IBMX, a fraction of the cells will differentiate into ALP-positive bone cells and a fraction into Oil Red O-positive fat cells. Subsequent addition of TGFβ reduces the number of fat cells and enhances the number of bone cells in a dose-dependent manner (see Fig. 1c). This observation implies that under these experimental conditions addition of TGFβ will stimulate the expression of osteoblast genes and reduce the expression of adipocyte genes. In order to identify genes involved in this lineage switch, we performed gene expression microarray analysis on hMSCs, treated for 1, 2, 3, or 7 days with differentiation medium containing DEX, insulin, and rosiglitazone, using as supplements BMP2 and combinations of IBMX and TGFβ. Untreated cells at day 0 served as the control experiment. In order to verify the extent of differentiation of the cells used for the microarray experiments, we used real-time PCR to measure mRNA expression levels of the osteoblast-specific alkaline phosphatase (ALPL) gene and of the adipocyte-specific adiponectin (ADIPOQ) gene, a target gene of the adipogenic master gene PPARG. This analysis was carried out 7 days after incubation with BMP2 (B), BMP2 + TGFβ (BT), BMP2 + IBMX (BI), or BMP2 + TGFβ + IBMX (BTI). Figure 4a shows that under these conditions IBMX, in combination with TGFβ, enhanced ALPL expression. No inhibitory effect of TGFβ was observed on bone cell differentiation, in agreement with the data of Fig. 2b. ADIPOQ expression was strongly enhanced upon IBMX addition, but reduced again to very low levels in the additional presence of TGFβ (Fig. 4b). These data confirm that, at the gene expression level, TGFβ induces a switch from adipocytes to osteoblasts.Fig. 4 Expression of osteogenic and adipogenic markers in hMSCs under conditions used for gene expression microarray analysis. Cells were incubated for 7 days in adipogenic differentiation medium containing 50 ng/ml BMP2 (B-7), 50 ng/ml BMP2 + 5 ng/ml TGFβ (BT-7), 50 ng/ml BMP2 + 500 μM IBMX (BI-7), and 50 ng/ml BMP2 + 5 ng/ml TGFβ + 500 μM IBMX (BTI-7). Untreated cells at day zero (C-0) were used as a control. a mRNA expression of the bone marker ALP (ALPL), relative to that of the housekeeping gene RSP27A. Results represent the mean and standard deviation of duplicate experiments. Both BI-7 (p < 0.05) and BTI-7 (p < 0.01) are significantly higher than B-7 and BT-7. b mRNA expression of the fat marker adiponectin (ADIPOQ), relative to that of the housekeeping gene RSP27A. Results represent the mean and standard deviation of duplicate experiments. BI-7 is significantly higher than both B-7 and BTI-7 (p < 0.01) The data from the 54 microarray samples were normalized using RMA [15] followed by LIMMA [16] statistical analysis to identify differentially expressed genes and functional enrichment analysis using DAVID [17, 18]. From the 54,675 probes on the chip, 7755 probes appeared differentially expressed at any time point or treatment, compared with the t = 0 control, based on a q value of 10−5 and a minimum log2-fold change of 1. Our primary interest was to identify genes that controlled the TGFβ-induced switch from adipogenic to osteogenic differentiation. In the current experiment, genes downregulated by TGFβ are potentially involved in adipogenic differentiation and genes upregulated by TGFβ in osteogenic differentiation. A comparison between the samples BTI and BI resulted in 2911 differentially expressed probes at any time point, of which 1176 probes (735 genes) were differentially expressed at the early time points (days 1 and 2), when cells become committed for lineage specific differentiation. Extending the log2-fold change from 1 to a minimum of 2 resulted in a reduction of the number of differentially expressed genes between BTI and BI to 109, of which 25 were established drug targets according to the DrugBank database (www.drugbank.ca). Visual inspection of the time course for expression of these genes identified nine genes which showed the desired dynamics; that is, modulation at early time points and higher expression in BI than in BTI, as presented in Fig. 5.Fig. 5 Time course for expression of the nine selected genes for their involvement in adipogenic differentiation. Expression levels were obtained from analysis of the 50 ng/ml BMP2 and 250 μM IBMX (BI, white circle) and 50 ng/ml BMP2, 5 ng/ml TGFβ, and 250 μM IBMX (BTI, black square) chips. Expression levels are indicated on a log2 scale. BMP bone morphogenetic protein, IBMX 3-isobutyl-1-methylxanthine, TGFβ transforming growth factor beta Analysis of adipogenic differentiation inhibitors For the thus identified target genes, as presented in Table 1, we tested whether commercially available inhibitors could block the adipogenic differentiation of hMSCs under conditions similar to those used for the microarray analysis. We first confirmed the established observation that adipogenic differentiation does not occur in the absence of a PPARG agonist, such as rosiglitazone, and therefore an antagonist of this receptor was not further tested. We did, however, also observe that inhibitors of ADAMTS5 and AKR1B10 prevented adipogenic differentiation of hMSCs, while inhibitors of AGTR1, BDKRB2, and KCNK3 were without effect. Earlier studies in the literature have already indicated that inhibitors of metalloproteinases, including Batimastat, have a negative influence on adipogenic differentiation [23], but this is the first report for an inhibitory effect of an aldo-keto reductase inhibitor.Table 1 Selected genes involved in adipogenic differentiation Gene name Protein function Inhibitor Effect ADAMTS5 Metalloproteinase Batimastat Positive AGTR1 Angiotensin II receptor Losartan Negative AKR1B10 Aldo-keto reductase Zopolrestat Positive BDKRB2 Bradykinin receptor B2 Icatibant Negative CXCL12 Chemokine SDF-1 (Not tested) (Not tested) KCNK3 Potassium channel Doxapram Negative PPARG Nuclear receptor GW9662 Positive PRKAR2B cAMP protein kinase (Not tested) (Not tested) VCAM1 Vascular cell adhesion (Not tested) (Not tested) Table presents the HUGO name, function, commercially available drug, and status of experimentally observed effects positive observed effect, negative no observed effect Figure 6a shows the effect of Batimastat on adipogenic and osteogenic differentiation of hMSCs under the experimental conditions used for the microarray analysis. TGFβ and DMSO, as a vehicle for Batimastat, were used as a positive and a negative control. The data show that Batimastat inhibits adipogenic differentiation in a dose-dependent manner but, in contrast to TGFβ, this inhibition does not result in a concomitant enhancement of osteogenic differentiation. A similar observation was made for the AKR1B10 inhibitors Sorbinil (not shown) and Zopolrestat. The quantitative analysis presented in Fig. 6b shows that Zopolrestat actively inhibits adipogenic differentiation of hMSCs in a dose-dependent manner, although to a lesser extent than Batimastat.Fig. 6 Effect of selected inhibitors on adipogenic differentiation of hMSCs. a Effect of Batimastat, added at the indicated concentrations to hMSCs in adipogenic differentiation medium, on adipogenic (upper panel; Oil Red O (ORO) staining, day 9) and osteogenic differentiation (lower panel; alkaline phosphatase (ALP) staining, day 7). No addition (Cont), TGFβ (2 ng/ml), and DMSO (0.1 %; used as a solvent for Batimastat) were used as controls. b Inhibition of adipogenic differentiation by Batimastat (Bat) and Zopolrestat (Zop), added at the indicated micromolar concentrations. Quantitative Oil Red O staining was measured at 530 nm on hMSCs treated for 9 days with adipogenic differentiation medium. TGFβ (5 ng/ml) was used as a control. Significance levels are indicated relative to untreated controls (Cont). *p < 0.05; **p < 0.01; ***p < 0.001. DMSO dimethyl sulfoxide, TGFβ transforming growth factor beta Discussion Osteoporosis is a debilitating disease which affects tens of millions of people worldwide. Postmenopausal women are particularly at risk of developing this disease, since reduced estrogen activity enhances the bone-resorbing activity of osteoclasts. Additionally, aging in general results in a significant reduction in the number and function of bone-forming osteoblasts [24]. Treatment of patients with osteoporosis may include hormone replacement therapies and the use of bisphosphonates to inhibit the activity of osteoclasts. Moreover, vitamin D3 or parathyroid hormone can be prescribed to enhance new bone formation [25]. Recent years have seen an increasing interest in the interaction between fat and bone cells in the bone marrow. Patients suffering from osteoporosis show an increased number of adipocytes in their bone marrow, concomitant with a reduction in the pool of hMSCs that are able to differentiate into osteoblasts [2, 3]. In addition, adipokines secreted by these adipocytes may further enhance osteoclast activity [26], while an increasing fat content of the bone marrow may also impair the bone cell niche required for the functioning of hematopoietic stem cells [27]. These considerations show that there is great need for developing drugs that prevent the differentiation of hMSCs into fat cells and may thereby enhance their differentiation into bone cells. Likewise, drugs that prevent adipogenic differentiation could also be useful in the battle against obesity. In the present study we have shown that, under proper in-vitro conditions, TGFβ is able to stimulate osteogenic differentiation and prevent adipogenic differentiation within the same culture. These culture conditions require not only the presence of DEX and BMP, but also of a cAMP-enhancing stimulus such as IBMX or PGE2. Because of its strong side effects TGFβ is not suited for in-vivo applications, but our results show that the current in-vitro system can be used for identifying genes whose expression is repressed following a TGFβ-induced switch from adipogenic to osteogenic differentiation of hMSCs. By concentrating on those genes for which FDA-approved drugs are available, we have identified nine potential genes that could be tested for inhibition of adipogenic differentiation of hMSCs. Using this approach we have identified the nuclear hormone receptor PPARG, the metalloproteinase ADAMTS5, and the aldo-keto reductase AKR1B10 as potential drug targets for treatment of osteoporosis and obesity. TGFβ is a highly pleiotropic cytokine which plays an important role in many physiological processes, as well as in cancer [28, 29]. Because of its strong inhibitory effect on the immune system, systemic treatment with TGFβ is not considered a realistic option, except for protection against autoimmune diseases [30]. Studies in laboratory animals have shown that TGFβ treatment can result in skin fibrosis and toxicity, without displaying significant antitumor effects [31, 32]. Local injection of TGFβ into the knee joint has been shown to enhance cartilage integrity, leading to prevention of osteoarthritis [33]. Our present study shows that the effect of TGFβ on osteogenic differentiation of hMSCs strongly depends on the culture conditions. In osteogenic differentiation medium TGFβ inhibits bone cell differentiation, while it promotes this process in adipogenic differentiation medium. Since the local conditions in the fatty bone marrow of osteoporosis patients are not well defined, it is difficult to predict whether injection of TGFβ will result in a net enhancement or a decrease of functional osteoblast cells. Furthermore, current clinical trials directed towards TGFβ are aimed at inhibiting its activity in cancer patients, since overactivation of TGFβ-induced pathways have been associated with cancer progression [28, 29]. Among the genes that were downregulated at early time points following TGFβ treatment of hMSCs in adipogenic differentiation medium is PPARG. This observation is not unexpected, since ligand-induced activation of PPARG (e.g., by rosiglitazone) is known to be essential for adipogenic differentiation. We have studied the role of PPARG in this process not by using the PPARG-specific antagonist GW9662 (see Table 1), but by omitting rosiglitazone from the culture medium, which resulted in a complete block of fat cell formation (data not shown). The promoting role of PPARG agonists in obesity is well established, but on the contrary these hormones have been shown to be clinically active as antidiabetic drugs [34]. Because of these multiple faces of PPARG, inhibition of this nuclear hormone receptor does not seem an attractive approach for the prevention of fatty bone marrow formation in osteoporosis patients. The second gene for which inhibitors were found to prevent fat cell differentiation is ADAMTS5, a disintegrin and metalloproteinase with thrombospondin motifs [35]. Its main function is the cleavage of the aggrecan core protein, in which it appears more efficient than other matrix metalloproteinases (MMPs) [36]. Recent studies on Adamts5–/– mice, however, have indicated that ADAMTS5 may not responsible for aggrecan proteolysis, but instead regulates glucose uptake by mediating the endocytotic trafficking of LRP1 and GLUT4 [37]. Other studies have shown that deletion of active ADAMTS5 prevents cartilage degradation in a murine model of osteoarthritis [38]. Batimastat and the related drug Marimastat have primarily been developed as antineoplastic drugs. They prevent angiogenesis by blocking metalloproteinases including MMPs and ADAM family members [39]. Both drugs performed poorly in clinical trials on metastatic breast cancer patients [40] and were therefore never marketed. Previous studies have shown that Batimastat blocks the enzymatic activity of MMP2 and MMP9, and prevents the differentiation of mouse 3T3-F442A preadipocytes into fat cells [23, 41]. Our present results show that Batimastat also prevents adipogenic differentiation of hMSCs. Long-term studies on Batimastat and Marimastat in humans are lacking and therefore it cannot be concluded whether these drugs present a real potential for the treatment of patients with osteoporosis or obesity. MMPs are not only involved in cancer progression, but also play an important role in inflammation and immunity [42]. Multiple natural compounds have been identified which seem to block MMP activity [43]. It will be interesting to test the effects of these compounds, some of which are used as food supplements, in relation to osteoporosis and obesity. In this study we have made the novel observation that inhibitors of aldo-keto reductases prevent adipogenic differentiation of hMSCs. AKR1B10, which was downregulated by TGFβ in our studies, is particularly active on lipid substrates. It plays an important role in the reduction of retinaldehyde to retinol, as well as in the lipid modification of the K-Ras oncogene. In humans, this gene is particularly expressed in the intestine, adrenal gland, and liver. Inhibition of AKR1B10 prevents the outgrowth of pancreatic carcinoma cells by modulating the Ras pathway [44, 45]. Moreover, expression of AKR1B10 is considered to be a tumor marker for NSCLC [46] and liver tumors [47]. To the best of our knowledge, a role of AKR1B10 in adipogenic differentiation has not yet been studied. However, an RNA-mediated knockdown study has indicated that AKR1B10 is an important regulator of fatty acid biosynthesis in human RAO-3 breast cancer cells [48]. AKR1B10 is structurally very similar to AKR1B1, and many inhibitors of AKR1B1 also bind AKR1B10. These include the drugs Sorbinil and Zopolrestat, which have been used in the present study. These and related FDA-approved drugs are used particularly for treatment of patients with diabetic polyneuropathy [49]. They do so by inhibiting the metabolism of glucose by the so-called polyol pathway, which converts glucose into sorbitol. This reduced sugar accumulates in the cell and, as a result of osmotic stress, induces microvascular damage to the retina, kidney, and nerves. Although each of these drugs has its specific adverse effects, including rash, toxicity, and hypersensitivity reactions, at least some of them were well tolerated in clinical trials lasting more than a year [49]. However, no long-term beneficial effects of these drugs were observed in diabetes patients. More recently, AKR1B1 inhibitors have also been tested as anticancer drugs [50]. So far, no reports have been made in the literature on the effects of aldo-keto reductase inhibitors on patients with osteoporosis or obesity. Similar to observations for MMPs, multiple naturally occurring inhibitors for aldo-keto reductases have been identified, particularly from plant tissue [51, 52]. Feeding mice with the most potent of these natural AKR1B inhibitors, bisdemethoxycurcumin, has been shown to reduce particularly the incidence of intestinal cancer. Interestingly, some of these natural compounds inhibit not only AKR1B members but also MMPs. In ongoing research we are testing the effects of these natural compounds on fat cell differentiation. These studies may provide a lead towards the further development of more optimized compounds which specifically prevent adipogenic differentiation in vivo. TGFβ is generally considered to be an inhibitor of bone cell differentiation, but our current results show that in the presence of cAMP-enhancing agents TGFβ is able to promote osteogenic differentiation. PGE2, which has been shown to raise cAMP levels in hMSCs [53], is known to stimulate osteogenesis upon short-term admission in vivo [54], but it is unclear whether PGE2 exerts its action by preventing TGFβ from inhibiting bone formation. Kim et al. [12] have shown that cAMP-activated protein kinases play a central role in the choice between osteogenic and adipogenic differentiation of hMSCs, but again no correlation was made with the activity of TGFβ. Our present data are summarized in Fig. 7, which show that PPARG, the nuclear transcription factor essential for adipogenic commitment, is inhibited by TGFβ, which consequently suppresses the maturation to adiponectin and Oil Red O-positive fat cells. On its own TGFβ suppresses the activity of RUNX2, the nuclear transcription factor essential for osteogenic commitment by a SMAD3/HDAC5-mediated mechanism [20], resulting in impaired maturation to ALP and matrix mineralization-positive bone cells. However, in the presence of IBMX, which strongly represses HDAC5, TGFβ becomes an activator of RUNX2-mediated osteogenesis. Obviously, the TGFβ-mediated inhibition of adipogenesis is not HDAC5 sensitive.Fig. 7 Overview of signaling pathways activated in hMSCs by TGFβ in the absence and presence of IBMX: adipogenic differentiation (left) and osteogenic differentiation (right). For details, see text. BMP bone morphogenetic protein, HDAC histone deacetylate, IBMX 3-isobutyl-1-methylxanthine, TGFβ transforming growth factor beta Using our gene expression microarray analysis we have identified novel inhibitors of adipogenic differentiation. We thereby focused on genes which were differentially expressed on days 1 and 2 following TGFβ treatment. This time frame corresponds with the upregulation of commitment genes for adipogenic differentiation such as PPARG, as shown in Fig. 5. Genes differentially expressed at later time points were particularly involved in fatty acid metabolism (data not shown). Figure 6a shows that under the experimental conditions tested inhibitors of these adipogenic commitment genes did not promote osteogenic differentiation to the same extent as TGFβ. The possibility should therefore be considered that within 24–48 hours the cells have already undergone an irreversible commitment towards either adipogenic or osteogenic differentiation. In that respect it may be interesting to study whether TGFβ added at later time points can still promote cells under adipogenic differentiation conditions to become osteoblasts. Alternatively, the possibility should be considered that under high cAMP conditions TGFβ is able to stimulate specific pathways leading to osteogenic differentiation. Our current results showing that, in the presence of cAMP-enhancing agents, TGFβ is able to prevent the formation of fat cells and promote the formation of bone cells have been obtained on commercially available mesenchymal stem cells from bone marrow of healthy human donors. Given the observation that patients suffering from osteoporosis show an increased number of adipocytes in their bone marrow, it will be interesting to carry out similar experiments with mesenchymal stem cells from such patients. This may indicate if this aberrant pattern of differentiation results from intrinsic changes in their stem cells or from an altered microenvironment in their bone marrow. Conclusions Our data show that in the presence of cAMP-enhancing agents TGFβ stimulates the ability of hMSCs to differentiate into bone cells, while impairing their ability to differentiate into fat cells. Under these conditions TGFβ treatment results in a reduced expression of genes which contribute to adipogenic differentiation, including PPARG, ADAMTS5, and AKR1B10. Since FDA-approved drugs are available for these genes, they are potential targets for treatment of patients suffering from osteoporosis or obesity. Abbreviations ADM, adipogenic differentiation medium; ALP, alkaline phosphatase; BMP, bone morphogenetic protein; DAVID, Database for Annotation, Visualization and Integrated Discovery; DEX, dexamethasone; DMEM, Dulbecco’s modified Eagle’s medium; DMSO, dimethyl sulfoxide; hMSC, human mesenchymal stem cell; IBMX, 3-isobutyl-1-methylxanthine; LIMMA, Linear Models for Microarray Data; MMP, matrix metalloproteinase; ODM, osteogenic differentiation medium; PGE2, prostaglandin E2; PM, proliferation medium; PNPP, p-nitrophenyl phosphate; RMA, robust microarray analysis; TGFβ, transforming growth factor beta. Acknowledgements The authors would like to thank Dr Ester Piek and Ingrid de Grijs for their contributions in the initial phase of the project and Dr W. Olijve for fruitful discussions. The present studies were made possible by a grant from ERASysBio + to the LINCONET consortium (Dutch contribution obtained from ZonMw, grant 90201174). Merck Sharpe & Dohme (Oss, the Netherlands) is acknowledged for financial support in the initial phase of this project. Microarray hybridizations were carried out by the MicroArray Department at the University of Amsterdam. Authors’ contributions EJvZ was responsible for the overall design of the study and drafted the final manuscript. ID was responsible for drafting the manuscript with respect to the microarray data and for a critical evaluation of the manuscript. JMH carried out the cell biological assays and was involved in drafting the experimental part of the manuscript. SPvdW was responsible for the design of the cell biological experiments, drafted the cell biological part of the manuscript, and made critical revisions to the final draft. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. ==== Refs References 1. Pino AM Rosen CJ Rodriguez JP In osteoporosis, differentiation of mesenchymal stem cells (MSCs) improves bone marrow adipogenesis Biol Res 2012 45 3 279 87 10.4067/S0716-97602012000300009 23283437 2. Justesen J Adipocyte tissue volume in bone marrow is increased with aging and in patients with osteoporosis Biogerontology 2001 2 3 165 71 10.1023/A:1011513223894 11708718 3. Rosen CJ Marrow fat and the bone microenvironment: developmental, functional, and pathological implications Crit Rev Eukaryot Gene Expr 2009 19 2 109 24 10.1615/CritRevEukarGeneExpr.v19.i2.20 19392647 4. Moerman EJ Aging activates adipogenic and suppresses osteogenic programs in mesenchymal marrow stroma/stem cells: the role of PPAR-gamma2 transcription factor and TGF-beta/BMP signaling pathways Aging Cell 2004 3 6 379 89 10.1111/j.1474-9728.2004.00127.x 15569355 5. Ito H Clinical considerations of regenerative medicine in osteoporosis Curr Osteoporos Rep 2014 12 2 230 4 10.1007/s11914-014-0201-8 24619559 6. Reid IR Short-term and long-term effects of osteoporosis therapies Nat Rev Endocrinol 2015 11 7 418 28 10.1038/nrendo.2015.71 25963272 7. Sotoca AM Weber M Zoelen EJJ Daskalaki A Gene expression regulation underlying osteo-, adipo-, and chondro-genic lineage commitment of human mesenchymal stem cells Medical Advancements in Aging and Regenerative Technologies: Clinical Tools and Applications 2013 Hershey IGI Global 76 94 8. Muruganandan S Roman AA Sinal CJ Adipocyte differentiation of bone marrow-derived mesenchymal stem cells: cross talk with the osteoblastogenic program Cell Mol Life Sci 2009 66 2 236 53 10.1007/s00018-008-8429-z 18854943 9. Bennett CN Regulation of osteoblastogenesis and bone mass by Wnt10b Proc Natl Acad Sci U S A 2005 102 9 3324 9 10.1073/pnas.0408742102 15728361 10. Roelen BA Dijke P Controlling mesenchymal stem cell differentiation by TGFBeta family members J Orthop Sci 2003 8 5 740 8 10.1007/s00776-003-0702-2 14557946 11. Rosen ED MacDougald OA Adipocyte differentiation from the inside out Nat Rev Mol Cell Biol 2006 7 12 885 96 10.1038/nrm2066 17139329 12. Kim EK Human mesenchymal stem cell differentiation to the osteogenic or adipogenic lineage is regulated by AMP-activated protein kinase J Cell Physiol 2012 227 4 1680 7 10.1002/jcp.22892 21678424 13. Piek E Osteo-transcriptomics of human mesenchymal stem cells: accelerated gene expression and osteoblast differentiation induced by vitamin D reveals c-MYC as an enhancer of BMP2-induced osteogenesis Bone 2010 46 3 613 27 10.1016/j.bone.2009.10.024 19857615 14. Eijssen LM User-friendly solutions for microarray quality control and pre-processing on ArrayAnalysis.org Nucleic Acids Res 2013 41 Web Server issue W71 6 10.1093/nar/gkt293 23620278 15. Irizarry RA Exploration, normalization, and summaries of high density oligonucleotide array probe level data Biostatistics 2003 4 2 249 64 10.1093/biostatistics/4.2.249 12925520 16. Smyth GK Linear models and empirical bayes methods for assessing differential expression in microarray experiments Stat Appl Genet Mol Biol 2004 3 Article3 16646809 17. da Huang W Sherman BT Lempicki RA Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources Nat Protoc 2009 4 1 44 57 10.1038/nprot.2008.211 19131956 18. da Huang W Sherman BT Lempicki RA Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists Nucleic Acids Res 2009 37 1 1 13 10.1093/nar/gkn923 19033363 19. Wishart DS DrugBank: a comprehensive resource for in silico drug discovery and exploration Nucleic Acids Res 2006 34 Database issue D668 72 10.1093/nar/gkj067 16381955 20. Kang JS Repression of Runx2 function by TGF-beta through recruitment of class II histone deacetylases by Smad3 Embo J 2005 24 14 2543 55 10.1038/sj.emboj.7600729 15990875 21. Maroni P Chemical and genetic blockade of HDACs enhances osteogenic differentiation of human adipose tissue-derived stem cells by oppositely affecting osteogenic and adipogenic transcription factors Biochem Biophys Res Commun 2012 428 2 271 7 10.1016/j.bbrc.2012.10.044 23085045 22. Zhou Y Peng J Jiang S Role of histone acetyltransferases and histone deacetylases in adipocyte differentiation and adipogenesis Eur J Cell Biol 2014 93 4 170 7 10.1016/j.ejcb.2014.03.001 24810880 23. Bouloumie A Adipocyte produces matrix metalloproteinases 2 and 9: involvement in adipose differentiation Diabetes 2001 50 9 2080 6 10.2337/diabetes.50.9.2080 11522674 24. Bermeo S Gunaratnam K Duque G Fat and bone interactions Curr Osteoporos Rep 2014 12 2 235 42 10.1007/s11914-014-0199-y 24599601 25. Komm BS The safety and tolerability profile of therapies for the prevention and treatment of osteoporosis in postmenopausal women Expert Rev Clin Pharmacol 2015 8 6 769 84 10.1586/17512433.2015.1099432 26482902 26. Devlin MJ Rosen CJ The bone-fat interface: basic and clinical implications of marrow adiposity Lancet Diabetes Endocrinol 2015 3 2 141 7 10.1016/S2213-8587(14)70007-5 24731667 27. Tuljapurkar SR Changes in human bone marrow fat content associated with changes in hematopoietic stem cell numbers and cytokine levels with aging J Anat 2011 219 5 574 81 10.1111/j.1469-7580.2011.01423.x 21923862 28. Wrzesinski SH Wan YY Flavell RA Transforming growth factor-beta and the immune response: implications for anticancer therapy Clin Cancer Res 2007 13 18 Pt 1 5262 70 10.1158/1078-0432.CCR-07-1157 17875754 29. Neuzillet C Targeting the TGFbeta pathway for cancer therapy Pharmacol Ther. 2015 147 22 31 10.1016/j.pharmthera.2014.11.001 25444759 30. Santambrogio L Studies on the mechanisms by which transforming growth factor-beta (TGF-beta) protects against allergic encephalomyelitis. Antagonism between TGF-beta and tumor necrosis factor J Immunol 1993 151 2 1116 27 8335893 31. Mori T Role and interaction of connective tissue growth factor with transforming growth factor-beta in persistent fibrosis: a mouse fibrosis model J Cell Physiol 1999 181 1 153 9 10.1002/(SICI)1097-4652(199910)181:1<153::AID-JCP16>3.0.CO;2-K 10457363 32. Robinson SP Rose WC Transforming growth factor beta 1: lack of in vivo antitumor activity on A549 and Wehi 3BD+ tumors Anticancer Res 1992 12 1 73 9 1567184 33. Blaney Davidson EN van der Kraan PM van den Berg WB TGF-beta and osteoarthritis Osteoarthritis Cartilage 2007 15 6 597 604 10.1016/j.joca.2007.02.005 17391995 34. Lehrke M Lazar MA The many faces of PPARgamma Cell 2005 123 6 993 9 10.1016/j.cell.2005.11.026 16360030 35. Seals DF Courtneidge SA The ADAMs family of metalloproteases: multidomain proteins with multiple functions Genes Dev 2003 17 1 7 30 10.1101/gad.1039703 12514095 36. Durigova M MMPs are less efficient than ADAMTS5 in cleaving aggrecan core protein Matrix Biol 2011 30 2 145 53 10.1016/j.matbio.2010.10.007 21055468 37. Gorski DJ Deletion of ADAMTS5 does not affect aggrecan or versican degradation but promotes glucose uptake and proteoglycan synthesis in murine adipose derived stromal cells Matrix Biol. 2015 47 66 84 10.1016/j.matbio.2015.03.008 25840345 38. Glasson SS Deletion of active ADAMTS5 prevents cartilage degradation in a murine model of osteoarthritis Nature 2005 434 7033 644 8 10.1038/nature03369 15800624 39. Rothenberg ML Nelson AR Hande KR New drugs on the horizon: matrix metalloproteinase inhibitors Stem Cells 1999 17 4 237 40 10.1002/stem.170237 10437989 40. Sparano JA Randomized phase III trial of marimastat versus placebo in patients with metastatic breast cancer who have responding or stable disease after first-line chemotherapy: Eastern Cooperative Oncology Group trial E2196 J Clin Oncol 2004 22 23 4683 90 10.1200/JCO.2004.08.054 15570070 41. Bourlier V Protease inhibitor treatments reveal specific involvement of matrix metalloproteinase-9 in human adipocyte differentiation J Pharmacol Exp Ther 2005 312 3 1272 9 10.1124/jpet.104.077263 15537822 42. Khokha R Murthy A Weiss A Metalloproteinases and their natural inhibitors in inflammation and immunity Nat Rev Immunol 2013 13 9 649 65 10.1038/nri3499 23969736 43. Mannello F Natural bio-drugs as matrix metalloproteinase inhibitors: new perspectives on the horizon? Recent Pat Anticancer Drug Discov 2006 1 1 91 103 10.2174/157489206775246421 18221029 44. Penning TM The aldo-keto reductases (AKRs): overview Chem Biol Interact. 2015 234 236 46 10.1016/j.cbi.2014.09.024 25304492 45. Zhang W Knockdown or inhibition of aldo-keto reductase 1B10 inhibits pancreatic carcinoma growth via modulating Kras-E-cadherin pathway Cancer Lett 2014 355 2 273 80 10.1016/j.canlet.2014.09.031 25304374 46. Fukumoto S Overexpression of the aldo-keto reductase family protein AKR1B10 is highly correlated with smokers’ non-small cell lung carcinomas Clin Cancer Res 2005 11 5 1776 85 10.1158/1078-0432.CCR-04-1238 15755999 47. Liu Z Epidermal growth factor induces tumour marker AKR1B10 expression through activator protein-1 signalling in hepatocellular carcinoma cells Biochem J 2012 442 2 273 82 10.1042/BJ20111322 22329800 48. Ma J Aldo-keto reductase family 1 B10 affects fatty acid synthesis by regulating the stability of acetyl-CoA carboxylase-alpha in breast cancer cells J Biol Chem 2008 283 6 3418 23 10.1074/jbc.M707650200 18056116 49. Chalk C Benstead TJ Moore F Aldose reductase inhibitors for the treatment of diabetic polyneuropathy Cochrane Database Syst Rev 2007 4 Cd004572 17943821 50. Liu J Wen G Cao D Aldo-keto reductase family 1 member B1 inhibitors: old drugs with new perspectives Recent Pat Anticancer Drug Discov 2009 4 3 246 53 10.2174/157489209789206931 19522700 51. Matsunaga T Potent and selective inhibition of the tumor marker AKR1B10 by bisdemethoxycurcumin: probing the active site of the enzyme with molecular modeling and site-directed mutagenesis Biochem Biophys Res Commun 2009 389 1 128 32 10.1016/j.bbrc.2009.08.107 19706287 52. Endo S Selective inhibition of the tumor marker AKR1B10 by antiinflammatory N-phenylanthranilic acids and glycyrrhetic acid Biol Pharm Bull 2010 33 5 886 90 10.1248/bpb.33.886 20460771 53. Kleiveland CR Kassem M Lea T Human mesenchymal stem cell proliferation is regulated by PGE2 through differential activation of cAMP-dependent protein kinase isoforms Exp Cell Res 2008 314 8 1831 8 10.1016/j.yexcr.2008.02.004 18395713 54. Tian XY Continuous PGE2 leads to net bone loss while intermittent PGE2 leads to net bone gain in lumbar vertebral bodies of adult female rats Bone 2008 42 5 914 20 10.1016/j.bone.2007.12.228 18316259

PMC005xxxxxx/PMC5000486.txt

==== Front Cardiovasc DiabetolCardiovasc DiabetolCardiovascular Diabetology1475-2840BioMed Central London 44310.1186/s12933-016-0443-0Original InvestigationTNF-α induces vascular insulin resistance via positive modulation of PTEN and decreased Akt/eNOS/NO signaling in high fat diet-fed mice da Costa Rafael Menezes +55-16-33153181rafael.menezess@yahoo.com.br 1Neves Karla Bianca karlabneves@hotmail.com 1Mestriner Fabíola Leslie famestri@usp.br 1Louzada-Junior Paulo plouzada@fmrp.usp.br 2Bruder-Nascimento Thiago bruderthiago@yahoo.com.br 1Tostes Rita C. rtostes@usp.br 11 Department of Pharmacology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, SP Brazil 2 Division of Clinical Immunology, Department of Clinical Medicine, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, SP Brazil 25 8 2016 25 8 2016 2016 15 1 11914 6 2016 18 8 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background High fat diet (HFD) induces insulin resistance in various tissues, including the vasculature. HFD also increases plasma levels of TNF-α, a cytokine that contributes to insulin resistance and vascular dysfunction. Considering that the enzyme phosphatase and tension homologue (PTEN), whose expression is increased by TNF-α, reduces Akt signaling and, consequently, nitric oxide (NO) production, we hypothesized that PTEN contributes to TNF-α-mediated vascular resistance to insulin induced by HFD. Mechanisms underlying PTEN effects were determined. Methods Mesenteric vascular beds were isolated from C57Bl/6J and TNF-α KO mice submitted to control or HFD diet for 18 weeks to assess molecular mechanisms by which TNF-α and PTEN contribute to vascular dysfunction. Results Vasodilation in response to insulin was decreased in HFD-fed mice and in ex vivo control arteries incubated with TNF-α. TNF-α receptors deficiency and TNF-α blockade with infliximab abolished the effects of HFD and TNF-α on insulin-induced vasodilation. PTEN vascular expression (total and phosphorylated isoforms) was increased in HFD-fed mice. Treatment with a PTEN inhibitor improved insulin-induced vasodilation in HFD-fed mice. TNF-α receptor deletion restored PTEN expression/activity and Akt/eNOS/NO signaling in HFD-fed mice. Conclusion TNF-α induces vascular insulin resistance by mechanisms that involve positive modulation of PTEN and inhibition of Akt/eNOS/NO signaling. Our findings highlight TNF-α and PTEN as potential targets to limit insulin resistance and vascular complications associated with obesity-related conditions. Keywords High fat dietInsulinTNF-αPTENVascular functionhttp://dx.doi.org/10.13039/501100001807Fundação de Amparo à Pesquisa do Estado de São Paulo2013/08216-2 - CRIDTostes Rita C. http://dx.doi.org/10.13039/501100002322Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorhttp://dx.doi.org/10.13039/501100003593Conselho Nacional de Desenvolvimento Científico e Tecnológicoissue-copyright-statement© The Author(s) 2016 ==== Body Background Obesity is an important cause of morbidity and mortality worldwide [1, 2]. Overweight and obesity trigger metabolic abnormalities such as dyslipidemia, insulin resistance and vascular dysfunction, which contribute to the development of type 2 diabetes and cardiovascular diseases [3]. Insulin plays an important role on vascular tone control [4–6]. Insulin binding to the insulin receptor (IR) activates the phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway, resulting in endothelial nitric oxide synthase (eNOS) activation, nitric oxide (NO) release and vasodilation [7, 8]. Vascular insulin resistance is considered a primary defect in vascular dysfunction [9], and inflammatory mediators are potential contributors to insulin resistance [10]. Obesity is often associated with resistance to vascular actions of insulin [11]. Obesity is also tightly related to high levels of inflammatory mediators, including the cytokine tumor necrosis factor-alpha (TNF-α) [12]. TNF-α content is increased in murine adipose tissue, and increased circulating TNF-α levels are reported in obese humans and experimental animal models of obesity [13]. It is well established that TNF-α induces insulin resistance [14, 15]. In the vasculature TNF-α reduces IRS-1 phosphorylation and decreases NO release by the PI3K/Akt/eNOS pathway [16]. Moreover, blockade of TNF-α in obese rats increases vascular sensitivity to insulin and mice lacking TNF-α receptors remain insulin sensitive when submitted to high-fat diet (HFD) [17]. Although various studies demonstrated a crosstalk between TNF-α and insulin resistance, the mechanisms involved remain to be elucidated. Preliminary evidence indicates that increased levels of the enzyme phosphatase and tensin homologue (PTEN), widely implicated as a negative regulator of insulin/Akt signaling [18], negatively affect insulin sensitivity [19]. A recent study showed that PTEN haploinsufficiency is a monogenic cause of profound constitutive insulin sensitization. Moreover, PTEN mutations increase risks of obesity and cancer but decreases risk of type 2 diabetes [20], showing that in fact proteins related to metabolism and cell growth are closely associated with the development of metabolic diseases. TNF-α is closely linked to PTEN regulation [21]. In human leukemic cells TNF-α increases PTEN protein expression via various nuclear transcription factors [22]. In addition, TNF-α increases PTEN phosphorylation in C2C12 cells, a mouse myoblast cell line, leading to insulin resistance [23]. Selective PTEN deletion in skeletal muscle protects against the development of fat- and age-dependent insulin resistance [24]. However, it is not known whether a similar mechanism takes place in the vasculature or whether such mechanism contributes to insulin resistance associated with HFD/obesity. Therefore, the present study tested the hypothesis that HFD induces vascular insulin resistance via increased PTEN activity and impaired Akt/eNOS signaling. In addition, we investigated whether TNF-α triggers PTEN-mediated vascular insulin resistance in HFD-fed animals. Methods Animals and diets All experimental protocols were performed in accordance with the Ethical Principles in Animal Experimentation approved by the Brazilian College of Animal Experimentation (COBEA) and were approved by the Ethics Committee on Animal Use (CEUA) of the University of Sao Paulo, Ribeirao Preto Campus, Brazil (Protocol no 149/2014). Five week-old male C57Bl/6J and TNF-α receptor-deficient mice (TNF-α KO) were obtained from the Laboratory of Molecular Immunology and Embryology, Transgenose Institute, Centre National de la Recherche Scientifique (CNRS), Orléans, France and maintained in the Animal Facility of the University of Sao Paulo, Ribeirao Preto, Brazil on 12-h light/dark cycles under controlled temperature (22 ± 1 °C) with ad libitum access to food and water. After a one-week acclimatization period, mice were divided into 2 groups: (1) mice maintained in control diet (protein 22 %, carbohydrate 70 % and fat 8 % of energy, PragSolucoes); (2) mice receiving HFD (protein 10 %, carbohydrate 25 % and fat 65 % of energy, PragSolucoes) for 18 weeks. After the treatment period, mice were killed by carbon dioxide (CO2) inhalation. Nutritional and metabolic profile of high fat diet-induced obese mice Nutritional profile was weekly determined by analyzing the caloric intake, feed efficiency, body weight and body fat. Caloric intake (per mouse) was calculated by the weekly food intake multiplied by the dietary energetic value. Feeding efficiency, defined by the ability to transform consumed calories into body weight, was determined with the formula: mean body weight gain (g)/total calorie intake. Animal body weight was measured weekly and obesity was defined using the adiposity index ([body fat (g)/final body weight (g)] × 100). Body fat was calculated by summing the epididymal, retroperitoneal and visceral fat [25]. After 18 weeks of HFD, glucose concentrations were determined in serum samples from mice fasted for 12 h, using an enzymatic colorimetric glucose oxidase method (Doles®). Plasma insulin concentration (ng/mL) was determined by radioimmunoassay (Insulin Kit®). Insulin sensitivity was calculated using the HOMA-IR index (Homeostasis Model Assessment) [26], which takes into account insulin and fasting blood glucose levels, using the following mathematical formula: HOMA-IR = fasting insulin × fasting glucose/22.5. Oral glucose tolerance test The oral glucose tolerance test (OGTT) was performed to evaluate glucose tolerance. Mice were deprived of food for 6 h. Blood was sampled from the caudal vein immediately before (baseline, t0) and after (t15, t30, t60, t90, t120 min) administration of 2 g of glucose/kg by oral gavage. Glucose levels were determined using a glucose analyzer (Accu-Check, Roche Diagnostics). Assessment of vascular function Mesenteric vascular beds were isolated from C57Bl/6J and TNF-α KO mice fed with control diet or HFD. Second-order branches of the superior mesenteric artery were dissected and mounted on a wire myograph (DMT, Danish Myo Technology, Aarhus, Denmark). Vessel segments (2 mm in length) were mounted on 25 µm wires in a vessel bath chamber for isometric tension recording and equilibrated for 30 min in Krebs-Henseleit-modified physiological salt solution (120 mM NaCl, 25 mM NaHCO3, 4.7 mM KCl, 1.18 mM KH2PO4, 1.18 mM MgSO4, 2.5 mM CaCl2, 0.026 mM EDTA, and 5.5 mM glucose), at 37 °C, continuously bubbled with 95 % O2 and 5 % CO2, pH 7.4. At the beginning of each experiment, arteries were contracted with KCl 120 mM to test for functional integrity. Endothelial function was assessed by testing the relaxant effect of acetylcholine (ACh, 2 µM) on vessels contracted with phenylephrine (PE, 2 µM). Rings exhibiting a vasodilator response to ACh greater than 80 % were considered endothelium-intact vessels. Concentration–response curves to Insulin (10−10–10−5 M) were performed in endothelium-intact arteries to assess insulin-dependent relaxation. In some protocols, arteries were pre-incubated with a vanadium complex that acts as a highly potent and specific phosphorylation inhibitor of PTEN [27] (VO-OHpic, 10−4 M), TNF-α (5 ng/mL), TNF-α inhibitor (Infliximab, 10−6 M), Akt activator (YS-49, 10−6 M) or eNOS inhibitor (L-NAME, 10−5 M), 60 min prior to the concentration–response curves. Nitric oxide metabolites levels The mesenteric bed, free from adipose tissue, was immediately frozen in liquid nitrogen, pulverized and homogenized in 20 mM Tris–HCl (pH 7.4). The samples were centrifuged (5000×g, 10 min, 4 °C) and the total protein content was quantified using the Bradford method (Bio-Rad) [28]. The samples were analyzed in duplicate for nitrite and nitrate (NOx) using chemiluminescence-based assay ozone. Briefly, mesenteric bed samples were treated with cold ethanol (1:2 mesenteric bed to ethanol, for 30 min at −20 °C) and centrifuged (4000×g, 10 min). NOx levels were measured by injecting 25 μL of supernatant in a container vent glass containing 0.8 % of Vanadium (III) in HCl (1 N) at 90 °C, which reduces NOx into NO gas. A stream of nitrogen was bubbled through the purge vessel containing vanadium (III) with sodium hydroxide [NaOH (1 N)], and then through an analyzer (Sievers Nitric Oxide Analyzer® 280, GE Analytical Instruments, Boulder, CO, USA). Fluorescence detection of nitric oxide production NO production was determined by the fluorescent NO indicator, 5,6 Diaminofluorescein diacetate (DAF-2 DA). Mesenteric arteries were embedded in Tissue Tek® O.C.T. Compound (Sakura Finetek, Torrance, CA, USA). Unfixed frozen cross Sects. (5 μm) were incubated with DAF-2 DA (12.5 μM; Sigma) diluted in phosphate buffer with CaCl2 (0.4 mM) and insulin (2 µM); in a light protected and humidified chamber at 37 °C for 1 h. Fluorescence was detected with a 490–515 nm long-pass filter, under a microscope (Olympus, BX50) with a 100× objective lens coupled to a digital camera. Fluorescent images were analyzed by measuring the mean optical density of the fluorescence in a computer system (Image J software) and normalized by the area. Western Blot analysis Mesenteric vascular beds were frozen in liquid nitrogen and homogenized in a buffer (50 mM Tris/HCl, 150 mM NaCl, 1 % Nonidet P40, 1 mM EDTA, 1 μg/ml leupeptin, 1 μg/ml pepstatin, 1 μg/ml aprotinin, 1 mM sodium orthovanadate, 1 mM PMSF and 1 mM sodium fluoride). Proteins were extracted (60 μg) and separated by electrophoresis on 10 % polyacrylamide gel, and transferred on to nitrocellulose membranes. Non-specific binding sites were blocked with 5 % BSA in TBS containing 0.1 % Tween 20 (for 1 h at 24 °C). Membranes were incubated with antibodies (at the indicated dilutions) overnight at 4 °C. Antibodies were used as follows: Phospho-Akt(Ser473) (1:1000 dilution; Cell Signaling Technology), Phospho-eNOS(Ser1177) (1:500 dilution; Cell Signaling Technology), Phospho-eNOS(Thr495) (1:500 dilution; Cell Signaling Technology), PTEN (1:500 dilution; Cell Signaling Technology), Phospho-PTEN (1:500 dilution; Cell Signaling Technology) and anti-β-actin (1:3000 dilution; Abcam). After incubation with secondary antibodies, signals were obtained by chemiluminescence, visualized by autoradiography and quantified densitometrically. Plasma TNF-α level Plasma TNF-α concentration was measured with mTNF-alpha DuoSet ELISA assay kit (DY410-R&D Systems, USA). Compounds Phenylephrine, acetylcholine, L-NAME, VO-OHpic and YS-49 were purchased from Sigma Chemical Co (St. Louis, MO, USA). Insulin (Insunorm®) was purchased from Aspen Pharma. Infliximab (Remicade®) was purchased from Janssen Biologics. Data and statistical analyses Relaxation responses to Insulin are expressed as a percentage of contraction in response to PE. The individual concentration–response curves were fitted into a curve by non-linear regression analysis. pD2 (defined as the negative logarithm of the EC50 values) and maximal response (Emax) values were compared by Two-way analysis of variance (ANOVA) followed by the Bonferroni post hoc test. The Prism software, version 5.0 (GraphPad Software Inc., San. Diego, CA, USA) was used to analyze these parameters as well as to fit the sigmoidal curves. Data are presented as mean ± SEM. N represents the number of animals used p values less than 0.05 were considered significant. Results Metabolic parameters in C57Bl/6J and TNF-α KO mice fed with control and high-fat diets After 18 weeks on the HFD there was a marked increase in all nutritional and anthropometric parameters both in C57Bl/6J mice and in TNF-α KO mice (Table 1) compared with animals on the control diet. No difference in glucose tolerance, determined by the OGTT, was observed between C57Bl/6J mice and TNF-α KO mice fed with control diet. HFD decreased glucose tolerance in C57Bl/6J, whereas TNF-α deletion partially protected from HFD-induced glucose intolerance (Fig. 1a, b). In addition, insulin plasma levels and HOMA-IR index were increased in HFD-fed C57Bl/6J mice compared with their control mice. TNF-α deficiency partially prevented the increase in insulin plasma levels and HOMA-IR index (Fig. 1c, d).Table 1 Characteristics of C57Bl/6J and TNF-α receptors deficient mice fed with control and high fat diets Control diet Control diet High fat diet High fat diet C57Bl/6J TNF-α KO C57Bl/6J TNF-α KO Initial body mass (g) 20.9 ± 0.5 20.6 ± 0.3 21.7 ± 0.4 21.2 ± 0.4 Final body mass (g) 28.8 ± 0.6 26.6 ± 0.6 42.5 ± 0.8* 40.9 ± 0.9* Caloric intake (kcal/week) 74.8 ± 0.5 74.2 ± 0.5 91.4 ± 1.0* 94.8 ± 0.8* Weight gain (g) 7.9 ± 0.4 5.9 ± 0.3 20.8 ± 0.9* 18.8 ± 1.1* Feed efficiency (g/kcal) ×100 0.3 ± 0.04 0.2 ± 0.04 0.8 ± 0.08* 0.8 ± 0.03* Epididymal fat (g) 0.50 ± 0.02 0.47 ± 0.03 4.41 ± 0.07* 4.13 ± 0.07* Visceral fat (g) 0.15 ± 0.02 0.12 ± 0.02 2.85 ± 0.03* 2.77 ± 0.04* Retroperitoneal fat (g) 0.14 ± 0.07 0.15 ± 0.03 2.99 ± 0.03* 1.78 ± 0.04* Total fat (g) 0.79 ± 0.05 0.77 ± 0.09 10.25 ± 0.11* 8.72 ± 0.21* Adiposity index (%) 2.24 ± 0.1 1.77 ± 0.2 13.27 ± 0.6* 12.25 ± 0.7* Glycemia (mg/dL) 100.1 ± 2.4 96.8 ± 3.1 192.9 ± 3.7* 188.7 ± 1.3* Results are expressed as mean ± SEM. * p < 0.05 vs. respective control. n = 8–10 in each experimental group Fig. 1 TNF-α contributes to glucose intolerance and increased insulin levels in HFD-fed mice. OGTT was performed in C57Bl/6J and TNF-α KO mice fed with control or HFD diets (for 18 weeks). After a 6 h-fasting period, baseline blood glucose was measured. Mice received 2 mg/kg glucose by gavage and blood samples were collected at 30, 60, 90 and 120 min after the challenge (a). Area under the curve (AUC) in the plot of blood glucose concentration against time (b). Insulin plasma levels (c). HOMA-IR index (d). Results represent the mean ± S.E.M. n = 7–8 in each experimental group. *p < 0.05 vs. C57Bl/6J Control, #p < 0.05 vs. C57Bl/6J HFD TNF-α reduces vascular relaxation As shown in Fig. 2a HFD-fed C57Bl/6J mice exhibited a 6.5-fold increase in plasma TNF-α levels compared with control mice. Figure 2b–d and Table 2 show that TNF-α contributes to reduced acetylcholine and insulin-induced vasodilation in HFD-fed mice. No difference was observed in vasodilation between C57Bl/6J and TNF-α KO mice fed with control diet. HFD reduced acetylcholine and insulin-induced vascular relaxation in C57Bl/6J mice. However, TNF-α deletion prevented HFD-induced vascular dysfunction (Fig. 2b, c). Endothelium removal abolished insulin-induced vasodilation in all groups. In addition, no significant differences were observed in relaxation mediated by sodium nitroprusside between wild-type and TNF-α KO mice or between control and HFD mice (not shown).Fig. 2 TNF-α decreases vascular relaxation in HFD-fed mice. Plasma TNF-α levels (a). Concentration-effect curves to acetylcholine and insulin were performed in endothelium-intact mesenteric resistance arteries of C57Bl/6J and TNF-α KO mice fed with control or HFD diets (b, c). The role of TNF-α on the vasculature was investigated using infliximab in vessels of C57Bl/6J fed with control or HFD diet (d). Results represent the mean ± S.E.M. n = 5–6 in each experimental group. *p < 0.05 vs. C57Bl/6J Control; #p < 0.05 vs. C57Bl/6J HFD Table 2 pD2 and Emax (%) values of acetylcholine and insulin-induced relaxation in mesenteric arteries of control or HFD-fed mice incubated with vehicle or infliximab Groups pD2 Emax Control HFD Control HFD C57Bl/6J (acetylcholine) 7.29 ± 0.06 (n = 6) 6.80 ± 0.04 (n = 6)* 92.8 ± 1.9 (n = 6) 59.9 ± 1.8 (n = 6)* TNF-α−/− (acetylcholine) 7.16 ± 0.02 (n = 6) 6.94 ± 0.04 (n = 6)# 94.4 ± 2.1 (n = 6) 87.8 ± 1.3 (n = 6)# C57Bl/6J (insulin) 7.01 ± 0.15 (n = 5) 6.02 ± 0.18 (n = 6)* 80.8 ± 2.7 (n = 5) 52.8 ± 6.8 (n = 5)* TNF-α−/− (insulin) 6.84 ± 0.51 (n = 5) 6.91 ± 0.20 (n = 6)# 84.4 ± 2.1 (n = 5) 86.7 ± 2.9 (n = 5)# C57Bl/6J_Infliximab 7.03 ± 0.14 (n = 5) 6.69 ± 0.21 (n = 6)# 85.0 ± 1.8 (n = 5) 63.7 ± 2.2 (n = 5)* Data represent the mean ± SEM of n experiments. Two-way ANOVA with Bonferroni post-test. * p < 0.05 vs. C57Bl/6J Control; # p < 0.05 vs. C57Bl/6J HFD To assess direct effects of TNF-α in the vasculature, vessels were incubated with infliximab, a chimeric monoclonal antibody against TNF-α. Infliximab did not affect insulin-induced vascular relaxation in C57Bl/6J mice fed with the control diet. However, infliximab augmented insulin vasodilation in HFD-fed C57Bl/6J mice (Fig. 2d). TNF-α and PTEN-dependent mechanisms contribute to vascular insulin resistance in HFD-fed mice Figure 3a, b illustrates total and phosphorylated levels of PTEN in the mesenteric bed of the experimental groups. HFD treatment increased vascular PTEN protein expression, as well as PTEN phosphorylation levels in C57Bl/6J mice, effects not seen in vessels from TNF-α KO mice. To assess whether PTEN is involved in HFD-induced vascular insulin resistance, mesenteric vessels from C57Bl/6J mice, fed with control or HFD, were incubated with a PTEN inhibitor (VO-OHpic) (Fig. 3c; Table 3). The PTEN inhibitor did not affect relaxation in arteries from control mice. However, VO-OHpic completely prevented vascular insulin resistance in vessels from HFD-fed C57Bl/6J mice. In addition, control vessels incubated with recombinant TNF-α exhibited decreased insulin-induced relaxation. Concomitant incubation of vessels with TNF-α and the PTEN inhibitor prevented the effects of TNF-α on insulin vasodilation (Fig. 3d; Table 4). In this context, TNF-α increased PTEN phosphorylation, which was reversed in the presence of PTEN inhibitor (Fig. 3e).Fig. 3 Vascular PTEN protein phosphorylation modulates insulin-induced relaxation in HFD-fed mice. Western blot quantification of total (a) and phosphorylated (b) PTEN expression levels in mesenteric arteries. Concentration-effect curves to insulin were performed in endothelium-intact resistance mesenteric arteries. The role of PTEN in the vasculature was investigated using VO-OHpic in vessels of C57Bl/6J mice fed with control and HFD diets (c) and vessels of C57Bl/6J incubated with TNF-α (d). Western blot quantification of phosphorylated PTEN expression levels in mesenteric arteries (e). Results represent the mean ± S.E.M. n = 5–6 in each experimental group. *p < 0.05 vs. C57Bl/6J Control; #p < 0.05 vs. C57Bl/6J HFD; &p < 0.05 vs. C57Bl/6J Control_TNF-α Table 3 pD2 and Emax (%) values of insulin-induced relaxation in mesenteric arteries of control or HFD-fed mice incubated with vehicle, VO-OHpic or TNF-α Groups pD2 Emax Control HFD Control HFD C57Bl/6J 7.01 ± 0.15 (n = 5) 6.02 ± 0.18 (n = 6)* 80.8 ± 2.7 (n = 5) 52.8 ± 6.8 (n = 5)* C57Bl/6J_VO-OHpic 6.93 ± 0.22 (n = 5) 6.87 ± 0.11 (n = 7)# 86.9 ± 1.9 (n = 5) 78.0 ± 4.1 (n = 5)# C57Bl/6J_TNF-α 6.30 ± 0.14 (n = 6)* – 49.4 ± 2.7 (n = 6) – C57Bl/6J_TNF-α + VO-OHpic 7.29 ± 0.13 (n = 6)& – 63.5 ± 1.6 (n = 6)*& – Data represent the mean ± SEM of n experiments. Two-way ANOVA with Bonferroni post-test. * p < 0.05 vs. C57Bl/6J Control; # p < 0.05 vs. C57Bl/6J HFD; & p < 0.05 vs. C57Bl/6J_TNFα Table 4 pD2 and Emax (%) values of insulin-induced relaxation in mesenteric arteries of control or HFD-fed mice incubated with vehicle, VO-OHpic, TNF-α or L-NAME Groups pD2 Emax Control HFD Control HFD C57Bl/6J 7.01 ± 0.15 (n = 5) 6.02 ± 0.18 (n = 6)* 80.8 ± 2.7 (n = 5) 52.8 ± 6.8 (n = 5)* C57Bl/6J_YS-49 6.99 ± 0.19 (n = 5) 7.12 ± 0.10 (n = 6)# 91.8 ± 1.3 (n = 5)* 83.7 ± 2.0 (n = 5)# C57Bl/6J_L-NAME 6.30 ± 0.14 (n = 6)* – 47.4 ± 4.7 (n = 6)* – C57Bl/6J_TNF-α + VO-OHpic 7.29 ± 0.13 (n = 6) – 63.5 ± 1.6 (n = 6) – C57Bl/6J_TNF-α + VO-OHpic + L-NAME 6.49 ± 0.23 (n = 6)& – 33.5 ± 5.6 (n = 6)& – Date represent the mean ± SEM of n experiments. Two-way ANOVA with Bonferroni post-test. * p < 0.05 vs. C57Bl/6J Control; # p < 0.05 vs. C57Bl/6J HFD; & p < 0.05 vs. C57Bl/6J_TNFα + VO-OHpic HFD-induced obesity impairs Akt/NO signaling pathway by TNF-α-dependent mechanisms In order to elucidate the mechanisms involved on the crosstalk between TNF-α and PTEN, which affects the sensitivity of mesenteric arteries to insulin, the role of PTEN on the modulatory effects of TNF-α in vascular NO bioavailability was evaluated. The nitric oxide synthase inhibitor L-NAME significantly reduced insulin vasodilation in C57Bl/6J mice on control diet. L-NAME also effectively reduced insulin-induced relaxation in vessels incubated with TNF-α and PTEN inhibitor (Fig. 4a; Table 4), indicating that PTEN activity is involved on TNF-α-induced decreased NO bioavailability in mesenteric arteries.Fig. 4 TNF-α contributes to decreased Akt/NO signaling in HFD-fed mice. Concentration-effect curves to insulin were performed in endothelium-intact mesenteric arteries. The role of the PTEN on TNF-α-modulate NO in vessels was investigated using L-NAME (a). Western blot quantification of Akt(Ser473) phosphorylation levels in mesenteric arteries (b). The role of Akt on the relaxation was investigated using YS-49 in vessels of C57Bl/6J mice fed with control or HFD diet (c). Western blot quantification of mesenteric arteries eNOS(Ser1177/Thr495) phosphorylation levels in mesenteric arteries (d). DAF-2 DA-derived fluorescence (e). NO metabolites levels (f). Results represent the mean ± S.E.M. n = 5–6 in each experimental group. Scale bar: 100 µm. *p < 0.05 vs. C57Bl/6J Control; #p < 0.05 vs. C57Bl/6J HFD; &p < 0.05 vs. C57Bl/6J_TNFα + VO-OHpic As TNF-α increases PTEN activity, reducing Akt activity [21] and NO release, we investigated whether TNF-α decreases insulin-induced vascular relaxation by interfering with Akt/NO signaling in HFD-fed mice. The vasculature of HFD-fed C57Bl/6J mice exhibited reduced phosphorylation levels of Akt (Ser473), which was not observed in vessels from HFD-fed TNF-α KO mice (Fig. 4b). To determine whether Akt signaling pathway is involved on insulin vascular resistance in HFD-fed mice, vessels were pre-incubated with an Akt activator, YS-49, prior to the concentration-effect curves to insulin (Fig. 4c; Table 4). The Akt activator restored insulin relaxation in mesenteric arteries from HFD-fed C57Bl/6J mice. YS-49 did not change insulin-induced vascular relaxation in mice fed with the control diet. Signaling downstream to Akt, i.e. phosphorylation levels of eNOS (at Ser1177 and Thr495, stimulatory and inhibitory sites, respectively), was also analyzed (Fig. 4d). Vessels from HFD-fed C57Bl/6J mice presented reduced levels of phosphorylated eNOS at Ser1177 residue and increased levels of phosphorylated eNOS at Thr495 residue. Vessels from HFD-fed TNF-α receptor deficient mice exhibited increased Ser1177 phosphorylation levels and decreased Thr495 phosphorylation. To confirm that reduced vascular eNOS (Ser1177) phosphorylation levels in HFD-fed C57Bl/6J mice are associated with reduced NO release, NO levels were determined by using two techniques: the fluorescent NO indicator (DAF-2 DA) (Fig. 4e) and measurement of NO metabolites levels (Fig. 4f). The vasculature of HFD-fed C57Bl/6J mice exhibited decreased NO formation, which was not observed in vessels from HFD-fed TNF-α KO mice. Discussion Obesity induces various structural and functional changes in the vasculature, compromising the integrity and function of the cardiovascular system. The present study investigated mechanisms by which TNF-α decreases vascular insulin sensitivity consequent to a HFD. The key finding of our study is that HFD increases TNF-α circulating levels, which increases PTEN phosphatase activity, impairing Akt/eNOS/NO signaling pathway and compromising vascular relaxation. High fat diet and TNF-α Obesity development is usually associated with consumption of diets rich in fat and carbohydrates [29]. Increased body mass associated with fat accumulation is an important criterion for obesity characterization [30]. In the present study HFD significantly increased adiposity index and triggered the accumulation of adipose tissue in C57Bl/6J mice. These conditions facilitate development of co-morbidities that result in increased glucose levels and body mass. Of importance, TNF-α KO mice fed with HFD for 18 weeks also showed increased body weight, increased adiposity index and serum glucose levels, indicating that the differences found in vascular function between C57Bl/6J and TNF-α KO mice do not depend on the improvement of body mass profile or body composition phenotype. Obesity is also characterized by the development of a chronic low-grade inflammation. The concept of metabolic inflammation came from the identification of high levels of circulating TNF-α, an inflammatory cytokine associated with lipid [31] and carbohydrates [32] metabolism. Accordingly, HFD-fed C57Bl/6J mice exhibited increased TNF-α plasma levels. TNF-α and other cytokines have been described as biomarkers of cardiovascular risk in metabolic diseases. For instance, patients with type 2 diabetes mellitus and hypertension show severe increase of serum TNF-α [33], which is significantly attenuated by acetylsalicylic acid [34]. In this context, TNF-α blockade has antiatherosclerotic effects in hyperlipidemic mice lacking apoE [35]. High fat intake is associated with major risk factors for development of type 2 diabetes mellitus and cardiovascular disorders [36]. Mice fed with HFD exhibited glucose tolerance and increased plasma levels of insulin. The lack of TNF-α receptors partially protected against these metabolic abnormalities, in line with previous reports. Uysal (1997) demonstrated that TNF-α deficient mice are protected against HFD-induced increased glucose and insulin levels, but not body weight gain [37]. In addition, TNF-α or TNF-α receptors deficient mice are protected against obesity-induced insulin resistance and hyperglycemia [38, 39]. Furthermore, TNF-α blocks glucose uptake by inhibiting insulin-stimulated tyrosine kinase activity of the insulin receptor in various cell types, including adipocytes, hepatocytes and muscle cells [40]. TNF-α and vascular insulin resistance Insulin directly contributes to vascular tone control [41–43]. Insulin stimulates NO production by mechanisms involving activation of PI3K/Akt/eNOS signaling in the endothelial layer. Insulin-induced vasodilation increases blood flow and stimulates glucose uptake by the skeletal muscle, thereby linking metabolic and hemodynamic homeostasis [44]. Vascular insulin resistance is characterized by the inability of a tissue to respond to insulin [45] and vascular insulin resistance is associated with decreased NO production. In this study HFD promoted insulin resistance in the vasculature and deletion of TNF-α receptors prevented this effect. TNF-α is involved in endothelial dysfunction and reduced NO release in obese individuals [46, 47]. TNF-α also favors release of contractile mediators [48], such as COX-2-derived products and reactive oxygen species (ROS) [49]. Of importance, endothelial dysfunction evoked by TNF-α is reduced in fit and well-controlled type 1 diabetes mellitus patients [50]. In addition, TNF-α plays an important role in the changes of macrovascular and microvascular circulation. Oleate, the main lipid component of virgin olive oil, protects against cardiovascular insulin resistance and improves endothelial dysfunction in response to TNF-α [51]. An important finding of this study is that infliximab increased insulin sensitivity of mesenteric arteries from HFD-fed C57Bl/6J mice, indicating a synergic effect between TNF-α produced by the vasculature and circulating TNF-α. Infliximab treatment has anti-inflammatory effects in the vasculature and improves endothelium-dependent vasomotor responses in patients with systemic vasculitis [52]. Crosstalk between TNF-α, PTEN and vascular dysfunction It is well known that TNF-α interferes with vascular beneficial effects of insulin, possibly at the level of IRS [53]. Our results show the involvement of PTEN on TNF-α-induced reduced vascular insulin responses. There is evidence showing that PTEN modulates hyperglycemia and insulin resistance [54]. In addition, PTEN deletion in pancreatic α-cells protects against HFD-induced insulin resistance [55]. PTEN, through its lipid phosphatase activity, catalyzes the conversion of PIP3 (Akt substrate) to PIP2 by dephosphorylating the 3-position of the inositol ring of PIP3, attenuating Akt/eNOS/NO signaling [56]. PTEN expression changes under different conditions. PTEN mRNA decreases in the adipose tissue after exposure to cold, but increases with obesity [57]. The present study shows that HFD-fed C57Bl/6J mice exhibit increased vascular expression and activity of this phosphatase. Of importance, TNF-α receptor deletion prevented HFD-induced increased PTEN expression and activity. Experimental evidence indicates that NF-kappaB signaling pathway is the link between TNF-α and PTEN in leukemic [22], glioma [58] and intestinal cells [59]. Mechanisms linking TNF-α receptor and PTEN activation/expression were not investigated, which represents a limitation of our study. One of the mechanisms that regulate PTEN activity is reversible oxidation of the cysteine residue at the phosphatase active site [60]. Accordingly, treatment of macrophages with lipopolysaccharide stimulates ROS production and increases the fraction of oxidized PTEN from 5 to 16 % [61], showing a crosstalk between ROS production by the immune system and PTEN regulation. In hepatocytes TNF-α increases PTEN expression, which is blunted by PTEN siRNA knockdown and VO-OHpic treatment [62]. These results suggest an important crosstalk between inflammatory mediators and PTEN activity and are in line with the idea that PTEN is involved in apoptosis and inflammatory processes [18]. Our findings indicate that TNF-α is a positive modulator of PTEN activity. Since PTEN inhibition restores vascular insulin sensitivity, decreased by TNF-α and HFD, PTEN may be considered a major contributor to TNF-α-induced insulin resistance. The mechanisms whereby PTEN changes vascular function are poorly understood. Our data indicate that TNF-α via increased PTEN expression and activity compromises NO bioavailability. Accordingly, mesenteric arteries incubated with TNF-α present reduced sensitivity to insulin effects as well as reduced Akt/eNOS signaling and NO levels. PTEN inhibition improved insulin-dependent vasodilation, and restored NO levels, as indicated by the effects of L-NAME on insulin-induced vascular relaxation. In addition, TNF-α is the major regulator of PTEN activity in the vasculature of HFD-fed mice, decreasing Akt/eNOS/NO signaling. Our findings corroborate a previous report showing decreased NO release by human aortic endothelial cells overexpressing PTEN [63]. On the other hand, NO by inducing S-nitrosylation and ubiquitination, modulates both PTEN protein degradation and enzymatic activity in neurons, representing a regulatory mechanism of the Akt/NOS signaling pathway on PTEN [64]. Conclusions Taken together, our study suggests that in obesity, TNF-α induces vascular insulin resistance by increasing PTEN activity that negatively modulates Akt/eNOS/NO signaling and insulin vasodilation. Since vascular insulin resistance represents a primary defect in vascular dysfunction, TNF-α and PTEN are potential therapeutic targets for obesity-associated cardiovascular and metabolic dysfunction. Abbreviations PI3Kphosphatidylinositol 3-kinase eNOSendothelial nitric oxide synthase NOnitric oxide HFDhigh fat diet TNF-αtumor necrosis factor alpha PTENphosphatase and tension homologue Authors’ contributions RC, TBN and RT participated in the design of the study; RC, KN and FM conducted the experiments; RC, KN, TBN, PLJ and RT performed the data analysis; RC, TBN, PLJ and RT wrote or reviewed the paper. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Availability of data and materials The datasets supporting the conclusions of this article are included within the article. Funding This work was supported by grants from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP 2013/08216-2-CRID), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil. ==== Refs References 1. Kopelman P Obesity as a medical problem Nature 2000 404 635 643 10766250 2. Barton M Baretella O Meyer MR Obesity and risk of vascular disease: importance of endothelium-dependent vasoconstriction Br J Pharmacol 2012 165 591 602 10.1111/j.1476-5381.2011.01472.x 21557734 3. Poirier P Giles TD Bray GA Hong Y Stern JS Pi-Sunyer FX Eckel RH Obesity and cardiovascular disease: pathophysiology, evaluation, and effect of weight loss Arterioscler Thromb Vasc Biol 2006 26 968 976 10.1161/01.ATV.0000216787.85457.f3 16627822 4. Wolpert HA Steen SN Istfan NW Simonson DC Insulin modulates circulating endothelin-1 levels in humans Metabolism 1993 42 1027 1030 10.1016/0026-0495(93)90018-J 8345807 5. Chaudhuri A Dandona P Fonseca V Cardiovascular benefits of exogenous insulin J Clin Endocrinol Metab 2012 97 3079 3091 10.1210/jc.2012-1112 22723317 6. Salt IP Examining the role of insulin in the regulation of cardiovascular health Future Cardiol 2013 9 39 52 10.2217/fca.12.77 23259474 7. Montagnani M Chen H Barr VA Quon MJ Insulin-stimulated activation of eNOS is independent of Ca2+ but requires phosphorylation by Akt at Ser(1179) J Biol Chem 2001 276 30392 30398 10.1074/jbc.M103702200 11402048 8. Muniyappa R Quon MJ Insulin action and insulin resistance in vascular endothelium Curr Opin Clin Nutr Metab Care. 2007 10 523 530 10.1097/MCO.0b013e32819f8ecd 17563474 9. Muniyappa R Sowers JR Role of insulin resistance in endothelial dysfunction Rev Endocr Metab Disord. 2013 14 5 12 10.1007/s11154-012-9229-1 23306778 10. Shoelson SE Lee J Goldfine AB Inflammation and insulin resistance J Clin Invest. 2006 116 1793 1801 10.1172/JCI29069 16823477 11. Fulton DJ Mechanisms of vascular insulin resistance: a substitute Akt? Circ Res 2009 104 1035 1037 10.1161/CIRCRESAHA.109.198028 19423861 12. Tzanavari T Giannogonas P Karalis KP TNF-alpha and obesity Curr Dir Autoimmun. 2010 11 145 156 10.1159/000289203 20173393 13. Jung UJ Choi MS Obesity and its metabolic complications: the role of adipokines and the relationship between obesity, inflammation, insulin resistance, dyslipidemia and nonalcoholic fatty liver disease Int J Mol Sci 2014 15 6184 6223 10.3390/ijms15046184 24733068 14. Hotamisligil GS Mechanisms of TNF-alpha-induced insulin resistance Exp Clin Endocrinol Diabetes 1999 107 119 125 10.1055/s-0029-1212086 10320052 15. Nieto-Vazquez I Fernández-Veledo S Krämer DK Vila-Bedmar R Garcia-Guerra L Lorenzo M Insulin resistance associated to obesity: the link TNF-alpha Arch Physiol Biochem 2008 114 183 194 10.1080/13813450802181047 18629684 16. Kanety H Feinstein R Papa MZ Hemi R Karasik A Tumor necrosis factor alpha-induced phosphorylation of insulin receptor substrate-1 (IRS-1). Possible mechanism for suppression of insulin-stimulated tyrosine phosphorylation of IRS-1 J Biol Chem 1995 270 23780 23784 10.1074/jbc.270.40.23780 7559552 17. Liang H Yin B Zhang H Zhang S Zeng Q Wang J Jiang X Yuan L Wang CY Li Z Blockade of tumor necrosis factor (TNF) receptor type 1-mediated TNF-alpha signaling protected Wistar rats from diet-induced obesity and insulin resistance Endocrinology 2008 149 2943 2951 10.1210/en.2007-0978 18339717 18. Song MS Salmena L Pandolfi PP The functions and regulation of the PTEN tumour supressor Nat Rev Mol Cell Biol 2012 13 283 296 22473468 19. Gupta A Dey CS PTEN, a widely known negative regulator of insulin/PI3K signaling, positively regulates neuronal insulin resistance Mol Biol Cell 2012 23 3882 3898 10.1091/mbc.E12-05-0337 22875989 20. Pal A Barber TM Van de Bunt M Rudge SA Zhang Q Lachlan KL Cooper NS Linden H Levy JC Wakelam MJ Walker L Karpe F Gloyn AL PTEN mutations as a cause of constitutive insulin sensitivity and obesity N Engl J Med 2012 367 1002 1011 10.1056/NEJMoa1113966 22970944 21. Solomon SS Odunusi O Carrigan D Majumdar G Kakoola D Lenchik NI Gerling IC TNF-alpha inhibits insulin action in liver and adipose tissue: a model of metabolic syndrome Horm Metab Res 2010 42 115 121 10.1055/s-0029-1241834 19960405 22. Lee YR Yu HN Noh EM Youn HJ Song EK Han MK Park CS Kim BS Park YS Park BK Lee SH Kim JS TNF-alpha upregulates PTEN via NF-kappaB signaling pathways in human leukemic cells Exp Mol Med 2007 39 121 127 10.1038/emm.2007.14 17334236 23. Lee H Jee Y Hong K Hwang GS Chun KH MicroRNA-494, upregulated by tumor necrosis factor-α, desensitizes insulin effect in C2C12 muscle cells PLoS ONE 2013 8 e83471 10.1371/journal.pone.0083471 24349514 24. Wijesekara N Konrad D Eweida M Jefferies C Liadis N Giacca A Crackower M Suzuki A Mak TW Kahn CR Klip A Woo M Muscle-specific Pten deletion protects against insulin resistance and diabetes Mol Cell Biol 2005 25 1135 1145 10.1128/MCB.25.3.1135-1145.2005 15657439 25. Taylor BA Phillips SJ Detection of obesity QTLs on mouse chromosomes 1 and 7 by selective DNA pooling Genomics 1996 34 389 398 10.1006/geno.1996.0302 8786140 26. Pan Y Qiao QY Pan LH Zhou DC Hu C Gu HF Fu SK Liu XL Jin HM Losartan reduces insulin resistance by inhibiting oxidative stress and enhancing insulin signaling transduction Exp Clin Endocrinol Diabetes 2015 123 170 177 25502581 27. Rosivatz E Matthews JG McDonald NQ Mulet X Ho KK Lossi N Schmid AC Mirabelli M Pomeranz KM Erneux C Lam EW Vilar R Woscholski R A small molecule inhibitor for phosphatase and tensin homologue deleted on chromosome 10 (PTEN) ACS Chem Biol 2006 1 780 790 10.1021/cb600352f 17240976 28. Bradford MM A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding Anal Biochem 1976 72 248 254 10.1016/0003-2697(76)90527-3 942051 29. Koul D Takada Y Shen R Aggarwal BB Yung WK PTEN enhances TNF-induced apoptosis through modulation of nuclear factor-kappaB signaling pathway in human glioma cells Biochem Biophys Res Commun 2006 350 463 471 10.1016/j.bbrc.2006.09.077 17011514 30. Neves KB Lobato NS Lopes RA Filgueira FP Zanotto CZ Oliveira AM Tostes RC Chemerin reduces vascular nitric oxide/cGMP signalling in rat aorta: a link to vascular dysfunction in obesity? Clin Sci 2014 127 111 122 10.1042/CS20130286 24498891 31. Chen X Xun K Chen L Wang Y TNF-alpha, a potent lipid metabolism regulator Cell Biochem Funct 2009 27 407 416 10.1002/cbf.1596 19757404 32. Porter MH Cutchins A Fine JB Bai Y DiGirolamo M Effects of TNF-alpha on glucose metabolism and lipolysis in adipose tissue and isolated fat-cell preparations J Lab Clin Med 2002 139 140 146 10.1067/mlc.2002.121552 11944024 33. Derosa G Mugellini A Pesce RM D’Angelo A Maffioli P A study about the relevance of adding acetylsalicylic acid in primary prevention in subjects with type 2 diabetes mellitus: effects on some new emerging biomarkers of cardiovascular risk Cardiovasc Diabetol 2015 14 95 10.1186/s12933-015-0254-8 26223257 34. Osnes LT Foss KB Joø GB Okkenhaug C Westvik AB Ovstebø R Kierulf P Acetylsalicylic acid and sodium salicylate inhibit LPS-induced NF-kappa B/c-Rel nuclear translocation, and synthesis of tissue factor (TF) and tumor necrosis factor alfa (TNF-alpha) in human monocytes Thromb Haemost 1996 76 970 976 8972019 35. Zhu L Giunzioni I Tavori H Covarrubias R Ding L Zhang Y Ormseth M Major AS Stafford JM Linton MF Fazio S Loss of macrophage low-density lipoprotein receptor-related protein 1 confers resistance to the antiatherogenic effects of tumor necrosis factor-α inhibition Arterioscler Thromb Vasc Biol 2016 36 1483 1495 10.1161/ATVBAHA.116.307736 27365402 36. Katcher HI Legro RS Kunselman AR Gillies PJ Demers LM Bagshaw DM Kris-Etherton PM The effects of a whole grain-enriched hypocaloric diet on cardiovascular disease risk factors in men and women with metabolic syndrome Am J Clin Nutr 2008 87 79 90 18175740 37. Uysal KT Wiesbrock SM Marino MW Hotamisligil GS Protection from obesity-induced insulin resistance in mice lacking TNF-alpha function Nature 1997 389 610 614 10.1038/39335 9335502 38. Schreyer SA Chua SC Jr LeBoeuf RC Obesity and diabetes in TNF-alpha receptor- deficient mice J Clin Invest. 1998 102 402 411 10.1172/JCI2849 9664082 39. Araújo EP De Souza CT Ueno M Cintra DE Bertolo MB Carvalheira JB Saad MJ Velloso LA Infliximab restores glucose homeostasis in an animal model of diet-induced obesity and diabetes Endocrinology 2007 148 5991 5997 10.1210/en.2007-0132 17761768 40. Kroder G Bossenmaier B Kellerer M Capp E Stoyanov B Mühlhöfer A Berti L Horikoshi H Ullrich A Häring H Tumor necrosis factor-alpha- and hyperglycemia-induced insulin resistance. Evidence for different mechanisms and different effects on insulin signaling J Clin Invest 1996 97 1471 1477 10.1172/JCI118569 8617880 41. Mather KJ Steinberg HO Baron AD Insulin resistance in the vasculature J Clin Invest 2013 123 1003 1004 10.1172/JCI67166 23454764 42. Muniyappa R Montagnani M Koh KK Quon MJ Cardiovascular actions of insulin Endocr Rev 2007 28 463 491 10.1210/er.2007-0006 17525361 43. Ren J Samson WK Sowers JR Insulin-like growth factor I as a cardiac hormone: physiological and pathophysiological implications in heart disease J Mol Cell Cardiol 1999 31 2049 2061 10.1006/jmcc.1999.1036 10591031 44. Yu Q Gao F Ma XL Insulin says NO to cardiovascular disease Cardiovasc Res 2011 89 516 524 10.1093/cvr/cvq349 21051417 45. Bruder-Nascimento T da Silva MA Tostes RC The involvement of aldosterone on vascular insulin resistance: implications in obesity and type 2 diabetes Diabetol Metab Syndr 2014 6 90 10.1186/1758-5996-6-90 25352918 46. Donato AJ Henson GD Morgan RG Enz RA Walker AE Lesniewski LA TNF-α impairs endothelial function in adipose tissue resistance arteries of mice with diet-induced obesity Am J Physiol Heart Circ Physiol 2012 303 H672 H679 10.1152/ajpheart.00271.2012 22821989 47. Kim F Gallis B Corson MA TNF-alpha inhibits flow and insulin signaling leading to NO production in aortic endothelial cells Am J Physiol Cell Physiol 2001 280 C1057 C1065 11287317 48. Murdaca G Spanò F Cagnati P Puppo F Free radicals and endothelial dysfunction: potential positive effects of TNF-α inhibitors Redox Rep 2013 18 95 99 10.1179/1351000213Y.0000000046 23676793 49. Bruder-Nascimento T Kennard S Antonova G Mintz JD Bence KK Belin de Chantemèle EJ. Ptp1b deletion in pro-opiomelanocortin neurons increases energy expenditure and impairs endothelial function via TNF-α dependent mechanisms Clin Sci 2016 130 881 893 10.1042/CS20160073 26935109 50. West DJ Campbell MD Gonzalez JT Walker M Stevenson EJ Ahmed FW Wijaya S Shaw JA Weaver JU The inflammation, vascular repair and injury responses to exercise in fit males with and without type 1 diabetes: an observational study Cardiovasc Diabetol 2015 14 71 10.1186/s12933-015-0235-y 26044827 51. Perdomo L Beneit N Otero YF Escribano Ó Díaz-Castroverde S Gómez-Hernández A Benito M Protective role of oleic acid against cardiovascular insulin resistance and in the early and late cellular atherosclerotic process Cardiovasc Diabetol 2015 14 75 10.1186/s12933-015-0237-9 26055507 52. Booth AD Jayne DR Kharbanda RK McEniery CM Mackenzie IS Brown J Wilkinson IB Infliximab improves endothelial dysfunction in systemic vasculitis: a model of vascular inflammation Circulation 2004 109 1718 1723 10.1161/01.CIR.0000124720.18538.DD 15037536 53. Peraldi P Hotamisligil GS Buurman WA White MF Spiegelman BM Tumor necrosis factor (TNF)-alpha inhibits insulin signaling through stimulation of the p55 TNF receptor and activation of sphingomyelinase J Biol Chem 1996 271 13018 13022 10.1074/jbc.271.22.13018 8662983 54. Lee SK Lee JO Kim JH Kim SJ You GY Moon JW Jung JH Park SH Uhm KO Park JM Suh PG Kim HS Metformin sensitizes insulin signaling through AMPK-mediated PTEN down-regulation in preadipocyte 3T3-L1 cells J Cell Biochem 2011 112 1259 1267 10.1002/jcb.23000 21465524 55. Wang L Luk CT Cai EP Schroer SA Allister EM Shi SY Wheeler MB Gaisano HY Woo M PTEN deletion in pancreatic α-cells protects against high-fat diet-induced hyperglucagonemia and insulin resistance Diabetes 2015 64 147 157 10.2337/db13-1715 25092678 56. Bermúdez Brito M Goulielmaki E Papakonstanti EA Focus on PTEN regulation Front Oncol 2015 5 166 10.3389/fonc.2015.00166 26284192 57. Komazawa N Matsuda M Kondoh G Mizunoya W Iwaki M Takagi T Sumikawa Y Inoue K Suzuki A Mak TW Nakano T Fushiki T Takeda J Shimomura I Enhanced insulin sensitivity, energy expenditure and thermogenesis in adipose-specific Pten suppression in mice Nat Med 2004 10 1208 1215 10.1038/nm1117 15489860 58. Kim S Domon-Dell C Wang Q Chung DH Di Cristofano A Pandolfi PP Freund JN Evers BM PTEN and TNF-alpha regulation of the intestinal-specific Cdx-2 homeobox gene through a PI3K, PKB/Akt, and NF-kappaB-dependent pathway Gastroenterology 2002 123 1163 1178 10.1053/gast.2002.36043 12360479 59. Golay A Bobbioni E The role of dietary fat in obesity Int J Obes Relat Metab Disord 1997 21 Suppl 3 S2 S11 9225171 60. Cho SH Lee CH Ahn Y Kim H Kim H Ahn CY Yang KS Lee SR Redox regulation of PTEN and protein tyrosine phosphatases in H(2)O(2) mediated cell signaling FEBS Lett 2004 560 7 13 10.1016/S0014-5793(04)00112-7 15017976 61. Leslie NR Bennett D Lindsay YE Stewart H Gray A Downes CP Redox regulation of PI3-kinase signalling via inactivation of PTEN EMBO J 2003 22 5501 5510 10.1093/emboj/cdg513 14532122 62. Bulger DA Conley J Conner SH Majumdar G Solomon SS Role of PTEN in TNFα induced insulin resistance Biochem Biophys Res Commun. 2015 461 533 536 10.1016/j.bbrc.2015.04.063 25918024 63. Church JE Qian J Kumar S Black SM Venema RC Papapetropoulos A Fulton DJ Inhibition of endothelial nitric oxide synthase by the lipid phosphatase PTEN Vascul Pharmacol 2010 52 191 198 10.1016/j.vph.2009.11.007 19962452 64. Kwak YD Ma T Diao S Zhang X Chen Y Hsu J Lipton SA Masliah E Xu H Liao FF NO signaling and S-nitrosylation regulate PTEN inhibition in neurodegeneration Mol Neurodegener 2010 5 49 10.1186/1750-1326-5-49 21067594

PMC005xxxxxx/PMC5000487.txt

==== Front J NeuroinflammationJ NeuroinflammationJournal of Neuroinflammation1742-2094BioMed Central London 68010.1186/s12974-016-0680-xResearchDynamic change of neutrophil to lymphocyte ratio and hemorrhagic transformation after thrombolysis in stroke Guo Zhiliang guozhiliang3@163.com 12Yu Shuhong yushuhong11@163.com 1Xiao Lulu xiaolulu1107@126.com 1Chen Xin 1252356496@qq.com 1Ye Ruidong yeruid@gmail.com 1Zheng Ping zhengp@unimelb.edu.au 3Dai Qiliang dql.nju@gmail.com 1Sun Wen sunwen_neuro@yeah.net 1Zhou Changsheng zhouyisheng@hotmail.com 4Wang Shuiping wspsmmu@163.com 5Zhu Wusheng +86 25 84801861zwsemail@sina.com 1Liu Xinfeng +86 25 80860124xfliu2@vip.163.com 11 Department of Neurology, Jinling Hospital, Medical School of Nanjing University, 305 E Zhongshan Rd, Nanjing, 210002 Jiangsu Province China 2 Department of Neurology, Second Affiliated Hospital of Soochow University, Suzhou, 215004 China 3 Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia 4 Department of Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002 China 5 Department of Neurology, PLA 123 Hospital, 1052 Yanshan Road, Yuhui District, Bengbu, 233000 China 26 8 2016 26 8 2016 2016 13 1 19915 12 2015 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The neutrophil to lymphocyte ratio (NLR) has been shown to predict short- and long-term outcomes in ischemic stroke patients. We sought to explore the temporal profile of the plasma NLR in stroke patients treated with intravenous thrombolysis (IVT) and its relationship with intracranial bleeding complications after thrombolysis. Methods A total of 189 ischemic stroke patients were prospectively enrolled. Blood samples for leukocyte, neutrophil, and lymphocyte counts were obtained at admission and at 3–6, 12–18, and 36–48 h after IVT. Head CT was performed on admission and repeated after 36–48 h, and a CT scan was done immediately in case of clinical worsening. Hemorrhagic events were categorized as symptomatic intracranial hemorrhage (sICH) and parenchymal hematomas (PH) according to previously published criteria. Results An increasing trend in the NLR was observed after stroke, and the NLR was higher in patients who developed PH or sICH at 3–6, 12–18, and 36–48 h after IVT (P < 0.01) than in those without PH or sICH. The optimal cutoff value for the serum NLR as an indicator for auxiliary diagnosis of PH and sICH was 10.59 at 12–18 h. Furthermore, the NLR obtained at 12–18-h post-treatment was independently associated with PH (adjusted odds ratio [OR] 1.14) and sICH (adjusted OR 1.14). In addition, patients with a NLR ≥10.59 had an 8.50-fold greater risk for PH (95 % confidence interval [CI] 2.69–26.89) and a 7.93-fold greater risk for sICH (95 % CI 2.25–27.99) than patients with a NLR <10.59. Conclusions NLR is a dynamic variable, and its variation is associated with HT after thrombolysis in stroke patients. Electronic supplementary material The online version of this article (doi:10.1186/s12974-016-0680-x) contains supplementary material, which is available to authorized users. Keywords Neutrophil to lymphocyte ratio (NLR)Ischemic strokeThrombolysisHemorrhagic transformationBiomarkerhttp://dx.doi.org/10.13039/501100001809National Natural Science Foundation of China8117109981501193Sun Wen Zhu Wusheng http://dx.doi.org/10.13039/501100001809National Natural Science Foundation of China (CN)81471182Ye Ruidong issue-copyright-statement© The Author(s) 2016 ==== Body Background Multiple randomized controlled trials have demonstrated the efficacy of intravenous recombinant tissue plasminogen activator (IV rtPA) administered up to 4.5 h after the onset of symptoms of ischemic stroke [1]. However, the risk of hemorrhagic transformation (HT) is increased by as much as tenfold after IV rtPA, largely due to reperfusion injury and the toxic effects of rtPA [2]. In addition to the already known indicators for HT [2], the detection of new paradigms is still worthwhile. In addition, an improved understanding of the prevention or early risk assessment of rtPA-related HT may also be applicable to other reperfusion strategies such as endovascular therapy. In animal studies, neutrophils have been shown to contribute to intracerebral hemorrhaging after treatment with rtPA following cerebral ischemia, while depletion of neutrophils reduces blood–brain barrier (BBB) disruption and the rate of HT [3, 4]. In humans, infiltration of matrix metalloproteinase-9 (MMP-9)-positive neutrophils is associated with BBB breakdown, basal lamina type IV collagen degradation, and HT [5]. Recent studies suggested that the initial neutrophil to lymphocyte ratio (NLR) is associated with mortality and infarct size in ischemic stroke [6, 7] and can predict the 90-day outcome after endovascular therapy [8]. However, all of these studies mainly focused on static NLR values at baseline, which may not reflect the comprehensive dynamic changes of patients’ conditions. Furthermore, there is also a lack of information on the clinical value of the NLR in acute ischemic stroke patients treated with IV rtPA, especially its relationship with the most serious and common complication of IV rtPA treatment, HT. Thus, we aimed to explore the temporal variation of the NLR in patients and its relationship with the most serious subtypes of HT, namely symptomatic intracranial hemorrhage (sICH) and parenchymal hematoma (PH), in patients with ischemic stroke treated with IV rtPA [9]. Methods Study population Consecutive ischemic stroke patients admitted to the Departments of Neurology at two hospitals (Jinling Hospital and PLA 123 Hospital, both large comprehensive hospitals) from March 2012 to August 2015 were prospectively recruited. The inclusion criteria for enrollment were (1) age ≥18 years and (2) diagnosis of acute ischemic stroke and treatment with IV rtPA within 4.5-h post-onset. The study exclusion criteria were (1) evidence of active infection before admission or any systemic infection that occurred during the first 48 h after treatment with IV rtPA (41 patients); (2) cancer, chronic inflammation, autoimmune disease, or steroid therapy (6 patients); and (3) unavailability to complete blood cell count or medical records (8 patients discharged on the same day of admission). At last, 189 consecutive ischemic stroke patients were included in the current study. The study protocol was approved by the Institutional Human Research Ethics Committees of Jinling Hospital and PLA 123 Hospital, and all patients or their relatives gave informed consent. Treatment administration IV rtPA (alteplase, 0.9 mg/kg up to a maximum of 90 mg/kg) was used with 10 % of the total dosage as a bolus, followed by a 60-min infusion of the remaining dose. Patients who were receiving a bridging therapy consisting of IV rtPA followed by endovascular therapy were also enrolled. The method of endovascular therapy, such as local intra-arterial thrombolysis using rtPA, mechanical thrombectomy, angioplasty, stent placement, or multimodal endovascular therapy, was left to the discretion of the neurointerventionists. Clinical protocol and laboratory tests Patient’s medical history, including potential stroke risk factors, clinical examination findings, blood and coagulation test results, 12-lead electrocardiographs, and chest radiographs were obtained at admission. Stroke severity was assessed by a certified neurologist using the National Institutes of Health Stroke Scale (NIHSS) at admission and at 3–6, 12–18, and 36–48 h after treatment with IV rtPA. Neurological deterioration was defined as death or an increase of ≥4 points in the NIHSS score between the two examinations [10]. Venous blood samples were obtained from all patients at admission and at 3–6, 12–18, and 36–48 h after treatment with IV rtPA. Total leukocyte, neutrophil, and lymphocyte counts were determined using a COULTER LH780 Hematology Analyzer (Beckman Coulter, Inc, Orange County, CA). The NLR was calculated as the ratio of the percentage of neutrophils over the percentage of lymphocytes, both obtained from the same blood sample. CT and intracranial hemorrhage On admission, all patients underwent a CT scan within the first 4.5 h of stroke onset. CT was repeated at 36–48 h, and another CT scan was done immediately in case of rapid neurological deterioration to evaluate the presence of HT. CT images were reviewed by a neuroradiologist with extensive experience in acute stroke who was blinded to patients’ medical records. PH was defined as hemorrhage with a mass effect according to previously published criteria [11]. sICH was defined as any hemorrhage in the brain on the CT scan accompanied by the presence of neurological deterioration [10]. Statistical analysis To compare baseline characteristics between groups according to the presence of PH or sICH, parametric and non-parametric comparisons were performed with the t test, χ2 test, and Mann-Whitney U test as appropriate. The relation of the NLR with two endpoints was investigated using logistic regression models. For multivariate analysis, we first included age and sex (model 1) and then additionally included variables that significantly correlated with PH or sICH in the univariate analysis (P < 0.10; models 2 or 3). Receiver operating characteristic (ROC) curves were used to test the overall discriminative ability of the NLR for PH or sICH and to establish optimal cutoff points at which the sum of the specificity and sensitivity was the highest. The differences in discriminative ability were tested using the DeLong method [12]. Finally, logistic regression analysis was performed again with the same independent variables as in the previous model, except for values of the NLR that were included as a binary variable according to the cutoff point. Statistical analysis was performed using SPSS for Windows, version 17.0 (SPSS Inc., Chicago, IL, USA) and SAS version 9.1 (SAS Institute Inc., Cary, NC). Two-tailed significance values were applied, and statistical significance was defined as P < 0.05. Results Baseline characteristics of patients One hundred eighty-nine patients with ischemic stroke met the study criteria. The demographic and clinical characteristics between the included and excluded patients are detailed in Additional file 1: Table S1. These included cohorts from different hospitals are described in Additional file 1: Table S2. Among the 189 patients, 28 (14.8 %) presented with PH, and 17 (9.0 %) developed sICH. The mean time of sICH (determined by head CT) was 12.23 ± 7.74 h after thrombolysis. The main baseline characteristics of patients according to the presence or absence of PH or to the presence or absence of sICH are presented in Table 1.Table 1 Baseline characteristics of patients according to the presence/absence of PH or sICH No PH (n = 161) PH (n = 28) P No sICH (n = 172) sICH (n = 17) P Age, years, mean (SD) 64.1 ± 10.3 70.1 ± 10.5 0.005 64.6 ± 10.4 68.7 ± 11.7 0.133 Females, % 59 (36.6) 7 (25.0) 0.233 60 (34.9) 6 (35.3) 0.973 Body mass index, kg/m2, mean (SD) 24.4 ± 3.1 23.9 ± 3.0 0.401 24.4 ± 3.0 24.0 ± 3.5 0.601 Hypertension, % 101 (62.7) 21 (75.0) 0.210 111 (64.5) 11 (64.7) 0.989 Diabetes, % 50 (31.1) 7 (25.0) 0.519 51 (29.7) 6 (35.3) 0.629 Hyperlipidemia, % 73 (45.3) 12 (42.9) 0.807 79 (45.9) 6 (35.3) 0.400 Previous stroke, % 14 (8.7) 5 (17.9) 0.251 17 (9.9) 2 (11.8) 1.000 Coronary artery disease, % 18 (11.2) 5 (17.9) 0.494 19 (11.0) 4 (23.5) 0.266 Atrial fibrillation, % 48 (29.8) 12 (42.9) 0.171 50 (29.1) 10 (58.8) 0.012 Current smokers, % 53 (32.9) 8 (28.6) 0.650 56 (32.6) 5 (29.4) 0.791 Ongoing antiplatelet therapy, % 9 (5.6) 7 (25.0) 0.002 12 (7.0) 4 (23.5) 0.060 SBP, mm Hg, mean (SD) 148.4 ± 18.4 154.5 ± 17.1 0.104 148.9 ± 18.2 153.2 ± 18.7 0.302 DBP, mm Hg, mean (SD) 81.4 ± 9.8 83.2 ± 10.4 0.368 81.3 ± 9.7 84.8 ± 11.2 0.163 Blood glucose, mmol/L, median (IQR) 7.2 (5.3–9.0) 7.0 (5.8–9.5) 0.133 7.0 (5.3–9.0) 8.0 (5.5–9.5) 0.645 Platelets, 109/L, mean (SD) 187.9 ± 50.8 178.9 ± 40.0 0.371 187.3 ± 49.9 179.7 ± 44.5 0.545 INR, mean (SD) 1.01 ± 0.08 1.01 ± 0.09 0.468 1.01 ± 0.08 1.03 ± 0.08 0.302 Baseline NIHSS, median (IQR) 11 (6–15) 17 (10–22.5) 0.001 12 (6–15) 13 (10–20) 0.198 Onset to treatment, min, mean (SD) 170.6 ± 48.8 183.4 ± 51.9 0.207 171.1 ± 48.9 187.2 ± 52.1 0.198 IV rtPA + endovascular therapy, % 49 (30.4) 9 (32.1) 0.856 51 (29.7) 7 (41.2) 0.326 DBP diastolic blood pressure, INR international normalized ratio, IQR interquartile range, IV rtPA intravenous recombinant tissue plasminogen activator, NIHSS National Institutes of Health Stroke Scale, PH parenchymal hemorrhage, SBP systolic blood pressure, SD standard deviation, sICH symptomatic intracranial hemorrhage Temporal profile of NLR depending on the type of HT The NLR was obtained at four different time points: at admission, 3–6 h after rtPA treatment, 12–18 h after rtPA treatment, and 36–48 h after rtPA treatment. The temporal profiles of the NLR according to the presence of PH or sICH are presented in Figs. 1 and 2 and Additional file 1: Table S3 and Figure S1. The NLR at admission did not differ between patients with and without PH (P = 0.819). Thereafter, an increasing trend in the NLR was observed in both groups (Additional file 1: Figure S1). However, the NLR values in the PH group were significantly higher than those in the No PH group at 3–6, 12–18, and 36–48 h after rtPA (P < 0.001). The temporal profile of the NLR according to the presence of sICH was similar to that according to the presence of PH.Fig. 1 Temporal profile of plasma neutrophil to lymphocyte ratio (NLR) in stroke patients treated with recombinant tissue plasminogen activator (rtPA) according to the presence of parenchymal hemorrhage (PH). Blue boxes patients without PH, green boxes patients with PH. *P < 0.001 between patients with and without PH Fig. 2 Temporal profile of plasma neutrophil to lymphocyte ratio (NLR) in stroke patients treated with recombinant tissue plasminogen activator (rtPA) according to the presence of symptomatic intracranial hemorrhage (sICH). Blue boxes patients without sICH, green boxes patients with sICH. # P = 0.009 between patients with and without sICH; ## P < 0.001 between patients with and without sICH Association of plasma NLR with hemorrhagic transformation ROC curve analysis was performed to assess the best cutoff value of the NLR for discriminating PH and sICH (Fig. 3 and Table 2). The optimal cutoff value of the NLR that best distinguished the presence/absence of PH and sICH was 10.59 at 12–18 h after rtPA treatment, which can be obtained earlier than the NLR at 36–48 h after rtPA. The areas under the curve (AUCs) for the ability of the NLR to predict PH or sICH were 0.833 with 78.6 % sensitivity and 79.5 % specificity and 0.814 with 76.5 % sensitivity and 75.6 % specificity, respectively.Fig. 3 Discriminative ability of the neutrophil to lymphocyte ratio (NLR) for parenchymal hemorrhage (PH) and symptomatic intracranial hemorrhage (sICH). a Receiver operator characteristic (ROC) curve for NLR in auxiliary diagnosis of PH and b ROC curve for NLR in the auxiliary diagnosis of sICH Table 2 Diagnostic values of the neutrophil to lymphocyte ratio (NLR) for PH and sICH AUC (95 % CI) P Cutoff value Sensitivity (%) Specificity (%) For PH  3–6 h NLR 0.717 (0.630–0.803) <0.001 5.45 78.6 65.2  12–18 h NLR 0.833 (0.764–0.903) Reference 10.59 78.6 79.5  36–48 h NLR 0.830 (0.758–0.902) 0.887 14.36 60.7 91.9 For sICH  3–6 h NLR 0.691 (0.597–0.785) <0.001 5.45 76.5 62.8  12–18 h NLR 0.814 (0.728–0.900) Reference 10.59 76.5 75.6  36–48 h NLR 0.766 (0.666–0.866) 0.166 14.36 52.9 87.8 AUC area under the curve, CI confidence interval, PH parenchymal hematoma, sICH symptomatic intracranial hemorrhage Table 3 summarizes the results of the binary logistic regression analysis of PH and sICH. The NLR as a continuous variable was independently associated with a greater risk of PH with an adjusted odds ratio (OR) of 1.17 (95 % CI, 1.10–1.26) with adjustment for age and sex (model 1) and 1.14 (1.05–1.23) with further adjustment for ongoing antiplatelet therapy and baseline NIHSS (model 2), respectively. In addition, age (adjusted OR 1.06, 95 % CI: 1.01–1.11; P = 0.014) and ongoing antiplatelet therapy (adjusted OR 4.00, 95 % CI: 1.13–14.14; P = 0.031) remained significant outcome predictors for PH. Furthermore, in our study, the risk of PH was also associated with NLR levels as a dichotomous variable (OR 8.50, 95 % CI: 2.69–26.89; P < 0.001) after adjustment for age, sex, ongoing antiplatelet therapy, and baseline NIHSS (model 2). This relationship was further confirmed in the dose-response model (Additional file 1: Figure S2). For the binary logistic regression analysis for sICH, similar associations were found between the NLR and sICH. A NLR level ≥10.59 (OR 7.93, 95 % CI 2.25–27.99; P = 0.001) remained significantly associated with sICH after adjusting for age, sex, atrial fibrillation, and ongoing antiplatelet therapy (model 3).Table 3 Associations of the neutrophil to lymphocyte ratio (NLR) with PH and sICH PH OR (95 % CI) sICH OR (95 % CI) Univariate analysis Model 1 Model 2 Univariate analysis Model 1 Model 3 NLRa 1.19 (1.10–1.28)* 1.17 (1.10–1.26)* 1.14 (1.05–1.23)** 1.16 (1.08–1.26)* 1.16 (1.07–1.25)* 1.14 (1.06–1.23)** NLRb (≥10.59 vs <10.59) 14.22 (5.34–37.91)* 11.86 (4.35–32.36)* 8.50 (2.69–26.89)* 10.06 (3.11–32.52)* 9.55 (2.84–32.04)* 7.93 (2.25–27.99)** Model 1 bivariate logistic regression analyses with adjustment for age and sex. Model 2 bivariate logistic regression analyses with adjustment for age, sex, ongoing antiplatelet therapy, and baseline NIHSS. Model 3 bivariate logistic regression analyses with adjustment for age, sex, atrial fibrillation, and ongoing antiplatelet therapy. CI confidence interval, OR odds ratio, PH parenchymal hemorrhage, sICH symptomatic intracranial hemorrhage *P < 0.001; **P < 0.05 aNLR as a continuous variable bNLR as a dichotomous variable Discussion This study first shows that the NLR is a dynamic variable, and its variation is associated with HT after treatment with IV rtPA in patients with acute stroke. In addition, the best discriminating value of the NLR for PH and sICH was 10.59 or more at 12–18-h post-treatment, which was associated with an 8.50-fold increased risk for PH and a 7.93-fold increased risk for sICH. In previous studies, a high NLR was found to be independently associated with an increased risk of stroke in atrial fibrillation [13]. Moreover, the initial NLR is associated with infarct size and mortality rate in ischemic stroke [6, 7], and it also has predictive value for 90-day outcome after endovascular therapy [8]. However, the previous studies did not explore the clinical value of the NLR in acute ischemic stroke patients treated with IV rtPA. Recently, Maestrini et al. reported that higher neutrophil counts and NLR before thrombolysis for cerebral ischemia are independently associated with sICH and worse outcome at 3 months [14]. However, they did not exclude patients with previous infections, which might contribute to the difference in the predictive values of the baseline NLR for sICH between their study and ours. That is because infections can lead to poor outcome after stroke via many different mechanisms, which may include (1) increased BBB disruption and tissue damage by neutrophil-derived various proteases, reactive oxygen species (ROS), as well as numerous inflammatory mediators; (2) impaired tissue reperfusion through endothelia-dependent mechanisms; (3) increased platelet activation and microvascular coagulation; and (4) CRP-induced ischemic tissue injury via a complement-dependent mechanism [15, 16]. Therefore, this shows that neutrophils are just one of many different mechanisms, and the association between the baseline NLR and endpoints may disappear after adjustment for infections. The reasons for such a difference may also relate to what the NLR represents. Changes observed in the baseline NLR could reflect the disease itself or external environment factors such as infection or cancer. Our results and their conclusions do not contradict per se because their study population is different to ours, with the NLR at baseline reflecting both the disease itself and the external environment factors in their study, but only the disease itself in our study. The study by Maestrini et al. has a higher statistical power than our study based on the larger sample size [14], and we also believe that their results are fully credible and reliable. Higher numbers of baseline neutrophils at baseline have greater potential to induce tissue damage via the release of various proteolytic enzymes, ROS, and numerous inflammatory mediators [2]. Thus, in theory, patients with infection or other conditions that can potentially change baseline the NLR have a higher risk for the occurrence of HT after treatment with IV rtPA. Similarly, when we reintegrate the patients with infection or other conditions with potential to change the NLR into our analysis, the baseline NLR is higher in patients with HT (Additional file 1: Figure S3). Moreover, the neutrophil and lymphocyte counts after ischemic stroke exhibit significant temporal variation [17], which is also indirectly confirmed by Maestrini et al. in their evaluation of the influence of the onset-to-sample time on the neutrophil count, leukocyte count, and NLR [14]. This suggests that the neutrophil count, lymphocyte count, and NLR are “dynamic” variables. However, Maestrini et al. mainly focused on static neutrophil count and NLR values at baseline [14], which may not have dynamically and comprehensively reflected the patients’ conditions. The clinical application value of dynamically testing the neutrophil count, lymphocyte count, and NLR in sICH and worse outcomes may be meaningful. Holding strict exclusion criteria in our study, we found that the NLR changed dynamically and a high NLR at 12–18 h after treatment with IV rtPA was independently associated with HT after IV rtPA. In addition, although there were no differences between the NLR at 12–18 h and the NLR at 36–48 h for auxiliary diagnosis of PH and sICH, we hold that the NLR at 12–18 h may be more valuable than that at 36–48 h. First, the NLR at 12–18 h could be obtained earlier than the NLR at 36–48 h, which could allow for better monitoring and could better reflect the severity and progression of disease, helping clinicians to adjust medication regimens and apply related auxiliary examination in time. Moreover, the NLR at 12–18 h was not inferior to the NLR at 36–48 h, and it exhibited a tendency to rise superior to the NLR at 36–48 h for diagnosing sICH. Therefore, we believe that the NLR at 12–18 h is the appropriate selection based on the main concerns in the present study. The mechanisms underlying these observations are not well established, but they seem to be related to the roles of neutrophils and lymphocytes in ischemic insult and the disruption of the BBB. Circulating neutrophils are recruited to the site of cerebral injury shortly after ischemia occurs and then further contribute to BBB disruption and tissue damage via a variety of mechanisms [18–20]. Neutrophils have been shown to be an important source of MMP-9, which may open the BBB inside the lumen of the blood vessel by acting directly on tight junction proteins or may be absorbed into endothelial cells and act on the basement membrane [2]. In a rat cerebral ischemia model, treatments preventing neutrophil infiltration reduced MMP-9 released in the brain [21]. Moreover, inhibition or depletion of neutrophils can reduce the BBB breakdown and the rate of HT in ischemic stroke [3, 22]. In contrast, when neutrophils are increased via lipopolysaccharide or granulocyte colony-stimulating factor administration, there is an increase in BBB disruption in a mice model [23] and an increase in MMP-9 and rtPA-related HT in a rat stroke model [4]. In humans with ischemic stroke, early neutrophilia is associated with larger infarct volumes [24], and MMP-9-positive neutrophil infiltration has also been associated with disruption of the BBB, basal lamina type IV collagen degradation, and HT [5]. Thus, neutrophils may mediate HT through neutrophil-derived MMPs in ischemic stroke. In addition to neutrophil-derived MMPs, other factors released from neutrophils after stroke [20], including ROS, myeloperoxidase, elastase, cathepsin G, proteinase 3, cytokines, and chemokines, can also disrupt the neurovascular unit and ultimately result in increased BBB permeability and HT [17]. In addition to the mechanisms mediated by factors released from neutrophils, novel aspects of neutrophil biology may also contribute to ischemic brain injury. Recently, activated neutrophils have been described to form neutrophil extracellular traps (NETs), a web-like structure composed of DNA, histones, and specific granule proteins, such as neutrophil elastase and myeloperoxidase, in response to various stimuli [25]. Recent evidence indicates that a lack of NETs during myocardial and liver ischemia/reperfusion (I/R) injury offers significant cardioprotective, hepatoprotective, and anti-inflammatory effects [26, 27]. Furthermore, extracellular chromatin and histones exacerbate cerebral I/R injury in mice [28]. These results suggest that NETs may play a role in BBB disruption and tissue damage. Further studies are needed to explore whether NETs have deleterious effects on HT. The lymphocyte counts might serve as an index for general health, influenced by acute physiologic stress [29]. Relative lymphopenia on the other hand reflects the cortisol-induced stress response and sympathetic tone [30], which can increase the production of proinflammatory cytokines that aggravate ischemic injury [31]. This means that low lymphocyte counts in patients with HT are not merely an initial response to severe stroke, but that lymphocytes may be actively involved in a protective mechanism in the ischemic brain. Experimental evidence suggests that specific subtypes of lymphocytes (namely, regulatory T cells) play key roles in abrogating the inflammatory response and are major cerebroprotective immunomodulators in acute stroke [32]. Our findings suggest that lower lymphocyte counts in patients with HT (data not shown) might have been the result of fewer regulatory T cells being available to curtail the inflammatory response, thereby leading to greater tissue damage. However, other subtypes of lymphocytes (namely, proinflammatory lymphocytes) may have a deleterious effect on I/R injury [33]. It is uncertain which subtype of lymphocytes has a dominant role in the pathophysiology of cerebral ischemia, and we demonstrated that a decrease in lymphocytes as a whole has a negative effect on HT. Further studies are also needed to elucidate the complex immunomodulatory interactions that occur after stroke. The NLR reflects the balance between neutrophil and lymphocyte levels, which may be comprehensively represent the immunological conditions. In this sense, the NLR is superior to only the neutrophil count or lymphocyte count for distinguishing the occurrence of HT, and this may also explain why the AUC for the NLR appeared to be greater than those for neutrophil and lymphocyte counts at each corresponding time point (Additional file 1: Table S4). On the other hand, inflammatory cytokines released by neutrophils may trigger lymphocyte apoptosis [34]. This suggests that the NLR may not simply reflect the neutrophil and lymphocyte counts but also overactivation of neutrophils, thus leading to a wider gap between the two leukocyte types, and this also supports the superiority of the NLR. The main strength of our study is that the clinical information and blood samples taken at different time points from all patients were collected in a prospective fashion with strict exclusion criteria. Previous infections and early hospital infections in stroke are associated with an increase in leukocytes and poor outcomes [14, 35]. We limited these potential confounders by ruling out patients with infection. In addition, our observations of elevated neutrophil counts in patients with HT (data not shown) may offer a partial explanation as to why stroke patients with infection may have poor outcomes. Nonetheless, our current findings also have some limitations. First, the small sample size weakens the statistical strength of our conclusions. Therefore, further studies with larger samples are needed. Second, the study population included patients receiving a bridging strategy of the use of IV rtPA followed by endovascular therapy, which may interfere with our results. Nevertheless, similar results were found for patients experiencing a bridging strategy even if the sample was small (data not shown). On the other hand, this shows that the NLR may also be applicable to distinguish the presence and absence of HT in other reperfusion strategies such as endovascular therapy. Regrettably, a control group that did not experience reperfusion therapy was not included in our study. Third, we neither explored the mechanisms by which neutrophils and lymphocytes affect the BBB breakdown and HT nor investigated what factors regulate the dynamic changes in neutrophil and lymphocyte counts after ischemic stroke in animal studies. These will be the focus of our next work. Conclusions In conclusion, our results suggest that the NLR is a dynamic variable and its variation is associated with the occurrence of HT after thrombolysis in patients with stroke. Additional file Additional file 1: Tables S1 to S3 and Figures S1 to S4. (PDF 461 kb) Abbreviations AUCArea under the curve BBBBlood–brain barrier CIConfidence interval DBPDiastolic blood pressure HTHemorrhagic transformation I/RIschemia/reperfusion INRInternational normalized ratio IQRInterquartile range IV rtPAIntravenous recombinant tissue plasminogen activator IVTIntravenous thrombolysis MMP-9Matrix metalloproteinase-9 NETsNeutrophil extracellular traps NIHSSNational Institutes of Health Stroke Scale NLRNeutrophil to lymphocyte ratio OROdds ratio PHParenchymal hematoma ROCReceiver operating characteristic ROSReactive oxygen species SBPSystolic blood pressure SDStandard deviation sICHSymptomatic intracerebral hemorrhage Acknowledgements Not applicable. Funding This study was supported in part by the National Natural Science Foundation of China (Nos. 81171099, 81501193, and 81471182). The collection of this study was supported in part by the National Natural Science Foundation of China (Nos. 81171099, 81501193, and 81471182). The design of the study and analysis and interpretation of data and writing the manuscript was supported by the National Natural Science Foundation of China (Nos. 81171099 and 81501193). Availability of data and materials The datasets during and/or analyzed during the current study are available from the corresponding author on reasonable request. Authors’ contributions ZLG was responsible for the study design, interpretation of the results, statistical analysis, and manuscript drafting. SHY and LLX were involved in the study design, interpretation of the results, statistical analysis, and critical revision of the manuscript. XC, CSZ, and SPW performed the data collection. RDY, QLD, and WS were involved in the study design and critical revision of the manuscript. PZ was in involved in the critical revision of the manuscript. WSZ and XFL participated in the study design, interpretation of the results, and critical revision of the manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate The study protocol was approved by the Institutional Human Research Ethics Committees of Jinling Hospital and PLA 123 Hospital, and all patients or their relatives gave informed consent. ==== Refs References 1. Emberson J Lees KR Lyden P Blackwell L Albers G Bluhmki E Effect of treatment delay, age, and stroke severity on the effects of intravenous thrombolysis with alteplase for acute ischaemic stroke: a meta-analysis of individual patient data from randomised trials Lancet 2014 384 1929 1935 10.1016/S0140-6736(14)60584-5 25106063 2. Jickling GC Liu D Stamova B Ander BP Zhan X Lu A Hemorrhagic transformation after ischemic stroke in animals and humans J Cereb Blood Flow Metab 2014 34 185 199 10.1038/jcbfm.2013.203 24281743 3. Gautier S Ouk T Petrault O Caron J Bordet R Neutrophils contribute to intracerebral haemorrhages after treatment with recombinant tissue plasminogen activator following cerebral ischaemia Br J Pharmacol 2009 156 673 679 10.1111/j.1476-5381.2009.00068.x 19210512 4. Gautier S Ouk T Tagzirt M Lefebvre C Laprais M Petrault O Impact of the neutrophil response to granulocyte colony-stimulating factor on the risk of hemorrhage when used in combination with tissue plasminogen activator during the acute phase of experimental stroke J Neuroinflammation 2014 11 96 10.1186/1742-2094-11-96 24885160 5. Rosell A Cuadrado E Ortega-Aznar A Hernandez-Guillamon M Lo EH Montaner J MMP-9-positive neutrophil infiltration is associated to blood-brain barrier breakdown and basal lamina type IV collagen degradation during hemorrhagic transformation after human ischemic stroke Stroke 2008 39 1121 1126 10.1161/STROKEAHA.107.500868 18323498 6. Gokhan S Ozhasenekler A Mansur Durgun H Akil E Ustundag M Orak M Neutrophil lymphocyte ratios in stroke subtypes and transient ischemic attack Eur Rev Med Pharmacol Sci 2013 17 653 657 23543449 7. Tokgoz S Keskin S Kayrak M Seyithanoglu A Ogmegul A Is neutrophil/lymphocyte ratio predict to short-term mortality in acute cerebral infarct independently from infarct volume? J Stroke Cerebrovasc Dis 2014 23 2163 2168 10.1016/j.jstrokecerebrovasdis.2014.04.007 25106834 8. Brooks SD Spears C Cummings C VanGilder RL Stinehart KR Gutmann L Admission neutrophil-lymphocyte ratio predicts 90 day outcome after endovascular stroke therapy J Neurointerv Surg 2014 6 578 583 10.1136/neurintsurg-2013-010780 24122003 9. Montaner J Molina CA Monasterio J Abilleira S Arenillas JF Ribo M Matrix metalloproteinase-9 pretreatment level predicts intracranial hemorrhagic complications after thrombolysis in human stroke Circulation 2003 107 598 603 10.1161/01.CIR.0000046451.38849.90 12566373 10. Hacke W Kaste M Fieschi C von Kummer R Davalos A Meier D Randomised double-blind placebo-controlled trial of thrombolytic therapy with intravenous alteplase in acute ischaemic stroke (ECASS II). Second European-Australasian Acute Stroke Study Investigators Lancet (London, England) 1998 352 1245 1251 10.1016/S0140-6736(98)08020-9 11. Hacke W Kaste M Fieschi C Toni D Lesaffre E von Kummer R Intravenous thrombolysis with recombinant tissue plasminogen activator for acute hemispheric stroke. The European Cooperative Acute Stroke Study (ecass) JAMA 1995 274 1017 1025 10.1001/jama.1995.03530130023023 7563451 12. DeLong ER DeLong DM Clarke-Pearson DL Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach Biometrics 1988 44 837 845 10.2307/2531595 3203132 13. Saliba W Barnett-Griness O Elias M Rennert G Neutrophil to lymphocyte ratio (NLR) and risk of first episode stroke in patients with atrial fibrillation: a cohort study J Thromb Haemost 2015 13 1971 1979 10.1111/jth.13006 25988740 14. Maestrini I Strbian D Gautier S Haapaniemi E Moulin S Sairanen T Higher neutrophil counts before thrombolysis for cerebral ischemia predict worse outcomes Neurology 2015 85 1408 1416 10.1212/WNL.0000000000002029 26362283 15. McColl BW Allan SM Rothwell NJ Systemic infection, inflammation and acute ischemic stroke Neuroscience 2009 158 1049 1061 10.1016/j.neuroscience.2008.08.019 18789376 16. Dziedzic T Systemic inflammation as a therapeutic target in acute ischemic stroke Expert Rev Neurother 2015 15 523 531 10.1586/14737175.2015.1035712 25865856 17. Jickling GC Liu D Ander BP Stamova B Zhan X Sharp FR Targeting neutrophils in ischemic stroke: translational insights from experimental studies J Cereb Blood Flow Metab 2015 35 888 901 10.1038/jcbfm.2015.45 25806703 18. Perez-de-Puig I Miro-Mur F Ferrer-Ferrer M Gelpi E Pedragosa J Justicia C Neutrophil recruitment to the brain in mouse and human ischemic stroke Acta Neuropathol 2015 129 239 257 10.1007/s00401-014-1381-0 25548073 19. Neumann J Riek-Burchardt M Herz J Doeppner TR Konig R Hutten H Very-late-antigen-4 (VLA-4)-mediated brain invasion by neutrophils leads to interactions with microglia, increased ischemic injury and impaired behavior in experimental stroke Acta Neuropathol 2015 129 259 277 10.1007/s00401-014-1355-2 25391494 20. Kolaczkowska E Kubes P Neutrophil recruitment and function in health and inflammation Nat Rev Immunol 2013 13 159 175 10.1038/nri3399 23435331 21. Justicia C Panes J Sole S Cervera A Deulofeu R Chamorro A Neutrophil infiltration increases matrix metalloproteinase-9 in the ischemic brain after occlusion/reperfusion of the middle cerebral artery in rats J Cereb Blood Flow Metab 2003 23 1430 1440 10.1097/01.WCB.0000090680.07515.C8 14663338 22. Zhang L Zhang ZG Zhang RL Lu M Krams M Chopp M Effects of a selective CD11b/CD18 antagonist and recombinant human tissue plasminogen activator treatment alone and in combination in a rat embolic model of stroke Stroke 2003 34 1790 1795 10.1161/01.STR.0000077016.55891.2E 12805500 23. McColl BW Rothwell NJ Allan SM Systemic inflammatory stimulus potentiates the acute phase and CXC chemokine responses to experimental stroke and exacerbates brain damage via interleukin-1- and neutrophil-dependent mechanisms J Neurosci 2007 27 4403 4412 10.1523/JNEUROSCI.5376-06.2007 17442825 24. Buck BH Liebeskind DS Saver JL Bang OY Yun SW Starkman S Early neutrophilia is associated with volume of ischemic tissue in acute stroke Stroke 2008 39 355 360 10.1161/STROKEAHA.107.490128 18162626 25. Brinkmann V Reichard U Goosmann C Fauler B Uhlemann Y Weiss DS Neutrophil extracellular traps kill bacteria Science 2004 303 1532 1535 10.1126/science.1092385 15001782 26. Savchenko AS Borissoff JI Martinod K De Meyer SF Gallant M Erpenbeck L VWF-mediated leukocyte recruitment with chromatin decondensation by PAD4 increases myocardial ischemia/reperfusion injury in mice Blood 2014 123 141 148 10.1182/blood-2013-07-514992 24200682 27. Huang H Tohme S Al-Khafaji AB Tai S Loughran P Chen L Damage-associated molecular pattern-activated neutrophil extracellular trap exacerbates sterile inflammatory liver injury Hepatology 2015 62 600 614 10.1002/hep.27841 25855125 28. De Meyer SF Suidan GL Fuchs TA Monestier M Wagner DD Extracellular chromatin is an important mediator of ischemic stroke in mice Arterioscler Thromb Vasc Biol 2012 32 1884 1891 10.1161/ATVBAHA.112.250993 22628431 29. Li Z Cui L Ma J Ma X Li G Association between neutrophil to lymphocyte ratio and atrial fibrillation Int J Cardiol 2015 187 361 362 10.1016/j.ijcard.2015.03.114 25841125 30. Acanfora D Gheorghiade M Trojano L Furgi G Pasini E Picone C Relative lymphocyte count: a prognostic indicator of mortality in elderly patients with congestive heart failure Am Heart J 2001 142 167 173 10.1067/mhj.2001.115792 11431674 31. Park BJ Shim JY Lee HR Lee JH Jung DH Kim HB Relationship of neutrophil-lymphocyte ratio with arterial stiffness and coronary calcium score Clin Chim Acta 2011 412 925 929 10.1016/j.cca.2011.01.021 21266168 32. Liesz A Suri-Payer E Veltkamp C Doerr H Sommer C Rivest S Regulatory T cells are key cerebroprotective immunomodulators in acute experimental stroke Nat Med 2009 15 192 199 10.1038/nm.1927 19169263 33. Liesz A Hu X Kleinschnitz C Offner H Functional role of regulatory lymphocytes in stroke: facts and controversies Stroke 2015 46 1422 1430 10.1161/STROKEAHA.114.008608 25791715 34. Shantsila E Lip GY Stroke in atrial fibrillation and improving the identification of ‘high risk’ patients: the crossroads of immunity and thrombosis J Thromb Haemost 2015 13 1968 1970 10.1111/jth.13121 26303061 35. Tiainen M Meretoja A Strbian D Suvanto J Curtze S Lindsberg PJ Body temperature, blood infection parameters, and outcome of thrombolysis-treated ischemic stroke patients Int J Stroke 2013 8 632 638 10.1111/ijs.12039 23590464

PMC005xxxxxx/PMC5000488.txt

==== Front BMC Infect DisBMC Infect. DisBMC Infectious Diseases1471-2334BioMed Central London 178710.1186/s12879-016-1787-5Research ArticleRisk of MERS importation and onward transmission: a systematic review and analysis of cases reported to WHO Poletto Chiara +33 1 44738436chiara.poletto@inserm.fr 1Boëlle Pierre-Yves 1Colizza Vittoria 121 Sorbonne Universités, UPMC Univ Paris 06, INSERM, Institut Pierre Louis d’épidémiologie et de Santé Publique (IPLESP UMRS 1136), 75012 Paris, France 2 Institute for Scientific Interchange Foundation, via Alassio 11/c, 10126 Torino, Italy 25 8 2016 25 8 2016 2016 16 1 44811 2 2016 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The continuing circulation of MERS in the Middle East makes the international dissemination of the disease a permanent threat. To inform risk assessment, we investigated the spatiotemporal pattern of MERS global dissemination and looked for factors explaining the heterogeneity observed in transmission events following importation. Methods We reviewed imported MERS cases worldwide up to July 2015. We modelled importations in time based on air travel combined with incidence in Middle East. We used the detailed history of MERS case management after importation (time to hospitalization and isolation, number of hospitals visited,…) in logistic regression to identify risk factors for secondary transmission. We assessed changes in time to hospitalization and isolation in relation to collective and public health attention to the epidemic, measured by three indicators (Google Trends, ProMED-mail, Disease Outbreak News). Results Modelled importation events were found to reproduce both the temporal and geographical structure of those observed – the Pearson correlation coefficient between predicted and observed monthly time series was large (r = 0.78, p < 10−4). The risk of secondary transmission following importation increased with the time to case isolation or death (OR = 1.7 p = 0.04) and more precisely with the duration of hospitalization (OR = 1.7, p = 0.02). The average daily number of secondary cases was 0.02 [0.0,0.12] in the community and 0.20 [0.03,9.0] in the hospital. Time from hospitalisation to isolation decreased in periods of high public health attention (2.33 ± 0.34 vs. 6.44 ± 0.97 days during baseline attention). Conclusions Countries at risk of importation should focus their resources on strict infection control measures for the management of potential cases in healthcare settings and on prompt MERS cases identification. Individual and collective awareness are key to substantially improve such preparedness. Electronic supplementary material The online version of this article (doi:10.1186/s12879-016-1787-5) contains supplementary material, which is available to authorized users. Keywords MERSEpidemic preparednessImported casesSecondary transmissionEC-Health278433Colizza Vittoria Agence Nationale de la Recherche (FR)ANR-12-MONU-0018Colizza Vittoria Reacting (INSERM)issue-copyright-statement© The Author(s) 2016 ==== Body Background Concern with the Middle East respiratory syndrome (MERS) remains high among public health authorities worldwide due to the failure to stop the spread of the disease three years after its first description [1]. As of February 2016, 26 countries reported cases, for a total of 1,626 laboratory-confirmed cases of infection with MERS [2]. Cases outside the Middle East region were either travellers or had close contact with imported cases. The majority of case importation events led to little or no secondary transmission, as expected due to the low human-to-human transmission risk [3–7]. Yet, in May 2015, a case imported to South Korea triggered the largest outbreak outside the Middle East, with a total of 186 confirmed cases [2]. This large epidemic was quite unexpected and calls for a better understanding of the potential for MERS dissemination worldwide and risk of onward transmission. It has been proposed that countries having a high risk of MERS importation were those receiving the most air passengers from the Middle East [5, 8]. Joint analysis of incidence data in the Middle East region with international travel flows allowed estimating the expected number of MERS introductions in countries outside the affected area [9, 10], for example on coming back from pilgrimage in Mecca [9] or distinguishing between residents and visitors [10]. In the latter, predictions were based on cumulative attack rates per country in the affected area [10], thus disregarding the strong temporal nature of MERS epidemic [11]. In case of importation of a case, experience has shown that household and nosocomial transmission was possible [12–14] with infrequent large outbreaks as in South Korea [2]. A marked heterogeneity in the epidemic outcome following importation has been observed and characterized by transmission trees in South Korea [15] and theoretical results regarding the potential for multiple generations [16] and role of super-spreading events [16, 17]. Yet a comprehensive understanding of the risk factors for local transmission once a MERS case is imported is still missing. Here we aimed at providing a comprehensive analysis of the risk of MERS importation and subsequent onward transmission through a systematic analysis of all known MERS importation events. We produced predictions based on air traffic data for the risk of MERS importation and estimated the expected number of symptomatic cases imported in countries outside the affected area – here defined as Saudi Arabia, Qatar, Oman, Kuwait, Jordan, United Arab Emirates, Yemen, Bahrain, and also referred to as Middle East. The analysis accounted for seasonal variations of air traffic flows and for temporal and spatial variations of MERS incidence in the Middle East. Predictions were validated against confirmed importations and lack thereof. Focusing on onward transmission, we analysed the risk for local transmission according to sources of heterogeneity in terms of individual awareness (time to hospital admission, declaration of history of travel), country’s reaction (baseline hospital protocols, heightening of infection control strategies), cultural aspects and local customs (e.g. health-seeking behaviour) and phase of the outbreak. We modelled the outcome of importation events according to how cases were identified and managed to provide quantitative estimates on the expected number of secondary cases in the community and in the hospital setting. We finally explored whether MERS awareness in different communities at the time of importation affected case management. Methods Data collection on imported cases Confirmed cases by World Health Organisation (WHO) between September 1, 2012 and July 31, 2015 were considered with the exclusion of repatriations events [18]. We focused on cases with clear and documented travel origin. We thus excluded cases with no association to travel and cases in countries in the Middle East region, here defined as Saudi Arabia, Qatar, Oman, Kuwait, Jordan, United Arab Emirates, Yemen, Bahrain, where continuous sporadic cases are documented. For each importation event, we collected from the scientific literature, Disease Outbreak News of WHO (DON-WHO), and other official public health sources the following information: dates of travel and symptoms onset, date of suspected MERS-CoV infection and date of confirmation, date of hospital admission, date of case isolation or death, declaration of travel history, number of secondary cases generated by the imported case, hospitalization history. Information was primarily extracted by one of us (CP) and double-checked by others (PYB, VC). Model-predicted number of imported cases We modeled imported cases out of Middle East during the same period as above based on air-traffic data and observed incidence in the source region. We used air-traffic worldwide provided by the International Air Transport Association [19]. The dataset refers to 2013 and includes monthly number of origin–destination trips connecting 3362 urban areas distributed on all countries. We extended the dataset to the whole study period by assuming perfect annual periodicity. For reported cases in Middle East we considered the official counts published in the Disease Outbreak News of WHO and recovered from [20, 21]. We aggregated incidence by week and we grouped cases spatially in 20 regions corresponding to the provinces of Saudi Arabia and the other countries. We computed the number of MERS-CoV infections exported each week to a destination country outside Middle East assuming that infected individuals have the possibility to travel before hospitalized. We accounted for the distribution of time from infection to hospitalization, computed as the convolution of the incubation period distribution and that of onset to hospitalization (see Additional file 1 for the details). To estimate actual number of importations we adjusted incidence in Middle East for reporting ratio. The latter was computed by assuming 100 % detection accuracy in imported cases in European and North-American countries, where alertness and surveillance have been high to detect importations [22–24]. Eventually, we computed the predictive probability of the weekly number of importation cases worldwide depending on how many cases were reported in the Middle East in the past month. Further details are reported in the Additional file 1. Risk of transmission following importation We studied the factors affecting the risk of transmission following importation. We used bias reduced logistic regression to analyse the outcome of each imported case, classified as “with secondary case” vs. “without secondary case” [25]. We then modelled the number of secondary cases following importation assuming a Poisson process. Several versions of the model were explored to test potential determinants of the observed heterogeneity in transmission. The first factor considered was the presence/absence of dependence of transmission on the setting (community vs. hospital), as accounted for by models S+ and S- respectively. We then considered possible dependence on the total duration of the transmission risk period (with, model D+, vs. without, model D-). This was defined as the duration from symptoms onset or date of travel, if travelling after symptoms onset, to isolation or death. For models S+ we used setting-specific transmission risk periods. Eventually we compare presence/absence of heterogeneity in transmission between patients (with, model P+, vs. without, model P-). The decomposition tested in the models accounts for the aspects that were shown to be relevant in the heterogeneity of transmission by the risk analysis. Notice that in all models tested we assumed that no transmission is possible after patient isolation. To account for duration we set the mean of the Poisson distribution to μCdC + μHdH, where dC and dH were the number of days in the community and in hospital, and μC and μH the average number of secondary cases per day in each setting. Overdispersion in transmission was introduced by replacing μH with a Gamma-distributed random parameter mH with mean μH and standard deviation σH. We further distinguished between a model with over-dispersion of transmission only in the hospital (P+/D+/S+), and a model accounting for such a level of heterogeneity in both hospital and community (P++/D+/S+). All listed transmission hypotheses yielded 8 different models that were fitted to the data and compared by the Akaike Information Criterion (AIC). More details on the analysis are reported in the Additional file 1. Collective attention and awareness and relation with imported case history As possible external factor affecting the history of importation events, we studied the effect of attention or awareness as obtained from various digital sources. We focused on three indicators: the popularity of the search query [“novel coronavirus” OR “MERS-CoV”] in Google Trends, as an indicator for collective attention in the general public; the number of alerts published by ProMED-mail with the same keywords, as an indicator of attention in the international infectious disease community; and the number of DON on MERS published by WHO, as an indicator of official source of information for public health authorities. Each source provided a time-series spanning the whole study period; values were scaled to range between 0 and 1 at the time-series maximum. For each indicator, we computed the correlation coefficient between the time spent in the community or in the hospital and the attention level at the occurrence date of these events. We defined periods of high attention as those where the indicator value was in its upper quartile distribution. We compared the length of the periods spent in the community or in the hospital before isolation occurring in high attention periods or in the remaining baseline periods. Alternative definitions of the threshold for high attention periods were tested (Additional file 1). Results Risk of MERS importation A total of 22 importation events were reported worldwide (see Table 1 and Additional file 1): nine in Europe (41 %), six in Asia (27 %), five in Africa (23 %), and two in North America (9 %). All cases were symptomatic. Confirmed secondary cases following importation were observed on four occasions (two in Europe, one in Africa, and one in Asia). Two further secondary cases in Italy were not confirmed by WHO [18, 26, 27] and were only investigated in the sensitivity analysis. Exception made for the CH1 case who travelled from South Korea, all cases were originating from Middle East. Importation events were reported throughout the whole study period, with half of them occurring during 2014. Cases with associated confirmed transmissions following importation occurred during 2013 (UK1, FR1, TUN1) and 2015 (SK1). Timeline of importations is summarised in Fig. 1a.Table 1 Case importation events of MERS to countries outside of the Middle East region # Case ID Country Date of travel Date of onset of symptoms Date of MERS confirmation Sec. cases 1 UK1 United Kingdom 28/1/13 24/1/13 8/2/13 2 2 FR1 France 17/4/13 22/4/13 7/5/13 1 3 IT1 Italy 25/5/13 24/5/13 31/5/13 0 4 TUN1 Tunisia 28/4/13 28/4/13 8/5/13 1 5 TUN2 Tunisia 10/5/13 11/5/13 16/5/13 0 6 MA1 Malaysia 28/3/14 04/4/14 14/4/14 0 7 G1 Greece 17/4/14 prior to traveling 18/4/15 0 8 EG1 Egypt 25/4/14 22/4/14 26/4/14 0 9 US1 United States 24/4/14 18/4/14 2/5/14 0 10 US2 United States 1/5/14 1/5/14 9/5/14 0 11 NETH1 The Netherlands 10/5/14 01/5/14 13/5/14 0 12 NETH2 The Netherlands 10/5/14 05/5/14 14/5/14 0 13 AL1 Algeria 28/5/14 23/5/14 30/5/14 0 14 AL2 Algeria 29/5/14 23/5/14 30/5/14 0 15 A1 Austria 22/9/14 prior to traveling 29/9/14 0 16 TUR1 Turkey 6/10/14 25/9/14 - 0 17 PH1 Philippines 1/2/15 26/1/15 10/2/15 0 18 GE1 Germany 8/2/15 11/2/15 7/3/15 0 19 SK1 South Korea 4/5/15 11/5/15 20/5/15 31 20 CH1 China 26/5/15 21/5/15 28/5/15 0 21 TH1 Thailand 15/6/15 10/6/15 18/6/15 0 22 PH2 Philippines 19/6/15 30/6/15 4/7/15 0 Fig. 1 MERS importation events. a Timeline of confirmed importation events. The height of the bar is proportional to the number of importations registered in the month, and imported cases’ IDs are listed close to the bar. Importation events causing secondary transmissions are highlighted with a box. All cases originated from travels from the Middle East (red bars), except the case imported in China (CH1, blue bar) who travelled from South Korea. b Expected weekly number of MERS exportation to countries out of Middle East as a function of time. The average weekly number of exportations is indicated with the dashed line. Blue diamonds indicate observed exportations (detailed in panel a) The comparison between predicted and observed exported cases from Middle East is reported in Fig. 1b. Confirmed MERS importations occurred when computed expected number of cases was large. The Pearson correlation coefficient between the observed and predicted number of cases flying out of the Middle-East region each month was 0.78 (p < 10− 4). At the country level (Fig. 2a), we found that countries experiencing importation cases had indeed a higher expected probability of importing a case (Wilcoxon test p < 10− 4). Five of the ten countries with the highest probability of importing cases actually reported importation cases: these were mostly European countries. The remaining five did not report importation cases despite being at high risk of importation: these included countries in South-East Asia (e.g. India, Pakistan, Indonesia and Bangladesh). Observed number of importation cases matched prediction in all countries, except for India, Egypt and Pakistan (Fig. 2b). Among European and North-American countries observed importations were even more strongly associated with model predictions: 100 % of the top five countries registered at least one case, and 70 % of top ten, see Additional file 1: Figure S2.Fig. 2 MERS importations by country. a Risk of importation by country worldwide. Confirmed importations are signalled by black symbols. b Observed vs. predicted number of MERS imported cases by country over the whole study period. Top 50 countries ranked by the predicted number of importations are shown (including all reported importations). Bars indicate the 95 % prediction interval Building on the good agreement between observed and predicted cases worldwide, we analyse the risk of importation events that would be expected according to a given disease activity in the Middle East. Figure 3 reports the probability of observing at least one imported case in each continent according to the number of cases observed in the Middle East over the last month (see Additional file 1: Figure S3 for predicted number of importations). Following a month with increased disease incidence in the Middle-East (more than 100 cases – for example April 2014 or August 2015), the probability of having at least 1 case would be 64 % in Asia, 32 % in Africa, 18 % in Europe, 7 % in the Americas and 0 in Oceania.Fig. 3 Probability of observing at least one case within a week as a function of the observed epidemic activity at the source in the preceding month. Different curves correspond to different continents Risk of transmission following importation For each MERS-confirmed imported case, we reconstructed the detailed case history (Fig. 4). In the four events where local transmission was confirmed, the duration of the transmission risk period, from symptoms onset or date of travel if symptomatic to isolation or death, was longer than in others (11.8 days vs. 5.4, p = 0.007). FR1, SK1, and UK1 were characterised by a long hospitalisation period (ten days for UK1, nine days for FR1 and SK1) and a short period in the community (two days or less). TUN1 showed a longer period in the community (eight days) than in the hospital (six days). Importation events with no local transmission had shorter duration of hospitalisation on average (2.9 vs. 8.5 days). The number of visited hospitals prior to isolation ranged between one and four (four visited by SK1).Fig. 4 Case history of MERS importations. Cases are aligned to the beginning of the infectious risk period, i.e. the most recent between the importation date and the date of symptoms onset. Days in the infection risk period are color-coded according to the patient’s history, ending with isolation (dark red) or death (black). Importation events are sorted by duration of the infection risk period. Where no information was available on time of isolation, we assumed infection risk period to end with case confirmation. A box is used to highlight cases that led to secondary transmission Results of the bias reduced logistic regression show that imported cases with the longest transmission risk period more frequently had secondary cases (OR = 1.7, CI 95 % [1.2,6.7]), all the more when more time was spent in the hospital (OR = 1.7 [1.2,7.3]). Number of clinics visited was also associated to increased risk of transmission. The small sample made it difficult to conclude for other characteristics, although it suggested an increased probability for secondary cases if onset occurred after travelling, and if history of travel to the Middle East region was not reported (Table 2).Table 2 Risk factors for secondary cases after importation (univariate analysis) Variable OR 95 % CI P Onset before importation 0.2 [0.00, 1.7] 0.19 Infection risk period (per day) 1.7 [1.2, 6.7] 0.04 Time before hospitalization (per day) 1.1 [0.7, 1.6] 0.62 Time in the hospital (per day) 1.7 [1.2, 7.3] 0.02 Number of visited healthcare facilities 3.3 [1.2, 25.4] 0.05 Declared history of travela (No vs. Yes) 8.2 [0.32, 625] 0.21 ainformation available for 15 cases out of 22 Results of the AIC comparison among transmission models are reported in Table 3. We found that the models allowing over-dispersion of transmission in the hospital provided a better fit to the data. The best fit was obtained with model P+/D+/S+. Model P+/D+/S-, where transmission in and outside the hospital was similar, performed nearly as well as the best model. Model P++/D+/S+, where overdispersion was present in the community and in the hospital performed more poorly, essentially because the variance of the random coefficients was not well estimated. Community parameters were estimated with a very large variance showing that the likelihood was almost flat and the model difficult to identify.Table 3 AIC values for all model tested Model AIC P D S - - - 197.1 - + - 150.0 - + + 141.1 + - - 45.5 + + - 43.4 + + + 43.3 ++ + + 46.0 Parameters estimated with the two best fitting models are listed in Table 4. In the best fitting model estimated average daily secondary cases was ten times smaller in the community than in the hospital. The importation events causing secondary transmissions had larger model-predicted probabilities of transmission (Fig. 5). Finally, the model showed that most importations were likely to cause less than five secondary cases, especially when time to isolation was short. It also showed that outbreaks leading to more than 30 cases were possible, although with a relatively small probability (1–5 % predicted for the South Korean episode). In model P+/D+/S-, the probabilities of a large number of secondary cases following importation were larger than in the best fitting model (see Additional file 1: Figure S4).Table 4 Parameters estimated for the two best fitting models Model Parameters P D S μC μH σC σH + + - 0.15 [0.04,1.69] 0.53 [0.16, 8.7] + + + 0.02 [0.0, 0.12] 0.20 [0.03, 9.0] - 0.73 [0.20, 75.0] Fig. 5 Model-predicted probability of secondary cases after importation. (left, middle) Model predicted probability of at least one secondary case (left), of more than one secondary case (middle) as a function of the time spent in the community and in the hospital prior to isolation or death. In red countries that experienced local transmission generating at least one secondary case (left) or more than one secondary case (middle). (right) Model predicted probability of the number of secondary cases as a function of the time spent in the hospital, assuming 3 days in the community before hospitalisation Accounting for the unconfirmed secondary cases in Italy yielded similar association between infectious risk period and increased transmission risk, but less marked evidence for setting-specific differences in transmission (Additional file 1). Collective attention and awareness and relation with imported case history Trends of attention measured by the three indicators showed similar profiles, with periods of high popularity interspersed within periods of lower attention in the various sources (Fig. 6a). The correlations between indicators were large, ranging between 0.65 (Google Trends vs. DON-WHO, p < 10− 4) and 0.86 (ProMED-mail vs. DON-WHO, p < 10− 4). The latter is expected as ProMED-mail contains all news of DON-WHO. ProMED-mail and DON-WHO showed more variation over time than Google Trends, where fewer and more distinct peaks were observed. Peaks were more likely to occur following MERS related events (Fig. 6a), such as e.g. the confirmation of MERS infection in imported cases worldwide (UK1, FR1) or the outbreaks in Saudi Arabia (Spring 2014 and February 2015) [2].Fig. 6 Relation between attention and time from hospitalisation to isolation. a Attention as measured by Google Trends, ProMED-mail and DON-WHO from January 2013 to July 2015. Dates corresponding to specific epidemic events are shown on the top of the plot. b Duration of hospitalisation versus attention (from the Google Trends indicator) at the time of admission to the hospital. c Timeline of attention (Google Trends, right axis) and duration from hospitalisation to isolation for each imported case (left axis), at the time of admission to the hospital. Periods of high attention are indicated by vertical shaded areas. Importation events are coloured according to attention level at their time of hospitalisation (red for high attention, orange otherwise). d Average duration from hospitalisation to isolation in periods of high and baseline attention for three indicators (GT= Google Trends, DON= Don of WHO, PM= ProMED-mail). Error bars show standard errors We compared the length of the periods spent in the community or in the hospital before isolation with the attention level at the occurrence date of these events. The duration from hospitalisation to isolation was larger in periods of low attention for all three indicators. The correlation coefficient was -0.66 (p = 0.001) between duration and Google Trends attention level (Fig. 6b), -0.69 (p = 0.0005) for ProMED-mail, and -0.58 (p = 0.005) for DON-WHO (Additional file 1: Figure S5). More precisely, we found that the imported cases in Italy (IT1), Greece (G1), United States (US1 and US2), Algeria (AL1 and AL2), Egypt (EG1), the Netherlands (NETH1 and NETH2), Germany (GE1), Thailand (TH1), and Philippines (PH2), all hospitalised during periods of high attention (Fig. 6c), had average time from hospitalisation to isolation of 2.33 ± 0.34 days compared to 6.44 ± 0.97 days computed for cases occurring when attention was lower (Fig. 6d). All indicators of attention yielded similar results, with more rapid isolation in periods of high attention (Fig. 6d). Two cases occurring outside Google Trends high attention periods were nevertheless isolated quickly and captured by the other indicators (CH1 occurring in a period of high attention for ProMED-mail and DON-WHO, MA1 during high attention for DON-WHO). There was no substantial difference when criteria for the calculation of the moving average and thresholds defining high attention were varied (Additional file 1). Attention was not found to impact duration of the community period. For the case of attention measured by Google Trends, for example, we obtained a Pearson correlation coefficient between attention and length of stay in the community equal to 0.22 (p = 0.32). Average values in periods of high and baseline attention were respectively 2.85 ± 0.83 and 2.44 ± 0.74. Also in this case results were robust in varying criteria for the moving average calculation and the high attention definition. Discussion The large number of cases reported in the South Korean outbreak following a MERS case importation generated substantial concern on the risks that countries face towards importation and possible onward transmission. Our quantitative analysis provide important information that can help preparedness and response to such events: MERS international dissemination is strongly associated to air travel flows combined with cases incidence in the source area; transmission is more likely to occur in hospitals; large outbreaks are possible though rare; and high attention to MERS epidemic in the public and among professionals lead to efficient case management. The role of air travel as driver for pathogen international dissemination has been considered in several prospective studies [28–37], with few retrospective validations [33, 38–42]. For the case of MERS [5, 8–10], qualitative comparisons between predictions and observed importations were presented [9, 10]. Our analysis produces the first quantitative assessment of the accuracy of model predictions for the risk of importation worldwide accounting for all countries with and without reported importations. In addition, importation risk and expected number of imported cases is evaluated across time. The temporal factor is often neglected when dealing with subcritical epidemic as in the case of MERS and overall attack rates are generally considered [10]. MERS epidemic was shown however to display a strong temporal component, both in the zoonotic and human-to-human transmission [11]. Here we found indeed that such temporal variation also affects the expected number of exportations from the Middle East region. The largest concentration of exportations (nine episodes from March to May 2014) occurred during the outbreaks affecting the provinces of Riyadh and Makkah in Saudi Arabia in Spring 2014, causing a 18-fold increase in the expected number of exportations. Spatial resolution is also important, as already highlighted in [10] with a country-level description. Here we considered a total of 20 regions in the affected area, including the countries of Saudi Arabia, Qatar, Oman, Kuwait, Jordan, United Arab Emirates, Yemen, Bahrain similarly to [10], and additionally disaggregating Saudi Arabia into its 13 provinces [11]. A further element of novelty of the present study is its ability to provide projections on the expected number of importations by country with no prior knowledge on either MERS epidemiology or under-reporting ratio. This is possible by relying on three main assumptions: (i) 100 % detection accuracy of MERS surveillance in countries of European Union and North America; (ii) uniform under-reporting of cases in the affected area in time and space [11]; (iii) homogeneous mixing between travellers and local residents. The third assumption may be responsible for some of the limitations of the model. The major discrepancy we found between predictions and observations is the large risk of importation predicted for India, Pakistan, and Indonesia, though these countries did not report any MERS case. This was also observed in [10]. It may suggest that cases were imported in these countries but went undetected. However it may also be due to non-homogeneity in the mixing or travel behaviour of classes of individuals, namely travellers to the affected area vs. region residents, that is known to impact the conditions for pathogen dissemination [43]. Non-homogeneous mixing may affect travellers’ probability to be infected by the virus because of altered risk of contact with zoonotic sources or of exposure to nosocomial outbreaks. This may vary among travellers and be related for instance to different purpose of visit (e.g. short-visit tourists vs. seasonal workers). The similarity of findings regarding high-risk countries between our study and previous work [10], notwithstanding different modelling assumptions, suggests that country-specific aspects may be determinant for the observed discrepancy. On one side there is a surveillance system whose accuracy may vary by country. On the other, purpose of visit and associated mixing may be country-related. India, Pakistan, and Indonesia are indeed in the top 4 nationalities in the expat community in Saudi Arabia [44]. The detailed analysis of the history following importation provided important findings on the risk of a local outbreak generated by an infected traveller. While no secondary cases were reported in the majority of observed importation events, four events led to one (in two instances), two, or 31 secondary cases. This heterogeneity was captured by our models through large overdispersion in transmission, in agreement with previous works [15–17]. Our findings suggest that the probability to observe a future MERS importation leading to a number of secondary cases larger than the South Korean one is of the order of 1-5 %, consistent with prior work on the full nosocomial South Korean outbreak [15]. In line with another study, the risk of observing a secondary case is predicted to be larger than 20 % if isolation in hospital is not fast (>one week), independently of the time spent in the community [16]. The observed variability in epidemic outcomes may result from at least four characteristics. First, the duration of the transmission risk period in the destination country, from date of importation or symptoms onset to isolation or death, is clearly an important risk factor for local transmission. The longer the transmission risk period, the larger are the opportunities for susceptible individuals to be exposed to the infectious case, both in the community and after hospitalization. Second, nosocomial transmission of MERS appeared more efficient than transmission in the community. This points to the need for focusing interventions on rapid case identification and effective isolation and for improving infection control protocols in hospitals to prevent transmission. The large outbreak observed in South Korea was indeed attributed to sub-optimal infection prevention and control measures in hospitals [45]. These findings are in line with previous analyses on MERS transmission in healthcare settings and with modelling studies evaluating the impact of mechanisms to control SARS spread in 2003 [15, 46–48]. The third aspect pertains to heterogeneity in case finding and management. For example, imported cases could visit one to four health-care facilities before getting a diagnosis. This behaviour may be based on individuals’ decisions but it may also be induced by country-specific regulations of the national health-care system that determines how patients can access professionals or it may be influenced by local customs. This behaviour was found to be associated with a higher probability of secondary transmission in our study, indicating that the local practice of seeking care in multiple health-care facilities may have contributed to the initial spread in South Korea, in agreement with the findings of Ref. [45]. The fourth aspect is represented by lack of individual awareness regarding the potential risk that was found to be a contributing factor increasing transmission risk. Indeed, not reporting a history of travel to the health practitioners increased the probability of having secondary cases (although not statistically significant). For emerging diseases whose non-specific symptoms preclude a fast diagnosis, travel history is a critical element for patient assessment. Moreover, cases who experienced onset of symptoms before importation were less likely to generate secondary cases. Traveling while ill from a country where a MERS outbreak is ongoing increased individual awareness on the infection risk and induced a more precautionary individual behaviour. Clearly, these two aspects are correlated, as 70 % of the cases who declared history of travel also travelled while ill. We explored three digital indicators for collective attention and awareness corresponding to different communities: general population, professionals and health authorities. Digital sources have been recently used in the context of early detection and surveillance [49, 50]. They have also been used as a source to study public concern in response to an ongoing epidemic threat [49, 51]. Our analysis showed that general public’s attention measured by Google Trends is highly correlated with the amount of news circulating amongst the international infectious disease community (ProMED-mail) and of official reports published by the WHO. Its curve in time shows the presence of high peaks followed by a quick decline. This is a common behaviour generally found in the social media response following specific triggering events [49, 52, 53]. In our study, events triggering collective attention can be identified with unexpected episodes of case importations or resurgence of the epidemic in the affected area. Here we found that MERS confirmation and isolation during peaks of collective attention were considerably faster. This suggests that an increased collective awareness may induce changes in the management of the patient allowing the health system to successfully reduce the time from admission to isolation. Being this time critical for transmission risk, increased awareness is identified as a key factor to control the generation of cases after MERS importation. Similar results were also obtained for the indicators measuring awareness in the public health and infectious diseases community. The case importation in South Korea occurred when attention was at its baseline level (as measured by all indicators), and indeed it was reported that MERS appearance was “unfamiliar to most physicians” in the country [54]. No correlation was found instead between collective attention and time to admission. This suggests that collective attention may preferably act on the case management by health authorities, whereas individual awareness may more likely be responsible for individual change of health-seeking behaviour, as discussed previously. The impact of collective awareness and public health mobilization strategies in response to an epidemic has already been observed in past outbreak. As SARS outbreak progressed, reduced duration from onset to hospital admission and reduced number of hospital visits per patient were observed due to overall increased awareness and public health recommendations [47, 55–57]. Similarly, during the South Korean outbreak of MERS, infection control measures strengthened, and the delay from illness onset to confirmation shortened as the epidemic progressed [58, 59]. There are however two important differences between our findings and the above. First, awareness and concerns are known to be stronger for the population experiencing the outbreak (as in the above cases) than for yet unaffected populations (as in our study) [53]. Nonetheless, our findings show that higher awareness, even when induced by non-local events, allow countries to better manage an importation episode. Second, here we were able to explicitly measure awareness in time and relate it to a quantifiable change of behaviour (case management), further illustrating its impact on transmission. From the use of surveys to digital data, quantifying awareness has become an important aspect of epidemic surveillance and control [49, 51, 60–62]. Few studies have however measured how variation in awareness affects an epidemic during its course [50, 63]. Moreover, MERS poses additional challenges as public attention is known to wane rapidly in response to external events [64] unless it is prompted by additional triggering events or mounting concern, as it happened with the rapidly increasing number of cases of Ebola epidemic [5]. The subcritical nature of MERS epidemic, with an incidence characterized by subcritical spread and sporadic peaks [11], induces a similarly fragmented timeline of attention. For example, the large peak of Spring 2014 increased the risk of MERS dissemination. The management of imported cases during that period however benefited from an increased attention to the disease epidemic, and no secondary transmission was observed. Conversely, despite the risk of importation was much lower during the beginning of 2012 and Spring 2015, the few importations observed during that period were able to initiate local transmission and threaten the health security of the destination countries. By analysing the various aspects characterizing the epidemic, our analysis is able to identify the factors that may help improving the reaction of countries at risk of importation. Other limitations of our study need to be mentioned. We assumed that no importation events had been missed in Europe and estimated under-reporting in the Middle-East accordingly. However, if 1 importation case had been missed in Europe, underreporting would be 25 % rather than 18 %, and the model-predicted number of cases worldwide increase by 10 % over the period. If one further assumes that secondary transmission was unlikely for these unrecognized cases, the probability of transmission following importation would be overestimated. For example, taking the model-predicted number of importation cases worldwide for the period as exact, the probability of local transmission would have been 6 % (4 among 70) rather than the current 18 % (4 among 22). Furthermore, the second best-fitting model among the ones considered for transmission following importation, with only marginally larger AIC, did not support setting-specific transmission. Our main result is however in line with previous findings on nosocomial transmission of MERS in the Middle East [15]. In addition, there were two secondary cases in the Italian episode that were not confirmed by official sources. Including these two cases in the analysis, we still found that longer time to isolation was associated with more secondary transmission, although evidence on setting-specific differences in transmission was less marked (see Additional file 1). Conclusions We evaluated the risk of MERS exportation worldwide integrating seasonal air traffic flows and time-varying incidence of cases in the affected area, and accounting for under-reporting of cases. We conducted a comprehensive analysis of all reported MERS imported cases to validate modelled importation risk and assess onward transmission. Our findings confirm the critical role of air travel in the risk of international dissemination. In case of MERS introduction, prompt identification of the infection in patients seeking medical attention, strict infection control measures, and effective isolation of the patient in the nosocomial setting are key to efficient prevention and control of the outbreak. Increasing awareness at collective and public health levels worldwide is found to be associated with higher local preparedness, prompter and strengthened precautionary measures and isolation procedures to prevent further spread. Our findings provide a quantitative assessment for public heath authorities to face the variability associated to importation risk and potential for local transmission, to inform preparedness plans, and identify the critical measures that should be considered to reduce the likelihood of future outbreaks. Additional files Additional file 1: The file contains detailed information on importation event history, detailed explanation of the statistical analysis, sensitivity analysis. (PDF 6580 kb) Additional file 2: The file contains timeline of attention from the three digital sources considered in the paper. (XLSX 40 kb) Acknowledgements Not applicable. Funding We receive funding from the EC-Health Contract No. 278433 (PREDEMICS); the ANR Contract No. ANR-12-MONU-0018 (HARMSFLU); Reacting (INSERM). Availability of data and materials The present study rests on publicly available sources and scientific literature for the history of importation events. These data are integrated and organised in table in the article and in the Additional files 1. Collected data of attention for the three digital sources are provided in the Additional file 2. Authors’ contributors All authors conceived and designed the study, collected the data, analyzed the data and wrote the manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate Not applicable. ==== Refs References 1. World Health Organization WHO statement on the tenth meeting of the IHR Emergency Committee regarding MERS [Internet] 2015 2. World Health Organization. Middle East respiratory syndrome coronavirus (MERS-CoV) [Internet]. Available from: http://www.who.int/emergencies/mers-cov/en/ Accessed 20 Jan 2016. 3. Breban R Riou J Fontanet A Interhuman transmissibility of Middle East respiratory syndrome coronavirus: estimation of pandemic risk Lancet 2013 382 9893 694 9 10.1016/S0140-6736(13)61492-0 23831141 4. Cauchemez S Fraser C Van Kerkhove MD Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility Lancet Infect Dis 2014 14 1 50 6 10.1016/S1473-3099(13)70304-9 24239323 5. Poletto C, Pelat C, Levy-Bruhl D, Yazdanpanah Y, Boelle PY, Colizza V. Assessment of the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic in the Middle East and risk of international spread using a novel maximum likelihood analysis approach. Euro Surveill. 2014;19(23). 6. Majumder MS, Rivers C, Lofgren E, Fisman D. Estimation of MERS-Coronavirus Reproductive Number and Case Fatality Rate for the Spring 2014 Saudi Arabia Outbreak: Insights from Publicly Available Data. PLoS Curr Outbreaks. 2014. doi: 10.1371/currents.outbreaks.98d2f8f3382d84f390736cd5f5fe133c. 7. Chowell G Blumberg S Simonsen L Miller MA Viboud C Synthesizing data and models for the spread of MERS-CoV, 2013: key role of index cases and hospital transmission Epidemics 2014 9 40 51 10.1016/j.epidem.2014.09.011 25480133 8. Khan K, Sears J, Hu VW, et al. Potential for the international spread of middle East respiratory syndrome in association with mass gatherings in saudi arabia. PLoS Curr Outbreaks. 2013. doi: 10.1371/currents.outbreaks.a7b70897ac2fa4f79b59f90d24c860b8. 9. Lessler J, Rodriguez-Barraquer I, Cummings DAT, Garske T, Van Kerkhove M, Mills H, et al. Estimating Potential Incidence of MERS-CoV Associated with Hajj Pilgrims to Saudi Arabia, 2014. PLoS Curr Outbreaks. 2014. doi: 10.1371/currents.outbreaks.c5c9c9abd636164a9b6fd4dbda974369. 10. Carias C, O’Hagan JJ, Jewett A, Gambhir M, Cohen NJ, Haber Y, et al. Exportations of symptomatic cases of MERS-CoV infection to countries outside the Middle East. Emerg Infect Dis. 2016. http://dx.doi.org/10.3201/eid2204.150976. 11. Poletto C Colizza V Boelle PY Quantifying spatiotemporal heterogeneity of MERS-CoV transmission in the Middle East region: A combined modelling approach Epidemics 2016 15 1 9 10.1016/j.epidem.2015.12.001 27266844 12. Health Protection Agency (HPA) UK. Novel Coronavirus Investigation team. Evidence of person-to-person transmission within a family cluster of novel coronavirus infections, United Kingdom, February 2013. Euro Surveill. 2013;18(11). 13. Mailles A, Blanckaert K, Chaud P, van der Werf S, Lina B, Caro V, et al. First cases of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infections in France, investigations and implications for the prevention of human-to-human transmission, France, May 2013. Euro Surveill. 2013;18(24). 14. Abroug F Slim A Ouanes-Besbes L Hadj Kacem M-A Dachraoui F Ouanes I Family cluster of Middle East respiratory syndrome coronavirus infections, Tunisia, 2013 Emerg Infect Dis 2014 20 9 1527 30 10.3201/eid2009.140378 25148113 15. Chowell G Abdirizak F Lee S Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study BMC Med 2015 13 210 10.1186/s12916-015-0450-0 26336062 16. Nishiura H, Miyamatsu Y, Chowell G, Saitoh M. Assessing the risk of observing multiple generations of Middle East respiratory syndrome (MERS) cases given an imported case. Euro Surveill. 2015;20(27). 17. Kucharski AJ Althaus CL The role of superspreading in Middle East respiratory syndrome coronavirus (MERS-CoV) transmission Euro Surveill 2015 20 25 14 8 10.2807/1560-7917.ES2015.20.25.21167 26132768 18. WHO. Summary of Current Situation, Literature Update and Risk Assessment [Internet]. WHO; 2015. Available from: http://www.who.int/csr/disease/coronavirus_infections/risk-assessment-7july2015/en/. Accessed 19 Jan 2016. 19. International Air Transport Association. [http://www.iata.org]. Accessed 27 Jan 2016. 20. Rambaut A. MERS-cov Spatial Temporal and Epidemiological Information. Available from http://epidemic.bio.ed.ac.uk/coronavirus_background. Accessed 19 Nov 2015. 21. Flutrackers. 2012-2016 Case List of MoH/WHO Novel Coronavirus MERS nCoV Announced Cases. . Available from https://flutrackers.com/forum/forum/novel-coronavirus-ncov-mers-2012-2014/146270-2012-2016-case-list-of-moh-who-novel-coronavirus-mers-ncov-announced-cases Accessed 19 Jan 2016. 22. Centers for Disease Control and Prevention (CDC). Middle East Respiratory Syndrome (MERS) [internet]. Available from : http://www.cdc.gov/coronavirus/mers/index.html Accessed 27 Jan 2016. 23. European Centre for Disease Prevention and Control. Coronavirus Infections [internet]. Available from: http://ecdc.europa.eu/en/healthtopics/coronavirus-infections/Pages/index.aspx Accessed 27 Jan 2016. 24. Public Health Agency of Canada. Middle East Respiratory Syndrome (MERS) [internet]. Available from: http://healthycanadians.gc.ca/diseases-conditions-maladies-affections/disease-maladie/middle-east-respiratory-syndrome-respiratoire-moyen-orient/index-eng.php Accessed 27 Jan 2016. 25. Kosmidis I Firth D Bias reduction in exponential family nonlinear models Biometrika 2009 96 793 804 10.1093/biomet/asp055 26. Puzelli S Azzi A Santini M Di Martino A Facchini M Castrucci M Investigation of an imported case of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infection in Florence, Italy, May to June 2013 Eurosurveillance 2013 18 34 20564 10.2807/1560-7917.ES2013.18.34.20564 23987829 27. WHO. Middle East respiratory syndrome coronavirus (MERS-CoV) - update 20 September 2013 [Internet]. WHO; 2015. Available from: http://www.who.int/csr/don/2013_09_20/en/. Accessed 19 Nov 2015. 28. Cooper BS Pitman RJ Edmunds WJ Gay N Delaying the international spread of pandemic influenza PLoS Med 2006 3 e12 10.1371/journal.pmed.0030212 16435888 29. Ferguson NM Cummings DAT Fraser C Cajka JC Cooley PC Burke DS Strategies for mitigating an influenza pandemic Nature 2006 442 448 452 10.1038/nature04795 16642006 30. Epstein JM, Goedecke M, Yu F, Morris RJ, Wagener DK, Babashev GV. Controlling pandemic flu: the value of international air travel restrictions. PLoS ONE. 2:e401. 31. Fraser C Donnelly C Cauchemez S Hanage W Van Kerkhove M Hollingsworth T Pandemic potential of a strain of influenza A/H1N1: early findings Science 2009 324 1557 1561 10.1126/science.1176062 19433588 32. Balcan D Hu H Gonçalves B Bajardi P Poletto C Ramasco JJ Seasonal transmission potential and activity peaks of the new influenza A/H1N1: a Monte Carlo likelihood analysis based on human mobility BMC Med 2009 7 45 10.1186/1741-7015-7-45 19744314 33. Bajardi P Poletto C Ramasco JJ Tizzoni M Colizza V Vespignani A Human mobility networks, travel restrictions and the global spread of 2009 H1N1 pandemic PLoS One 2011 6 e16591 10.1371/journal.pone.0016591 21304943 34. Poletto C Gomes MF Pastore Y Piontti A Rossi L Bioglio L Chao DL Assessing the impact of travel restrictions on international spread of the 2014 West African Ebola epidemic Euro Surveill 2014 19 42 20936 10.2807/1560-7917.ES2014.19.42.20936 25358040 35. Semenza JC Sudre B Miniota J Rossi M Hu W Kossowsky D International Dispersal of Dengue through Air Travel: Importation Risk for Europe PLoS Negl Trop Dis 2014 8 12 e3278 10.1371/journal.pntd.0003278 25474491 36. Gardner L Sarkar S A Global Airport-Based Risk Model for the Spread of Dengue Infection via the Air Transport Network PLoS One 2013 8 8 e72129 10.1371/journal.pone.0072129 24009672 37. Bogoch II Creatore MI Cetron MS Brownstein JS Pesik N Miniota J Assessment of the potential for international dissemination of Ebola virus via commercial air travel during the 2014 west African outbreak Lancet 2015 385 9962 29 35 10.1016/S0140-6736(14)61828-6 25458732 38. Hufnagel L Brockmann D Geisel T Forecast and control of epidemics in a globalized world Proc Natl Acad Sci U S A 2004 101 15124 15129 10.1073/pnas.0308344101 15477600 39. Colizza V Barrat A Barthélemy M Vespignani A Predictability and epidemic pathways in global outbreaks of infectious diseases: the SARS case study BMC Med 2007 5 34 10.1186/1741-7015-5-34 18031574 40. Tizzoni M Bajardi P Poletto C Ramasco JJ Balcan D Gonçalves B Real-time numerical forecast of global epidemic spreading: case study of 2009/H1N1pdm BMC Med 2012 10 165 10.1186/1741-7015-10-165 23237460 41. Johansson MA Powers AM Pesik N Cohen NJ Staples JE Nowcasting the Spread of Chikungunya Virus in the Americas PLoS One 2014 9 8 e104915 10.1371/journal.pone.0104915 25111394 42. Khan K Arino J Hu W Raposo P Sears J Calderon F Spread of a novel influenza A (H1N1) virus via global airline transportation N Engl J Med 2009 361 2 212 214 10.1056/NEJMc0904559 19564630 43. Apolloni A Poletto C Ramasco JJ Jensen P Colizza V Metapopulation epidemic models with heterogeneous mixing and travel behavior TBioMed 2014 11 3 44. Gulf Research Center. Demography, migration, and labour market in Saudi Arabia. Available from: http://gulfmigration.eu/media/pubs/exno/GLMM_EN_2014_01.pdf Accessed 20 Jan 2016. 45. Nishiura H Endo A Saitoh M Kinoshita R Ueno R Nakaoka S Identifying determinants of heterogeneous transmission dynamics of the Middle East respiratory syndrome (MERS) outbreak in the Republic of Korea, 2015: a retrospective epidemiological analysis BMJ Open 2016 6 e009936 10.1136/bmjopen-2015-009936 26908522 46. McDonald LC Simor AE Su I-J SARS in healthcare facilities Toronto and Taiwan Emerg Infect Dis 2004 10 5 777 81 10.3201/eid1005.030791 15200808 47. Riley S Fraser C Donnelly CA Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions Science 2003 300 5627 1961 6 10.1126/science.1086478 12766206 48. Chowell G Fenimore PW Castillo-Garsow MA Castillo-Chavez C SARS outbreaks in Ontario, Hong Kong and Singapore: the role of diagnosis and isolation as a control mechanism J Theor Biol 2003 224 1 1 8 10.1016/S0022-5193(03)00228-5 12900200 49. Signorini A Segre AM Polgreen PM The use of Twitter to track levels of disease activity and public concern in the U.S. during the influenza A H1N1 pandemic PLoS One 2011 6 5 e19467 10.1371/journal.pone.0019467 21573238 50. Odlum M Yoon S What can we learn about the Ebola outbreak from tweets? Am J Infect Control 2015 43 6 563 71 10.1016/j.ajic.2015.02.023 26042846 51. Chew C Eysenbach G Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak PLoS One 2010 5 11 e14118 10.1371/journal.pone.0014118 21124761 52. Fung IC-H Tse ZTH Cheung C-N Miu AS Fu K-W Ebola and the social media Lancet 2014 384 9961 2207 10.1016/S0140-6736(14)62418-1 25625391 53. Fung IC-H Fu K-W Ying Y Chinese social media reaction to the MERS-CoV and avian influenza A(H7N9) outbreaks Infect Dis Poverty 2013 2 1 31 10.1186/2049-9957-2-31 24359669 54. World Health Organization. High-level messages [Internet]. Available from: http://www.wpro.who.int/mediacentre/mers-hlmsg/en/ Accessed 22 Oct 2015. 55. Donnelly CA Ghani AC Leung GM Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong Lancet 2003 361 9371 1761 6 10.1016/S0140-6736(03)13410-1 12781533 56. Feng D Jia N Fang L-Q Duration of symptom onset to hospital admission and admission to discharge or death in SARS in mainland China: a descriptive study Trop Med Int Health 2009 14 28 35 10.1111/j.1365-3156.2008.02188.x 19508437 57. Shu-qian LIU Chong-hua YAO Juan ZHANG Jiang-lian SU Gui-hong LIN Outpatients’ behavior of seeking medical care after onset of severe acute respiratory syndrome and community control measures in Beijing Asia Pac Fam Med 2005 4 3-4 58. Central MERS-CoV Control Office. Ministry of Health and Welfare. The Korean Government’s Responde to MERS. Briefing for Foreign Correspondence [Internet]. 2015. Available from: https://www.mohw.go.kr/eng/sg/ssg0111vw.jsp?PAR_MENU_ID=1001&MENU_ID=100111&page=9&CONT_SEQ=324451. Accessed 22 2015 Oct. 59. Cowling BJ Park M Fang VJ Wu P Leung GM Wu JT Preliminary epidemiological assessment of MERS-CoV outbreak in South Korea, May to June 2015 Euro Surveill 2015 20 25 7 13 10.2807/1560-7917.ES2015.20.25.21163 26132767 60. Rubin GJ Amlôt R Page L Wessely S Public perceptions, anxiety, and behaviour change in relation to the swine flu outbreak: cross sectional telephone survey BMJ 2009 339 b2651 10.1136/bmj.b2651 19574308 61. Rizzo C, Fabiani M, Amlôt R, et al. Survey on the Likely Behavioural Changes of the General Public in Four European Countries During the 2009/2010 Pandemic. In: Manfredi P, D’Onofrio A, editors. Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases [Internet]. New York: Springer; 2013. p. 23–41. Available from: http://link.springer.com/chapter/10.1007/978-1-4614-5474-8_2 Accessed 27 Oct 2015. 62. Anema A Kluberg S Wilson K Digital surveillance for enhanced detection and response to outbreaks Lancet Infect Dis 2014 14 11 1035 7 10.1016/S1473-3099(14)70953-3 25444397 63. Majumder MS, Kluberg S, Santillana M, Mekaru S, Brownstein JS. 2014 Ebola Outbreak: Media Events Track Changes in Observed Reproductive Number. PLoS Curr Outbreaks. 2015. doi: 10.1371/currents.outbreaks.e6659013c1d7f11bdab6a20705d1e865. 64. Lehmann J Gonçalves B Ramasco JJ Cattuto C Dynamical classes of collective attention in Twitter 2012

PMC005xxxxxx/PMC5000489.txt

==== Front Crit CareCritical Care1364-85351466-609XBioMed Central London 142810.1186/s13054-016-1428-9CommentaryLatent AKI is… still AKI: the quantification of the burden of renal dysfunction Ricci Zaccaria +39 0668592449zaccaria.ricci@gmail.com 1Romagnoli Stefano stefano.romagnoli@unifi.it 23Di Chiara Luca luca.dichiara@opbg.net 11 Department of Cardiology and Cardiac Surgery, Pediatric Cardiac Intensive Care Unit, Bambino Gesù Children’s Hospital, IRCCS, Piazza S. Onofrio 4, 00165 Rome, Italy 2 Department of Health Science, University of Florence, Florence, Italy 3 Department of Anesthesia and Intensive Care, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy 26 8 2016 26 8 2016 2016 20 1 238© The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.The association between pediatric cardiac surgery, acute kidney injury (AKI), and clinical outcomes has been studied several times in the recent literature. In this issue of Critical Care an interesting and original study analyzed the path from causal AKI entities to clinical AKI consequences through the application of structural equation modeling. The authors described the complex connections linking duration of cardiopulmonary bypass, cross clamp-time, and descriptors of low cardiac output syndrome to AKI modeled as a complex variable composed of post-operative serum creatinine increase of 50 % over baseline, urine output <0.5 ml/kg/h, and urine creatinine-normalized neutrophil gelatinase lipocalin within 12 h of surgery. Similarly, the causal relationships between AKI and hard outcomes in the analyzed population were verified and quantified. The authors, for the first time, produce a repeatable coefficient (0.741) that may become a useful quality benchmark and could be applied to test future interventions aiming to reduce the burden of AKI on children’s clinical course. Keywords Acute kidney injuryCongenital heart diseaseCardiopulmonary bypassNeutrophil gelatinase associated lipocalinissue-copyright-statement© The Author(s) 2016 ==== Body Main text In this issue of Critical Care, Bojan and coauthors investigated the complex relationships between acute kidney injury (AKI), modeled as a latent variable, and several exposures, including hard outcomes, in a retrospective analysis of infants undergoing cardiopulmonary bypass surgery [1]. To do so, they applied structural equation modeling (SEM), which is a relatively novel way to apply statistical analysis to clinical medicine. Clinical events are caused by a huge variety of combined variables and may generate a similar cascade of more or less predictable consequences. Attempts by researchers to force such clinical events into a mathematical model have often been frustrated or resulted in simplistic models: currently, the only way to generate a high level of evidence in order to show the effects of a treatment or the actual burden of a complex clinical condition (i.e., AKI) is to conduct randomized controlled studies or pragmatic prospective studies on a very large number of patients. Studies on pediatric critically ill patients are often retrospective, rarely randomized [2], and, in the vast majority of cases, conducted on small samples [3]. As alternatives, studies including the multi-faceted combination of several clinical factors and confounders are needed. SEM, through complex modeling and calculations, is used to depict relationships among multiple simultaneously observed variables in order to provide a quantitative test of a theoretical model hypothesized by the researcher [4]. In other words, SEM may allow researchers to verify if it is correct that AKI negatively affects clinical outcomes and to quantify its effects. More specifically, SEM applies two major types of variables: latent variables and observed variables. Latent variables are variables that are not directly observable or measured (i.e., intelligence, productivity, multi-factorial syndromes) and, hence, are inferred from a set of observed variables that can actually be measured using tests, surveys, and so on [4]. In the article by Bojan and coworkers, several perioperative variables were available for analysis of 75 neonates and 125 infants with congenital heart diseases. This particularly severely ill cohort, which was rather homogeneous according to age, included patients requiring complex surgery and undergoing averagely long cardiopulmonary bypass and with a 20 % incidence of post-operative AKI. Interestingly, Bojan and coauthors modeled the latent variable AKI as a construct of a post-operative serum creatinine increase of 50 % over baseline, urine output <0.5 ml/kg/h, and urine creatinine-normalized neutrophil gelatinase lipocalin within 12 h of surgery. These three elements were extracted as the best performers in identifying the latent AKI factor during an exploratory analysis preceding SEM: interestingly, as for the purposes of the current analysis, they outperformed the Acute Kidney Injury Network classification, which was not included in the SEM analysis. Recent published literature on pediatric cardiac surgery-associated AKI has already advocated the need for more extensive and timely examination of renal dysfunction, including the use of different criteria to AKI classification staging, such as fluid overload computation and biomarker application [5, 6]. The detection of early or subclinical forms of renal involvement [7, 8] in the pathophysiologic processes following bypass cardiac surgery directly and indirectly affect patients’ outcomes [9, 10] and SEM was likely able to detect this sequence of events. Bojan and coauthors also hypothesized that cardiopulmonary bypass would have a significantly greater role than low cardiac output on AKI development. It must be acknowledged that no direct measure of cardiac output was included in their study and its assessment is currently poorly applied in the context of pediatric cardiac surgery [11] and pediatric intensive care [12, 13]: it would be interesting to perform a similar analysis including direct cardiac output estimation. What their study actually adds to the current literature, however, is the quantification of the association between “latent” AKI and hard outcomes (namely, duration of mechanical ventilation, length of intensive care unit stay, and in-hospital mortality): the authors provided the readers with a measurement of this association (a compound coefficient of 0.741). This value might be interpreted as a quality benchmark for comparison of the performance of other centers. Otherwise, it could be re-evaluated in future studies, including a larger number of subjects, a more complete set of AKI covariates (fluid overload amount, number or amount of nephrotoxic agents, measurement of advanced hemodynamic variables), or a different population (i.e., neonates with hypoplastic heart syndrome [14]). Finally, the impact of specific therapeutic or preventive interventions might be measured using SEM in order to ultimately verify if a reduction in renal dysfunction occurrence is actually possible and if the burden of AKI on patients’ outcomes may be ultimately limited. Conclusions This study has added another small piece of knowledge to the pediatric cardiac AKI literature. Renal dysfunction has to be acknowledged as a complex and multifactorial syndrome that requires careful observation and accurate diagnosis, possibly not limited to classification staging but also implementing early biomarker analysis. Subclinical as well as established AKI significantly affects patients’ clinical courses and novel preventive or therapeutic interventions are urgently needed to finally improve outcomes. Abbreviations AKI, acute kidney injury; SEM, structural equation modeling See related research by Bojan et al., http://ccforum.biomedcentral.com/articles/10.1186/s13054-016-1350-1 Authors’ contributions ZR wrote the commentary; SR and LDC revised and approved it. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. ==== Refs References 1. Bojan M Basto Duarte MC Ermak N Lopez-Lopez V Mogenet A Froissart M Structural equation modelling exploration of the key pathophysiological processes involved in cardiac surgery-related acute kidney injury in infants Crit Care 2016 20 171 10.1186/s13054-016-1350-1 27262736 2. Duffett M Choong K Cupido C Hartling L Menon K Thabane L Randomized controlled trials in pediatric critical care: a scoping review Crit Care Med 2012 40 162 10.1097/CCM.0b013e31822d74a2 21926613 3. Duffett M Choong K Hartling L Menon K Thabane L Cook DJ Pilot randomized trials in pediatric critical care Pediatr Crit Care Med 2015 16 e239 44 10.1097/PCC.0000000000000475 26121101 4. Lei P-W Wu Q Introduction to structural equation modeling: issues and practical considerations Educ Meas Issues Pract ITEMS Modul 2007 26 33 43 10.1111/j.1745-3992.2007.00099.x 5. Wilder N Yu S Donohue J Goldberg CS Blatt NB Fluid overload is associated with late poor outcomes in neonates following cardiac surgery Pediatr Crit Care Med 2016 17 1 8 10.1097/PCC.0000000000000715 26731318 6. Basu RK Wong HR Krawczeski CD Wheeler DS Manning PB Chawla LS Combining functional and tubular damage biomarkers improves diagnostic precision for acute kidney injury after cardiac surgery J Am Coll Cardiol 2014 64 2753 62 10.1016/j.jacc.2014.09.066 25541128 7. Katz N Ronco C Acute kidney stress—a useful term based on evolution in the understanding of acute kidney injury Crit Care 2015 20 23 10.1186/s13054-016-1184-x 26796793 8. Ronco C Kellum JA Haase M Subclinical AKI is still AKI Crit Care 2012 16 313 10.1186/cc11426 22721504 9. Li S Krawczeski CD Zappitelli M Devarajan P Thiessen-Philbrook H Coca SG Incidence, risk factors, and outcomes of acute kidney injury after pediatric cardiac surgery: a prospective multicenter study Crit Care Med 2011 39 1493 9 10.1097/CCM.0b013e31821201d3 21336114 10. Blinder JJ Goldstein SL Lee V-V Baycroft A Fraser CD Nelson D Congenital heart surgery in infants: effects of acute kidney injury on outcomes J Thorac Cardiovasc Surg 2012 143 368 74 10.1016/j.jtcvs.2011.06.021 21798562 11. Garisto C Favia I Ricci Z Romagnoli S Haiberger R Polito A Pressure recording analytical method and bioreactance for stroke volume index monitoring during pediatric cardiac surgery Paediatr Anaesth 2014 25 143 9 10.1111/pan.12360 24491036 12. Ronco R Riquelme C Cardiac output measurement in children: what is lacking? Pediatr Crit Care Med 2008 9 333 4 10.1097/PCC.0b013e318172eb8c 18446096 13. Saxena R Durward A Steeley S Murdoch IA Tibby SM Predicting fluid responsiveness in 100 critically ill children: the effect of baseline contractility Intensive Care Med 2015 41 2161 9 10.1007/s00134-015-4075-8 26415680 14. Wong JH Selewski DT Yu S Leopold KE Roberts KH Donohue JE Severe Acute Kidney Injury Following Stage 1 Norwood Palliation: Effect on Outcomes and Risk of Severe Acute Kidney Injury at Subsequent Surgical Stages Pediatr Crit Care Med. 2016 17 615 23 10.1097/PCC.0000000000000734 27099973

PMC005xxxxxx/PMC5000490.txt

==== Front BMC Vet ResBMC Vet. ResBMC Veterinary Research1746-6148BioMed Central London 80210.1186/s12917-016-0802-9Research ArticleEstablishment and application of a competitive enzyme-linked immunosorbent assay differentiating PCV2 antibodies from mixture of PCV1/PCV2 antibodies in pig sera Han Shuizhong pulikehsz@163.com 1Xiao Yan xiaoyan811029@126.com 1Zheng Dingding 1476911377@qq.com 1Gu Yanli 49244083@qq.com 1Xuan Yajie xuanyajie@163.com 1Jin Yudan xiaoyu20073689@163.com 1Pang Wenqiang pangwq123@hotmail.com 1Huang Yuxin pyhuangyuxin@163.com 1Li Xiangdong xiaonanzhong@163.com 1Deng Junhua dengbetter88@163.com 1Tian Kegong tiankg@263.net 121 National Research Center for Veterinary Medicine, Luoyang, People’s Republic of China 2 College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, People’s Republic of China 26 8 2016 26 8 2016 2016 12 1 17526 4 2016 17 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Porcine cirovirus type 1 (PCV1) and type 2 (PCV2) are circulating in Chinese pig herds and the infected pigs develop antibodies to both viruses. Current commercial available ELISA kits cannot differentiate PCV2-specific antibodies from the mixtures of PCV1 and PCV2 antibodies in PCV1/2-infected or PCV2-vaccinated pigs. Therefore, the need for developing PCV2-specific ELISA methods is urgent to evaluate PCV2 antibody level in exclusion of PCV1 antibody interference after PCV2 vaccination. Results Virus-like particles (VLPs) of PCV2 based on the recombinant Cap protein were expressed in Escherichia coli. A competing ELISA was established by using the VLPs as coating antigen and a PCV2-specific monoclonal antibody as the competing antibody. The competing ELISA was compared with the results obtained by using an immunoperoxidase monolayer assay on 160 serum samples. The sensitivity and specificity of this competing ELISA were determined as 96.5 and 96.0 %, at 2 standard deviation from the mean or 91.8 and 100 % at 3 standard deviations from the mean. Next, a serological survey of 1297 vaccinated serum samples collected from commercial pig herds in Beijing, Hunan and Henan provinces in China was conducted. The results showed that 85.9 % of sera having positive PCV2 antibodies. Conclusions The competing ELISA we developed in this study was both sensitive and specific to PCV2 and was suitable for large-scale PCV2 antibody monitoring in exclusion of PCV1 antibody interference after PCV2 vaccination. Keywords Porcine circovirus 2(PCV2)Recombinant cap proteinVirus-like particleCompetitive ELISAissue-copyright-statement© The Author(s) 2016 ==== Body Background Porcine circovirus (PCV) was first identified as a noncytopathic contaminant of PK-15 cell, and subsequently classified in the family Circoviridae [1]. PCV is a spherical non-enveloped virus with a diameter of approximately 17 nm, and a single-stranded closed circular genomic DNA 1.7 kb in size [2]. There are two genotypes of PCV, namely PCV1 and PCV2. Serological analysis reveals that cross-reactivity exists between PCV1 and PCV2 [3]. PCV1 is widely known to be nonpathogenic agent, and no discernible pathogenic have been associated with PCV1 infection in swine [4]. Conversely, PCV2 is related to several diseases, such as postweaning multisystemic wasting syndrome (PMWS), porcine dermatitis and nephropathy syndrome (PDNS), porcine respiratory disease complex (PRDC), reproductive disorders, enteritis, and proliferative and necrotizing pneumonia (PNP), totally as porcine circovirus disease (PCVD) [5]. PCV2 genome contains two major open reading frames (ORFs): ORF1 and ORF2. ORF1 encodes the protein which involves in viral DNA replication, whereas ORF2 encodes an approximately 30 kDa immunogenic capsid (Cap) protein [6]. It was reported that the recombinant Cap protein could self-assemble to form virus-like particles expressed either in insect cells or Escherichia coli [6, 7]. The recombinant Cap protein reacted strongly with serum from PCV2-infected or PCV2-vaccinated pigs, which suggested that it was a good candidate antigen for the development of diagnostic assays [8, 9]. In order to detect PCV2 antibody in serum, the most common diagnostic methods include indirect fluorescent assay (IFA) and immunoperoxidase monolayer assay (IPMA) [10, 11]. However, these tests are not PCV2-specific due to the fact of antigenic cross-reactivity between PCV2 and PCV1. Meanwhile, these techniques are not only time-consuming and labor-intensive, but also require experienced technicians to judge the result arbitrarily. Compared with the current available methods, Enzyme-linked immunosorbent assay (ELISA) can be automated which decrease the potential bias and fit for mass detection. Several ELISA assays have been developed using the PCV2 virons or recombinant Cap protein expressed in insect cells [12–15]. In present study, a competitive ELISA (cELISA), using virus-like particles (VLP) of PCV2 rCap protein as the coating antigen and PCV2-specific monoclonal antibody (MAb) as the detecting antibody, was established. The establishment of this cELISA will facilitate to simply detect PCV2-specific antibodies from swine serum samples without PCV1 antibody interference. Methods PCV2 antigen and monoclonal antibody preparation VLPs formed by recombinant Cap protein were produced in E.coli BL21 (DE3) strain as previously described [16] and used as the coating antigen for cELISA. Briefly, the supernatant of cell lysates containing recombinant Cap (rCap) protein was precipitated by 60 % saturated ammonium sulfate and resuspended, followed by anion ion-exchange chromatographic purification. The purified recombinant PCV2 Cap proteins have been completely re-assembled into VLPs in a buffer of 50 mM Tris–HCl and 500 mM NaCl. 200 μl (0.4 μg/μl) recombinant PCV2 Cap protein plus equal volume of Freund’s complete adjuvant was used as an immunogen to inject each of five female Balb/c mice (purchased from Vital Rivea Experimental Animal Technology Ltd., Beijing) via intraperitoneal injection for Mab production. Three booster immunizations with same dose of antigen plus Freund’s incomplete adjuvant were conducted at two-week intervals. Three days after the final booster injection, the mice were euthanized and spleen cells were fused with SP2/0 cells using standard procedure [17]. The hybridoma cells were maintained in RPMI1640 medium (Gibco, USA) with 17 % fetal bovine serum (Hyclone, USA). The supernatant of the hybridoma cells were harvested and tested for antibodies to PCV2 and PCV1 by IPMA. The colony of 3H11 MAb reactive to PCV2 but not to PCV1 tested by IPMA was subcloned two times and selected for use in the cELISA. The MAbs were labeled with horseradish peroxidase (HRP) according to the conventional methods [18]. Serum samples Five colostrum-deprived specific-pathogen-free piglets (Purchased from SPF Swine Breeding and Management Centre, Beijing) were intranasally inoculated with 105.0 TCID50 infective doses of PCV2 SH strain. Serum samples were collected 0, 7, 14, 21, 28, 35, and 42 days post-vaccination (dpi) and separated for serological testing by IPMA and cELISA. Serum samples collected at 0 dpi worked as negative controls. One hundred and sixty clinical serum samples stored at National Research Center for Veterinary Medicine were tested by IPMA for cELISA development. In the retrospective serologic study, a total of 1297 field pig serum samples were collected by Veterinary Diagnostic Laboratory from Beijing (377 samples), Hunan (432 samples) and Henan (488 samples) provinces in China. The experiments were carried out under the consent of animal owners. The serum samples were tested by the cELISA established in this study. Immunoperoxidase monolayer assay (IPMA) IPMA was used to detect the presence of antibodies to PCV2. Briefly, the confluent monolayer of PKK cells (a PK-15 deprived cell line) infected with PCV2 SH (MOI=0.01) or free of PCV, were fixed in 80 % acetone for 30 min at 4 °C. The plates were stored at −20 °C after three times washing with PBS (0.01 mol/L, pH7.2). The MAb or serum samples were diluted 1:50 with PBS (0.01 mol/L, pH7.2), and added into the PCV2- and mock-infected PKK cells, respectively, 50 μl/well, and then incubated at 37 °C for 40 min. The anti-PCV polyclonal antiserum (VMRD, USA) and negative serum gained from colostrums-deprived piglets were respectively prepared as the positive and negative control. After three times washing, 50 μl of 1:200 dilution of HRP-conjugated goat anti-mouse or goat-pig IgG (Sigma, USA) was added and incubated at 37 °C for 30 min. After three times washing, 50 μl of the substrates 3-amino-9-ethylcarbazole was added and incubated for 30 min at room temperature. After three times washing, the 1:10 dilution hematoxylin was added. Twenty seconds later, the plates were washed with water and examined under an inverted light microscope. Development of cELISA Optimized dilution of PCV2 VLP antigen and horseradish peroxidase-conjugated PCV2-specific MAb were established by systematic checkerboard titrations. The polystyrene microliter ELISA plates were coated with 1.6 μg PCV2 VLP in phosphate buffer (0.02 mol/L, pH7.4) at 4 °C for 16 ~ 24 h. After three times washing, the plates were blocked with 200 μl of 20 % calf bovine serum in phosphate buffer (0.02 mol/L, pH7.4) for 2 h at 37 °C. After three times washing, 50 μl of the serum samples were added to each well, then 50 μl of 1:2000 dilution MAb 3H11 conjugated with HRP (Sigma, USA) were added to the wells except the blank well. The plates were incubated at 37 °C for 30 min. After five times washing, 100 μl of the substrate solution (0.2 mg/ml of TMB and 0.2 % H2O2 in 0.05 mol/L citrate buffer, pH4.6) was added and the colorimetric reaction was developed at 37 °C for 15 min. The reaction was stopped by adding 50 μl of 2 mol/L sulphuric acid. The optical density (OD) was measured at 450 nm. The controls included positive control (in triplicate), negative control (in triple) and one blank control. The OD450 of the samples were converted to a percent inhibition (PI) value using the following formulation: PI (%) = (OD450 value of negative value − OD450 value of sample)/OD450 value of negative value × 100 %. Reproducibility, thermal stability and specificity of the cELISA Inter-assay and intra-assay repeatability for the established cELISA was evaluated by testing the sixty filed sera. For the inter-assay repeatability, three replicates of each serum samples were detected by the same batch of pre-coated ELISA plates. For the intra-assay repeatability, each serum samples were detected by three batches of pre-coated ELISA plates. Mean PI value and coefficient of variation (CV) of three replications of each test were calculated. Thermal stability for the established cELISA was evaluated by testing five filed serums using the plates stored at 4 and 37 °C for six days, respectively. The PI value of each serum detected with the plates stored at 37 °C for six days was compared with those had been stored at 4 °C. Statistical analysis of the PI value was carried out by Student’s test using the SPSS 19.0 software. The significance level was set at 0.05 (p < 0.05). To explore the specificity, positive sera for PCV1, classical swine fever virus (CSFV), high pathogenic porcine reproductive and respiratory syndrome virus (HP-PRRSV), porcine parvovirus (PPV), and porcine pseudorabies virus (PRV) were tested with the established cELISA. Results Sera from experimentally infected piglets Standard PCV2-negative and positive serum samples were house-made by infecting pig with PCV2. Sera from these pigs sampled at 28, 35 and 42 day post-infection (dpi) were reactive with PCV2-infected cells by IPMA and were used as PCV2-postive serum samples. Sera at 0, 7, and 14 dpi were not reactive with PCV2 and were used as negative serum samples in this study. The positive sera had OD450 values < 0.719 when tested by cELISA established in this study with the inhibition in excess of 77.8 %. By contrast, the negative sera had OD450 values larger than 1.270 with inhibition less than 60.8 %. Determination of the cut-off of cELISA by using clinical sera A total of 160 field serum samples tested by IPMA were used to determine the cut-off value of established cELISA (Table 1). Among them, 75 samples were confirmed to be serological PCV2-negative by IPMA. These serum samples were tested by the established cELISA in this study. Distributions of the cELISA PI values showing the frequency of IPMA-positive and -negative samples are shown in Fig. 1. The average PI values (x-axis) of the 75 IPMA negative sera detected by cELISA were 34.4 % ± 12.0 % (mean ± SD). When 58.4 % (mean + 2SD) was used as the cutoff value for percentage inhibition, the sensitivity was 96.5 % and specificity was 96.0 %, giving a 95 % confidence. When the cutoff increased to 70.4 % (mean + 3SD), the sensitivity and specificity of the cELISA was 91.8 and 100 %, giving a 99 % confidence.Table 1 Determination of sensitivity and specificity of the cELISA using cut-off values of the mean negative PI plus two SD or three SD cELISA* IPMA* Positive Negative Total Positive 82a 3a 85a 78b 0b 78b Negative 3a 72a 75a 7b 75b 80b Total 85 75 160 Note:*IPMA immunoperoxidase monolayer assay, cELISA competitive enzyme-linked immunosorbent assay aComepetitive ELISA positive 58.4 % inhibition or greater bComepetitive ELISA positive 70.4 % inhibition or greater Fig. 1 Distribution of the cELISA PI values for detection of IPMA positive and negative pig sera. The horizontal bar shows the frequency of IPMA-positive and -negative samples and the vertical bar shows the inhibition values Reproducibility, thermal stability and specificity of the cELISA The reproducibility of the cELISA was determined by calculating the coefficient of variation (CV) of the PI values from field serum samples. The inter-assay CV of the 40 PCV2-positive serum samples ranged from 0.06 to 4.62 %, while the intra-assay CV of those same samples ranged from 0.16 to 7.46 % (Table 2). The inter-assay and intra-assay of the 20 negative samples also exhibited good repeatability, showing 2.2–14.8 % and 5.1–14.6 % respectively. These data showed that this assay was repeatable with low and acceptable variations.Table 2 Coefficient values of the 60 field sera tested by the cELISA Inhibition range(%) No. of sera tested CV range (%) Inter-assay Intra-assay 81–100 20 0.06–2.31 0.16–7.46 70–80 20 0.8–4.62 0.64–5.31 <60 20 2.2–14.8 5.1–14.6 The thermal stability assay was performed by comparing the PI values of 5 PCV2 positive serum samples on different ELISA plates which have been stored at 4 and 37 °C for six days. The results showed there was no significant difference (p = 0.107) existed between these two temperature conditions. In addition, the cross-reactivity of the cELISA with several positive sera against CSFV, HP-PRRSV, PPV, PRV and PCV1 was also tested according to the cELISA procedures. The OD450 values of all these sera were in excess of 1.930 (PI ≤ 38.5 %) and were negative. Serological survey of PCV2-vaccinated pigs using the established cELISA The results for the 1297 field serum samples, collected from three provinces in China are shown in Table 3. Of these, 1106 samples were positive (85.3 %) and 191 samples (14.7 %) were negative for PCV2 antibodies. Regionally, the positive rate was 80.6 % (348/432) in Hunan province, 79.3 % (387/488) in Henan province and 98.4 % (371/377) in Beijing city.Table 3 Prevalence of antibodies to PCV2 in pig sera collected from Henan, Hunan, and Beijing Areas Positive Negative Total Positive rate Beijing city 371 6 377 98.4 % Hunan province 348 84 432 80.6 % Henan province 387 101 488 79.3 % Total 1106 191 1297 85.3 % Discussion PCV2 is currently circulating worldwide and leads to huge economic losses to swine industries. The commonly used and most effective strategy to control this disease is vaccination. The antibodies elicited by vaccination are mainly targeted to the PCV2 Cap protein, the sole and highly immunogenic structural protein of virus. Therefore, evaluation of PCV2 antibodies after virus infection or vaccination may reflect the herd infection status or the efficacy of vaccines. Currently, the common analytical methods developed for the qualitative and quantitative analysis of PCV2 antibodies in serum samples are IIF and IPMA. However, the antibodies detected by IIF and IPMA were not PCV2-specific due to the antigenic cross-reactivity between the Rep proteins encoded by PCV2 and PCV1 [19]. Therefore, development of specific and convenient methods for PCV2 antibody evaluation is more meaningful in PCV2 serological test. It was previously reported that ELISA coated with the recombinant PCV2 Cap protein or peptide could be used for the specific detection of PCV2 antibody [8, 20]. Several indirect ELISA methods using the recombinant Cap protein have been developed for detecting the presence of PCV2 antibody in pig sera [12–14]. However, the indirect ELISA has some limitations including the high level of false positives due to the complex components of serum samples such as Rheumatoid factor and antibodies specific for other animal serum components. Compared with indirect ELISA, cELISA have distinct advantages. First, the secondary antibody against the tested species is nonessential. Secondly, the nonspecific background caused by the tested sera could be lower by using the specific anti-PCV2 MAb. A cELISA have been previously established for the detection of PCV2 antibodies [15]. In their studies, live PCV2 virions from the cell cultures have been used as the coating antigen. The use of live virus has the issue of biosecurity and the production of live virus as antigen is laborious and time-consuming. Therefore, in our study, E. coli-originated PCV2 VLPs have been used as coating antigen with the advantages of intact antigenicity and easier preparation. Besides the PCV2 VLPs used as coating antigen in this study, a PCV2-specific MAb was employed as a competitor with test sera. The MAb used in this assay is not reactive with PCV1 which exclude the inference of PCV1 antibodies that existed in the serum samples. Both the serum samples from experimental infected with PCV2 and from the clinical animals were used to establish the cELISA. The sensitivity and specificity of the cELISA was determined by detecting 160 field serums which have been confirmed IPMA. When the cutoff value of this cELISA was set to 58.4 % inhibition, three IPMA positive/cELISA negative serum samples were detected. These serum samples may contain antibodies to different stain of PCV2 that were reactive by IPMA but not with cELISA since a wide range of viral epitopes could be recognized by the polyclonal antibodies in IPMA. Three IPMA negative/cELISA positive samples were also detected. This discrepancy may be explained by the higher sensitivity of cELISA than IPMA. When the cutoff increased to 70.4 % inhibition, the IPMA negative/cELISA positive disappeared and the numbers of IPMA positive/cELISA negative serums increase to seven. Hence, the gray zone of the cELISA was set to be in the region of 58.4 to 70.4 %, and the samples should be retested when PI values fall into the range. The established cELISA was next applied to do the PCV2 serological survey by using 1297 serum samples collected from three different provinces. The results of the survey reveals the PCV2 antibody positive rates ranged from 79.3 to 98.4 % which indicates the good herd immunity after vaccination. Conclusions To summarize, a cELISA was successfully established in this study to specifically detect PCV2 antibodies in exclusion of PCV1 antibody interference in serum samples. The specificity and convenience of this cELISA will be a useful tool to evaluate the strength of post-vaccination antibody response and monitor the efficacy of current vaccines. Abbreviations PCV2Porcine cirovirus 2 PCV1Porcine cirovirus 1 ORFsOpen reading frames ELISAEnzyme-linked immunosorbent assay CapCapsid IFAIndirect fluorescent assay IPMAImmunoperoxidase monolayer assay cELISACompetitive enzyme-linked immunosorbent assay VLPVirus-like particles MAbMonoclonal antibody E.coliEscherichia coli HRPHorseradish peroxidase TCID50Tissue culture infective dose DpiDays post-vaccination PBSPhosphate-buffered saline ODOptical density PIpercent inhibition iELISAIndirect enzyme-linked immunosorbent assay We want to thank all staffs who got involved in animal experiments in this study at National Research Center for Veterinary Medicine. Funding This work was supported by grant from Applied Technology R&D Funding Program in Luoyang City (Grant no.1401082A), Major Science and Technology Program in Henan Province (Grant No.131100110200), Innovation Scientists and Technicians Troop Construction Projects of Henan Province (Grant No.142101510001), Talents Plan for Scientific and Technological Innovation in Henan Province (Grant No.144200510002), and Science and Technology Innovation team in Henan Province (Team No.C20130005). Availability of data and materials The data set(s) supporting the results of this article is included within the article. Authors’ contributions SH conducted ELISA validation, statistical analysis. YX and JD conducted ELISA establish and statistical analysis. DZ conducted the screen of the hybridoma cell. YG conducted the screen of the hybridoma cell. YX conducted ELISA validation and IPMA detection. YJ conducted the production of ascetic. WP and YH prepared PCV2 VLPs. XL and KT conducted the design of the study and draft the manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate The animal trial in this study was approved by the Animal Care and Ethics Committee of China National Research Center for Veterinary Medicine and conventional animal welfare regulations and standards were taken into account. ==== Refs References 1. Tischer I Rasch R Tochtermann G Characterization of papovavirus-and picornavirus-like particles in permanent pig kidney cell lines Zentralbl Bakteriol Orig A 1974 226 2 153 67 4151202 2. Tischer I Gelderblom H Vettermann W Koch MA A very small porcine virus with circular single-stranded DNA Nature 1982 295 5844 64 6 10.1038/295064a0 7057875 3. Allan GM McNeilly F Kennedy S Daft B Clarke EG Ellis JA Haines DM Meehan BM Adair BM Isolation of porcine circovirus-like viruses from pigs with a wasting disease in the USA and Europe J Vet Diagn Invest 1998 10 1 3 10 10.1177/104063879801000102 9526853 4. Tischer I Bode L Peters D Pociuli S Germann B Distribution of antibodies to porcine circovirus in swine populations of different breeding farms Arch Virol 1995 140 4 737 43 10.1007/BF01309961 7794114 5. Segales J Allan GM Domingo M Porcine circovirus diseases Anim Health Res Rev 2005 6 2 119 42 10.1079/AHR2005106 16583778 6. Nawagitgul P Morozov I Bolin SR Harms PA Sorden SD Paul PS Open reading frame 2 of porcine circovirus type 2 encodes a major capsid protein J Gen Virol 2000 81 Pt 9 2281 7 10.1099/0022-1317-81-9-2281 10950986 7. Yin S Sun S Yang S Shang Y Cai X Liu X Self-assembly of virus-like particles of porcine circovirus type 2 capsid protein expressed from Escherichia coli Virol J 2010 7 166 10.1186/1743-422X-7-166 20646322 8. Sun SQ Guo HC Sun DH Yin SH Shang YJ Cai XP Liu XT Development and validation of an ELISA using a protein encoded by ORF2 antigenic domain of porcine circovirus type 2 Virol J 2010 7 274 10.1186/1743-422X-7-274 20958981 9. Ge M Luo W Jiang D Li R Zhao W Chen G Yang X Yu X Development and application of a double-antigen sandwich enzyme-linked immunosorbent assay for detection of antibodies to porcine circovirus 2 Clin Vaccine Immunol 2012 19 9 1480 6 10.1128/CVI.00234-12 22815145 10. Allan GM Mackie DP McNair J Adair BM McNulty MS Production, preliminary characterisation and applications of monoclonal antibodies to porcine circovirus Vet Immunol Immunopathol 1994 43 4 357 71 10.1016/0165-2427(94)90157-0 7856071 11. Dulac GC Afshar A Porcine circovirus antigens in PK-15 cell line (ATCC CCL-33) and evidence of antibodies to circovirus in Canadian pigs Can J Vet Res 1989 53 4 431 3 2686830 12. Blanchard P Mahe D Cariolet R Truong C Le Dimna M Arnauld C Rose N Eveno E Albina E Madec F An ORF2 protein-based ELISA for porcine circovirus type 2 antibodies in post-weaning multisystemic wasting syndrome Vet Microbiol 2003 94 3 183 94 10.1016/S0378-1135(03)00131-7 12814886 13. Shang SB Li YF Guo JQ Wang ZT Chen QX Shen HG Zhou JY Development and validation of a recombinant capsid protein-based ELISA for detection of antibody to porcine circovirus type 2 Res Vet Sci 2008 84 1 150 7 10.1016/j.rvsc.2007.02.007 17467754 14. Nawagitgul P Harms PA Morozov I Thacker BJ Sorden SD Lekcharoensuk C Paul PS Modified indirect porcine circovirus (PCV) type 2-based and recombinant capsid protein (ORF2)-based enzyme-linked immunosorbent assays for detection of antibodies to PCV Clin Diagn Lab Immunol 2002 9 1 33 40 11777826 15. Walker IW Konoby CA Jewhurst VA McNair I McNeilly F Meehan BM Cottrell TS Ellis JA Allan GM Development and application of a competitive enzyme-linked immunosorbent assay for the detection of serum antibodies to porcine circovirus type 2 J Vet Diagn Invest 2000 12 5 400 5 10.1177/104063870001200502 11021425 16. Xi X Mo X Xiao Y Yin B Lv C Wang Y Sun Z Yang Q Yao Y Xuan Y Production of Escherichia coli-based virus-like particle vaccine against porcine circovirus type 2 challenge in piglets: Structure characterization and protective efficacy validation J Biotechnol 2016 223 8 12 10.1016/j.jbiotec.2016.02.025 26907669 17. Galfre G Milstein C Preparation of monoclonal antibodies: strategies and procedures Methods Enzymol 1981 73 Pt B 3 46 10.1016/0076-6879(81)73054-4 7300683 18. Wilson MB, Nakane PK. Recent development in the periodate method of conjugating horseadish peroxidase (HRPO) to antibodies: In: Knapp W, Holubar K, Wick G, Eds. Immunofluorescence and Related Staining Techniques. Amsterdam:Elservier/North-Holland Biomedical Press, 1978:215–224. 19. Rodriguez-Arrioja GM Segales J Balasch M Rosell C Quintant J Folch JM Plana-Duran J Mankertz A Domingo M Serum antibodies to porcine circovirus type 1 and type 2 in pigs with and without PMWS Vet Rec 2000 146 26 762 4 10.1136/vr.146.26.762 10909911 20. Mahe D Blanchard P Truong C Arnauld C Le Cann P Cariolet R Madec F Albina E Jestin A Differential recognition of ORF2 protein from type 1 and type 2 porcine circoviruses and identification of immunorelevant epitopes J Gen Virol 2000 81 Pt 7 1815 24 10.1099/0022-1317-81-7-1815 10859388

PMC005xxxxxx/PMC5000491.txt

==== Front BMC Public HealthBMC Public HealthBMC Public Health1471-2458BioMed Central London 356510.1186/s12889-016-3565-0Research ArticleA multilevel analysis of lifestyle variations in symptoms of acute respiratory infection among young children under five in Nigeria Adesanya Oluwafunmilade A. dejilade@yahoo.com 1Chiao Chi +886-2-28267916cchiao@ym.edu.tw 21 Institute of Public Health, International Health Program, School of Medicine, Institute of Public Health, National Yang-Ming University, Taipei, Taiwan 2 School of Medicine, Institute of Health and Welfare Policy, National Yang-Ming University, No. 155, Sec. 2, Li-Nong St, 112 Taipei, Taiwan People’s Republic of China 25 8 2016 25 8 2016 2016 16 1 88012 5 2016 20 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Nigeria has the second highest estimated number of deaths due to acute respiratory infection (ARI) among children under five in the world. A common hypothesis is that the inequitable distribution of socioeconomic resources shapes individual lifestyles and health behaviors, which leads to poorer health, including symptoms of ARI. This study examined whether lifestyle factors are associated with ARI risk among Nigerian children aged less than 5 years, taking individual-level and contextual-level risk factors into consideration. Methods Data were obtained from the nationally representative 2013 Nigeria Demographic and Health Survey. A total of 28,596 surviving children aged 5 years or younger living in 896 communities were analyzed. We employed two-level multilevel logistic regressions to model the relationship between lifestyle factors and ARI symptoms. Results The multivariate results from multilevel regressions indicated that the odds of having ARI symptoms were increased by a number of lifestyle factors such as in-house biomass cooking (OR = 2.30; p < 0.01) and no hand-washing (OR = 1.66; p < 0.001). An increased risk of ARI symptoms was also significantly associated with living in the North West region and the community with a high proportion of orphaned/vulnerable children (OR = 1.74; p < 0.001). Conclusions Our findings underscore the importance of Nigerian children’s lifestyle within the neighborhoods where they reside above their individual characteristics. Program-based strategies that are aimed at reducing ARI symptoms should consider policies that embrace making available basic housing standards, providing improved cooking stoves and enhancing healthy behaviors. Keywords (MeSH): Symptoms of acute respiratory infection (ARI)Lifestyle factorsMultilevel analysisYoung childrenNigeriaMinistry of Science and Technology in Taiwan104-2628-H-010-001Chiao Chi issue-copyright-statement© The Author(s) 2016 ==== Body Background Acute respiratory tract infection (ARI) remains one of major infectious causes of mortality and morbidity among children and it accounts for more than one-third of mortality among children under 5 years old; it results in approximately 2 million deaths per year around the world [1, 2]. In developing countries, 70 % of childhood morbidities among children under 5 years are due to ARI [3] with an average annual incidence of five–six episodes of ARI per child per year [4]. Sub-Saharan Africa is the second highest contributor to the global count of ARI [5, 6]. As such infections are one of major causes of pediatric outpatient visits [7], with 27 to 96 % of such visits resulting in hospitalization [8]. Prior studies have shown that the determinants of a child health are influenced by their personal lifestyle factors, namely those that are practiced within their household and community [9]. Specifically, findings from a randomized control trial and a systematic review have both confirmed that practicing hand-washing by individuals and the promotion of hand-washing among community members are able to significantly reduce the risk of ARI [10, 11]. In line with this evidence, lifestyle factors practiced in households are believed to be highly important determinants of child health outcomes. To measure lifestyle factors, Mishra and his colleagues measured the extent of exposure to cooking smoke by examining the type of fuel used for cooking in households; these were grouped into three categories (high, medium and low pollution fuels) in order to represent the extent of exposure to cooking smoke [12]. In another study, Kilabuko and Nakai, employing the same type of question, but categorizing children into two groups: was able to separate children into those from homes using biomass fuels or those from homes using kerosene/charcoal [13]. Furthermore, a population based study from India also measured the extent of exposure to cooking smoke; this was done by examining what type of fuel households uses most commonly for cooking; by examining whether household members smoked and identifying whether there was a separate kitchen [14]. Given the important influence of household practices on child health as these become integrated with various behavioral and lifestyle factors, studies that only account for one or two modifiable lifestyle practices are very likely not able to fully capture the whole range of factors that a child with ARI is exposed to. To be specific, prior studies seem to have overlooked the possibility that there is synergy between biomass based cooking and the place where cooking takes place; for example; effective exposure is likely to be higher in households where biomass cooking takes place indoors. As a result of these possibilities, the present study assessed simultaneously a range of lifestyle factors; these consisted of cooking methodology (type of cooking fuel and place of cooking), hand-washing and smoking by parents. Several mechanisms have been proposed for plausibly linking in a biological context, household air pollution, and ARI among children; the most widely accepted of these are links related to cooking with a biomass fuel and to cigarette smoking in the household; these were recently systematically reviewed by Gordon et al. [15]. In addition to this review, a longitudinal study in Kenya has measured the average daily exposure to particulate matter (e.g., PM10) emitted by biomass combustion; the findings revealed that exposed children who were under 5 years old had a higher risk of ARI as compared to their older counterparts [16]. In another study, Sonego et al. conducted a systematic investigation in low and middle income countries studying the link between low socioeconomic status and ARI; their results supported such an association [17]. The findings were also supported by a population based study in Nepal [18]. Another population-based study in Zimbabwe studied the association between household use of biomass fuels and ARI among preschool children and their findings supported the hypothesis that biomass fuel utilization and region of residence were significantly associated with a higher risk of ARI, even after controlling for the children’s gender and birth order [12]. The empirical gaps in the current literature thus seem to involve the relationship between personal lifestyle and related health behaviors, as practiced in households and neighborhoods, and the risk of ARI symptoms [9, 19]. For example, households using biomass as a cooking fuel are clustered in specific communities and the observed community effect of biomass cooking may also involve effects related to lifestyle behaviors within individual households. Thus an increased risk of ARI is therefore not necessarily connected to the community’s collective lifestyle but may rather be associated with individual lifestyle practices within the household [20]. The present study is guided by the social ecological theory [21, 22] which focuses on the complex interplay between the nested environmental levels that envelop children and the individuals in their immediate environment in terms of their influence on health [21]. The theory emphasizes that individuals are embedded within a context and to an extent their lifestyles practices are the result of various societal and social influences; these originate from their immediate environment and include household and community characteristics. Households that are integrated within a given environment are likely to be the most proximal niche in which modifiable daily lifestyle practices can act to shape children’s health [23]. We thus hypothesized that young children with symptoms of ARI will show an association between the presence of ARI and poor personal health-related practice, as well as their risky contextual lifestyle factors. Furthermore, Amoako et al., who used a population based survey, explored the relationships between the proximate/socio-economic determinants and poor health outcomes among children who have orphan/vulnerable child (OVC) status. They found that OVC status would seem to put the child in peril of ARI; and that the factors that may contribute to the vulnerability of OVC include absence of parental care, a lack of environmental hygiene, their vaccination status, and their ability to access healthcare [24]. In this context, Watts et al. used the Zimbabwe OVC Baseline Survey to investigate similar problems and found that OVC were at greater risk of ARI due to their limited access to medical care including vaccinations [25]. Nonetheless, the above studies have not examined the associations between childhood ARI symptoms, lifestyle factors, personal hygiene in particular, and OVC status in a sub-Saharan African country. Using a national sample of children under five in Nigeria, the main objective of this study is to better understand the association between lifestyle factors and ARI symptoms. Our conceptual framework regards lifestyle factors at both individual and community levels are our main interest and we posit links between lifestyle factors, OVC status, and ARI symptoms. That is, the present study aims to examine whether lifestyle factors, as measured by cooking methodology, household smoking status, and personal hygiene, are associated with the symptoms of ARI, while taking OVC status, as well as other individual and contextual-level social risks, into consideration. Nigeria, is one of the highest contributor to under-five mortality globally [7] with its under-five mortality (U5M) standing at 109 out of 1000 live births [26]. This is far from achieving the proposal that all countries reduce their U5Ms to as low as 25 out of 1000 live births by 2030 [27]. A progress report in 2015 by the International Vaccine Access Center, revealed that Nigeria is the second largest contributor world-wide to the global burden of child pneumonia and diarrhea; in this context ARI is one of the major causes of U5M [6, 28]. Methods Population We used cross-sectional data from the 2013 Nigeria Demographic and Health Survey (NDHS), a nationally representative set of data. The survey employed a national probability sample of households that involved a three-stage cluster sampling technique. The country was stratified into 36 states and the Capital Abuja; thus there were 37 districts overall. During the first stage, the primary sample unit (PSU), was based on the 2006 Nigeria population census enumeration areas (EAs). Each PSU corresponds with a smaller geographic unit (such as a neighborhood in an urban area or a village in rural area); this gave rise to a total of 896 clusters. A sample cluster within the PSU was then selected using a probability proportional to population size approach. During the second stage, households were selected within each PSU by systematic sampling of the households present in each selected cluster. The third stage involved the distribution of households across each state, which followed a probability proportional to the urban and rural areas within Nigeria; the final results consisted of a total of 40,680 households. Data collection of the 2013 NDHS was carried out by trained field workers from the 36 states in Nigeria. The questionnaires was translated into the three major Nigerian languages, Hausa, Igbo, and Yoruba; these were then pre-tested, re-fined, and finalized for the survey and finally back translated to ensure that the questions measured what they were intended to measure. The questionnaire were filled-in by the interviewers in order to collect the required information [29]. Among the successfully sampled households, information on 31,482 children (a combination of dead/alive children) under the age of 5 years was collected with a 95.2 % response rate. In this study, we defined a community as a sample cluster (that is a PSU), which usually was a village or an urban census block. In addition, we restricted our analyses to children who were under 5 years of age and were alive at the time of sampling. The final sample consisted of 28,596 pre-school children and this large sample size has enough statistical power for multi-level analysis. We compared the characteristics of the children included in the study with those of the children who were excluded. A total of 2886 children were excluded due to either survival status or unavailability of information on ARI symptoms. The children excluded were more likely to be older, to be socioeconomic disadvantaged and/or to reside in North western regions (the results not tabled). The dataset is available online from ICF international, Rockville, MD, USA [30]. The study protocol used secondary data analysis of the DHS and was approved by the Research Ethics Committee of National Yang-Ming University (Taipei, Taiwan). Outcome and major explanatory measures The outcome of the study was symptoms of ARI that was defined and measured by the 2013 NDHS [30], an women’s health questionnaire that was administered to eligible women (15–49 years) in order to reveal information on the respiratory health of children aged 0–59 months. Mothers were asked whether their children under 5 years old had been ill with a cough during the 2 weeks preceding the survey. For children who had a cough, the mother was additionally asked if the child, when sick with a cough during the last 2 weeks prior to the survey, also suffered from short, rapid breathing accompanied by a fever. Children who met all of the abovementioned criteria were regarded as having ARI and were coded with a value of 1; otherwise, the children were coded with a value of 0. Lifestyle factors questions derived from the household data were made up of characteristics related to the individual’s style of living as observed by the interviewers. They consisted of assessments of the cooking method used in the household [13, 14], the smoking status of members of the household [14] and the personal hygiene practices of the household [11]. Household cooking method was derived from two variables, namely the major type of fuel used for cooking by a given household and the place where cooking was conducted in a given household. The cooking methods were grouped into five categories: households using kerosene/charcoal outdoors or in a separate place, households using biomass cooking indoors, households using biomass cooking outdoor and in a separate place, households using kerosene/charcoal in the house and various other cooking systems that are less polluting cooking methods than the above, such as gas or electricity. The smoking status of any member of the household was asked in a non-specific manner in the household data and this information was classified into whether or not a household member smoked. The interviewers observed child hand washing and this practice was dichotomized into either observed or not within the household. In addition to the above, also from the household data, the identification of orphans and vulnerable children (OVC) was carried out by identifying individuals who had experienced the death of a family member, who had a parent who had been ill for at least 3 months in the past 12 months, or who came from a household where a member of that household member had been ill for at least 3 months in the past 12 months [31]. We used a set of variables from the survey, such as whether or not a child had one or both parents dead, whether the child had lived with a parent who had been sick for at least 3 months in the past 12 months, and whether the child had lived in a household where at least one adult has been sick for at least 3 months or even died in the past 12 months. If a child had one or more of such experiences, the child was coded as 1, otherwise the child was coded as 0. Based on prior studies [13, 18, 32], we also included several individual control variables that are related to the socio-demographic background of the children, namely gender, age, and birth order, as well as the socio-demographic background of the children’s mothers, namely maternal education and household wealth index. These covariates have often been tied to the symptoms of ARI. Table 1 gives the categorization and distribution of community control variables from the 2014 DHS dataset in Nigeria. We have included five community-level measures: community wealth index, community OVC status, community use of biomass cooking fuel, place of residence and the region of the province. The above variables are classified into two categories, derived and integral, in order to establish the characteristics of each community [33]. The former were constructed by aggregating the household or individual survey data at sample cluster level, that is the PSU. Community wealth index, community OVC status, and community use of biomass cooking fuel were constructed from an aggregate of households within a given PSU with further grouping into quartiles or tertiles. The computation of the integral community variables was done by extraction from the census of the population and the housing; these resulted in a place of residence, namely urban or rural [34] and a province of residence, namely North West, North Central, North East, South East, South South, and South West [35].Table 1 Hypothesized neighborhood socioeconomic influences, together with the distribution and categorization of neighborhood-level variables, which were used to predict the likelihood of development of ARI symptoms; 2013 NDHS (children 0–5, n = 896) Neighborhood characteristic Percentage or mean (Std Dev) Categorization Community use of biomass cooking fuel 78.82 (40.85) Community biomass use: 0–1 Low (0 to 0.738) 27.87 (44.84) Lowest use of biomass cooking fuel Median (0.739 to0. 98) 90.57 (29.22) Median use of biomass cooking fuel High (0.981 to 1) 99.84 (3.87) Highest use of biomass cooking fuel Community wealth index 44.55 (49.70) Lowest quartile versus higher quartile The first quartile (0 to 0) 0 The second quartile (2 to 40) 16.31 (36.95) The third quartile (40 to 92) 70.18 (45.74) The fourth quartile (93 to 100) 98.82 (10.77) Highest proportion of middle, rich and richest in the community Community OVC status 4.23 (20.13) Proportion of OVC within a community: 0–1 Low (0) 0 Lowest OVC rate in community Median (1.5 to 5.0) 3.31 (1) Median OVC rate in community High (5.1 to 50) 11.02 (5.5) Highest OVC rate in community Residence Urban 35.88 (1.10) Rural 64.11 (1.10) Province North West 17.27 (0.89) North Central 13.71 (0.84) North East 36.60 (1.06) South East 8.81 (0.67) South South 9.46 (0.54) South West 14.13 (0.83) Analytical strategy We began the various analyses by characterizing the distribution of communities, the distribution of households, the distribution of children-level characteristics, and the prevalence of ARI symptoms by sample characteristics. Due to the hierarchical structure of DHS data, children nested within a community are often exposed to a common set of community derived influences. Children from the same community often practiced lifestyle behaviors that more similar to each other than to those of children from other communities. We thus employed for the analysis Stata 13.0; this has been updated with the Gllamm program for random intercept multilevel models [36]. In the modeling strategy, children at level 1 were nested within communities at level 2. The random effect at the community (PSU) level was found to be significant (p < 0.05) with an intra-class correlation coefficient of 0.29, demonstrating that almost 30% of the total variation with respect to having ARI symptoms was at child’s community. We elaborated on the significance of individual lifestyle and health behaviors by progressively adjusting for individual, household and community characteristics. The first elaboration targeted lifestyle and health behaviors in order to investigate the association between various preventive practices and ARI symptoms (Model 1), after adjusting for child’s OVC status, child’s gender, child’s age, birth order, maternal education and household wealth. Next, we added community related characteristics (e.g., community OVC, region, urban residence, community wealth, and community use of cooking fuel) to the model in order to test for possibility that confounding factors associated with lifestyle and health behaviors might affect any relationship with ARI symptoms (Model 2). All the steps in the analysis took into account the multi-stage sampling design of the study and adjusted for other confounding variables, such as related individual and household characteristics. Results Table 2 shows the distribution of household’s lifestyle behaviors and children characteristics. About two-fifths (42.11 %) of households used biomass fuel for indoor cooking, while less than one-tenth (6.82 %) of households had a member that smoked. Finally, about two-fifths (61.22 %) of young children did not practice hand washing. Overall the ARI prevalence was 1.93 %. A higher prevalence of ARI symptoms was found among children living in a household with in-house biomass cooking (2.07 %), among children living in a household where a household member smoked (2.89 %); and among children who did not practice hand-washing (2.27 %). In addition, compared with non-OVC, OVC had a much higher prevalence of ARI symptoms (3.54 %). The prevalence of ARI symptoms by OVC status and region further indicated that OVC who lived in the North East region (7.52 %) were specifically at a much greater risk of ARI symptoms (Fig. 1).Table 2 ARI prevalence by sample characteristics for children under 5 years of age [percentage or mean (Std Dev)], NDHS 2013 Total (N =28,596) ARI prevalence Percentage or mean Std. Dev. Percentage or mean Explanatory variables Lifestyle and health behaviors Cooking method Kerosene/charcoal outdoors or in a separate place 10.03 0.64 In-house use of biomass fuel for cooking 42.11 2.07 In-house use of kerosene/charcoal for cooking 11.33 1.20 Cooking using biomass fuel outdoors or in a separate place 34.86 2.39 Other 1.68 1.29 Smoking status of members of the household Yes 6.82 2.89 No 93.18 1.86 Hand-washing Observed 38.78 1.36 Not observed 61.22 2.27 Individual and household covariates Child’s background Gender Female 49.89 1.96 Male 50.11 1.90 Age (in months) 28.14 17.32 0–5 10.32 1.46 6–11 11.27 2.82 12–23 20.37 3.08 24–35 18.95 2.08 36–59 39.08 1.12 Birth order 3.88 2.54 1–3 52.20 1.79 4–6 31.73 1.76 >6 16.07 2.70 OVC status OVC 3.91 3.54 Non-OVC 96.09 1.86 Household’s background Maternal education No education 48.31 1.96 Primary education 19.16 2.05 Secondary and above 32.53 1.81 Household wealth Richest 18.14 0.98 Richer 18.14 1.35 Middle 19.07 2.03 Poorer 22.40 2.88 Poorest 22.96 2.09 Outcome measure Symptoms of ARI 1.93 aUnweighted N’s and weighted percentages and means are reported. Percentages may not add up to 100 due to rounding Fig. 1 Prevalence of acute respiratory tract infection (ARI) symptoms among individuals with the status of orphans/vulnerable children (OVC) by region Table 3 presents the multilevel logistic regression models used to investigate the relationship between lifestyle and health behaviors in relation to ARI symptoms. Model 1 shows that an unhealthy lifestyle and unhealthy behaviors are significantly associated with ARI symptoms. The odds of having ARI symptoms were increased among young children who lived in households using biomass fuel for cooking indoors (AOR = 2.38; p < 0.01), who lived in households using in-house kerosene/charcoal for cooking (AOR = 2.08; p < 0.01), who lived in households using biomass fuel for cooking outdoors (AOR = 2.54; p < 0.01), who lived with a member of the household who smoked (AOR = 1.37; p < 0.05), and who lived in households where hand-washing was not observed (AOR = 1.59; p < 0.001), even when the analysis was controlled for a wide range of individual and household characteristics.Table 3 Results of the multilevel regressions of the odds of ARI symptoms among young children, 2013 NDHS (N = 28,596) MODEL 1 MODEL 2 Covariates AOR 95 % CI AOR 95 % CI Lifestyle and health behaviors Cooking method (ref = Kerosene/charcoal outdoors or a separate place) In-house use of biomass fuel 2.38** 1.34–4.24 2.30** 1.26–4.20 In-house use of kerosene/charcoal 2.08* 1.17–3.70 2.11** 1.19–3.72 Outdoor or separate use of biomass fuel 2.54** 1.45–4.45 2.28** 1.27–4.10 Other 2.51 0.95–6.64 2.42 0.94–6.25 Smoking of members of the household (ref = No) Ever smoked 1.37* 1.01–1.87 1.33 0.98–1.81 Hand-washing (ref = Observed) Not observed 1.59*** 1.28–1.98 1.66** 1.33–2.07 Neighborhood characteristic Community OVC status (ref = Low) Median 1.28 0.94–1.75 High 1.74*** 1.34–2.25 Region of residence (ref = North West) North Central 0.39*** 0.27–0.57 North East 0.15*** 0.11–0.20 South East 0.30*** 0.19–0.48 South South 0.35*** 0.22–0.57 South West 0.26*** 0.15–0.43 Community wealth index (ref = The first quartile) The second quartile 1.03 0.67–1.58 The third quartile 0.94 0.54–1.62 The fourth quartile 1.05 0.56–1.95 Community use of biomass cooking fuel (ref = Low use) Median use 0.82 0.51–1.31 High use 1.07 0.63–1.81 Urban residence (ref = Rural) 0.95 0.68–1.33 Individual and household backgrounds Female gendered (ref = Male) 1.02 0.85–1.21 1.03 0.86–1.22 Birth order (ref = 1–3) 4–6 0.92 0.75–1.13 0.94 0.76–1.15 >6 1.35* 1.07–1.71 1.37** 1.08–1.73 Age in months (ref = 36–59) 0–5 1.21 0.85–1.73 1.20 0.85–1.71 6–11 2.67*** 2.02–3.53 2.66*** 2.01–3.51 12–23 2.88*** 2.28–3.64 2.85*** 2.25–3.60 24–35 1.82*** 1.40–2.36 1.80*** 1.30–2.34 OVC (ref = Non-OVC) 1.43* 1.01–2.02 1.27 0.90–1.80 Maternal education (ref = Secondary or above) No education 0.63** 0.47–0.84 0.63** 0.47–0.85 Primary education 0.70* 0.53–0.93 0.69** 0.53–0.92 Household wealth (ref = Richest) Richer 1.19 0.76–1.87 1.15 0.74–1.79 Middle 1.72* 1.06–2.82 1.61 0.97–2.65 Poorer 2.72*** 1.64–4.51 2.39** 1.38–4.14 Poorest 1.94* 1.13–3.32 1.60 0.88–2.91 Model statistics Coeff SE Coeff SE Log likelihood −2561.92 −2479.75 Comparison to previous model Chi-square 82.17*** Degrees of freedom 13 Random variance Intra-class correlation (ICC) 0.26* 0.13* Variance between neighborhoods 1.17*** 0.01 0.70*** 0.08 Intra-class correlation (ICC) measures the degrees of clustering with random intercepts. The correlation of the 2-level multilevel logistic regressions is calculated by σμ 2/ [σμ 2 + π2/3], where σμ 2 denotes neighborhood- level variance Abbreviations: AOR represents adjusted odds ratios for sample cluster, CI represents confidence interval * p < 0.05; ** p < 0.01; *** p < 0.001 Model 2 added the neighborhood characteristics. Compared to Model 1, their inclusion produced some reductions in the significance of the coefficients with respect to lifestyle; these consisted of household cooking method and household smoking status. These findings indicate that some lifestyle effects are somehow redundant with respect to neighborhood characteristics. Nevertheless hand-washing still had an independent and significant association with ARI symptoms. Turning to the neighborhood level, there were some significant effects of the neighborhood-level characteristics on the prevalence of ARI symptoms. Young children living in a community with a high proportion of OVC were more likely to have ARI symptoms (AOR = 1.74, p < 0.001). Furthermore, the OR of having ARI symptoms was higher for children living in the North West region. However, community education and community wealth were found not to be significant when trying to explain ARI symptoms. Finally, no significant differences were found in relation to urban versus rural residence. Model 2 also revealed a number of statistically significant individual background effects. The ORs for ARI symptoms were significantly higher for children living in households who were poorer compared with those living in the richest households. Surprisingly, compared to mothers with secondary or higher levels of education, a lower odds of having ARI symptoms were found among mothers with no education (AOR = 0.63; p < 0.01) and primary education (AOR = 0.69; p < 0.01). In addition, we did not find a statistically significant association between ARI symptoms and a number of other individual characteristics such as gender and OVC status. The multilevel models were able to assess the relationship between variation in lifestyle factors and the odds of having ARI symptoms. Using log likelihood statistics as a means to assess the model-fitting, Model 2 showed a significant improvement in fit over Model 1 [χ2 (13) = 82.17; p < 0.001], as shown at the bottom of Table 3 [37]. Furthermore, a significance decrease in neighborhood variance from 1.17 in Model 1 to 0.70 in Model 2 was observed. This means that about 40 % of ARI variance is attributable to neighborhood and other individual factors. These findings reveal a plausible contextual phenomenon that would seem to help shape the community differences among young children regarding having ARI symptoms. Discussion Using multilevel modeling to disentangle the dynamics of interplay occurring between each environmental niche, this study addressed gaps in the literature regarding lifestyle and health behaviors and their relationship with ARI symptoms, as well as further assessing the effect of neighborhood and individual characteristics on such relationships by including lifestyle factors at various levels, which in turn attributes the unexplained variation in ARI symptoms to different levels [38]. In the analyses, personal lifestyle factors showed a significant association with the children’s ARI symptoms. Young children living in households that used biomass fuel for cooking fuel indoor, or used biomass fuel for cooking fuel outdoor were more than two times more likely to have ARI symptoms than those living in households that use either kerosene/charcoal for cooking outdoors or where cooking was conducted in a separate place [16, 39, 40]. Children who practiced hand-washing had a 34 % lower odds of having ARI symptoms [11]. Nevertheless, the significant association found for the smoking status of household members regarding children’s ARI symptoms was reduced to non-significance after the inclusion of neighborhood and individual characteristics. Prior studies have suggested that second-hand smoke exposure in households is a risk factor with respect to ARI symptoms. However, it needs to be noted that Nigeria has one of the lowest levels of smoking prevalence around the world [41, 42] and taking this into consideration, the small proportion of active household smokers who live with children are still likely to expose them to an increased risk of ARI, but this may not have been detectable at the significance level used in this study [43, 44]. Inconsistent with prior studies [20, 34, 45], our findings do not indicate a significant association between contextual lifestyle factors at neighborhood level and the prevalence of ARI symptoms. This lack of significance at the neighborhood level points towards the possibility that the proximal lifestyle practiced within the household of a given likelihood has more relevance to the disease than any neighborhood effect. For instance, our findings do not show a significant association between communities that have a higher rate of cooking with biomass fuel indoors and children’s ARI symptoms. In a separate analysis not shown here, we found that the use by communities of biomass cooking fuels was prevalent in Nigeria irrespective of ARI status. This lack of variation may help to partially explain why these findings did not reach significance [20]. The homogeneity in exposure to biomass combustion in the place of residence is extensive. Guided by social ecological theory [21, 22], we proposed that several community characteristics, such as proportion of OVC within a community and the region of a community, can also be associated with ARI symptoms among young children showing an interplay between each environmental niche and child developing ARI symptoms, such as the proximal effect of the household level environment and lifestyles, specifically, where children are nested. This includes how it is determined by community level factors or resources, which intuitively are likely to interact with household lifestyles and behaviors. Our findings support our hypothesis that communities with a high OVC rate have significantly higher odds of having ARI symptoms among young children. In addition, the region of residence can also be another indicator of community characteristics. The North Eastern and North Western regions of Nigeria are exposed to higher levels of dust exposure; this is because these areas of Nigeria lie along the Gulf of Guinea trajectory. Specifically, dust and sand storms are not uncommon in these regions, namely across northern Nigeria [46]. In addition, homes situated on the road side exposed to road traffic pollution [47] and there also may be poor indoor ventilation of houses [48]. Furthermore, the northern Nigeria has suffered from serious political problems and religious unrest in recent times, which has resulted in within region migration [42]; it is within the regions affected by these factors that we have found young children are at higher risk of ARI symptoms. Yet, another plausible explanation for this variation in ARI symptoms at the regional level across Nigeria may be the presence of social and economic development spatial inequality between different areas [49]. Our analysis supports the findings of various prior studies [18], namely that the most vulnerable age for having ARI symptoms is between 12 months old and 23 months old. Overcrowding is another major reason for ARI symptoms as our results found that children with a higher birth order were also more likely to ARI symptoms. Yet, our analysis indicated a significant negative association between maternal education and ARI symptoms. This suggests that children born to uneducated mothers were less likely to develop ARI symptoms. This is in line with a pilot study from Indonesia, which found that a mother’s education level had an indirect effect on childhood pneumonia and respiratory illness [50]. It seems likely that educated mothers are more likely to be autonomous and thus are also more likely to be employed; this will result in their children being left alone or in care of someone whose lifestyle may influence or exacerbate the likely of symptoms of ARI. Another possibility is an underestimation of the occurrence of ARI symptoms due to recall bias of the event, ARI symptoms may not have been fully understood by uneducated mothers, or because the children of uneducated mothers have a higher likelihood of dying from ARI and thus being excluded from this study [13]. Finally, our findings did not find a gender difference regarding ARI symptoms in Nigeria and this is also consistent with prior findings [12]. The present study has used advances in multi-level modeling strategies in order to avoid the possibility of the bias that is often associated with sample clustering. Yet, our findings need to be interpreted within the context of the study’s limitations. In addition to the common limitations associated with self-reported measures of lifestyle factors, the association of individual and neighborhood factors with ARI symptoms might be influenced by endogeneity problems. Due to the cross-sectional nature of the data, this limits our ability to infer a causal relationship. In addition, having found that children living in poorer households using biomass fuel clearly have a high risk of dying from ARI, this leads to a possibility of some selection in the cross-sectional sample used in this study; this in turn leads to the possibility of a downward bias on the effect of cooking smoke on ARI symptoms. However, in the light of a high prevalence of ARI, together with the relatively small number of deaths in the sample, the effect of this bias on our estimated effect is likely to be minimal. In addition, recall bias and underreporting of ARI symptoms is also a possible issue among those living in households using biomass fuel, the majority of whom are individuals who are most likely to lack awareness of ARI symptoms during the 2-week period used in this study. This self-report measure thus may contribute to an underestimation of ARI symptoms as the information on ARI was not validated by a medical examination. In situation of a developing country such as Nigeria, where clinical information on ARI is usually not available or is relatively unreliable, the measure of ARI symptoms used in our study has been shown to provide an accurate estimation of ARI. On average, within a population; this is because the definition is based on a combination of three symptoms that are easily recognizable by mothers, namely fever, cough and rapid breath. Such an approach also has the advantage of minimizing misclassification [12]. It should be noted that due to data limitation, seasonal factors cannot directly be taken into account. However, prior research has validated ARI measures in DHS surveys by using the month of interview as a proxy season factor. Evidence shows no significant influence on the findings with and without this season factor [51]. Finally, our analyses are based on using sets of multilevel logistic models with random intercept and fixed coefficients only. Our findings cannot provide evidence of the effects of individual factors variance across neighborhoods. However, by using a multilevel analytical approach, our study does provide important insights and does identify lifestyle and health behaviors from a multilevel perspective in Nigeria, which is a country with a serious ARI epidemic. Future research is needed to assess the potential community differences in lifestyle and the longitudinal effect of this dynamic variable on ARI symptoms among young children in sub-Saharan Africa. Conclusions Despite the above caveats, the results from the present study fill several noteworthy gaps in the current literature. The large sample size of the Nigerian DHS survey permits extensive analyses of subgroups and their lifestyle and community differences; additionally, the unique design and sampling procedures provide an important opportunity for assessing the association between individual/household lifestyle characteristics, community influences and ARI symptoms. Much of the existing literature related to ARI symptoms among young children in African countries is descriptive and has been focused at the individual level. This study extends these efforts by examining neighborhood mechanisms through which differences in lifestyle and health behaviors and differences in neighborhood environment are associated with ARI symptoms. Furthermore, the DHS survey provides a wealth of information about several key constructs, namely lifestyle factors, OVC status, and neighborhood resources; this information allows an examination of patterns related to ARI symptoms among young children in much greater detail than has been possible in prior research. The findings on the lifestyle/health variables, and their relationships to ARI symptoms within this context, have thus been able to advance our knowledge. This will allow researchers and policy makers to evaluate the potential effectiveness of current programs that are aimed at improving public policy regarding ARI among young children. Abbreviations ARIAcute respiratory infection EAEnumeration area OVCOrphan and vulnerable child PSUPrimary sampling unit U5MUnder five mortality Acknowledgements The authors would like to thank the Editor and reviewers for their useful comments and suggestions for the improvement in the quality of this paper. Funding This work was supported by the Ministry of Science and Technology in Taiwan under grant 104-2628-H-010-001. Availability of data and materials The data supporting the findings of this study can be accessed from The DHS Program in http://dhsprogram.com/. Authors’ contributions OAA was responsible for development of study hypotheses, data analysis, and drafting of the article. CC contributed to developing study hypotheses, critical revision, and finalizing of the article. Both authors involved in the writing of the paper, and all approved the final submission. Authors’ information OAA is PhD candidate and a fellowship recipient for TaiwanICDF in International Health Program, National Yang Ming University, Taipei, Taiwan, R.O.C. CC is Professor of the Institute of Health Welfare Policy, School of Medicine, National Yang-Ming University, Taipei, Taiwan, R.O.C. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate This study was approved by the Institutional Review Board (IRB) of National Yang-Ming University in Taiwan (IRB number YM104025E-1). ==== Refs References 1. Walker CLF Rudan I Liu L Nair H Theodoratou E Bhutta ZA Global burden of childhood pneumonia and diarrhoea Lancet 2013 381 9875 1405 1416 10.1016/S0140-6736(13)60222-6 23582727 2. Liu L Johnson HL Cousens S Perin J Scott S Lawn JE Global, regional, and national causes of child mortality: an updated systematic analysis for 2010 with time trends since 2000 Lancet 2012 379 9832 2151 2161 10.1016/S0140-6736(12)60560-1 22579125 3. Dongre AR Deshmukh PR Garg BS Health expenditure and care seeking on acute child morbidities in peri-urban Wardha: a prospective study Indian J Pediatr 2010 77 5 503 507 10.1007/s12098-010-0063-8 20401704 4. Oyejide C, Osinusi K. Acute respiratory tract infection in children in Idikan community, Ibadan, Nigeria: severity, risk factors, and frequency of occurrence. Review of Infectious Diseases. 1990;12 (Supplement 8):S1042-SI046. 5. Wardlaw TM Johansson EW Hodge MJ Pneumonia: the forgotten killer of children 2006 New York United Nations Children’s Fund (UNICEF) 1 40 6. United Nations Children’s Fund (UNICEF) Commiting to Child Survival: A Promise Renewed Progress report 2015 [Internet] 2015 New York UNICEF 7. World Health Organisation/United Nations Children’s Fund. Countdown to 2015: Maternal, Newborn & Child Survival2012. Available from: http://www.countdown2015mnch.org/documents/2012Report/2012-part-1.pdf. 8. Weber MW Mulholland EK Greenwood BM Respiratory syncytial virus infection in tropical and developing countries Trop Med Int Health 1998 3 4 268 280 10.1046/j.1365-3156.1998.00213.x 9623927 9. Dahlgren G Whitehead M Policies and strategies to promote social equity in health 1991 Stockholm Institute for future studies 10. Cairncross S Editorial: Handwashing with soap—a new way to prevent ARIs? Trop Med Int Health 2003 8 8 677 679 10.1046/j.1365-3156.2003.01096.x 12869087 11. Rabie T Curtis V Handwashing and risk of respiratory infections: a quantitative systematic review Trop Med Int Health 2006 11 3 258 267 10.1111/j.1365-3156.2006.01568.x 16553905 12. Mishra V Indoor air pollution from biomass combustion and acute respiratory illness in preschool age children in Zimbabwe Int J Epidemiol 2003 32 5 847 853 10.1093/ije/dyg240 14559763 13. Kilabuko JH Nakai S Effects of cooking fuels on acute respiratory infections in children in Tanzania Int J Environ Res Public Health 2007 4 4 283 288 10.3390/ijerph200704040003 18180538 14. Mishra V Smith KR Retherford RD Effects of cooking smoke and environmental tobacco smoke on acute respiratory infections in young Indian children Popul Environ 2005 26 5 375 396 10.1007/s11111-005-0005-y 15. Gordon SB Bruce NG Grigg J Hibberd PL Kurmi OP Lam K-bH Respiratory risks from household air pollution in low and middle income countries Lancet Respiratory Med 2014 2 10 823 860 10.1016/S2213-2600(14)70168-7 16. Ezzati M Kammen DM Indoor air pollution from biomass combustion and acute respiratory infections in Kenya: an exposure-response study Lancet 2001 358 9282 619 624 10.1016/S0140-6736(01)05777-4 11530148 17. Sonego M, Pellegrin MC, Becker G, Lazzerini M. Risk Factors for Mortality from Acute Lower Respiratory Infections (ALRI) in Children under Five Years of Age in Low and Middle-Income Countries: A Systematic Review and Meta-Analysis of Observational Studies. PLoS ONE. 2015;10(1):e0116380. 18. Acharya P Mishra SR Berg-Beckhoff G Solid fuel in kitchen and acute respiratory tract infection among under five children: evidence from Nepal demographic and health survey 2011 J Community Health 2015 40 3 515 521 10.1007/s10900-014-9965-0 25388626 19. Marmot M Fair society, healthy lives : the Marmot Review : strategic review of health inequalities in England post-2010 [Internet] 2010 Torrington Place London University College London 20. Sellström E Bremberg S Review Article: The significance of neighbourhood context to child and adolescent health and well-being: A systematic review of multilevel studies Scand J Public Health 2006 34 5 544 554 10.1080/14034940600551251 16990166 21. Bronfenbrenner U The Ecology of Human Development: Experiments by Nature and Design 1979 Cambridge Harvard University Press 330 22. Mcleroy KR Bibeau D Steckler A Glanz K An ecological perspective on health promotion programs Health Educ Behav 1988 15 4 351 377 10.1177/109019818801500401 23. Bronfenbrenner U Bronfenbrenner U Ecolological models of human development International encyclopedia of Education 1994 2 Oxford Elsevier 37 43 24. Amoako Johnson F Padmadas SS Smith PW Orphanhood and vulnerability: a conduit to poor child health outcomes in Rwanda AIDS Care 2010 22 3 314 323 10.1080/09540120903193682 20390511 25. Watts H Gregson S Saito S Lopman B Beasley M Monasch R Poorer health and nutritional outcomes in orphans and vulnerable young children not explained by greater exposure to extreme poverty in Zimbabwe Trop Med Int Health 2007 12 5 584 593 10.1111/j.1365-3156.2007.01832.x 17445126 26. The World Bank Nigeria Mortality rate, under-5 (per 1,000) [Internet] 2015 NW Washington, DC The World Bank Group 27. World Health Organisation. Global Health Observatory (GHO) data; Child mortality and causes of death [Internet]. 2015 [cited 2015 Nov 23]. Available from: http://www.who.int/gho/child_health/mortality/en/. 28. International Vaccine Access Center (IVAC) Pneumonia and diarrhea progress report 2015:sustainable Progress in the Post-2015 Era [Internet] 2015 Baltimore John Hopkins Bloomberg School of Public Health 29. United States Agency for International Development (USAID) Demographic and Health Survey Sampling and Household Listing Manual [Internet] 2012 Calverton MEASURE DHS/ICF International 30. Nigeria National Population Commission Nigeria Demographic and Health Survey Preliminary Report [Internet] 2013 Calverton ICF International 31. Dlamini BN, Chiao C. Closing the health gap in a generation: exploring the association between household characteristics and schooling status among orphans and vulnerable children in Swaziland. AIDS care. 2015 (ahead-of-print):1–10. 32. Mishra VK Retherford RD Cooking smoke increases the risk of acute respiratory infection in children Natl Fam Health Surv Bull 1997 8 1 4 12293014 33. Chiao C Mishra V Sambisa W Individual-and community-level determinants of social acceptance of people living with HIV in Kenya: results from a national population-based survey Health Place 2009 15 3 742 750 10.1016/j.healthplace.2008.12.001 34. Adekanmbi VT, Kandala N-B, Stranges S, Uthman OA. Contextual socioeconomic factors associated with childhood mortality in Nigeria: a multilevel analysis. J Epidemiol Commun Health. 2015;69(11):1102–8. 35. Adedini SA Odimegwu C Imasiku EN Ononokpono DN Ibisomi L Regional variations in infant and child mortality in Nigeria: a multilevel analysis J Biosoc Sci 2015 47 02 165 187 10.1017/S0021932013000734 24411023 36. StataCorp Stata Statistical Software Release 13.0. College Station 2013 Texas Stata Corporation 37. Merlo J Chaix B Yang M Lynch J Rastam L A brief conceptual tutorial of multilevel analysis in social epidemiology: linking the statistical concept of clustering to the idea of contextual phenomenon J Epidemiol Community Health 2005 59 6 443 449 10.1136/jech.2004.023473 15911637 38. Rabe-Hesketh S Skrondal A Rabe-Hesketh S Skrondal A Dichotomous or binary responses Multilevel and longitudinal modeling using Stata 2008 Texas USA Stata Press 231 275 39. Torres-Duque C Maldonado D Perez-Padilla R Ezzati M Viegi G Forum of International Respiratory Studies Task Force on Health Effects of Biomass E. Biomass fuels and respiratory diseases: a review of the evidence Proc Am Thorac Soc 2008 5 5 577 590 10.1513/pats.200707-100RP 18625750 40. Smith KR Samet JM Romieu I Bruce N Indoor air pollution in developing countries and acute lower respiratory infections in children Thorax 2000 55 6 518 532 10.1136/thorax.55.6.518 10817802 41. Center for Public Policy Alternatives A Primer on Tobacco Consumption and Regulation in NigeriaLagos 2015 Nigeria CPPA 42. Greenhalgh E Bayly M Winstanley MH Trends in the prevalence of smoking. 3rd Edition ed. Scollo M, Winstanley M, editors 2008 Melbourne Cancer Council Victoria 43. Li JS Peat JK Xuan W Berry G Meta‐analysis on the association between environmental tobacco smoke (ETS) exposure and the prevalence of lower respiratory tract infection in early childhood Pediatr Pulmonol 1999 27 1 5 13 10.1002/(SICI)1099-0496(199901)27:1<5::AID-PPUL3>3.0.CO;2-5 10023785 44. Strachan DP Cook DG Health effects of passive smoking. 1. Parental smoking and lower respiratory illness in infancy and early childhood Thorax 1997 52 10 905 914 10.1136/thx.52.10.905 9404380 45. Roux AVD Merkin SS Arnett D Chambless L Massing M Nieto FJ Neighborhood of residence and incidence of coronary heart disease N Engl J Med 2001 345 2 99 106 10.1056/NEJM200107123450205 11450679 46. Ologunorisa T Tamuno T Spatial and seasonal variations of sandstorms over Nigeria Theor Appl Climatol 2003 75 1–2 55 63 47. Laumbach RJ Kipen HM Respiratory health effects of air pollution: update on biomass smoke and traffic pollution J Allergy Clin Immunol 2012 129 1 3 11 10.1016/j.jaci.2011.11.021 22196520 48. Ballard-Tremeer G, Mathee A. Review of interventions to reduce the exposure of women and young children to indoor air pollution in developing countries. WHO/USAID consultation on Indoor Air Pollution and Health May. 2000:3–4 49. Kandala N-B Ji C Stallard N Stranges S Cappuccio FP Spatial analysis of risk factors for childhood morbidity in Nigeria Am J Trop Med Hyg 2007 77 4 770 779 17978086 50. Shibata T Wilson JL Watson LM Leduc A Meng C La Ane R Childhood acute respiratory infections and household environment in an Eastern indonesian urban setting Int J Environ Res Public Health 2014 11 12 12190 12203 10.3390/ijerph111212190 25429685 51. Chiao C. Community vulnerability and symptoms of acute respiratory infection among preschool age children in the Democratic Republic of Congo, Malawi, and Nigeria: evidence from Demographic and Health Surveys. J Epidemiol Commun Health. 2016. In press.

PMC005xxxxxx/PMC5000496.txt

==== Front BMC Musculoskelet DisordBMC Musculoskelet DisordBMC Musculoskeletal Disorders1471-2474BioMed Central London 122110.1186/s12891-016-1221-6Research ArticleSpinal growth velocity versus height velocity in predicting curve progression in peri-pubertal girls with idiopathic scoliosis Shi Benlong shi-benlong@163.com 13Mao Saihu siemens_636@163.com 13Liu Zhen drliuzhen@163.com 13Sun Xu drsunxu@163.com 13Zhu Zezhang zhuzezhang@126.com 13Zhu Feng spine@vip.sina.com 13Cheng Jack C. Y. jackcheng@cuhk.edu.hk 23Qiu Yong +86-25-68182022scoliosis2002@sina.com 131 Spine Surgery, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Zhongshan Road No. 321, Nanjing, 210008 China 2 Department of Orthopaedics and Traumatology, Chinese University of Hong Kong, Hong Kong, China 3 Joint Scoliosis Research Center of the Chinese University of Hong Kong & Nanjing University, Nanjing, China 26 8 2016 26 8 2016 2016 17 1 36814 7 2016 13 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Height velocity (HV) is traditionally used to monitor the residual growth potential in idiopathic scoliosis (IS). The temporal timing of rapid increase in standing height often does not match exactly that of the increase in spine height. The purposes of this study were to analyze the correlation between change of angle velocity (AV) vs the changes of spinal growth velocity (SGV) and HV, and the associated predictive value on curve progression in IS. Methods Pre-pubertal IS girls with single curve receiving standardized bracing treatment followed longitudinally with documented curve progression >5° were retrospectively reviewed. The age, standing height, Cobb angle (main curve), spinal length, Risser sign, HV, SGV and AV at each visit were measured and calculated. The visit with the highest AV value of each patient was selected for the final analysis and correlated with the corresponding peak height velocity (PHV) and peak spinal growth velocity (PSGV). Results Sixty-two IS girls were reviewed. Chi-square test revealed PSGV contributed more to the highest AV than PHV (P = 0.001). Pearson correlation analysis demonstrated that AV was correlated with SGV (r = 0.454, P < 0.001) and HV (r = 0.280, P = 0.027). Multiple linear regression analysis showed that high AV was better predicted by higher SGV (B = 0.321, P = 0.007) rather than higher HV (B = 0.259, P = 0.362) (R = 0.467). Conclusions Variations of spinal growth velocity exerted more direct influence over changes in angle velocity as compared with height velocity. High spinal growth velocity predisposed to more rapid curve progression in patients with idiopathic scoliosis. Keywords Idiopathic scoliosisSpinal growth velocityHeight velocityAngle velocityCurve progressionthe National Natural Science Foundation of China 81301603Mao Saihu the Development Project of Nanjing Science and Technology Commission and Foundation201402028Sun Xu issue-copyright-statement© The Author(s) 2016 ==== Body Background Idiopathic scoliosis (IS) is prevalent among adolescents during the pubertal spurt and in the severe cases, may lead to significant morbidities [1, 2]. The risk of curve progression was found to correlate significantly with period of rapid skeletal linear growth and in particular the time relative to the peak height velocity (PHV) [3, 4]. The height velocity (HV) has thus provided useful reference information of the residual growth potential and could inform the treatment strategy clinically [5, 6]. The calculation of HV, however, would require serial longitudinal data of standing height, comprising the summation of the sitting height and subischial height. Busscher et al. [7] reported that growth occurs in multi-dimensions, at different rates in different parts of the body, and noted the existence of a distal-to-proximal growth gradient in adolescents. The temporal timing of the rapid increase of standing height during pubertal spurt often does not match exactly that of the increase in spine height. The alternative of using sitting height to avoid the influence of asynchronous growth in the lower limbs is also limited by the lack of reliable methods in assessing the true loss of spinal length resulting from curve progression [8]. We hypothesized that direct monitoring of spinal growth velocity (SGV), free of the two aforementioned limitations, might have higher predictive value of curve progression during the rapid pubertal growth as compared to the conventional HV in IS. Current information concerning the velocity of spinal growth and its relationship with curve progression is, however, inadequate. The aims of this study were to analyze the correlation between change of angle velocity vs the changes in growth velocity of standing height and spine height, and the associated predictive value on curve progression in idiopathic scoliosis. Methods Subjects This retrospective study was approved by the Ethics Committee of Drum Tower Hospital of Nanjing University Medical School. IS patients treated with standardized bracing programme from January 2008 to September 2010 with complete set of serial anthropometric and radiographic measurements were reviewed. The indication for bracing treatment were: (1) initial chronologic age <14 years and menarche age <1 year; (2) Risser sign between 0 and 2; (3) initial major curve magnitude between 20 and 40°; and (4) no prior treatment history. Enrolment into the current study was limited to: (1) IS girls with single thoracic or thoracolumbar/lumbar curve treated with standard Milwaukee or Boston brace and followed up until brace weaning [9]; (2) menarche age less than 6 months and Risser 0 at the initiation of bracing; (3) compliance of the bracing treatment of more than 75 %; and (4) curve progression of more than 5° at final follow-up. The exclusion criteria were: (1) patients with previous spinal surgery; (2) patients with any signs of growth abnormalities (such as a lower extremity growth arrest or deficiency), neurological abnormality, skeletal dysplasia or dwarfism. Anthropometric and radiographic measurements For the anthropometric data, standing height was measured in centimeters by a senior resident using a wall-mounted ruler with a perpendicular slide at each visit in standing position, looking straight ahead without shoes, socks or brace. For radiographic measurement, standing anteroposterior radiographs of the whole spine without orthosis were taken. The coronal spinal length measurements were made on digital images at the PACS (Picture Archiving and Communications Systems, PACS) workstation. The intersection of catercorner in each vertebral body was defined as the centre of the vertebral body. Total length from radiographs along the line reaching the midpoint of both the superior and inferior endplates from T1 to L5, as well as the centre of each vertebral body in between was defined as the coronal spinal length (Fig. 1) [10, 11]. The calculation of HV and SGV were defined as the growth obtained from dividing the height increase by the time interval between two consecutive clinic visits at a minimal interval of 6-months [4, 12]: HV(SGV) = (Height (coronal spinal length)n – Height (coronal spinal length)n-1) /(Time interval n−(n−1)). A growth velocity curve was then constructed for each patient. The age, at which the maximum growth velocity occurred, was designated as the peak height velocity (PHV) and peak spinal growth velocity (PSGV), respectively [12, 13].Fig. 1 Spinal length was measured by the line through the midpoints of superior endplate, diagonal intersection of each vertebra, midpoints of inferior endplate and discs from the superior endplate of T1 to the inferior endplate of L5. The major and minor curves were (a) 25° and (b) 16°, respectively The Cobb angle of the major curve of each subject was consecutively measured. Angle velocity (AV) was defined as increase in Cobb angle divided by the time interval between two consecutive clinic visits at a minimal interval of 6-months, expressed in angle degrees per year: AV = (Anglen-Anglen-1) /(Time interval n−(n−1)) [12]. The US Risser staging system was adopted [14]. For each patient, the visit with the highest AV value during the longitudinal follow-up together with the corresponding anthropometric and radiographic measurements, were selected for the final statistical analysis. For the radiological measurements, a senior resident and a senior attending spine surgeon respectively measured the spinal length and Cobb angle twice at an interval of 1 week and the mean values were adapted for the analysis. Statistical methods Data were statistically analyzed with the SPSS Statistics (v 17.0) software packages. The measured values were expressed as mean and standard deviation (SD). Descriptive statistics was performed to analyze patients’ demographics. For the intra- and inter-observer reliability analysis, the intraclass correlation coefficient (ICC) was calculated. The Chi-square test was used to compare the percentages of PHV and PSGV in the selected cases. The 2-tailed Pearson coefficients of correlation were calculated to assess the relationships between AV, SGV and other maturity indicators. Multiple linear regression analysis was performed to analyze the contributions of each maturity assessments to AV. Statistically significant difference was defined as P < 0.05. Results A cohort of 62 IS girls were included in the study (Table 1). The average values of PHV and PSGV were 11.7 ± 4.6 cm/year (range, 4.0–20.5 cm/year) and 32.7 ± 15.4 mm/year (range, 8–93.3 mm/year), respectively, and the average timing of PHV and PSGV were 11.6 ± 1.4 years (range, 9.2–14.1 years) and 12.2 ± 2.3 years (range, 9.1–14.8 years), respectively. Table 2 showed the relatively good intra- and inter-observer reliabilities in the measurement of spine length.Table 1 Summary of the 62 follow-up selected from 62 patients Mean (SD) Range Spine length (mm) 340.9 (20.0) 283–394 SGV (mm/year) 21.0 (13.4) 3–70 Standing height (cm) 155.2 (6.6) 132.5–165.5 HV (cm/year) 7.1 (4.9) 0.67–20.5 Cobb angle (°) 28.0 (6.0) 20–40 AV (°/year) 12.0 (10.6) 3.3–50 AV angle velocity, SGV spinal growth velocity, HV height velocity Table 2 Intra- and inter-observer reliabilities analysis Parameters Intra-observer reliability (observer 1/observer 2) Inter-observer reliability Standing height 0.913/- - Spinal length 0.738/0.707 0.738 Cobb angle 0.938/0.946 0.833 Chi-square test PHV was identified in 18 (29.0 %) and PSGV in 37 (59.7 %) cases, respectively. The Chi-square test revealed that PSGV contributed more to the occurrence of highest AV than PHV (P = 0.001). A demo case was shown in Fig. 2.Fig. 2 A demo case illustrating the influence of variations of growth velocity in relation to fluctuation of curve progressive velocity. a: Longitudinal curves of height velocity, spinal growth velocity, angle velocity and Cobb angle were constructed respectively. a & b: peak angle velocity occurred simultaneously with PSGV but not PHV Pearson correlation analysis Pearson correlation analysis revealed significant correlation between SGV and HV (r = 0.394, P = 0.002). In addition, AV was significantly correlated with SGV (r = 0.454, P < 0.001) and HV (r = 0.280, P = 0.027), respectively. In contrast, no statistically significant correlation was detected between AV and other indicators of growth potential (Table 3).Table 3 Correlation between AV/SGV and maturity indicators AV SGV r P r P Chronologic age −0.068 0.599 −0.013 0.981 Risser sign −0.155 0.229 −0.121 0.350 Spine length −0.169 0.190 −0.028 0.831 SGV 0.454 <0.001 1 - Standing height −0.117 0.363 −0.242 0.059 HV 0.280 0.027 0.394 0.002 Cobb angle 0.189 0.142 0.037 0.773 Abbreviation: Refer to Table 1 Multiple linear regression analysis Interactions between AV and the maturity parameters including chronologic age, Risser sign, spinal length and standing height, together with Cobb angle of main curve were tested and excluded. The multiple linear regression analysis (Table 4) demonstrated that high AV was significantly predicted by higher SGV (B = 0.321, 95 % CI = 0.142–0.620, P = 0.007) rather than higher HV (B = 0.259, 95 % CI = −0.190–0.912, P = 0.362) (R = 0.467).Table 4 Multiple linear regression analysis of AV B 95 % CI P Constant 3.393 −2.154–7.167 0.145 SGV 0.321 0.142–0.620 0.007 HV 0.259 −0.190–0.912 0.362 Abbreviation: Refer to Table 1 Discussion It is well known that the growth and curve progression in IS are closely interrelated [4, 15]. The most commonly used assessments of curve progression in IS included chronologic age, Risser sign, status of triradiate cartilage, menarche age, digital skeletal age, HV, secondary sexual characteristics, electromyography and hormonal levels [5, 10, 16–18]. A good and reliable understanding of the influence of peripubertal growth on the curve progression allows the surgeons to plan and prescribe the best strategy of treatment at the appropriate time. Sanders et al. [4] proved that the timing relative to peak height growth velocity was highly prognostic as it is significantly correlated with the curve acceleration phase. An increase of standing height more than 4 cm/year with curves more than 25° was significantly associated with increase in the angle velocity [19]. Escalada’s longitudinal study confirmed that PHV and peak angle velocity (PAV) took place simultaneously 1 year before menarche in progressive idiopathic scoliosis with bracing [12]. Despite being helpful as a first indication for curve acceleration phase, the predictive values of height velocity were partly downgraded by the existence of distal-to-proximal growth gradient in adolescents. The peak growth of distal body parts, for example, foot length or subischial leg length were found to precede the peak growth of more proximal body parts including the spine [7]. This growth gradient may introduce deviations when we use the height growth velocity as the first-line predictor of curve progression. Few studies, however, have been designated to investigate the influence of the spinal growth on curve progression. In this study, serial longitudinal spine growth data measured from standing anteroposterior radiographs and the calculated SGV was documented. These longitudinal growth data did confirm the existence of a time gap between growth peak of body height and spinal length by an average of 0.6 years (timing of PHV and PSGV were 11.6 years and 12.2 years). In addition, correlation of maturity indicators with changes of AV was only found to be significant with SGV and HV, respectively. A multiple linear regression model was created to further analyze the covariate effects of those which had significant association with AV in the crude analysis. Our results revealed that AV was significantly correlated with SGV rather than HV, indicating the major advantage of using SGV as an alternative to HV for predicting the change of AV. Similar results were reported by Ylikoski [20] that curve progression correlated with the spinal growth, and this correlation could be stronger with greater initial curve magnitude and with thoracic scoliosis. Wu et al. [21] reported that the correlation between spinal growth and curve progression was more prominent in the progressed group as compared with the stable group. This was in line with the fact that curve progression was determined by multiple factors, and spinal growth was one prominent but not the only decisive factor. A restricted cohort limited to progressive patients could help to highlight the accelerating effect of linear growth on curve progressive velocity in braced patients, as was confirmed in this study. In addition, the Chi-square test showed the percentage of PSGV was much higher than that of PHV in the selected 62 follow-up with highest AV values of each patient, which further support the closer relationship between high AV and high SGV. Wever et al. [10] reported that the expected spinal growth at diagnosis was crucially important to further curve progression. In this retrospective study [10], a significantly greater curve progression rate in the rapid to moderate spine growth (≥10 mm per year) as compared with the smaller or no spine growth period (<10 mm per year) was observed. Based on these reports and results of our study, patients with pubertal spinal growth spurt undergoing bracing treatment should be monitored strictly and carefully for compliance and progress. The underlying mechanism responsible for scoliosis progression during rapid spinal growth still remains controversial. It was hypothesized that the rapid asymmetric growth of the apical regions may result in exacerbated lateral deviation and curve progression according to the Hueter-Volkmann law [22]. Others have stressed the importance of the supportive musculoligamentous structures, which might fail to stabilize the growing spine because of the potential deficiency in the neuromuscular control system [23]. This theory was partially supported by the repeatedly confirmed association of susceptibility and curve progression of AIS with LBX1gene, which was expressed in the central nervous system and skeletal muscle and could play an important role in developmental processes [24]. Despite these plausible hypotheses, the detailed mechanism remains largely unknown. Several common limitations shared by growth-related studies need to be addressed. Firstly, this study was limited by its retrospective nature and the relatively small sample size confined to girls with single and progressive curves. The conclusion might not be appropriate for complex curves in which the growth velocity might have a different influence on curve progression. The bracing treatment could significantly affect the curve progressive velocity. Despite the limitations, we do believe that analyzing the correlation between curve progression velocity and spinal growth velocity vs height velocity could provide useful information for the surgeon in designing the brace treatment strategy. Conclusions This study has attempted to bridge the gap between spinal growth and curve progression. It was confirmed that variations of spinal growth velocity exerted more direct influence over changes in angle velocity (curve progressive velocity) as compared with height velocity in IS girls. In addition, high spinal growth velocity was found to predispose to higher incidence of rapid curve progression in the early pubertal period. Abbreviations AVAngle velocity HVHeight velocity ISIdiopathic scoliosis PHVPeak height velocity PSGVPeak spinal growth velocity SGVSpinal growth velocity Acknowledgements This work was financially supported by the National Natural Science Foundation of China (81301603) and the Development Project of Nanjing Science and Technology Commission and Foundation (201402028). Availability of data and material The data and materials in current paper may be made available upon request through sending e-mail to first author. Authors’ contributions YQ, JC and ZZ conceived the study and design. ZL and XS undertook acquisition of data. BS and FZ contributed materials essential for the study. BS and SM analyzed and interpreted the data and drafted the manuscript. ZZ and YQ performed critical revision of the manuscript. YQ and JC supervised the study. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Written consent for publication was provided by the parents of the participant to be included in the study. Ethics approval and consent to participate The Drum Tower Hospital’s review board approved this retrospective study and waived the requirement for written informed consent to review the radiographs and clinical data of enrolled patients. ==== Refs References 1. Lam TP Hung VW Yeung HY Chu WC Ng BK Lee KM Qin L Cheng JC Quantitative ultrasound for predicting curve progression in adolescent idiopathic scoliosis: a prospective cohort study of 294 cases followed-up beyond skeletal maturity Ultrasound Med Biol 2013 39 3 381 387 10.1016/j.ultrasmedbio.2012.09.012 23245828 2. DiMeglio A Canavese F Charles YP Growth and adolescent idiopathic scoliosis: when and how much? J Pediatr Orthop 2011 31 1 Suppl S28 36 10.1097/BPO.0b013e318202c25d 21173616 3. Ylikoski M Growth and progression of adolescent idiopathic scoliosis in girls J. Pediatr. Orthop. B 2005 14 5 320 324 10.1097/01202412-200509000-00002 16093941 4. Sanders JO Maturity indicators in spinal deformity J Bone Joint Surg Am 2007 89 Suppl 1 14 20 10.2106/JBJS.F.00318 17272419 5. Loncar-Dusek M Pecina M Prebeg Z A longitudinal study of growth velocity and development of secondary gender characteristics versus onset of idiopathic scoliosis Clin Orthop Relat Res 1991 270 278 282 1884550 6. Song KM Little DG Peak height velocity as a maturity indicator for males with idiopathic scoliosis J Pediatr Orthop 2000 20 3 286 288 10823591 7. Busscher I Gerver WJ Kingma I Wapstra FH Verkerke GJ Veldhuizen AG The growth of different body length dimensions is not predictive for the peak growth velocity of sitting height in the individual child Eur Spine J 2011 20 5 791 797 10.1007/s00586-010-1584-6 20936309 8. Bjure J Grimby G Nachemson A Correction of body height in predicting spirometric values in scoliotic patients Scand J Clin Lab Invest 1968 21 2 191 192 10.3109/00365516809084283 5706641 9. Xu L Qiu X Sun X Mao S Liu Z Qiao J Qiu Y Potential genetic markers predicting the outcome of brace treatment in patients with adolescent idiopathic scoliosis Eur Spine J 2011 20 10 1757 1764 10.1007/s00586-011-1874-7 21691901 10. Wever DJ Tonseth KA Veldhuizen AG Cool JC van Horn JR Curve progression and spinal growth in brace treated idiopathic scoliosis Clin Orthop Relat Res 2000 377 169 179 10.1097/00003086-200008000-00023 10943199 11. Cheung J Veldhuizen AG Halberts JP Sluiter WJ Van Horn JR Geometric and electromyographic assessments in the evaluation of curve progression in idiopathic scoliosis Spine 2006 31 3 322 329 10.1097/01.brs.0000197155.68983.d8 16449906 12. Escalada F Marco E Duarte E Ma Muniesa J Boza R Tejero M Caceres E Assessment of angle velocity in girls with adolescent idiopathic scoliosis Scoliosis 2009 4 20 10.1186/1748-7161-4-20 19758424 13. Sanders JO Browne RH Cooney TE Finegold DN McConnell SJ Margraf SA Correlates of the peak height velocity in girls with idiopathic scoliosis Spine 2006 31 20 2289 2295 10.1097/01.brs.0000236844.41595.26 16985455 14. Risser JC The Iliac apophysis; an invaluable sign in the management of scoliosis Clin Orthop 1958 11 111 119 13561591 15. Shi B, Mao S, Xu L, Sun X, Zhu Z, Qian B, Liu Z, Cheng JC, Qiu Y. Integrated Multi-dimensional Maturity Assessments Predicting the High Risk Occurrence of Peak Angle Velocity During Puberty in Progressive Female Idiopathic Scoliosis. Clin Spine Surg. 2016. doi:10.1097/BSD.0000000000000203 16. Little DG Song KM Katz D Herring JA Relationship of peak height velocity to other maturity indicators in idiopathic scoliosis in girls J Bone Joint Surg Am 2000 82 5 685 693 10819279 17. Nault ML Parent S Phan P Roy-Beaudry M Labelle H Rivard M A modified Risser grading system predicts the curve acceleration phase of female adolescent idiopathic scoliosis J Bone Joint Surg Am 2010 92 5 1073 1081 10.2106/JBJS.H.01759 20439651 18. Mao SH Li HB Jiang J Sun X Cheng JC Qiu Y An updated analysis of pubertal linear growth characteristics and age at menarche in ethnic Chinese Am J Hum Biol 2011 23 1 132 137 10.1002/ajhb.21116 21080381 19. Yrjonen T Ylikoski M Effect of growth velocity on the progression of adolescent idiopathic scoliosis in boys J. Pediatr. Orthop. B 2006 15 5 311 315 10.1097/01202412-200609000-00001 16891955 20. Ylikoski M Spinal growth and progression of adolescent idiopathic scoliosis Eur Spine J 1993 1 4 236 239 10.1007/BF00298366 20054924 21. Wu H Ronsky JL Cheriet F Harder J Kupper JC Zernicke RF Time series spinal radiographs as prognostic factors for scoliosis and progression of spinal deformities Eur Spine J 2011 20 1 112 117 10.1007/s00586-010-1512-9 20661754 22. Stokes IA Spence H Aronsson DD Kilmer N Mechanical modulation of vertebral body growth. Implications for scoliosis progression Spine 1996 21 10 1162 1167 10.1097/00007632-199605150-00007 8727190 23. Dobosiewicz K Neurophysiological mechanism of the unloading reflex as a prognostic factor in the early stages of idiopathic adolescent scoliosis Eur Spine J 1997 6 2 93 97 10.1007/BF01358739 9209875 24. Jiang H Qiu X Dai J Yan H Zhu Z Qian B Qiu Y Association of rs11190870 near LBX1 with adolescent idiopathic scoliosis susceptibility in a Han Chinese population Eur Spine J 2013 22 2 282 286 10.1007/s00586-012-2532-4 23096252

PMC005xxxxxx/PMC5000497.txt

==== Front BMC Med EducBMC Med EducBMC Medical Education1472-6920BioMed Central London 74510.1186/s12909-016-0745-7Research ArticleThe Doctor of Medicine curriculum review at the School of Medicine, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania: a tracer study report from 2009 Mwakigonja Amos Rodger rodgeramos@yahoo.com Department of Pathology, Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam, Tanzania 25 8 2016 25 8 2016 2016 16 1 2237 4 2016 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The School of Medicine (SoM) is one among five at Muhimbili University of Health and Allied Sciences (MUHAS). It currently houses eight undergraduate and many post-graduate programmes. The Doctor of Medicine (MD) programme reported herein is the oldest having ten semesters (5 years) followed by a 1 year compulsory rotatory internship at a hospital approved by the Medical Council of Tanganyika (MCT). However, this training was largely knowledge-based and thus the need to shift towards competency-based education (CBE) and full modularization necessitated this study. Methods A cross-sectional tracer study of MUHAS MD graduates from SoM who completed training between 2006 and 2008 was conducted using quantitative (structured interviewer-administered questionnaires) as well as qualitative methods [In-depth questionnaire (IDI) and Focus group discussions (FGDs)]. Results A total of 147 MD graduates were traced and interviewed, representing 29 % of the 510 students who graduated from the SoM between 2006 and 2008. Majority (70.1 %, n = 103/147) were males. About 70 % graduated in 2008 and majority (68 %, n = 100/147) were doing internship. Majority (60.5 % n = 89/147) were based in/near Dar es Salaam at district, regional or referral hospitals. With reasonable concordance, most competencies ranked low except on four aspects. Teaching, System-based Practice and Good Practice had the lowest. Seminars/Tutorials, Laboratory Skills/Practicals, Theatre Skills, Outpatients clinics, Family Case Studies, Visits/Excursions and Self Reflection were rated less useful teaching methods compared to Lectures, Teaching Ward Rounds, Elective Studies, Field Work, Presentations, Continuous Assessments Tests, Final Examinations, Short Answers, Clinical/Practical Examinations. ICT and Library facilities were not considered to meet the students learning needs and Clinical Logbooks also ranked low. Teachers were generally ranked less favorably including in professional role-modelling and accessibility outside scheduled teaching sessions. Conclusions This tracer study results allowed subsequent curriculum review and the introduction of full modularization and competency-based learning at MUHAS. It is envisioned that these tracer study findings will improve teaching, learning and inform next curriculum review at MUHAS leading to increased output of appropriately trained health professionals to fill the big gap in human resources for health (HRH) in Tanzania. The revised curricula are also being processed through TCU for accreditation as required. Electronic supplementary material The online version of this article (doi:10.1186/s12909-016-0745-7) contains supplementary material, which is available to authorized users. Keywords Curriculum reviewDoctor of medicineTracer studyTanzaniaissue-copyright-statement© The Author(s) 2016 ==== Body Background Curricula for academic programs need to be reviewed from time to time in order to ensure that they are current with respect to socio-economic and demographic changes at national and global levels, as well as changes in community needs and technological advances [1]. In the case of curricula for health sciences, reviews also need to take into consideration the changing pattern of disease occurrence and the increasing demands for health care. Therefore, the University recommends review of academic curricula after every 5 years. However, curriculum revision should always be informed by findings from tracer studies as well as being guided by assessment for competencies and skills including their reflections on the curriculum they went through and how much they find it useful/not useful during their post-graduation practice [1, 2]. The revised curricula should also be processed through the Tanzania Commission for Universities (TCU) for accreditation as required. It is in this light that the School of Medicine as well as other schools at MUHAS have conducted two tracer studies since the commencement of the semesterized programmes about 7 years ago [3]. In these studies, medical graduates, their co-workers, employers as well as their end-users (patients) were interviewed while selective graduates also had in-depth questionnaires and focus group discussions. Herein we report the results of the second tracer study. The aim was to evaluate how much graduates displayed those competencies and skills and whether they performed better or worse compared to graduates from other medical schools [3]. Setting of the School of Medicine The School of Medicine started as the Dar es Salaam School of Medicine in 1963 with initial intake of eight students. In 1968, the school was upgraded to a Faculty of Medicine of the Dar es Salaam University College, which was a constituent College of the University of East Africa [4]. In 1970, the University of East Africa ceased to exist and the Dar es Salaam University College became the University of Dar es Salaam, whereby the Faculty of Medicine became one of its units. In 1977, following the creation of Muhimbili Medical Centre (MMC), the Faculty of Medicine administratively merged with Muhimbili Hospital. Subsequently, in 1991, the Faculty of Medicine was upgraded to a College and its name changed to Muhimbili University College of Health Sciences (MUCHS), consisting of four Faculties (Medicine, Pharmacy, Dentistry and Nursing) and five institutes (Public Health, Traditional Medicine, Primary Health Care and Continuing Medical Education, Development Studies and Allied Health Sciences). In 2003, after MMC ceased to exist, MUCHS and Muhimbili National Hospital (MNH) became autonomous and the Faculty of Medicine was changed to the School of Medicine (SoM) [4]. Beginning January 2007, the SoM is one of the units under the Muhimbili University of Health and Allied Sciences (MUHAS). This followed the upgrading of MUCHS into MUHAS following the signing of the charter establishing the University on 28th March 2007 by H.E. the President of the United Republic of Tanzania [4]. The former and current tracer studies The first tracer study was conducted in 2003 by the then Muhimbili University College of Health Sciences (MUCHS) thus there was a need to revise the existing curriculum in 2009. This activity was preceded by a change of the former term system to a semesterized teaching system. The aim of the first Tracer Study was to obtain baseline information from the former graduates, their employers and end users for the purpose of guiding the curriculum review process for the different academic programs and also to serve as a point of reference for future follow-up tracer studies. Specifically the first Tracer Study aimed to establish the needs of employers of MUCHS graduates; determine the market demand for the MUCHS graduates; obtain information on the adequacy of the existing programs at MUCHS; establish the expectations of the end-users regarding the roles of MUCHS graduates and the level of acceptability of the MUCHS graduates to the community they serve. The current tracer study was the second one that was conducted in order to generate information that would inform revision of the curriculum [2]. The overall goal was to obtain important information for developing competency-based curricula that are relevant to the national socio-economic development; respond to market demands and stakeholders needs; and conform to MUHAS vision and educational standards. It is envisioned that this would in turn improve teaching and learning and lead to increased output of appropriately trained health professionals to fill the big gap in human resources for health in the country [3, 5]. The current tracer study was included in the Academic Learning Project which was funded by the Bill and Melinda Gates Foundation through the MUHAS-UCSF Partnership under the Directorate of Continuing Education and Professional Development (DCEPD) at MUHAS [1, 6, 7]. Purpose of the tracer study and development of competency-based MD curriculum The current tracer study report has covered MD graduates only because BMLS and BSc. RTT programmes were still new at the time of revision and did not yet have graduates to be traced. In this regard, recent medical graduates from SoM who had undergone training through the semesterized MD programme, where assessed as to how much they felt they possessed competencies and skills including the MUHAS core competencies as well as those specific for the MD degree; and how much they felt enabled/empowered or disadvantaged by the curriculum they went through [3]. The overall goal was to develop competency-based curricula,that are relevant to the national socio-economic development; respond to market demands and stakeholders needs; and conform to MUHAS vision and educational standards. The findings of the index tracer study directly informed and guided the ongoing curriculum review exercise including the introduction of MUHAS core as well as MD-specific competencies and skills; repackaging of the curriculum, full modularization, increased inter-professional interactions and teamwork as well as other improvements. Methods Study design This was a cross-sectional tracer study of MUHAS MD graduates from SoM who completed training between 2006 and 2008 was conducted using quantitative (structured interviewer-administered questionnaires) as well as qualitative methods [In-depth questionnaire (IDI) and Focus group discussions (FGDs)]. Study area The study was based at the School of Medicine (SoM) which is one among five at Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam, Tanzania. It currently houses eight undergraduate and many post-graduate programmes (Additional file 1 attached). The Tracer Study tools were designed based on the information obtained from the gap analysis exercise that was carried out for each course by representatives of all Schools and Institutes. Sampling and inclusion/exclusion criteria In August 2009, teams of MUHAS academic staff and students traveled to Ilala, Kinondoni, Temeke, Mkuranga, Kisarawe, Bagamoyo, Rufiji, Mwanza, Mbeya, Arusha, Moshi, Tanga and Dodoma to administer questionnaires and interviews. These areas represented Dar es Salaam and upcountry regions and also were chosen for logistical reasons including proximity and presence of major tertiary hospitals were many graduates could be found. Medical students who had graduated between 2006 and 2008 and were located at their places of employment (hospitals, clinics, dispensaries, government agencies and other places) were included, as well as their co-workers, supervisors and employers. In some cases their clients/patients were also interviewed. Graduates before 2006 were not included since they did not use the existing semesterized curriculum. Non-MD graduates were also excluded from this study. Quantitative methods The topics of the questionnaires covered: 1) the demographics of those interviewed; 2) assessment of the competencies of MUHAS graduates by the graduates and by their employers; 3) assessment by the graduates of the relevance and organization of the courses at MUHAS; and 4) assessment by the graduates of the learning/teaching environment (Additional file 2). The competencies used in the questionnaires were grouped as: a) general competencies expected of all MUHAS graduates; b) specific professional competencies expected of the graduates from a school/institute; and c) specific clinical/practical competencies expected of the graduates from a school/institute (Additional file 3). Survey data were entered into the database program, WAMP, and then transferred to SPSS for analysis. All opinions were scored using a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). For each item scored using the Likert scale, mean and standard deviation scores were calculated as well as the percentage of respondents who agreed with the statement (that is responses of either “strongly agree” or “agree”). Thus, figures in cells (Additional file 4) are the percentages agreeing, mean (SD) of Likert Scale from 1 to 5. A mean reading of ≥4 is defined as high while that <4 is low. Qualitative methods In-depth questionnaire (IDI) During this tracer study, the School of Medicine also conducted qualitative research including in-depth interviews (IDI) as well as focused group discussions (FGD). Recent SoM graduates were surveyed about their experiences with the MUHAS medical curriculum. IDI responses were solicited in regards to specific courses of their choosing. The main areas that students were asked to comment on were the strengths of the course, the weaknesses of the course and suggestions for improvements to the course. Several overarching themes emerged from these responses; including references to professors, practical experience, over enrolment, facilities and educational materials, curricular content and finally duration of courses. Each main theme will be defined and discussed with references to strengths, weaknesses and necessary improvements. The preliminary analyses were prepared by members of the Academic Learning Project (ALP). Further analyses were conducted by the ALP Metrics Team after findings were shared with the Schools and Institute. Focus group discussions (FGDs) A series of focus groups were conducted in the summer of 2009 with recent graduates from the Muhimbili University of Health and Allied Sciences (MUHAS) and these were conducted in conjunction with University of California, San Francisco (UCSF). These focus groups were made up of six to eight recent graduates who had finished their programme of study in the spring of 2009. Students were grouped according to the school from which they graduated. There were six groups representing the Medical, Dentistry, Nursing, Pharmacy Schools and the Allied Health Science and Environmental Health programs. The discussions explored graduates perceptions of the curriculum and possible improvements. Discussion focused on over enrolment, facilities, supplies and faculty, preparation for practical work and fieldwork experiences. Students provided very specific recommendations for each health science school, which is included in a section of this report. Discussions were semi-structured and included prompt questions soliciting opinions on the challenges of the curriculum and how students propose to improve them Focus group discussions were recorded and transcribed. Data was then coded and analyzed according to major themes. In order to provide information for the curriculum revision, this report focuses mostly on constructive criticism directed at areas in need of improvement whereas in the focus group discussions focused both on praise and criticism. Major themes of discussion included facilities and supplies, over enrolment, educational time frame, theoretical preparation for practical work, experiential learning and fieldwork, communication, course load, skills and faculty. These themes are discussed below, followed by specific improvements that were proposed in each school. Participants The student focus groups were held in July of 2009 with 35 students who had recently completed the degree in medicine. The focus group intended to seek information from these most recent graduates about their perceptions regarding the training that they received at MUHAS and professional competency. The 2009 graduates were our target focus group participants as they were not included in the Tracer study having not yet assumed professional/ internship positions. Questionnaire design The focus group questions were designed by a team of MUHAS and UCSF faculty and students. The questions/prompts intended to illicit responses that would inform curriculum revisions. The questions explored the graduates’ perceptions around how competency is built and assessed and asked for specific feedback on programs of study. In this respect, the questions used were derived from the themes of questions in the Tracer study (Additional file 2). Data analysis The focus group discussions were tape recorded and transcribed. Translations were done from Swahili to English where needed. Transcripts were coded thematically. Results were analyzed according to theme across schools. These results use cross-cutting themes to report on the combined data from all schools. Additionally, student recommendations for specific programs were compiled according to school. Tracer study limitations Financial constraints limited coverage and duration of the study thus could not allow the tracing of graduates who were working in remote areas/or temporarily away from their work places The tracer study covered mostly centers within urban/semi-urban health care facilities Some few graduates were available but did not participate The questionnaire coding system did not allow the tallying of responses from co-workers, supervisor and employer to the graduate to allow direct feedback. Results Quantitative studies results General demographics and geographic coverage of MD graduates A total of 147 MUHAS MD Graduates were traced and interviewed, representing 29 % of the 510 students who graduated from the School of Medicine between 2006 and 2008 (Table 1). Seventy percent of those interviewed had graduated in 2008, representing 51 % of those who had graduated in that year. The distribution by district of employment is shown in Table 2. Majority (60.5 %, n = 89/147) were based in or near Dar es Salaam (Fig. 1). Only 3 graduates were missing during the interviews and all were from 2009. Majority of graduates during the study period were males below 30 years of age although data on age for some few (5.4 %, n = 8/147) participants was missing (Fig. 2, Table 3). However, data on sex was available for all interviewed graduates. The distribution of MD graduates according to the type of employment and organization where they are currently employed is shown in Table 1.Table 1 Distribution of MUHAS MD graduates by employing organization Employing organization Ministry or district health administration 37 25.2 National hospital 14 9.5 Regional or referral hospital 34 23.1 Private or religious hospital 11 7.5 University or training institution 9 6.1 International non-governmental organization or agency 1 0.7 Other 17 11.6 Missing 24 16.3 Total 147 100.0 NB Majority of MUHAS graduates during the study period were working in public hospitals in either referral, regional or district health administrations Table 2 MD graduates interviewed for the 2009 Tracer Study Total number who graduated Number interviewed Number interviewed as a % of those who graduated Percentage interviewed by year of graduation Graduation year 2006 134 12 9.0 8.2 2007 175 28 16 19.0 2008 201 103 51.2 70.1 2009 1 – 0.7 Missing 3 – 2.0 Total 510 147 29.2 100.0 Fig. 1 Pie Chart showing the distribution of interviewed graduates by supervisor by site (district of working station). Majority were working in/near Dar es Salaam Fig. 2 Bar Chart showing the demographic characteristics of interviewed graduates. Majority of MUHAS graduates during the study period were males below 30 years of age Table 3 Demographics and employment status of the interviewed graduates Number % Sex Male 103 70.1 Female 44 29.9 Missing 0 0.0 Total 147 100.0 Age in years 25 6 4.1 26 13 8.8 27 17 11.6 28 41 27.9 29 28 19.0 30 15 10.2 31 6 4.1 32 5 3.4 34 2 1.4 35 2 1.4 38 1 .7 39 3 2.0 Missing 8 5.4 Total 147 100.0 Employment status Intern 100 68.0 Full time 33 22.4 Part time 1 .7 Contract 13 8.8 Missing 0 0.0 Total 147 100.0 General observations Majority (60.5 %) of graduates from the 2008 year group were based around the Dar es Salaam region. Majority of these graduates were male and working as interns (housemen). Most competencies ranked low including teaching skills, health care system and good practice which had the lowest and respondents seemed generally in agreement were rating was low (Table 4).Table 4 Competencies common to all MUHAS graduates Competence Figures in cells are the percentages agreeing, mean (SD) of Likert Scale from 1 to 5, where 1 = strongly disagree and 5 = strongly agree Graduate n = 147 Supervisor n = 48 Supervisor n = 48 I was “trained to” “Professionals are expected to” “Graduate is able to” B1: Relationships with patients Establish constructive relationships and communicate effectively with patients, clients and/or communities in order to address their needs and preferences 84.9 % 95.6 % 80.0 % 4.29 (0.90) 4.71 (0.73) 3.98 (0.89) Provide service to individuals and groups that is appropriate to their different backgrounds 80.6 % 95.5 % 72.7 % 4.17 (1.02) 4.70 (0.73) 3.82 (1.10) Communicate health issues and polices effectively to the public 69.2 % 95.3 % 72.1 % 3.92 (1.08) 4.74 (0.73) 3.79 (1.08) B2: Relationships with colleagues Listen to and take advice from colleagues 84.2 % 97.7 % 68.3 % 4.34 (1.06) 4.82 (0.66) 3.68 (1.16) Motivate colleagues 72.6 % 97.6 % 56.8 % 3.97 (1.11) 4.68 (0.72) 3.55 (1.13) Contribute effectively to team work 82.2 % 97.7 % 65.9 % 4.27 0 (.90) 4.88 (0.62) 3.86 (0.95) Work effectively with other health professionals 84.7 % 97.7 % 75.0 % 4.30 (1.00) 4.82 (0.66) 4.07 (.90) B3: Teaching Prepare and deliver effective health promotion messages to educate communities 67.8 % 95.3 % 52.3 % 3.84 (1.08) 4.58 (0.76) 3.50 (1.02) Teach a course for health professionals or students 65.3 % 86.4 % 46.5 % 3.78 (1.26) 4.50 (0.93) 3.51 (0.93) B4: Good practice Systematically evaluate one’s own performance and practice 64.8 % 95.5 % 34.1 % 3.69 (1.11) 4.57 (0.76) 3.27 (1.06) Regularly seek information necessary to improve professional practice (life-long learning) 75.3 % 97.7 % 59.1 % 4.05 (1.10) 4.77 (0.68) 3.66 (1.14) Apply evidence-based decision making 74.3 % 97.6 % 59.5 % 4.03 (1.04) 4.67 (0.72) 3.57 (1.00) Participate in applied research activities 67.8 % 90.2 % 50.0 % 3.88 (1.16) 4.51 (0.75) 3.41 (1.23) Use information technology to optimize learning 50.7 % 97.6 % 55.0 % 3.48 (1.20) 4.71 (0.60) 3.65 (1.08) Show leadership and managerial skills 56.6 % 95.3 % 47.7 % 3.66 (1.15) 4.65 (0.65) 3.30 (1.17) B5: Health care systems Show knowledge of how the health care system functions (structures, policies, regulations, standards and guidelines) 60.0 % 90.7 % 44.4 % 3.80 (0.94) 4.56 (0.73) 3.44 (1.08) Work effectively in various health care delivery settings and systems (hospitals, government, ministries, NGO’s, communities, industry) 63.2 % 97.7 % 64.4 % 3.83 (1.00) 4.72 (0.59) 3.82 (1.01) Coordinate and implement health service delivery and health interventions within the health care system 66.9 % 97.7 % 53.3v 3.83 (1.048) 4.60 (0.62) 3.47 (0.94) Incorporate considerations of cost effectiveness into health service delivery 63.4 % 88.4 % 52.3 % 3.83 (1.02) 4.51 (0.77) 3.45 (1.00) Incorporate considerations of patient cost burden into health service delivery. 67.6 % 90.9 % 50.0 % 3.83 (1.04) 4.50 (0.73) 3.39 (1.06) Promote quality care in health systems through audits, accreditations, and/or evaluations 48.3 % 93.0 % 46.5 % 3.43 (1.22) 4.56 (0.70) 3.33 (1.15) Identify system challenges and implement potential solutions 55.2 % 94.9 % 46.5 % 3.59 (1.18) 4.56 (0.79) 3.44 (1.16) Maintain ethical standards (confidentiality, informed consent, avoid practice errors, avoid conflicts of interest) 94.5 % 97.7 % 73.9 % 4.59 (.70) 4.77 (0.68) 3.87 (1.24) Apply entrepreneurial skills for advancement of practice and the profession 51.0 % 88.1 % 51.1 % 3.46 (1.28) 4.38 (0.901) 3.47 (1.16) Show sensitivity and responsiveness to diversity (culture, age, socioeconomic status, gender, religion, and disability) 70.3 % 97.7 % 63.6 % 4.03 (1.03) 4.65 (.72) 3.73 (1.17) Show respect, compassion, and integrity while interacting with patients, clients, communities and health professionals 88.3 % 97.7 % 68.9 % 4.44 (0.86) 4.74 (0.69) 3.80 (1.14) Advocate and implement fair distribution of health care resources in Tanzania 64.3 % 90.7 % 51.2 % 3.85 (1.14) 4.63 (0.72) 3.47 (1.12) Specific observations Core competencies: Regarding the competency of relation with patients: All graduates were ranked low by supervisors and similarly for relation with colleagues: All were ranked low by supervisors except working effectively with other health professionals. Furthermore, for teaching, good practice, working within the system in the context of health care as well as professionalism, all sub-competencies were ranked low by graduates and supervisors. Professional knowledge: was favorably ranked in all aspects except that supervisors ranked the students low in knowledge of causes and progression of diseases, employing knowledge of non-communicable disease, common surgical conditions and common obstetrical and gynaecological conditions. Furthermore, Practical/Clinical Skills: All were also ranked low by supervisors except for universal precaution. As regards the assessment of some of MUHAS core competencies by graduates themselves in relation to their training; as well as what others expect from them and what they are finally able to perform, it was generally observed that expectations seemed to be higher than the training they received as well as the competencies and skills they were able to demonstrate in their practice (Fig. 3).Fig. 3 Bar Chart showing the assessment of some of MUHAS core competencies by graduates themselves in relation to their training; as well as what others expect from them including what they are finally able to perform. Generally, expectations seemed to be higher than the training they received as well as the competencies and skills they were able to demonstrate in practice Graduates opinions of courses undertaken at MUHAS: In the opinion of graduates, nine courses namely: Anatomy, Biochemistry, Behavioral Sciences, Development Studies, Introduction to Clinical Medicine, Nutrition Field Project, Clinical Pharmacology, Introduction to Clinical Medicine, Orthopaedics & Traumatology did not prepare them well enough for their professional needs after graduation. In the opinion of graduates, the courses that they studied in earlier semesters at MUHAS did not prepare them well to undertake the following courses: Behavioral Sciences, Development studies, Microbiology and Immunology, Introduction to Clinical Medicine, Pathology, Epidemiology and Research methodology, Nutrition Field Project, Forensic Pathology, Clinical Pharmacology, Medical Ethics, Orthopaedics & Traumatology. In the opinion of graduates, Seminars/Tutorials, Laboratory Skills/Practicals, Theatre skills, Outpatients clinics, Family Case Studies, visits/excursions and Self Reflection were rated as less useful teaching methods compared to Lectures, Teaching Ward Rounds, Elective Studies, Field Work and Presentations. ICT and Library facilities were not considered to meet the students learning needs as well as Clinical logbooks were ranked low as a method of assessment. Furthermore, Teachers were ranked less favorably in all assessed roles including professional role modelling by teachers, accessibility of teachers outside scheduled teaching sessions, monitoring of students, teaching sessions, academic advice given and nature of students’ relationship with teaching staff. Of these, teachers were ranked lowest for accessibility of teachers outside scheduled teaching sessions (Table 5).Table 5 Graduates opinions regarding the learning environment n = 147 Figures in cells are based on a Likert Scale from 1 to 5, where 1 = strongly disagree and 5 = strongly agree Numbers Percentage agree Mean (SD) “How useful were the following teaching method to helping you learn?” Lectures 104 79.90 % 4.07 (0.87) Seminars/Tutorials 83 69.90 % 3.90 (1.02) Laboratory skills/Practicals 118 51.70 % 3.54 (1.11) Theatre skills 123 45.50 % 3.39 (1.33) Teaching ward rounds 96 80.60 % 4.12 (0.99) Outpatients clinics 88 66.20 % 3.80 (1.02) Family case studies 117 47.20 % 3.37 (1.19) Elective studies 118 75.00 % 4.04 (0.91) Field work 121 78.60 % 4.17 (0.92) Presentation 90 86.80 % 4.32 (0.82) Self reflection 99 68.30 % 3.89 (1.03) visits/excursions 104 31.70 % 3.39 (1.58) “The following meet my learning needs” Computer lab 119 21.50 % 2.27 (1.35) Libraries 105 60.10 % 3.46 (1.23) Internet Access 99 23.90 % 2.39 (1.37) “How useful were the following assessment methods to your learning?” Continuous assessments 59 82.20 % 4.17 (0.92) Final examinations 108 76.70 % 4.14 (0.91) Multiple choice 111 72.10 % 3.88 (0.93) Essays 110 76.00 % 3.96 (0.95) Short answer s 113 80.40 % 4.06 (0.87) Oral examination 117 68.00 % 3.81 (1.23) Field work/projects 109 72.00 % 4.16 (0.90) Clinical/practical examination 121 84.80 % 4.28 (0.88) Clinical logbooks 135 40.20 % 3.24 (1.37) Research report 107 70.50 % 3.88 (0.99) Presentations 121 81.80 % 4.22 (0.94) “Rate MUHAS teachers in the following roles” Professional role modelling by teachers 126 47.90 % 3.24 (1.13) Accessibility of teachers outside scheduled teaching sessions 114 19.00 % 2.34 (1.15) Monitoring of students 95 31.50 % 2.77 (1.20) Teaching sessions 128 57.90 % 3.51 (1.02) Academic advice given 45 31.70 % 2.83 (1.28) Nature of your relationship with teaching staff 34 23.30 % 2.68 (1.25) Qualitative studies results Students chose a wide variety of courses to comment on. The distribution of the courses is represented in Tables 6 which shows courses that had the most respondents.Table 6 Graduates opinions regarding courses undertaken at MUHAS Figures in cells are the means of Likert Scale from 1 to 5, were 1 = strongly disagree and 5 = strongly agree This course prepared me for my current professional needs MUHAS prepared me to take this course n = 147 n = 147 Number Percentage agree Percentage agree Anatomy 104 70.9 % 3.96 (1.11) Biochemistry 83 56.5 % 3.59 (1.18) Medical Ethics I 118 80.0 % 4.11 (1.05) Physiology 123 83.6 % 4.30 (0.90) 75.90 % 4.04 (1.13) Behavioral Sciences 96 65.0 % 3.82 (1.04) 56.50 % 3.50 (1.33) Development studies 88 60.0 % 3.69 (1.15) 50.00 % 3.38 (1.35) Microbiology/Immunology 117 79.3 % 4.21 (0.96) 74.80 % 3.97 (1.06) Parasitology/Medical Entomology 118 80.0 % 4.19 (0.94) 79.00 % 4.03 (1.06) Clinical Physiology 121 82.0 % 4.24 (0.97) 78.80 % 4.16 (1.04) Development studies 90 61.0 % 3.64 (1.13) 59.00 % 3.61 (1.28) Introduction to Clinical Medicine 99 67.6 % 3.83 (1.24) 67.80 % 3.84 (1.32) Pathology 104 70.8 % 4.02 (1.05) 73.30 % 3.99 (1.17) Epidemiology & Research Methods 119 81.2 % 4.17 (0.92) 63.60 % 3.76 (0.11) Nutrition Field Project 105 71.3 % 3.95 (1.14) 72.00 % 3.95 (1.12) Introduction to Clinical Medicine 99 67.4 % 3.84 (1.27) 71.40 % 3.92 (1.24) Forensic Pathology 59 39.9 % 2.91 (1.45) 45.40 % 3.13 (1.46) Clinical Pharmacology 108 73.5 % 3.96 (1.12) 70.10 % 3.86 (1.22) Management of Disease I 111 75.7 % 4.04 (1.12) 79.80 % 4.08 (1.09) Medical Ethics II 110 75.0 % 4.06 (1.09) 70.00 % 3.88 (1.20) Medical Ethics III 113 76.6 % 4.10 (1.04) 71.70 % 3.96 (1.14) Management of Disease II 117 79.6 % 4.19 (1.00) 71.70 % 4.24 (1.00) Community medicine 109 74.1 % 4.00 (1.12) 76.10 % 4.01 (1.11) Paediatrics & Child Health 121 82.0 % 4.20 (1.08) 77.80 % 4.13 (1.10) Obstetrics & Gynaecology 135 92.1 % 4.50 (0.78) 85.30 % 4.36 (0.94) Elective Period 107 72.8 % 4.05 (1.01) 76.40 % 4.07 (1.08) Surgery 121 82.0 % 4.21 (0.97) 80.20 % 4.15 (1.01) Internal medicine 126 85.4 % 4.35 (0.98) 80.00 % 4.19 (1.07) Surgical Specialties 114 77.5 % 4.12 (1.04) 76.30 % 4.14 (1.10) Orthopaedics & Traumatology 95 64.5 % 3.78 (1.25) 66.40 % 3.82 (1.28) Psychiatry 128 86.8 % 4.45 (0.81) 81.10 % 4.21 (1.00) Themes with 3 % of more of responses are presented as individual themes, and other responses compiled into an “other” category. Responses were then analyzed into major thematic categories of: professors/staff, over-enrolment and class size, facilities and educational materials, curricular content, and duration of courses. The quality of the responses varied by question; for course strengths, 12 % of answers were coded as generic and contained statements such as “the course was good”. The responses for weaknesses and improvements were much more content rich with only 2–4 % of answers coded as general. Answers were coded as generic when they did not contain any specific references and when they used undescriptive adjectives such as “good” or “bad”. Professors/Staff A large percentage of students’ comments referred to employees of MUHAS, particularly the lecturers, tutors and support staff. About 49 % of students mentioned characteristics of professors as strengths of a course, and 315 as weaknesses. Their comments focused on the availability of professors, as well as their attitudes and their ability to convey the material. They also focused on the role of the tutors and teaching assistants. Students spoke about the importance of engaged professors, their attendance in class and in the clinic, and consistent delivery of the material. Finally organization and commitment were also important qualities students looked for in their professors. Positive attitude, friendly demeanor and approachability were noted with high praise. Some of the quotes from students regarding Professors strengths included:“Lecturers were well organized and available” “Lectures are well narrated” “Lectures were delivered with effectiveness” “Lecturers were committed to teaching” “Lecturers were committed and subject interesting, focused the current problems e.g. avian flu epidemic” “Lecturers- highly committed and very friendly” “Nice lecturers, well informed, well prepared” “Tutors were available and very responsive” and “Lecturers tried their best to deliver information, lectures were participatory.” Weaknesses focused on a lack of availability, attendance, particularly in the clinical rounds and finally on the attitude of the professors. Students noted that professors were often not present in class or in the practicals. Students perceived that faculty were overworked and overcommitted and linked this to the lack of faculty within a department. Several other students mentioned that perhaps, if the professors spent less of their time doing research or working in the private sector, they might have more time to teach. Some of the quotes from students regarding Professors weaknesses included:“Poor teaching methods and lack of participatory teaching” “No good cooperation between lecturer and employer” “No permanent teacher for this subject” “Few supervisors were monitoring and guiding us” “Some of the lecturers were showing favoritism towards some students” “Lecturers did not engage fully on delivering materials, so theoretically lecturers were not friendly with students” “One lecturer provides too much load for him” “Lecturers are so harsh and very embarrassing and lack good cooperation with their students” “Every lecturers needs his/her own way of examination to patients (not following the reference books)” “During ward round teachers are not around most of the time” Furthermore, students found that many weaknesses in regards to the professors were linked with over-enrolment and a lack of formal training in education. Suggestions to improve the learning environment included formal classes in education methods and hiring of support staff such as tutors and teaching assistants. Likewise, suggestions for improved attendance of teachers included hiring more lecturers and creating a system that would hold teachers accountable for their attendance. Over enrolment and class size The number of students present in the learning environment was extremely important to MUHAS students. About 18 % of students cited over-enrolment specifically as a problem. Only 3 % of students mentioned small class size as a strength of a course they had taken at MUHAS. Weaknesses and suggestions for improvements focused on decreasing class size especially in regards to lab work and practical, hands-on learning. Solutions to the problems of over enrolment were overwhelmingly to increase facilities, increase the number of classes to reduce size of class and to employ more professors and teaching staff. Other suggestions included enlarging facilities, especially labs; and improving teaching materials and resources to address the large number of students. Students also recommended creating study groups and lab groups of ~6 or fewer students. Very few students mentioned decreasing enrolment, but rather increasing the university’s capacity. Facilities and educational materials Students frequently mentioned educational materials, such as books, handouts, study materials, access to models, reference materials and books and technology in their responses. While no students mentioned the availability of educational supplies as acourse strength, 18 % cited it as a weakness, and 17 % made recommendations based on improving access to supplies. In addition to materials, facilities including labs, audiovisual rooms, and cadaver rooms were brought up in all three sections. Classes were commended for having materials and facilities that were adequate for learning. There was a high frequency of responses in regard to practical and clinical work, especially in regards to the availability of lab materials and access to facilities. Many suggestions for improving facilities suggested expansions to adjust for over enrolment. In addition to facilities, improved, up-to-date learning material was deemed critical to improving the classes. Duration of courses The duration of courses was especially important in regards to the weaknesses and suggestions for improvement. Many of the students suggested increasing the amount of time in their schedules for specific, information-rich courses, as well as rearranging the syllabus to include more time for practical and clinic-based learning. Other suggestions included extending classes to include a second semester. Appropriate time for classes was deemed necessary by the students in all three categories. Other suggestions “(have someone else complete) arrangements to be done (for) seeking patients instead of students seeking patients” “Lower registration fee for volunteer patients” “Establish a cardiology unit at MUHAS with basic diagnostic and interventional facility” “Reduce the number of appointments to patients and that will encourage more patients” “Focus to be made on microbiological problems in our region” “The MUHAS (should) have its own ultrasound machines instead of depending on those of MNH” “Use computers and PowerPoint methods, abandon old methods of teaching using transparent” “Lecturer – student communication should be improved” “Lecturers should adhere to timetable set” “Machines and materials are required to appreciate what are taught in theory” “Improve standard in wards for patients and health professionals” Specific course comments Graduates gave the following opinions regarding various courses they attended at MUHAS: For basic sciences, strengths included Learning and reading materials were available, thorough professors that were also enthusiastic, cooperative, and friendly as well as good course organization. Weaknesses included overcrowding, lack of enough lab supplies lecturers were not often present in lab section and lack of enough time. Recommendations included more instructions for lab work, increase the time, increase the number of tutors, increase access to teaching materials, improve lab equipment, Make slides and other materials available for study and expand some of the courses to two semesters. For clinical sciences, strengths included engaged, available, interesting and committed lecturers, ward rounds were very useful and taught very well, large number of staff and well prepared teaching materials and also professors were well organized and gave good demonstrations. Weaknesses included overcrowding in the ward, Not enough orientation to clinical and surgical skills (for example limited exposure to skills such as stitching or normal delivery), inappropriate and subjective exams, biased assessments, poor time schedule for exams and lack of enough time to cover all the materials. Recommendations included improving the learning environment and the attitudes of the professors, increasing the amount of time spent on bedside teaching and increase the supervision in clinic, add a two semester teaching program, change mode of teaching and examination, require senior teachers to attend ward rounds, increase the number of lectures, have the professors follow standard book protocols, group students to facilitate learning, encourage students to participate in procedures as well as increase theatre time and rotation time. Focused group discussions results Summary A series of focus groups were conducted in the summer of 2009 with recent graduates from the Muhimbili University of Health and Allied Sciences (MUHAS). The discussions explored graduates perceptions of the curriculum and possible improvements. Discussion focused on over enrolment, facilities, supplies and faculty, preparation for practical work and fieldwork experiences. Students provided very specific recommendations for each health science school, which is included in a section of this report. Discussions were semi-structured and included prompt questions soliciting opinions on the challenges of the curriculum and how students propose to improve them Focus group discussions were recorded and transcribed. Data was then coded and analyzed according to major themes. In order to provide information for the curriculum revision, this report focuses mostly on constructive criticism directed at areas in need of improvement whereas in the focus group discussions focused both on praise and criticism. Major themes of discussion included facilities and supplies, over enrolment, educational time frame, theoretical preparation for practical work, experiential learning and fieldwork, communication, course load, skills and faculty. These themes are discussed below, followed by specific improvements that were proposed in each school. Thematic analysis results Facilities and supplies All groups, aside from the environmental health science students, mentioned facilities and supplies during their discussions. Facilities refer to spaces for learning such as classrooms, laboratories and clinical space for internships and equipment refers to educational materials, such as books and computers. Comments regarding facilities ranged from lack of seats and desks in classrooms, to requests for more clinical space. Over all five groups there was an equal frequency of comments about facilities and supplies. In particular, Medicine students mentioned a lack of technology and equipment. Most of the students concerns were directed at clinical facilities. Students reported a lack of clinical facilities that met the standards for their internships. The hospitals and clinics did not have the required departments that were required for their rotations. Within their fieldwork and rounds, students reported a lack of supplies and patients to work on. Finally, there were also comments on the lack of educational supplies such as media, copies of handouts and books. Some of the quotes from students regarding facilities and materials included: Strengths “Good arrangement of firms where all students get same materials” “Lecturers were available, laboratory was well-equipped” “Dedicated lecturers. Availability of reading materials & Lecturers” “Illustration unit helped us in cadaver room” Weaknesses “Had inadequate and old teaching material” “There are no models for teaching and based on skeletal anatomy mainly” “The materials especially books were not available we use past papers” “The teaching system is very old and poor, no PowerPoint even the materials were not updated” Over enrolment Over enrolment was specifically mentioned by medical students. The increased enrolment was discussed most often in reference to lack of facilities and lack of equipment. Students from the Medical school spoke about roles of government and politicians in enrolment quotas.“To me may be the disappointments are seeing…the government is having the good idea of increasing the number of enrolling the number of MD students” (Medical Student, p16). A medical student mentioned the conflict between the need to increase medical workforce by increasing the number of medical students in the country and the lack of facilities and professors. One student mentioned the university’s inability to hire more professors to meet the need for the increased number of students. The students believe that the university has increased enrolment without increasing facilities, supplies and professors, which has decreased the quality of education.“(The) other thing is that I think the number of teachers, the number has been there since… the admission of those the years, the past years, may be they were taking fifty students but now they are taking about more than two hundred but the, still the number is limited” (Medical Student, p20). Educational time frame Comments included lack of continuity or connection between subjects, repetition of material and a heavy course load. The observations regarding time were coupled with desire to gain the best education possible and were most often related to inefficient use of time or lack of time. Students were not in agreement on the continuity and the flow of courses. Most of the groups had similar observations that there were no connections between the different courses. These comments were followed with some disagreement and generation of specific examples of subjects that did provide continuity. The concept of efficiency was brought up often in reference to repetition within the curriculum. Repetition in the curriculum was particularly important to medical students. However, time and efficiency of learning were often linked in the students’ discussion. Some of the quotes from students regarding facilities and materials included:“Short period of rotation” “Very long course; is covered within a very short time” “Things were too condensed and became too exhausting” “Course duration was not consistent with course materials” “The programme has a lot of free time which can be used in other rotations” “Time/days selected for field work are too short compared to the work suggested to be done during the field project” Theoretical preparation for practical work One of the most important topics discussed frequency in every focus group was theoretical preparation for practical work. The biggest comment that was repeated in every school was that students did not feel that they were being adequately prepared for their clinical experience. Much discussion was directed at reordering the classes so that appropriate theoretical knowledge could be gained before clinical exposure. Students reported either being taught theoretical concepts after fieldwork, not having enough of theoretical training or not receiving any theoretical training. Most students shared the view that they were undertrained in the practical part of their education. Though this viewpoint was a major concern, it was also shared with its inverse, receiving too much theory without the clinical background. Some of the quotes from students regarding the balance between theory and field/clinical/laboratory practice included:“Time/days selected for field work are too short compared to the work suggested to be done during the field project” “A lot of information and short time allocated” “Limited laboratory time and specimens” “Need enough time to practice” “Set enough time to practice all necessary procedures” “Machines and materials are required to appreciate what are taught in theory” “Short period of rotation” “More time should be allocated to these ward rounds” This was echoed in all of the focus groups and demonstrates the delicate balance between theoretical and practical learning. Discussion Recent medical graduates from the SoM who had undergone training through the semesterized programme, where thus assessed both quantitatively and qualitatively in order to gauge how much they felt they possessed competencies and skills including MUHAS core competencies (Additional file 3) as well as those specific for the MD degree (Additional file 3); and how much they felt enabled/empowered or disadvantaged by the curriculum they went through [2]. Furthermore, supervisors, co-workers, patients and employers were asked to evaluate how much graduates displayed those competencies and skills and whether they performed better or worse compared to graduates from other medical schools [2]. The overall goal was to develop competency-based curricula that are relevant to the national socio-economic development; respond to market demands and stakeholders needs; and conform to MUHAS vision and educational standards. As regards the quantitative analysis it was revealed that with the exception of FOUR aspects, most competencies ranked low including teaching, health care system and good practice which ranked the lowest as can be seen in Table 4 and Additional file 4 and that there was reasonable concordance were rating was low. This generally implies that expectations seemed to be higher than the training the graduates received including the competencies and skills that they were able to demonstrate in their practice. However, the competency of Professional Knowledge was favorably ranked in all aspects except that, supervisors ranked the graduates low in knowledge of causes and progression of diseases, employing knowledge of non-communicable disease, common surgical conditions and common Obs & Gyn conditions. Nevertheless, this low ranking may be representative of a graduate population who had undergone mostly the knowledge-based curriculum in contrast to the new competency-based learning which was being introduced during this index review. Furthermore, in-depth questionnaire analysis generally revealed some strengths including teachers’ enthusiasm, organization as well as good demonstrations. Some of the weakness included inavailability and lack of enough faculty as well as poor teacher-student relationship. Focused group discussions also revealed lack of equipment and facilities, over-enrolment and faculty deficiencies as seen above. The findings of the index tracer study directly informed and guided the ongoing curriculum review exercise including introduction of MUHAS core as well as MD-specific competencies and skills, repackaging, full modularization, increased inter-professional interactions and teamwork, other improvements [2]. A good example is the reorganization/restructuring of the MD programme from 3 years basics and 2 years clinical sciences formerly (Additional file 5) which is now reversed to 2 years basics and 3 years to accommodate the one of the most important findings of the tracer study-need for improved clinical skills and competencies and hence more time for clinical sciences (Additional file 5). This goes alongside the re-introduction of junior and senior clinical rotations to allow for repeated learning which is pivotal to clinical apprenticeship. Other important outcomes of this tracer study are the extension of some basic science courses including anatomy, biochemistry, physiology and pathology to two semesters (Additional file 5). The MD curriculum has been a subject of multiple minor cosmetic changes ever since. These are based on implementation challenges and are not the scope of this study. This semesterized, modularized and competency-based curriculum has been in implementation will now be almost due for a subsequent revision and thus it is important to publish these findings in order also to inform the next Tracer Study and Curriculum Review. Conclusions Thus the second tracer study as well as curriculum review exercise were conducted and whose results allowed for the repackaging of the MD curriculum, the introduction of full modularization as well as that of competency-based learning within SoM and MUHAS generally. It is envisioned that these tracer study findings will improve teaching and learning at MUHAS and lead to increased output of appropriately trained health professionals to fill the big gap in human resources for health (HRH) in the country. This will also promote interprofessional interactions and teamwork geared towards patient care as well as health promotion. The revised curriculum was also submitted for processing through the TCU for accreditation as required by the National Regulatory Authority. It is recommended that programmes, courses, modules as well as topics should emphasize on the teaching and assessment of competencies and skills and that focus should shift from the emphasis on teaching (teacher-centered education) to learning (student-centered education). The fact that the new curriculum will soon be subject to another review necessitates the publication of these results so that new changes are informed by the current findings. Additional files Additional file 1: SoM Postgraduate Programmes During the Tracer Study. (DOC 29 kb) Additional file 2: Distribution of Respondents by School. (DOC 264 kb) Additional file 3: List of General and Specific Program Competencies. (DOC 36 kb) Additional file 4: Quantitative Tables. (DOC 234 kb) Additional file 5: MD Programme Summaries. (DOC 109 kb) Abbreviations ALPAcademic Learning Project DCEPDDirectorate of Continuing Education and Professional Development ICTInformation, communication and technology MDDoctor of Medicine MMedMaster of medicine MUCHSMuhimbili University College of Health Sciences MUHASMuhimbili University of Allied and Health Sciences SoMSchool of medicine TCUTanzania Commission for Universities UCSFUniversity of California San Francisco Acknowledgements MUHAS Faculty, graduates, employers, workmates as well as patients/clients who participated in the tracer study are gratefully acknowledged for their resourceful contribution and commitment. I wish to thank the Directorate of Continuing Education and Professional Development (DCEPD) as well as the then MUHAS-UCSF Academic Learning Programme (ALP) under Prof. Ephata Kaaya and Mr. Dominicus Haule for guiding the Tracer Study across the University and for their significant support, sharing of their wealth of experience in Medical Education. The project was closed several years back. The ALP Metrics section including assistance from Chloe Le Marchand of UCSF is highly appreciated. Furthermore, I appreciate the help of Dr. Martha Nkya who by then was a 3rd year MD student and assisted me with data collection and entry into questionnaires. This work was done during the Deanship of Professors Charles Mkony and Muhsin Aboud whose general support is also high appreciated. I also acknowledge the general guidance of the MUHAS Curriculums Committee then under Prof. Eligius Lyamuya. I am sincerely grateful to Dr. Doreen Mloka the current DCEPD and Chair of UCC for encouraging me to publish this work. This Tracer Study was supported by a grant from the Bill and Melinda Gates Foundation. Funding This Tracer Study was supported by the then MUHAS-UCSF Academic Learning Programme (ALP) through a grant from the Bill and Melinda Gates Foundation. Availability of data and materials Original data tables and information not containing personal identifiers is available included in supplementary files attached with the manuscript. Furthermore, questionnaire templates are also appended herewith. However, original filled-in questionnaires and voice records of interviewees will not be shared as is strictly confidential and participants did not consent for that original information to be published. Authors’ contributions Not applicable. Authors’ information ARM is a practicing Consultant Anatomical Pathologist, Lymphomatologist, Nephropathologist, Medical Educationist as well as a Senior Lecturer and the immediate Former Head and Chair of Pathology at the Muhimbili University of Health and Allied Sciences (MUHAS) as well as Former Chair of Anatomical Pathology Services at the Muhimbili National Hospital (MNH), Dar es Salaam, Tanzania. He is also the Founding Chair of the School of Medicine Curriculums Committee as well as Coordinator of Curriculum Review within the School. Furthermore, ARM is a Founding Member of University Curriculums Committee (UCC) as well as the Founding Member of the MUHAS Health Professions Educators Group (HPEGS) which is also responsible for teaching Medical Education and conducting Faculty Development Workshops at MUHAS. ARM also served as the Examinations Officer in-charge for the School of Medicine from 2009 to 2012. ARM is a graduate of both the University of Dar es Salaam (UDSM) in Tanzania as well as the Karolinska Institute in Stockholm, Sweden. Competing interests The author declares that he has no competing financial interests. Consent for publication Not applicable. No individual/personal participant data was collected or reported in the manuscript. No personal identifiers are used. Ethics approval and consent to participate Ethical clearance of this study was sought and obtained through the MUHAS-UCSF Academic Learning Project (ALP) from the MUHAS Ethical Committee and permission to interview graduates was sought from relevant authorities and employers at the various centres we visited. Informed consent with details on the purpose of the study, the rights of the participant and benefits on participation was obtained from prospective interviewees although no personal identifiers were used and no human or animal data was collected in the study or reported in the manuscript. ==== Refs References 1. Macfarlane SB Kaaya EE Universities in transition to improve population health: a Tanzanian case study J Public Health Policy 2012 33 Suppl 1 S3 12 10.1057/jphp.2012.52 23254847 2. Ngassapa OD Kaaya EE Fyfe MV Lyamuya EF Kakoko DC Kayombo EJ Kisenge RR Loeser H Mwakigonja AR Outwater AH Curricular transformation of health professions education in Tanzania: the process at Muhimbili University of Health and Allied Sciences (2008–2011) J Public Health Policy 2012 33 Suppl 1 S64 91 10.1057/jphp.2012.43 23254850 3. Pemba S Macfarlane SB Mpembeni R Goodell AJ Kaaya EE Tracking university graduates in the workforce: information to improve education and health systems in Tanzania J Public Health Policy 2012 33 Suppl 1 S202 215 10.1057/jphp.2012.48 23254844 4. Mkony CA Emergence of a university of health sciences: health professions education in Tanzania J Public Health Policy 2012 33 Suppl 1 S45 63 10.1057/jphp.2012.51 23254849 5. Kwesigabo G Mwangu MA Kakoko DC Warriner I Mkony CA Killewo J Macfarlane SB Kaaya EE Freeman P Tanzania’s health system and workforce crisis J Public Health Policy 2012 33 Suppl 1 S35 44 10.1057/jphp.2012.55 23254848 6. Pallangyo K Debas HT Lyamuya E Loeser H Mkony CA O’Sullivan PS Kaaya EE Macfarlane SB Partnering on education for health: Muhimbili University of Health and Allied Sciences and the University of California San Francisco J Public Health Policy 2012 33 Suppl 1 S13 22 10.1057/jphp.2012.40 23254839 7. Kolars JC Cahill K Donkor P Kaaya E Lawson A Serwadda D Sewankambo NK Perspective: partnering for medical education in Sub-Saharan Africa: seeking the evidence for effective collaborations Acad Med 2012 87 2 216 220 10.1097/ACM.0b013e31823ede39 22189887

PMC005xxxxxx/PMC5000498.txt

==== Front BMC GenomicsBMC GenomicsBMC Genomics1471-2164BioMed Central London 288610.1186/s12864-016-2886-9Research ArticleOGS2: genome re-annotation of the jewel wasp Nasonia vitripennis Rago Alfredo axr280@bham.ac.uk 1Gilbert Donald G. gilbertd@indiana.edu 2Choi Jeong-Hyeon JECHOI@augusta.edu 3Sackton Timothy B. tsackton@oeb.harvard.edu 4Wang Xu xw54@cornell.edu 5Kelkar Yogeshwar D. yogeshwarkelkar@gmail.com 6Werren John H. jack.werren@rochester.edu 7Colbourne John K. J.K.Colbourne@bahm.ac.uk 11 Environmental Genomics Group, School of Biosciences, University of Birmingham, Birmingham, UK 2 Department of Biology, Indiana University, Bloomington, IN USA 3 Cancer Center, Department of Biostatistics and Epidemiology, Medical College of Georgia, Georgia Regents University, Augusta, USA 4 Department of Organismic and Evolutionary Biology, and FAS Informatics Group, Harvard University, Cambridge, USA 5 Department of Molecular Biology and Genetics, Cornell Center for Comparative and Population Genomics, Cornell University, Ithaca, USA 6 Department of Biostatistics and Computational Biology, University of Rochester Medical School, Rochester, USA 7 Department of Biology, University of Rochester, Rochester, USA 25 8 2016 25 8 2016 2016 17 1 67812 9 2015 6 7 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Nasonia vitripennis is an emerging insect model system with haplodiploid genetics. It holds a key position within the insect phylogeny for comparative, evolutionary and behavioral genetic studies. The draft genomes for N. vitripennis and two sibling species were published in 2010, yet a considerable amount of transcriptiome data have since been produced thereby enabling improvements to the original (OGS1.2) annotated gene set. We describe and apply the EvidentialGene method used to produce an updated gene set (OGS2). We also carry out comparative analyses showcasing the usefulness of the revised annotated gene set. Results The revised annotation (OGS2) now consists of 24,388 genes with supporting evidence, compared to 18,850 for OGS1.2. Improvements include the nearly complete annotation of untranslated regions (UTR) for 97 % of the genes compared to 28 % of genes for OGS1.2. The fraction of RNA-Seq validated introns also grow from 85 to 98 % in this latest gene set. The EST and RNA-Seq expression data provide support for several non-protein coding loci and 7712 alternative transcripts for 4146 genes. Notably, we report 180 alternative transcripts for the gene lola. Nasonia now has among the most complete insect gene set; only 27 conserved single copy orthologs in arthropods are missing from OGS2. Its genome also contains 2.1-fold more duplicated genes and 1.4-fold more single copy genes than the Drosophila melanogaster genome. The Nasonia gene count is larger than those of other sequenced hymenopteran species, owing both to improvements in the genome annotation and to unique genes in the wasp lineage. We identify 1008 genes and 171 gene families that deviate significantly from other hymenopterans in their rates of protein evolution and duplication history, respectively. We also provide an analysis of alternative splicing that reveals that genes with no annotated isoforms are characterized by shorter transcripts, fewer introns, faster protein evolution and higher probabilities of duplication than genes having alternative transcripts. Conclusions Genome-wide expression data greatly improves the annotation of the N. vitripennis genome, by increasing the gene count, reducing the number of missing genes and providing more comprehensive data on splicing and gene structure. The improved gene set identifies lineage-specific genomic features tied to Nasonia’s biology, as well as numerous novel genes. OGS2 and its associated search tools are available at http://arthropods.eugenes.org/EvidentialGene/nasonia/, www.hymenopteragenome.org/nasonia/ and waspAtlas: www.tinyURL.com/waspAtlas. The EvidentialGene pipeline is available at https://sourceforge.net/projects/evidentialgene/. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2886-9) contains supplementary material, which is available to authorized users. Keywords Genome annotationHymenopteraParasitoid waspTranscriptomeAlternative gene splicingGene duplicationHistonesProtein evolutionhttp://dx.doi.org/10.13039/100000002National Institutes of HealthR24 GM-084917Werren John H. http://dx.doi.org/10.13039/100000001National Science Foundation0640462Gilbert Donald G. http://dx.doi.org/http://dx.doi.org/10.13039/501100000855University Of BirminghamLilly Endowment, Inc.METACyt Initiative of Indiana UniversityColbourne John K. issue-copyright-statement© The Author(s) 2016 ==== Body Background The jewel wasp Nasonia vitripennis belongs to the superfamily Chalcidoidea, which is a vast group of hymenopterans that consists mostly of parasitoids that deposit their eggs in or on other arthropods. Parasitoids play an important role at controlling insect populations and are used extensively as an alternative to pesticides [1]. Nasonia is the genetic model system for parasitoids and a model for evolutionary and developmental genetic studies [2, 3]. As an hymenopteran, it provides a study system with naturally occurring haploid stages (males) and is a non-social relative to the ant and bee lineages, having diverged from them approximately 170–180 MYA [4, 5]. The Nasonia genus includes at least four species [6] that are partially to completely reproductively isolated by the bacterial parasite Wolbachia, yet can be crossed after its removal [7, 8], allowing the study of speciation from both a genetic [9–12] and non-genetic [13] perspective. The draft genome assembly of N. vitripennis was published in 2010 [4]. At that time, it provided a first comparative study of hymenopteran genomes with reference to the honeybee, Apis mellifera. The N. vitripennis genome project also included genome sequences for the cross-fertile species N. giraulti and N. longicornis, which were aligned to the N. vitripennis reference genome assembly. Utilizing information from these genomes, advancements have been made in areas as diverse as behavioural ecology [14], speciation [10, 11], immune responses [15] and DNA methylation [16]. In the coming years, projects such as the i5K and 1KITE [5] will continue to deliver new insect genomes and transcriptomes to the research community, with the goal of improving genomic knowledge for this most speciose animal clade [17]. Expanding the taxonomic breadth and number of well annotated genomes is important to develop new research avenues, and several quality measures are necessary for the accurate interpretation of comparative genomic, transcriptomic and epigenomic data [18]. Completeness (the number of reported genes compared to the actual number of genes in the organisms’ gene set) is one such measure; an incomplete gene set may exclude the true causal genes responsible for trait variation in quantitative genetic analyses and confound the interpretation of genome-wide association studies. The accuracy and reliability of gene models are equally important for genetic and genomic studies. Erroneous models can arise either from the fragmentation of true genes or by falsely joining neighboring genes (also termed fused or chimeric models, not to be confounded with their biological counterparts) because of mismatched splice sites, missing exons, or the addition of spurious exons. False models are especially problematic for the functional study of genes by misrepresenting their true expression levels. Finally, an accurate annotation of untranslated regions is required to investigate post-transcriptional regulation. Untranslated regions (UTRs) consist of 5′ and 3′ terminal portions of the mRNAs, as well as introns that are removed from the final mRNA via splicing. UTRs are functionally relevant since they are often targets for regulatory mechanisms such as microRNAs mediated regulation [19, 20], ribosomal binding affinity [21] and transcript localization [22]. The quality of genome annotations is improved by using more sequence data of gene transcripts. These data often expand the initially reported gene repertoires, indicating that (except for a few model species) current gene inventories are still far from completion. The gene numbers and accuracy of annotations for model species have generally increased over decades of work (e.g. 10 % more genes and 200 % more alternates for Arabidopsis over 15 years [23]). Species specific, targeted strategies are employed to refine the annotated gene sets. For example, by applying specific targeted solutions to the technical challenges of annotating the honey bee genome (largely because of its unusual base composition), its initial count of ca 10,000 genes [24] increased to a more acceptable gene count of 15,314 [25]. Improving a gene set’s quality however does not necessarily require targeted strategies. Integrating multiple gene-model construction algorithms and incorporating novel expression data can often provide sufficient evidence to improve existing models while also uncovering new loci and their variants. This is especially true if the source data are tissue-specific or include novel environmental conditions and developmental stages, which are likely to reveal the expression of specialized genes or transcripts [26, 27]. For example, the Anolis carolinensis gene set was updated in 2013 by adding tissue and embryonic specific RNA-Seq datasets, which provided sufficient new data to increase the overall gene count from 17,792 to 22,962 genes and from 18,939 to 59,373 transcripts – an increase of 29 % and 210 % respectively [28]! These case studies indicate that we are still far from reaching the point of diminishing returns on investments at improving the annotation of eukaryote genomes. As such, the genomics community is aware that updates to integrate novel expression and sequence data must remain a priority in order to provide a more accurate representation of the real biological background of animals. The construction of a biologically accurate gene set for any species is a complex process, where all data sources of gene evidence should be compared to resolve discrepancies; for each possible artifact there are biologically true equivalents to consider (gene fusions, functional fragments from partial duplication events, exons that become disrupted or functional during evolution). Each data source of evidence can also introduce measurement errors while each gene modeling or assembly method can produce flawed models at a non-deterministic frequency. Therefore, a consensus approach is perhaps the best way at resolving discrepancies among gene structures and to eliminate errors. This approach is implemented by the EvidentialGene method [29] described below. We report on a more comprehensive official gene set for N. vitripennis (OGS2), which vastly improves our understanding of its genome biology. Since its public release in 2012 [30], OGS2 has been used in a number of studies [11, 14–16, 31] and as a resource for comparative genomics (e.g., through databases such as OrthoDB [32, 33]). Here we describe N. vitripennis OGS2 in detail and compare it to the earlier annotation set using several quality measures. We use OGS2 for a comparative analysis of gene family expansion and sequence evolution with reference to other hymenopteran genomes. Finally, we reveal the usefulness of the novel gene set by presenting a multi-factorial analysis of the features that characterize alternatively spliced genes, demonstrating that genes with annotated isoforms are characterized by longer transcripts, greater number of introns, slower rate of protein evolution and lower probabilities of duplication when compared to genes with no alternate transcripts. Results and discussion Source data and gene model construction RNA-Seq produced 187,823,326 single-end sequence reads and included 124,188 paired-end and 51,665 single-end EST sequences from previously published ([4]; SOM) and unpublished data sets. The reads were mapped onto the draft Nvit_1.0 genome and assembled into gene transcripts using three methods (Cufflinks, Velvet and PASA) with six different sets of parameters producing between 46,259 and 242,217 de-novo constructed mRNA (Table 1). Twenty one thousand, six hundred and one (21,601) and 10,426 constructed mRNA aligned to the final gene models by 10 % and 95 % overlap, respectively (Table 1). The multiple-constructed mRNAs for each gene were evaluated by three classes of evidence-based criteria, which were then combined to calculate weighted-evidence scores resulting in a final pick of 44,164 transcripts of which 7,837 are alternate splice variants (Table 1). These Nasonia transcript assemblies were also used to construct NCBI’s gene set (NCBI build 2.1; http://www.ncbi.nlm.nih.gov/genome/guide/wasp/release_notes.html).Table 1 Gene evidence sources for Nasonia vitripennis OGS2. Mapping results of ESTs and RNA-Seq reads with >95 % coverage of length >100 bp to the assembled N. vitripennis genome (Nvit_1.0) using three mapping software and six parameters. An average of 2.5 % of reads are multiply mapped by GSNAP, measured over 8 RNA-Seq libraries. Number of constructed transcript assemblies matching the final gene model by 10 % and 95 % sequence overlap is also indicated RNA assemblies Mapped to genome 10 % of gene 95 % of gene Cufflink 10 46,259 40,853 12,386 4902 Cufflink 08 71,761 56,640 14,317 5287 Velvet p2 121,672 95,360 16,190 7706 Velvet p3 151,038 116,591 17,556 7851 Velvet p4 242,217 122,194 16,406 6874 PASA 69,805 69,805 13,099 6253 All genes 21,601 10,426 Alt. Transcripts 7,837 RNA read counts EST paired 124,188 EST single 51,665 RNA-Seq single 187,823,326 During the development of this updated gene set, several advances in the use of complex gene evidence for producing and selecting accurate and complete gene sets were tested and employed. We used an automated method of selecting gene models that best fit the range of gene evidence, including reference proteins, expressed sequence reads (EST, RNA-Seq), and whole genome tiling array expression. Our method also included a per-locus assessment and classification of the agreements among the various types of gene evidence, because each gene modeler produces locus-specific models that best fit the evidence. Testing and refining the evidence scores, with expert assessment and direction, is a core component of this process. We found that expression evidence from tiling arrays and RNA-Seq accurately track gene structures, by sharply rising at the start of exons and dropping at their ends, on average (Additional file 1: Figure S1). Therefore, combining both sources of evidence improve the delineation of gene structures. We learned during our gene modeling efforts that tiling array expression data were problematic when using available modeling tools, despite the high average accuracy for gene structure, as they only consist of exon data, without defining individual gene end points nor intron splice sites at nucleotide resolution. As a result, genes modeled with strong contributions from tiling expression were often aberrant (Additional file 1: Figure S2), with UTRs much longer than coding sequences, overlapping two or more reference protein models, and extending through introns defined using other evidence. While average tiling expression matches gene structure well, for individual loci that exon signal is obscured by lack of precise gene end point and intron signals, which are however available from RNA-Seq reads and assemblies. RNA reads and assemblies were more reliable for precisely defining gene structures by providing evidence in four forms: (1) reads mapped to the genome (exon parts), (2) introns from splice-mapped reads on genome, (3) full or partial transcripts assembled onto the genome and (4) assembled de-novo structures without the genome. These all contributed different and important aspects of gene structure evidence for modeling. Intron-exon splice sites are particularly reliable evidence of gene structures; each intron is measured by expressed reads that are splice-mapped to a genome, where the accuracy of the splice point increases with read coverage over that point. On the other hand, assembled transcripts can capture a gene fully, without further modeling; however, they also exhibit more errors of fragmentation or over-extension (gene joins) that must be assessed using other sources of evidence. De-novo assembled transcripts have the unique advantage of being unaffected by large breaks in genes on the genome, long introns and transposons, and mis-assemblies. Unlike the gene predictor algorithms, transcript assembly methods are also not focused on modeling coding sequences, and thus better reconstruct non-coding transcripts. The main drawback of the available RNA-Seq data for this study is that they were generated by early-generation instruments and chemistries (Illumina and Roche-454), which produced sequence reads of lower quality and quantity than desired for obtaining many complete gene assemblies. Yet these were usefully combined with other gene evidence and predictor methods. The complete EvidentialGene construction pipeline software, along with the Nasonia-specific configurations and methods, is available for public use at http://arthropods.eugenes.org/EvidentialGene/nasonia/ and https://sourceforge.net/projects/evidentialgene/ [30, 34]. A final set of 36,327 distinct loci, selected by EvidentialGene methods was compared to other available and draft Nasonia gene sets (Tables 2 and 3). The predicted models include UTRs based on expression data and genome gene signals. Putative long non-coding genes (lncRNA) from the transcript assemblies – those with weak coding potential and no homology to reference proteins – were retained in the full gene set. The models and EST evidence were assessed with PASA for valid alternate transcripts. Gene proteins were annotated with Uniprot descriptions, and classified by evidence scores, including transposable elements.Table 2 Summary of the improved Official Gene Set (OGS2) comparing all gene constructions to good constructions having expression and/or homology evidence and to the previous OGS1.2 gene models. Percentages are of the total number of genes for the set Summary Statistics OGS2 All Models OGS2 Good Models OGS1.2 Final Models Genes 36,327 24,388 18,850 Protein coding genes 25,725 (71 %) 24,388 15,566a Non-coding genes 3,997 (11 %) 0 0 Transposon protein genes 6,605 (20 %) 385a 2,935a Single transcript genes 32,079 (88 %) 20,243 (83 %) 18,759 (99.5 %) Genes assigned to orthologb 15,176 (42 %) 15,173 (62 %) -- Transcripts 44,164 32,101 18,941 Alternative transcripts 7837 7712 91 Mean isoforms per gene 1.22 1.32 1 Complete proteins 41,256 (93 %) 30,521 (95 %) 18,941 (100 %) Median transcript length 1571 bp 1603 bp 1176 bp Median CDS length 777 bp 981 bp 1032 bp Transcripts with UTR 41,313 (94 %) 30,512 (95 %) 5264 (28 %) a2,935 OGS1.2 models are classified with strong homology to transposon proteins during OGS2 work, 385 models with expression and other insect homology but also transposon homology were retained in OGS2 “good” model set b5,763 additional genes of OGS2 have significant protein homology, but are not assigned as orthologs in OrthoMCL orthology analysis, 3,454 of 24,388 “good” models lack significant homology, but have expression evidence Table 3 The types of evidence and levels of support for Nasonia vitripennis gene sets (OGS2 and others). Sequence-level statistics for the different types of evidence are given as proportions of the gene sets that are validated. Gene structure level statistics (ESTgene, Progene, RNAgene) are counts of the number of models that reach three structure level agreements. Homology level statistics are counts of the number of models and proportions matching proteins of reference species and paralogous (same species) proteins. See Methods section for details on the evidence types and the statistics that were measured Evidence Available evidence Statistic OGS1.2 Evidence-prediction set OGS2 OGS2 Good genes NCBI RefSeq Full-length RNA-Seq assembly EST 18 Mb Seq. Overlap 0.506 0.814 0.768 0.715 0.672 0.724 Protein 26 Mb Seq. Overlap 0.674 0.696 0.729 0.693 0.616 0.612 RNA 46 Mb Seq. Overlap 0.381 0.551 0.599 0.54 0.468 0.571 RefSeq 17 Mb Seq. Overlap 1 0.934 0.958 0.908 0.857 0.839 Intron 66,593 Splices Hit 0.846 0.965 0.981 0.969 0.903 0.975 TAR 75 Mb Seq. Overlap 0.292 0.850 0.533 0.443 0.37 0.386 Transposon 28 Mb Seq. Overlap 0.168 0.282 0.406 0.099 0.009 0.039 ESTgene 10,194 Perfect 2737 3996 4952 4900 3631 4293 ESTgene 10,194 Equal 66 % 3491 5059 6283 6198 4284 5187 ESTgene 10,194 Some 6263 9940 11,313 11,157 7123 8373 Progene 44,040 Perfect 4808 6713 8048 8010 6215 4935 Progene 44,040 Equal 66 % 7759 12,217 14,046 13,837 9003 8567 Progene 44,040 Some 11,563 18,173 21,759 19,718 10,861 18,457 RNAgene 28,016 Perfect 6004 9531 14,899 13,804 8502 28,016 RNAgene 28,016 Equal 66 % 8173 13,552 18,829 17,608 10,202 28,016 RNAgene 28,016 Some 11,933 19,602 24,936 22,179 12,258 28,016 Homolog 11,683 Matches 16,174 16,669 23,994 17,341 11,950 13,187 Homolog 11,683 Found 10,426 10,593 11,683 11,683 9323 9650 Homolog 11,683 Bits/Amino Acid 0.449 0.424 0.416 0.455 0.562 0.558 Paralog Matches 12,843 14,503 19,423 12,576 7904 10,520 Paralog Bits/Amino Acid 0.459 0.45 0.564 0.517 0.554 0.635 Genome Coding Seq. 28 Mb 31 Mb 36 Mb 29 Mb 10 Mb 16 Mb Genome Exon Seq. 29 Mb 52 Mb 70 Mb 45 Mb 24 Mb 24 Mb Genome Gene count 18,941 23,605 36,327 24,388 12,989 20,926 Finally, 24,388 constructions were chosen to be “good models” (Table 2), having the best match to EST and protein homology evidence. Models excluded from the “good” set include: (1) those with expressed RNA assemblies but with weak or no coding potential, (2) most of those with significant homology to known transposon proteins, and (3) those with minor or no expression and protein evidence from the quality assessment. However, 385 genes having homology to putative transposon proteins but also with expression and homology to other insect species genes were retained as an indeterminate subset annotated as “expressTE”. We used the “good models” set for all downstream analyses, but note instances where the remainders include some genes of biological value. Gene model quality assessment We compared the relative contribution of both expression and homology to the construction of gene models in OGS2. Details of this evidence scoring of gene models are described in the Methods section, with results summarized in Table 3 for each evidence type, and is here presented as percentages of evidence that overlaps or is recovered in gene models on the genome assembly. Expression data supports 17,925 genes (74 % of OGS2) at strong (>2/3 overlap) or medium (>1/3 overlap) levels of evidence. Strong or medium homology support is present for 17,238 genes (71 % of OGS2). The intersection of strong and medium support from both lines of evidence contains 12,912 genes (53 % of OGS2, Fig. 1), suggesting a high degree of convergence (p-value = 2E-14, Fisher’s exact test).Fig. 1 Number of genes with strong (>2/3 overlap) or medium (>1/3 overlap) support from sequence orthology, evidence of transcription, or both. Panels show the source of evidence for genes within the ortholog and paralog subsets and the whole OGS2 While still significant (p-value = 1E-8, Fisher’s exact test, N = 13,861), the level of convergence between expression and orthology support decreases to 44 % for the subset of duplicated genes, likely due to a reduced relative support of expression data (Fig. 1). The decrease in expression support can be explained by a more restricted expression profile for paralogs, which often arises after gene duplication events [35]. Therefore, further transcriptomic data from different tissue types and conditions should increase the level of convergence between the orthology and expression sets. Conversely, genes without duplicates show greater convergence between orthology and expression support (81 % of 24,388 genes, Fig. 1). Most of the 24,388 OGS2 genes that map to the N. vitripennis genome assembly (Additional file 2: Table S1) also map to the genome assemblies of sibling species N. longicornus and N. giraulti [4] using GMAP [36]; 664 do not map to N. longicornus, and 735 do not map to N. giraulti (391 are missing in both, yet 50 of these have non-wasp orthologs). All 4,141 high identity paralog loci from N. vitripennis map to assemblies of both siblings, though some are overlapping loci (Additional file 2: Table S1). The majority of paralog mapping patterns are the same for all 3 species (i.e., their relative positions are shared for all three species): 83 % (3442/4141) of the paralogs for all species, 99 % (4098/4141) of the paralogs for 2 or 3 species. The differences include both real biological differences and assembly errors. Of the 2481 paralogs on separate scaffolds of the N. vitripennis genome, 328 overlap first paralog spans in other species, therefore may be missing or mis-assembled. Of 239 tandemly arrayed paralogs in N. vitripennis, 128 are also tandem in other species, 101 are on separate scaffolds in other species, and 69 overlap first paralog spans in other species (ie. missing or mis-assembled). We also report that 3558 genes (15 % of OGS2) have no homology support and are therefore annotated only by means of expression data, and that 1818 genes (7.5 % of OGS2) have no expression support and are therefore annotated only by means of orthology matching. Eight hundred and thirty-three (833) genes in OGS2 are expert-curated including 38 that span different scaffolds, odorant genes, and other cases that could not be annotated automatically. Finally, 374 transcripts have complete proteins from transcript assemblies that do not match genome sequence due to genome gaps and frame-shifts. Gene set completeness We assessed the level of completeness of the OGS2 gene set using OrthoMCL to classify genes into orthologous gene families that are common to arthropods (Tables 4 and 5). The comparison of genes among nine species indicates that OGS2 is equally or more complete than the other insect gene sets, having fewer missing gene families, and similar numbers of orthologous gene groups and single copy orthologs. Additionally, OGS2 reveals that Nasonia has twice the number of duplicated genes than Drosophila melanogaster or Tribolium castaneum, both with homology (in-paralogs) and without (unique duplicates), plus a greater number of unique singletons. Measures of protein sizes and alignment score (Table 5) indicate that OGS2 genes are larger on average than genes from other versions of the Nasonia annotated gene sets, yet near to the Apis mellifera ortholog gene sizes.Table 4 Number of insect genes classified to gene families (GF) that are common among the arthropods by OrthoMCL (ARP9, version arp11u11). Five out of nine insect species are summarized. Dupl and Singl designate the proportion duplicated and singleton genes relative to the median found among insects (Dupl:5000, Singl:10000) Gene Families (GF) Gene Counts Proportions Gene Sets GF Ortholog GF GF missing genes Genes Species specific genes Species specific paralogs Single ortholog genes Duplicated ortholog genes Dupl Singl Nasonia OGS2 10,293 8983 92 24,296 5446 6686 8239 3925 2.1 1.4 Apis 8591 8560 170 10,145 987 88 8182 888 0.2 0.9 Harpegnathos 9633 9291 107 15,029 2943 1567 8710 1809 0.7 1.2 Tribolium 8893 8388 116 16,985 4586 2163 7608 2628 1.0 1.2 Drosophila 8464 7636 187 14,289 2824 2556 6994 1915 0.9 1.0 Table 5 Gene set quality measurements, including deviation of protein size from the group median, and maximal bit score per species in pairwise comparisons within the arthropod orthology groups. The bit score measures both gene model artefacts of alternative gene sets within species, and evolutionary divergence. Protein sizes may be more evolutionarily conserved, and may detect artefacts across and within speciesa Gene set Average homology bitscore Protein size deviation from median Percent shorter than 2 standard deviations from median Nasonia OGS2 727.6 −7.7 3.2 Nasonia NCBI 722.3 −7.8 2.7 Nasonia OGS1.2 683.5 −12.7 4 Apis 733.9 −0.3 2.4 Harpegnathos 694.3 −30 7.3 Tribolium 552 −26.1 4.5 Drosophila 508.7 54.5 1.3 aFor each orthology group, the median protein size of all genes among the species within the group is determined. Then for each species gene set, the maximal BLASTp bit score of a gene within that group is recorded as metric #1, and the protein size difference from the group median of that maximal match is recorded as metric #2. These metrics are averaged for all groups per species, and reported as average bit score, as average size deviation, and as percentage of size outliers (2 standard deviations below median sizes). These gene set quality measurements are provided by the Evigene scripts: “eval_orthogroup_genesets.pl” and “orthomcl_tabulate.pl”. Partial gene models are a common artefact of draft gene sets, indicated by both a negative deviation from group median sizes, and larger percentage of outliers. A similar calculation is part of the OrthoDB methodology [108] The transcript assemblies contain 62 orthologous gene groups that are not included within OGS2 because these transcripts are only poorly positioned onto the Nasonia genome assembly. These may be included in a more complete gene set as transcript assemblies, but are not yet part of this genome-mapped OGS2 gene set (Additional file 2: Table S2). A total of 75 orthologous gene groups are missing in Nasonia but present in 9 other insect genomes (Additional file 2: Table S3). We also used the OrthoDB method to independently assess completeness. We counted the number of missing conserved single-copy genes that are otherwise present among the sequenced Arthropoda (Benchmarking Sets of Universal Single-Copy Orthologs [BUSCO] in OrthoDB Release-6), as well as the multi-copy Nasonia genes that are otherwise classified as single copy in other Arthropoda. For the majority of gene families, there were no discrepancies between the results obtained from OrthoDB and OrthoMCL. Although the BUSCO results suggest that OGS2 lacks 67 of the 3377 (2 %, listed in Additional file 3) conserved ortholog groups, further analyses found all but 27. Conserved families missing in Nasonia OGS2 according to OrthoDB can be attributed to (i) genome artifacts (10 missing genes were found split across assembly scaffolds, or lost in gaps but found in transcript assembly), (ii) gene model artifacts (9 loci were apparent join errors appended to a second gene protein), (iii) OrthoDB discrepancies at classifying proteins to families (25 loci were assigned to different gene families by OrthoMCL and by OrthoDB family). Twenty-seven conserved single copy genes are either truly missing or sufficiently diverged to avoid detection. This number is comparable to those in other Arthropoda, which lack a number of BUSCO genes ranging from 3 (Drosophila erecta) to 708 (Strigamia maritima), with a median of 42. Experimental evidence supports the lineage-specific gene loss for the three BUSCO genes involved in developmental regulation: short gastrulation (sog, OG EOG6S4MX5), spaetzle 3 (OG EOG61C5BT) and daughters against dpp (Dad or smad6, OG EOG69CNQ7). Despite their ultra-conserved status across currently sequenced arthropods, detailed investigations of Nasonia development suggest that those genes are truly absent from its genome due to modifications in the BMP signaling pathway [37] rather than because of omissions in the current annotation. Since genes in the BUSCO set are defined as single-copy in 90 % of 30 arthropod species, we compared the number of duplicated BUSCO genes in OGS2 to estimate the fraction of potential false gene duplications. We counted 141 (4 %) multiple-copy OGS2 of the total 3377 BUSCO single-copy gene families (Additional file 4). Of those, 62 (44 %) are reported as duplicates uniquely for Nasonia, 61 for Nasonia plus one additional species, and 18 for Nasonia plus two other species. Other species have similar rates of duplicated single-copy genes: 78 for Apis mellifera and Harpegnathos saltator, 96 for Pogonomyrmex barbatus, 119 for Atta cephalotes (all Hymenoptera), 107 for Anopheles, and 437 for Aedes mosquitos. Nasonia OGS2 is therefore well within the observed range of duplications of BUSCO genes. To further assess whether the reported duplicates are likely to be false models, we removed the best supported gene from each orthologous group and measured the expression support of the remaining models. One hundred and fifty-three (153) out of 175 genes (87 %) show medium or strong support for expression and only 2 have no expression support. Lineage-specific duplications are supported by the observation that the majority of genes belonging to ultra-conserved ortholog groups display moderate to strong expression, even after removing the most supported duplicate and map to different genomic locations (data not shown). Improvements in genome annotation OGS2 improves our knowledge of the Nasonia genome in several ways (Table 2). First, the number of annotated genes climbs from 18,850 to 24,388 (an increase of 29 %). This greater completeness of the Nasonia gene set is corroborated by the sharp decrease in Arthropod ortholog groups missing from the Nasonia genome. OGS1.2 lacked 609 ortholog groups that are present in all other Arthropoda (OrthoDB Release-5). Only 331 conserved OGs are now missing from OGS2 when compared to the same subset of species (OrthoDB Release-6) and 253 when considering all currently available arthropod species. The spans of coding exons are very similar between OGS2 and OGS1.2 for 10,583 loci, which have a median percent equivalence of 92 % between both sets. Changes in coding sequences are mostly attributable to error correction such as splitting and merging of models: 1617 original gene models (10 % of OGS1.2) have been split into separate genes in OGS2, while 3555 OGS2 genes (15 % of OGS2) contain a portion of an OGS1.2 split gene, and 494 OGS2 genes result from the joining of two or more OGS1.2 fragment genes (30 from three or more). Moreover, the proportion of genes with UTR extensions is now near complete: 23,069 (95 %) of OGS2 gene models have annotated UTRs compared to only 5,264 genes (28 %) within OGS1.2. These gene models match 98 % of 66,593 intron locations on the genome assembly, identified by multiple reads of expressed RNA (>3; Table 3), compared to 85 % within OGS1.2 and 90 % within NCBI-11 RefSeq. Intron splice sites are strong indicators of genes, including species-specific genes. This measure therefore indicates a high level of gene set completeness, independent of protein homology. Finally, OGS2 dramatically increased the number of annotated transcripts from 91 alternate transcripts in 91 genes (0.5 % of OGS1.2, Additional file 2: Table S4 in [4]) to 7712 transcripts among 4146 genes (17 % of OGS2). Therefore, OGS2 increases the completeness of the reported Nasonia gene repertoire and the quality of gene models as well as allowing a first overview of Nasonia transcriptional diversity. The current release also increases the diversity of annotated wasp genes. Of all OGS2 gene models, 12,296 (50 %) could not be assigned a putative function via orthology with other annotated genes. Four thousand, six hundred and fifty-six (4656) genes from this subset (38 %) could be assigned to 2334 arthropod orthologous groups, 490 of which (21 %) are present as multiple copy in Nasonia. The remaining 7640 genes with no known function are found exclusively in OGS2 and could not be assigned to orthologous groups shared with other arthropods (OrthoDB, release 6). This subset is likely to include both incorrect models and innovations along the wasp lineage. Three thousand, nine hundred and eighty-three (3983) of those Nasonia-only genes (52 %) are present as duplicates in OGS2, a proportion that is significantly greater than that reported for the whole genome (fisher’s exact test, p-value < 2.2E-16). Of the 7640 lineage-specific genes with no annotated function, 4498 (59 %) have been newly annotated in OGS2. Mapping of OGS2 to Nasonia vitripennis 2.1 genome reference assembly (Nvit_2.1) To facilitate the broad use of the new OGS2 Nasonia gene set, we mapped it to the latest assembly (Nvit_2.1), using the UCSC LiftOver tools. The gene set is almost unchanged when transferred to the newer coordinate system. Out of 226,902 exons in the Nvit_1.0 gene set, 226,441 (99.8 %) can be successfully mapped to the Nvit_2.1 assembly. Focusing on transcript models, we find that 98.7 % of transcript models are identical between coordinate systems (43,590 out of 44,164). Of the 574 transcript models that differed between coordinate systems, 167 have all exons present but with small changes in the length of either exons or introns. For example, one exon is 170 bp shorter in the newer assembly for locus Nasvi2EG031848t1. An additional 155 genes are missing all their exons, and 252 are missing at least one exon but are present as partial models in Nvit_2.1. In addition to the General Feature Format file (GFF) with gene models in the Nvit_1.0 coordinate system, we also provide a reduced GFF (only exon and CDS features) with features mapped to Nvit_2.1 coordinates, a table with the status of each transcript in the new assembly, and UCSC-style liftOver chains to convert between Nvit_2.1 and Nvit_1.0 (Additional file 5). A relational file matching gene models between OGS1.2, OGS2.0 and NCBI-101 based on genome assembly locations is also included (Additional file 6). NCBI 2014 gene annotation of Nasonia When OGS2 was produced in 2011, its quality metrics ranked above Nasonia gene sets of NCBI and OGS1.2 (Tables 2 and 3). Since then, the NCBI gene set has improved along with enhancements to NCBI’s Eukaryote Genome Annotation Pipeline [38], producing Nasonia vitripennis Annotation Release 101 in 2014 (which we abbreviate as NCBI-101). These improvements partly resulted from greater use of RNA expressed sequences, and improvements at identifying related insect gene sets for consensus orthology. Among this project’s contributions were its RNA assemblies for Nasonia that NCBI used for gene modelling. The NCBI-101 Nasonia gene set includes 13,141 protein-coding gene loci, 24,626 transcripts, and 945 noncoding or pseudogenic genes. We compared protein-coding exon spans of the OGS2 genes that were lifted onto assembly Nvit_2.1 with those of NCBI-101 mRNA loci, using exon locations on the newer assembly. Model equivalences are measured as percentage of base overlap of coding-exon and full exon locations on the same genome assembly. These model equivalences are tabulated in Additional file 6. Of the NCBI loci, 12,319 (93 %) genes have at least some equivalence to OGS2 loci; a majority of 8400 (64 %) genes have nearly identical coding spans at > = 95 % equivalence, and 10,820 (82 %) genes are mostly the same (> = 66 % equal). The non-equivalent loci, with no exon overlap, include 11,535 (47 %) of the OGS2 “good” set and 867 (7 %) of the NCBI-101 set, plus 574 OGS2 loci noted above that are not properly located on the Nvit_2.1 assembly. Protein homology to other insects is very similar for NCBI-101 and the OGS2 gene sets. Of the conserved eukaryotic protein domains in NCBI’s Conserved Domain Database, we find 9165 domains in NCBI-101 and 9347 in OGS2 from 9505 total aligned domains using RPSBlast, having similar alignment lengths (average 233 aa for NCBI-101, 235 aa for OGS2). Among the complete proteins of related species and gene families identified with OrthoMCL (see Methods section), NCBI-101 contains 68 % of the gene families compared to 67 % for OGS2, both with average 85 % alignment to these proteins. Of the 11,535 non-equivalent OGS2 loci, 85 % are expressed genes with homolog alignments ranging from none to full; the remainder is supported only by protein homology. Expressed paralogs are the most common (6296/11,535, 55 %) subclass. Of 867 non-equivalent NCBI-101 loci, 512 have uncharacterized proteins, and 21 have model exceptions on this genome assembly (frameshifts, mis-maps). Of 339 NCBI-101 loci with characterized products, many are those we identified in the Nasonia transcript assemblies that were not located in our genome gene models (Additional file 2: Table S2). Also, 389 of the extra NCBI-101 loci are found within our OGS2 full (“not-good”) gene set; 76 of those are characterized proteins. Recent experiments have demonstrated that these “extra” loci in OGS2 are biologically significant. For example, of the 248 OGS2 genes that are immune responsive [15], 94 (38 %) are not among the NCBI-101 loci. Nasonia genes expressed in brain and nervous tissue [31] include 39 of 304 (13 %) not among the NCBI-101 gene set. Expanded gene families Our examination of the updated gene families of OGS2 identified 411 Arthropoda ortholog groups that have duplicated exclusively in the Nasonia lineage (4 % of all ortholog groups within OGS2). These groups consist of 1230 genes, of which 599 loci (49 %) have no assigned homolog (Additional file 7). The most frequent category among annotated expanded genes within the “good models” set is that of transposon associated proteins (102 genes, 30 ortholog groups), followed by kinases/phospatases (38 genes, 16 ortholog groups) and odorant receptors (23 genes, 7 ortholog groups). The enzyme 5-hydroxyprostaglandin dehydrogenase (6 paralogs, 2 ortholog groups) also shows an evolutionarily interesting lineage-specific expansion. This protein is essential for male pheromone processing, and is a prime candidate for driving mate selection and speciation, based on positional cloning of genes involved in pheromone differences between Nasonia species [11]. Protein evolution in Hymenoptera We calculated the sequence divergence of each Nasonia gene from its orthologs in both ants and bees. We then selected Nasonia genes that have a significantly higher or lower proportion of sequence divergence to ant and bee orthologs when compared to the rest of the Nasonia gene set (see Methods section for details). This method identified 504 genes (the most extreme 5 % of the frequency distribution) for both the rapidly and the slowly evolving gene categories (Fig. 2a; Additional file 8).Fig. 2 Protein divergence of OGS2 genes against orthologs in other Hymenoptera. Every point represents a gene mapped on three coordinates originating from the corners. Each gene’s distance from a corner is proportional to the average amino-acid distance of orthologs between the two clades. AB = ant to bee distance; AN = ant to Nasonia distance; BN = bee to Nasonia distance. Diverging genes are highlighted in orange (fast) and blue (slow) as detected by the compound ratio (A) and intersection of ratios (B). See materials and methods for full description We also adopted a more stringent approach by measuring the divergence scores of Nasonia genes against genes of the ant and bee lineages separately, then selecting only those genes that scored as rapidly or slowly diverging in both. This intersection method identified 596 and 394 genes that have differentially accelerated or slowed evolutionary rates in the Nasonia clade, respectively (Fig. 2b; Additional file 8). We note that both methods are unrooted, which therefore identify genes with greater divergence in Nasonia relative to bees and to ants, not to the common ancestor of these three lineages. In all subsets, the most significantly enriched Gene Ontology terms are “nuclear location” for the cellular component category, “DNA/chromatin binding” for the molecular function category and “transcriptional regulation” for the biological process category. These data are consistent with the view that evolution of unique metazoan traits occurs more by changes in transcriptional regulators rather than in structural proteins [39, 40]. Histone genes Although histone genes are generally highly conserved, we identified several members of the histone complex with sequences that evolved relatively rapidly in the Nasonia lineage. Specifically, we observe a greater rate of sequence divergence for the histone proteins H2A when compared to ant and bee variants. Histone H2A proteins package DNA into chromatin and are implicated in epigenetically mediated gene expression regulation in vertebrates [41–43]. Regulatory variants of H2A histones are also present in the Apis mellifera genome [44]. There are currently twenty-four (24) H2A genes within OGS2, 22 of which are assigned to a single ortholog group (OG) (Arthropoda OG EOG6VT4F0) and 18 of which are assigned to a single Hymenoptera group (OG EOG65QGR3). Compared to other Hymenoptera, this ortholog group is more rapidly evolving in Nasonia and has a greater number of paralogs: four times greater than Linepithema humile (the 2nd highest number with only five copies). However, we cannot rule out that the number of H2A genes in other hymenopterans is underestimated, especially considering the comparable number of H2A genes that are found in other arthropods (e.g. 21 in Daphnia pulex, 22 in the Culex quinquefasciatus, 22 in Drosophila melanogaster). As of now, only two Nasonia H2A genes have strong homology with genes within Hymenoptera, while most others have higher scoring sequence similarity matches (using Blast) among vertebrate histones. This pattern can be explained by a lineage specific increase in protein sequence evolution, which would decrease the similarity between histones of Nasonia and of other hymenopterans, and therefore increase their relative similarity to those of more distantly related species by a phenomenon called long-branch attraction. Thus, even though the match to vertebrate seems better than to hymenoptera, this result is most likely an artifact, yet is still indicative of a faster evolutionary rate of Nasonia histones compared to those of other hymenoptera. Histone H3 is known to exhibit a wide range of modifications, many of which have known effects on the transcriptional status of the underlying genes [27, 45]. Several Nasonia H3 proteins (Hymenoptera OG EOG6R4ZDK) appear to significantly evolve less rapidly when compared to ant and bee orthologs. We find that this apparently slower evolutionary rate of this orthologous group is due to a mis-identification of this OG, which is comprised of at least two different paralogs at the base of the hymenopteran lineage (Additional file 9). One of these putative sub-groups is retained in two copies across all Hymenoptera. The other sub-group is present in 2–4 copies in most Hymenoptera; yet Nasonia has 14 copies. The combination of an artefactual fusion of two OGs and unequal representation of Nasonia duplicates between the two groups is therefore the cause for an apparent slower relative evolutionary rate; the the correct interpretation consists of a lineage-specific expansion. Nasonia also retains an H3 gene of the OrthoDB group EOG62V6ZW, which is shared with other arthropods but not with other Hymenoptera, and and H3 gene of the OrthoDB group EOG6ZCRM6, which is seemingly lost in the bee lineage. The Nasonia H2B histone proteins are encoded by 21 genes; only four are assigned to an ortholog group containing other hymenopteran genes (EOG6Z8X7C of OrthoDB, whereas 8 are assigned to an OrthoMCL group). All genes are diverging at comparable rates while Nasonia’s copy number within this orthology group is similar to that of other hymenopterans (5 in Pogonomyrmex barbatus and Atta cephalotes). The remaining seventeen H2B histones could not be analyzed by our method, as they are not assigned to other hymenopteran H2B histone gene families (OrthoDB, release 6). Those genes may be mis-identified by the annotation pipelines, yet the NCBI-101 gene set independently annotates 18 of these 21 loci as H2B histone proteins, suggesting that this annotation is supported by available evidence, and may comprise a Nasonia-specific expanded histone gene cluster(s). By contrast, the Nasonia H1 histone is present as a single copy in the genome with no significant difference in its divergence rate from those of other Hymenoptera. We found that families of histone modification enzymes have specifically expanded in the Nasonia genome: 4 of 38 histone-related gene families (10 %) meet our criteria for lineage-specific expansion (see Methods section). By comparison, expansions are found in only 0.013 % of gene families for the rest of the genome. Our data therefore suggests that the Nasonia genome is enriched for histone modification enzymes due of lineage-specific gene expansions (Additional file 2: Table S4; p-value = 0.024, Fisher’s Exact test). The finding suggests that histone modification, rather than DNA methylation, may play an important role in the lineage-specific features of epigenetic modulation in Nasonia, consistent with findings that DNA methylation does not differ between the sexes in Nasonia, nor correlate with epigenetic changes in gene expression [31]. Non-coding RNA An early observation from the RNA-Seq and tiling array data sets is an abundance of expression in non-protein coding regions. These poorly annotated regions (in Nasonia and in other genomes of well-studied model organisms) require attention, as they are either UTRs of annotated protein coding genes, or putative long non-coding RNA (lncRNA). Our full gene set contains 3,997 putative lncRNA that were recovered from the Nasonia transcript assemblies (listed in “OGS2 All models”, Table 2). Among the OGS2 good coding models, 5,450 genes have annotated UTRs that sum to >50 % of their transcript length. The remaining ~40 % of expressed RNA remains to be annotated (Table 3, RNA evidence). Because our genome annotation methods focused on coding regions, resulting in an acceptable number of expected orthologs compared to the proteomes of other species, the remaining expression is likely non-coding. This large fraction of expressed RNA that has yet to be annotated is expected; these are found to exceed protein-coding genes in mammals [46], and to have significant similarities to characterized lncRNAs and UTRs [47]. Long expression spans near conserved coding genes are also observed in the Drosophila and Mus genomes, including nervous system specific expression, modeled both as long UTRs [48] and as lncRNA [49, 50]. We provide six examples of such long expression spans near Nasonia genes along with their presumed orthologs (ELAV-2 RNA-binding protein, calmodulin CaMKI, casein kinase II beta, odd-skipped, dunce/cAMP-specific 3′,5′-cyclic phosphodiesterase, and homeobox gene extradenticle) in Pogonomyrmex, Apis, Drosophila and Mus (Additional file 10). These expression spans are annotated as UTRs, sense and antisense lncRNA, or often without annotation. Difficulty at modeling these spans is not unique for Nasonia; a benchmark comparison of annotation methods (including those we used) for reconstructing Human and Drosophila non-coding genes found that all methods lacked accuracy [51]. Knowledge of these non-coding regions is nevertheless valuable for biological study, even when imperfect. For example, a recent study of Nasonia genes expressed in brain and nervous tissue [52] identified 306 OGS2 genes as differentially transcribed for learning in wasps – including dunce, CaMKI and ELAV-2 – with their associated long non-coding spans. Among the 3,997 putative lncRNA listed in “OGS2 All models”, 15 are discovered to be differentially expressed for learning [52] (Additional file 10) suggesting a significant role for non-coding RNAs in regulating neuronal development and function [53, 54]. Finally, 322 expressed non-coding regions located upstream of Nasonia coding genes are identified across insect genomes [55]. Functional genomic studies will help elucidate the importance of this significant portion of non-coding expression. Alternate transcript diversity including lola expansion OGS2 includes alternate transcripts assembled from available expressed sequence using genome-mapped assembly and de-novo assembly methods. A total of 7712 alternate forms are identified for 4145 genes (17 % of the total reported genes). One thousand, seven hundred and twenty-five (1725) genes (42 %) have at least 3 isoforms, 219 genes (5 %) have at least 6 isoforms and 26 genes have at least 10 isoforms. One gene (longitudinals lacking or lola) has a notable expansion of over 180 alternate forms, of which 89 are included in the OGS2 gene set. The remaining alternative transcripts are identified by read splice introns. Named for its observable wing phenotype in Drosophila, lola is also expressed in many tissues and developmental stages, and has a putative role in neuronal development [56]. Lola alternate transcripts all share a common 5′ set of six exons, with one hub exon that branches to alternate 3′ coding sequences of 500–900 bp, spanning 350 kb of the genome, with a new alternate each 1400 bases (median). Apis mellifera shares this lola alternate expansion, with 58 annotated alternates branching over 200 kb from the single hub exon, as shown in Fig. 3. In both species, additional alternates may be discovered with further expression evidence, as the regular spacing in Nasonia suggests up to 250 may fit into this region of the genome. Examination of non-hymenopteran insects shows no similarly large expansion for lola.Fig. 3 Alternate spliced, expressed introns for gene longitudinalis lacking (lola) in Apis (blue) and Nasonia (red). Graph shows intron spans from a common hub exon, in bases on their genomes. The observed 181 introns in Nasonia cover 325 kilobases (kbp), and up to 200 kbp in the 58 observed introns in Apis. These are regularly spaced 1400 bases apart, related by divergent 3′ exons (one or two) of 500 to 900 bp, which produce different coding sequences and protein isoforms. The tiny blue and red bars at top of figure are short introns that join pairs of 3′ end exons in lola gene span. Introns are displayed in size order (y axis), but for a plotting mistake at Apis long end The Nasonia gene with the second largest number of isoforms is the neuronal developmental transcription factor fruitless, with 17 alternative isoforms. Fruitless was already characterized as having an unique gene structure in Nasonia compared to dipterans, and its differential splicing is involved in both development and sexual differentiation [57]. Two other fruitless paralogs are also reported within OGS2, while no other insect genome shows paralogs for this gene. Other genes with a high number of reported isoforms include mostly transcription factors and various kinases/phosphatases (Additional file 11). Evolution of alternative splicing The augmented number or genes with reported isoforms in OGS2 allowed an examination of factors that contribute to the evolution of this regulatory mechanism. From a total of 4146 genes with reported isoforms, only 476 (11 % of all genes with isoforms, 2 % of OGS2) have annotated paralogs (Fig. 4a). This proportion is significantly less (p-value <2.2xE-16, Fisher’s Exact Test) than the product of proportions of genes with alternative transcripts and that of genes with duplicates (17 % × 43 % = 7.3 %). In addition, genes without paralogs also have a greater number of introns than those with duplicate copies in the genome (Kruskal-Wallis rank sum test, p-value <2.2E-16 for both strict and broad sense paralogs). Possible interpretations of these patterns are considered in the discussion section below.Fig. 4 Number of genes with alternative isoforms in OGS2 (a) split by presence of paralogs and (b) split by methylation in adult females Methylation has been proposed as a molecular mechanism for the regulation of alternative splicing in humans [58]. In Hymenoptera, studies of both bees and ants consistently locate methylation target sites at the intron-exon junctions [44, 59, 60]. However, a study on the Nasonia methylome [16] reports alternative transcripts in non-methylated genes and no correlation between presence of alternate splicing and methylation status. We re-tested for the overrepresentation of alternative splicing with OGS2 sets of known methylated and known non-methylated genes (reported in [16]) (Fig. 4b). Results indicate a significant overrepresentation of isoforms among methylated genes (p-value = 2.2e-16, Fisher’s exact test), with alternative transcripts reported for 41 % of methylated genes, while only 14 % of non-methylated genes have transcript isoforms. To exclude spurious results due to correlation with unaccounted variables, we fitted a generalized linear mixed model (GLMM) to estimate the probability of observing alternative transcripts in OGS2 genes according to a variety of factors (see Methods section for details). The final statistical model (Fig. 5) is composed of the following co-factors: strict sense paralogy (presence of a reciprocal best match within the genome), number of broad-sense paralogs (OGS2 genes within the same arthropod ortholog group), ratio of Nasonia-specific protein evolution within Hymenoptera (see Methods section “Identification of fast- and slow-diverging genes in the Nasonia relative to ants and bees”), number of introns, methylation status in adult female and furthest matching ortholog. We also fitted a random error structure to account for individual differences between ortholog groups.Fig. 5 Effect of different factors on the probability of observing alternate isoforms of OGS2 gene models. Factors are ranked by relative importance (y axis). Factors with complete support and levels of the same factor were adjusted for plotting. Effect sizes are shown as the fold change in probability from the intercept (with 95 % confidence intervals). Numeric variables were log transformed prior to analysis Expression level and intron support are also expected to be main predictors of observed alternative isoforms, since isoforms of genes with greater transcript abundances will be easier to detect via RNA-Seq. We could not include expression and intron support as factors in our analyses due to their high correlation with methylation status (see Methods section, Additional file 12: Figure S5). We therefore restricted our analyses to the subset of genes that have both strong expression and strong intron support (N = 5447, Fig. 5). Results indicate that the number of predicted introns and transcript length are positive predictors of alternative isoforms. Both findings are consistent with recent studies on the Apis transcriptome [60]. The presence of introns enables the evolution of alternative splicing, since the latter requires differential inclusion of exons. The role of transcript length is more difficult to interpret. It is possible that genes with longer transcripts simply reflect better annotation quality. Alternatively, longer transcripts may allow for longer intronic sequences, which may facilitate the emergence of alternative splicing by providing a greater number of targets for the generation of novel splice sites or by switching from the intron signaling mechanism to the more error prone exon signaling mechanism [61]. We explicitly included coding sequence to transcript length ratios among factors of interest to study these effects. We found that the proportion of coding transcript sequence (CDS/transcript length) is less well supported than transcript length itself (47 % relative importance versus 100 %). Furthermore, genes with higher proportions of non-coding sequence have a lower probability of displaying alternative transcripts. Even by assuming a role for intronic to exonic sequence length proportions, we find that shorter exons are prevalent among spliced genes, contrary to both the novel splice site and exon definition modes of new isoform generation. We should however note that the prevalence of long introns flanking alternative exons appears to be primarily driven by isoforms that comprise a minor proportion of all splice variants of a gene [61]. It is therefore possible that the slight skew towards genes with low proportions of intronic sequences might be driven by issues in annotating low-abundance isoforms rather than by biological constraints. Our initial genome-wide analyses detected a correlation between methylation and alternative splicing. However, we observe alternative transcripts for non-methylated genes as well as methylated genes. This finding indicates that methylation is not necessary for alternative splicing in Nasonia. Furthermore, after focusing on the subset of genes with strong expression and intron support, methylation status in adult females is only weakly correlated with presence of isoforms (relative importance 30 %). We find low support for a negative correlation between Nasonia-specific sequence divergence and probability of observing alternative splicing. Methylated genes are known to have a slower rate of protein sequence evolution in Nasonia [16], while the presence of paralogs often increase protein evolutionary rates by releasing pleiotropic constraints on individual gene copies. Yet, rate of sequence evolution and lack of isoforms remained correlated, even after controlling for the effect of methylation and paralogy (relative importance 52 %). This finding suggests that, despite the relatively low level of support, the inverse correlation between protein sequence evolution and alternative splicing may be direct result, rather than being derived from indirect correlations, and is consistent with studies of the Apis genome [60]. Both measures of paralogy (by reciprocal best hits or number of genes within the same arthropod ortholog group) retained a moderate level of support (74 % and 57 % respectively) when compared to other factors. Presence and number of paralogs are correlated with a lower probability of observing alternative transcripts. Since we performed all our analyses on the subset of genes with strong expression support, we can dismiss an effect due to the relatively lower expression support available for duplicated genes (see Fig. 1). The relatively large confidence intervals of the estimated effect of this factor on the probability of observing splicing of a given gene may either indicate a weak effect or result from the under-representation of paralogs in our subset (6 % of the “good expression” gene set versus 43 % of OGS2). Finally, we tested whether isoforms are observed more or less frequently amongst genes which emerged at a specific taxonomic level by using furthest phylostratigraphic match as a proxy for gene age [62]. While average probabilities decrease with gene age, this trend was not validated as statistically significant (data not shown). Furthermore, no single gene age category significantly alters the probability of observing alternative splicing in its assigned genes (relative importance: 0.07). The inverse relationship between alternative splicing and gene duplication in particular is consistent with observations on the evolution of mammalian model species’ genomes [63]. There are currently several competing models that explain the negative correlation between gene family size and number of isoforms. The “function sharing” model hypothesizes that duplication events reduce the selective pressure to maintain alternative transcripts in both gene copies [64]. This model is based on the assumption that both paralogs and isoforms provide equal opportunities for functional diversification. The reduced selective constraint would lead to the reciprocal loss of isoforms and subfunctionalization of the gene copies [65]. Such a scenario had been proposed for the Dscam genes in Arthropoda [66]. The function-sharing model predicts that genes will gradually accumulate isoforms that are lost shortly after duplication events. By contrast, Roux and Robinson-Rechavi [64] proposed an “age-dependent” model, in which the inverse correlation between duplication and gain of isoforms is not direct but rather arises independently because of structural properties. Short gene length could be advantageous for whole gene duplication, while genes with an already high number of exons will have a higher propensity towards single exon duplication due to replication and recombination errors [64]. The lower numbers of isoforms for genes with duplicates would thus result from the different rates of accumulation of isoforms and duplicates rather than loss of redundant transcripts. This hypothesis has been criticized in depth [67]. Finally, the underlying equivalence between the diversification potential of duplication and alternative splicing assumed by both the function-sharing and the age-dependent models is refuted by [68]. This finding suggests that a gene’s probability of having isoforms rather than duplicates might be less dependent on its structural properties and more dependent on the different adaptive potential of the novel proteins generated by two diversification modes, or functional constraint. Our analyses support longer transcripts and high numbers of exons as predictors of the presence of isoforms. While this is in agreement with the age-dependent model, we do not find a significant correlation between age of a gene family and the presence of isoforms. This could be either be caused by an actual lack of correlation, inaccurate dating [69] or by the fact that the divergence from the most recent outgroup (~180 MYA) is sufficiently great that every new family gains at least one detectable isoform. Absence of duplicates has moderate support as a predictor of splicing, even after controlling for the structural properties of genes. Together with the lack of support for gene family age, this observation is congruent with the predictions of the function-sharing model. However, we must point out that a true test to falsify the function-sharing model would require testing the significance of the date from last duplication event, which we could not measure with our dataset. Comparisons between the sibling species N. giraulti and N. longicornis are especially suited to this task, as they provide a sufficiently short timescale to assess transcriptome changes lead by duplication when compared to more basal Hymenoptera. Since we lack estimates on the potential functional overlap of duplicates and isoforms in the genes we analyzed, we could not explicitly test the independent model. However, the fact that we observe a strong effect of structural gene properties runs contrary to the expectation of a process driven by their different potential to generate adaptive variants. In conclusion, while we find no evidence for age itself being a determinant of the presence of isoforms, we do find strong support for structural gene properties. This might be explained by an hybrid model in which the final outcome is determined both by the propensity of a gene to produce either isoforms (or duplicates), and by their differential fixation because of their adaptive potential (independent model) or overlap (function-sharing model). We must point that our study assesses the presence or absence of isoforms, rather than their number, and only considers the subset of highly expressed genes, which might have different selective pressures than restricted ones. Our choices are necessary to provide a fair comparison, since lowly expressed genes have intrinsically lower probabilities of having observable isoforms and the number of isoforms is likely to increase as more diverse RNA samples are sequenced. However, they also skew our analysis towards a non-random subset of genes, which might be subject to different selective pressures. As such, tackling a truly comprehensive analysis of splicing and duplication in the Nasonia genome will require more sequencing efforts. Community resources for Nasonia genomics Several information resource projects support the use of Nasonia for genomics investigations, reviewed by Lynch [3]. Gene set improvements of OGS2 are available at the Hymenoptera Genome Database (HGD) [70] and more recently at WaspAtlas [71]. The HGD provides genome map views and BLAST sequence searches for Nasonia, including this OGS2 gene set, and 8 other Hymenoptera species. WaspAtlas offers gene annotation and functional information searches of Nasonia gene sets including OGS2, integrating expression and DNA methylation annotations. This OGS2 gene set along with associated gene evidence and alternate gene sets are also available with genome map views and BLAST sequence homology searches through the EvidentialGene project of euGenes genome database [30, 34]. NCBI provides genome map views, sequence and gene annotation searches [38] for their annotations of Nasonia. With a growing wealth of genome information, the value of these resources will improve where they can manage to integrate and sensibly organize such data as RNA sequence expression studies, DNA methylation data, proteomics, new genomic data, and cross-integrate with the improving genomics data of related species. Conclusions OGS2 provides a major quantitative and qualitative update to the toolbox for Nasonia’s genomics research. Better-defined UTRs enable the study of post-transcriptional regulation via targeting of small RNAs. Novel reported isoforms provide a more accurate representation of gene expression. We also highlight interesting areas for future molecular biology research using this organism, such as histone modification. Furthermore, we provide an estimate of the most unique traits of the Nasonia genome when compared with other Hymenoptera, which can assist the discovery of genetic mechanisms underlying the typical features of this lineage. The advances in gene annotation for OGS2 are notable today, however as gene evidence accumulates in the future, new and improved gene sets will need to be constructed until a verifiably complete and biologically accurate gene set is produced. Transcriptomic data in the form of high quality and inexpensive RNA-Seq is now the leading form of gene evidence for most genome projects, surpassing gene prediction and mapping of reference gene proteins. Along with abundant high quality RNA-Seq for the model Drosophila, Tribolium, and other insects, the Apis mellifera gene set has recently been improved by addition of several billion paired reads, sufficient for the assembly of all but the weakly expressed genes. This approach has been employed at NCBI for updated genome-based models, and at EvidentialGene with RNA-only assemblies. The RNA assemblies may well surpass genome-modeled genes for orthology completeness as well as species-unique completeness [72]. As a proof of concept, all of the novel data that enabled the annotation improvements made by OGS2 are derived from functional genomics methods (RNA-Seq, tiling arrays and ESTs). Transcriptomic data can thus improve genome annotation, even when the underlying genome assembly is frozen. As shown by the publication of results from the modENCODE Drosophila project [73], new genes and transcripts are discovered, even for a genome that has been intensively investigated for over half a century. Our modeling estimated that 50 % of all Nasonia loci may possess alternative transcripts, comparable to the 57 % observed from the Drosophila transcriptome [26], whereas we recovered alternates from RNA assemblies at only 17 % of all loci. Therefore, even though it is unlikely that the addition of novel data will drastically increase the gene count for the Nasonia genome, we expect an increase in the number of reported isoforms with the addition of stage, tissue and condition specific transcriptomes. Perhaps more importantly, new data will increase the quality of gene models, where RNA transcript assemblies will validate and improve gene structures, an unresolved subset of which we believe are fragments or gene joins, and will provide further evidence for intron/exon patterning. Our phylogenetic analyses were restricted in scope to the portion of the genome that could be assigned to an ortholog group, and its interpretation hindered by the large number of genes of unknown function. In order for the genomics of this organism to be better linked to its biology, there is a pressing need for more functional studies tailored to Nasonia’s unique features. Genome wide association studies and quantitative trait loci are especially complimentary for this purpose, as they provide a first connection between the well-defined transcriptionally active regions and biologically relevant traits [74, 75]. As a final note, OGS2 is currently rich in models that have little support. These lowly supported models might prove to be a valuable resource for future studies on the unique features of the wasp lineage, as their current status as low-level support loci could either be indicative of a restricted expression pattern or of a recent evolution or emergence in the hymenopteran phylogeny. Methods We constructed gene models by using software methods that incorporate various sources of biological evidence for genes, including transcriptional data from RNA-Seq and tiling-path microarrays and sequence homology with genes described in other species. We performed model quality assessment to select the best gene model per locus and to compare gene sets, using the same gene evidence plus additional sources. After quality assessment, we performed error and discrepancy analyses followed by updated gene set selection in a negative feedback fashion to minimize errors. All selected gene models are supported by some kind of evidence; ab-initio predictions without gene evidence are not included in OGS2. A small set of problem genes were manually curated and corrected by expert examination of evidence. Gene evidence from expressed transcripts Total RNA samples for sequencing were collected from whole embryos, pupae, whole adults, adult heads and adult abdomens using the extraction and purification protocol described in [15]. Single-end sequencing libraries were created using the TruSeq chemistry by Illumina following the manufacturer’s instructions. Sequencing was performed on both the GAIIx and HiSeq 2000 Illumina instruments with single-end read lengths of 40, 51 and 80 base pairs. The sequences were deposited at NCBI as BioProject PRJNA219398. Expressed Sequence Tags (EST) from four normalized cDNA libraries – which contributed to the OGS1.2 annotation – were also used in gene construction (accession numbers GE352825-GE467204 and ES613911-ES651267). The library construction and sequencing procedures are described in the Supporting Online Material for [4]. RNA from short and longer reads were assembled into long mRNA transcripts using both genome-mapped assembly (PASA, Cufflinks) [76, 77] and de-novo assembly (Velvet/Oases) [78, 79] (Table 1). De-novo assembly combined paired-end EST with short read RNA-Seq, whereas PASA only assembled ESTs and Cufflinks only assembled short RNA-Seq reads because of software limitations. We used Cufflinks v1.0.3 and v0.8 with default options, PASA v2.2011 with standard options and Velvet v1.1.05, oases v0.1.22 with options -ins_length_long = 400 -conserveLong yes -min_pair 2, and kmer values 27 and 31. EST and RNA-Seq were mapped onto the draft genome sequence with GSNAP [80] for assembly by PASA and Cufflinks. The de-novo assembled transcripts were mapped onto the draft genome sequence with GMAP [36], and incorporated into further gene construction as transcript evidence. Longest open reading frame (ORF) proteins were computed from de-novo transcripts, and used in gene orthology assessment and genome assembly discrepancy analyses. Intron evidence was collected from properly spliced reads and transcripts mapped onto the genome assembly; the number of spliced reads per intron location was used as a quality score. We found a total of 66,595 intron locations supported by 3 or more reads, including 1100 introns longer than 20 kbp (285 kbp maximum) supported by at least 10 reads. Gene evidence from expression tiling array We used whole genome tiling-path microarrays with tile spacing of 20 bp to discover transcribed Nasonia loci. We extracted total RNA from samples of 5 different life stages, 0–10 h embryos, 18–30 h embryos, 51–57 h larvae, 1-day yellow pupae (little to no red eye pigment), and 1 day post-eclosion adults. We used six replicates per sample, averaging 400 individuals per replicate for embryos, 300 for larvae, 20 for pupae and 20 for adults. Samples were extracted in Trizol (Invitrogen, cat #15596-026) then processed and expression data produced at the Indiana University Center for Genomics and Bioinformatics using previously published methods [81]. Tiling array expression analyses result in exon-like spans, called transcriptionally active regions (TARs), from runs of adjacent expressed 50 bp tiles (Table 6). The log-normalized intensity of replicated tile array signals is primary expression evidence for TARs. Both genome tiling and RNA-Seq expression track gene exon structures well (Additional file 1: Figure S1) suggesting their suitability for gene modelling. TARs were used as exon-like evidence in gene predictions in two ways: as input to AUGUSTUS predictor in the form of exon hints (genome span scores) and as input to exonerate cDNA mapping to gene structures, in combination with other evidence (Table 3, Additional file 1: Figure S2).Table 6 Genome tiling array expression gene evidence. TAR = Transcriptionally Active Regions representing runs of adjacently expressed 50 bp isothermal probes on a genome-wide tiling path microarray [4] Expression group TAR exons Unique TARs Exonerate gene models Adult female 1,139,061 29,626 46,402 Adult male 1,165,881 20,625 49,344 Embryo 10 h old female 700,773 21,704 33,286 Embryo 10 h old male 677,712 6788 31,408 Embryo 18 h old female 781,163 13,268 31,342 Embryo 18 h old male 813,130 15,662 33,612 Larva female 670,292 7173 29,442 Larva male 667,030 3814 28,284 Pupa female 1,246,557 16,563 51,858 Pupa male 1,322,223 15,769 54,119 Ovaries 631,449 7113 27,483 Testes 658,960 21,449 30,348 Gene evidence from related species proteins Gene homology evidence for the gene construction pipeline was collected from 220,000 proteins of 2 ants (Camponotus floridanus, n = 15,133, Harpegnathos saltator, n = 15,029), 3 bees (Apis mellifera n = 10,145, Bombus terrestris n = 9492, B. impatiens n = 9869), Drosophila melanogaster (r5.30, n = 14,289), pea aphid (Acyrthosiphon pisum r2, n = 38,440), Tribolium castaneum (v3, 2008, n = 16,985), Daphnia pulex (v1 2007, n = 30,506), and human (UniProt 2011, n = 20,238). These proteins were aligned using tBLASTn (NCBI) to the repeat and transposon soft-masked genome, then refined with Exonerate [82] to create protein gene models, with options “exonerate --model protein2genome:bestfit --exhaustive 1 --subopt 0 --forcegtag 1 --softmasktarget 1”. Gene construction on genome assembly We constructed OGS2 gene models upon the Nvit_1.0 draft genome assembly, which is the same assembly used for OGS1.2 [4] primarily to preserve tiling array locations. An updated 2.0 genome assembly is also available from the NCBI (NCBI Nasonia vitripennis Annotation Release 101), yet does not differ from Nvit_1.0 but for a modest splitting of the largest scaffold into two units and mapping of scaffolds onto the linkage map of Nasonia [83]. Transposon and repeat locations remain as found in the initial report, though we performed an updated Repbase database [84] and RepeatMasker run [85] including an evidence quality assessment. OGS1.2 gene models are retained as inputs for our updated version. These lack UTRs for 70 % of genes – a desired improvement. We used NCBI-11 models for Nasonia and the published genome assemblies of the two sibling species, N. longicornis and N. giraulti to assess gene models. The new Nasonia gene models are derived using the evidence-directed AUGUSTUS predictor [86–88]. Several gene prediction sets are produced to create a superset of models that include the models selected to be best, based on matching all gene evidence using EvidentialGene methods [29, 34]. AUGUSTUS flexibly uses both Hidden Markov Model (HMM) training models and available gene evidence for each locus. Training the predictor HMM involves steps described by the authors [87, 88], with validated genes for this species. We selected 2000 Nasonia reference genes that appeared to be full length from the EST/RNA transcript assemblies. We split these into subsets for training and validation of the resulting predictor. We created and used several training sets, plus one that is un-optimized. Evidence sets and configuration weightings were constructed to include: (1) complete gene structure information (exon, CDS, intron, gene spans); and (2) an extra influence of one major component (proteins, EST exons, full transcript assemblies). The first was necessary to reduce aberrant gene models generated by over-influence of one structure component. For example, evidence of exons from only ESTs or tiling TARs lead to missed introns and missed gene ends. The second was required to reduce conflicting signals, and returned better models under the influence of an appropriate gene evidence class. For instance, extra influence of homologous proteins returned models that more closely matched those proteins. Following each prediction run, the results were assessed for overall quality and matched to evidence. This assessment then suggested the options for new configurations and evidence mixtures. AUGUSTUS is also able to model alternate transcripts from evidence. But those are seldom supported by transcript assemblies and tend to include aberrations. Therefore, we did not use this option and instead used only transcripts assembled directly from EST/RNA reads in selecting alternate splice-forms. We also used as gene information, but not as evidence for re-constructing genes, the version OGS1.2 gene set [4], and NCBI (NCBI-11, RefSeq release v2, September 2011 [38]) gene models for Nasonia. We obtained a total of 333,121 alternate gene models from different evidence sets and parameters, as input to the EvidentialGene classifier (255,785 models from 16 separate AUGUSTUS runs as described above; 18,941 from OGS1.2; 30,379 from EST/RNA assemblies). EvidentialGene uses gene evidence described above from expression and protein sources to annotate each model and exon, then calculates quality scores per model for each type of gene evidence (see next paragraph below). Locus overlaps of gene models are also calculated, using the primary criteria of CDS-overlap on same DNA strand (reverse-strand CDS-overlap is rare, but locus UTR overlaps are relatively common). A weighted sum of the various evidence component scores is calculated, configurable to gene set requirements. Selecting the best locus from among a large set of gene models is accomplished according to two basic criteria: (1) gene evidence must pass a minimum threshold score, and (2) the combined score is maximal for all models overlapping the same CDS-locations. Other criteria and tests are included and used for classification, such as orthology scores. One indicator of a joined model error (Additional file 1: Figure S3) is a homology score for the joined model that is no greater than for un-joined models, though its coding span is larger. Determining a final gene set is an iterative process that involves evaluation after selection, modification of score weights, and reselection. After the majority of optimal models are found, smaller subsets of problem loci are sampled and examined, with additional evaluations to resolve these. This is a negative-feedback process designed to filter out errors and suboptimal gene models, with successive iterations changing fewer models until the optimal set is found. It also involves expert curation to identify and remove suboptimal models, and locate or promote missed high value models (e.g., unique orthologs). The quality scores per model are calculated using the following types of evidence: (a) the level of RNA sequence coverage and tiling array signal over the gene model coordinates on the genome assembly; (b) the number of EST and RNA sequence reads spanning the intron splice sites that matched to annotated exon ends; (c) gene structure agreement, as end-to-end match of exons in the model with the evidence in support of gene structure, summarized in Table 3 for evidence structure from EST/RNA assemblies and reference proteins; (d) sequence homology to proteins from eleven species-specific reference databases using BLASTp scores of all significant matches to the reference set of genes including the number of reference protein matches, bitscore per protein match, and the similarity scores for alignments to same species paralog proteins. These quality scores are summarized for several Nasonia gene sets (Table 3) and partitioned according to the source of evidence (EST, RNA sequences, tiled expression spans, reference sequences (Nasonia RefSeq), and reference species proteins. Each gene model for each locus is therefore scored by weighted evidence. Finally, the maximal evidence scored, non-overlapping model set is determined, with respect to inter-locus effects of gene joins and other factors. The EvidentialGene script “annotate_predictions.pl” encapsulates this algorithm. The configurations for this Nasonia annotation project are specified in “evigene_wasp2.conf”, which identifies the sources of gene evidence, the gene model sets, the evidence scoring and weighting schemes, plus other factors. An independent evaluation of gene sets for evidence-based recovery is produced by the script “evaluate_predictions.pl”. The summary output table from “evaluate_predictions.pl”, which lists the types of evidence and the recovered gene set, is the source of Table 3. This evidence-based recovery process is calculated for each iterative gene selection, followed by expert examination of sample loci, for adjustments that are made to the weighting scheme, to optimize as many of the evidence components as possible. During this process, the expert-selected models are retained. This evidence scoring of genes is roughly similar to EvidenceModeler [89] and GLEAN [90]. As with EvidenceModeler, an evidence weighing statement is part of the configuration, and an optimal weighting is derived by iterative trials and evaluations. Coding potential for the gene models was scored according to (i) homology to reference proteins, (ii) size of calculated open reading frames (ORF in base pairs), (iii) relative size of ORF to total transcript size, (iv) introns in coding span. These and other measures are commonly used (e.g., [47, 91]), but are often not definitive (see Additional file 10). Our assignment of the gene models to locus type – including protein-coding, non-coding, and transposon – is based on coding potential and other factors that are shared with the NCBI locus typing [38]. For transposons, this includes sequence similarity to known transposon sequences that are previously reported [4], and protein homology to other annotated transposon proteins. Gene names in OGS2 have been assigned on the basis of sequence alignment to UniProt proteins, to reference insect genes, and to the consensus gene family names from OrthoMCL orthology analyses, by using a BLASTp e-value threshold < 1e-5 and three levels of percentage alignment criteria: levels > 10 % (minimum score to name), > 33 %, and > 66 %. The names are in accordance with UniProt protein naming guidelines [92]. Weak and modest alignments were given the added name qualifiers (“-like” for < 33 %, and “putative” for < 66 %). Some genes were named despite having < 10 % alignment (82); most are transposons with additional evidence of transposon sequence alignment, some are expert choices (e.g., Nasvi2EG008578t1, odorant receptor), and some are poorly associated names. The gene annotations include preferred name, orthology family name, and naming reference gene IDs, and alignment scores. Ortholog group assignments and gene family expansions Orthology of Nasonia protein coding genes was assigned using two methods: OrthoMCL [93] and OrthoDB [32]. OrthoMCL was used during gene construction as an essential measure of gene quality, for refining gene model classifications. For OrthoMCL, related species proteomes with Nasonia gene models were aligned using all-by-all reciprocal best BLASTp [94, 95] of 11 species’ proteomes (wasp plus those listed above). Alternate transcripts were removed after BLASTp matching, in order to use the most similar gene variants. Clustering of these blast alignments into gene families was also done using OrthoMCL. The resulting gene families are narrow or broad, depending on the chosen alignment options, especially the distance at which to break groups. Resulting groups are rather like the leaves at the tips of a phylogenetic tree. Further MCL clustering of these groups showed relations between many of the narrowly clustered groups. Significance criteria were applied using recommended options: a similarity p-value < 1e-05, protein percent identity > 40 %, and MCL inflation of 1.5 (this affects the granularity of clustering). Reciprocal best similarity pairs between species, and reciprocal better similarity pairs within species (i.e., recently arisen paralogs, or in-paralogs, proteins that are more similar to each other within one species than to any protein in the other species) were added to a similarity matrix. The protein similarity matrix was normalized by species and subjected to Markov clustering (MCL; [96, 97]) to generate ortholog groups including recent in-paralogs. An additional round of MCL clustering was applied to identify between-group relations. After producing the Nasonia OGS2 genes, its protein sequences were incorporated into release-6 of the OrthoDB database [32]. Ortholog groups are here defined as groups of genes related by descent from a single common ancestor at the base of the taxonomic level of interest. All genes within a single ortholog group evolved from a series of speciation and/or gene duplication events from a unique ancestor. Their amino acid sequences can thus be aligned and compared with each other. Ortholog groups provide efficient units of analysis for genes over long timescales as they enable partitioning in evolutionarily relevant categories without the need to resolve precise 1 to 1 relationships. From the total 24,388 OGS2 genes, 15,173 (62 %) could be assigned to an ortholog group among the Arthropoda in OrthoDB version 6. We assessed which ortholog groups are characterized by evolutionary expansions in the Nasonia lineage. We selected 9601 ortholog groups that have paralogs in Nasonia and over 80 % of the other sequenced Arthropoda. To further increase the stringency of the selection criteria, we removed all genes from this set that have any duplicates in other hymenopteran species. Of the total 9601 ortholog groups, 411 (0.05 %) have duplicates specific to the Nasonia lineage among the Hymenoptera. We used sequence similarity searches to cross-validate the absence of ultra-conserved ortholog groups of the BUSCO dataset (OrthoDB) from the Nasonia genome. We retrieved protein sequences for all genes within those ortholog groups from all sequenced arthropods. Identification of fast- and slow-diverging genes in the Nasonia relative to ants and bees We retrieved amino-acid alignments for ortholog groups among the Hymenoptera from OrthoDB version 6 and selected those that contained at least one gene in the Nasonia genome and at least one gene in one ant and one bee genome (8696 OGs). We generated a pairwise sequence divergence matrix, comparing all genes versus all genes within each of those ortholog groups by applying a JTT protein evolution model as implemented in the R package phangorn [98]. We then estimated the proportion of between-genus sequence divergence due to the Nasonia genes using the following ratio AN+BNAN+BN+AB where AN and BN are the median pairwise amino-acid distances between the Nasonia gene and Ant or Bee orthologs respectively, and AB is the median pairwise distance between the ant and bee orthologs in the genes’ ortholog group. We analyzed this ratio with a generalized linear mixed model (GLMM) with logit link function, using overall median sequence divergence of the ortholog group, presence of Nasonia paralogs and transposon-associated expression as predictors to account for the role of those factors in protein evolution. We also used the ortholog group ID as a random blocking factor to account for individual differences in evolutionary rates between ortholog groups. We then extracted the GLMM’s residuals to evaluate the remaining unexplained levels of sequence evolution. We selected genes that exceeded the 95th percentile of the distribution of residuals as highly diverging, and those below the 5th percentile as slowly diverging. We did not include relative non-synonymous to synonymous substitution rates in the GLMM because the analysis is based on protein sequence alignments scored by a weighted matrix of amino acid substitutions. To avoid false positives due to exceedingly fast or slow protein sequence evolution in either the ant or bee clade, we also computed separately the rates of divergence between Nasonia and the ant or bee lineages (AN/AN+BN+AB and BN/AN+BN+AB). We then generated two independent GLMMs for these ratios with the same factors used for the compound ratio and reported the genes that scored as significantly faster or slower (above 80th percentile or below 20th percentile) in both cases. This second set provides a high confidence list of genes that are differentially diverging in the Nasonia lineage but show limited differentiation between the ant and bee lineages. We point out that this is a tool to identify proteins that may be evolving more quickly at the amino acid level in the Nasonia clade. Because the analysis is unrooted, the method does not identify proteins that are specifically evolving more quickly since divergence of Nasonia from its common ancestor with ants and bees, but also includes changes from that common ancestor to the split between ants and bees. More precise evolutionary analyses will require phylogenetic reconstruction for all the genes, but the current set is useful for identifying likely candidates for divergence among these taxa. Given the very long branches involved in such analyses, use of dN/dS ratios as an index of adaptive evolution would be inappropriate due to total saturation of synonymous substitutions. Functional enrichment testing We tested all gene sets for functional enrichment of Gene Ontology (GO) terms obtained by Blast2GO [99], using the two-tailed Fisher’s exact test with a False Discovery Rate (FDR) of 5 % against the complete gene complement of N. vitripennis. The Nasonia GO annotation for OGS2 was provided by the Nasonia community [70]. Of the 24,388 OGS2 genes with supporting evidence, 24,373 are present in the community-provided Blast2Go annotation files and 6446 of these (26,4 %) have GO assignments. Alternative splicing analysis We used GLMMs to test for factors correlated with the presence or absence of alternative transcripts in OGS2. Our test factors include presence of strict sense paralogs (defined as reciprocal best sequence similarity match within the same genome versus reciprocal best match within other genomes), number of broad sense paralogs (genes within the same genome belonging to the same arthropod OrthoDB ortholog group plus one, log and z transformed), number of predicted introns (log and z transformed), transcript length (log and z transformed, using the longest transcript per gene), proportion of coding sequence over total transcript length (CDS/Transcript length, log transformed and normalized), ratio of Nasonia-specific protein evolution (see Methods section “Identification of fast- and slow-diverging genes in the Nasonia relative to ants and bees”, log and z transformed), methylation status in adult females [16] and phylostratigraphic age [15]. We selected only genes with a complete record for all tested factors. Since the detection of isoforms is proportional to the coverage of that gene, we further restricted our analyses only to genes with both strong expression support and strong intron support, which have comparable levels of transcriptional data available. Therefore, our final dataset was comprised of 5447 genes. To estimate over-dispersion, we fitted a GLM with quasi-binomial error distribution including all analysis parameters. This model did not show over-dispersion, with a c-hat of 1. We therefore fitted subsequent models to a binomial distribution with logit link function. All subsequent models also included a random intercept error structure for each ortholog group among arthropods, to account for different selective pressure on different gene families. We estimated the support of individual factors by fitting a full model incorporating all parameters, then compared this model to others incorporating all factor combinations by applying the Akaike Information Criterion, corrected for finite sample size (AICc). We calculated the relative importance of factors as the sum of weights of all models containing that factor over the total weight of all models within the set. Since the final model set contained several models with similar AICc values (Additional file 13), we choose to present the results as model-averaged estimates rather than to choose a single best model. Mapping OGS2 to Nvit_2.1 reference genome assembly To map GFF files between assemblies, we first generated a chain file as follows: we split the Nvit_1.0 assembly into 5 kb fragments, and aligned each fragment to the Nvit_2.1 reference using BLAT (options: tileSize = 11, minScore = 100, minIdentity = 98, fastMap), using an ooc file produced with the makeOoc option to BLAT. We then combined all the BLAT output using liftUp to convert the result files into the parent (in this case Nvit_1.0) coordinate system. The resulting psl file was processed with axtChain (options: linearGap = medium, psl), chainMergeSort, chainSplit (options: lump = 20), chainNet, and chainSubset to produce a chain file. We then produced the reciprocal file using chainSwap. Both chain files (Nvit_to NVIT, and Nvit_to NVIT) are provided as supplemental material (Additional file 5). Additional software tools Most statistical analyses were performed in R version 3.0.0 [100] using the following packages: plyr [101] and reshape2 [102] for data handling, phangorn for sequence analyses [98], lme4 [103] for GLMMs, MuMIn [104] for multi-model comparisons and model-averaging, vcd [105] and ggplot2 [106] for plotting. Functional enrichment testing was performed using Blast2GO [99]. Abbreviations BUSCO, benchmarking universal single copy orthologs; CDS, protein coding sequences; EST, expressed sequence tags; GLMM, generalized linear mixed model; lncRNA, long noncoding RNA; mRNA, messenger RNA; NCBI-101, NCBI Nasonia vitripennis annotation release 101; Nvit_1.0, Nasonia vitripennis genome assembly 1.0; Nvit_2.1, Nasonia vitripennis genome assembly 2.1; OG, orthologous group; OGS1.2, official gene set 1.2; OGS2, official gene set 2; RNA-Seq, RNA-sequencing; UTR, untranslated region Additional files Additional file 1: Figure S1. Expression values relative to gene structures for RNA-Seq (Reads) and genome tiling path microarrays (Tile) for species Nasonia (purple, this project), Drosophila (red, blue, [74]) and Daphnia (green, [107]). Annotated gene near-exon spans are scored per base for average expression scores from the data sets, and relative expression plotted with respect to gene transcript start (first exon), stop (last exon), and inner exon start, stop positions. Both methods (genome tiling and RNA-Seq) have abrupt expression strength changes at exon boundaries, on average, indicating their value in modeling gene structure positions. Expression scores are read-coverage for RNA-Seq, and log-normalized intensity for tiling array, as described in the Methods section. Figure S2. Gene modeling example with tile expression data, including gene evidence (upper tracks with tiling, introns, proteins), tiling TAR-exon to Exonerate models (middle), and gene predictions from tile TAR hints (lower), on genome map. The lower tracks have excessive false UTR spans attached to gene models, primarily due to tiling expression that lacks gene start/stop and intron splice joining signals. These false UTR spans are supported by expression evidence, but as a combination of alternate exons, separate gene loci, and non-coding expression. Intermediate tracks (Exonerate models) often match gene structures from other methods, but have a high proportion of unsupported exon extensions as for lower track. Figure S3. Gene join error example. A mistaken gene model from honey bee (tan, lower, LOC552483) is transferred to Nasonia in NCBI RefSeq models (dark orange, middle), merging a ribosomal protein (right) and Ankyrin repeat protein (left). EvidentialGene models (yellow, top) did not contain this mistake, due to the combination of RNA-Seq assemblies (purple, bottom) that are un-joined (but could be parts of one gene), the lack of intron joining evidence, and the orthology assessment metrics that distinguish gene joins from true complete genes. NCBI Refseq models for both Apis (new LOC102654426 and mRpL52 in NCBI Apis rel. 102) and Nasonia have been updated to correct this join error. Figure S4. Log counts of methylated and unmethylated genes in different classes of expression support. Grey bars indicate genes with no known methylation status. (ZIP 938 kb) Additional file 2: Table S1. Consensus in the location of the OGS2 gene set on the genome assemblies of sibling species Nasonia longicornis and N. giraulti, including recent, high identity paralogs. Almost all OGS2 genes are located on 2 sibling species draft assemblies [4], using GMAP [36] transcript mapping. Paralog locus consensus patterns are tabulated for inparalogs (sharing orthology to other species) and uniquepar (lacking strong homology to other species). Of the total paralog families, each with several genes, most paralogs are on different scaffolds for all species. The counts of tandem paralogs with different separations are indicated. Table S2. A set of 62 orthology groups found in Nasonia transcript assemblies that are poorly mapped onto the current genome, but should be considered as part of a complete Nasonia gene set. Table S3. A total of 75 orthology groups missing from Nasonia but found in 9 other insect genomes. Table S4. Histone genes present in OGS2.0 annotated with presence or absence of lineage-specific expansions. NA entries were not assigned to orthologous groups at the level of Hymenoptera. (ZIP 33 kb) Additional file 3: OrthoDB6 BUSCO (Benchmarking Universal Single Copy Orthologs) genes missing from OGS2. (XLS 1367 kb) Additional file 4: OrthoDB6 BUSCO (Benchmarking Universal Single Copy Orthologs) genes present in multiple copies in OGS2. (XLS 51 kb) Additional file 5: Chain files, GFF mapping and transcript status of OGS2 on Nvit_2.1 genome assembly. (XLS 17233 kb) Additional file 6: Table of OGS2 gene transcripts equivalences to OGS1 and NCBI-101 gene sets, using the CDS-exon locations on the genome assembly. “NCBI101geneID” and “OGS1geneID” include equivalence value as percent equal to CDS.EXON. For example: Nasvi2EG000002t1 nasvn14g1803t1/99.70 is 99 % CDS equal, 70 % exon equal; NV10001-RA/74.89 is 74 % CDS equal, 89 % exon equal. The “NCBI101geneID” is the local ID “gene1803” from the NCBI GFF gene table, adding “nasvn14g” prefix and alternate transcript suffix “t1,t2,..”, with associated column of public “NCBI101transcriptID” (XM_ or NM_). “Genome21loc” is the gene span location on Nvit_2.1 scaffold assembly, “Genome1loc” is the gene span location on Nvit_1.0 scaffold assembly (most Nvit_2.1 and 1.0 are equivalent). “NCBI101also” and “OGS1also” are additional gene transcripts with partial equivalence to the OGS2 gene. Nonequivalence values: “na” for “NCBI101geneID”, “novid” for “OGS1geneID”. “WaspAtlasNCBI101” lists NCBI-101 equivalent genes provided by [40]. Disagreements are marked by “*”. These appear to be UTR-exon or gene-span overlaps, rather than the CDS-exon overlap used in this table equivalence. (XLSX 2889 kb) Additional file 7: OGS2 genes whose ortholog groups are characterized by lineage-specific expansions or contractions. (XLS 3711 kb) Additional file 8: Protein evolutionary distances of OGS2.0 genes compared to ant and bee lineages, residuals distances after model fitting and fast/slow evolving categorization at the 5th and 20th quantile threshold. (XLS 2790 kb) Additional file 9: Protein alignment of the OG EOG6R4ZDK (hymenopteran histone H3). Clipped to include only residues shared between all genes. (TXT 13 kb) Additional file 10: Supplement document on long non-coding RNA expression and genes within the Nasonia genome and genomes of other animals. (DOCX 6088 kb) Additional file 11: Genes with more than 10 isoforms present in OGS2. (XLS 48 kb) Additional file 12: Figure S5. Correlation between methylation status and expression support in OGS2.0. (PDF 4 kb) Additional file 13: Model selection table for models comprising different combinations of factors with a putative role in characterizing genes with and without annotated isoforms. (XLS 59 kb) Acknowledgements We are grateful to the associate editor and two referees during the peer review process, who have critically evaluated this work. Funding This work was supported in part by the National Science Foundation (grant No. 0640462 to DGG), including genomics computational resources via TeraGrid amd XSEDE. Additional support was provided by a start-up grant to JKC by the University of Birmingham (UK) and earlier by the Center for Genomics and Bioinformatics (CGB) at Indiana University, which was supported in part by the METACyt Initiative of Indiana University, funded in part through a major grant from the Lilly Endowment, Inc. and US NIH R24 GM-084917 to JHW. Availability of data and materials Source of the wasps used in this study is a laboratory strain in the lab of Prof John (Jack) Werren. The data sets supporting the results of this article are available at the NCBI data repository under accession numbers: GE352825-GE467204 and ES613911-ES651267 and as BioProject PRJNA219398. OGS2 and its associated search tools are available at http://arthropods.eugenes.org/EvidentialGene/nasonia/, www.hymenopteragenome.org/nasonia/ and waspAtlas: www.tinyURL.com/waspAtlas. The EvidentialGene pipeline is available at https://sourceforge.net/projects/evidentialgene/. Authors’ contributions AR performed the statistical analyses on the gene set and wrote the manuscript. DG conceived, designed and developed gene construction methods, and provided public web access genome database of Nasonia. JHC modeled, evaluated and annotated gene constructions, and performed summary analyses. TS provided the sequencing data and assisted in drafting the manuscript. YK provided the comparisons between OGS2 and NCBI Annotation Release 101. JHW and JKC conceived the study, provided scientific guidance and participated in the writing of the manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no any competing interests. Consent for publication Not applicable. Ethics approval and consent to participate Not applicable. ==== Refs References 1. Quicke DLJ, et al. Parasitic Wasps. London: Chapman & Hall Ltd; 1997. 2. Werren JH Loehlin DW The parasitoid wasp Nasonia: An emerging model system with haploid male genetics Cold Spring Harb Protoc 2009 4 1 31 3. Lynch JA The Expanding Genetic Toolbox of the Wasp Nasonia vitripennis and Its Relatives Genetics 2015 199 897 904 10.1534/genetics.112.147512 25855650 4. Werren JH Richards S Desjardins CA Niehuis O Gadau J Colbourne JK Beukeboom LW Desplan C Elsik CG Grimmelikhuijzen CJP Kitts P Lynch JA Murphy T Oliveira DCSG Smith CD van de Zande L Worley KC Zdobnov EM Aerts M Albert S Anaya VH Anzola JM Barchuk AR Behura SK Bera AN Berenbaum MR Bertossa RC Bitondi MMG Bordenstein SR Bork P Functional and evolutionary insights from the genomes of three parasitoid Nasonia species Science 2010 327 343 8 10.1126/science.1178028 20075255 5. Misof B Phylogenomics resolves the timing and pattern of insect evolution Science 2014 346 763 768 10.1126/science.1257570 25378627 6. Raychoudhury R Desjardins CA Buellesbach J Loehlin DW Grillenberger BK Beukeboom L Schmitt T Werren JH Behavioral and genetic characteristics of a new species of Nasonia Heredity (Edinb) 2010 104 278 288 10.1038/hdy.2009.147 20087394 7. Breeuwer J Werren JH Microorganisms associated with chromosome destruction and reproductive isolation between two insect species Nature 1990 346 6284 558 60s 10.1038/346558a0 2377229 8. Bordenstein SR O’Hara FP Werren JH Wolbachia-induced bidirectional incompatibility precedes other hybrid incompatibilities in Nasonia Nature 2001 409 707 710 10.1038/35055543 11217858 9. Werren JH Cohen LB Gadau J Ponce R Lynch JA Dissection of the complex genetic basis of craniofacial anomalies using haploid genetics and interspecies hybrids in Nasonia wasps Dev Biol 2015 26721604 10. Gibson JD Niehuis O Peirson BRE Cash EI Gadau J Genetic and developmental basis of F2 hybrid breakdown in Nasonia parasitoid wasps Evolution 2013 67 2124 32 10.1111/evo.12080 23815665 11. Niehuis O Buellesbach J Gibson JD Pothmann D Hanner C Mutti NS Judson AK Gadau J Ruther J Schmitt T Behavioural and genetic analyses of Nasonia shed light on the evolution of sex pheromones Nature 2013 494 345 8 10.1038/nature11838 23407492 12. Loehlin DW Werren JH Evolution of Shape by Multiple Regulatory Changes to a Growth Gene Science 2012 335 943 947 10.1126/science.1215193 22363002 13. Brucker RMR Bordenstein SSR The hologenomic basis of speciation: gut bacteria cause hybrid lethality in the genus Nasonia Science 2013 466 667 670 10.1126/science.1240659 23868918 14. Pannebakker BA Trivedi U Blaxter ML Blaxter MA Watt R Shuker DM The transcriptomic basis of oviposition behaviour in the parasitoid wasp Nasonia vitripennis PLoS One 2013 8 e68608 10.1371/journal.pone.0068608 23894324 15. Sackton TB Werren JH Clark AG Characterizing the infection-induced transcriptome of Nasonia vitripennis reveals a preponderance of taxonomically-restricted immune genes PLoS One 2013 8 e83984 10.1371/journal.pone.0083984 24386321 16. Wang X Wheeler D Avery A Rago A Choi J-H Colbourne JK Clark AG Werren JH Function and evolution of DNA methylation in Nasonia vitripennis PLoS Genet 2013 9 e1003872 10.1371/journal.pgen.1003872 24130511 17. Barribeau SM Gerardo NM An evolutionarily and ecologically focused strategy for genome sequencing efforts Heredity (Edinb) 2012 108 577 80 10.1038/hdy.2011.109 22126851 18. Waterhouse RM A maturing understanding of the composition of the insect gene repertoire Curr Opin Insect Sci 2015 7 January 15 23 10.1016/j.cois.2015.01.004 19. Pauli A Rinn JL Schier AF Non-coding RNAs as regulators of embryogenesis Nat Rev Genet 2011 12 136 149 10.1038/nrg2904 21245830 20. Carthew RW Sontheimer EJ Origins and Mechanisms of miRNAs and siRNAs Cell 2009 136 642 55 10.1016/j.cell.2009.01.035 19239886 21. Xue S Tian S Fujii K Kladwang W Das R Barna M RNA regulons in Hox 5′ UTRs confer ribosome specificity to gene regulation Nature 2015 517 7532 33 8 10.1038/nature14010 25409156 22. Olesnicky EC Desplan C Distinct mechanisms for mRNA localization during embryonic axis specification in the wasp Nasonia Dev Biol 2007 306 134 42 10.1016/j.ydbio.2007.03.012 17434472 23. Sterck L Rombauts S Vandepoele K Rouzé P Van de Peer Y How many genes are there in plants (… why are they there)? Curr Opin Plant Biol 2007 10 199 203 10.1016/j.pbi.2007.01.004 17289424 24. Weinstock GM Robinson GE Gibbs RA Worley KC Evans JD Maleszka R Robertson HM Weaver DB Beye M Bork P Elsik CG Hartfelder K Hunt GJ Zdobnov EM Amdam GV Bitondi MMG Collins AM Cristino AS Michael H Lattorff G Lobo CH Moritz RFA Nunes FMF Page RE Simões ZLP Wheeler D Carninci P Fukuda S Hayashizaki Y Kai C Insights into social insects from the genome of the honeybee Apis mellifera Nature 2006 443 931 949 10.1038/nature05260 17073008 25. Elsik CG Worley KC Bennett AK Beye M Camara F Childers CP de Graaf DC Debyser G Deng J Devreese B Elhaik E Evans JD Foster LJ Graur D Guigo R Hoff KJ Holder ME Hudson ME Hunt GJ Jiang H Joshi V Khetani RS Kosarev P Kovar CL Ma J Maleszka R Moritz RFA Munoz-Torres MC Murphy TD Muzny DM Finding the missing honey bee genes: lessons learned from a genome upgrade BMC Genomics 2014 15 86 10.1186/1471-2164-15-86 24479613 26. Brown JB Boley N Eisman R May GE Stoiber MH Duff MO Booth BW Wen J Park S Suzuki AM Wan KH Yu C Zhang D Carlson JW Cherbas L Eads BD Miller D Mockaitis K Roberts J Davis CA Frise E Hammonds AS Olson S Shenker S Sturgill D Samsonova AA Weiszmann R Robinson G Hernandez J Andrews J Diversity and dynamics of the Drosophila transcriptome Nature 2014 512 393 399 10.1038/nature12962 24670639 27. Gerstein MB Rozowsky J Yan K-K Wang D Cheng C Brown JB Davis CA Hillier L Sisu C Li JJ Pei B Harmanci AO Duff MO Djebali S Alexander RP Alver BH Auerbach R Bell K Bickel PJ Boeck ME Boley NP Booth BW Cherbas L Cherbas P Di C Dobin A Drenkow J Ewing B Fang G Fastuca M Comparative analysis of the transcriptome across distant species Nature 2014 512 445 448 10.1038/nature13424 25164755 28. Eckalbar WL Hutchins ED Markov GJ Allen AN Corneveaux JJ Lindblad-Toh K Di Palma F Alföldi J Huentelman MJ Kusumi K Genome reannotation of the lizard Anolis carolinensis based on 14 adult and embryonic deep transcriptomes BMC Genomics 2013 14 49 10.1186/1471-2164-14-49 23343042 29. Gilbert DG. Perfect(ing) Arthropod Genes with Next Gen Informatics. In: 4th annual Arthropod Genomics Symposium. Kansas State U; 2010.  http://arthropods.eugenes.org/EvidentialGene/about/PerfectGenes2010.pdf. 30. Gilbert DG Evidential Genes for Nasonia vitripennis 2012 31. Wang X Werren JH Clark AG Genetic and epigenetic architecture of sex-biased expression in the jewel wasps Nasonia vitripennis and giraulti Proc Natl Acad Sci 2015 112 E3545 E3554 10.1073/pnas.1510338112 26100871 32. Waterhouse RM Tegenfeldt F Li J Zdobnov EM Kriventseva EV OrthoDB: a hierarchical catalog of animal, fungal and bacterial orthologs Nucleic Acids Res 2013 41 Database issue D358 65 10.1093/nar/gks1116 23180791 33. Kriventseva EV Tegenfeldt F Petty TJ Waterhouse RM Pozdnyakov IA Ioannidis P Sim FA Zdobnov M OrthoDB v8 : update of the hierarchical catalog of orthologs and the underlying free software Nucleic Acids Res 2015 43 Database issue D250 6 10.1093/nar/gku1220 25428351 34. Gilbert DG euGenes: a eukaryote genome information system Nucleic Acids Res 2002 30 145 148 10.1093/nar/30.1.145 11752277 35. Van de Peer Y Maere S Meyer A The evolutionary significance of ancient genome duplications Nat Rev Genet 2009 10 725 32 10.1038/nrg2600 19652647 36. Wu TD Watanabe CK GMAP: A genomic mapping and alignment program for mRNA and EST sequences Bioinformatics 2005 21 1859 1875 10.1093/bioinformatics/bti310 15728110 37. Buchta T Ozüak O Stappert D Roth S Lynch JA Patterning the dorsal-ventral axis of the wasp Nasonia vitripennis Dev Biol 2013 381 189 202 10.1016/j.ydbio.2013.05.026 23735637 38. Thibaud-Nissen F, Souvorov A, Murphy T, DiCuccio M, Kitts P. Eukaryotic Genome Annotation Pipeline. In: The NCBI Handbook [Internet]. 2nd ed. Bethesda: National Center for Biotechnology Information (US); 2013. https://www.ncbi.nlm.nih.gov/books/NBK169439/. Accessed 21 May 2016. 39. Knoll AH Early Animal Evolution: Emerging Views from Comparative Biology and Geology Science 1999 284 2129 2137 10.1126/science.284.5423.2129 10381872 40. Chen K Rajewsky N The evolution of gene regulation by transcription factors and microRNAs Nat Rev Genet 2007 8 93 103 10.1038/nrg1990 17230196 41. Pauls S Geldmacher-Voss B Campos-Ortega JA A zebrafish histone variant H2A.F/Z and a transgenic H2A.F/Z:GFP fusion protein for in vivo studies of embryonic development Dev Genes Evol 2001 211 603 10 10.1007/s00427-001-0196-x 11819118 42. Hardy S Jacques P-E Gévry N Forest A Fortin M-E Laflamme L Gaudreau L Robert F The euchromatic and heterochromatic landscapes are shaped by antagonizing effects of transcription on H2A.Z deposition PLoS Genet 2009 5 e1000687 10.1371/journal.pgen.1000687 19834540 43. Talbert PB Henikoff S Histone variants--ancient wrap artists of the epigenome Nat Rev Mol Cell Biol 2010 11 264 75 10.1038/nrm2861 20197778 44. Lyko F Foret S Kucharski R Wolf S Falckenhayn C Maleszka R The honey bee epigenomes: differential methylation of brain DNA in queens and workers PLoS Biol 2010 8 e1000506 10.1371/journal.pbio.1000506 21072239 45. Müller J Hart CM Francis NJ Vargas ML Sengupta A Wild B Miller EL O’Connor MB Kingston RE Simon JA Histone Methyltransferase Activity of a Drosophila Polycomb Group Repressor Complex Cell 2002 111 197 208 10.1016/S0092-8674(02)00976-5 12408864 46. Managadze D Lobkovsky AE Wolf YI Shabalina SA Rogozin IB Koonin EV The Vast, Conserved Mammalian lincRNome PLoS Comput Biol 2013 9 2 e1002917 10.1371/journal.pcbi.1002917 23468607 47. Niazi F Valadkhan S Computational analysis of functional long noncoding RNAs reveals lack of peptide-coding capacity and parallels with 39 UTRs RNA 2012 18 825 843 10.1261/rna.029520.111 22361292 48. Smibert P Miura P Westholm JO Shenker S May G Duff MO Zhang D Eads BD Carlson J Brown JB Eisman RC Andrews J Kaufman T Cherbas P Celniker SE Graveley BR Lai EC Global Patterns of Tissue-Specific Alternative Polyadenylation in Drosophila Cell Rep 2012 1 277 289 10.1016/j.celrep.2012.01.001 22685694 49. Young RS Marques AC Tibbit C Haerty W Bassett AR Liu J-L Ponting CP Identification and Properties of 1,119 Candidate LincRNA Loci in the Drosophila melanogaster Genome Genome Biol Evol 2012 4 4 427 442 10.1093/gbe/evs020 22403033 50. Ponjavic J Oliver PL Lunter G Ponting CP Genomic and transcriptional co-localization of protein-coding and long non-coding RNA pairs in the developing brain PLoS Genet 2009 5 e1000617 10.1371/journal.pgen.1000617 19696892 51. Steijger T Abril JF Engstrom PG Kokocinski F The RGASP Consortium, et al. Assessment of transcript reconstruction methods for RNA-seq Nat Methods 2013 52. Hoedjes KM Smid HM Schijlen EG Vet LE van Vugt JJ Learning-induced gene expression in the heads of two Nasonia species that differ in long-term memory formation BMC Genomics 2015 16 1 13 10.1186/s12864-015-1355-1 25553907 53. Yan Eusocial insects as emerging models for behavioural epigenetics Nat Rev Genet 2014 15 677 688 10.1038/nrg3787 25200663 54. Roberts TC Morris KV Wood MJA The role of long non-coding RNAs in neurodevelopment, brain function and neurological disease Phil Trans R Soc B 2014 369 20130507 10.1098/rstb.2013.0507 25135968 55. Davies Conserved Noncoding in Nasonia + other insects BMC Evol Biol 2015 15 227 10.1186/s12862-015-0499-6 26482678 56. Giniger E, Tietje K, Jan L, Jan Y. lola encodes a putative transcription factor required for axon growth and guidance in Drosophila. Development. 1994;1398:1385–98. 57. Bertossa RC van de Zande L Beukeboom LW The Fruitless gene in Nasonia displays complex sex-specific splicing and contains new zinc finger domains Mol Biol Evol 2009 26 1557 69 10.1093/molbev/msp067 19349644 58. Shukla S Kavak E Gregory M Imashimizu M Shutinoski B Kashlev M Oberdoerffer P Sandberg R Oberdoerffer S CTCF-promoted RNA polymerase II pausing links DNA methylation to splicing Nature 2011 479 74 9 10.1038/nature10442 21964334 59. Bonasio R Li Q Lian J Mutti NS Jin L Zhao H Zhang P Wen P Xiang H Ding Y Jin Z Shen SS Wang Z Wang W Wang J Berger SL Liebig J Zhang G Reinberg D Genome-wide and caste-specific DNA methylomes of the ants Camponotus floridanus and Harpegnathos saltator Curr Biol 2012 22 1755 64 10.1016/j.cub.2012.07.042 22885060 60. Flores K Wolschin F Corneveaux JJ Allen AN Huentelman MJ Amdam GV Genome-wide association between DNA methylation and alternative splicing in an invertebrate BMC Genomics 2012 13 480 10.1186/1471-2164-13-480 22978521 61. Roy M, Kim N, Xing Y, Lee C. The effect of intron length on exon creation ratios during the evolution of mammalian genomes. RNA. 2008;2261–2273. 62. Domazet-Lošo T Tautz D A phylogenetically based transcriptome age index mirrors ontogenetic divergence patterns Nature 2010 468 815 8 10.1038/nature09632 21150997 63. Kopelman NM Lancet D Yanai I Alternative splicing and gene duplication are inversely correlated evolutionary mechanisms Nat Genet 2005 37 588 589 10.1038/ng1575 15895079 64. Roux J Robinson-Rechavi M Age-dependent gain of alternative splice forms and biased duplication explain the relation between splicing and duplication Genome Res 2011 21 357 363 10.1101/gr.113803.110 21173032 65. Su Z Evolution of alternative splicing after gene duplication Genome Res 2005 16 182 189 10.1101/gr.4197006 16365379 66. Brites D Brena C Ebert D Du Pasquier L More than one way to produce protein diversity: Duplication and limited alternative splicing of an adhesion molecule gene in basal arthropods Evolution (N Y) 2013 67 2999 3011 67. Su Z Gu X Revisit on the evolutionary relationship between alternative splicing and gene duplication Gene 2012 504 102 106 10.1016/j.gene.2012.05.012 22621894 68. Talavera D Vogel C Orozco M Teichmann SA De La Cruz X The (In)dependence of alternative splicing and gene duplication PLoS Comput Biol 2007 3 0375 0388 10.1371/journal.pcbi.0030033 69. Moyers BA Zhang J Phylostratigraphic Bias Creates Spurious Patterns of Genome Evolution Mol Biol Evol 2014 32 258 267 10.1093/molbev/msu286 25312911 70. Munoz-Torres MC, Reese JT, Childers CP, Bennett AK, Sundaram JP, Childs KL, Anzola JM, Milshina N, Elsik CG. Hymenoptera Genome Database: Integrated community resources for insect species of the order Hymenoptera. Nucleic Acids Res. 2011;39 Suppl 1:658–62. 71. Davies NJ Tauber E WaspAtlas : A Nasonia vitripennis gene database 2015 bav103 72. Gilbert DG. Gene-omes built from mRNA seq not genome DNA. 7th annual arthropod genomics symposium. Notre Dame: 2013. doi:10.7490/f1000research.1112594.1. 73. Roy S Ernst J Kharchenko PV Kheradpour P Negre N Eaton ML Landolin JM Bristow CA Ma L Lin MF Washietl S Arshinoff BI Ay F Meyer PE Robine N Washington NL Di Stefano L Berezikov E Brown CD Candeias R Carlson JW Carr A Jungreis I Marbach D Sealfon R Tolstorukov MY Will S Alekseyenko AA Artieri C Booth BW Identification of functional elements and regulatory circuits by Drosophila modENCODE Science 2010 330 1787 97 10.1126/science.1198374 21177974 74. Mackay TFC Stone EA Ayroles JF The genetics of quantitative traits: challenges and prospects Nat Rev Genet 2009 10 565 77 10.1038/nrg2612 19584810 75. Ayroles JF Carbone MA Stone EA Jordan KW Lyman RF Magwire MM Rollmann SM Duncan LH Lawrence F Anholt RRH Mackay TFC Systems genetics of complex traits in Drosophila melanogaster Nat Genet 2009 41 299 307 10.1038/ng.332 19234471 76. Haas BJ Delcher AL Mount SMSM Wortman JR Smith RK Hannick LI Maiti R Ronning CM Rusch DB Town CD Salzberg SL White O Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies Nucleic Acids Res 2003 31 5654 5666 10.1093/nar/gkg770 14500829 77. Trapnell C Williams BA Pertea G Mortazavi A Kwan G van Baren MJ Salzberg SL Wold BJ Pachter L Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation Nat Biotechnol 2010 28 511 5 10.1038/nbt.1621 20436464 78. Zerbino DR Birney E Velvet: Algorithms for de novo short read assembly using de Bruijn graphs Genome Res 2008 18 821 829 10.1101/gr.074492.107 18349386 79. Schulz MH Zerbino DR Vingron M Birney E Oases: robust de novoRNA-seq assembly across the dynamic range of expression levels Bioinformatics 2012 28 1086 1092 10.1093/bioinformatics/bts094 22368243 80. Wu TD Nacu S Fast and SNP-tolerant detection of complex variants and splicing in short reads Bioinformatics 2010 26 873 881 10.1093/bioinformatics/btq057 20147302 81. Lopez JA, Colbourne JK. Dual-Labeled Expression-Tiling Microarray Protocol for Empirical Annotation of Genome Sequences. CGB Technical Report. Bloomington, Indiana: The Center for Genomics and Bioinformatics, Indiana University; 2011. doi:10.2506/cgbtr-201102. 82. Slater GSC Birney E Automated generation of heuristics for biological sequence comparison BMC Bioinformatics 2005 6 31 10.1186/1471-2105-6-31 15713233 83. Desjardins CA Gadau J Lopez JA Niehuis O Avery AR Loehlin DW Richards S Colbourne JK Werren JH Fine-scale mapping of the nasonia genome to chromosomes using a high-density genotyping microarray G3 (Bethesda) 2013 3 205 15 10.1534/g3.112.004739 23390597 84. Roberts RJ Vincze T Posfai J Macelis D REBASE-A database for DNA restriction and modification: Enzymes, genes and genomes Nucleic Acids Res 2009 38 2009 2011 85. Smit AFA, Hubley R, Green P. RepeatMasker Open-4.0. 2013–2015. http://www.repeatmasker.org. Accessed 7 Aug 2016. 86. Stanke M, Morgenstern B. AUGUSTUS: A web server for gene prediction in eukaryotes that allows user-defined constraints. Nucleic Acids Res. 2005;33 Suppl 2:465–7. 87. Stanke M, Waack S. Gene prediction with a hidden Markov model and a new intron submodel. Bioinformatics. 2003;19 Suppl 2:215–25. 88. Stanke M Schöffmann O Morgenstern B Waack S Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources BMC Bioinformatics 2006 7 62 10.1186/1471-2105-7-62 16469098 89. Haas BJ Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments Genome Biol 2008 9 R7 10.1186/gb-2008-9-1-r7 18190707 90. Elsik CG Creating a honey bee consensus gene set Genome Biol 2007 8 R13 10.1186/gb-2007-8-1-r13 17241472 91. Fickett JW Recognition of protein coding regions in DNA sequences Nucleic Acids Res 1982 10 5303 5318 10.1093/nar/10.17.5303 7145702 92. Generalised protein naming guidelines. 2016. http://www.uniprot.org/docs/gennameprot.txt. Accessed 21 May 2016. 93. Li L, Stoeckert CJ Jr, Roos DS. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res. 2003;13(9):2178-89. 94. Altschul SF Gish W Miller W Myers EW Lipman DJ Basic local alignment search tool J Mol Biol 1990 215 403 410 10.1016/S0022-2836(05)80360-2 2231712 95. Altschul S Madden T Schaffer A Zhang J Zhang Z Miller W Dj L Gapped BLAST and PSI- BLAST: a new generation of protein database search programs Nucleic Acids Res 1997 25 3389 3402 10.1093/nar/25.17.3389 9254694 96. Enright AJ Dongen SV Ouzounis CA An efficient algorithm for large-scale detection of protein families Nucleic Acids Res 2002 30 1575 1584 10.1093/nar/30.7.1575 11917018 97. van Dongen S. Graph Clustering by Flow Simulation. University of Utrecht; 2000. http://dspace.library.uu.nl/handle/1874/848. Accessed 7 Aug 2016. 98. Schliep KP phangorn: phylogenetic analysis in R Bioinformatics 2011 27 592 593 10.1093/bioinformatics/btq706 21169378 99. Conesa A Götz S García-Gómez JM Terol J Talón M Robles M Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research Bioinformatics 2005 21 3674 3676 10.1093/bioinformatics/bti610 16081474 100. R Core Team R: A Language and Environment for Statistical Computing 2013 101. Wickham H The Split-Apply-Combine Strategy for Data Analysis J Stat Softw 2011 40 1 29 102. Wickham H Reshaping Data with the reshape Package J Stat Softw 2007 21 1 20 10.18637/jss.v021.i12 103. Bates D Maechler M Bolker B lme4: Linear mixed-effects models using S4 classes 2013 104. Barton K MuMIn: Multi-model inference 2011 105. Meyer D Zeileis A Hornik K vcd: Visualizing Categorical Data 2014 106. Wickham H ggplot2: Elegant Graphics for Data Analysis 2009 New York Springer 107. Colbourne JK Pfrender ME Gilbert DG Thomas WK Tucker A Oakley TH Tokishita S Aerts A Arnold GJ Basu MK Bauer DJ Cáceres CE Carmel L Casola C Choi J-H Detter JC Dong Q Dusheyko S Eads BD Fröhlich T Geiler-Samerotte KA Gerlach D Hatcher P Jogdeo S Krijgsveld J Kriventseva EV Kültz D Laforsch C Lindquist E Lopez JA The ecoresponsive genome of Daphnia pulex Science 2011 331 555 61 10.1126/science.1197761 21292972 108. Simão FA Waterhouse RM Ioannidis P Kriventseva EV Zdobnov EM BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs Bioinformatics 2015 31 3210 3212 10.1093/bioinformatics/btv351 26059717

PMC005xxxxxx/PMC5000499.txt

==== Front Genet Sel EvolGenet. Sel. EvolGenetics, Selection, Evolution : GSE0999-193X1297-9686BioMed Central London 23910.1186/s12711-016-0239-4Research ArticleWhole-genome resequencing of Xishuangbanna fighting chicken to identify signatures of selection Guo Xing guoxing0405@126.com Fang Qi fangqi1986513@126.com Ma Chendong machendong513@126.com Zhou Bangyuan zhoubangyuan@126.com Wan Yi wanyi0405@126.com Jiang Runshen jiangrunshen@ahau.edu.cn College of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036 People’s Republic of China 26 8 2016 26 8 2016 2016 48 1 625 2 2016 5 8 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Selective breeding for genetic improvement is expected to leave distinctive selection signatures within genomes. The identification of selection signatures can help to elucidate the mechanisms of selection and accelerate genetic improvement. Fighting chickens have undergone extensive artificial selection, resulting in modifications to their morphology, physiology and behavior compared to wild species. Comparing the genomes of fighting chickens and wild species offers a unique opportunity for identifying signatures of artificial selection. Results We identified selection signals in 100-kb windows sliding in 10-kb steps by using two approaches: the pooled heterozygosity (Hp) and the fixation index (FST) between Xishuangbanna fighting chicken (YNLC) and Red Jungle Fowl. A total of 413 candidate genes were found to be putatively under selection in YNLC. These genes were related to traits such as growth, disease resistance, aggressive behavior and energy metabolism, as well as the morphogenesis and homeostasis of many tissues and organs. Conclusions This study reveals mechanisms and targets of artificial selection, which will contribute to improve our knowledge about the evolution of fighting chickens and facilitate future quantitative trait loci mapping. Electronic supplementary material The online version of this article (doi:10.1186/s12711-016-0239-4) contains supplementary material, which is available to authorized users. http://dx.doi.org/10.13039/501100001809National Natural Science Foundation of ChinaNo. 31572395Jiang Runshen issue-copyright-statement© The Author(s) 2016 ==== Body Background Domesticated chickens have long been bred for entertainment and consumption [1]. Fighting chickens are a group of ancient breeds that have been bred for the purpose of cock fighting and have played an important role in the development of human culture [2]. The Xishuangbanna fighting chicken (YNLC) is a typical fighting chicken breed that has been subjected to strong artificial selection, which has led to remarkable phenotypic characteristics in morphology, physiology, and behavior. The YNLC represents an excellent model that can provide new insights into the influence of artificial selection on genetic variation and how this shapes phenotypic diversity. Selection leads to specific changes in the patterns of variation among selected loci and in neutral loci linked to them. These genomic footprints of selection are known as selection signatures and can be used to identify loci that have been subjected to selection [3]. Various statistical approaches have been proposed for the detection of selection signatures [4–7]. The pooled heterozygosity (Hp) statistic is a variability estimator based on allele counts across sliding windows of adjacent loci and can be used to identify regions that deviate from the norm [8]. The fixation index (FST) can be used to quantify the degree of genetic differentiation among populations based on differences in allele frequencies [9]. Both Hp and FST statistics are useful for the detection of selection signatures [10]. In this study, we used two outlier approaches (Hp and FST) to detect signatures of selection in YNLC and provide insights into the mechanisms of evolution of this specific breed. Methods Re-sequencing of chicken samples, mapping and SNP calling We downloaded the genomic data for eight YNLC and six wild Red Jungle Fowl (RJF) from the EMBL-EBI database (see Additional file 1: Table S1). Details about the sequenced samples and method of sequencing are in [11, 12]. As mentioned in these two papers, individual DNA libraries with an insert size of 500 bp were constructed and sequenced by using the Illumina HiSeq 2000 platform. The samples were sequenced at a genome coverage of 11.1X to 36.6X (see Additional file 1: Table S1) which is appropriate for analysis of selective sweeps [13, 14]. All reads were preprocessed for quality control and filtered using our in-house script in Perl. Before aligning reads onto the reference genome, we performed the following quality checks [15]:If there were more than 10 % unidentified nucleotides (N) or 10-nucleotide adaptors (<10 % mismatch) in either of the paired reads, the reads were removed. If there were more than 50 % low-quality bases (Q ≤ 5) in either of the paired reads, the reads were removed. Duplicated reads were also removed, only paired-end reads were kept for subsequent analyses. High-quality paired-end reads were mapped to the chicken reference genome sequence (ftp://ensembl.org/pub/release-67/fasta/gallus_gallus/dna/) using the BWA software [16] and the command ‘mem -t 4 -k 32 -M’. Duplicated reads were removed using the picard package [16]. After alignment, we performed single nucleotide polymorphism (SNP) calling on a population scale for the two groups (YNLC and RJF) using SAMtools [17]. The ‘mpileup’ command was used to identify SNPs with the parameters ‘-m 2 -F 0.002 -d 1000’. Putative functional effects of SNPs were annotated using the ANNOVAR package [18]. To exclude SNP calling errors caused by incorrect mapping, only high-quality SNPs (root-mean-square mapping quality ≥20, coverage depth ≥4 and ≤1000, distance between adjacent SNPs ≥5 bp and rate of missing data within each group <50 %) were retained for subsequent analyses. Analysis of selection signatures We used allele frequencies at variable sites to identify signatures of selection in 100-kb windows with a step size of 10 kb by using two approaches. For each window, we calculated Hp and FST. At each detected SNP position, we counted the number of reads corresponding to the most and least frequently observed allele (nMAJ and nMIN, respectively) for each breed pool (i.e. all eight samples for YNLC and all six samples for RJF were combined, respectively). For each window, we calculated Hp as follows [6]: Hp=2∑nMAJ∑nMIN∑nMAJ∑nMIN2. Subsequently, individual Hp values were Z-transformed as follows: ZHp=ZHp-μZHpσZHp. FST was calculated from the allele frequencies (not the allele counts) using the standard equation according to the principles of population genetics [19]: FST=Pi_total-Pi_withinPi_within, where Pi_within=Pi_population1+Pi_population2/2, and Pi=1-fA2-fT2-fC2-fG2 with fN being the frequency of nucleotide Ni.e.A,T,C or G,Pi_total is the total Pi for which allele frequencies in both populations are averages and Pi is calculated as above. The FST values were Z-transformed as follows: ZFST=FST-μFSTσFST, where μFST is the mean FST, and σFST is the standard deviation of FST [20]. Hp and FST were calculated by using our in-house script in Perl. The major challenge of such analyses is to exclude signals caused by demographic events and population structure. It is difficult to assign strict thresholds to distinguish selection and drift. We surveyed published literature and used an empirical procedure according to previous studies [21, 22]. Putatively selected regions were located in fully overlapping windows with an extremely low ZHp value (top 5 % level) and extremely high ZFST values (top 5 % level). Functional enrichment analysis The genes putatively under selection were submitted to g:profiler (http://biit.cs.ut.ee/gprofiler/. Version: r1488_e83_eg30.) for enrichment analysis of the Gene Ontology (GO) and KEGG pathways. All chicken genes that are annotated in Ensembl were used as the background set. Benjamini–Hochberg FDR (false discovery rate) was used for correcting the P values. Only terms with a P value <0.05 were considered as significant and listed. Results Detection of SNPs A total of 16.40 × 106 SNPs were identified from the genomes of 14 individuals, i.e. eight YNLC (13.15 × 106 SNPs) and six RJF individuals (13.87 × 106 SNPs) (see Additional file 2: Table S2). Most SNPs identified for the YNLC individuals were located in intergenic and intron regions (57.16 and 38.77 %, respectively); 1.36 % of these 13.15 × 106 SNPs were predicted to be within protein-coding regions and 0.40 % as amino acid altering mutations (non-synonymous and stop gain/loss); 1.30 % of the 13.15 × 106 SNPs were within 1-kb regions upstream or downstream of the transcription start or end sites, and thus may have a possible role in transcriptional regulation, with 510 SNPs of these residing within splice sites (Table 1; see Additional file 2: Table S2).Table 1 Summary and annotation of SNPs in YNLCa Categoryb YNLC Upstream 186,263 Exonic Stop gain 379 Stop loss 51 Synonymous 126,014 Non-synonymous 51,933 Intronic 5,098,263 Splicing 510 Downstream 163,867 Upstream/downstream 6747 Intergenic 7,515,849 aYNLC: Xishuangbanna fighting chicken bUpstream: a variant that is located in the 1-kb region upstream of the gene start site; stop gain: a non-synonymous (ns) SNP that leads to the creation of a stop codon at the variant site; stop loss: a non-synonymous SNP that leads to the elimination of a stop codon at the variant site; splicing: a variant within 2 bp of a splice junction; downstream: a variant that is located in the 1-kb region downstream of the gene end site; upstream/downstream: a variant that is located in the downstream and upstream regions of two genes Genome-wide selective sweep signals To detect selection signatures, we searched the genome of the YNLC chicken for regions with reduced Hp and increased genetic distances to the RJF genome (FST). Putatively selected genes were located by extracting windows that simultaneously presented extremely low ZHp (top 5 % level, ZHp=-1.75) and extremely high ZFST (top 5 % level, ZFST=1.82). A total of 413 candidate genes (Fig. 1 , Additional file 3: Table S3, Additional file 4: Figure S1) were identified in the YNLC genome, which should harbor genes that underwent selection for fighting aptitude. We compared our results with those previously reported by Rubin et al. [6] and detected 91 overlapping genes between the two studies (see Additional file 3: Table S3). We searched for significantly overrepresented GO terms and KEGG pathways among the candidate genes that are specific to YNLC. The most enriched clusters were related to immunity, disease resistance, organ development, response to stimulus, and metabolic processes (see Additional file 5: Table S4, Additional file 6: Table S5).Fig. 1 Distribution of ZHp and ZFST calculated for 100-kb windows sliding in 10-kb steps. Blue points identify Xishuangbanna game chicken (YNLC) genomic regions with both an extremely low ZHp value (top 5 % level) and an extremely high ZFST value (top 5 % level) Discussion Four hundred and thirteen genes were discovered in our study, of which 91 overlapped with those reported in [6] and among these, we identified several notable domestication-related genes i.e.: IGF1 (insulin-like growth factor 1), which encodes a peptide that has a similar molecular structure to that of insulin and is a candidate gene for avian growth [6]; BCO2 (β-carotene oxygenase 2), which is associated with yellow skin in domestic chickens [23]; and NELL1 (NEL-like 1) which is assumed to be related to skeletal integrity in chickens [24]. Positive selection on these genes in the YNLC was expected since domestic chickens collectively share morphology and physiology shifts that accompanied domestication [25]. Many genes that were putatively under selection and identified in our study were not reported by Rubin et al. [6]. Functional enrichment analysis of genes that are specific to the YNLC breed revealed that many candidate genes are related to immunity and disease resistance (see Additional file 5: Table S4), which may reflect artificial selection for individuals with improved innate immunity and disease resistance. Among the identified candidate genes, quite a few are involved in organ development (see Additional file 5: Table S4), e.g. CBFB (core-binding factor subunit beta) and GRHL3 (grainyhead-like 3), which are critical for growth and development of the craniofacial skeleton [26, 27]. These genes may explain why fighting chickens have a wider mandibular joint and frontal bone as compared to other breeds [28]. Many of the genes identified are related to limb development, i.e. Gli3 (transcriptional activator Gli3) and PTCH1 (patched 1), which are involved in the hedgehog (Hh) signal transduction pathway that controls the patterning, growth, morphogenesis and homeostasis of many tissues [29], such as digit patterning [30] and limb development [31]; EFNA5 (ephrin-A5), a GPI-anchored ephrin-Aligand that binds to the Eph receptors, is pivotal in cell migration in the avian forelimb [32]. Compared with other breeds, fighting chickens exhibit larger hindlimb and forelimb muscles, especially for triceps surae and biceps brachii [33], which may reflect adaptation to running and jumping that are essential traits in this breed. The triceps surae muscles assist in extending the foot joints, while the large triceps surae muscles allow fighting chickens to have a high level of jumping performance. The biceps brachii muscles facilitate strong flapping of the wings and act as powerful flexors of the elbow joint to support both jumping and hitting actions. In addition, fighting chickens have long legs, an extended hip joint, and a curved knee joint [33, 34], which indicate that they have adapted to running and upright posture. Fighting chickens are bred specifically for cockfighting and fighting cocks possess congenital aggression towards all males of the same species. Several of the identified genes are related to aggressive behavior (Table 2). For example, the brain-derived neurotrophic factor (BDNF) gene (Fig. 2), a member of the nerve growth factor gene family, plays a major role in neuronal growth, proliferation, differentiation and neuronal survival [35]. A mutation in the human BDNF gene has been reported to be correlated with aggressive behavior in humans [36]. Furthermore, BDNF loss-of-function mice have been used as a model to study animal aggression [37]. Another gene neurotensin/neuromedin N precursor (NTS) encodes a common precursor for neurotensin (NT) and neuromedin N (NN). NT is involved in interactions with dopamine [38] and corticotropin-releasing factor (CRF) signaling [39], two neurotransmitter systems known to modulate aggressive behavior [40, 41]. Furthermore, NT mRNA levels were shown to be significantly reduced in high maternal aggression mice [42].Table 2 Putative selected genes involved in aggressive behavior Gene ID Gene name References ENSGALG00000012163 BDNF [36, 37] ENSGALG00000027192 NTS [42] ENSGALG00000003163 GNAO1 [43] Fig. 2 Example of the BDNF gene (arrow) with selection signals in Xishuangbanna game chicken (YNLC). ZFST (blue) and ZHp (red) Cockfighting is a very toilsome and furious form of exercise. The ability to sustain and effectively allocate fuel substrates for oxidative metabolism is critical for cockfighting. Energy metabolism-related genes were found to be under selection in YNLC (see Additional file 5: Table S4). The RICTOR (RPTOR independent companion of MTOR complex 2) gene encodes an essential subunit of the target of the rapamycin (mTOR) complex (mTORC) 2. In fat cells, RICTOR/mTORC2 plays an important role in whole-body energy homeostasis [44]. The SDHB (succinate dehydrogenase (SDH) subunit B) gene encodes a crucial metabolic enzyme that is involved in the respiratory chain and Krebs cycle [45]. Positive selection of these genes may represent adaptation of the energy metabolism in fighting chickens. Conclusions In this work, we used two distinct methods to detect selection signatures across the genomes of YNLC and RJF chicken. Our analyses identified genes under positive selection in YNLC, which included genes related to aggressive behavior, immunity, energy metabolism and tissue and organ development. Our data will help improve our understanding of the mechanisms and identify the targets of artificial selection in fighting chickens and facilitate future quantitative trait loci (QTL) mapping. Additional files 10.1186/s12711-016-0239-4 Summary of the downloaded chicken genome re-sequencing data. Description: The table provides sequencing depth and accession numbers from the downloaded chicken genome. 10.1186/s12711-016-0239-4 Summary and annotation of SNPs in Xishuangbanna fighting chicken (YNLC) and Red Jungle Fowl (RJF). 10.1186/s12711-016-0239-4 Putatively selected genes (top 5 % level of ZHp and ZFST values) in the Xishuangbanna fighting chicken (YNLC). 10.1186/s12711-016-0239-4 Genome-wide distribution of ZHp and ZFST along chromosomes. This figure presents the putatively selected regions on YNLC chromosomes. 10.1186/s12711-016-0239-4 GO analysis for all genes under selection in YNLC. The table provides the significantly overrepresented gene ontology (GO) terms among putatively selected genes in YNLC. 10.1186/s12711-016-0239-4 KEGG analysis for all genes under selection in YNLC. The table provides the significantly enriched KEGG pathways among putatively selected genes in YNLC. Authors’ contributions XG, QF, CM, BZ and YW analysed data and performed bioinformatics. XG and RJ drafted the manuscript. All authors read and approved the final manuscript. Acknowledgements This work was supported by a grant from the National Natural Science Foundation of China (No. 31572395). Competing interests The authors declare that they have no competing interests. ==== Refs References 1. Komiyama T Iwama H Osada N Nakamura Y Kobayashi H Tateno Y Dopamine receptor genes and evolutionary differentiation in the domestication of fighting cocks and long-crowing chickens PLoS One 2014 9 e101778 10.1371/journal.pone.0101778 25078403 2. Zhu W Li H Song W Xu W Shu J Han W The genetic diversity and origin of Chinese game chicken Avian Biol Res 2009 2 197 202 10.3184/175815509X12564806862768 3. Kreitman M Methods to detect selection in populations with applications to the human Annu Rev Genom Hum Genet 2000 1 539 559 10.1146/annurev.genom.1.1.539 4. Tajima F Statistical method for testing the neutral mutation hypothesis by DNA polymorphism Genetics 1989 123 585 595 2513255 5. Voight BF Kudaravalli S Wen X Pritchard JK A map of recent positive selection in the human genome PLoS Biol 2006 4 e72 10.1371/journal.pbio.0040072 16494531 6. Rubin CJ Zody MC Eriksson J Meadows JRS Sherwood E Webster MT Whole-genome resequencing reveals loci under selection during chicken domestication Nature 2010 464 587 591 10.1038/nature08832 20220755 7. Wang GD Fan RX Zhai W Liu F Wang L Zhong L Genetic convergence in the adaptation of dogs and humans to the high-altitude environment of the Tibetan plateau Genome Biol Evol 2014 6 2122 2128 10.1093/gbe/evu162 25091388 8. Qanbari S Strom TM Haberer G Weigend S Gheyas AA Turner F A high resolution genome-wide scan for significant selective sweeps: an application to pooled sequence data in laying chickens PLoS One 2012 7 e49525 10.1371/journal.pone.0049525 23209582 9. Lewontin RC Krakauer J Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms Genetics 1973 74 175 195 4711903 10. Axelsson E Ratnakumar A Arendt ML Maqbool K Webster MT Perloski M The genomic signature of dog domestication reveals adaptation to a starch-rich diet Nature 2013 495 360 364 10.1038/nature11837 23354050 11. Yan YY Yi GQ Sun CQ Qu LJ Yang N Genome-wide characterization of insertion and deletion variation in chicken using next generation sequencing PLoS One 2014 9 e104652 10.1371/journal.pone.0104652 25133774 12. Wang MS Li Y Peng MS Zhong L Wang ZJ Li QY Genomic analyses reveal potential independent adaptation to high altitude in Tibetan chickens Mol Biol Evol 2015 32 1880 1889 10.1093/molbev/msv071 25788450 13. Qiu Q Wang LZ Wang K Yang YZ Ma T Wang ZF Yak whole-genome resequencing reveals domestication signatures and prehistoric population expansions Nat Commun 2015 6 10283 10.1038/ncomms10283 26691338 14. Chen C Liu ZG Pan Q Chen X Wang HH Guo HK Genomic analyses reveal demographic history and temperate adaptation of the newly discovered honey bee subspecies Apis mellifera sinisxinyuan n. ssp Mol Biol Evol 2016 33 1337 1348 10.1093/molbev/msw017 26823447 15. Li MZ Tian SL Yeung CKL Meng XH Tang QZ Niu LL Whole-genome sequencing of Berkshire (European native pig) provides insights into its origin and domestication Sci Rep 2014 4 4678 24728479 16. Li H Durbin R Fast and accurate short read alignment with burrows–wheeler transform Bioinformatics 2009 25 1754 1760 10.1093/bioinformatics/btp324 19451168 17. Li H Handsaker B Wysoker A Fennell T Ruan J Homer N The sequence alignment/map format and SAMtools Bioinformatics 2009 25 2078 2079 10.1093/bioinformatics/btp352 19505943 18. Wang K Li MY Hakonarson H ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data Nucleic Acids Res 2010 38 e164 10.1093/nar/gkq603 20601685 19. Hartl DL Clark AG Principles of population genetics 2007 4 Sunderland Sinauer Associates 20. Karlsson EK Baranowska I Wade CM Salmon Hillbertz NHC Zody MC Anderson N Efficient mapping of mendelian traits in dogs through genome-wide association Nat Genet 2007 39 1321 1328 10.1038/ng.2007.10 17906626 21. Li M Tian S Jin L Zhou G Li Y Zhang Y Genomic analyses identify distinct patterns of selection in domesticated pigs and Tibetan wild boars Nat Genet 2013 45 1431 1438 10.1038/ng.2811 24162736 22. Qu Y Tian SL Han NJ Zhao HW Gao B Fu J Genetic responses to seasonal variation in altitudinal stress: whole-genome resequencing of great tit in eastern Himalayas Sci Rep 2015 5 14256 10.1038/srep14256 26404527 23. Eriksson J Larson G Gunnarsson U Bed’hom B Tixier-Boichard M Stromstedt L Identification of the yellow skin gene reveals a hybrid origin of the domestic chicken PLoS Genet 2008 4 e1000010 10.1371/journal.pgen.1000010 18454198 24. Elferink MG Megens HJ Vereijken A Hu X Crooijmans RPMA Groenen MAM Signatures of selection in the genomes of commercial and non-commercial chicken breeds PLoS One 2012 7 e32720 10.1371/journal.pone.0032720 22384281 25. Wang MS Zhang RW Su LY Li Y Peng MS Liu HQ Positive selection rather than relaxation of functional constraint drives the evolution of vision during chicken domestication Cell Res 2016 26 556 573 10.1038/cr.2016.44 27033669 26. Kundu M Javed A Jeon JP Horner A Shum L Eckhaus M Cbf beta interacts with Runx2 and has a critical role in bone development Nat Genet 2002 32 639 644 10.1038/ng1050 12434156 27. Dworkin S Simkin J Darido C Partridge DD Georgy SR Caddy J Grainyhead-like 3 regulation of endothelin-1 in the pharyngeal endoderm is critical for growth and development of the craniofacial skeleton Mech Dev 2014 133 77 90 10.1016/j.mod.2014.05.005 24915580 28. Kudo K Tsunekawa N Ogawa H Endo H Comparative functional morphology of skulls among Japanese breeds of domestic fowls J Poult Sci 2016 53 43 50 10.2141/jpsa.0150055 29. Ingham PW McMahon AP Hedgehog signaling in animal development: paradigms and principles Genes Dev 2001 15 3059 3087 10.1101/gad.938601 11731473 30. Litingtung Y Dahn RD Li YN Fallon JF Chiang C Shh and Gli3 are dispensable for limb skeleton formation but regulate digit number and identity Nature 2002 418 979 983 10.1038/nature01033 12198547 31. Büscher D Bosse B Heymer J Rüther U Evidence for genetic control of Sonic hedgehog by Gli3 in mouse limb development Mech Dev 1997 62 175 182 10.1016/S0925-4773(97)00656-4 9152009 32. Swartz ME Eberhart J Pasquale EB Krull CE EphA4/ephrin-A5 interactions in muscle precursor cell migration in the avian forelimb Development 2001 128 4669 4680 11731448 33. Endo H Mori K Hosojima M Mekwichai W Ogawa H Tsunekawa N Functional-morphological characteristics in the musculoskeletal system of standing-type cocks Including some game breeds Jpn J Zoo Wildl Med 2012 17 131 138 10.5686/jjzwm.17.131 34. Vasinopas L Meckvichai W The difference of morphological characteristics between fighting and meat type Thai native chickens Khon Kaen Agr J 2015 43 70 73 35. Zhou J Bradford HF Stern GM The stimulatory effect of brain-derived neurotrophic factor on dopaminergic phenotype expression of embryonic rat cortical neurons in vitro Brain Res Dev Brain Res 1994 81 318 324 10.1016/0165-3806(94)90318-2 7813052 36. Spalletta G Morris DW Angelucci F Rubino IA Spoletini I Bria P BDNF Val66Met polymorphism is associated with aggressive behavior in schizophrenia Eur Psychiatry 2010 25 311 313 10.1016/j.eurpsy.2009.10.008 20430595 37. Ito W Chehab M Thakur S Li J Morozov A BDNF -restricted knockout mice as an animal model for aggression Genes Brain Behav 2011 10 365 374 10.1111/j.1601-183X.2010.00676.x 21255268 38. Cáceda R Kinkead B Nemeroff CB Neurotensin: role in psychiatric and neurological diseases Peptides 2006 27 2385 2404 10.1016/j.peptides.2006.04.024 16891042 39. Rowe W Viau V Meaney MJ Quirion R Stimulation of CRH-mediated ACTH secretion by central administration of neurotensin: evidence for the participation of the paraventricular nucleus J Neuroendocrinol 1995 7 109 117 10.1111/j.1365-2826.1995.tb00673.x 7767323 40. Gammie SC Negron A Newman SM Rhodes JS Corticotropin-releasing factor inhibits maternal aggression in mice Behav Neurosci 2004 118 805 814 10.1037/0735-7044.118.4.805 15301606 41. Ricci LA Schwartzer JJ Melloni RH Jr Alterations in the anterior hypothalamic dopamine system in aggressive adolescent AAS-treated hamsters Horm Behav 2009 55 348 355 10.1016/j.yhbeh.2008.10.011 19014946 42. Gammie SC Auger AP Jessen HM Vanzo RJ Awad TA Stevenson SA Altered gene expression in mice selected for high maternal aggression Genes Brain Behav 2007 6 432 443 10.1111/j.1601-183X.2006.00271.x 16939635 43. Chamero P Katsoulidou V Hendrix P Bufe B Roberts R Matsunami H G protein Gαo is essential for vomeronasal function and aggressive behavior in mice Proc Natl Acad Sci USA 2011 108 12898 12903 10.1073/pnas.1107770108 21768373 44. Kumar A Lawrence JC Jung DY Ko HJ Keller SR Kim JK Fat cell–specific ablation of rictor in mice impairs insulin-regulated fat cell and whole-body glucose and lipid metabolism Diabetes 2010 59 1397 1406 10.2337/db09-1061 20332342 45. Ackrell BAC Cytopathies involving mitochondrial complex II Mol Asp Med 2002 23 369 384 10.1016/S0098-2997(02)00012-2

PMC005xxxxxx/PMC5000500.txt

==== Front J Cardiothorac SurgJ Cardiothorac SurgJournal of Cardiothoracic Surgery1749-8090BioMed Central London 53510.1186/s13019-016-0535-7Research ArticleMidterm outcome after surgical correction of anomalous left coronary artery from the pulmonary artery Ling Yunfei 1Bhushan Sandeep 1Fan Qiang 1http://orcid.org/0000-0002-9636-5965Tang Menglin + 86 28 85422897zjmtg2014@126.com 21 Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan People’s Republic of China 2 Department of Intensive Care Unit, West China Hospital, Sichuan University, No. 37 GuoXue Xiang, Chengdu, Sichuan 610041 People’s Republic of China 26 8 2016 26 8 2016 2016 11 1 13719 4 2016 23 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background This study was undertaken to determine the midterm outcome in patients with anomalous left coronary artery from the pulmonary artery (ALCAPA) undergoing coronary reimplantation and Takeuchi repair. Methods A retrospective review of patients who had ALCAPA repair between January 2009 and December 2015. Mortality, echocardiography assessment of left ventricular function including ejection fractionand, shortening fraction, severity of mitral regurgitation, stenosis of the coronary ostium were studied retrospectively. Results Sixteen patients were described. The mean age at the time of surgery was 22.5 ± 10.3 years (range, 9 months-35.6 years) and 2 patients were younger than 1 year old, Surgical interventions included left coronary artery reimplantation in 13 patients (81 %) and Takeuchi repair in 3 (19 %). Concomitant mitral valve repair was performed in 2 cases, no cases required mechanical circulatory support postoperatively. There was no mortality. At median follow-up of 4.6 years, EF improved from 33.2 % ±6.8 % to 60.9 % ± 8.1 % (p <0.05), mean SF from 28.5 % ± 12.1 % to 40.2 % ± 5.4 % (p <0.05). Only one patient was with moderate mitral regurgitation. All 16 cases had normal ejection fraction and shortening fraction without stenosis of the coronary ostium at last follow-up. Conclusions Early establishment of a 2-coronary artery achieved excellent outcomes without morbidity and mechanical circulatory support. Normal ejection fraction and shortening fraction recovered smoothly. There is no stenosis of the coronary ostium at the midterm follow-up. Keywords Anomalous coronary artery from pulmonary arteryOutcomeSurgical correctionCoronary artery reimplantationissue-copyright-statement© The Author(s) 2016 ==== Body Background Anomalous left coronary artery from the pulmonary artery (ALCAPA), also known as Bland-White-Garland syndrome, is a rare congenital abnormality that affects 1 of every 300,000 live births and accounts for 0.25 %– 0.5 % of all congenital heart defects [1, 2]. There are two types of ALCAPA: the infant type and the adult type, each of which has different manifestations and outcomes. If left untreated, about 90 % of patients of infant type die within the 1st year of life [3]. However, some adult type patients do not present with symptoms until later in life. These older patients often manifest their anomalies as mitral regurgitation (MR), ischemic cardiomyopathy, malignant dysrhythmias, or even sudden death [4, 5]. So a diagnosis of ALCAPA indicates immediate surgical intervention regardless of the age level except for the newborn.Fig. 1 ALCAPA in an infant: TTE showed the LCA originating from the pulmonary artery Fig. 2 ALCAPA in an adult before the surgery: Coronariograms revealed a tortuous and dilated RCA as well as an equally tortuous and dilated LCA and well-established collateral vessels between LCA and RCA Fig. 3 After the surgical correction of ALCAPA. Coronariograms revealed LCA arising from the AAO and well-established collateral vessels between LCA and RCA Multiple techniques have been introduced to establish a 2-coronary artery system artery, including coronary artery bypass grafting, coronary baffling procedures, and direct reimplantation of the left coronary artery (LCA) to the aorta. Although early diagnosis and prompt surgical intervention lead to excellent results, the possibility of postoperative complications such as persistent MR, late-onset congestive heart failure, and arterial stenosis necessitates long term follow-up. We herein present 16 patients with ALCAPA and discuss the midterm outcome in patients with ALCAPA undergoing a primary LCA reimplantation and Takeuchi repair. Methods Patients A retrospective review of charts for patients who underwent surgery for ALCAPA at West China Hospital from January 2009 and December 2015 was performed. Patients whose primary ALCAPA repair was performed at another hospital or whose ALCAPA repair was not the primary operation were excluded. Date included patient demographics, preoperative clinical data, early and late complications, reoperations, and clinical assessment at most recent cardiology follow-up were obtained from electronic medical records and archived paper charts. Demographic information including age, weight, and BSA were recorded. Operative variables analyzed include mitral valve intervention, duration of mechanical ventilation, duration of intensive care unit and hospital stay and postoperative complications. Ventricular function was assessed by standard echocardiographic methods: ejection fraction (EF) and shortening fraction (SF) on most recent transthoracic echocardiogram. Degree of MR was assessed by qualified and experienced echocardiographic reviewers as none (or trivial), mild, moderate, or severe. Stenosis of coronary ostium was determined by color doppler echocardiography, CT scan or coronary angiogram. Surgical technique Takeuchi repair: After initiation of cardiopulmonary bypass and cardiac arrest, a pulmonary arteriotomy was performed, creating a transverse flap of pulmonary artery tissue. An aortopulmonary window was created, and the pulmonary artery flap was used to baffle the left coronary artery into the aorta. The pulmonary artery was then reconstructed with autologous pericardium [5–7]. LCA reimplantation: To the patients with the origin of the LCA close to the ascending aorta. After standard cardiopulmonary bypass and institution of cardioplegia, the left coronary artery was harvested with a large button of pulmonary arterial wall and widely mobilized without injuring any branches. After inspection of the aortic valve (usually through a separate aortotomy), an aortic flap was performed to minimize torsion of the vessel. The coronary button was anastomosed to the aortic wall with fine polypropylene suture. The pulmonary arterial trunk was reconstructed with a patch of autologous pericardium. However, to the patients with the origin of the LCA far away from the aortic root the coronary ostium was excised along with a strip of the pulmonary artery wall. Autologous pericardium was used to reconstruct the posterior wall of this “elongated” coronary artery and the neo-ostium was then anastomosed end-to-side with the ascending aorta [5, 8, 9]. Statistically analysis Continuous variables were reported as medians with minimum and maximum or means with standard deviations. Categoric variables were reported as frequencies with percentages. Independent continuous variables were compared by unpaired Student’s t test for normally distributed data, and Mann–Whitney U-test was used for the comparison of parameters that did not exhibit a normal distribution. Two-tailed p value less than 0.05 was considered statistically significant. Results Perioperative data and postoperative course A total of 16 patients (62.5 % female) were identified with the diagnosis of ALCAPA (Figs. 1 and 2) and LCA reimplantation was performed in 13 patients (81 %), 3 patients (19 %) was underwent Takeuchi repair. Median age at time of repair was 22.5 ± 10.3 years (range, 9 months-35.6 years) and 2 patients were younger than 1 year old. 2 patients (12.5 %) were associated severe MR, 10 patients (62.5 %) with mild or moderate MR and 4 patients (25 %) without MR. Concomitant mitral valve repair was performed in 2 of 16 patients with significant (severe) preoperative MR. Of the 10 patients with mild or moderate MR who did not undergo surgical intervention for MR, Only 1 patient continued to have moderate MR at 3-year follow-up. No patient required mechanical circulatory support preoperatively or postoperatively (Table 1).Table 1 Characteristics of patients who underwent surgical repair of ALCAPA Characteristics N = 16 Age, years 22.3 (9 months-35.6 years)  >5 year-old 3 (18.76)  <5 year-old 13 (81.25) Male 6 (37.5) Body surface area 0.9 (0.72–1.56) Surgery type  Reimplantation 13 (81.25)  Takeuchi repair 3 (18.75) MR  Severe 2 (12.5)  Mild or moderate 10 (62.5)  None 4 (25) Cardiopulmonary bypass time, minutes 154 ± 43 Aortic cross-clamp time, minutes 86 ± 37 Outcomes of ALCAPA repair at follow-up Median follow-up time was 4.6 years (range, 1 to 6). Cardiovascular complications at follow-up occurred in 2 patients (%), Right bundle branch block in 1 patient (9 %) and the other who accepted Takeuchi repair was with mild supravalvular pulmonary stenosis which requires further follow-up. There was no death or important morbidities and no stenosis of the coronary ostium (Fig. 3). During the last follow up, only 1patient was associated with moderate MR, The rest were with mild or none MR (Table 2). EF improved from 33.2 % ±6.8 % to 60.9 % ± 8.1 % (p <0.05), mean SF from 28.5 % ± 12.1 % to 40.2 % ± 5.4 % (p <0.05).Table 2 Middle outcomes of patients who underwent repair of ALCAPA Outcomes n = 16 (%) Mechanical ventilation, days 3 (1–10) ICU length of stay, days 5.4 (2–12) Hospital length of stay, days 14.6 (11–23) Cardiovascular complications  Arrhythmias 1 (6.25)  Supravalvular pulmonary stenosis 1 (6.25) MR at follow-up  Severe 0 (0)  Moderate 1 (6.25)  None or mild 15 (93.75) Discussion The origin of the LCA from the pulmonary artery is well tolerated in fetal and early neonatal life because pulmonary arterial pressure is same as systemic pressure, which leads to antegrade flow in both the anomalous LCA and the normal right coronary artery RCA. Soon after birth, when pulmonary arterial pressure decreases, flow in the LCA decreases and then reverses, which leads to myocardial ischemia and infarction [10, 11]. The extent of myocardial necrosis of the left ventricle is determined by the balance between timing of closure of the ductus arteriosus, changes in pulmonary vascular resistance, and speed of development of preexisting collateral circulation between the right and left coronary arteries [12]. Our study demonstrates that excellent early and midterm outcomes with no mortality can be obtained with the contemporary repair of ALCAPA in the majority of patients. Normal systolic function and shortening fraction is recoverable in most patients after establishment of a 2-coronary artery system with a low incidence of reoperations. Intervening on the mitral valve during the initial surgical repair of ALCAPA remains controversial [13, 14]. Mitral valve intervention was performed in only 2 patients with severe MR, and no other patient has required MR intervention during the surgical repair of ALCAPA. In general, mitral valve repair or replacement is not necessary at the time of ALCAPA repair, especially in the patients younger than 1 year old, but if MR remains persistent, and depending on the severity, it can be managed surgically at a later date and mitral valvuloplasty was preferred [15, 16]. The degree of MR tends to improve with the majority of patients after surgical repair of ALCAPA [17]. The most popular surgical methods are creation of a two-coronary artery system via LCA ligation plus CABG, Takeuchi operation, and LCA reimplantation. Simple ligation of the ACAPA plus CABG, resulting in a single coronary artery system, has been abandoned because of subendocardial ischemia, angina, and sudden death during the follow up [1, 18]. The Takeuchi operation can be adopted when a distance exists between the LCA ostium and the aorta. Its major complications are supravalvular pulmonary stenosis, aortic valve insufficiency, baffle obstruction, and leaks [19]. Most cardiac surgeons prefer to reimplant the anomalous LCA directly onto the aorta and we have modified our technique by using the autologous pericardium to reconstruct the posterior wall of this “elongated” coronary artery and the neo-ostium was then anastomosed end-to-side with the ascending aorta. In our series, 3 patients survived Takeuchi operation and one experienced supravalvular pulmonary stenosis, 13 patients undergoing coronary translocation and achieved excellent results. Conclusions In conclusion, we have achieved excellent outcomes of ALCAPA repaired by the establishment of a two-coronary system by coronary artery reimplantation and Takeuchi repair. Reintervention after ALCAPA repair is rare. Most patients with ALCAPA will have some degree of MR. However, even without intervention upon the mitral valve at time of ALCAPA repair, the regurgitation tends to improve with the majority of patients. Normal EF and SF recovered smoothly. There is no stenosis of the coronary ostium at the midterm follow-up. Abbreviations ALCAPAAnomalous left coronary artery from the pulmonary artery EFEjection fraction LCALeft coronary artery MRMitral regurgitation RCARight coronary artery SFShortening fraction Acknowledgements Not applicable Funding Not applicable Availability of data and materials The datasets during and/or analysed during the current study available from the corresponding author on reasonable request. Authors’ contributions YL collected clinical materials of these patients, participated in the design of the study and performed the statistical analysis, and drafted the manuscript. SB and QF participated in the study design, data analysis and study coordination. MT and YL participated in the design of the study and supervised the trial process. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Written informed consent was obtained from the patients for publication of this study. Copies of the written consent are available for review by the Editor-in-Chief of this journal. Ethics approval and consent to participate The ethics committee of West china hospital had approved the study. ==== Refs References 1. Dodge-Khatami A Mavroudis C Backer CL Anomalous origin of the left coronary artery from the pulmonary artery: collective review of surgical therapy Ann Thorac Surg 2002 74 3 946 955 10.1016/S0003-4975(02)03633-0 12238882 2. Wu QY Xu ZH Surgical treatment of anomalous origin of coronary artery from the pulmonary artery Chin Med J 2008 121 8 721 724 18701026 3. Erdinc M Hosgor K Karahan O Repair of anomalous origin of the left coronary artery arising from right pulmonary artery with rolled-conduitextended reimplantation in an adult J Card Surg 2011 26 6 604 607 10.1111/j.1540-8191.2011.01337.x 22017250 4. Peña E Nguyen ET Merchant N Dennie C ALCAPA Syndrome: not just a pediatric disease 1 Radiographics 2009 29 2 553 565 10.1148/rg.292085059 19325065 5. Cabrera AG Chen DW Pignatelli RH Khan MS Jeewa A Mery CM Outcomes of anomalous left coronary artery from pulmonary artery repair: beyond normal function Ann Thorac Surg 2015 99 4 1342 1347 10.1016/j.athoracsur.2014.12.035 25725925 6. Ginde S Earing MG Bartz PJ Cava JR Tweddell JS Late complications after takeuchi repair of anomalous left coronary artery from the pulmonary artery: case series and review of literature Pediatr Cardiol 2012 33 7 1115 1123 10.1007/s00246-012-0260-5 22438016 7. Lange R Vogt M Horer J Cleuziou J Menzel A Holper K Long-term results of repair of anomalous origin of the left coronary artery from the pulmonary artery Ann Thorac Surg 2007 83 4 1463 1471 10.1016/j.athoracsur.2006.11.005 17383358 8. Sfyridis PG Lytrivi ID Kirvassilis GV Papagiannis JK Michalis LK Sarris GE Anterior aortic reimplantation of anomalous left coronary artery from the pulmonary artery (ALCAPA) Originating from the nonfacing sinus in an adult J Card Surg 2010 25 2 214 217 10.1111/j.1540-8191.2009.00967.x 20039983 9. Dionne PO Poirier N Forcillo J Stevens LM Chartrand-Lefebvre C Mansour S A rare case of anomalous origin of the left main coronary artery in an adult patient J Cardiothorac Surg 2013 8 1 15 10.1186/1749-8090-8-15 23336304 10. Rajbanshi BG Burkhart HM Schaff HV Daly RC Phillips SD Dearani JA Surgical strategies for anomalous origin of coronary artery from pulmonary artery in adults J Thorac Cardiovasc Surg 2014 148 1 220 224 10.1016/j.jtcvs.2013.08.026 24079879 11. Zheng J Ding W Xiao Y Jin M Zhang G Cheng P Anomalous origin of the left coronary artery from the pulmonary artery in children: 15 years experience Pediatr Cardiol 2011 32 1 24 31 10.1007/s00246-010-9798-2 20976445 12. Vinereanu D Ionescu AA Fraser AG Assessment of left ventricular long axis contraction can detect early myocardial dysfunction in asymptomatic patients with severe aortic regurgitation Heart 2001 85 1 30 36 10.1136/heart.85.1.30 11119457 13. Weigand J Marshall CD Bacha EA Chen JM Richmond ME Repair of anomalous left coronary artery from the pulmonary artery in the modern era: preoperative predictors of immediate postoperative outcomes and long term cardiac follow-up Pediatr Cardiol 2015 36 3 489 497 10.1007/s00246-014-1038-8 25301273 14. Alexi-Meskishvili V Nasseri BA Nordmeyer S Schmitt B Weng YG Böttcher W Repair of anomalous origin of the left coronary artery from the pulmonary artery in infants and children J Thorac Cardiovasc Surg 2011 142 4 868 874 10.1016/j.jtcvs.2011.04.006 21665229 15. Brown JW Ruzmetov M Parent JJ Rodefeld MD Turrentine MW Does the degree of preoperative mitral regurgitation predict survival or the need for mitral valve repair or replacement in patients with anomalous origin of the left coronary artery from the pulmonary artery? J Thorac Cardiovasc Surg 2008 136 743 748 10.1016/j.jtcvs.2007.12.065 18805280 16. Singh TP Di Carli MF Sullivan NM Leonen MF Morrow WR Myocardial flow reserve in long-term survivors of repair of anomalous left coronary artery from pulmonary artery JACC 1998 31 2 437 443 10.1016/S0735-1097(97)00488-9 9462590 17. Huddleston CB Balzer DT Mendeloff EN Repair of anomalous left main coronary artery arising from the pulmonary artery in infants: long-term impact on the mitral valve Ann Thorac Surg 2011 71 1985 1989 10.1016/S0003-4975(01)02518-8 11426779 18. Kececioglu D Voth E Morguet A Munz DL Vogt J Myocardial ischemia and leftventricular function after ligation of left coronary artery (Bland-White-Garland syndrome): a long-term follow-up Thorac Cardiovasc Surg 1992 40 283 287 10.1055/s-2007-1020165 1485318 19. Bunton R Jonas RA Lang P Rein AJ Castaneda AR Anomalous origin of left coronary artery from pulmonary artery:ligation versus establishment of a two coronary artery system J Thorac Cardiovasc Surg 1987 93 103 108 3796022

PMC005xxxxxx/PMC5000501.txt

==== Front BMC CancerBMC CancerBMC Cancer1471-2407BioMed Central London 271610.1186/s12885-016-2716-0Research ArticleMicroRNA-21 regulates prostaglandin E2 signaling pathway by targeting 15-hydroxyprostaglandin dehydrogenase in tongue squamous cell carcinoma He Qianting qiantinghe@hotmail.com 12Chen Zujian zujianchen@hotmail.com 1Dong Qian dongqian1783@126.com 2Zhang Leitao justinleitao@hotmail.com 13Chen Dan prof.dan.chen@gmail.com 12Patel Aditi apate231@uic.edu 1Koya Ajay koya2@uic.edu 1Luan Xianghong luan@uic.edu 4Cabay Robert J. rcabay1@uic.edu 5Dai Yang yangdai@uic.edu 67Wang Anxun anxunwang@yahoo.com 2Zhou Xiaofeng xfzhou@uic.edu 1781 Center for Molecular Biology of Oral Diseases, Department of Periodontics, College of Dentistry, University of Illinois at Chicago, Chicago, IL USA 2 Department of Oral and Maxillofacial Surgery, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China 3 Department of Oral and Maxillofacial Surgery, Nan Fang Hospital, Southern Medical University, Guangzhou, China 4 Department of Oral Biology, College of Dentistry, University of Illinois at Chicago, Chicago, IL USA 5 Department of Pathology, College of Medicine, University of Illinois at Chicago, Chicago, IL USA 6 Department of Bioengineering, College of Engineering, University of Illinois at Chicago, Chicago, IL USA 7 UIC Cancer Center, Graduate College, University of Illinois at Chicago, Chicago, IL USA 8 Guanghua School and Research Institute of Stomatology, Sun Yat-sen University, Guangzhou, China 25 8 2016 25 8 2016 2016 16 1 68514 3 2016 11 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Oral tongue squamous cell carcinoma (OTSCC) is one of the most aggressive forms of head and neck/oral cancer (HNOC), and is a complex disease with extensive genetic and epigenetic defects, including microRNA deregulation. Identifying the deregulation of microRNA-mRNA regulatory modules (MRMs) is crucial for understanding the role of microRNA in OTSCC. Methods A comprehensive bioinformatics analysis was performed to identify MRMs in HNOC by examining the correlation among differentially expressed microRNA and mRNA profiling datasets and integrating with 12 different sequence-based microRNA target prediction algorithms. Confirmation experiments were performed to further assess the correlation among MRMs using OTSCC patient samples and HNOC cell lines. Functional analyses were performed to validate one of the identified MRMs: miR-21-15-Hydroxyprostaglandin Dehydrogenase (HPGD) regulatory module. Results Our bioinformatics analysis revealed 53 MRMs that are deregulated in HNOC. Four high confidence MRMs were further defined by confirmation experiments using OTSCC patient samples and HNOC cell lines, including miR-21-HPGD regulatory module. HPGD is a known anti-tumorigenic effecter, and it regulates the tumorigenic actions of Prostaglandin E2 (PGE2) by converts PGE2 to its biologically inactive metabolite. Ectopic transfection of miR-21 reduced the expression of HPGD in OTSCC cell lines, and the direct targeting of the miR-21 to the HPGD mRNA was confirmed using a luciferase reporter gene assay. The PGE2-mediated upregulation of miR-21 was also confirmed which suggested the existence of a positive feed-forward loop that involves miR-21, HPGD and PGE2 in OTSCC cells that contribute to tumorigenesis. Conclusions We identified a number of high-confidence MRMs in OTSCC, including miR-21-HPGD regulatory module, which may play an important role in the miR-21-HPGD-PGE2 feed-forward loop that contributes to tumorigenesis. Electronic supplementary material The online version of this article (doi:10.1186/s12885-016-2716-0) contains supplementary material, which is available to authorized users. Keywords microRNAmicroRNA-mRNA regulatory modulemiR-21HPGDPGE2http://dx.doi.org/10.13039/100000054National Cancer InstituteCA139596CA171436Zhou Xiaofeng http://dx.doi.org/10.13039/100001299Prevent Cancer FoundationLilly USA Research Award in Cancer Prevention and Early DetectionZhou Xiaofeng UIC College of DentistryCMBOD Oral Cancer Research Program - seed grantZhou Xiaofeng National Nature Science Foundation of ChinaNSFC81472523Wang Anxun National Nature Science Foundation of China NSFC81272953Wang Anxun http://dx.doi.org/10.13039/100000072National Institute of Dental and Craniofacial ResearchDE025926Zhou Xiaofeng issue-copyright-statement© The Author(s) 2016 ==== Body Background Head and neck/oral cancer (HNOC) is a commonly encountered malignancy. Head and neck squamous cell carcinoma (HNSCC), which arises from the epithelium lining of this region, makes up the majority (over 90 %) of HNOC. Oral tongue squamous cell carcinoma (OTSCC) is one of the most aggressive form of HNSCCs, which exhibits a propensity for rapid local invasion and spread [1], has a distinct nodal metastasis pattern [2, 3]. OTSCC patients also suffer from a high recurrence rate [4]. OTSCC is a complex disease with extensive genetic and epigenetic defects, including microRNA deregulation. MicroRNAs are pivotal regulators of physiological and disease processes through their control of diverse cellular processes. Several microRNAs have been functionally classified as oncogenes or tumor suppressors, and the aberrant expression of microRNA has been observed in almost all cancer types including OTSCC [5–8]. Deregulation of these cancer-associated microRNAs can significantly impact tumor initiation and progression by activating pathways promoting uncontrolled proliferation, favoring survival, inhibiting differentiation, and promoting invasion [9, 10]. MicroRNAs are not directly involved in protein coding, but are able to control the expression of their target genes at post-transcriptional levels by facilitating mRNA degradation and/or repressing translation. As such, the identification and detection of functional microRNA-mRNA regulatory modules (MRMs) are crucial components for understanding of microRNA functions. MicroRNAs are a class of small non-coding RNAs of approximately 22 nucleotides in length that are endogenously expressed in mammalian cells. They are related to, but distinct from, siRNAs. A key difference between siRNA and microRNA is that siRNA requires almost complete complementary to its targeting sequence for it to exert the silencing function, whereas microRNA usually binds to its target genes through partial complementary. While numerous sequence-based bioinformatics methods for microRNA target prediction have been developed, these methods often lead to high false discovery rates [11]. In order to minimize false positives and to detect the functional microRNA targets under a specific biological condition, recent approaches often integrate the microRNA and mRNA profiling analysis in conjunction with the sequence-based target prediction. Two types of experiments are common: 1) differential mRNA profiling experiment on a microRNA transfected cell line and its negative control, and 2) simultaneous microRNA and mRNA profiling analysis on samples of different phenotypes (e.g., normal vs. tumor). The first approach has been used by many groups, including us, to define the functional microRNA targets when a specific microRNA is over- or under- expressed [12–14]. The second approach aims to discover microRNA with altered expression related to different phenotypes and to uncover their targets mRNAs. This approach is based on the simple principle that inverse relationships in their expression profiles should be held between a specific microRNA and its functional target genes. When integrated with the sequence-based bioinformatics target prediction, this approach is believed to lead to the identification of high confidence microRNA targets. Our group and several others have recently undertaken extensive RNA-based surveys to identify gene expression and microRNA abnormalities in OTSCC. In this study, we utilized our existing transcription profiling dataset [15], and a meta-analysis of 13 published microRNA profiling studies [16], and integrate them with a collection of 12 sequence-based bioinformatics tools to define the deregulation of functional MRMs in OTSCC. We then evaluated these MRMs in 2 OTSCC patient cohorts and a panel of HNSCC cell lines. With our comprehensive approach, we identified a panel of high confidence microRNA-mRNA regulatory modules in OTSCC, including miR-21-15-Hydroxyprostaglandin Dehydrogenase (HPGD) regulatory module. We also confirmed the positive feed-forward loop that involves miR-21, HPGD and Prostaglandin E2 (PGE2) in HNOC cells that contribute to tumorigenesis. Methods MicroRNA target prediction The microRNA target prediction was performed using the comparative analysis function of the miRWalk [17], which contains a collection of 10 bioinformatics tools, including DIANAmT, miRanda, miRDB, miRWalk, RNAhybrid, PicTar (4-way), PicTar (5-way), PITA, RNA22, TargetScan5.1. In addition, MicroCosm 5.0 and TargetScanHuman 6.2 were also used for predicting the microRNA targets. For our study, genes that were predicted by at least one method were defined as candidate microRNA targets. The base-pairing and the minimum free energy (mfe) for the binding of microRNA to its targeting sequences were predicted using the RNAhybrid program [18]. Cell Culture, transfection and function assays The human HNSCC cell lines (1386Ln [19], 1386Tu [19], 686Ln [20], 686Tu [20], CAL27 [21], SCC2 [22], SCC4 [22], SCC9 [23], SCC15 [23], SCC25 [23], Tca8113 [24], UM1 [25], UM2 [25]) were maintained in DMEM/F12 medium (Gibco) supplemented with 10% FBS, 100 units/ml penicillin, and 100 μg/ml streptomycin (Invitrogen). All cells were maintained in a humidified incubator containing 5 % CO2 at 37 °C. For functional analysis, hsa-miR-21 and non-targeting microRNA mimic (Dharmacon), and gene specific siRNAs for COX2 and HPGD (Santa Cruz Biotechnology) were transfected into the cells using DharmaFECT Transfection Reagent 1 as described previously [26, 27]. For PGE2 treatment, 20 μM of PGE2 or vehicle (DMSO) was added to the cells and incubated for 24 h. For CelecoxiB treatment, 10 μM of CelecoxiB or vehicle (DMSO) was added to the cells and incubated for 24 h. Cell proliferation was measured by MTT assay as described previously [28]. Clinical samples from OTSCC patients We downloaded the RNASeq and miRNASeq profiling datasets on 12 OTSCC and paired normal tissue samples from The Cancer Genome Atlas (TCGA) Data Protal [tcga-data.nci.nih.gov]. The gene expression values were extracted as normalized count, and the microRNA levels were extracted as reads per million miRNA mapped from the datasets. The demographics of the patients were as follows: 6 male, 6 female and average age = 62 (range: 36–88), 1 stage T1 cases, 5 stage T2 cases, 3 stage T3 case and 3 T4 cases. Oral cytology samples were obtained from 13 patients with pathologically characterized primary OSCC of the tongue before tumor resection (including 6 stage T1 cases 6 stage T2 cases and 1 stage T3 case) as previously described [29, 30]. These procedures are in compliance with the Helsinki Declaration, and was approved by the Ethical Committee of the First Affiliated Hospital, Sun Yat-Sen University (reference number: 2014-C-001). The informed consent was obtained from participants. Patients were excluded if there is a history of lung carcinoma or HNSCC elsewhere and may represent metastatic disease. The demographics of the patients were as follows: 8 male, 5 female and average age = 51.8 (range: 32–78). The total RNA was isolated using miRNeasy Mini kit (Qiagen), and quantified by a spectrophotometer or the RiboGreen RNA Quantitation Reagent (Molecular Probes). Quantitative RT-PCR Analysis The relative microRNA levels were determined by TaqMan microRNA assays (Applied Biosystems) as previously described [16, 31]. The relative mRNA levels were determined by quantitative two-step RT-PCR assay with pre-designed gene specific primer sets (Origene) as described before [16, 31]. The relative microRNA and mRNA levels were computed using the 2-delta delta Ct analysis method, where U6 and beta-actin were used as internal controls, respectively. Western-blot analysis Western blots were performed as described previously [16] using antibodies specific for HPGD (Cayman Chemical) and beta-actin (Sigma-Aldrich) and an immuno-star HRP substrate Kit (Bio-RAD). Fluorescent immunocytochemical analysis Immunofluorescence analysis was performed as previously described [16]. In brief, cells were cultured on 8 chamber polypropylene vessel tissue culture treated glass slides (Millipore) fixed with cold methanol, permeabilized with 0.5 % Triton X-100/PBS, and blocked with 1% BSA in PBS. The slides were incubated with primary antibodies against HPGD (1:500, Cayman Chemical). The slides were then incubated with a FITC-conjugated anti-rabbit IgG antibody (1:50, Santa Cruz). The slides were mounted with ProLong Gold antifade reagent containing DAPI (Invitrogen) following the manufacturer’s protocol. The slides were then examined with a fluorescence microscope (Carl Zeiss). Dual-Luciferase reporter assay The luciferase reporter gene constructs (pGL-E1 and pGL-E2E3) were created by cloning a 55-bp fragment from the 3′-UTR (position 2625–2680 of the HPGD mRNA sequence NM_000860, containing the miR-21 site E1) and a 61-bp fragment from the 3′-UTR (position 2860–2921 of the HPGD mRNA sequence NM_000860, containing the miR-21 targeting sites E2 and E3) into the Xba I site of the pGL3-Control firefly luciferase reporter vector (Promega) as described previously [9]. The corresponding mutant constructs (pGL-E1m, pGL-E2mE3, pGL-E2E3m and pGL-E2mE3m) were created by replacing the seed regions (positions 2–8) of the miR-21 binding sites with 5′-TTTTTTT-3′. All constructs were verified by sequencing. The reporter constructs and the pRL-TK vector (Promega) were co-transfected using Lipofectamine 2000 (Invitrogen). The luciferase activities were then determined as described previously [26] using a GloMax 20/20 luminometer (Promega). Experiments were performed in quadruplicate. Statistical analysis Data was analyzed using the Statistical Package for Social Science (SPSS), version 17.0. Student’s t-test was used to compare differences between groups. Pearson’s correlation coefficient was computed for examining the relationship between the expression of microRNA and their target genes. For all analyses, p < 0.05 was considered statistically significant. Results We first developed a list of putative microRNA-mRNA regulatory modules (MRMs) based on the simple principle that inverse relationships should be anticipated in the expression of a specific microRNA and its functional target gene (mRNA). We used a total of 97 differentially expressed coding genes (44 up-regulated and 53 down-regulated mRNAs, see Additional file 1: Table S1A and S1B, respectively) and 9 differentially expressed microRNAs (5 up-regulated and 4 down-regulated microRNAs, see Additional file 1: Table S1C) from our previous genomic profiling studies on OTSCC [15, 16] for the development of this putative MRMs list. This putative MRMs list consists of 265 putative MRMs defined by microRNA up-regulation and mRNA down-regulation, and 176 putative MRMs defined by microRNA down-regulation and mRNA up-regulation. We then tested these putative MRMs using a panel of 12 different sequence-based microRNA target prediction algorithms (DIANAmT, miRanda, microCosm, miRDB, miRWalk, RNAhybrid, PicTar (4-way), PicTar (5-way), PITA, RNA22, TargetScan5.1, and TargetScanHuman6.2) to refine our putative MRMs list. A total of 132 candidate MRMs were identified (predicted as microRNA target by at least 1 bioinformatics algorithm, see Additional file 2: Table S2A and Additional file 3: Table S2B). As shown in Table 1, 38 potential MRMs were predicted by at least 3 bioinformatics target prediction algorithms, where the up-regulation of the microRNA contributes to the down-regulation of mRNA, and 15 potential MRMs were predicted by at least 3 bioinformatics target prediction algorithms (Table 2), where down-regulation of the microRNA contributes to the up-regulation of mRNA. The differential expression of microRNAs and coding genes (mRNAs) involved in these 53 potential MRMs (9 microRNAs and 34 mRNAs) was then validated using dataset on 12 OTSCC and paired normal tissues (extracted from TCGA Data Portal). As shown in Additional file 4: Table S3, statistically significant differential expression was observed for 8 out of 9 microRNAs and 23 out of 34 mRNAs tested in the validation OTSCC cohort.Table 1 Putative microRNA-mRNA regulatory module defined by microRNA up-regulation and mRNA down-regulationa Putative miR-mRNA regulatory module Bioinformatics Predictionc Correlation (TCGA dataset)d Correlation (HNSCC cell line)e Correlation (patient sample)f miR (up)b mRNA (down)b Pearson r p value Pearson r p value Pearson r p value hsa-miR-155 ADH1B 6 −0.3263 0.120034 −0.0317 0.914331 hsa-miR-31 ADH1B 3 −0.3651 0.079472 0.3863 hsa-miR-223 ADIPOQ 5 −0.3104 0.140425 0.476 hsa-miR-130b ADIPOQ 3 −0.3612 0.083075 0.2356 hsa-miR-223 ALOX12 5 −0.2752 0.193414 0.5856 hsa-miR-130b ATP1A2 6 −0.4324 0.035023 −0.1899 0.515529 hsa-miR-31 ATP1A2 3 −0.3265 0.120034 0.2494 hsa-miR-223 CEACAM5 6 −0.0421 0.845504 −0.1689 0.563792 hsa-miR-21 CEACAM5 5 −0.107 0.618738 −0.0834 0.776829 hsa-miR-130b CEACAM5 4 −0.1968 0.358677 −0.2497 0.389269 hsa-miR-223 CEACAM7 6 −0.111 0.605605 −0.1364 0.641958 hsa-miR-21 CILP 5 −0.4095 0.047201 −0.1815 0.534608 hsa-miR-21 CLU 3 −0.4126 0.045447 −0.1612 0.581947 hsa-miR-31 EMP1 5 −0.1491 0.487134 −0.0997 0.7345 hsa-miR-130b EMP1 4 −0.5049 0.012034 0.0951 hsa-miR-21 GPD1L 5 −0.6784 0.000269 −0.4509 0.105628 −0.9536 0.00001 hsa-miR-155 GPD1L 5 −0.3008 0.154363 0.208 hsa-miR-223 HLF 7 −0.5536 0.005067 0.0789 hsa-miR-31 HLF 6 −0.5107 0.010896 0.2482 hsa-miR-130b HLF 6 −0.62 0.001231 0.067 hsa-miR-21 HLF 3 −0.7801 <0.00001 −0.5774 0.0307 −0.6707 0.048 hsa-miR-31 HPGD 6 −0.2577 0.225391 0.0659 hsa-miR-21 HPGD 6 −0.55 0.005363 −0.5841 0.0283 −0.7972 0.0011 hsa-miR-130b HPGD 3 −0.4602 0.023715 −0.3617 0.203821 hsa-miR-21 ID4 5 −0.5229 0.008886 −0.1121 0.702802 hsa-miR-31 KRT15 3 −0.1438 0.505031 −0.0053 0.985653 hsa-miR-21 LEPR 5 −0.2902 0.169251 0.6053 hsa-miR-223 LEPR 4 −0.1443 0.502026 −0.3246 0.257504 hsa-miR-130b MGLL 4 −0.6913 0.000183 −0.5158 0.05903 −0.1864 0.542035 hsa-miR-223 NEBL 6 −0.518 0.009519 −0.0598 0.8391 hsa-miR-130b NEBL 5 −0.5237 0.008733 0.091 hsa-miR-21 NEBL 3 −0.5582 0.004605 −0.1793 0.539655 hsa-miR-223 NMU 5 −0.2119 0.322319 0.6125 hsa-miR-31 PPP1R3C 4 −0.2695 0.203707 0.5588 hsa-miR-155 PTN 6 0.1331 −0.1157 0.693673 hsa-miR-130b TGM1 7 −0.5858 0.002676 0.0162 hsa-miR-155 ZNF185 6 −0.0065 0.977802 −0.2152 0.46 hsa-miR-21 ZNF185 5 −0.3451 0.098725 −0.0739 0.8018 aThe putative microRNA-mRNA regulatory module (MRM) was constructed based on microRNA and mRNA expression profiles of OTSCC, as we previously reported in [16] and [15], respectively bDifferential expression of microRNAs and mRNAs was validated using dataset on 12 OTSCC and paired normal tissue samples that were extracted from TCGA. Genes that show statistically significant differential expression were identified with bold font cThe candidate targets of a microRNA were predicted using a collection of 12 bioinformatics tools, including DIANAmT, miRanda, microCosm, miRDB, miRWalk, RNAhybrid, PicTar (4-way), PicTar (5-way), PITA, RNA22, TargetScan5, and TargetScanHuman 6.2. The number of bioinformatics tools (out of a total of 12 tools tested here) that predict a gene to be a microRNA target was presented. The gene/microRNA pairs predicted by at least 3 tools were listed in the table dCorrelations of microRNA and mRNA levels were assessed using dataset on 12 OTSCC and paired normal controls that were extracted from TCGA. Inverted correlation (negative Pearson r value) is expected for a MRM, and p value was calculated eCorrelations of microRNA and mRNA levels were assessed by quantitative real-time PCR based on 13 HNSCC cell line. Inverted correlation (negative Pearson r value) is expected for a MRM, and p value was calculated fCorrelations of 4 pairs of microRNA and mRNA levels were assessed by quantitative real-time PCR based on 13 OTSCC patient oral cytology samples. Inverted correlation (negative Pearson r value) is expected for a MRM, and p value was calculated Table 2 Putative microRNA-mRNA regulatory module defined by microRNA down-regulation and mRNA up-regulationa Putative miR-mRNA regulatory module Bioinformatics Predictionc Correlation (TCGA dataset)d Correlation (HNSCC cell line)e miR (down)b mRNA (up)b Pearson r p value Pearson r p value hsa-miR-375 COL4A6 5 −0.3145 0.13511 0.2432 hsa-miR-375 COL5A1 5 −0.3659 0.079472 −0.2159 0.4585 hsa-miR-125b COL5A1 5 −0.437 0.03274 −0.0325 0.9122 hsa-miR-375 COL5A2 5 −0.3708 0.075136 −0.231 0.426861 hsa-miR-375 CXCL1 4 −0.0864 0.689479 0.7146 hsa-miR-125b CXCL13 6 −0.3346 0.110688 −0.1736 0.552828 hsa-miR-375 DFNA5 4 −0.4936 0.014374 −0.0855 0.771344 hsa-miR-100 FSTL4 3 −0.0923 0.668975 −0.1796 0.538966 hsa-miR-99a FSTL4 3 −0.1413 0.511067 −0.1847 0.527303 hsa-miR-125b HMGA2 5 −0.4628 0.023036 −0.0557 0.849995 hsa-miR-375 IFI44L 4 −0.1937 0.366226 0.42 hsa-miR-125b IGFBP3 4 −0.3656 0.079472 −0.2774 0.336959 hsa-miR-125b LAMC2 5 −0.6952 0.000164 0.3459 hsa-miR-375 LAMC2 3 −0.4309 0.035971 0.4508 hsa-miR-375 ODC1 3 −0.2375 0.264826 −0.1239 0.673024 aThe putative microRNA-mRNA regulatory module (MRM) was constructed based on microRNA and mRNA expression profiles of OTSCC, as we previously reported in [16] and [15], respectively bDifferential expression of microRNAs and mRNAs was validated using dataset on 12 OTSCC and paired normal tissue samples that was extracted from TCGA. Genes that show statistically significant differential expression were identified with bold font cThe candidate targets of a microRNA were predicted using a collection of 12 bioinformatics tools, including DIANAmT, miRanda, microCosm, miRDB, miRWalk, RNAhybrid, PicTar (4-way), PicTar (5-way), PITA, RNA22, TargetScan5, and TargetScanHuman 6.2. The number of bioinformatics tools (out of a total of 12 tools tested here) that predict a gene to be a microRNA target was presented. The gene/microRNA pairs predicted by at least 3 tools were listed in the table dCorrelations of microRNA and mRNA levels were assessed using dataset on 12 paired OTSCC and normal controls that was extracted from TCGA Data Portal. Inverted correlation (negative Pearson r value) is expected for a MRM, and p value was calculated eCorrelations of microRNA and mRNA levels were assessed by quantitative real-time PCR based on 13 HNSCC cell line. Inverted correlation (negative Pearson r value) is expected for a MRM, and p value was calculated To further evaluate these potential MRMs, we examined the correlative relationship between the microRNA levels and the expression of their target genes in these 12 OTSCC and 12 paired normal tissues (extracted from TCGA Data Portal), as well as 13 HNSCC cell lines (Table 1 and Fig. 1). Among these 53 microRNA-mRNA pairs tested, 4 exhibited apparent inverse correlations in both OTSCC tissue samples and HNSCC cell lines (miR-21-GPD1L, miR-21-HLF, miR-21-HPGD and miR-130b-MGLL, with Pearson’s correlation coefficient r = −0.6784, −0.7801, −0.55, −0.6913 for OTSCC tissue samples, and r = −0.4509, −0.5774, −0.5841, and −0.5158 for HNSCC cell lines, respectively). The inverse correlations for miR-21-GPD1L, miR-21-HLF, miR-21-HPGD and miR-130b-MGLL were statistically significant in OTSCC tissue samples, and the inverse correlations for miR-21-HLF and miR-21-HPGD were also statistically significant in HNSCC cell lines.Fig. 1 Correlation of microRNAs and the expression of their target genes in OTSCC. The levels of miR-21 and miR-130b and the expression of HPGD, GPD1L, HLF and MGLL were extracted for 12 OTSCC and paired normal tissue samples from The Cancer Genome Atlas (TCGA) (a, d, g, j), assessed by qRT-PCR on 13 HNSCC cell lines (b, e, h, k), and on 13 oral cytology samples from OTSCC patients (c, f, i, l). The correlation of the miR-21 level with the expression of GPD1L (a, b, c), HLF (d, e, f), HPGD (g, h, i), and the correlation of miR-130b level with the expression of MGLL (j, k, l) were assessed, and the Pearson’s correlation coefficient (r) was calculated We further evaluated these 4 MRMs in oral cytology samples from 13 OTSCC cases, and statistically significant inverse correlations were observed for miR-21-GPD1L, miR-21-HLF, and miR-21-HPGD, but not for miR-130b-MGLL (r = −0.9536, p = 0.00001; r = −0.6707, p = 0.048; r = −0.7972, p = 0.0011; and r = −0.1864, p = 0.542035; Table 1 and Fig. 1). We further explore the interaction of miR-21 and HPGD in our study. As shown in Fig. 2a, ectopic transfection of miR-21 mimic to UM1, UM2, SCC9 and Tca8113 cells led to a statistically significant reduction in HPGD mRNA level as compared to cells treated with control mimic. The miR-21 has no apparent effect on HPGD expression in HeLa cells. As shown in Fig. 2b and c, ectopic transfection of miR-21 mimic to UM1 cells led to reduced HPGD expression at protein level and reduced immunostaining of HPGD, respectively, as compared to the cells treated with control mimic. As shown in Fig. 2d, ectopic transfection of miR-21 mimic also enhanced the proliferation of OTSCC cells, which is consistent with previous observations [10, 32], and confirmed the oncogenic effect of miR-21.Fig. 2 MiR-21-mediated down-regulation of HPGD and up-regulation of proliferation. a miR-21 mimic and negative control mimic were introduced into the UM1, UM2, SCC9 Tca8113 and HeLa cells. qRT-PCR was performed to assess the expression of HPGD. b Western blot was performed to assess the expression of HPGD at protein level in UM1 cells treated with either miR-21 mimic or negative control mimic. c The expression HPGD was measured by fluorescent immunocytochemical analysis in UM1 cells treated with either miR-21 mimic or negative control mimic (Green: HPGD; Blue: DAPI nuclear staining). d The UM1 and Tca8113 cells were treated with miR-21 mimic or negative control mimic, and the cell proliferation was assessed by MTT assay. Data represents at least 3 independent triplicate experiments with similar results. * indicates p < 0.05 Bioinformatics analysis revealed that there are three miR-21 targeting sites located in the 3′-UTR of the HPGD mRNA (E1 at position 2652 to 2671, E2 at position 2880 to 2901, E3 at 2890 to 2911) and the targeting sites E2 and E3 are partially overlapped (Fig. 3a). The predicted minimum free energy (mfe) for the binding of these sites to miR-21 are −17.6, −11.4 and −16.5 kcal/mol, respectively. To test whether the miR-21 directly interacts with these predicted targeting sites in HPGD mRNA, dual luciferase reporter assays were performed using constructs containing these targeting sites (Fig. 3b). When cells were transfected with miR-21, the luciferase activities of the construct containing targeting site E1 (pGL-E1) was significantly reduced as compared to the cells transfected with negative control. When the seed region of this targeting site was mutated (pGL-E1m), the effect of miR-21 on the luciferase activity was abolished. For sites E2 and E3, when cells were transfected with miR-21, the luciferase activities of the construct containing both targeting sites E2 and E3 (pGL-E2E3) was not changes as compared to the cells transfected with negative control. Interestingly, when the seed region of E2 was mutated (pGL-E2mE3), the miR-21-mediated down-regulation of the luciferase activity was observed. MiR-21 has no effect on constructs with E3 mutation (pGL-E2E3m) or mutations of both E2 and E3 (pGL-E2mE3m).Fig. 3 MiR-21 direct targeting HPGD mRNA. a Three predicted miR-21 targeting sites (E1, E2, E3) are located in the 3′-UTR of HPGD mRNA. The numbers under the diagram are the starting bp-position of the seed regions for the miR-21 targeting sites. The base-pairing and the minimum free energy (mfe) for the binding of miR-21 to the targeting sequences were predicted using the RNAhybrid program [18]. b Dual luciferase reporter assays were performed to test the interaction of miR-21 and its targeting sequences in the HPGD mRNA using constructs containing the predicted targeting sequences (pGL-E1 and pGL-E2E3) and mutated targeting sequences (pGL-E1m, pGL-E2mE3, pGL-E2E3m, pGL-E2mE3m) cloned into the 3′-UTR of the reporter gene. Data represent at least 3 independent experiments with similar results. *: p < 0.05 As shown in Fig. 4a and b, both siRNA-mediated knockdown of COX2 and treatment with COX2 inhibitor (CelecoxiB) led to down-regulation of miR-21 in UM1 cells. As shown in Fig. 4c, directly apply PGE2 to the UM1 cells led to the up-regulation of miR-21, and knockdown of HPGD (Fig. 4d) also led to the up-regulation of miR-21. As anticipated, treating cells with PGE2 and CelecoxiB led to up-regulation and down-regulation of cell proliferation, respectively, which is consistent with previous observations [33, 34] (Fig. 4e). These results are in agreement with observation made by Lu et al. in cholangiocarcinoma [35], which confirm the PGE2-mediated miR-21 up-regulation in OTSCC and suggest a PGE2-miR-21-HPGD positive feed-forward loop that contributes to tumorigenesis (Fig. 4f).Fig. 4 PGE2 regulates its own degradation by regulating miR-21 and its target gene HPGD. UM1 cells were treated with either control siRNA or specific siRNAs against COX2 (a), or treated with either COX2 inhibitor CelecoxiB or vehicle (b), or treated with either PGE2 or vehicle (c), or treated with either control siRNA or specific siRNAs against HPGD (d). The relative level of miR-21 was assessed by qRT-PCR. e UM1 cells were treated with PGE2, CelecoxiB or vehicle, and the cell proliferation was assessed by MTT assay. Data represent at least 3 independent experiments with similar results. *: p < 0.05. f Potential role of the positive feed-forward loop among PGE2, miR-21 and PHGD in OTSCC Discussion Despite the significant increase in the number of experimentally validated microRNA-mRNA regulatory relationships, the majority of the microRNA targeted genes remains unknown. MicroRNA usually binds to its target genes through partial complementary. While numerous sequence-based bioinformatics methods for microRNA target prediction have been developed, these methods often lead to high false discovery rates [11]. However, the integration of these bioinformatics tools with mRNA/microRNA differential expression profiles often lead to the identification of high confidence microRNA-mRNA regulatory modules. In this study, we carried out this integrated analysis to identify MRMs in two steps. First, based on the simple principle that inverse relationships should be anticipated in the expression of a specific microRNA and its functional target genes, we developed a list of putative microRNA-mRNA regulatory modules by linking each microRNAs with all inversely regulated mRNAs based on the results of our previous mRNA and microRNA profiling studies on OTSCC [15, 16]. The second step is to these putative MRMs bioinformaticsly using sequence-based microRNA target prediction algorithm. Since there are many available sequence-based microRNA target prediction tools, and each of these tools utilizes a different model to define targeting sequences that are associated with functionality, the predictions differ when applied to the same microRNAs, with each method having different levels of coverage and false positive prediction [11]. In order to reduce the potential false positives, we used a voting scheme to combine the predictions from the 12 commonly used bioinformatics tools, including DIANAmT, miRanda, microCosm, miRDB, miRWalk, RNAhybrid, PicTar (4-way), PicTar (5-way), PITA, RNA22, TargetScan5.1, and TargetScanHuman6.2. With this integrated approach, we developed a list of 53 potential MRMs that are differentially expressed in OTSCC. Since the microRNA regulates its target gene mainly at post-transcriptional level, inverse correlation between the levels of microRNA and mRNA pair is a key characteristic of a functional MRM. We further prioritized the list of differentially expressed MRMs in OTSCC by examining the correlative relationship between the microRNA levels and the expression of their target genes in 3 sets of samples (12 OTSCC and 12 paired normal tissues, 13 HNSCC cell lines, and 13 oral cytology samples from OTSCC cases). This comprehensive prioritization step led to 4 promising MRMs, including miR-21-GPD1L, miR-21-HLF, miR-21-HPGD and miR-130b-MGLL. Deregulations of miR-21 and miR-130b, as well as deregulation of GPD1L, HLF, HPGD and MGLL have been reported either in HNOC or other cancer types [15, 16, 36–42], and these MRMs represent significant functional relevance in OTSCC. GPD1L has the glycerol-3-phosphate dehydrogenase enzyme activity and is a regulator of HIF-1α stability [40]. And a recent study showed that the GPD1L expression is a strong predictor for local recurrence and survival in HNSCC [39]. HLF belongs to the PAR (proline and acidic amino acid-rich) subfamily of bZIP transcription factors [43, 44], and plays a role in development and circadian rhythm regulation in the mammalian. HLF fusion proteins that resulted from chromosomal translocation (e.g., E2A-HLF) are often linked to leukemia. However, the role of HLF in OTSCC is not entirely clear. MGLL is involved in Prostaglandin E2 (PGE2) production in response to inflammation and infection which leads to fever [45]. Arachidonic acid (AA), a precursor for PGE2, is typically liberated from AA-containing phospholipids by the action of phospholipases A2 (PLA2s). MGLL is a monoacylglycerol lipase which hydrolyzes 2-arachidonoylglycerol (2-AG), an endocannabinoid that functions in the central nervous system, to AA and glycerol, representing an alternative AA-producing pathway. MGLL may also play a role in certain types of cancer by regulating both endocannabinoid and fatty acid pathways, and supporting protumorigenic metabolism [46]. This appears to be contradict with the apparent down-regulation of MGLL observed in OTSCC [15], and the miR-130b-MGLL regulatory module predicted here. Nonetheless, whether MGLL plays a role in OTSCC and, if so, by what mechanism are questions that remain unanswered. HPGD is a known anti-tumorigenic effecter, and it regulates the tumorigenic actions of Prostaglandin E2 (PGE2) by converts PGE2 to its biologically inactive metabolite, and down-regulation of HPGD has been observed in many human cancer types [47–53]. Since miR-21 is one of the most consistently observed up-regulated microRNA in OTSCC [16, 54], the miR-21-HPGD regulatory module may represents a critical mechanism of regulating PGE2 signaling. Our functional study confirmed the effect of miR-21 on HPGD expression level, and the direct interaction of miR-21 with the HPGD mRNA in OTSCC cells. We identified three miR-21 targeting sites located in the 3′-UTR of the HPGD mRNA, including a previously reported site (E1) [35], and two partially overlapped sites (E2 and E3). While we confirmed the miR-21-mediated and E1 site-dependent target gene downregulation, E2 and E3 sites appear to have no effect. This may be because that targeting sites E2 and E3 are partially overlapped, and may interfere with the proper interaction with the RISC complex. The elimination of E2 may partially restore the capability of E3 (which has a stronger binding affinity among the two sites) to binding to the RISC complex. This is different than our previous observation where miR-138 was able to interact with multiple overlapping target sites on the FOSL1 mRNA [55]. Additional studies are needed to explore this mutual exclusive phenomenon among multiple targeting sites. The HPGD gene has 6 known transcript variants (NCBI accession: NM_000860, NM_001145816, NM_001256301, NM_001256305, NM_001256306, NM_001256307), and all 6 variants have the same 3′-UTR. As such, the interaction between miR-21 and HPGD mRNA is not likely to be affected by alternative splicing. Interestingly, we did not observe any miR-21 effect on HPGD expression in HeLa cells (a cell line that originated from a cervical cancer case). It is possible that this apparent difference in the miR-21 effect on HPGD expression may be due to differences in cancer types. It is worth noting that the effect of miR-21 on HPGD expression has also been observed in other cancer type [35]. Alternatively, this difference may be cell-line specific. HeLa cells (or the OTSCC cell lines used here) may have specific mutation(s) that dictate the miR-21 effects on HPGD. More in-depth functional analysis will be needed to fully evaluate the miR-21-HPGD regulatory module in different cancer types and in other biological systems. The levels of COX2 and its catalytic product PGE2 are increased in a variety of malignancies, including HNOC [56–59]. The tumorigenic actions of PGE2 are attributable to its modulation of cell proliferation, survival, migration, and invasion. The level of PGE2 is controlled by the status of PGE2 synthesis and degradation. Whereas the cyclooxygenases (COX1 and COX2) are rate-limiting key enzymes that control PGE2 biosynthesis, HPGD is a key enzyme that converts PGE2 to its biologically inactive metabolite, 13,14-dihydro-15-keto-PGE2, thus leading to PGE2 inactivation [60, 61]. Consistent with the antitumorigenic effect of HPGD, the down-regulation of HPGD has been observed in many human cancer types [47–53]. Lu et al., first reported the PGE2-mediated up-regulation of miR-21 in cholangiocarcinoma, and suggested a positive feed-forward loop that involves PGE2, miR-21 and HPGD [35]. Our results are consistent with these previous observations, and confirm the existence of a PGE2-miR-21-HPGD positive feed-forward loop in OTSCC that contributes to tumorigenesis (Fig. 4f). Conclusions In summary, we identified a number of high-confidence MRMs in OTSCC, including miR-21-GPD1L, miR-21-HLF, miR-21-HPGD and miR-130b-MGLL regulatory modules. Among these MRMs, miR-21-HPGD regulatory module may play an important role as part of a feed-forward loop that regulates the PGE2 signaling. Such a feed-forward regulatory mechanism likely plays a critical role in OTSCC initiation and progression. Thus, combining the COX2 inhibitor-based therapies with miR-21 inhibitors may represent a promising therapeutic strategy for treating patients with OTSCC. Additional files Additional file 1: Table S1. Lists of 97 differentially expressed mRNA transcripts and 9 microRNAs in OTSCC based on our previous genomic profiling studies [15, 16]. (DOC 140 kb) Additional file 2: Table S2A. Candidate microRNA-mRNA regulatory module defined by microRNA up-regulation and mRNA down-regulation. (XLSX 15 kb) Additional file 3: Table S2B. Candidate microRNA-mRNA regulatory module defined by microRNA down-regulation and mRNA up-regulation. (XLSX 11 kb) Additional file 4: Table S3. Validation of the differential expression of microRNAs and mRNAs involved in putative MRM using TCGA dataset. (XLSX 12 kb) Abbreviations HNOCHead and neck/oral cancer HNSCCHead and neck squamous cell carcinoma HPGD15-Hydroxyprostaglandin Dehydrogenase mfeMinimum free energy MRMmicroRNA-mRNA regulatory module OTSCCOral tongue squamous cell carcinoma TCGAThe cancer genome atlas This work was supported in part by NIH PHS grants (CA139596, CA171436 and DE025926), the Lilly USA Research Award in Cancer Prevention and Early Detection from Prevent Cancer Foundation, and a seed grant from CMBOD Oral Cancer Research Program (UIC College of Dentistry) to X.Z., and grants from National Nature Science Foundation of China (NSFC81472523, NSFC81272953) to A.W. Availability of data and materials Additional data supporting the findings presented in this manuscript is presented as supplementary materials associated with this manuscript. Authors’ contributions QH, RJC, AW, XZ contributed to the concept and study design; QH, ZC, QD, LZ, DC, AP, AK, XL performed experimental studies and data acquisition; QH, YD, XZ performed bioinformatics and statistical analysis; QH, XL, RJC, YD, AW, XZ contributed to the manuscript preparation and editing. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate The study involves human subjects was approved by the Ethical Committee of the First Affiliated Hospital, Sun Yat-Sen University, and the informed consent was obtained from participants. Name of ethics committee: The Ethical Committee of the First Affiliated Hospital, Sun Yat-Sen University. ==== Refs References 1. Franceschi D Gupta R Spiro RH Shah JP Improved survival in the treatment of squamous carcinoma of the oral tongue Am J Surg 1993 166 360 5 10.1016/S0002-9610(05)80333-2 8214293 2. Byers RM Weber RS Andrews T McGill D Kare R Wolf P Frequency and therapeutic implications of “skip metastases” in the neck from squamous carcinoma of the oral tongue Head Neck 1997 19 14 9 10.1002/(SICI)1097-0347(199701)19:1<14::AID-HED3>3.0.CO;2-Y 9030939 3. Robbins KT Clayman G Levine PA Medina J Sessions R Shaha A Som P Neck dissection classification update: revisions proposed by the American head and neck society and the American academy of otolaryngology-head and neck surgery Arch Otolaryngol Head Neck Surg 2002 128 751 8 10.1001/archotol.128.7.751 12117328 4. Fakih AR Rao RS Borges AM Patel AR Elective versus therapeutic neck dissection in early carcinoma of the oral tongue Am J Surg 1989 158 309 13 10.1016/0002-9610(89)90122-0 2802032 5. Wong TS Liu XB Wong BY Ng RW Yuen AP Wei WI Mature miR-184 as potential oncogenic microRNA of squamous cell carcinoma of tongue Clin Cancer Res 2008 14 2588 92 10.1158/1078-0432.CCR-07-0666 18451220 6. Kozaki K Imoto I Mogi S Omura K Inazawa J Exploration of tumor-suppressive microRNAs silenced by DNA hypermethylation in oral cancer Cancer Res 2008 68 2094 105 10.1158/0008-5472.CAN-07-5194 18381414 7. Tran N McLean T Zhang X Zhao CJ Thomson JM O'Brien C Rose B MicroRNA expression profiles in head and neck cancer cell lines Biochem Biophys Res Commun 2007 358 12 7 10.1016/j.bbrc.2007.03.201 17475218 8. Hebert C Norris K Scheper MA Nikitakis N Sauk JJ High mobility group A2 is a target for miRNA-98 in head and neck squamous cell carcinoma Mol Cancer 2007 6 5 10.1186/1476-4598-6-5 17222355 9. Jin Y Chen Z Liu X Zhou X Evaluating the microRNA targeting sites by luciferase reporter gene assay Methods Mol Biol 2012 936 117 27 10.1007/978-1-62703-083-0_10 23007504 10. Sun Z Li S Kaufmann AM Albers AE miR-21 increases the programmed cell death 4 gene-regulated cell proliferation in head and neck squamous carcinoma cell lines Oncol Rep 2014 32 2283 9 25175929 11. Dai Y Zhou X Computational methods for the identification of microRNA targets Open Access Bioinformatics 2010 2 29 39 22162940 12. Lim LP Lau NC Garrett-Engele P Grimson A Schelter JM Castle J Bartel DP Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs Nature 2005 433 769 73 10.1038/nature03315 15685193 13. Jiang L Dai Y Liu X Wang C Wang A Chen Z Heidbreder CE Identification and experimental validation of G protein alpha inhibiting activity polypeptide 2 (GNAI2) as a microRNA-138 target in tongue squamous cell carcinoma Hum Genet 2011 129 189 97 10.1007/s00439-010-0915-3 21079996 14. Chen D Chen Z Jin Y Dragas D Zhang L Adjei BS Wang A MicroRNA-99 family members suppress homeobox A1 expression in epithelial cells PLoS One 2013 8 e80625 10.1371/journal.pone.0080625 24312487 15. Ye H Yu T Temam S Ziober BL Wang J Schwartz JL Mao L Transcriptomic dissection of tongue squamous cell carcinoma BMC Genomics 2008 9 69 10.1186/1471-2164-9-69 18254958 16. Chen Z Jin Y Yu D Wang A Mahjabeen I Wang C Liu X Down-regulation of the microRNA-99 family members in head and neck squamous cell carcinoma Oral Oncol 2012 48 686 91 10.1016/j.oraloncology.2012.02.020 22425712 17. Dweep H Sticht C Pandey P Gretz N miRWalk--database: prediction of possible miRNA binding sites by “walking” the genes of three genomes J Biomed Inform 2011 44 839 47 10.1016/j.jbi.2011.05.002 21605702 18. Kruger J Rehmsmeier M RNAhybrid: microRNA target prediction easy, fast and flexible Nucleic Acids Res 2006 34 W451 4 10.1093/nar/gkl243 16845047 19. Wreesmann VB Wang D Goberdhan A Prasad M Ngai I Schnaser EA Sacks PG Genetic abnormalities associated with nodal metastasis in head and neck cancer Head Neck 2004 26 10 5 10.1002/hed.10344 14724901 20. Vigneswaran N Wu J Zacharias W Upregulation of cystatin M during the progression of oropharyngeal squamous cell carcinoma from primary tumor to metastasis Oral Oncol 2003 39 559 68 10.1016/S1368-8375(03)00038-1 12798398 21. Gioanni J Fischel JL Lambert JC Demard F Mazeau C Zanghellini E Ettore F Two new human tumor cell lines derived from squamous cell carcinomas of the tongue: establishment, characterization and response to cytotoxic treatment Eur J Cancer Clin Oncol 1988 24 1445 55 10.1016/0277-5379(88)90335-5 3181269 22. Krause CJ Carey TE Ott RW Hurbis C McClatchey KD Regezi JA Human squamous cell carcinoma. Establishment and characterization of new permanent cell lines Arch Otolaryngol 1981 107 703 10 10.1001/archotol.1981.00790470051012 7295166 23. Rheinwald JG Beckett MA Tumorigenic keratinocyte lines requiring anchorage and fibroblast support cultures from human squamous cell carcinomas Cancer Res 1981 41 1657 63 7214336 24. He RG Xu X Zhou X Zhang X Qiu W Zhang X Liu A The establishment and some biological characteristics of a squamous cell cancer cell line of the human tongue (Tca8113) Ai Zheng 1983 3 97 100 25. Nakayama S Sasaki A Mese H Alcalde RE Matsumura T Establishment of high and low metastasis cell lines derived from a human tongue squamous cell carcinoma Invasion Metastasis 1998 18 219 28 10.1159/000024515 10729767 26. Jiang L Liu X Kolokythas A Yu J Wang A Heidbreder CE Shi F Down-regulation of the Rho GTPase signaling pathway is involved in the microRNA-138 mediated inhibition of cell migration and invasion in tongue squamous cell carcinoma Int J Cancer 2010 127 505 512 10.1002/ijc.25320 20232393 27. Liu X Jiang L Wang A Yu J Shi F Zhou X MicroRNA-138 suppresses invasion and promotes apoptosis in head and neck squamous cell carcinoma cell lines Cancer Lett 2009 286 217 22 10.1016/j.canlet.2009.05.030 19540661 28. Liu X Wang A Heidbreder CE Jiang L Yu J Kolokythas A Huang L MicroRNA-24 targeting RNA-binding protein DND1 in tongue squamous cell carcinoma FEBS Lett 2010 584 4115 4120 10.1016/j.febslet.2010.08.040 20816961 29. Schwartz JL Panda S Beam C Bach LE Adami GR RNA from brush oral cytology to measure squamous cell carcinoma gene expression J Oral Pathol Med 2008 37 70 7 10.1111/j.1600-0714.2007.00596.x 18197850 30. Kolokythas A Schwartz JL Pytynia KB Panda S Yao M Homann B Sroussi HY Analysis of RNA from brush cytology detects changes in B2M, CYP1B1 and KRT17 levels with OSCC in tobacco users Oral Oncol 2011 47 532 6 10.1016/j.oraloncology.2011.03.029 21549635 31. Jin Y Tymen SD Chen D Fang ZJ Zhao Y Dragas D Dai Y MicroRNA-99 Family Targets AKT/mTOR Signaling Pathway in Dermal Wound Healing PLoS One 2013 8 e64434 10.1371/journal.pone.0064434 23724047 32. Li J Huang H Sun L Yang M Pan C Chen W Wu D MiR-21 indicates poor prognosis in tongue squamous cell carcinomas as an apoptosis inhibitor Clin Cancer Res 2009 15 3998 4008 10.1158/1078-0432.CCR-08-3053 19509158 33. Qian M Qian D Jing H Li Y Ma C Zhou Y Combined cetuximab and celecoxib treatment exhibits a synergistic anticancer effect on human oral squamous cell carcinoma in vitro and in vivo Oncol Rep 2014 32 1681 8 25328959 34. Abrahao AC Castilho RM Squarize CH Molinolo AA dos Santos-Pinto D Jr Gutkind JS A role for COX2-derived PGE2 and PGE2-receptor subtypes in head and neck squamous carcinoma cell proliferation Oral Onco 2010 46 880 7 10.1016/j.oraloncology.2010.09.005 35. Lu L Byrnes K Han C Wang Y Wu T miR-21 targets 15-PGDH and promotes cholangiocarcinoma growth Mol Cancer Res 2014 12 890 900 10.1158/1541-7786.MCR-13-0419 24699315 36. Seidel MG Look AT E2A-HLF usurps control of evolutionarily conserved survival pathways Oncogene 2001 20 5718 25 10.1038/sj.onc.1204591 11607821 37. Greenhough A Smartt HJ Moore AE Roberts HR Williams AC Paraskeva C Kaidi A The COX-2/PGE2 pathway: key roles in the hallmarks of cancer and adaptation to the tumour microenvironment Carcinogenesis 2009 30 377 86 10.1093/carcin/bgp014 19136477 38. Chen D Cabay RJ Jin Y Wang A Lu Y Shah-Khan M Zhou X MicroRNA deregulations in head and neck squamous cell carcinomas J Oral Maxillofac Res 2013 4 e2 10.5037/jomr.2013.4102 24422025 39. Feng Z Li JN Wang L Pu YF Wang Y Guo CB The prognostic value of glycerol-3-phosphate dehydrogenase 1-like expression in head and neck squamous cell carcinoma Histopathology 2014 64 348 55 10.1111/his.12258 24274692 40. Kelly TJ Souza AL Clish CB Puigserver P A hypoxia-induced positive feedback loop promotes hypoxia-inducible factor 1alpha stability through miR-210 suppression of glycerol-3-phosphate dehydrogenase 1-like Mol Cell Biol 2011 31 2696 706 10.1128/MCB.01242-10 21555452 41. Cadenas C Vosbeck S Hein EM Hellwig B Langer A Hayen H Franckenstein D Glycerophospholipid profile in oncogene-induced senescence Biochim Biophys Acta 1821 2012 1256 68 42. Galli GG Multhaupt HA Carrara M de Lichtenberg KH Christensen IB Linnemann D Santoni-Rugiu E Prdm5 suppresses Apc(Min)-driven intestinal adenomas and regulates monoacylglycerol lipase expression Oncogene 2014 33 3342 50 10.1038/onc.2013.283 23873026 43. Hunger SP Ohyashiki K Toyama K Cleary ML Hlf, a novel hepatic bZIP protein, shows altered DNA-binding properties following fusion to E2A in t(17;19) acute lymphoblastic leukemia Genes Dev 1992 6 1608 20 10.1101/gad.6.9.1608 1516826 44. Inaba T Roberts WM Shapiro LH Jolly KW Raimondi SC Smith SD Look AT Fusion of the leucine zipper gene HLF to the E2A gene in human acute B-lineage leukemia Science 1992 257 531 4 10.1126/science.1386162 1386162 45. Kita Y Yoshida K Tokuoka SM Hamano F Yamazaki M Sakimura K Kano M Fever is mediated by conversion of endocannabinoid 2-arachidonoylglycerol to prostaglandin E2 PLoS One 2015 10 e0133663 10.1371/journal.pone.0133663 26196692 46. Nomura DK Lombardi DP Chang JW Niessen S Ward AM Long JZ Hoover HH Monoacylglycerol lipase exerts dual control over endocannabinoid and fatty acid pathways to support prostate cancer Chem Biol 2011 18 846 56 10.1016/j.chembiol.2011.05.009 21802006 47. Backlund MG Mann JR Holla VR Buchanan FG Tai HH Musiek ES Milne GL 15-Hydroxyprostaglandin dehydrogenase is down-regulated in colorectal cancer J Biol Chem 2005 280 3217 23 10.1074/jbc.M411221200 15542609 48. Wolf I O'Kelly J Rubinek T Tong M Nguyen A Lin BT Tai HH 15-hydroxyprostaglandin dehydrogenase is a tumor suppressor of human breast cancer Cancer Res 2006 66 7818 23 10.1158/0008-5472.CAN-05-4368 16885386 49. Thiel A Ganesan A Mrena J Junnila S Nykanen A Hemmes A Tai HH 15-hydroxyprostaglandin dehydrogenase is down-regulated in gastric cancer Clin Cancer Res 2009 15 4572 80 10.1158/1078-0432.CCR-08-2518 19584167 50. Backlund MG Mann JR Holla VR Shi Q Daikoku T Dey SK DuBois RN Repression of 15-hydroxyprostaglandin dehydrogenase involves histone deacetylase 2 and snail in colorectal cancer Cancer Res 2008 68 9331 7 10.1158/0008-5472.CAN-08-2893 19010907 51. Myung SJ Rerko RM Yan M Platzer P Guda K Dotson A Lawrence E 15-Hydroxyprostaglandin dehydrogenase is an in vivo suppressor of colon tumorigenesis Proc Natl Acad Sci U S A 2006 103 12098 102 10.1073/pnas.0603235103 16880406 52. Tseng-Rogenski S Gee J Ignatoski KW Kunju LP Bucheit A Kintner HJ Morris D Loss of 15-hydroxyprostaglandin dehydrogenase expression contributes to bladder cancer progression Am J Pathol 2010 176 1462 8 10.2353/ajpath.2010.090875 20093479 53. Tatsuwaki H Tanigawa T Watanabe T Machida H Okazaki H Yamagami H Shiba M Reduction of 15-hydroxyprostaglandin dehydrogenase expression is an independent predictor of poor survival associated with enhanced cell proliferation in gastric adenocarcinoma Cancer Sci 2010 101 550 8 10.1111/j.1349-7006.2009.01390.x 19917058 54. Jamali Z Asl Aminabadi N Attaran R Pournagiazar F Ghertasi Oskouei S Ahmadpour F MicroRNAs as prognostic molecular signatures in human head and neck squamous cell carcinoma: a systematic review and meta-analysis Oral Oncol 2015 51 321 31 10.1016/j.oraloncology.2015.01.008 25677760 55. Jin Y Wang C Liu X Mu W Chen Z Yu D Wang A Molecular characterization of the microRNA-138-Fos-like antigen 1 (FOSL1) regulatory module in squamous cell carcinoma J Biol Chem 2011 286 40104 9 10.1074/jbc.C111.296707 21969367 56. Buchanan FG Wang D Bargiacchi F DuBois RN Prostaglandin E2 regulates cell migration via the intracellular activation of the epidermal growth factor receptor J Biol Chem 2003 278 35451 7 10.1074/jbc.M302474200 12824187 57. Dannenberg AJ Subbaramaiah K Targeting cyclooxygenase-2 in human neoplasia: rationale and promise Cancer Cell 2003 4 431 6 10.1016/S1535-6108(03)00310-6 14706335 58. Schuon R Brieger J Franke RL Jakob R Mann WJ Increased PGE2 levels in nonmalignant mucosa adjacent to squamous cell carcinoma of the head and neck ORL J Otorhinolaryngol Relat Spec 2005 67 96 100 10.1159/000084996 15821352 59. Snyderman CH Milanovich M Wagner RL Johnson JT Prognostic significance of prostaglandin E2 production in fresh tissues of head and neck cancer patients Head Neck 1995 17 108 13 10.1002/hed.2880170206 7558806 60. Wang D Dubois RN Eicosanoids and cancer Nat Rev Cancer 2010 10 181 93 10.1038/nrc2809 20168319 61. Tai HH Prostaglandin catabolic enzymes as tumor suppressors Cancer Metastasis Rev 2011 30 409 17 10.1007/s10555-011-9314-z 22020925

PMC005xxxxxx/PMC5000502.txt

==== Front BMC Complement Altern MedBMC Complement Altern MedBMC Complementary and Alternative Medicine1472-6882BioMed Central London 126310.1186/s12906-016-1263-1Research ArticleIn vitro organo-protective effect of bark extracts from Syzygium guineense var macrocarpum against ferric-nitrilotriacetate-induced stress in wistar rats homogenates Tankeu Francine Nzufo yerema2003@yahoo.fr 1http://orcid.org/0000-0003-1602-6494Pieme Constant Anatole 00237 674551871apieme@yahoo.fr 1Biapa Nya Cabral Prosper brbiapa@yahoo.fr 2Njimou Romain Jacques jnjimou@yahoo.fr 3Moukette Bruno Moukette mouket2006@yahoo.fr 1Chianese Angelo angelo.chianese@uniroma1.it 3Ngogang Jeanne Yonkeu jngogang@yahoo.fr 11 Department of Biochemistry and Physiological Sciences; Faculty of Medicine and Biomedical Sciences, Laboratory of Biochemistry, University of Yaoundé I, PO Box 1364, Yaounde, Cameroon 2 Laboratory of Medicinal plant Biochemistry, Food Science and Nutrition, Department of Biochemistry, Faculty of Science, University of Dschang, PO Box 67, Dschang, Cameroon 3 Department of Chemical Materials Environmental Engineering, University of Rome “La Sapienza”, Via Eudossiana No. 18, Piazzale Aldo Moro 5, 00185 Rome, Italy 26 8 2016 26 8 2016 2016 16 1 3155 11 2015 5 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Overconsumption of oxygen in mammalian cells often lead to the production of reactive oxygen species (ROS) resulting from different mechanisms. Escape of scavenging enzymes/components or nutritional failure are the most important origins. Plant-derived molecules may protect biological molecules either by quenching free radicals, delaying or preventing the ROS formation or by restoring antioxidant enzymes activities. The present study assessed the antioxidant, phenolic profile and protective effect of barks extracts of Syzyguim guineense var macrocarpum against ferric nitriloacetate-induced stress in the liver, heart kidney and brain tissues of wistar rat homogenates. Methods Three extracts (aqueous, ethanol and aqueous-ethanol) from the barks of S. guineense var macrocarpum were used in this study. The spectrophotometric standardized methods were used to determine the free radical scavenging and antioxidant potential of the extracts. The protective properties of these plant extracts were also investigated as well as the quantification of secondary metabolites content (total phenolic, flavonoids and flavonols content). The HPLC method helped for characterizing phenolic compounds present in these extracts. Results and Discussion All the extracts exhibited a free radical scavenging potential in a concentration dependent manner which varied from 15.18 ± 0.80 to 97.15 ± 0.71 % depending to the type of extract and the method used. The ethanol extract had the higher phenolic content (432.85 mg QE/g extract), including total flavonoids (961.66 mg QE/g extract) and flavonols content (25.12 mg QE/g extract) and higher total antioxidant capacity. Among the phenolic compounds present in the extracts, the HLPC profile revealed the presence of syringic acid and apigenin in all the extracts. The extracts demonstrated their protective effect mostly in liver and brain homogenates by delaying or preventing lipid peroxidation, restoring enzymatic activities and enhancing glutathione levels. Conclusion The overall results demonstrated that the extracts exhibited significant antioxidant and protective effects in liver and brain liver homogenates. Keywords Syzygium guineense var macrocarpumSODPeroxidaseMalondialdehyde homogenatesGlutathioneissue-copyright-statement© The Author(s) 2016 ==== Body Background Free radicals are produced from various physiological mechanisms owing to their significant biological roles in a myriad of signaling pathways at a reasonable dose [1, 2]. They are involved in defense mechanisms against pathogenic microorganisms and/or cancer cells and detoxification of harmful molecules [3]. Besides, reactive oxygen species (ROS) play vital roles in cells including stimulation of the signal transduction pathways, cell cycle regulation enzyme activation, and protein modification [4, 5]. In normal cells, free radicals are continuously produced in lower concentrations and can be neutralized by endogenous antioxidant species. Indeed, human body is endowed with protective mechanisms against deleterious effects of free radicals including both enzymatic and non enzymatic antioxidants [6]. However, when the naturally-occurring equilibrium between anti- and pro-oxidant agents is lost, higher ROS levels bypass the antioxidant function leading to a biochemical/physiological state described as oxidative stress [7, 8]. Oxidative stress refers to a state of imbalance between the production of free radicals and/reactive metabolites and removal of the latter by antioxidants [9]. Several factors are known to be responsible of this state. Among them, tobacco, alcohol, UV rays, medications, toxic metals, herbicides, nutritional failure or genetic defects responsible of non/poor expression of a gene encoding a protein or an antioxidant enzyme protein involved in the synthesis of an antioxidant could be listed [10]. Besides those exogenous factors, there are also endogenous sources mainly intracellular metabolism involving the mitochondrial respiratory chain, the defective autophagy of mitochondria and defective metabolism of redox metals [4, 11]. Oxidative stress can cause tremendous harmful effects including alteration of the protein structures and hence loss of vital functions. Evidence has indicated that oxidative stress is a potentiating factor of the onset of a broad range of diseases [12–14]. Among these, hemolytic anemia and β-hemoglobinopathies (sickle cell anemia and thalassemia), cancer, atherosclerosis and, Alhzeimer’s disease are believed to be aggravated by ROS [15–17]. These deleterious effects are counteracted by natural antioxidants [18, 19]. Numerous research results demonstrated that natural antioxidant molecules are anticarcinogenic anti-angiogenic and potent inhibitors of sickle cell haemoglobin polymerization [18, 20–22]. Phenolics-enriched plant extracts exhibited strong antioxidant and beneficial effect against chemically-induced stress in vitro [23–25] and in vivo [26, 27]. This justifies the upsurge of interest that naturally-occurring antioxidants from spices, vegetables, and herbs has been gaining [16, 23, 25, 28]. Syzygium guineense (Wild) DC. is a leafy forest tree of the Myrtaceae family, found in many parts of Africa both wild and domesticated which comprises three varieties. It is used in African traditional medicine to treat epilepsy, stomach-ache, diarrhoea, malaria, coughs, broken bones, wounds, asthma, sore throat, intercostal pain and as a tonic. The powdered bark is used as an antispasmodic and purgative [29]. The antibacterial properties of the aqueous extract of S. guineense have been demonstrated on different strains of bacteria responsible for diarrhea [30]. Ethanol extracts of the stem bark of S. guineense showed molluscicidal activities and cardioprotective properties, mainly due to the reduction of blood pressure [31]. Antibacterial activity of triterpenes isolated from S. guineense has been demonstrated [32]. Other biological properties such as anti-inflammatory, analgesic and immunological activities of different part of S. guineense have been reported [33]. The chemical composition of essential oil from S. guineense was also investigated [34]. A recent study demonstrated that leaves, stem bark and roots of S. guineense have antioxidant properties and are rich in polyphenols [23]. Almost all these biological properties are about the guineense variety. Up-to-date, no study investigating either the in vitro antioxidant activity or the protective effects of extracts of the macrocarpum variety has been carried out. Hence, this study attempted to investigate the in vitro free radical scavenging potential, antioxidant activity and the protective effect of S. guineense var macrocarpum barks extracts against ferric nitiloacetate-induced stress in the liver, heart and kidney and brain tissues of Wistar rats homogenates as well as their polyphenolic profile. Methods Plant material Barks of Syzygium guineense var. macrocarpum were harvested in the surrounding islands of the Sanaga River (Centre region- Cameroon) in November 2014 and identified at the National Herbarium of Cameroon under the reference number 49885 HNC. Preparation of plant extracts The harvested samples were cleaned, dried at room temperature and crushed. The powdered samples obtained were soaked separately in water, 95° ethanol, and the mixture water: ethanol (30:70;v/v) at pH = 3 for 48 h respectively. The mixtures were then filtered using Buchner funnel and Whatman N° 1 filter paper, concentrated under rotary evaporator. The aqueous and water:ethanol extracts were lyophilized while the ethanol extract was dried in an oven at 50 °C to obtain the crude extracts. The resulting crude extracts were labelled as follows: SGFH2O: Syzygium guineense var macrocarpum aqueous extract (barks); SGFEtOH: Syzygium guineense var macrocarpum ethanolic extract (barks); SGF H2O/EtOH: Syzygium guineense var macrocarpum aqueous-ethanolic extract (barks). The crude extracts were stored at 4 °C until use. Before assaying each parameter, a stock solution of 1 mg/mL was prepared from which serial dilutions (0.025, 0.075, 0.150, 0.200 and 0.300 mg/mL) were prepared for the determination of the free radical scavenging activity. The phenolic metabolites content and antioxidant potential of different bark extracts were determined at 1 mg/mL. Determination of free radical scavenging and antioxidant properties Determination of free radical scavenging activity Scavenging activity of DPPH radical This assay measures the free radical scavenging potential of each crude extract. The method described by [35] was used. Briefly, 1000 μL of a 0.1 mM DPPH ethanolic solution was added to 3000 μL of each diluted extract or Vitamin C used as standard. After 30 min of incubation in the darkness at room temperature the absorbance was measured at 517 nm against a blank. Scavenging effect of the ABTS+ radical The radical scavenging capacity was measured by using ABTS+ solution radical cation. The assay was performed according to the method described by [36] with slight modifications. A stock solution of ABTS+ consisted of a 7.4 mM ABTS solution and 2.45 mM potassium persulfate solution in the ratio of 1:1. The mixture was allowed to react for 12 h at room temperature in the dark. A working solution was prepared by diluting 8 times the previous stock solution (20000 μL stock solution in 100000 μL volumetric flask, diluting it to the mark with ethanol) to get the absorbance of 0.7 ± 0.05 at 734 nm. After addition of 75 μL of extracts or vitamin C used as standard to 2000 μL of ABTS+ working solution, absorbance was measured at 734 nm after exactly 6 min. The % inhibition for DPPH and ABTS assay was calculated according to the formula Scaveningeffect%=100×Ao−As/Ao Where Ao is the absorbance of the blank; As is the absorbance of the sample Determination of antioxidant properties Total antioxidant activity by Ferric Reducing Antioxidant Power assay (FRAP) The FRAP assay was conducted following a previously described method [37] with slight modifications. The fresh FRAP reagent contained: acetate buffer (300 mM pH 3,6), 2,4, 6- Tri (2-pyridyl)-s-triazin (TPTZ) (10 mM) and FeCl3 · 6H2O (50 mM) in a 5:1:1 proportion respectively. FRAP reagent (2000 μL) was mixed to 75 μL of each tested extract and stored for 12 min. The activity of Vitamin C was used to plot the standard curve. The absorbance was read at 593 nm and results expressed as equivalent vitamin C/g of dried extract (mg eq Vit C/g DE). Phosphomolybdenum antioxidant assay The total antioxidant activity of extracts was evaluated by green phosphomolybdenum complex according to the method described by [38]. Phosphomolybenum reagent was prepared by mixing 0.6 M sulphuric acid, 28 mM sodium phosphate and 4 mM ammonium molybdate in 1:1:1 proportions. Phosphomolybdenum reagent (1000 μL) was introduced in test tubes. After addition of 10 μL of each extract sample, the mixture was homogeinized and the tubes incubated in a dry thermal bath at 95 °C for 90 min. Thereafter, tubes were cooled down and the absorbance of the mixture measured at 695 nm against a blank. The vitamin C was used as the standard and a calibration curve in the range of 0 – 0.3 mg/mL was prepared and BHT was used for the comparison. The reducing capacity of samples was expressed as mg of vitamin C equivalents/g of dried extract (mg vitC eq/g extract). Determination of total phenol content Total phenol content of the spice extract was determined using Folin-ciocalteu method [39]. This method is based on the reduction of phosphotungstate-phosphomolybdate reagent in alkaline medium. In different test tubes, 200 μL of 1 mg/ml of sample were introduced. Then, 800 μL of 10 fold diluted Folin reagent and 2000 μL of sodium carbonate solution (7.5 %) were added. After stirring, the mixture was kept away from light for 2 h and the absorbance was measured at 765 nm. The phenolic content was determined from a quercetin standard curve. A concentration range from 0 to 0.3 mg/mL of quercetin was prepared and allowed to determine the total polyphenol content expressed in mg equivalents of quercetin/g of extract (mg QE/g extract). Determination of total flavonoid content Total flavonoid content was determined using a well described method [40]. Briefly, 100 μL of extract were added to 300 μL of distilled water and 30 μL of NaNO2 (5 %). After 5 min of incubation at 25 °C, 30 μL of AlCl3 (10 %) were added. After further 5 min, the reaction mixture was treated with 200 μL of 1 mM NaOH and the reaction mixture diluted to 1000 μL with distilled water. Quercetin served to draw the standard calibration curve in the range of 0–0.3 mg/mL and the absorbance was measured at 510 nm. The results were expressed as mg quercetin equivalents/g of dried extract (mg QE/g extract). Determination of total flavonol content Total flavonols content in the plant extracts was determined according to the previously described technique [41] with slight modifications. In different test tubes, each extract (2000 μL) and standard solutions (2000 μL) were placed and then 2 % aluminum chloride (2000 μL), 50 g/L sodium acetate (3000 μL) were added and mixed well. The mixture was incubated at 20 °C for 2.5 h and absorbance was read at 440 nm. Total flavonols content was calculated as mg quercétine equivalent/g of extract using the equation based on the calibration curve and expressed as mg quercetin/g of dried extract (mgQE/g extract). Determination of the polyphenolic content by HPLC High Performance Liquid Chromatography (HPLC) with UV detection is frequently used to separate and characterize phenolic compounds present in extracts. The polyphenolic profile was determined according to a previously described method [28]. The analysis was performed on an Agilent Technologies 1200 HPLC system fitted with a SUPELCOSIL LC-18 column (length 250 mm, diameter 4.6 mm, packaging size 5 mm). Samples were dissolved in pure water to reach the concentration (300 mg/10 mL) and centrifuged at 4706 rpm for 10 min. The obtained supernatant was filtered through a cellulose acetate membrane filter (0.20 μm or 0.45 μm, Schleicher & Schuell). 25 μL of filtrate were injected into the HPLC system and eluted as described below. The column temperature was set at 20 °C. The mobile phase consisted of a mixture of an aqueous solution of acetic acid at 0.5 % by volume (“A”) and acetic nitrile (“B”). Elution was performed by following this protocol: At start and for the first 2 min of the run, 100 % of A. From 2 to 60 min after the run start, a linear composition ramp was used, targeting 40 % of A and 60 % of B. The flow rate was set to 1 mL/min. Polyphenols were detected by a UV detector (280 nm). Beforehand, the retention times of the identified polyphenolic compounds of interest available were measured by using of single standard solutions at a concentration of 100000 mg/mL. The quantification of identified compound was based on the area under peak determined at 280 nm and expressed relative to each corresponding phenolic standard. Evaluation of organ protective effects of plant extracts Preparation of different tissue homogenates Normal albino wistar rats (10) were sacrified and the organs (liver, kidney, brain and heart) were isolated and weighed. Each homogenate was prepared by mixing 10 % (w/v) of each ground organ and phosphate buffer (pH 7, 0.1 M) followed by a centrifugation at 3000 rpm for 30 min. The study was approved by the Faculty of Medicine and Biomedical Sciences Ethical committee authorizing the use of animals. Preparation of ferric-nitrilotriacetate solution The oxidizing solution was prepared according to [42] Briefly,1.62 g and 7.64 g of FeCl3 and NTA were dissolved in 100000 μL of HCl 0,1 N to reach the concentrations of 200 mM and 400 mM respectively. The obtained solution was then mixed to a H2O2 200 mM 1:1 (v/v) The oxidant solution was prepared immediately before utilization. Total protein content The total protein content of the mixture of liver was measured according to the protein kit supplier methods (Human Kit-Hu102536, Boehringer, Ingelheim, Germany). This result was used to express the activities of the different enzymes per g of organs. In vitro lipid peroxidation assay The capacity of the spice extract to inhibit the lipid peroxidation was evaluated according to a previously implemented method [43]. In brief, 580 μL of phosphate buffer (0,1 M; pH 7,4), 200 μL of spice extract and 200 μL of each homogenate were successively introduced in different test tubes. Lipid peroxidation was then initiated by adding 20 μL of oxidizing solution (0.1 M HCl, FeCl3 200 mM, 400 mM NTA, 200 mM H2O2) in the mixture. The whole was thereafter placed in a water bath at 37 °C for 1 h. At the end of the incubation, 100 μL of this mixture was pipeted and placed in new tests tubes to which 1000 μL of MDA reagent (TCA (10 %) and 1 ml of TBA (0.67 %) were added to terminate the reaction. All the tubes were then heated again at 100 °C for 20 min and transferred to an ice bath to be cooled and centrifuged at 3000 rpm for 5 min. The optical density was measured at 535 nm and the concentration of MDA was calculated using the formula: OD=εClandexpressedinnM,whereεmolarextinctioncoefficient=1.56×105/M/cmandl=lengthofthetank. Superoxide dismutase (SOD) activity assay An indirect method of inhibiting autooxidation of epinephrine to its adrenochrome was used to assay SOD activity in plant-treated homogenates [44]. An aliquot consisting in (580 μL PBS, 200 μL of each extract or standard, 200 μL of liver, kidney, kidney, heart homogenate) and 20 μL of inducing solution was introduced in different test tubes and the obtained mixture was then incubated at 37 °C for 1 h to obtain the test solutions. The latter (test solutions) will be used to investigate the other enzymatic parameters as well as non enzymatic ones. To 20 μL of each test solution (Fe3+- NTA induced homogenates treated with plant extract or standard), 150 μL were added to 500 μL of carbonate buffer (pH 10.2; 0, 3 M; pKa 10.3), 250 μL of an EDTA solution (0.6 mM); The obtained mixture was then homogenized and 150 μL of an epinephrine solution (4.5 mm) were added to initiate the reaction. Four other tubes were run in the same conditions to serve as normal, negative and positive controls. The extract was replaced respectively by distilled water, oxidant, Vit C and quercetin. The optical density was read after 30 min and 120 min at 480 nm. The following equation allowed the calculation of the SOD activity: SODunit/mgprotein=SODunits/mL/min/proteinmg/mL×df Where df = dilution factor The SOD activity was thereafter expressed as Unit/min/mg of protein (UI/mg Prot.) Catalase activity The catalase activity of plant extracts on different homogenates was assessed according to a formerly described method [45] with some amendments. The above tests solutions (100 μL) were dispensed in test tubes containing 900 μL phosphate buffer (0.01 M, pH 7). After homogenization the reaction was started by the addition of 400 μL of a hydrogen peroxide solution (200 mM), and after 60 s, 2000 μL of an acetic acid-dichromate solution were added to stop the reaction. The mixture was boiled for 10 min and the absorbance was measured at 530 nm. Glutathione peroxydase activity In different test tubes, 580 μL of PBS (0.1 M; pH 7.4), 200 μL of each plant extract or vit C and quercetin used as standards, 200 μL of each homogenate (liver, heart, kidney and brain) and 20 μL oxidizing solution (HCl 0.1 M, FeCl3 200 mM, NTA 400 mM, H2O2 200 mM) were introduced. The normal control, negative and positive controls were run simultaneously in the same conditions except that, the oxidizing solution was replaced respectively by distilled water for the normal control, the plant extract by the distilled water for the negative control and vit C and quercetin for the positive controls. The mixtures were thereafter incubated at 37 °C for 1 h. Then, 100 μL of each of these mixtures were dispensed in new test tubes containing 900 μL of PBS (0,01 M; pH 7). An aliquot of PBS 0,01 M, pH 6; pH 7 (320 μL), hydrogen peroxide 0.05 % (160 μL), and pyrogallol solution 0.05 % (320 μL) were added to distilled water (210 μL). 100 μL from the above mixture was added thereafter. The reaction was mixed and incubated for at least 10 min and the increase in absorbance at 420 nm was measured after 20 and 140 s using a spectrophotometer. Reduced glutathione assay The previously described method of Ellman [46], was used to determine glutathione antioxidant capacity of plant extracts. An aliquot of PBS (580 μL), 200 μL of extract and 200 μL of each homogenate (liver, kidney, brain and heart) and 20 μL of inducing solution was introduced in different test tubes. The obtained mixture was then incubated at 37 °C for 1 h. The above test solutions (20 μL) and 3000 μL of Ellman reagent (phosphate buffer 0,1 M; pH 6,5; 2,2-dithio-5,5′-dibenzoïc acid) were introduced in new test tubes. Glutathione concentrations were expressed in micromoles/L and calculated using the following formula: OD=εClwhereεglutathione=13600andl=opticalpath. Statistical analysis The results were presented as mean ± SD of triplicate assays. Analyses of data was conducted using one-way ANOVA (Analysis of variance) followed by Kruskal wallis test and Dunnett’s multiple test (SPSS program version 18.0 for Windows, IBM Corporation, New York, NY, USA). The Log probit was used to determinate the IC50. XLstat version 7 (Addinsoft, New York, NY, USA) was used to achieve the Spearman rho Correlation Analysis as well as the principal component analysis (PCA). The differences were considered as significant at p < 0.05. Results and Discussion A wide range of methods have been described for the free radical trapping potential and antioxidant properties of plant-derived components. DPPH is one of the most used assays to assess the antioxidant potential of tremendous naturally food derived and plant extracts. Results of DPPH free radical scavenging potential of different plant extracts are summarized in Table 1A. The DPPH free radical scavenging potential increases with the plant extract concentration. Inhibitory potential expressed as percentages ranged from (59.52 ± 0.56 to 93.57 ± 1.68 %) for the aqueous extract which presented a significant and lowest inhibitory potential compared to the ethanol extract (94.40 ± 0.13 %). However, Vitamin C had the most potent inhibitory potential (98.31 ± 0.27 %). These results suggest that these extracts are rich in hydrogen atom and or electron donating-substances as phenolic derived compounds, glycosylated derived compounds and anthocyans capable of pairing with the unstable DPPHo radical [47].Table 1 Radical scavenging potential of different barks extracts of Syzygium guineense var macrocapum Sample Concentration (μg/mL) SGF H2O SGF EtOH SGF H2O/EtOH VIT C A 25 59.52 ± 0.56c 66.27 ± 0.95b 55.21 ± 1.28bc 74.43 ± 1.79e 75 69.74 ± 0.16c 78.83 ± 0.95d 67.95 ± 1.36c 85.83 ± 0.66e 150 79.30 ± 0.68c 82.45 ± 1.25c 79.84 ± 0.37c 88.45 ± 0.62d 200 84.45 ± 0.61a 86.24 ± 4.73a 82.74 ± 0.14a 93.18 ± 2.58b 300 93.57 ± 1.68b 94.40 ± 0.13b 88.82 ± 1.78c 98.31 ± 0.27d IC50 (μg/mL) 2.585 2.321 2.692 2.01 B 25 19.95 ± 1.61d 15.18 ± 0.80a 23.19 ± 0.66d 24.00 ± 1.22a 75 36.47 ± 1.11c 39.10 ± 0.93c 26.54 ± 1.80e 64.91 ± 3.46b 150 78.34 ± 0.71b 53.01 ± 0.36c 34.56 ± 1.94e 90.81 ± 2.40cde 200 91.35 ± 0.15c 67.56 ± 1.29d 38.26 ± 0.66e 91.81 ± 1.57de 300 97.15 ± 0.71b 81.37 ± 0.94c 52.63 ± 0.71d 93.68 ± 1.16e IC50 (μg/mL) 2.299 2.922 5.119 1.632 Values are expressed as mean ± SD, In the same column the values designated different letters are significantly different at p < 0.05 A: DPPH radical scavenging potential of different plant extracts, B: ABTS radical scavenging potential of different plant extracts SGFH 2 O/EtOH syzygium guineense var macrocarpum (barks) aqueous-ethanol, SGFEtOH syzygium guineense var macrocarpum (barks) ethanolic, SGFH 2 O syzygium guineense var macrocarpum (barks) aqueous, Vit C vitamin C Besides the scavenging of free radicals, group I antioxidants also quench protons to suppress their reactivity. ABTS+ cation scavenging potential of plant extracts was also investigated (Table 1B). Conversely to the results obtained with DPPH•, the aqueous extract was more efficient to inhibit ABTS radical among the extracts and Vit C with a scavenging percentage of 97.15 ± 0.71 % demonstrated the highest inhibitory effects. The difference in activity found here between the different tested extracts can be due to the difference in number of hydroxyl groups present in molecules extracted by each solvent. Indeed, previous studies showed that the higher the number of free hydroxyl groups present in polyphenols, the higher their scavenging potential [48]. Moreover, the position of the hydroxyl group also influences the activity of the molecule [49, 50]. The 50 % inhibitory concentrations (IC50) for the DPPH and ABTS+ radicals are displayed respectively in (Table 1A and B). From these results the ethanolic extract exhibited the lowest IC50 values (1.944 μg/mL and 3.871 μg/μL) both for the DPPH• and ABTS+ free radical scavenging efficiency. The chelation of transition metals such as iron is a crucial in the prevention of radical generation which damage target biomolecules. Indeed, iron acts as catalyst in the Harber-Weiss reaction to generate the highly reactive hydroxyl radical. FRAP assay was used to investigate the capacity of plant extracts to act as preventive antioxidants. Results are displayed on Table 2. All the tested samples demonstrated a preventive antioxidant potential with different capacity depending of the tested extracts. However, the aqueous extract showed the significant best ferric reducing power compared to the other samples. In addition to the ferric reducing antioxidant power, the phosphomolybdenum antioxidant capacity of plant extracts investigated to better elucidate the antioxidant mechanism demonstrated that the best antioxidant capacity was exhibited by the aqueous ethanol extract. Moreover, the antioxidant capacity of this extract was twice higher than that of Butylated HydroxyToluene (BHT) used as the standard antioxidant.Table 2 Phenolic metabolites content and antioxidant potential of different barks extracts of Syzygium guineense var marcarpum SGFH2O SGFEtOH SGFH2O/EtOH Polyphenol content Total phenol content (mg QE/g Ext.) 432.38 ± 11.41a 352.85 ± 3.83c 236.19 ± 3.09d Flavonoids (mg QE/g Ext.) 961.66 ± 7.63a 716.66 ± 23.62db 316.66 ± 12.58e Flavonols (mgQE/g Ext.) 25.12 ± 5.12a 18.15 ± 0.97b 4.02 ± 1.04c Antioxidant potential Phosphomolybdenum 113.88 ± 13.36a 278.88 ± 32.50a 226.66 ± 38.35c BHT FRAP 209.13 ± 3.17a 278.88 ± 5.75d 141.72 ± 1.57a 122.22 ± 2.5a (Total Antoxidant Capacity) Values are expressed as mean ± SD, In the same column, the values designated different letters are significantly different at p < 0.05 SGFH 2 O/EtOH syzygium guineense macrocarpum (barks) aqueous-ethanol, SGFEtOH syzygium guineense macrocarpum (barks) ethanol, SGFH 2 O syzygium guineense macrocarpum (barks) aqueous, mg QE/g Ext. milligram quercetin equivalent/gram of extract Concerning the total phenol content, the ethanolic extract presented the highest content compared to the others. The same trend was observed with flavonoids and flavonols content (Table 2). These results highlighted the close relationship between the richness of plant extracts in polyphenols and their antioxidant capacity even though the antioxidant capacity depends on the mechanism involved. This suggestion is supported by the correlation coefficients values between total phenol content and FRAP assay (0.988), FRAP and flavonoids (1.00) and flavonol content (1.00) (Tables 3 and 4). The nature of the polyphenol and its concentration significantly affect the antioxidant activity of the extract. Our results from HPLC profile (Fig. 1 and Table 5) demonstrated a variety of polyphenol is different concentration which include phenolic acids (p-coumaric acid; syringic acid), flavonoids (catechin and caffeic acid) and other phenolic compounds.Table 3 Correlation study between variables; (1) Correlation between scavenging potential and polyphenol metabolites; (2) correlation between enzymatic antioxidant and lipid peroxidation parameter from rat organs Variables DPPH ABTS Molyb Frap Flavo Pheto Flavonol DPPH 1 ABTS 0.381 1 Molyb 0.000 −0.810 1 Frap 0.195 0.781 0.390 1 Flavo 0.195 0.781 0.390 1.000 1 Pheto 0.193 0.795 0.410 0.988 0.988 1 Flavonol 0.195 0.781 0.390 1.000 1.000 0.988 1 Bivariate Spermann rho correlation. Bold values are: significant coefficient, p = 0.05 (bilateral test) Molyb phosphomolybdenum test; Flavonols flavonol assay; Phetot polyphenol assay; Flavonoids flavonoid assay; ABTS ABTS radical scavenging test; DPPH DPPH radical scavenging test; Per peroxidase; SOD superoxide dismustase; CAT catalase; MDA malonedialdehyde; GLU Glutathione; L liver; H heart; K kidney; B brain Fig. 1 HPLC chromatogram profile of Syzygium guineense var macrocarpum (barks); a: aqueous extract; b: Ethanol extract; c: Aqueous ethanolic extract Table 4 Correlation study between variables. Correlation between enzymatic antioxidant and lipid peroxidation parameters from rat organs Variables Per L Per H Per K Per B SOD L SOD H SOD K SOD B CAT L CAT H CAT K CAT B MDA L MDAH MDAK MDAB GLU L GLU H GLU K GLU B Per L 1 Per H 0.321 1 Per K 0.321 0.071 1 Per B 0.107 0.107 0.643 1 SOD L 0.250 0.036 0.786 0.643 1 SOD H 0.429 0.179 0.750 0.464 0.964 1 SOD K 0.107 0.286 0.500 0.536 0.893 −0.821 1 SOD B 0.893 0.107 0.429 0.107 0.429 0.607 −0.321 1 CAT L 0.679 0.214 0.357 0.071 0.214 0.393 0.000 0.821 1 CAT H 0.179 0.429 0.643 0.821 0.464 −0.250 0.429 0.179 0.286 1 CAT K 0.607 0.286 0.250 0.214 0.143 −0.107 0.357 0.286 0.321 −0.214 1 CAT B 0.286 0.250 0.679 0.857 0.500 −0.286 0.393 0.286 0.321 0.964 −0.143 1 MDA L 0.396 0.360 0.342 0.450 0.000 −0.180 −0.288 −0.505 0.577 −0.324 −0.090 −0.270 1 MDA H 0.342 0.234 0.126 0.036 0.487 −0.631 0.450 −0.595 0.649 −0.450 0.324 −0.414 0.191 1 MDA K 0.393 0.571 0.179 0.429 0.107 −0.250 −0.071 −0.286 0.000 −0.286 −0.036 −0.214 0.631 −0.018 1 MDA B 0.429 0.214 0.036 0.750 0.321 0.143 −0.429 −0.393 0.250 −0.429 −0.143 −0.464 0.811 −0.126 0.750 1 GLU L 0.179 0.214 0.786 0.750 0.571 −0.393 0.429 0.143 0.250 0.929 −0.107 0.964 0.054 −0.378 0.000 −0.250 1 GLU H 0.571 0.357 0.214 0.536 0.286 −0.143 0.143 0.643 0.536 0.357 0.214 0.571 0.288 −0.180 0.036 −0.500 0.500 1 GLU K 0.571 0.214 0.000 0.464 0.036 0.143 0.000 0.786 0.786 0.429 0.036 0.571 0.505 −0.523 0.000 −0.464 0.464 0.893 1 GLU B 0.500 0.143 0.357 0.536 0.107 0.071 −0.071 0.643 0.571 0.643 −0.107 0.786 0.144 −0.631 0.071 −0.250 0.750 0.821 0.857 1 Bivariate Spermann rho correlation. Bold values are: significant coefficient, p = 0.05 (bilateral test) Per peroxidase, SOD superoxide dismustase, CAT catalase, MDA malonedialdehyde, GLU Glutathione, L liver, H heart, K kidney, B brain Organoprotective effects of the extracts Oxidation of biomolecules is currently considered as the main molecular mechanism involved in the toxicity process that lead to cell death. The iron complex of the chelating agent nitrilotriacetic acid was used to induce lipid peroxidation. Our results show that Fe3+- NTA led to a significant increase of lipid peroxidation associated with SOD, catalase, and glutathione peroxidase activity depletion in all tissues assayed compared to the negative control. These results are in accordance with those of [51] which showed Fe3+-NTA to be nephrotoxic, hepatotoxic. Indeed, Fe3+- NTA may act through the generation of free radicals with simultaneous decrease in antioxidant defenses. Lipid peroxidation is commonly quantified in research studies by measuring the accumulation of the by-products that result from this process. One of these by-products is malondialdehyde (MDA). The results of the protective effects of plant extracts against lipid peroxidation (Fig. 2) show that this property varied according to the plant extract and tissue homogenate. All the extracts lowered significantly (p < 0.05) the level of MDA when compared to the negative control. However, the aqueous- ethanolic extract exhibited the best protective activity by lowering 93, 13 and 6 fold respectively the MDA content in the liver, kidney and brain homogenates comparatively to the negative control. Conversely, in the heart homogenates the ethanol counterpart was the most active inhibitory effects of lipid peroxidation. These results highlight the beneficial effect of these plant extracts since lipid peroxidation is a major problem for food industry as well as for human health and it is associated to many diseases. Moreover, the inhibition of lipid peroxidation is confirmed by the restoration and potentialization of SOD, catalase, and peroxidase activities in plant-treated homogenates.Fig. 2 Lipid peroxidation inhibiting potential of barks extracts on different organ homogenates. The results are expressed as mean ± SD; For each organ homogenate, bars designated different letters are significantly different at p <0.05; SGFH2O/EtOH: Syzygium guineense macrocarpum (barks) aqueous-ethanol; SGFEtOH: syzygium guineense var macrocarpum (barks) ethanol; SGFH2O: syzygium guineense macrocarpum (barks) aqueous; Vit C: vitamin C; NC: negative control; NoC: Normal control SODs are the first line of defense against oxidative stress among the highly sophisticated antioxidant system evolved by mammalian cells to cope with deleterious effects of ROS. The ability of the extracts to restore the SOD activity after oxidative stress induced are summarized in the Fig. 3. The ability of plant extracts to protect SODs is homogenate-dependent. In the liver, all the fractions exhibited a protective capacity (although not significant comparatively to the negative control). In the heart homogenate conversely, the ethanol extract was the most efficient among the tested extract whereas, the aqueous and aqueous-ethanolic counterparts restored more efficiently the enzyme activity in the brain and kidney homogenates respectively. The ability of the samples to protect the cells may be linked to their antioxidant content. Antioxidant molecules may act either as electron donors or hydrogen atom donors as pointed out by the DPPH• and ABTS+ radicals scavenging potential or by modulating the antioxidant enzymes activities. Besides the aforementioned mechanisms, metal transition chelation is not to be excluded to this process. Indeed, numerous studies [52, 53] have shown that flavonoids present in the investigated samples in a significant higher amounts are efficient iron chelators. Furthermore, they can also act as hydrogen donors and superoxide anion quenchers.Fig. 3 SOD protective effect of barks extracts on different organ homogenates. The results are expressed as mean ± SD; For each organ homogenate, bars designated different letters are significantly different at p <0.05; SGFH2O/EtOH: Syzygium guineense var macrocarpum (Barks) aqueous-ethanol; SGFEtOH: syzygium guineense var macrocarpum (barks) ethanol; SGFH2O: syzygium guineense var macrocarpum (barks) aqueous; Vit C: vitamin C; NC: negative control; NoC: Normal control The ability of the plant extracts to potentiate the activity of catalase was also investigated since SODs are assisted by catalase in the conversion of hydrogen peroxide to water and oxygen. Results demonstrated that the exposure of liver, heart, brain and kidney homogenates to Fe3+-NTA reduces significantly the catalase activity in the negative control (homogenate treated only by the oxidant) while the treatment with all the sample extracts reversed significantly the depletion of the catalase activity (Fig. 4) in all the homogenates except the kidney where only the aqueous-ethanolic extract was significantly efficient. The aqueous extract exhibited the best protective effect of catalase both in the liver and brain homogenates whereas the aqueous-ethanolic and ethanol counterparts potentiate more the catalase activity in the kidney and heart homogenates respectively.Fig. 4 Catalase protective effect of Barks extracts on different organ homogenates. The results are expressed as mean ± SD; For each organ homogenate, bars designated different letters are significantly different at p <0.05; SGFH2O/EtOH: Syzygium guineense var macrocarpum (barks) aqueous-ethanol; SGFEtOH: Syzygium guineense var macrocarpum (barks) ethanol; SGFH2O: syzygium guineense var macrocarpum (barks) aqueous; Vit C: vitamin C; NC: negative control; NoC: Normal control Removal of hydroperoxide which generates free radical is another way of preventing oxidation. Hydroperoxides can be reduced by enzymes such as glutathione peroxidase which cleared off the organism by eliminating organic hydroperoxide as well as hydrogen peroxide and peroxinitrites. The Fig. 5 displays the peroxidase protective potential of plant extracts against Fe3+ NTA-induced oxidative stress. From these results, aqueous extract was the most active sample both in the liver and kidney homogenates while the aqueous-ethanolic and ethanol extracts augmented more efficiently the activity of peroxidase in the heart and brain homogenates respectively. These results further confirmed the ability of these plant extract to protect biomolecules from oxidative damage since hydroperoxides decomposed rapidly to give many secondary products such as lipid free radicals which subsequently contribute to increase the oxidation of other molecules such as proteins, nucleic acids and other lipids leading to cancer, neurodegenerative pathologies and ageing [54].Fig. 5 Peroxidase protective effect of Barks extracts on different organ homogenates. The results are expressed as mean ± SD; For each organ homogenate, bars affected with different letters are significantly different at p <0.05; SGF H2O/EtOH: Syzygium guineense var macrocarpum (barks) aqueous-ethanol; SGF EtOH: Syzygium guineense var macrocarpum (barks) ethanol; SGF H2O: Syzygium guineense var macrocarpum (barks) aqueous; Vit C: vitamin C; NC: negative control; NoC: Normal control Reduced glutathione (GSH) is often considered as the body’s master antioxidant since it is used as a cofactor by multiple peroxidases, transhydrogenases, and glutathione S- transferases enzymes. Figure 6 exhibits the reduced glutathione levels in different organ homogenates. The aqueous extract showed the most beneficial effect (p < 0.05) compared to the other samples by repleting GSH levels in all the homogenates. Furthermore, this beneficial effect is higher than that of vitamin C and quercetin used as positive controls except in the liver homogenate. This result further confirms the ability of these plant extracts to protect vital organs from deleterious effects of ROS since GSH is largely known to minimize the lipid peroxidation of cellular membranes and other such targets that are known to occur with oxidative stress [55].Fig. 6 Glutathione protective effect of Barks extracts on different organ homogenates. The results are expressed as mean ± SD; For each organ homogenate, bars designated different letters are significantly different at p <0.05; SGFH2O/EtOH: Syzygium guineense var macrocarpum (barks) aqueous-ethanol; SGFEtOH: syzygium guineense var macrocarpum (barks) ethanol; SGFH2O: syzygium guineense var macrocarpum (barks) aqueous; Vit C: vitamin C; NC: negative control; NoC: Normal control The Spearman correlation (Table 5A) studied was assessed to determine the degree of association between free radical scavenging efficacy and polyphenolic metabolites content in the one hand and between enzymatic antioxidant, lipid peroxidation markers of different homogenates (Table 5B). In general, results showed a positive and significant correlation between ABTS and FRAP (0.781; 0.05) on one hand, and ABTS and total phenol content (0.795; 0.05), flavonols (0.781; 0.05) and flavonoid (0.781; 0.05) on the other hand (Table 5A). Few significant and positive correlation were found between some markers of protective effects of the plant extracts investigated mainly SOD and peroxidase (Table 5B).Table 5 Representation of the amounts of phenolic compounds in different bark extracts Phenol standard SGFH2O SGFEtOH SGFH2O/EtOH characteristics Standard retention time (min) A (mUA) Conc (mg/g DW) A (mUA) Conc (mg/g DW) A (mUA) Conc (mg/g DW) 3.4-OH benzoic acid 19.10 ± 00 Apigenin 33.49 ± 00 822207.6 186.91 26395.9 6.00 11129.0 2.53 Caffeic acid 25.67 ± 00 Catechin 23.48 ± 00 26496.4 1925.87 Eugenol 29.43 ± 00 Gallic acid 14.38 ± 00 O-coumaric acid 25.11 ± 00 OH-tyrosol 21.91 ± 00 12969.4 1198.09 P-coumaric acid 30.52 ± 00 21333.2 417.71 Quercetin 42.19 ± 00 Rutin 29.45 ± 00 12728.4 1071.65 Syringic acid 25.55 ± 00 53931.2 1337.02 16325.6 404.73 16427.9 407.26 Tyrosol 21.77 ± 00 Vanillic acid 25.27 ± 00 A area of the peak, Conc concentration of the standard in milligrams/grams of dried extract, SGFH 2 O/EtOH syzygium guineense var macrocarpum (Barks) aqueous-ethanol, SGFEtOH Syzygium guineense var macrocarpum (barks) ethanol, SGFH 2 O Syzygium guineense var macrocarpum (barks) aqueous The plurality of methods used addition to the complexity of oxidative stress and variability of results from each method, have led us to perform a principal component analysis (PCA) to better determine the best extracts purely from a statistical point of view. From this analysis and the obtained results indicated that flavonols, total phenol content, flavonoids, and FRAP, are strongly correlated to the F1 axis with contribution percentages of 18.917, for flavonols, flavonoids and FRAP, and 18.914 for the total phenol content whereas phosphomolybdenum, and DPPH are closely loaded to F2 axis with 37.858 and 58.711 % contribution respectively (Fig. 7).Fig. 7 Degree of association between antioxidant capacity and free radical scavenging potential of different extracts. Principal Component Analysis test. a A’: Distribution of the tests, projection of the extracts and tests around the F1 and F2 axis; b B’: Distribution of the tests (from organs), projection of the extracts and tests (from organs) around the F1 and F2 axis. Molyb: Phosphomolybdenum test; Flavonols: Flavonol assay; Phetot: Polyphenol assay; Flavonoids: Flavonoid assay; ABTS: ABTS radical scavenging test; DPPH: DPPH radical scavenging test. SGFH2O/EtOH: Syzygium guineense macrocarpum aqueous-ethanol; SGFEtOH: syzygium guineense macrocarpum ethanol; SGFH2O: syzygium guineense macrocarpum aqueous; Vit C: vitamin C; NC: negative control; NoC: Normal control. Per: peroxidase; SOD: superoxide dismustase; CAT: catalase; MDA: malonedialdehyde; GLU: Glutathione; L: liver; H: heart; K: kidney; B: brain From the biplot (Fig. 7a’) the overall antioxidant effectiveness of plant extracts taking into account all the performed assays is as follows SGFEtOH/H2O > SGFH2O > SGFEtOH. Therefore the aqueous ethanolic extract of S. guineense var macrocarpum could be considered as the best extract regarding the antioxidant and protective effects. Conclusion All the extracts (aqueous, ethanol and aqueous-ethanol) from S. guineense showed a concentration-dependent free radical. Similarly, the total antioxidant potential varied according to the solvent of extraction and the method used while the organo-protective properties also varied with regards to the homogenate. The HPLC characterization revealed the presence of six identified phenolic compounds belonging to different classes. However, syringic acid and apigenin were found in all the extracts. Although these plant extracts demonstrated important organo protective effect on all the tested homogenates by delaying or preventing lipid peroxidation and restoring enzymatic and non enzymatic markers activities, further studies need to be carried out to identify the active molecules and their mechanism of action. Abbreviations ABTS2,2 -Azinobis(3-ethylbenzthiazoline)- 6-sulfonic acid DPPH2,2-diphenyl-1-picrylhydrazyl 1,1-diphenyl-2- picrylhydrazyl radical EDTAEthylene diamine tetra-acetic acid FeCl3Ferric chloride FRAPFerric reducing antioxidant power assay H2O2Hydrogen peroxide HClHydrochloric acid HPLCHigh performance liquid chromatography MDAMalonaldialdehyde NTANitrilotriacetate PBSPhosphate buffer saline PCAPrincipal component analysis ROSReactive oxygen species SGF H2O/EtOHSyzygium guineense var macrocarpum aqueous-ethanolic extract (barks) SGFEtOHSyzygium guineense var macrocarpum ethanolic extract (barks) SGFH2OSyzygium guineense var macrocarpum aqueous extract (barks) SODSuperoxide dismutase TBAThiobarbituric acid TCATrichloroacetic acid UV raysUltraviolet rays Vit CVitamin C Acknowledgements The authors are grateful to Mr Ngansop Eric from the National Herbarium of Cameroon who harvested and identified the plant material. Funding This section is not relevant for this work. Availability of data and materials This section is not relevant for this work. Authors’ contributions FTN conducted the study assisted by MMB; RJN conducted HPLC analysis of the extracts under the supervision of AC: BNPC conducted research and the statistical analysis and PCA helped in building and correcting the manuscript, PCA designed the research co-directed the research work with NYJ and provided reagents. All the authors read and approved the final manuscript. Competing interests The authors declared no potential conflicts of interest with respect to the research authorship and/or publication of this article. Consent for publication All authors have agreed to authorship and publication. Ethics approval and consent to participate This section is not relevant for this work. ==== Refs References 1. Knock G Ward J Redox regulation of protein kinases as a modulator of vascular function Anti Redox Signal 2011 15 1531 1547 10.1089/ars.2010.3614 2. Verbon E Post J Boonstra J The influence of reactive oxygen species on cell cycle progression in mammalian cells Gene 2012 511 1 6 10.1016/j.gene.2012.08.038 22981713 3. Rizzo A Berselli P Zava S Montorfano G Negroni M Corsetto P Berra B Saeed N Khan M Shabbir M Antioxidant activity, total phenolic and total flavonoid contents of whole plant extracts Torilis leptophylla L BMC Complement Altern Med 2012 12 221 232 10.1186/1472-6882-12-221 23153304 4. Jacob-Ferreira A Schulz R Activation of intracellular matrix metalloproteinase-2 by reactive oxygen-nitrogen species: Consequences and therapeutic strategies in the heart Arch Biochem Biophys 2013 540 82 93 10.1016/j.abb.2013.09.019 24103691 5. Lo Conte M Carroll K The redox biochemistry of protein sulfenylation and sulfinylation J Biol Chem 2013 288 26480 26488 10.1074/jbc.R113.467738 23861405 6. Erica N Pialoux V Role of Oxidative Stress in the Pathogenesis of Sickle Cell Disease IUBMB Life 2012 64 72 80 10.1002/iub.584 22131167 7. Sosa V Moliné T Somoza R Paciucci R Kondoh H LLeonart M Oxidative stress and cancer: an overview Ageing Res Rev 2013 12 376 390 10.1016/j.arr.2012.10.004 23123177 8. Areti A Ganesh V Naidu V Kuma A Oxidative stress and nerve damage: Role in chemotherapy induced peripheral neuropathy Redox Biol 2014 2 289 295 10.1016/j.redox.2014.01.006 24494204 9. Duracková Z Some current insights into oxidative stress Physiol Res 2011 59 459 469 19929132 10. Favier A. Le stress oxydant: Intérêt conceptuel et expérimental dans la compréhension des mécanismes des maladies et potentiel thérapeutique. L’actualité chimique. Laboratoire Lésions des acides nucléiques, Centre d’Étude Nucléaire de Grenoble. 2003; 11-12: 108–115. 11. Munkacsy E Rea S The paradox of mitochondrial dysfunction and extended longevity Exp Geront 2014 56 221 233 10.1016/j.exger.2014.03.016 12. Yi-Fang C Jie S Xian-Hong W Ru-Hai L Antioxidant and proliferative activities of common vegetables J Agric Food Chem 2002 50 6910 6916 10.1021/jf020665f 12405796 13. Aruoma O methodological consideration for characterizing potential antioxidant actions of bioactive coumpounds in plant foods Mutat Res 2003 523 9 20 10.1016/S0027-5107(02)00317-2 12628499 14. Prabhakar N Kumar G Nanduri J Semenza G ROS signaling in systemic and cellular responses to chronic intermittent hypoxia Anti Redox Signal 2007 9 1397 1403 10.1089/ars.2007.1732 15. Biapa N Oben J Ngogang J Scavenging radical kinetic and Antianaemic Screening Properties of some Medicinal Plants used in Cameroon Int J Appl Res Nat Prod 2011 4 29 35 16. García-Nebot M Recio I Hernández-Ledesma B Antioxidant activity and protective effects of peptide lunasin against oxidative stress in intestinal Caco-2 cells Food Chem Toxicol 2014 65 155 161 10.1016/j.fct.2013.12.021 24365261 17. Behera R Goelb S Dasa S Bouzahzaha B Domannb N Mahapatrab A Sahoo A Van-Valdhuizena P Hosmanec N Evans T Dasa B Oxidative Stress in Alzheimer’s Disease: Targeting with Nanotechnology BBJNTCT 2014 2 18 26 18. Nanfack P Biapa N Pieme C Moor V Moukette B Ngogang J The in vitro antisickling and antioxidant effects of aqueous extracts Zanthoxyllum heitzii on sickle cell disorder BMC Compl Alternat Med 2013 13 162 10.1186/1472-6882-13-162 19. Biapa P Matei H Bâlici S Oben J Ngogang J Protective effects of stem bark of Harungana madgascariensis on the red blood cell membrane BMC Compl Alternat Med 2013 13 1 9 10.1186/1472-6882-13-1 20. Imaga N Shaire E Ogbeide S Akindele S In vitro biochemical investigations of the effects of Carica papaya and Fagara zanthoxyloides on antioxidant status and sickle erythrocytes Afr J Biochem Res 2011 5 226 236 21. Nwaoguikpe R Braide W The antisickling effects of some micronutrients and antioxidant vitamins in sickle cell disease management J Med Med Sci 2012 3 334 340 22. Pieme C Kumar S Ambassa P Suresh K Ngameni B Ngogang J Bhushan S Saxena K Induction of mitochondrial dependent apoptosis and cell cycle arrest in human promyelocytic leukemia HL-60 cells by an extract from Dorstenia psilurus: a spice from Cameroon BMC Compl and Alternat Med 2013 13 1 9 10.1186/1472-6882-13-1 23. Pieme C Ngoupayo J Nkoulou C Moukette B Nono B Ama V Minkande J Ngogang J Syzyguim guineense Extracts Show Antioxidant Activities and Beneficial Activities on Oxidative Stress Induced by Ferric Chloride in the Liver Homogenate Antioxidants 2014 3 618 635 10.3390/antiox3030618 26785075 24. Oloyede OI Durojaiye O Adewale OB Prevention of Fe2+ induced lipid peroxidation by aqueous extract of Garcina kola leaf in some rat tissues IPP 2013 1 128 132 25. Ashraf A Sarfraz RA Mahmood A Din M Chemical composition and in vitro antioxidant and antitumor activities of Eucalyptus camaldulensis Dehn. leaves Ind Crops Prod 2015 74 25 241 248 10.1016/j.indcrop.2015.04.059 26. kotamballi N Chidambara M Guddadarangavvahally K Jayaprakasha Ravendra P Studies on Antioxidant Activity of Pomegranate (Punica granatum ) Peel Extract Using in Vivo Models J Agric Food Chem 2002 50 4791 4795 10.1021/jf0255735 12166961 27. Badmus A, Adedosu T, Adeleke G, Akinboro H, Odeyemi I, Ayoola I, Hiss C. In Vitro and In Vivo Biochemical Evaluations of the Methanolic Leaf Extract of Garcinia kola. Hindawi Publishing Corporation International Scholarly Research Notices. 2014; http://dx.doi.org/10.1155/2014/391692. 28. Moukette B Pieme C Biapa P Njimou J Moor V Stoller M Bravi M Ngogang J Phenolic content of Hypodaphnis zenkeri and its antioxidant effects against Fenton reactions’ mediated oxidative Injuries on Liver Homogenate Antioxidants 2014 3 866 889 10.3390/antiox3040866 26785245 29. Malele R Moshi M Mwangi J Achola K Munenge R Pharmacological properties of extracts from the stem bark of Syzygium guineense on the ileum and heart of laboratory rodents Afr J Health Sci 1997 4 43 45 17583982 30. Ashebir M Ashenafi M Assessment of the antibacterial activity of some traditional medicinal plants on some food-borne pathogens Ethiopian J Health Dev 1999 13 211 216 31. Oketch-Rabah HA Dossaji SF Molluscicides of plant origin: Molluscicidal activity of some Kenyan medicinal plants South Afr J Sci 1998 94 299 301 32. Djoukeng JD Abou-Mansour E Tabacchi R Tapondjou AL Boud H Lontsi D Antibacterial triterpenes from Syzygium guineense (Myrtaceae) J Ethnopharmacol 2005 101 283 286 10.1016/j.jep.2005.05.008 15967609 33. Ior LD Otimenyin SO Umar M Anti-inflammatory and analgesic activities of the ethanolic extract of the leaf of Syzygium guineense in rats and mice IOSR J Pharm 2012 2 33 36 34. Noudogbessi JP Yédomonhan P Sohounhloué DC Chalchat JC Figuérédo G Chemical composition of essential oil of Syzygium guineense (Willd.) DC. var. guineense (Myrtaceae) from Benin Rec Nat Prod 2008 2 33 38 35. Molyneux P. The use of the stable free radical diphenylpicrylhydrazyl (DPPH) for estimating antioxydant activity. J Sci Technol. 2004; 26: 211–219. 36. Re R Pellegrini N Proteggente A Pannala A Yang M Rice-Evans C Antioxidant activity applying an improved ABTS radical cation decolorization assay Free Rad Biol Med 1999 26 1231 1237 10.1016/S0891-5849(98)00315-3 10381194 37. Benzie F Strain J The Ferric Reducing Ability of Plasma (FRAP) as a measure of “Antioxidant Power”: The FRAP Assay Anal Biochem 1996 239 70 76 10.1006/abio.1996.0292 8660627 38. Prieto P Pineda M Aguilar M Spectophotometric quantitative of antioxidant capacity through the formation of a phosphomolybdenum complex: specific application to the determination of vitamin E Anal Biochem 1999 269 337 341 10.1006/abio.1999.4019 10222007 39. Singleton V Draper D The transfer of polyphenolic compuonds from grape seeds into wine Am J Enol Vitic 1964 15 34 40 40. Zhishen J Mengcheng T Jianming W The determination of flavonoid contents in mulberry and their scavenging effects on superoxide radicals Food Chem 1999 64 555 559 10.1016/S0308-8146(98)00102-2 41. Kumaran A Karunakaran R In vitro antioxidant activities of methanol extracts of Phyllanthus species from India LWT 2007 40 344 352 10.1016/j.lwt.2005.09.011 42. Awai M Narasaki M Yanianoi Y Seno S Induction of diabetes in animals by parenteral administration of ferric nitrilotriacetate. A model of experimental hemochromatosis Am J Pathol 1979 95 663 73 377994 43. Igbal M Sharma MD Zadeh HR Hasan N Abdulla M Athar M Glutathione metabolizing enzymes and oxidative stress in ferric nitriloacetate (Fe-NTA) mediated in hepatic injury Redox Rep 1996 2 385 391 10.1080/13510002.1996.11747079 27406673 44. Misra H Fridovich I Estimation of superoxide dismutase J Biochem 1972 247 3170 3178 45. Sinha A Colorimetric assay of catalase Anal Biochem 1972 47 389 394 10.1016/0003-2697(72)90132-7 4556490 46. Ellmann GL Tissue sulfydryl group Arch Biochem Biophys 1959 82 70 77 10.1016/0003-9861(59)90090-6 13650640 47. Popovici C Saykova I Tylkowski B Evaluation de l’activité antioxydant des composés phénoliques par la réactivité avec le radical libre DPPH Revue de Génie IndustrieL 2009 4 25 39 48. Dai J Mumper J Plant phenolics: extraction, analysis and their antioxidant and anticancer Properties Molecules 2010 15 7313 7352 10.3390/molecules15107313 20966876 49. Igor P. Etude des activités biologiques de Fagara zanthoxyloides Lam. (Rutaceae). Thèse Pharmacie, Universite de Bamako, Faculte de Medecine et d'Ondonto-Stomatologie, 2002. p. 133. 50. Sroka Z Cisowski W Hydrogen peroxide scavenging, antioxidant and anti-radical activity of some phenolic acids Food Chem Toxicol 2003 41 753 758 10.1016/S0278-6915(02)00329-0 12738180 51. Sundaram S Kanniappan GV Kannappan P Enzymatic and non enzymatic antioxidant activity of Tabernaemontana divaricata R. Br. against DEN and Fe-NTA induced renal damage in wistar albino rats J Appl Pharm Sci 2015 5 033 037 10.7324/JAPS.2015.50506 52. Morel I Lescoat G Cogrel P Sergent O Pasdeloup N Brissot P Cillard P Cillard J Antioxidant and iron-chelating activities of the flavonoids catechin, quercetin and diosmetin on iron-loaded rat hepatocytes cultures Biochem Pharmacol 1993 45 13 19 10.1016/0006-2952(93)90371-3 8424806 53. Van-Acker S Bast A Van der Vijgh W Rice-Evans C Packer L Stuctural aspects of antioxidant activity of flavonoids Flavonoids in health and disease 1998 New York Marcel Decker 221 251 54. Haleng J Pincemail J Defraigne JO Charlier C Chapelle JP Le stress oxydant Rev Med Liege 2007 62 628 638 18069575 55. Joerg B Schulz L Seyfried J Dichgans J Glutathione, oxidative stress and neurodegeneration Eur J Biochem 2000 267 4904 4911 10.1046/j.1432-1327.2000.01595.x 10931172

PMC005xxxxxx/PMC5000503.txt

==== Front BMC Complement Altern MedBMC Complement Altern MedBMC Complementary and Alternative Medicine1472-6882BioMed Central London 131410.1186/s12906-016-1314-7Research ArticleEffects of intermittent pressure imitating rolling manipulation on calcium ion homeostasis in human skeletal muscle cells http://orcid.org/0000-0003-2062-1798Zhang Hong 00-86-18930566930zhanghongdoctor@sina.com 1Liu Howe Howe.Liu@unthsc.edu 2Lin Qing szlinqing@126.com 3Zhang Guohui yyyyzgh827@126.com 1Mason David C. david.mason@unthsc.edu 21 Yueyang Hospital of Integrative Chinese and Western Medicine Affiliated to Shanghai University of Traditional Chinese Medicine, 100 GanHe Road, Shanghai, 200437 China 2 University of North Texas Health Science Center, Fort Worth, 76107 USA 3 Suzhou Health College, Jiangsu, 215009 China 26 8 2016 26 8 2016 2016 16 1 31415 5 2016 23 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Homeostasis imbalance of intracellular Ca2+ is one of the key pathophysiological factors in skeletal muscle injuries. Such imbalance can cause significant change in the metabolism of Ca2+-related biomarkers in skeletal muscle, such as superoxide dismutase (SOD), malondialdehyde (MDA) and creatine kinase (CK). Measurements of these biomarkers can be used to evaluate the degree of damage to human skeletal muscle cells (HSKMCs) injury. Rolling manipulation is the most popular myofascial release technique in Traditional Chinese Medicine. The mechanism of how this technique works in ameliorating muscle injury is unknown. This study aimed to investigate the possible Ca2+ mediated effects of intermittent pressure imitating rolling manipulation (IPIRM) of Traditional Chinese Medicine in the injured HSKMCs. Methods The normal HSKMCs was used as control normal group (CNG), while the injured HSKMCs were further divided into five different groups: control injured group (CIG), Rolling manipulation group (RMG), Rolling manipulation-Verapamil group (RMVG), static pressure group (SPG) and static pressure-Verapamil group (SPVG). RMG and RMVG cells were cyclically exposed to 9.5-12.5 N/cm2 of IPIRM at a frequency of 1.0 Hz for 10 min. SPG and SPVG were loaded to a continuous pressure of 12.5 N/cm2 for 10 min. Verapamil, a calcium antagonist, was added into the culture mediums of both RMVG and SPVG groups to block the influx of calcium ion. Result Compared with the CNG (normal cells), SOD activity was remarkably decreased while both MDA content and CK activity were significantly increased in the CIG (injured cells). When the injured cells were treated with the intermittent rolling manipulation pressure (RMG), the SOD activity was significantly increased and MDA content and CK activity were remarkably decreased. These effects were suppressed by adding the calcium antagonist Verapamil into the culture medium in RMVG. On the other hand, exposure to static pressure in SPG and SPVG affected neither the SOD activity nor the MDA content and CK activity in the injured muscle cells regardless of the presence of verapamil or not in the culture medium. Conclusion These data suggest that the intermittent rolling pressure with the manipulation could ameliorate HSKMCs injury through a Ca2+ dependent pathway. Static pressure did not lead to the same results. Keywords Rolling manipulationHuman skeletal muscle cellCalcium ionSuperoxide dismutaseMalondialdehydeCreatine kinasehttp://dx.doi.org/10.13039/501100001809National Natural Science Foundation of China81574095,81173359Zhang Hong Key Developing Diciplines of Shanghai Municipal Commission of Health and Family Planning2015ZB0407Zhang Hong issue-copyright-statement© The Author(s) 2016 ==== Body Background Chinese medicine massage (also known as Tui Na) has been used over thousands of years as a natural therapy in Chinese clinical settings. Rolling manipulation is a technique in Chinese medicine massage. Its effects on a variety of medical problems, such as muscle pain, have been described in both ancient and modern Chinese medical books [1, 2]. The first book about Chinese Massage (including rolling manipulation) was introduced to western society in 1997 by Maria Mercati [3] and then detailed in many other books written in English including a recent one by Sarah Pritchard [4]. In both books, stimulation of Qi (vital energy) was considered as the mechanism of Chinese massage. The cellular biomechanical effects of Chinese massage, which is presumably more acceptable to western science is still scarcely studied. Our search of literature published in English on this topic only produced two relevant studies. Yi et al. [5] reported that the rolling manipulation could facilitate blood flow at the local area that received the manipulation. Yao et al. [6] found that Chinese massage is able to increase intracellular Ca2+ concentration in mast cells of immune system. In general, it is believed that understanding the mechanism of Chinese massage (including rolling manipulation) will help clinicians develop and/or improve the techniques in a more scientifically understandable way [5]. Rolling manipulation is a myofascial release techniques. To perform rolling manipulation in the standing position, the operator is to have his shoulder slightly abducted, elbow and wrist slightly flexed, forearm pronated, hand relaxed in naturally flexed position, with the hypothenar eminence pressing on the body surface of the area being treated on a patient. Performing the technique the operator will have his shoulder slightly more abducted, elbow extending, forearm fully supinating, and wrist slightly extending with their fingers still all naturally flexed. This is a cyclical procedure approximately two cycles per second. During rolling manipulation, the force is transferred to the treated area primarily through elbow extension and forearm supination (Fig. 1). The force produced by the operator’s upper limb will stimulate the body surface in a coordinated rhythmical pattern.Fig. 1 a Starting position of rolling manipulation. b Hand position changed during operating rolling manipulation Low back and neck pain are musculoskeletal injuries which manifest as muscle tension, joint stiffness and soft tissue changes with an incidence of more than 50 % in office workers [7]. Rolling manipulation is usually used in the musculoskeletal diseases in clinical settings, and has been confirmed to relieve muscular tension of gastrocnemius muscles by myotonometer [8]. In experimental studies, rolling manipulation on the gastrocnemius muscle is shown to dilate popliteal artery diameter, to decrease vascular resistance, and to increase the average velocity and local tissue blood flow as assessed by Ultrasonic Color Doppler Diagnostic System [9, 10]. Previously, we observed that rolling manipulation with 4.0 kg in maximum pressure, 120 times/min in frequency for 10 min in duration was the optimal condition to improve the increment rate of average volume flow of the popliteal artery [11]. Furthermore, we found that rolling manipulation could activate the secretion function of the human umbilical vein endothelial cells (HUVECs), and promote the synthesis and release of nitric oxide (NO) which is one of endogenous vascular relaxing factors for vasodilatation [12]. We have developed a cell mechanical loading system. In this system, the force curve of rolling manipulation could be imitated and fitted by the biological material test system (MTS, type 858; MTS Company, Eden Prairie, USA). Muscle cells could be loaded by the intermittent pressure imitating the pressure-time curve of rolling manipulation through air pressure [13]. Traditional Chinese Manipulation is effective in treating disease through stimulating the body surface in a rhythmical pattern. The manipulation force could be converted into its biological effects to improve clinical symptoms. However, the mechanism of how the manipulation force could initiate or trigger these biological effects is still unknown. Homeostasis imbalance of intracellular Ca2+ is believed to be one of the key checkpoints during skeletal muscle injuries [14, 15]. Under physiological conditions, Ca2+ concentration in the sarcoplasmic reticulum, endoplasmic reticulum and mitochondria of the skeletal muscle cells fluctuates in a small range and maintains at an equilibrium state [16]. Under pathological conditions, Ca2+ concentration in the cytoplasm of the skeletal muscle cells increases. Such Ca2+ imbalance is associated with the significant changes of the biomarkers of skeletal muscle metabolism such as decreased superoxide dismutase (SOD), increased malondialdehyde (MDA) and increased creatine kinase (CK) in the injury muscle cells [17]. Therefore, changes of these biomarkers in skeletal muscles could be used as an indicator of muscle injury. To relieve muscle spasm is an important criterion for the evaluation of the therapeutic effect in Chinese manipulation. The mechanical stimulation during the manipulation may further be converted to different biological effects to achieve its therapeutic effect [18]. The key structure responsible for such signal conversion is the mechanical pressure receptor. The potential biochemical structures involved in this process include the ion channels, G-protein, tyrosine kinase and integrin family, among which the ion channels aroused much research interest [19]. It has been reported that the mechanical force from the manipulation could stimulate the ion channels in the cells, which activate the relevant signal pathways [20]. These ion channels include Ca2+, Na+ and K+ channels in the cells, in which Ca2+ channel is the focus as detailed below. The Ca2+ channel, which is also named the dihydropyrimidine receptor (DHPR), has dual functions as the voltage sensor and L-type voltage-gated Ca2+ channel [21]. The channel could couple the cell membrane depolarization with the Ca2+ release from the sarcoplasmic reticulum, also could be the responder of mechanical stimulation [22, 23]. As an intracellular secondary messenger, Ca2+ plays an important role in signal transduction, and is necessary for many important enzymes to be activated. Therefore, Ca2+ might take part in receiving the mechanical stimulation,in causing the morphological and functional changes in cells, and in converting the mechanical stimulation into the biochemical signals in cells [24, 25]. Hands-on rolling manipulation has been practiced by doctors for centuries to treat their patients with musculoskeletal dysfunctions. However, how the biological mechanism of therapeutic effects is achieved through the mechanical manipulation is still unknown. The aim of this study was to investigate how the manipulation pressure/force could trigger its biological effects with special focus on the possible calcium ion-mediated effects in human skeletal muscle cells. Methods This is a study with cross-sectional design. Development of a novel cell mechanical loading system A newly developed mechanical pressure loading system for living muscle cells is shown in Fig. 2. The system consisted of a biological material test system (MTS, type 858; MTS Company, Eden Prairie, USA), a jig, a connecting rod shaft, a piston with two silicone compressing rings for sealing, a stainless steel cylinder as pressure vessel, and a pressure sensor (EVT100A; Yuran Sensor Technology Company, Shanghai, China). The pressure was generated within a stainless steel cylinder interfaced to MTS, a servo-hydraulic loading frame. The cell-culture dish was put on the bottom of the chamber. The chamber was completely closed to create a pressure chamber.Fig. 2 Schematic diagram of the mechanical pressure loading system for living muscle cells Curve fitting of rolling manipulation The pressure-time curve of rolling manipulation was recorded in the Manipulation Technique Parameter Analyzer (TypeII, Shanghai Research Institute of Traditional Chinese Medicine, China) when the operator was performing rolling manipulation. The data of the pressure-time curve were imported into the Waveform Editor in MTS, and MTS output the load to the Cell Mechanical Loading System imitating rolling manipulation. The full curve in Fig. 3 was monitored by the pressure sensor in the Cell Mechanical Loading System, which showed that the cells were cyclically exposed to the 9.5-12.5 N/cm2 of intermittent pressure imitating rolling manipulation (IPIRM) at a frequency of 1.0 Hz. The dotted curve in Fig. 3 showed that the cells were loaded at a continuous pressure of 12.5 N/cm2.Fig. 3 The full curve was the pressure-time curve of IPIRM recorded by the pressure sensor in the Cell Mechanical Loading System. The dotted curve was recorded under a continuous pressure Cell culture and establishment of injured cell model The human skeletal muscle cells (HSKMCs; US Type Culture collection warehousing, San Diego, USA) from the 4 – 8th generation of skeletal muscle cell strain were used for this study. All cells were kept in CO2 cell culture box (Biorad Company, Hercules, USA) at 37 °C in a humidified atmosphere containing 5 % CO2. HSKMCs were cultured in DMEM high-glucose medium (HyClone Company, Logan, USA) containing 4.5 g glucose, 100,000U penicillin, 100 mg streptomycin, and 3 % fetal calf serum (FCS; HyClone Company, Logan, USA) per liter. They were considered to be cultured successfully when the following four criteria were identified under an inverted microscope: 1. The shape of human skeletal muscle cells was spindle-shaped. 2. No floating cells were found which indicated that the cultured cells had a good capacity of cellular adherence to wall of the culture bottle. 3. The cell nuclei were oval-shaped without any sign of breaking out, dissolving, or pyknosis. 4. The culture bottles were clear without pollution. Once the HSKMCs grew up to the whole bottom of each culture bottle, they were harvested and divided into two portions in order to re-proliferate further down. The human skeletal muscle injury modeling cells were induced by dexamethasone according to the reference literature [26]. Some researches conformed that excessive dosage of dexamethasone could produce injury to muscle cells by suppressing cells proliferation, reducing SOD level, increasing MDA, and causing intracellular Ca 2+ overloading [27, 28]. When HSKMCs in the culture bottle showed good adherence, i.e., covering 80-90 % on the bottom of the bottle observed under microscope, the cultured cells were harvested and then the medium in the bottle was abandoned. The mixture of the fresh DMEM high-glucose medium and dexamethasone sodium phosphate injection (The 3rd Pharmaceutical Factory, Jiangshu, China) was added into the culture bottle, and the final concentration of Dexamethasone sodium phosphate injection was 2.5 g/L. The cells were then cultured in the incubator containing 5 % CO2 for 24 h at 37 °C. Groups and treatment of HSKMCs The normal HSKMCs were used as control normal group (CNG), and they were cultured in 12 dishes. The injured HSKMCs were future divided respectively into 5 following different groups with 12 dishes per group: control injured group (CIG), rolling manipulation group (RMG), rolling manipulation-verapamil group (RMVG), Static pressure group (SPG) and Static pressure-verapamil group (SPVG). CNG (control normal group) and CIG (control injury group) cells were cultured in the same conditions as RMG, RMVG, SPG and SPVG cells except being loaded pressure. RMG and RMVG cells were cyclically exposed to 9.5-12.5 N/cm2 of IPIRM at a frequency of 1.0 Hz for 10 min. SPG and SPVG cells were loaded to a continuous pressure of 12.5 N/cm2 for 10 min. In both RMVG and SPVG, verapamil hydrochloride injection (Ver; Wellhope Pharmaceutical Company, Shanghai, China), a calcium ion influx inhibitor, was added into the culture medium with a concentration of 10-5 mol/L. Procedure of measuring SOD activity, MDA content, and CK activity The medium were removed by aspiration from culture vessels of each group cells described above. 1 ml of 0.25 % trypsin (Jibco Company, Grand Island, USA) was added into culture vessels, which were placed in 37 °C incubator for approximately 1.5 min. The trypsin was removed by aspiration until HSKMCs appeared rounded when they were observed using an inverted microscope. 6.0 ml of DMEM high-glucose medium were added into culture vessels to terminate trypsinization process. HSKMCs were collected at 1000 r/min for 10 min, and preserved in the refrigerator at -20 °C. SOD activity, CK activity, and MDA content were quantified in the same experiment and in duplicates with the use of commercially available SOD, CK and MDA kits (Nanjing Jiancheng Bioengineering institute, Jiangsu, China). Statistical analysis All data were continuous data that were expressed as mean ± standard deviation x¯±s. One-way Analysis of Variance (ANOVA) with post-hoc multiple comparisons was conducted to analyze the differences between different groups. All the data were analyzed with software (Statistical Package for the Social Sciences, version15.0). A p-value of less than 0.05 was considered to be statistically significant. Results Rolling manipulation pressure-time curve effects on SOD activity of HSKMCs As shown in Table 1, the SOD activity in the injured HSKMCs in CIG was remarkably decreased as compared with that of the normal HSKMCs in CNG(P < 0.05), demonstrating a decreased SOD activity with the muscle cell injury. However, the SOD activity in RMG was significantly higher than that of CIG (P < 0.05), indicating that IPIRM could reverse the SOD decrease in the injured HSKMCs. Meanwhile, the SOD activity in RMVG was significantly decreased than that of RMG (P < 0.05), showing that the ameliorating effect of intermittent pressure on the SOD could be suppressed by the presence of the Ca2+ channel antagonist.Table 1 Comparison of SOD, MDA, and CK in different groups of HSKMCs Groups SOD (U/mg prot) MDA (nmol/mg prot) CK (U/mg prot) Numbers of cases n = 10 n = 12 n = 12 CNG 26.06 ± 6.92 1.69 ± 0.36 1.90 ± 0.43 CIG 17.63 ± 5.48* 2.90 ± 0.51* 2.48 ± 0.68* RMG 34.70 ± 3.80** 2.10 ± 0.72** 1.94 ± 0.70** RMVG 22.80 ± 5.71*** 2.49 ± 0.35 2.18 ± 0.68 SPG 19.65 ± 3.39*** 3.09 ± 0.72*** 2.44 ± 0.61 SPVG 17.08 ± 3.36 2.75 ± 0.46 2.55 ± 0.61 SOD superoxide dismutase, MDA malondialdehyde, CK creatinkinase, CNG control normal group, CIG control injured group, RMG rolling manipulation group, RMVG rolling manipulation-verapamil group, SPG static pressure group, SPVG static pressure-verapamil group. What comparing with CNG, *meant P < 0.05; What comparing with CIG, ** meant P < 0.05; What comparing with RMG, *** meant P < 0.05 The SOD activity in SPG was not different from that of GIG and SPVG, but was significantly lower than that of RMG (P < 0.05), indicating that the static pressure had no effect on SOD activity in the injured HSKMCs. Effect of rolling manipulation on MDA content of HSKMCs As shown in Table 1, the MDA content in the injured HSKMCs in CIG was significantly increased as compared with that of the normal HSKMCs in CNG (P < 0.05), demonstrating an increase of MDA after the muscle cell injury. The MDA content in RMG was remarkably decreased as compared with that of CIG (P < 0.05), indicating that IPIRM could reduce MDA content in the injured HSKMCs. Meanwhile, the MDA content in RMVG was not different from than that of CIG (P > 0.05), which showing that intermittent pressure did not reduce MDA content in the injured HSKMCs with the presence of the calcium antagonist. In other words, the effect of intermittent pressure on MDA content could be suppressed when the mechanical signal was blocked by the Ca2+ channel antagonist. The MDA content in the injured HSKMCs in SPG was not different from that of GIG and SPVG, but was significantly higher than that of RMG (P < 0.05), indicating that the static pressure had no effect on MDA content in the injured HSKMCs. Effect of rolling manipulation on CK activity of HSKMCs As shown in Table 1, the CK activity in the injured HSKMCs in CIG was obviously increased as compared with that of the normal HSKMCs in CNG (P < 0.05), demonstrating a CK release after the muscle cell injury. The CK activity in RMG was significantly lower than that of CIG (P < 0.05), indicating that IPIRM could ameliorate the CK release after the muscle cell injury in HSKMCs. Meanwhile, the CK activity in RMVG was not different from that of CIG (P > 0.05), showing that the ameliorating effect of the intermittent pressure on the muscle cell injury could be blocked by the presence of the Ca2+ channel antagonist. Furthermore, the CK activity of the injured HSKMCs in SPG was not different from that in GIG and SPVG, indicating that the static pressure had no effect on the CK activity of injured HSKMCs. Discussion Rolling manipulation in traditional Chinese Medicine may affect human tissue and structures through the mechanical effects. These mechanical effects can be converted into its biological effects to ameliorate the clinical symptoms. The muscle cells are the basic function units in human body, and the final target of the manipulation force. How the muscle cells recognize the rolling changes of the mechanical force, and then convert the signals into some kind of physiological and chemical signals which further causes a series of its biological effects is the key to explain the mechanism of the rolling manipulation. In our present study, the SOD activity, the MDA content and the CK activity were used as the biomarkers of the cultured muscle cell injury model and further examined after exposure to various experimental conditions. As compared with that of the normal HSKMCs in CNG, the SOD activity was significantly decreased while both the MDA content and the CK activity were evidently increased in the injured HSKMCs in CIG. With IPIRM, the SOD activity was increased whereas the MDA content and the CK activity were decreased in the injured HSKMCs in RMG as compared with CIG. However, these effects could be further blocked by the presence of the calcium antagonist Verapamil in the culture medium in RMVG. Similar phenomenon were observed in the previous studies where the biological effects of mechanical stimulation on the osteoblasts can partially be inhibited by the L-type calcium channel antagonist nifedipine [29, 30]. On the other hand, the static pressure in SPG and SPVG showed neither effect on SOD activity nor the MDA content and the CK activity in the injured HSKMCs as compared with CIG in our study. Effects on SOD Lipid peroxidation plays an active part in chronic skeletal muscle injuries. The accumulation of oxygen free radicals can cause an increase of the lipid peroxidation, which leads to the damage of the cell structure and functions [31]. Superoxide dismutase (SOD) is an enzymatic defense mechanism in the contingency procedure to defend the lipid peroxidation, and is also one of the major antioxidant enzymes in human body especially in musculature [32]. Our study showed that SOD activity in the injured HSKMCs in CIG was remarkably decreased than that of CNG. With the treatment of intermittent pressure imitating rolling manipulation, the SOD activity was significantly increased in the RMG. This indicated that IPIRM could increase the SOD activity and enhance the antioxidant ability of injured HSKMCs. This result is in agreement with the previous report that the SOD activity was increased by the manipulation intervention like intermittent pressure [33]. Furthermore, the SOD activity was significantly decreased in RMVG with the presence of verapamil in RMVG than that of RMG. In other words, the effect of intermittent pressure on the SOD activity in the injured muscle cells could be blocked by the presence of the calcium channel antagonist. This suggests that the responsive increase of the SOD activity in the injured HSKMCs treated with IPIRM depends on the Ca2+ intracellular influx. This result is similar to previous findings that Ca2+ concentration in the cytoplasm is negatively related to the activity of SOD [34, 35]. Furthermore, SOD activity in SPG was not different from that of GIG and SPVG, but was significantly lower than that of RMG, indicating that the static pressure had no effect on the SOD activity in the injured HSKMCs. Effects on MDA Cellular Malondialdehyde (MDA) content reflects the active status of oxygen free radicals in the injured tissue. Lipid peroxidation caused by oxygen free radicals is closely related to the skeletal muscle injury [36, 37]. Similar to tissue SOD activity, the MDA content is another biomarker commonly used for chronic skeletal muscle injury. In our study, the MDA content in the injured HSKMCs in CIG was significantly increased as compared with that of the normal HSKMCs in CNG, demonstrating the existence of the muscle cell injury in the CIG. However, the MDA content in the injured HSKMCs in SPG was not different from that of CIG and SPVG, indicating that the static pressure had no effect on ameliorating muscle cell injury in the injured HSKMCs. With intermittent pressure imitating rolling manipulation (IPIRM), the MDA content in RMG was remarkably decreased in the injured muscle cells as compared with that of CIG, indicating that the ameliorating effect of IPIRM in the injured HSKMCs may be achieved through an improvement of the dynamic balance of lipid peroxidation in the injured HSKMCs. Similar results were reported previously where the MDA content was significantly increased in rat triceps after exhaustive downhill run, which could remarkably be decreased by the delivery of vitamin E, one product against lipid peroxidation caused by the oxygen free radical [38]. The MDA content in RMVG was not different from that of CIG. The fact that the the ameliorating effect of IPIRM in the injured HSKMCs on the MDA content was blocked by the presence of verapamil in the culture medium suggests that this ameliorating process is dependent on the cellular influx of the Ca2+ as a messenger. Effects on CK The CK activity in the skeletal muscle cells is closely associated with the transmembrane flow of Ca2+ and excitation-contraction coupling [39, 40]. CK in the muscle cells involves mainly in the ATP synthesis. In our study, the CK activity was significantly increased in the injured HSKMCs in CIG as compared with that of the normal HSKMCs in CNG, reflecting the reliability of our muscle cell injury model. With the exposure to the intermittent pressure IPIRM, the CK activity returned to the same level as that of the normal control group in RMG. This gives direct evidence that IPIRM ameliorates the muscle cell injury in our HSKMCs. Meanwhile, the CK activity in RMVG was not different from that of CIG, showing that the intermittent pressure could not reduce CK activity in the injured HSKMCs with the presence of the calcium channel antagonist verapamil. In other words, the ameliorating effect of intermittent pressure on the muscle cell injury was partially blocked by the Ca2+ channel blocker. So it could be inferred that Ca2+ might play a triggering role for the biological effects of IPIRM as a so called messenger. Furthermore, the CK activity in the injured HSKMCs in SPG was not different from that of GIG and SPVG, indicating that the static pressure had no ameliorating effect on the muscle cell injury in the injured HSKMCs. Conclusions These results suggest that there is a significant correlation between the calcium ion and the biological effects of the IPIRM in the injured HSKMCs. The Ca2+ channel might work as a responder to the mechanical stimulation, and the Ca2+ influx might be a key to trigger some kinds of downstream processes to ameliorating the muscle cell injury. It could be assumed that intermittent pressure imitating rolling manipulation could initiate Ca2+ channel activation and consequently regulate the influx of Ca2+ into the injured HSKMCs, and ultimately improve the functions of these injured muscle cells. However, there is no significant difference in the biomarkers MDA or CK between the RMG and the RMVG groups. Whether the beneficial effects of rolling manipulation are partially or completely mediated by Ca2+ is still unknown based on current results. Therefore, further studies by testing other parameters will be needed in future. Abbreviations BCABicinchoninic acid Ca2+Calcium ion CIGControl injured group CKCreatinkinase CNGControl normal group CO2Carbon dioxide DMEMDulbecco’s minimum essential medium DMSODimethyl sulphoxide FCSFetal calf serum HSMCsHuman skeletal muscle cells HUVECsHuman umbilical vein endothelial cells IPIRMIntermittent pressure imitating rolling manipulation MDAMalondialdehyde MTSMechalical testing simulation NONitric oxide NP-40Nonidet P 40 PBSPhosphate buffered solution RMGRolling manipulation group RMVGRolling manipulation-verapamil group rpmRevolutions per minute SODSuperoxide dismutase SPGStatic pressure group SPVGStatic pressure-verapamil group We thank Weigang Gu of Umeå University Hospital in Sweden, for technical assistance. This study was supported by the National Natural Science Foundation of China (grant number: 81574095, 81173359), and the Key Developing Diciplines of Shanghai Municipal Commission of Health and Family Planning [grant number: 2015ZB0407]. Funding This work was supported by the China’s National Natural Science Foundation [grant number:81574095, 81173359], and the Key Developing Diciplines of Shanghai Municipal Commission of Health and Family Planning [grant number: 2015ZB0407]. Availability of data and materials Yes. All data and materials will be available. Authors’ contributions All authors listed have contributed significantly to this project. All authors read and approved the final manuscript. Authors’ information Hong Zhang, M.D, PhD, Chair of Rehabilitation Medicine Department, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine,Shanghai University of Traditional Chinese Medicine, No 110, Ganhe Road, Hongkou District, Shanghai (200437), P.R.China, Email: zhanghongdoctor@sina.com; Tel:00-86-18930566930. Howe Liu, PT, PhD, MD, Professor of Physical Therapy, University of North Texas Health Science Center, MET 530, 3500 Camp Bowie Blvd., Fort Worth, TX 76107,USA, Email: Howe.Liu@unthsc.edu, Tel:(817) 735-2457. Qing Lin, MD, MS, Physical Education Department, Suzhou Health College, Jiangsu 215009, P.R.China, Email:szlinqing@126.com. Guohui Zhang, MD, MS, Rehabilitation Medicine Department, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, No 110, Ganhe Road, Hongkou District, Shanghai (200437), P.R.China, Email:yyyyzgh827@126.com. David C. Mason, D.O., FACOFP, Professor of Department of Osteopathic Manipulative Medicine, University of North Texas Health Science Center, MET 560, 3500 Camp Bowie Blvd. Fort Worth, TX 76107,USA, E-mail: david.mason@unthsc.edu. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate Not applicable. The human skeletal muscle cell line (HSKMC) were used in this study, and they were purchased from US Type Culture collection warehousing (San Diego,USA). So the ethics approval and consent is not applicable in this study. ==== Refs References 1. Yan JT Tuina in Traditional Chinese Medicine 2009 2 Beijing China Press of Traditional Chinese Medicine 2. Shen GQ Illustrations of Tuina 2004 Shanghai Shanghai Scientific & Technical Publishers 3. Mercati M The Handbook of Chinese Massage: Tui Na Techniques to Awaken Body and Mind 1997 Rochester Healing Art Press 4. Pritchard M Tui N A Manual of Chinese Massage Therapy 2015 London Singing Dragon press 5. Yi HH Xu SX Qian YH Lattice Boltzmann simulation of blood flow in blood vessels with the rolling massage Chin Phys Lett 2005 22 12 3210 3213 10.1088/0256-307X/22/12/064 6. Yao W Yang H Li Y Dynamics of calcium signals and leukotriene C4 release in mast cells network induced by mechanical stimuli and modulated by interstitial fluid flow Adv Appl Math Mech 2016 8 1 67 81 10.4208/aamm.2013.m234 7. Kuijer P Van der Beek AJ Visser B Effect of job rotation on need for recovery, musculoskeletal complaints, and sick leave due to musculoskeletal complaints: a prospective study among refuse collectors Am J Ind Med 2005 47 394 402 10.1002/ajim.20159 15828075 8. Cheng YW Zhan HS Yuan WA Preliminary study on effects of rolling therapy on muscular tension of gastrocnemius in healthy subjects Shanghai J Tradit Chin Med 2007 41 7 42 43 9. Zhou XW Jing WD Zhu L Experimental observation of the effect of rolling manipulation of ding on hemodynamics in different frequency, pressure and duration Shanghai J Tradit Chin Med 1998 6 42 44 10. Liu XH Zhu L Zhou XW Tan YP Studies on Chinese massage-induced hemodynamics effect of arterial blood flow by color doppler flow image J Appl Biomech 1996 1 4 228 231 11. Zhang H Ma HS Men ZT Study on optimizing dynamics parameters in activating vital energy and blood circulation effects of rolling manipulation in Chinese massage Shanghai J Tradit Chin Med 2006 40 9 68 12. Ma HS Zhang H Yan JT The mechanism research of activating the circulation of Qi and blood by rolling manipulation based on cell mechanical loading device Lishizhen Med Materia Med Res 2015 26 2 493 496 13. Xu J Li KB Qu Q Huang Z Zhang H A biodynamic experiment of traditional rolling massage and its experimental device development Chinese J Tissue Eng Res 2014 18 42 6789 6794 14. Zorbas YG Kakuris KK Deogenov VA Inadequacy of calcium supplements to normalize muscle calcium deficiency in healthy subjects during prolonged hypokinesia Nutrition 2008 24 3 217 23 10.1016/j.nut.2007.11.004 18178379 15. Fraysse B Liantonio A Cetrone M The alteration of calcium homeostasis in adult dystrophic mdx muscle fibers is worsened by a chronic exercise in vivo Neurobiol Dis 2004 17 2 144 54 10.1016/j.nbd.2004.06.002 15474352 16. Higuchi M Distinct mechanistic roles of Calpain and caspase activation in neurodegeneration as revealed in mice over expressing their specific inhibitors J Biol Chem 2005 280 15 15229 15237 10.1074/jbc.M500939200 15699033 17. Berchtold MW Brinkmeier H Müntener M Calcium ion in skeletal muscle: its crucial role for muscle function, plasticity and disease Physiol Rev 2000 80 3 1215 65 10893434 18. Menard MB Immediate effect of therapeutic massage on pain sensation and unpleasantness: a consecutive case series Glob Adv Health Med 2015 4 5 56 60 10.7453/gahmj.2015.059 26421235 19. Ranade SS Syeda R Patapoutian A Mechanically activated Ion channels Neuron 2015 87 6 1162 79 10.1016/j.neuron.2015.08.032 26402601 20. Burkholder TJ Mechanotransduction in skeletal muscle Front Biosci 2007 1 12 174 91 10.2741/2057 17127292 21. Jung H Best M Akkus O Microdamage induced calcium efflux frombone matrix activates intracellular calcium signaling in osteoblasts via L-type and T-type voltage-gated calcium channels Bone 2015 76 88 96 10.1016/j.bone.2015.03.014 25819792 22. Baker MA Hetherington I Ecroyd H Analysis of the mechanism by which calcium negatively regulates the tyrosine phosphory1ation cascade associated with sperm capacitation J Cell Sci 2004 117 Pt 2 211 222 10.1242/jcs.00842 14676274 23. Vajda FJ Neuroprotection and neurodegenerative disease J Clin Neurosci 2002 9 1 4 10.1054/jocn.2001.1027 11749009 24. Pinton P Rizzto R Bcl-2 and Ca2+ homeostasis in endoplasmic reticulum Cell Death Diff 2006 13 8 1409 1418 10.1038/sj.cdd.4401960 25. Shoshan-Barmati V Israelson A Brdiczk AD The voltage-dependent anion channel (VDAC) function in intracellular signaling cell life and cell death Curr Pharm Des 2006 6 12 2249 2370 10.2174/138161206777585111 26. Zhang X Mei XY Bian HM Liao AQ Zhang CY Injury model of skeletal muscle cells Pharm J Chin People’s Liberation Army 2003 19 2 85 86 27. Qin J Du R Yang YQ Zhang HQ Zhou Y Effect of insulin on dexamethasone-induced ultrastructural changes in skeletal and cardiac muscle Biologia 2012 67 3 602 609 10.2478/s11756-012-0031-z 28. Yang H Wei W Menconi M Hasselgren PO Dexamethasone-induced protein degradation in cultured myotubes is p300/HAT dependent Am J Physiol 2007 292 R337 R344 29. Campbell JJ Bader DL Lee DA Mechanical loading modulates intracellular calcium signaling in human mesenchymal stem cells J Appl Biomater Biomech 2008 6 1 9 15 20740441 30. Peake MA Cooling LM Magnay JL Thomas PB El Haj AJ Selected contribution: regulatory pathways involved in mechanical induction of c-fos gene expression in bone cells J Appl Physiol (1985) 2000 89 6 2498 2507 11090608 31. Lee KR Cronennett JL Shlafer M Effect of superoxide dismutase plus catalase on Ca2+ transport in ischenfic and reperfused skeletal muscle J Surg Res 1987 42 1 24 32 10.1016/0022-4804(87)90060-6 3807351 32. Amir Aslani B Ghobadi S Studies on oxidants and antioxidants with a brief glance at their relevance to the immune system Life Sci 2016 146 163 173 10.1016/j.lfs.2016.01.014 26792059 33. Liu CZ Lei B Effect of Tuina on oxygen free radicals metabolism in patients with chronic fatigue syndrome Zhongguo Zhen Jiu 2010 30 11 946 948 21246855 34. Giladi M Tal I Khananshvili D Structural features of ion transport and allosteric regulation in sodium-calcium exchanger (NCX) proteins Front Physiol 2016 7 30 10.3389/fphys.2016.00030 26903880 35. Vay L Hernández-Sanmiguel E Santo-Domingo J Lobatón CD Moreno A Montero M Alvarez J Modulation of Ca(2+) release and Ca(2+) oscillations in HeLa cells and fibroblasts by mitochondrial Ca(2+) uniporter stimulation J Physiol 2007 580 Pt 1 39 49 10.1113/jphysiol.2006.126391 17234694 36. Oredsson S Qvarfordt P Plate G Polymorphonuclear leucocytes increase reperfusion injury in skeletal muscle Int Angiol 1995 14 1 80 88 7658110 37. Luo XX Ogata H Xu X Ishitobi F Protective effect of tetramethylpyrazine on ischemic neuronal damage in the gerbil hippocampus No To Shinkei 1994 46 9 841 846 7999441 38. Wang XT Tian Y Xu WX Cui LH Xiang SY Lü SC Protective effects of modeled superoxide dismutase coordination compound (MSODa) against ischemia/reperfusion injury in rat skeletal muscle Cell Physiol Biochem 2015 37 2 465 476 10.1159/000430369 26315464 39. Mendonça LR Joviliano EE Ramalho FS Ramalho LN Evora PR Piccinato CE Bradykinin impairs and HOE 140 does not protect rat hindlimb skeletal muscle against tourniquet-induced reperfusion injury J Invest Surg 2016 29 1 13 19 10.3109/08941939.2015.1041656 26375056 40. Balnave CD Thompson MW Effect of training on eccentric exercise-induced muscle damage J Appl Physiol (1985) 1993 75 4 1545 1551 8282602

PMC005xxxxxx/PMC5000504.txt

==== Front BMC Womens HealthBMC Womens HealthBMC Women's Health1472-6874BioMed Central London 33710.1186/s12905-016-0337-zResearch ArticleA dyadic approach to understanding the impact of breast cancer on relationships between partners during early survivorship http://orcid.org/0000-0001-6893-3542Keesing Sharon + 61 08 9266 3630S.Keesing@curtin.edu.au 1Rosenwax Lorna L.Rosenwax@curtin.edu.au 2McNamara Beverley Bev.McNamara@curtin.edu.au 31 School of Occupational Therapy and Social Work, Curtin University, GPO Box U1987, Perth, WA 6845 Australia 2 Deputy Pro Vice-Chancellor, Health Sciences, Curtin University, Perth, WA Australia 3 Adjunct Professor, Curtin University, Perth, WA Australia 25 8 2016 25 8 2016 2016 16 1 5730 1 2016 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The shared impact of breast cancer for women and their male partners is emerging as an important consideration during the experience of a breast cancer diagnosis, particularly during survivorship. This study aimed to explore the experiences of women and their partners during early survivorship and contributes a range of insights into the lives of those intimately affected by breast cancer. Methods In-depth interviews were completed with Australian women survivors of breast cancer (n = 8) and their partners (n = 8), between six months and five years following cessation of treatment. Questions included a focus on the women and their partners’ daily experiences during early survivorship, including the management of ongoing symptoms, engagement in leisure and social interests, returning to work, communicating with each other, maintenance of the current relationship and other important roles and responsibilities. Thematic analysis was employed to determine key themes arising from the dyadic accounts of women and their partners’ experiences during early breast cancer survivorship. Results Women and their partners experienced many changes to their previous roles, responsibilities and relationships during early breast cancer survivorship. Couples also reported a range of communication, intimacy and sexuality concerns which greatly impacted their interactions with each other, adding further demands on the relationship. Three significant themes were determined: (1) a disconnection within the relationship - this was expressed as the woman survivor of breast cancer needing to prioritise her own needs, sometimes at the expense of her partner and the relationship; (2) reformulating the relationship - this reflects the strategies used by couples to negotiate changes within the relationship; and (3) support is needed to negotiate the future of the relationship - couples emphasised the need for additional support and resources to assist them in maintaining their relationship during early survivorship. Conclusion It can be concluded that the early survivorship period represents a crucial time for both women and their partners and there are currently limited options available to meet their shared needs and preferences for support. Findings indicate that a suitable model of care underpinned by a biopsychosocial framework, access to comprehensive assessment, timely support and the provision of targeted resources are urgently needed to assist women and their partners during this critical time. Keywords QualitativeBreast cancerSurvivorPartnerDyadsRelationshipsissue-copyright-statement© The Author(s) 2016 ==== Body Background Breast cancer is one of the most common cancers affecting women worldwide [1]. Advances in early detection and improved treatments have resulted in almost 90 % of women in Australia achieving a five-year survival [2]. The period following cessation of treatment, ‘survivorship’, is increasingly being recognised as an important time in the care of women diagnosed with this disease, due, in part, to the many physical, psychological and emotional sequelae of breast cancer [3]. In addition, the usual treatment regimes offered to manage breast cancer (e.g. surgery, chemotherapy, radiotherapy, adjuvant hormone therapy or combinations of these methods) can produce significant physical, psychological and emotional consequences for women in the longer term [4, 5]. Supportive care to address the consequences of breast cancer during survivorship has historically been focussed on the range of physical problems such as pain, lymphoedema, cognitive impairment, fatigue, premature menopause, sleep disturbances and other chronic health conditions [6, 7]. Also recognised are a range of psychological issues relating to a diagnosis of breast cancer including; changes in body image and self-identity, fear of recurrence, mood disturbances and significant disruption to activities, roles and relationships [8–11]. Internationally, targeted care during survivorship is increasingly recognised as critical to successful outcomes following a diagnosis of breast cancer. However, great diversity exists regarding service delivery models, the use of clinical guidelines, needs assessment tools, treatment summaries, survivorship care plans and care co-ordination [12–15]. Recent studies have also begun to explore other approaches to care including the use of self-management strategies, use of a chronic disease management approach, and the use of patient navigators [16–18]. Research findings indicate that a more focussed approach to comprehensive survivorship care is essential, with targeted interventions developed to address the unique and individual needs of women during this time [19–22]. Some progress has been made to evaluate the benefits of these interventions with promising results [23–26]. While the priority for survivorship care has been targeted towards women who are recovering from breast cancer, there is a recognition that the partners of women may also be considerably impacted by the experience of a breast cancer diagnosis [27–30]. Commonly reported concerns of partners during survivorship include a lack of information and education about survivorship, difficulty managing the expectations they have of themselves, difficulty coping with changes in the relationship with their partner, and problems re-adjusting to their previous role and responsibilities within the family [27, 31–33]. The shared experience of breast cancer may also create ongoing psychological issues for partners long after the cessation of treatment, including emotional withdrawal, guilt, anxiety, depression, difficulty communicating feelings of loss and grief, and fears of disease recurrence [5, 34, 35]. Partners may experience the same or higher levels of psychological distress as women and these may contribute to psychiatric issues in the longer term [36–38]. Supportive care which has focussed on the partners of women affected by breast cancer is predominantly confined to the period of diagnosis, treatment and end of life care [39–41]. However, several recent studies have explored the experiences and potential needs of partners during early survivorship [32, 38, 42, 43]. Women’s health and well-being can be significantly affected by their partner’s responses and unmet needs in the longer term [44, 45]. The potential for communication break-down, relationship worries and intimacy concerns between couples during survivorship is increased, hence it was found to be vital to consider the needs of both women and partners across the entire continuum of care, being diagnosis, treatment and survivorship [32, 46]. Cessation of treatment marks a milestone in the breast cancer journey yet many women report increased difficulties at this time as a result of less formal supports evident, fewer appointments with medical and health professionals, and the expectation that life will return to ‘normal’. Many women and partners find that life does not return to their previous level of function or routines and they are often unprepared for resultant changes [47, 48]. For women, the expectation is that their partner will move from caregiver and support person to their usual role, routines and responsibilities experienced before the breast cancer event. The literature reports inconsistencies regarding the impact of the breast cancer experience on relationships during this time. Some studies report an exacerbation of women and their partners’ existing problems relating to the expression of emotions, less open communication and changes in the usual resolution of problems, all of which may lead to increased stress and conflict [33, 49]. Partners may not respond in a helpful way due to their own distress, resulting in further communication and relationship difficulties [50, 51]. Conversely, several studies found that a diagnosis of breast cancer resulted in positive changes with couples becoming closer, perhaps from the development of sophisticated communication skills required to manage the challenges of the diagnosis and treatment [28, 52]. Our study supports recent literature which calls for further exploration of the interactions between women and their partners during diagnosis, treatment and survivorship to further understand this complex phenomenon [40, 53]. Specifically, we focus on the early survivorship period as there is a lack of strong evidence to understand the challenges experienced during this critical time. Some authors state that women and their partners should be considered as a ‘dyad’- with each person bringing their own experiences and coping strategies to the partnership, but with an interdependent approach to managing their relationship during survivorship [39, 53–57]. Our study suggests that the dyadic approach provides a comprehensive and in-depth view of survivorship and aims to extend the existing knowledge of this critical period for both women and their partners. Survivorship models of care and the Australian context Since the publication of the Institute of Medicine’s (2006) report ‘From cancer patient to cancer survivor: lost in transition’, there has been an increased focus on research and evaluations dedicated to the improvement of models of care and guidelines, as well as services and tools directed to survivors of cancer worldwide [58, 59]. In Australia, there continues to be considerable variation regarding the models of care offered to women survivors of breast cancer. These include specialist (oncologist) led consultations, primary care (physician or general practitioner) led services, shared care (often using a clinic-based model) directed by nurses, and patient initiated models [60–62]. The range of services offered to women is also varied according to the preferred model of care, location, public versus private health service coverage and the availability of suitably experienced health professionals. Consistency regarding the use of essential tools including survivorship care plans (SCP’s), treatment summaries and improved co-ordination of care is needed [62]. There are also limited available resources targeted towards the partners and families of women survivors of breast cancer during survivorship, with an increasing recognition that holistic models of care must consider the needs of partners and families when developing resources [63, 64]. In 2015, the Clinical Oncology Society of Australia (COSA) called for urgent attention to recognise the limitations of current survivorship practices and effect a range of improvements to survivorship care in Australia [65]. Further research must be directed towards improving the range of supports directed at partners and couples to address ongoing concerns. Aims The aims of the study were to: identify changes in the way couples communicate with each other during early survivorship; determine the behaviours and actions used by women and their partners in maintaining their relationship during early survivorship; and identify the needs and supports required by women and their partners during early survivorship. Methods The research used a dyadic interview methodology to explore and understand the experiences of couples during early survivorship of breast cancer. The use of dyadic interviews offers a range of benefits regarding the phenomena of concern [66–68]. Demonstration of both consensus and disparity between the interviewees, corroboration, improved levels of comfort and support between participants, observations regarding non-verbal behaviours, and a broader scope of the experience may all be evident using this technique [69]. The advantages of dyadic interviewing extend further to allow insight into how both individuals react and respond within the dyad, providing an alternative interpretation of the experience [70]. There are a growing number of studies utilising a dyadic approach to consider the experience of cancer for partners and spouses [39, 51, 71]. The benefits of a dyadic approach are relevant for exploring breast cancer survivorship, as during this period women and their partners usually need to negotiate and reconsider their previous relationship, routines and responsibilities. Dyadic interviewing has some potential disadvantages such as withholding of information due to the presence of an intimate partner, disagreement and interviewer bias [70]. The use of peer review, member checking and a reflexive journal were strategies used to minimise potential bias [72]. Well-developed interview techniques were also used to ensure each participant had adequate time to consider questions and acknowledge potential disagreements. In-depth interviews of women (n = 8) and their partners (n = 8) were completed, with six couples interviewed together and the remaining two couples interviewed individually due to scheduling difficulties. All participants were asked to describe their experiences regarding diagnosis, treatment and survivorship of their (or their partner’s) breast cancer with particular emphasis on the period following cessation of treatment (early survivorship) [73]. In-depth interviews allowed the researcher to ‘have a conversation’, listen, understand and make sense of the participant’s experience of the phenomena they were describing [74, 75]. Interview questions were developed following review of the literature [76, 77]. The questions were further refined following a pilot completed with a non-participant couple. The first author commenced each interview with a series of demographic questions, including age, occupation, level of education and marital status, which assisted to build rapport with each participant. Demographic information is presented in Table 1. Open-ended questions about the women’s experiences during diagnosis and treatment were completed with prompting questions to target the thoughts and feelings of the particular period in the participants’ life [78]. Further questions were asked regarding their experiences following the conclusion of treatment and the transition to survivorship (Table 2).Table 1 Demographics of women and men participants Participant Current age range (in years) Education Marital status Parenting and number of children living at home Partner interviewed separately Date of diagnosis Time since treatment completed Treatment Service type Religious or cultural background 1 45–50 University Degree Married Yes/2 No May 2011 3 years Bilateral mastectomy, chemotherapy, hormone therapy, preventative hysterectomy, Breast reconstruction Private Nil identified 2 45–50 University Degree Married Nil identified 3 35–40 Year 12 Married Yes/2 No October 2012 1 year Bilateral mastectomy, chemotherapy radiotherapy, hormone therapy, breast reconstruction Private Nil identified 4 30–35 Year 12 Married 10 months Nil identified 5 40–45 University Degree Married No Yes April 2013 1 year 3 months Unilateral lumpectomy, chemotherapy radiotherapy, hormone therapy Private Nil identified 6 45–50 University Degree Married Nil identified 7 45–50 Year 10 Married Yes/1 No May 2009 5 years Unilateral lumpectomy, chemotherapy radiotherapy, hormone therapy Public Nil identified 8 45–50 Not known Married 9 50–55 Diploma Married Yes/2 Yes August 2013 1 year Unilateral lumpectomy, chemotherapy, radiotherapy, hormone therapy Mix Nil identified 10 50–55 University Degree Married Nil identified 11 50–55 University Degree Married Yes/0 No October 2012 2 years Unilateral lumpectomy, radiotherapy Public Jewish 12 50–55 Not known Married 13 45–50 Year 12 Married Yes/1 No July 2012 2 years Bilateral lumpectomy, chemotherapy, Mastectomy, hormone therapy Private Nil identified 14 45–50 Year 12 Married 2 months 15 50–55 University Degree Married Yes/2 No February 2013 1 year Unilateral lumpectomy, Chemotherapy, Unilateral mastectomy, hormone therapy Mix Nil identified 16 50–55 University Degree Married 6 months Table 2 Questions for women participants 1. What follow up care has been arranged for you e.g. doctor’s visits, tests, medication reviews? 2. What sort of ongoing problems or symptoms are you experiencing and how do you manage these? 3. What are the long term effects of the cancer/medications/treatment? 4. Were you given a survivorship care plan- what does it contain? Do you have a copy of it? How has it been used? 5. Has your life returned to the way it was previously? If not, how have your roles and responsibilities changed since finishing your cancer treatment? 6. Have your relationships with others (partner, family members) changed since the treatment finished? How? 7. What might be some potential positives to come out of the cancer experience? 8. Have you had any problems with resuming work? If not working, how do you spend your days currently? 9. Can you describe any resources or services that you are currently using and are these successful? Do you participate in a support group- what is this/is it effective for your needs? Are you satisfied with the resources and supports you are currently using- why/why not? 10. Do you feel that your partner is experiencing any issues following the completion of treatment? What are these? 11. What would your recommendations be for other cancer survivors? 12. Do you think that having cancer has changed you as a person and in what way? 13. How have your future plans and goals changed as a result of the cancer and or treatment? Questions for partners 1. Now that treatment has finished for your partner, what’s your daily routine? How have your roles and responsibilities changed? Are you currently working? If not working, how do you currently spend your days? 2. Does your partner experience any ongoing problems or symptoms? Do these problems impact you and have you experienced any changes in your relationships with others (partner, family members) since the treatment finished? 3. Was your partner given a survivorship care plan- what does it contain? Do you have a copy of it? 4. Can you describe how the SCP has been used during this period? Was it utilised to identify any issues for you personally as well as your partner? 5. What might be some potential positives to come out of the cancer experience? 6. Has your life returned to the way it was previously, if not how has it changed? 7. Can you describe any supports that you are currently using (with or without your partner) and are these successful? Are you satisfied with the resources and supports you and your partner are currently using- why/why not? 8. Can you identify any needs that you personally feel have not been met? 9. Can you recommend any changes/improvements in services for the partners of cancer survivors? 10. Do you think that being the partner of a cancer survivor has changed you in any way? Have your future plans and goals changed as a result of the cancer and/or treatment? Focus was directed towards the daily experiences of each participant including the management of ongoing symptoms, mood, engagement in leisure, hobbies and interests, social activities, returning to work, communication with others, relationships and current roles (parent, partner, worker and friend). The questions were rephrased for the woman’s partner. Each interview commenced with the woman initially and then moved to her partner; however, participants were invited to contribute at any stage of each other’s interview. Each interview (between 45 and 90 min per participant) was conducted by the first author face to face, recorded and transcribed using electronic media [79]. A numeric code and pseudonym was assigned to each participant to maintain confidentiality of data. Sampling and recruitment Purposive methods were used to recruit eight women who identified as breast cancer survivors and their eight partners (all men); living in Perth, Western Australia [80]. Participant women were included if they met the stated inclusion criteria of age (35–70 years), had completed their treatment for breast cancer (excluding adjuvant hormone treatment) between six months and five years previously and spoke English. Purposive recruitment was identified as a strength to the study as this allowed women and their partners to offer their own unique perspectives on how the early survivorship experience affected their lives, both from the perspective of the individual as well as part of a dyad [81]. Potential women participants were excluded if they were receiving ongoing active treatment (e.g. surgery to remove a tumour, chemotherapy, radiotherapy) or palliative care. Participant women were recruited using a variety of strategies including written invitations on a network home page, community newspaper, local breast cancer network, community radio station and flyers posted on University noticeboards. Partners were invited to be interviewed if they identified as having an ongoing and significant relationship (married or defacto) with their wife/partner. They were asked to be involved in the study at the initial contact with participant women. All participants were provided with an information brochure outlining the purpose of the study, their time commitment to complete an interview on a voluntary basis, an assurance of confidentiality, benefits of the study, potential for discomfort and the opportunity to withdraw at any time. Participants were also provided with information regarding telephone support services should they require assistance following completion of the interview, as it was acknowledged that some of the questions might have elicited negative memories regarding previous experiences. Interviews were conducted either in the participant’s home, place of work, or at the first author’s workplace. Written informed consent was obtained from all participants in the study. Ethical approval from the Human Research Ethics Committee of Curtin University was obtained prior to commencement of data collection (Approval number: HR 51/2014). Data analysis Each transcript of the interviews was imported into NVivo © and this software was used to organise and categorise information from the participants. Thematic analysis was used to analyse the content of interviews using a six step process devised by Braun and Clark [82] and widely used in the qualitative literature. The first author read each of the transcripts line by line repeatedly to understand what was being stated by each of the respondents. The next step of the thematic analysis involved assigning a ‘description’ for each idea, event, reflection or phenomena discussed by the participant using an inductive approach [83]. These descriptions were then reviewed and further categorised into preliminary ‘themes’. Preliminary themes were refined across the three authors, provided with a defined title and finalised. Saturation of data was determined by the authors following this process as no new or emerging themes were discovered [74]. Trustworthiness Trustworthiness of the research was achieved using multiple methods. Peer review was utilised to discuss the development and progress of the research following interviews and during data analysis [84]. Member checking was used to confirm the authenticity of each transcript. Several participants made adjustments to the transcript following this opportunity. Memos and field notes were completed following each interview and contributed to the development of an audit trail [85]. Results A range of demographic similarities was evident among the group of participants. The mean age of women was 47 years (ranging from 38 to 52 years) and their partners 48 years (ranging from 34 to 53 years). All couples were married. Most women had secondary schooling and/or a university degree (n = 7). Similarly, six of the eight male participants had completed secondary schooling and/or a university degree. All women and their partners were currently working in paid employment. The mean time since completion of treatment was two years and two months, with a range of one year to five years. Participant women and their partners spoke openly and in-depth about their experiences and challenges during survivorship, with three distinct themes established following analysis: (1) a disconnection within the relationship - this was expressed as the woman survivor of breast cancer needing to prioritise her own needs, sometimes at the expense of her partner and the relationship; (2) reformulating the relationship - this reflects the strategies used by couples to negotiate changes within the relationship; and (3) support is needed to negotiate the future of the relationship - couples emphasised the need for additional support and resources to assist them in maintaining their relationship during early survivorship. The findings from this study support the extensive published literature regarding the physical and cognitive challenges experienced by women survivors of breast cancer. These included: changes to body image and identity, fatigue, sleep difficulties, pain, loss of range of movement in the affected limb, as well as a variety of cognitive symptoms including short term memory loss, concentration difficulties and poor motivation [86–91]. However, the use of a dyadic interviewing strategy presented a range of further issues impacting the relationships between women and their partners during early survivorship. The themes arising from these findings offer a unique ‘shared’ perspective of a couple’s experience during this time. A disconnection within the relationship The first theme identified a range of personal and relationship changes experienced between couples during early survivorship. Most women reported that the experience of surviving breast cancer resulted in a need to always think of oneself and prioritise personal needs, before anyone else’s. They felt this changed the way they responded to others, especially their partner, which was often detrimental to the relationship. Describing this as a form of ‘selfishness’, coupled with her need for privacy, Fran (one year and three months post-treatment) describes her thoughts:I just want my space, I want a good night’s sleep …it’s just so important. I found that with breast cancer in one aspect it’s made me more selfish. I’m looking after myself rather than looking at whether he’s OK or not… I don’t really care whether you’re OK…I just want to take care that I’m OK. The period of early survivorship created a sense of disempowerment and women felt a need to regain control in the new environment of ‘survivorship’. Women stated that this resulted in a need to suppress their thoughts and feelings, as a strategy for coping with lost ‘control’. This might be explained as a form of ‘self-protection’ and resulted in an emotional disconnection with their partner and the relationship. Danielle (one year and ten months post-treatment) discusses further:I was so upset I would just yell at him and it was easy to throw my hands in the air…it’s not what I want to do but I’m not thinking straight, I’m not thinking like me…Our relationship has changed, it’s hard to know how to respond, it takes time to become yourself again, the expectation that things should be back to normal and it’s not. Learning to live afterwards is not as easy as what people presume it’s going to be. And trying to know what I want… every day was different. Poor David would never really have a clue… or what mood I’d wake up in or what I wanted or what I needed because it was different from yesterday. Partners also reported a range of difficulties when asked about their own experiences during early survivorship. Many stated that whilst they recognised and understood the many changes affecting their spouse, they felt that all they could do was observe and try not to react negatively to the situation. Some partners managed these difficulties by disregarding their own emotional needs, with an acceptance that the experience of breast cancer was continuing to impact their relationship long after cessation of treatment. It was also recognised that this sometimes meant a withdrawal from each other and resulted in the partner feeling rejected and isolated. A sense of detachment occurred creating further communication issues and limited opportunities for intimacy. Christopher (Carla’s partner) explains:We’ve had a lot of tough periods and I’m a caring person…I think the relationship issues that we’ve had in the last couple of years post cancer has sort of been around me being a bit detached… maybe that detachment is almost like that trauma kind of response… I’ve got to keep my distance here a little bit because there’s just so much going on and I don’t know how much more I can manage or deal with. When prompted to discuss the changes in their relationship during this period, many women recognised that their partner was withdrawing, but that were ill-prepared to provide support, due to their own adjustment difficulties. Partners also confirmed that they needed support during this time; however, they were unaware of where or how to obtain assistance. Marg (one year and six months post-treatment) describes the difficulties she experienced with her partner:My husband doesn’t talk about those sort of things and he deals with it by just doing practical things. He was very good that way but he didn’t share with me his concerns or what that could mean for the family. He was going through a difficult time at his work and I don’t think he felt supported well himself. People knew what was going on with me, I don’t think he really felt very well supported and it did affect him. Couples were very open with regard to the consequences of these communication difficulties and how their relationship was affected. It meant that they felt ‘stuck’ in their attempts to connect with each other, sometimes leading to conflict and stress. Some couples discussed many barriers regarding intimacy and resumption of sexual activity, a situation with which neither individual was satisfied. David (Danielle’s partner) and then Lara (two years and two months post-treatment) discuss further:We’ve been sort of non-intimate, I think it’s been once in two years. It messes with your brain because you start getting this thought that your partner doesn’t love you. Obviously you have different ideas about it and one of the doctors explained how it works with the female body…and to the point they sort of push you away. They’re just a couple of lumps there…and I could have nipples put on but what would be the point? It’s not that there’s no point it’s just they still wouldn’t respond the way mine did … I want to feel the way I felt before but my body just isn’t the same and I felt a bit let down by my body… I am very hopeful that at some point I’ll feel more like me again. You know I haven’t totally written off our physical relationship. Changes to their communication with each other, continued stress, and a loss of intimacy during survivorship sometimes meant that couples’ future plans were very different to what they had anticipated prior to diagnosis. Christopher reflects on how the breast cancer experience impacted his relationship, resulting in changes to his thoughts about the future:The last couple of years have sort of been this rollercoaster of events… our way of coping and reactions and responses and that sort of thing… and it’s still going … I think it’s still going along in a way that’s sort of thrown us on a path that we wouldn’t have ordinarily been on perhaps. It’s led to us sort of drifting…drifting apart quite a bit…towards Carla’s kind of recovery phase and that led to a lot of questioning of where the relationship was at. Reformulating the relationship This theme reflects the opinions of women and partners regarding their attempts to accommodate changes in the relationship and the strategies they felt assisted them during early survivorship. Many women stated that their priority during early survivorship was to reclaim a sense of ‘self’ and that meant needing time and space for themselves before they could focus on the maintenance of their relationship. Women reported that a concentrated effort was required by their partners to understand and respect these needs, utilising open communication and empathy skills. Also recognised was that there were no clear answers about how long it would take to negotiate and adjust to the changes during this period. Marg explains her thoughts:You do feel like there’s some things I didn’t want to talk to or couldn’t talk to Matt about… It’s just, it’s happening to me and just have to sort it out and I knew that there was support all around me but there was just some things that I had to just do on my own and I thought at the end of the day yes it’s affecting everybody else but, I felt like it was happening just to me. When asked about their suggestions for managing the communication challenges in the relationship, many couples recognised that alternative solutions were needed. Communication styles that had worked previously were not always successful during early survivorship. Partners also commented on their role and capacity to support their spouse, given their own personal and emotional difficulties. Some partners stated that they were not always the first person that their spouse sought out for support, resulting in further frustration. David and Danielle describe how David’s usual actions and responses to his wife created problems for them:I’m one of those people who love people to death you know what I mean? Like the big saying is love can fix anything, if it doesn’t work just increase the dose sort of thing… So that’s me in a nutshell and Danielle was sort of…. I need my space… and felt even though I’m away half the time from *FIFO (fly-in fly-out) she felt a bit smothered by it because I was always coming to her and so that’s my homework is for me to stay away and for her to come to me instead of the other way around. [Danielle interjects]: I think one of the biggest things, is that guys have to be very careful that they’re not doing things that benefit them. You know with the closeness thing, David would give me hugs, that’s what he actually needed at the time, it wasn’t what I needed… so it’s a very tough thing to learn. *FIFO- is the term coined to describe the work routine of individuals who need to be transported from their city of residence by aeroplane to place of work, often every 2–4 weeks throughout the year. Women and their partners agreed that there were many challenges during this time; however, offered suggestions regarding potential ways to assist them in negotiating this new phase of their relationship. Couples agreed that they needed to acknowledge the communication issues, address their concerns together, and try to resolve these. A determined commitment to remain in the relationship was also articulated by women and partners with the view that progress would take time and patience from both parties. Lester (Lara’s partner) and Lara discuss their thoughts:It is a massive thing and that’ll be the show stopper for I’d say 60 – 70 % of marriages. It’s just that non-information and communication…can’t say more than stop the arguing side of things and talk and communicate what you’re actually trying to say. Don’t turn it into an argument, don’t storm out, just don’t. I think it’s always been a big thing for us that we’d be there for each other no matter what… If you know that your partner’s going to be there no matter what, ‘cause there’s no one, there’s not a lot of people in this world for you. Many women reported that they were able to access a range of informal supports (friends, work colleagues, female family members) which greatly assisted them during early survivorship. These people were vital supports and offered women the opportunity to talk with someone other than their partner about their thoughts and feelings during this unpredictable period. This was in stark contrast to their partners’ experiences, and it was generally recognised that their partners often did not utilise their friends or family to discuss issues or concerns regarding the relationship. Couples agreed that both women and their partners needed someone to talk to away from each other and that this was very useful; offering another resource or just some time to listen to them during stressful periods. Glenda (five years post-treatment) and Gary (Glenda’s partner) share their experience:I used to say to Gary… he was in a club, building a hot rod at the time and I knew when the hammer got louder, he was taking his anger out on it and all the guys used to turn up and say ‘what do you want a hand with?’… I actually thought when they were all down the shed they’d be saying ‘how you going Gary?’ you know? (Gary interjects) Blokes don’t talk to blokes like that you know… I mean you see these blokes’ sheds they’ve got if you’re depressed and things like that you know… Blokes… well blokes don’t talk about things like that. Support is needed to negotiate the future of the relationship Whereas the previous theme explored strategies that were used in an unplanned and ad hoc manner, the final theme identified the lack of a concrete plan which would enable the couples to move forward in a direct and co-ordinated manner. Women and their partners felt vulnerable and unprepared for this next stage in the breast cancer experience and were concerned about the future. The lack of a defined transition strategy, education and information about survivorship meant that many couples felt unprepared for this period, which also impacted their relationship with their partner. Danielle explains how this uncertainty affected her:I spoke to one of my doctors and he said to me when you were going through chemo and your treatment you wouldn’t have wanted me to say to you ‘you’re going to crash and burn afterwards’. He said ‘you wouldn’t want to hear that and you would have said no, I’m not’….. ‘So all we can do is wait for you to get to that and when you do we’re here’… But I think maybe, even if it was just information, even written, that you read in your own time when you’ve finished or maybe let you know that it is ok to feel like that. You know you may feel lost. No one really even said that. They’re just like oh… last treatment ‘See ya…’ When asked about the supports and services accessed during early survivorship, women confirmed that these were more difficult to obtain compared with those sourced during treatment. None of the women interviewed were offered a survivorship care plan or written information following completion of treatment. Some women reiterated that often it was not until treatment had concluded, that many new fears and concerns emerged, especially regarding the resumption of previous roles and responsibilities. Also noted was the distinct lack of awareness regarding the potential for relationship difficulties. Ingrid (one year post-treatment), reported that she would have benefitted from ongoing support from the breast cancer nurse when her medical treatment was completed:That’s where I think the breast care nurse would have come in handier for me at the end of treatment… Not before and not during, at the end. Even if it was just a phone call or maybe you know… a visit or you can go there and see her. Couples were united in their suggestions about the potential value of formal support from health professionals to assist them in negotiating improvements in communication within their relationship. Some women stated that they had sought support to assist them with a range of personal and shared issues. Women and their partners recognised that ongoing communication difficulties could lead to long-term issues, including irreparable changes in the nature of their relationship and that professional assistance was needed to manage this. Marg discussed her strategy for addressing concerns:If you don’t recognise what’s happening and everything’s really, really hard then I think you need someone to help set you in the right direction. But if you’re aware enough, if things are pretty tough….go and see someone… which I was able to do. But I don’t know if everyone can do that and that was very difficult but it was very good in the long run. There was recognition that the partners of women were largely ignored with regard to requiring targeted support during the early survivorship period. Partners stated that they could have benefitted from a range of formal supports, but that they were not made aware of any potential resources during this period. Partners identified that access to support during this period was an initial step towards adjustment and gave hope for the future. Gary emphasises his desire for timely support to build a foundation towards a positive outcome following the cessation of treatment.I don’t think there’s enough for the guys, there’s more information for the women. But as far as information for guys…what to expect and how to cope with your wife … I mean fair enough because she’s the one going through it …but they don’t sort of scope on what happens around them… you really had no one to talk to. But it may be a few phone calls and a human face to face in private or whatever… then they might give you something and then that builds momentum. So something along those lines. Discussion The findings of this study support previously published literature regarding the experience of survivorship for women and raises many additional concerns about how the partners of women are also significantly impacted during this time. The physical and cognitive consequences of breast cancer and its treatments that continue during treatment and survivorship are well established and supported by many qualitative and quantitative studies [17, 59, 86, 92, 93]. Recent research focussing on the early transition from treatment to survivorship identifies further issues including loneliness and an inability to cope, as well as anxiety and emotional distress sometimes leading to depression [5, 11, 26, 92]. Our study’s findings raise additional concerns for women and their partners during survivorship, many of which have not been previously reported. The women in this study expressed many psychological concerns relating to the early period following cessation of treatment. Women felt their physical, psychological and emotional needs were largely undervalued by their usual medical supports, with a sense that the psychological and emotional difficulties experienced during early survivorship were not considered a priority during this period. Women reported that the period immediately following cessation of treatment was the most problematic, with many emerging difficulties relating to the resumption of previous roles and responsibilities. A desire to ‘put themselves first’, a need for privacy, suppression of thoughts and feelings and being able to maintain control over their lives were frequently discussed as having a profound impact on daily function and maintenance of the relationship with their partner. The resultant stress of coping with the diagnosis and treatment of breast cancer may be superseded by the problems experienced during survivorship [19, 47, 94–101]. There is some evidence to suggest that resources provided during this time including information, education, peer support/mentoring and self-management tools may assist women in preventing further issues including depression and other psychological sequelae [16, 102–104]. The literature reports that most women experience improvements in quality of life beyond the five year period (long–term survivorship) [105, 106]. However, some women do not; those with a previous history of depression and women who completed chemotherapy are thought to be at greater risk of long term problems [107, 108]. This study found the partners of women reported many unmet needs and were unaware of where they could obtain assistance to help them manage the many challenges experienced during survivorship, also citing that there was a lack of recognition for the important role they played in supporting their partner during this time. Common issues reported by participant partners of this study included; difficulty understanding and accommodating their partner’s needs during survivorship, communication issues, problems with intimacy and resumption of sexual activity as well as feeling isolated and detached from their relationship with their spouse. These findings add weight to the existing evidence that many partners feel largely unsupported during the breast cancer experience generally [21, 42, 92, 109]. While the supportive care efforts to meet partners’ needs appear to be improving, these are concentrated during the treatment period. Significant distress may continue beyond this the treatment period, resulting in further adjustment difficulties, anxiety and depression [21, 42, 51, 110, 111]. Results of this study reflect the complex interaction between women and their partners during survivorship and support the view that the breast cancer experience must be considered as ‘shared’. The literature describes this concept as a form of ‘dyadic coping’ and it explains the method for which women and partners learn the skills required to accommodate the stress experienced as a result of illness [39, 54]. This perspective is supported by several studies indicating that the psychological distress experienced by cancer survivors and their partners is interdependent with the recognition that cancer is a ‘family’ disease [27, 44, 54, 112, 113]. However, there are few Australian studies that highlight the unique needs of partners during breast cancer survivorship [114–116]. Changes to intimate relationships were also recognised by participants. Women reported that the physical and emotional changes experienced during survivorship resulted in them being unsure about if, and when, they would feel comfortable to resume a sexual relationship with their partner. Thematic findings of this research offer many examples of women needing to remain distanced from their partner, physically, emotionally and sexually. Treatment for breast cancer (chemotherapy, surgery and radiation) as well as the use of adjuvant (hormone) therapy are noted to potentially contribute to the physical and psychological consequences of breast cancer and may offer some explanation towards the complex relationship problems experienced at this time [32, 33, 117–119]. The findings of this study support the view that the experience of breast cancer for women with partners is profound. While the period of diagnosis and treatment is identified as creating significant stress for both partners regarding their relationship, emotional, financial and spiritual concerns [39], our findings indicate that the early survivorship period may continue to create many additional difficulties for couples. There is an expectation that women and their partners resume their previous activities and relationships with ease following cessation of treatment; however, the themes explored in this paper indicate that couples may experience a range of ongoing issues and partners themselves may have unique problems that are often overlooked. There have been some efforts to date aimed at improving couples’ communication, coping skills and adjustment during survivorship. A systematic review conducted in 2013 [50] concluded that a range of psychological interventions completed with couples experiencing breast and gynaecological cancer were effective; however, the majority of the studies reviewed were focussed on the treatment stage [120–124]. Additional research has been completed examining a range of interventions applicable during survivorship including: adjustment to illness and the development of coping strategies [125]; addressing cancer related stress and improving marital communication [48]; and addressing body image concerns, intimacy and sexuality [126–128]. The findings of this study support the need for further development, application and evaluation of cost effective supports for couples affected by breast cancer, particularly during early survivorship. Recommendations regarding the development, utilisation and efficacy of supportive care must be viewed within the context of that care. Models of cancer care vary considerably across the world, with a range of underpinning philosophies including a traditional medicalised approach, a biopsychosocial framework and the wellness model [65, 129–131]. To date, there is no consensus on which model/approach is most appropriate for the provision of support during breast cancer survivorship. It is widely recommended that these models of care must provide timely, cost effective services and supports according to the preferences of consumers [17]. Evidence from our study demonstrates that the experience of early survivorship for couples is complex, with many psychological, social and sexual issues, suggesting that a biopsychosocial framework is appropriate in addressing couples’ ongoing needs. Researchers concur that there is an urgent need to further explore the efficacy of these approaches while observing the recommendations made by the Institute of Medicine (IOM), these being: the prevention of recurrent and new cancers; surveillance for cancer recurrence and medical and psychosocial late effects; strategies to manage the consequences of cancer; and co-ordination of specialists and primary providers [132]. The IOM also made key recommendations including the use of SCP’s to address many of the concerns raised by the current study’s participants [58]. There is a volume of literature suggesting that SCP’s may assist women to identify and address many of the ongoing issues and concerns relating to breast cancer survivorship [22, 25, 99, 133–135]. While participants of this study were not offered a SCP as a strategy for managing the consequences of breast cancer, the strongest recommendation of women and their partners was that they needed a formal plan to manage this new phase of their lives and to help them adjust to the many personal challenges being experienced during survivorship. Women and their partners interviewed in this study were left to negotiate this time on their own without the recommended supports and services needed to meet their varied and complex needs. Survivorship Care Plans may be an essential, yet underused resource that offers great potential to assist both women survivors and their partners to document, direct and facilitate the required supports and services in early survivorship. Our study suggests that any plan should also include the concerns of partners. Limitations There are limitations to this research and some of these are common to the methodology of dyadic interviewing. Most women were interviewed with their partner present, which may have created a situation where a participant might not have offered information that could create difficulties or discomfort for the other person. Interestingly, the data gathered from the two couples interviewed separately from their partners were not dissimilar to that divulged by partners interviewed together. This may be because couples who agreed to be interviewed together felt comfortable in discussing their concerns with one another. It may be that the concerns of couples experiencing extreme distress may not be captured by this research project. All couples were heterosexual, limiting the unique perspectives that may have been provided regarding same sex couples. Inclusion criteria did not preclude same sex couples; however, no same sex couples volunteered for interviews. Participants were asked about the support services utilised during survivorship; however, were not asked for their suggestions regarding potential recommendations, accessibility or the applicability of shared services and this is recognised as a limitation, warranting further investigation. Participant demographics indicate that the socio-economic status of couples was comparatively high and that the particular needs of individuals from low socio-economic groups were not represented in the findings. All participants were recruited from a large city and therefore may have been able to access services and supports if required. All participant women interviewed were married and therefore the findings may not be generalised to single/divorced women. However, it is reasonable to conclude that the findings may be transferrable to women residing in developed countries, where health and community services are comparable to existing Australian services. Conclusion Results of this research support a shift from the traditional medicalised approach to a ‘biopsychosocial’ framework incorporating comprehensive multi-disciplinary care which targets women’s and their partner’s complex physical, psychological, communication and emotional needs, especially during early survivorship . Further development of this framework must complement the existing resources and be targeted towards the shared needs and preferences of women and their partners. Women survivors of breast cancer are recognised as a significant, yet distinct group of health care recipients requiring specialised and targeted services to manage their health care during survivorship. This paper provides additional evidence that the partners of women also experience a range of psychological, emotional and relationship consequences during survivorship. Women and their partners want increased awareness of, and support for, the important role partners provide during treatment and survivorship. Abbreviations SCPSurvivorship care plan Acknowledgements The authors wish to acknowledge the many women survivors of breast cancer and their partners who provided valuable time and contributions to this research and the Breast Cancer Network of Australia who assisted with recruitment of participants. Funding The authors declare that funding was not obtained to complete the research. Availability of data and material The datasets generated during and/or analysed during the current study are not publicly available as individual privacy may be compromised but are available from the corresponding author on reasonable request. Authors’ contributions SK: conceptualisation and development of research design, recruitment of participants, interviews with participants, acquisition of data, analysis and interpretation of data, drafting and revising the manuscript. LR: research design, data analysis and interpretation of data, drafting and revising the manuscript. BM: research design, data analysis and interpretation of data, drafting and approving the manuscript. All authors read and approved the final manuscript. All authors agree to be accountable for all aspects of the work in ensuring that the accuracy and integrity of any part of the work are appropriately investigated and resolved. Competing interests The authors declare that they have no competing interests. Consent for publication The authors declare that written consent for publication was obtained from all study participants. Ethics approval and consent to participate The authors declare that the study has been approved by the Curtin University Human Research Ethics Committee (approval number HR 51/2014). Written consent to participate was obtained from all study participants. ==== Refs References 1. World Health Organisation. Cancer Fact Sheet No. 297 2015 [June 3 2015]. Available from: http://www.who.int/mediacentre/factsheets/fs297/en/. Accessed 3 June 2015. 2. Australian Institute of Health and Welfare. Breast Cancer in Australia: an overview. In: Australian Institute of Health and Welfare, editor. Canberra 2012. 3. Cheng K Devi R Wong W Koh C Perceived symptoms and the supportive care needs of breast cancer survivors six months to five years post-treatment period Eur J Oncol Nurs 2014 18 3 9 10.1016/j.ejon.2013.10.005 24315730 4. Tsuchiya M Horn S Ingham R Positive changes in Japanese breast cancer survivors: a qualitative study Psychol Health Med 2013 18 1 107 16 10.1080/13548506.2012.686620 22646702 5. Hodgkinson K Butow P Hunt G Pendlebury S Hobbs K Wain G Breast cancer survivors’ supportive care needs 2–10 years after diagnosis Support Care Cancer 2007 15 515 23 10.1007/s00520-006-0170-2 17120068 6. Keesing S, McNamara B, Rosenwax L. Cancer survivors’ experiences of using survivorship care plans: a systematic review of qualitative studies. J Cancer Surviv. 2015;9(2):260–268. 7. Gil K Mishel M Belyea M Germino B Porter L Carlton LaNey I Triggers of uncertainty about recurrence and long-term treatment side effects in older African American and Caucasian breast cancer survivors Oncol Nurs Forum 2004 31 3 633 9 10.1188/04.ONF.633-639 15146229 8. Fobair P. Oncology social work for survivorship. 2007 [cited 15th November 2013]. In: Cancer survivorship today and tomorrow [Internet]. California: UCLA Schools of public health and medicine, [cited 15th November 2013]; 14–27. 9. Pelusi J Sexuality and body image: research on breast cancer survivors documents altered body image and sexuality Am J Nurs 2006 106 Supplement 3 32 8 10.1097/00000446-200603003-00013 16481849 10. Lynn Gall T Cornblat M Breast cancer survivors give voice; a qualitative analysis of spiritual factors in long-term adjustment Psycho-Oncology 2002 11 6 524 35 10.1002/pon.613 12476434 11. Rosedale M Survivors loneliness of women following breast cancer Oncol Nurs Forum 2009 36 2 175 83 10.1188/09.ONF.175-183 19273406 12. Kenyon M Mayer D Owens A Late and long-term effects of breast cancer treatment and surveillance management for the general practitioner J Obstet Gynecol Neonatal Nurs 2014 43 3 383 98 10.1111/1552-6909.12300 13. Chubak J Aiello-Bowles E Tuzzio L Ludman E Rutter C Reid R Perspectives of cancer survivors on the role of different healthcare providers in an integrated delivery system J Cancer Surviv 2014 8 2 229 38 10.1007/s11764-013-0335-1 24352871 14. Jefford M Kinnane N Howell P Nolte L Galetakis S Bruce Mann G Implementing novel models of post-treatment care for cancer survivors: enablers, challenges and recommendations Asia Pac J Clin Oncol 2015 11 319 27 10.1111/ajco.12406 26245952 15. Todd B Feuerstein M Gehrke A Hydeman J Beaupin L Identifying the unmet needs of breast cancer patients post -primary treatment: the cancer survivor profile (CSPro) J Cancer Surviv 2015 9 137 60 10.1007/s11764-015-0428-0 25820913 16. Loh SY Packer T Chinna K Quek K Effectiveness of a patient self-management programme for breast cancer as a chronic illness: a non-randomised controlled clinical trial J Cancer Surviv 2013 7 331 42 10.1007/s11764-013-0274-x 23519654 17. McCann L Illingworth N Wengstrom Y hubbard G Kearney N Transitional experiences of women with breast cancer within the first year following diagnosis J Clin Nurs 2010 19 1969 76 10.1111/j.1365-2702.2009.03134.x 20936753 18. Richardson A Addington-Hall J Amir Z Foster C Stark D Armes J Knowledge, ignorance and priorities for research in key areas of cancer survivorship; findings from a scoping review Br J Cancer 2011 105 S82 S94 10.1038/bjc.2011.425 22048036 19. Allen J Savadatti S Gurmankin LA The transition from breast cancer ‘patient’ to ‘survivor’ Psycho Oncol 2009 18 71 8 10.1002/pon.1380 20. Tish Knobf M Clinical update: psychosocial responses in breast cancer survivors Semin Oncol Nurs 2011 27 3 e1 e14 10.1016/j.soncn.2011.05.001 21783006 21. Pauwels E Charlier C De Bourdeadhuij I Lechner L VanHoof E Care needs after primary breast cancer treatment. Survivors associated sociodemographic and medical characteristics Psycho Oncol 2013 22 125 32 10.1002/pon.2069 22. Easley J Miedema B Rehabilitation after breast cancer: recommendations from young survivors Rehabil Nurs 2012 37 4 163 70 10.1002/rnj.21 22744987 23. Stanton A Ganz P Kwan L Outcomes from the moving beyond cancer psychoeducational, randomised, controlled trial with breast cancer patients J Clin Oncol 2005 23 6009 18 10.1200/JCO.2005.09.101 16135469 24. Cimprich B Janz N Northouse L Wren P Given BA Given CW Taking charge: a self management program for women following breast cancer treatment Psycho Oncol 2005 14 704 17 10.1002/pon.891 25. Boekhout A A survivorship care plan for breast cancer survivors: extended results of a randomized clinical trial J Cancer Surviv 2015 9 9 683 91 10.1007/s11764-015-0443-1 25896265 26. Bloom J Stewart S D'Onofrio C Luce J Banks P Addressing the needs of young breast cancer survivors at the 5 year milestone: can a short term, low intesnsity intervention produce change? J Cancer Surviv 2008 2 3 190 204 10.1007/s11764-008-0058-x 18670888 27. Oktay J Bellin M Scarvolone S Appling S Helzlsouer K Managing the impact of post-treatment fatigue on the family: breast cancer survivors share their experiences Fam Syst Health 2011 29 2 127 37 10.1037/a0023947 21688904 28. Northouse L Swain M Adjustment of patients and husbands to the initial impact of breast cancer Nurs Res 1987 36 4 221 5 10.1097/00006199-198707000-00009 3648695 29. Chung C Huang E Couples experiences of breast cancer in Korea: a descriptive qualitative study Cancer Nurs 2012 35 3 211 20 10.1097/NCC.0b013e31822a60db 21909022 30. Pistrang N Barker C The partner relationship in psychological response to breast cancer Soc Sci Med 1995 40 6 789 97 10.1016/0277-9536(94)00136-H 7747213 31. Northouse L Templin T Mood D Oberst M Couples adjustment to cancer and benign breast disease: a longitudinal analysis Psycho-Oncology 1998 7 1 37 48 10.1002/(SICI)1099-1611(199801/02)7:1<37::AID-PON314>3.0.CO;2-# 9516649 32. Schmid-Buchi S Halfens R Dassen T van den Borne B Psychosocial problems and needs of post-treatment patients with breast cancer and their relatives Eur J Oncol Nurs 2011 15 260 6 10.1016/j.ejon.2009.11.001 20089447 33. Holmberg S Scott L Alexy W Fife B Relationship issues of women with breast cancer Cancer Nurs 2001 24 1 53 60 10.1097/00002820-200102000-00009 11219423 34. Chekryn J Cancer recurrence:personal meaning, communication and marital adjustment Cancer Nurs 1984 7 6 491 8 10.1097/00002820-198412000-00005 6568868 35. Shands M Lewis F Sinsheimer J Cochrane B Core concerns of couples living with early stage breast cancer Psycho Oncol 2006 15 12 1055 64 10.1002/pon.1036 36. Segrin C Badger T Interdependent psychological distress between latinas with breast cancer and their supportive partners J Lat Psychol 2013 1 21 34 10.1037/a0030345 37. Sjovall K, Attner B, Lithman T, Noreen D, Gunnars B, Thome B, et al. Influence on the health of the partner affected by tumour disease in the wife or husband based on a population-based register study of cancer in Sweden. J Clin Oncol. 2009;28;4781-86. 38. Miller L Caughlin J “We’re going to be survivors”: Couples identitity challenges during and after cancer treatment Commun Monogr 2013 80 1 63 82 10.1080/03637751.2012.739703 39. Ben-Zur H, Gilbar O, Lev S. Coping with breast cancer: patient, spouse and dyad models. Psychosom Med. 2001;63:32-39. 40. Zahlis e, Lewis F. Coming to grips with breast cancer: the spouse’s experience with his wife’s first six months. Psycho Oncology. 2010;28(1):79-97. 41. Grunfeld E Coyle D Whelan T Clinch J Reyno L Earle C Family caregiver burden: results of a longitudinal study of breast cancer patients and their principal caregivers Can Med Assoc J 2004 170 12 1795 801 10.1503/cmaj.1031205 15184333 42. Talley A Molix L Schlegel R Betencourt A The influence of breast cancer survivors’ perceived partner social support and need satisfaction on depressive symptoms: a longitutional analysis Psychol Health 2010 25 4 433 49 10.1080/08870440802582682 20397295 43. Pauwels E De Bourdeadhuij I Charlier C Lechner L Van Hoof E Psychosocial characteristics associated with breast cancer survivors’ intimate partners’ needs for information and support after primary breast cancer treatment J Psychosoc Oncol 2012 30 1 20 10.1080/07347332.2011.633982 22269073 44. Segrin C Badger T Psychological and physical distress are interdependent in breast cancer survivors and their partners Psychol Health Med 2014 19 6 716 23 10.1080/13548506.2013.871304 24383980 45. Fletcher B Miakowski C Given BA Schumacher K The cancer family caregiving experience: an updated and conceptual model Eur J Oncol Nurs 2012 16 4 387 98 10.1016/j.ejon.2011.09.001 22000812 46. Loaring J Larkin M Shaw R Flowers P Renegotiating sexual intimacy in the context of altered embodiment: the experiences of women with breast cancer and their partners following mastectomy and reconstruction Health Psychol 2015 34 4 426 36 10.1037/hea0000195 25822057 47. Jefford M Karahalios E Pollard A Baravelli C Carey M Franklin J Survivorship issues following treatment completion-results from focus groups with Australian cancer survivors and health professionals J Cancer Surviv 2008 2 20 32 10.1007/s11764-008-0043-4 18648984 48. Rowland J Meyerowitz B Crespi C Leedham B Desmond K Belin T Addressing intimacy and partner communication after breast cancer: a randomised controlled group intervention Breast Cancer Res Treat 2009 118 99 111 10.1007/s10549-009-0398-x 19390963 49. Kim Y Kashy D Wellish D Spillers R Kaw C Smith T Quality of life of couples dealing with cancer: dyadic and individual adjustment among breast and prostate cancer survivors and their spousal caregivers Ann Behav Med 2008 35 230 8 10.1007/s12160-008-9026-y 18365297 50. Brandao T Schulz M Matos P Psychological intervention with couples coping with breast cancer: a systematic review Psychol Health 2013 29 5 491 516 10.1080/08870446.2013.859257 24279379 51. Feldman B Broussard A Men’s adjustment to their partners breast cancer; a dyadic coping perspective Health Soc Work 2006 31 2 117 27 10.1093/hsw/31.2.117 16776029 52. Dorval M Guay S Mondor M Masse B Falardeau M Robidoux A Couples who get closer after breast cancer: frequency and predictors in a prospective investigation J Clin Oncol 2005 23 15 3588 96 10.1200/JCO.2005.01.628 15908669 53. Li Q Loke A A literature review on the mutual impact of the spousal caregiver-cancer patients dyads: ‘communication’, ‘reciprocal influence’ and ‘caregiver-patient congruence’ Eur J Oncol Nurs 2014 18 58 65 10.1016/j.ejon.2013.09.003 24100089 54. Kayser K Cheung P Rao N Chan Y Chan Y Lo P The influence of culture on couples coping with breast cancer: a comparative analysis of ocuples from China, India and the United States J Psychosoc Oncol 2014 32 3 264 88 10.1080/07347332.2014.897292 24611914 55. Girgis A Butow P Cancer survivorship: research priorities at the national and international levels Cancer Forum 2009 33 3 196 9 56. Picard L Dumont S Gagnon P Lessard G Coping strategies among couples adjusting to primary breast cancer Psycho Oncol 2005 23 2–3 115 35 57. Kayser K Watson L Andrade J Cancer as a ‘we disease’: examining the process of coping from a relational perspective (clinical report) Fam Syst Health 2007 25 404 18 10.1037/1091-7527.25.4.404 58. Institute of Medicine and National Research Council of the National Academies From cancer patient to cancer survivor: lost in transition Committee on cancer survivorship: improving care and quality of life NCPB 2005 Washington, D.C. National Academies Press 59. Jarrett N Scott I Addington-Hall J Amir Z Brearley S Hodges L Informing future research priorities into the psychological and social problems faced by cancer survivors: A rapid review and synthesis of the literature Eur J Oncol Nurs 2013 17 5 510 20 10.1016/j.ejon.2013.03.003 23619278 60. Lawler S Spathonis J Masters J Adams J Eakin E Follow-up care after breast cancer treatment: experiences and perceptions of service provision and provider interactions in rural Australian women Support Care Cancer 2011 19 12 1975 83 10.1007/s00520-010-1041-4 21080202 61. Jefford M Mann G Nolte L Russell L Brennan M Follow-up of women with early stage breast cancer Curr Breast Cancer Rep 2014 6 183 92 10.1007/s12609-014-0150-3 62. Brennan ME Butow P Marven M Spillane AJ Boyle FM Survivorship care after breast cancer treatment-experiences and preferences of Australian women Breast 2011 20 3 271 7 10.1016/j.breast.2010.12.006 21236671 63. Girgis A, Lambert S. Caregivers of cancer survivors: the state of the field. Cancer Forum. 2009;33(3):167-70. 64. Breast Cancer Network Australia National survivorship think tank 2009 65. Clinical Oncology Society of Australia Cancer survivorship care in Australia position statement critical components of cancer survivorship care 2015 66. Allen G A note on interviewing spouses together J Marriage Fam 1980 42 1 205 10 10.2307/351948 67. Manning J Kunkel A Qualitative approaches to dyadic data analyses in family communication research: an invited essay J Fam Commun 2015 15 185 92 10.1080/15267431.2015.1043434 68. Arskey H Collecting data through joint interviews Soc Res Update 1996 15 1 4 69. Morris S Joint and individual interviewing in the context of cancer Qual Health Res 2001 11 4 533 67 10.1177/104973201129119208 70. Eisikovits Z Koren C Approaches to and outcomes of dyadic interview analysis Qual Health Res 2010 20 12 1642 55 10.1177/1049732310376520 20663940 71. Torge C Using conjoint interviews with couples that have been living with disabilities and illnesses for a long time-implications and insights Qual Stud 2013 4 2 100 13 72. Liamputtong P Liamputtong P Rigour and ethics in qualitative research Qualitative Research Methods 2009 3 South Melbourne Oxford University Press 73. Serry T Liamputtong P Liamputtong P The in-depth interviewing method in health Research methods in health: Foundations for evidence-based practice 2010 Melbourne Oxford University Press 45 60 74. Liamputtong P Liamputtong P The science of words and the science of numbers: Research methods as foundations for evidence-based practice in health Research methods in health, foundations for evidence based practice 2010 Melbourne Oxford University Press 3 26 75. Kvale S Interviews 1996 Thousand Oaks Sage Publications 76. May K Interview techniques in qualitative research: concerns and challenges Qualitative nursing research: a contemporary dialogue [Internet] 1991 Thousand Oaks SAGE publications 77. Liamputtong P Liamputtong P The in-depth method of interviewing Qualitative Research Methods 2013 4 South Melbourne Oxford University Press 78. Roulston K Open ended questions The Sage encyclopaedia of qualtitative research methods [Internet] 2008 Thousand Oaks SAGE publications 79. Merrill B, West L. Interviewing and Recording Experience. In: Merrill B, West L, editors. Using biographical methods in social research SAGE Publications, Ltd. London, England: SAGE Publications, Ltd. 2011. p. 113–28. 80. Emmel N Theoretical or Purposive Sampling. Sampling and Choosing Cases i 2013 London SAGE Publications Ltd 81. Liamputtong P Theoretical frameworks and sampling in qualitative research. Qualitative Research Methods. 3rd ed 2009 South Melbourne Oxford Press 82. Braun V Clarke V Using thematic analysis in psychology Qual Res Psychol 2006 3 2 77 101 10.1191/1478088706qp063oa 83. Goulding C Analysis, Interpretation and the Writing Process Grounded Theory [Internet] 2002 London, England SAGE Publications Ltd 74 101 84. Sandelowski M The problem of rigour in qualitative research Adv Nurs Sci 1986 8 3 27 37 10.1097/00012272-198604000-00005 85. Ritchie J Berglund C Not everything can be reduced to numbers Health Research 2001 Melbourne Oxford University Press 149 73 86. Brunet J Sabiston C Burke S Surviving breast cancer:womens’s experiences with their changed bodies Body Image 2013 10 244 351 10.1016/j.bodyim.2013.02.002 87. Andreano J Waisman J Donley L Cahill L Effects of breast cancer treatment on the hormonal and cognitive consequences of acute stress Psycho Oncol 2012 21 1091 8 10.1002/pon.2006 88. Cheng K Thompson D Ling W Chan C Measuring symptom prevalence, severity and distress of cancer survivors Clin Eff Nurs 2005 9 154 60 10.1016/j.cein.2006.08.007 89. Binkley J Harris S Levangie P Pearl M Guglielmino J Kraus V Patient perspectives on breast cancer treatment side effects and the prospective surveillance model for physical rehabilitation for women with breast cancer Cancer 2012 118 8 (Supp) 2207 16 10.1002/cncr.27469 22488695 90. Shi Q Michonski J Stein K Kaw C Cleeland C Symptom burden in cancer survivors 1 year after diagnosis: a report from the american cancer Society’s studies of cancer survivors Cancer 2011 117 2779 90 10.1002/cncr.26146 21495026 91. Jones J Olson K Catton P Catton C Fleshner N Cancer-related fatigue and disability in post-treatment cancer survivors J Cancer Surviv 2016 10 1 51 61 10.1007/s11764-015-0450-2 25876557 92. Alfano C Rowland J Recovery issues in cancer survivorship: a new challenge for supportive care Cancer J 2006 12 5 432 43 10.1097/00130404-200609000-00012 17034679 93. Witt Sherman D Rosedale M Haber J Reclaiming life on one’s own terms: a grounded theory study of the process of breast cancer survivorship Oncol Nurs Forum 2012 39 3 E258 E68 10.1188/12.ONF.E258-E268 22543397 94. Jiwa M, Halkett G, Deas K, Ward P, O’Connor M, O’Driscoll C, et al. How do specialist breast nurses help breast cancer patients at follow up? Collegian. 2010;17:143-49. 95. Roundtree A Giordano S Price A Suarez-Almazor M Problems in transition and quality of care:perspectives of breast cancer survivors Support Care Cancer 2011 19 1921 9 10.1007/s00520-010-1031-6 21140173 96. Costanzo E Lutgendorf S Mattes M Adjusting to life after treatment; distress and quality of life following treatment for breast cancer Br J Cancer 2007 97 1625 31 10.1038/sj.bjc.6604091 18000503 97. Lemoignan J, Chasen M, Bharqava R. A retrospective study of the role of an occupational therapist in the cancer nutrition rehabilitation program. Supportive Care in Cancer. 2010;18(12):1589-96. 98. Jagielski C Hawley S Corbin K Weiss M Griggs J A phoenix rising: who considers herself a ‘survivor’ after a diagnosis of breast cancer? J Cancer Surviv 2012 6 451 7 10.1007/s11764-012-0240-z 22936393 99. Kantsiper M McDonald E Geller G Shockney L Snyder C Wolff A Transitioning to breast cancer survivorship: perspectives of patients, cancer specialists, and primary care providers J Gen Intern Med 2009 24 459 66 10.1007/s11606-009-1000-2 100. Elmir R Jackson D Beale B Schmied V Against all odds: Australian women’s experiences of recovery from breast cancer J Clin Nurs 2010 19 2531 8 10.1111/j.1365-2702.2010.03196.x 20636477 101. Thewes B, Butow P, Girgis A, Pendlebury S. The psychological needs of breast cancer survivors: a qualitative study of the shared and unique needs of younger versus older survivors. Psycho Oncol. 2004;13. 102. van den Berg S Gielissen M Custers J van den Graaf W Ottevanger P Prins J BREATH: Web based self-management for psychological adjustment after primary breast cancer-results of a multicentre randomised controlled trial J Clin Oncol 2015 33 25 2763 72 10.1200/JCO.2013.54.9386 26169621 103. Fenlon D Reed E Blows E Scanlon K Wray J Dewey A Moving forward: a qualitative research inquiry to inform the development of a resource pack for women following primary breast cancer treatment J Psychosoc Oncol 2015 33 85 105 10.1080/07347332.2014.977414 25415765 104. Lu Q You J Man J Loh A Young L Evaulating a culturally tailored peer-mentoring and education pilot intervention among Chinese breast cancer survivors using a mixed methods approach Oncol Nurs Forum 2014 41 6 629 37 10.1188/14.ONF.629-637 25355018 105. Mols F Vingerhoets A Coebergh J van de Poll-Franse L Quality of life among long-term breast cancer survivors: a systematic review Eur J Cancer 2005 41 2613 9 10.1016/j.ejca.2005.05.017 16226458 106. Hsu T Ennis M Hood N Graham M Goodwin P Quality of Life in long-term breast cancer survivors J Clin Oncol 2013 28 3540 8 10.1200/JCO.2012.48.1903 23980087 107. Janz N Friese C Li Y Graff J Hamilton A Hawley S Emotional well-being years post treatment for breast cancer: prospective, multi-ethnic and population-based analysis J Cancer Surviv 2014 8 131 42 10.1007/s11764-013-0309-3 24222081 108. Stava C Weiss L Vassilopoulou-Sellin R Health profiles of 814 very long term breast cancer survivors Clin Breast Cancer 2006 7 3 228 36 10.3816/CBC.2006.n.034 16942639 109. Adams E Boulton M Rose P Lund S Richardson A Wilson S A qualitative study exploring the experience of the partners of cancer survivors and their views on the role of primary care Support Care Cancer 2012 20 2785 94 10.1007/s00520-012-1400-4 22354621 110. Segrin C Badger T Psychological distress in different social network members of breast and prostate cancer survivors Res Nurs Health 2010 33 450 64 10.1002/nur.20394 20672304 111. Miller L Sources of uncertainty in cancer survivorship J Cancer Surviv 2012 6 431 40 10.1007/s11764-012-0229-7 22815086 112. Antoine P Vanlemmens L Fournier E Trocme M Christophe V Young couples experiences of breast cancer during hormone treatment Cancer Nurs 2013 36 3 213 20 10.1097/NCC.0b013e31826429a5 22964867 113. Blais M Maunsell E Grenier S Lauzier S Dorval M Pelletier S Validating the content of a brief informational intervention to empower patients and spouses following breast cancer: perspectives of both couple members J Cancer Surviv 2014 8 508 20 10.1007/s11764-014-0359-1 24770975 114. Connell S Patterson C Newman B Issues and concerns of young Australian women with breast cancer Support Care Cancer 2006 14 419 26 10.1007/s00520-005-0003-8 16463036 115. Stafford L Judd F Partners of long-term gynaecologic cancer survivors: Psychiatric morbidity, psychosexaual outcomes and supportive care needs Gynecol Oncol 2010 118 268 73 10.1016/j.ygyno.2010.05.019 20570323 116. Lambert S Girgis A Lecathelinais C Stacey F Walking a mile in their shoes:anxiety and depression among partners and caregivers of cancer survivors at 6 and 12 months post-diagnosis Support Care Cancer 2013 21 75 85 10.1007/s00520-012-1495-7 22661096 117. Melisko M Goldman M Rugo H Amelioration of sexual adverse effect in the early breast cancer patient J Cancer Surviv 2010 4 247 55 10.1007/s11764-010-0130-1 20602189 118. Boehmke M Dickerson S The diagnosis of breast cancer: transition from health to illness Oncol Nurs Forum 2006 33 6 1121 7 10.1188/06.ONF.1121-1127 17149395 119. Wiliams F, Jeanetta S. Lived experiences of breast cancer survivors after diagnosis, treatment and beyond: qulitative study. Health Expect. 2015. Epub May 7th 2015. 120. Kayser K Feldman B Borsetelman N Daniels A Effects of a randomised couple-based intervention on quality of life of breast cancer patients and their partners Soc Work Res 2010 34 1 20 32 10.1093/swr/34.1.20 121. Manne S G O Winkel G Social cognitive processes as moderators of a couple focussed group intervention for women with early stage breast cancer Health Psychol 2007 26 6 735 44 10.1037/0278-6133.26.6.735 18020846 122. Christensen D Post-mastectomy couples counselling: an outcome study of a structured treatment protocol J Sex Marital Ther 1983 9 4 266 75 10.1080/00926238308410913 6663643 123. Baucom D Porter L Kirby J Gremore T Wiesenthal L Aldridge W A couple-based intervention for female breast cancer Psycho Oncol 2009 18 3 276 83 10.1002/pon.1395 124. Kalaitzi C Papadopolous V Vlasis K Skandalakis P Filippou D Combined brief psychosexual intervention after mastectomy: effects on sexuality, body image and psychological well-being J Surg Oncol 2007 96 235 40 10.1002/jso.20811 17443731 125. Shields C Rosseau S A pilot study of an intervention for breast cancer survivors and their spouses Fam Process 2004 43 1 95 107 10.1111/j.1545-5300.2004.04301008.x 15359717 126. Krychman M Katz A Breast cancer and sexuality: multi-modal treatment options J Sex Med 2012 9 5 13 10.1111/j.1743-6109.2011.02566.x 22151953 127. Scott J Kayser K A review of couple-based interventions for enhancing women’s sexual adjustment and body image after cancer Cancer J 2009 15 48 56 10.1097/PPO.0b013e31819585df 19197174 128. Decker C Shoba P Miller KD Goulet R Fifea B A brief intervention to minimise psychosexual morbidity in dyads coping with breast cancer Oncol Nurs Forum 2012 39 2 176 85 10.1188/12.ONF.176-185 22374491 129. Irwin M Klemp J Glennon C Frazier L Oncology nurses’ perspectives on the state of cancer survivorship care: current practice and barriers to implementation Oncol Nurs Forum 2011 38 1 E 11 E 9 10.1188/11.ONF.E11-E19 130. Howell D Hack T Oliver T Chulak T Mauo S Aubin M Models of care for post treatment follow-up of adult cancer survivors: a systematic review and quality appraisal of the evidence J Cancer Surviv 2012 6 359 71 10.1007/s11764-012-0232-z 22777364 131. Landier W Survivorship care: essential components and models of delivery Oncology 2009 23 4 SUPP 46 53 19856598 132. National Breast Cancer Foundation Challenging breast cancer: a national action plan for research and funding 2004 Sydney NBCF 133. Smith S Singh-Carlson S Downie L Payeur N Wai E Survivors of breast cancer: patient perspectives on survivorship care planning J Cancer Surviv 2011 5 337 44 10.1007/s11764-011-0185-7 21643836 134. Ganz A Hahn E Implementing a survivorship care plan for patients with breast cancer J Clin Oncol 2008 26 759 66 10.1200/JCO.2007.14.2851 18258984 135. Dulko D Pace C Dittus K Sprague B Pollack L Hawkins N Barriers and facilitators to implementing cancer survivorship care plans Oncol Nurs Forum 2013 40 6 575 80 10.1188/13.ONF.575-580 24161636

PMC005xxxxxx/PMC5000505.txt

==== Front BMC Public HealthBMC Public HealthBMC Public Health1471-2458BioMed Central London 357110.1186/s12889-016-3571-2Research ArticleSmall scale water treatment practice and associated factors at Burie Zuria Woreda Rural Households, Northwest Ethiopia, 2015: cross sectional study Belay Hailegebriel haile192011@yahoo.com 1Dagnew Zewdu zewdudagnew@yahoo.com 2Abebe Nurilign +251-9-10-10-62-95nure113@gmail.com 21 Burie Woreda, Burie, Ethiopia 2 Public health department, Medicine and Health Sciences College, Debre Markos University, Debre Markos, Ethiopia 26 8 2016 26 8 2016 2016 16 1 88725 5 2016 19 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Consuming unsafe water results in infections that lead to illness or death from water borne diseases. Though there is an increasing effort from Ethiopian government to access safe water still there are households with limited access of safe water as a result, they depend on rain, well and spring water source for domestic use. However, the water treatment practice with the available technology is not studied before in the study area. This study was conducted in rural area where there was no improved water source for domestic consumption. Households’ access water from rain, spring, river and well water which need some ways of action to make water safe for the intended utilization termed as treatment. Hence, the aim of this study was to assess magnitude of small scale water treatment practices and associated factors at household level in Burie zuria woreda, North West Ethiopia, 2015. Methods Community based cross-sectional study design with multi-stage sampling technique was used to evaluate water treatment practice and associated factors among rural households in Burie Zuria Woreda. A total of 797 households included in the study. Completeness of questionnaires were checked daily and data were coded and entered into Epi-Data and transported to SPSS version 16 software package for further analysis. Binary and multivariable logistic regression models fit to identify associated factors at 95 % CI and P-value <0.05. Result A total of 797 out of 846 participants responded to a questionnaire with a response rate of 94.2 %. The mean age of respondents was 44.9(SD ±10.7) years. Among the total study participants, 357(44.8 %) of them were practicing small scale water treatment at household level. Methods of water treatment at household level were; chlorine, boiling and let stand and settle. Associated factors were female headed households practice water treatment than male headed households (AOR = 1.80, 95 % CI = 1.24–2.62), educational status of being literate was associated with water treatment than illiterates (AOR = 2.07, 95 % CI = 1.51–2.83), dipping of water was associated with water treatment practice than pouring from the water collection jar (AOR = 4.11, 95 % CI = 2.89–5.85) and those households more frequently fetch water were practicing water treatment than those fetch less frequently (AOR = 4.90, 95 % CI = 2.92–8.22) and (AOR = 3.76, 95 % CI = 1.97–7.18) respectively were found to be significantly associated with small scale water treatment practice at household level. Conclusions Small scale water treatment at household level is still low in the study area. Females headed households, educated people, dipping from the jar and those who fetch water more than twice a day were significant factors for water treatment. Therefore females’ practice should be maintained and scale up for male headed households. Those with no primary education need special emphasis to educate them on the importance of water treatment. Encourage education through non formal mechanisms for rural people are also recommended. Keywords Small scaleWater treatmentRuralFactorsBurieDebre Markos University7000Abebe Nurilign issue-copyright-statement© The Author(s) 2016 ==== Body Background Treating water and safely storing it in the home are commonly referred to as “household water treatment and safe storage” (HWTS) or treating water at the “point of use”. Although HWTS is not new, its recognition as a key strategy for improving public health is just emerging. For centuries, households have used a variety of methods for improving the appearance and taste of drinking water. Even before germ theory was well established, successive generations were taught to boil water, expose it to the sun or store it in metal containers with biocide properties, all in an effort to make it safer to drink [1]. Treat water that has become contaminated both at the source as well as through domestic handling with the goal of reducing contamination to levels of low microbial risk is said to be household water treatment [2]. Human being have a right to water and entitles everyone to have sufficient, safe, acceptable, physically accessible and affordable water for personal and domestic uses [3, 4]. Lack of clean drinking water, poor sanitation facilities and lack of community education programs are contributing to continued outbreaks of acute watery diarrhea in some parts of Ethiopia [5]. Water supply and sanitation situation in Ethiopia is very poor, as most of the population does not have access to safe and adequate water supply and sanitation facilities. As a result three-fourth of the health problems in Ethiopia is due to communicable diseases attributable to unsafe or inadequate water supply and improper waste management particularly excreta [6]. Ethiopian rural water coverage has increased at promising rates since 1990, from 8 to 26 % according to joint monitoring program (JMP/UNICEF-WHO) figures, and from 11 to 62 % according to government figures [7]. Even though there is great discrepancy between the two reports; both figures indicate that there is problem in water coverage in rural Ethiopia. To have access to safe drinking water does not only imply microbial and chemically safe water, but also to have a secured supply and public access to the water sources. Household treatment of water is widespread over the world, but in Ethiopia, only 5 % of the population make use of it. Nevertheless, access to safe drinking water is very low [8]. This study is first in its kind as far as the researchers’ knowledge of searching in the scientific published papers there was no published article in this area. Since the study was done in the rural area with sole source of water is not piped which is river, spring, rain water and hand dung well source of drinking water, that needs treatment at point of use. it can be used as initial point to change the peoples’ behavior to domestic water treatment. However, the practice of making water “safe” to dink-treatment is not studied in the study area. The government encourages, domestic water treatment using chlorine chemicals, boiling, and other means and proper utilization water through the rural health extension program. Therefore, recommended water treatment technologies in the package health extension manual are; boiling, expose for sun light, use of chlorine, filtration and other activities the society believe that make drinking water safe. Therefore, this stud tried to identify how the rural people use the available water treatment technology and factors associated with small scale/household level water treatment practice. Methods Study design Community based quantitative cross- sectional study design was employed to determine the magnitude of small scale water treatment practice and associated factors. Study area and period The study was conducted in Burie Zuria woreda (Woreda is second smallest administrative structure of Ethiopian government system next to Kebele). It is about 407 kilometers away from Addis Ababa-the capital city of Ethiopia in the North-Western direction and the study period was January 1 to March 15, 2015. The woreda has one urban and 18 rural Kebele (Kebele is the smallest administrative structure in Ethiopian government system) and the communities engage in animal rearing and crop production activities the total population of the woreda is 139,235. The woreda Water coverage (availability with 30 min travel or 1.5 Km away from households) and access (able to reach and use the available water) is 80 % and 84 % respectively as the information obtained from Woreda water office. According to 2007 national censes, Burie woreda has a total population of 143,132 of whom 71,208 are men and 71,924 are women; 25,975 (18.15 %) are urban inhabitants. Source of water is river, spring, hand dung well and rain water. The scarcity is there also especially at times of dry season (December to June) the study was done during these period. Populations Source populations were all rural households in Burie zuria Woreda and Study population was households who were living in the selected kebeles that fulfilled the inclusion criteria. Sampling unit was households and study units were head of the household. Households resided more than 6 months and age above18 years old were include since they can give complete image of the community and ethically accepted to participate in studies respectively. Head of households were interviewed with the assumption of getting correct response from them. Priority was given for women because they are more familiar with water handling than men. However where there is household with no women for any reason men were considered for interview. And individuals who were not accessed after second visit and those unable to communicate were excluded in the study. Sample size and sampling technique Sample size The sample size was calculated using single population proportion formula [9] by considering the following assumptions. n=Z2xpxqd2 1.962x50%x50%=3845%2, considering design effect 2 and 10 % of non-response rate, =846 households. Since there is no previous similar study, 50 % was taken as proportion (p), P = proportion of water treatment practice at household level, n = the required sample size, Z = A standard score corresponding to 95 % confidence level and d = margin error of 5 %. Sampling method and procedure Multi stage sampling technique was applied followed by systematic random sampling techniques. There were 19 kebeles in the woreda and out of these 20 % of the kebeles which are four in number (winma-Abay, Alefa, Gulem and Shakua) were selected by simple random sampling techniques and the household were selected by systematic random sampling method to get the desired study population. There were 1886 households in Winma-Abay kebele from this 272 households were selected. 1200 households were from Alefa kebele and 173 households were selected. 1120 and 1560 households were in shakua and Gulem kebeles respectively then 166 and 230 households were taken that gives 846 total study households. Variables Dependent variable Small scale water treatment practice (Yes/No). Independent variables Socio-demographic (Age, sex, educational status, and religion, marital status, occupational status, family size, head of a household and monthly income) and Environmental issues: Source of drinking water, days when water is not fetch, time taken for fetching, and ways of fetching the water from the collection jar. Operational definition Small scale water treatment was dictated as “Yes” for the question “Do you do anything to your water to make it safer to drink” if at least one of the following options was practiced at household level during data collection time. These were boiling, bleach/chlorine (Bishagary31 and Wuhager29), solar disinfection, stand and settle and strain through cloth filter. Options of water treatment were taken from WHO tool kit for household water treatment and storage evaluation program [10]. Data collection and measurement Nine grade ten completed data collectors and two diploma holders nurse supervisors were involved for data collection process. The training was given for two days for all data collectors and supervisors. The questionnaire was prepared based on the available literature reviewed to elicit magnitude and associated factors of water treatment. A conceptual framework was used for the development of the questionnaire. Data collection was done by pre tested and pre coded interview administered questionnaire. The questionnaire was originally prepared in English language and then translated to the local language (Amharic) and again translated to English for consistency. Data quality assurance The quality of data were assured by proper designing and pre-testing of the questionnaires and by giving training for the data collectors and supervisors before the actual data collection. Every day after data collection, questionnaires were reviewed and checked for completeness and relevance by the supervisors and principal investigator and the necessary feedback was offered to data collectors in the next morning. Also, the principal investigators and an experienced data clerk were carefully entered and thoroughly cleaned the data before the commencement of the analysis. Data processing and analysis Completeness of questionnaires was checked visually and data were coded and entered into Epi-data version 3.5.4 and transported to SPSS version 16 software package for analysis. For controlling errors 10 % of the questionnaire was double entered, also frequency checks were done. Variables with P-value <0.25 in bivariate analysis were entered to multivariate analysis and p-value of 0.05 at 95 % CI and odds ratio were used to declare statistically significance. Ethical consideration The proposal was approved by Ethical Review Committee of College of Medicine and Health Science, Debre Markos University. All the study participants were informed about the purpose of the study and finally their oral consent was obtained before collecting data. The respondents informed that they have the right to refuse or terminate at any point of the data collecting. The information provided by each respondent was kept confidential. The dissemination of the finding does not also refer specific respondent. Result Socio-demographic characteristics respondents A total of 797 participants responded to a questionnaire with a response rate of 94.2 %. The mean age of respondents was 44.9 (SD, ±10.7) years. Among the total respondents, 597(74.9 %) of them were male and majority 652 (81.8 %) of them were married. Some 281(35.3 %) of them were illiterate. By occupational status of the respondents, 737(92.5 %), 31(3.9 %) and 29(3.6 %) were farmers, daily laborers and merchants respectively. Most 531(66.6 %), of them had a family size of ≥5 and 647(81.2 %) a head of household father and 406(50.9 %) of the respondents monthly average income was ≥1000 ETB (Table 1).Table 1 Socio-demographic characteristics of respondents on small scale water treatment practice and associated factor at house hold level at Burie zuria woreda rural HHs, west Gojjam zone, Northwest Ethiopia, 2015 (N = 797) Variable Category Frequency % Sex Male 597 74.9 Female 200 25.1 Age 18–30 years 75 9.4 31–45 years 348 43.7 46–65 years 355 44.5 >65 years 19 2.4 Educational status Illiterate 281 35.3 Literate 516 64.7 Religion Orthodox 791 99.2 Muslim 6 0.8 Marital status Married 652 81.8 Single 54 6.8 Divorced 54 6.8 Widowed 37 4.6 Occupational status Farmer 737 92.5 Daily labourer 31 3.9 Merchant 29 3.6 Number of individuals in the family 1 31 3.9 2–4 235 29.5 ≥5 531 66.6 Head of a household Father 647 81.2 Mother 150 18.8 Monthly income ≤500 ETB 4 0.5 501–999 ETB 387 48.6 ≥1000 ETB 406 50.9 Environmental characteristics Among the total study participants, majority 716(89.8 %) of them were getting water from hand dug well and 578(72.5 %) reported that there were days in week households did not fetch water for religious purpose which were mostly (56.7 %) was on weekend (Table 2) and some monthly holidays.Table 2 Environmental characteristics of respondents on small scale water treatment practice and associated factor at house hold level at Burie zuria woreda rural Northwest Ethiopia, 2015 Variables Category Frequency % Source of drinking water Protected well 716 89.8 Unprotected well/spring 5 0.6 Rain water 76 9.6 Are there days of the week water source having no services? No 219 27.5 Yes 578 72.5 Which days source of water is off (N = 578) Saturday and Sunday 501 86.7 Holly day and Sunday 77 13.3 Experience of storing water for three days No 307 38.5 Yes 490 61.5 Type of container for storing the water (N = 490) Clay pot 264 53.9 Iron container 18 3.7 Jerri can 208 42.4 Number of containers (N = 490) One 99 20.2 Two 339 69.2 Three 52 10.6 Capacity of the container (N = 490) ≤25 Liters 200 40.8 >25 Liters 290 59.2 Containers covered (N = 490) No 5 1 Yes 485 99 Days the water is stored (N = 490) For two days 36 7.3 For three days 358 73.1 More than three days 96 19.6 Washing status of the container (N = 490) No 1 0.2 Yes 489 99.8 Materials used for washing the container Vegetation 427 87.1 Chemicals 4 0.8 only water 47 9.6 with soap 12 2.4 Time taken to fetch the water <30 minutes 773 97 30–60 minutes 24 3 The type of container for fetching the water Clay pot 165 20.7 Jerri can 632 80.1 How many times do you fetch per day One 181 22.7 Two 395 49.6 Three 151 18.9 Four 70 8.8 The way of water dipping Pouring 241 30.2 Dipping 556 69.8 Design of water drawing material With handle 685 85.9 Without handle 112 14.1 Place for putting water drawing material On shelf/table 728 91.3 On the floor 63 7.9 Inside the container 6 0.8 About, 490(61.5 %) of respondents had water storing experience out of which 264(53.9 %) stored in a clay pot. More than half 339(69.2 %), reported that they stored in two containers from which 290(59.2 %) of the containers had a capacity of storing ≥25 liters and from the observation during data collection period 485(60.85 %) water containers confirmed they had cover. The respondents water consumption per person per day was <10 liters. About 358(73.1 %) of households stored drinking water for three days and 489(99.8 %) responded that they washed the container before fetching water (Table 2). Small scale water treatment practice at household level Among the total study participants, 357(44.8 %) of them treated water at their home. They use different modality of treatment approaches. More than half 213(59.7 %) boil water, 74(20.7 %) settle and stand and 70(19.6 %) have used chlorine chemicals (wuhaAger29 and Bishagary31) which are available in the local market for water treatment purpose. It was composite of Bishagary31 (44.3 %), Wuhager29 (41.4 %) and chlorine10 (14.3 %) from chemicals. Factors associated with small scale water treatment practice at household level Bivariate analysis Small scale water treatment practice at household level varied under the influence of various factors. In this test each independent variables were tested against the dependent variable. Accordingly sex, educational status, occupational status and the way of fetching, timing for fetching were found to have P-value <0.25 in which this variables were taken to multivariate analysis (Table 3).Table 3 Bivariate Logistic Regression results on factors associated with small scale water treatment practice and associated factor at house hold level at Burie zuria woreda rural HHs, west Gojjam zone, Northwest Ethiopia, 2015 (N = 797) Variable Category Water treatment status COR (95 % CI) P-value Yes No Total Sex Male 289 308 597 1 Female 68 132 200 1.82(1.30–2.54) 0.000 Educational status of a respondent Illiterate 219 191 410 1 Literate 138 249 387 2.06(1.55–2.75) 0.000 Occupational status of a respondent Farmer 342 395 737 1 Daily laborer 6 25 31 3.60(1.46–8.89) 0.005 Merchant 9 20 29 1.92(0.86–4.28) 0.109 The way of fetching the water Pouring 158 83 241 1 Dipping 199 357 556 3.41(2.48–4.69) 0.000 Timing for fetching the water Once a day 84 67 151 1 Twice a day 215 180 395 1.05(0.72–1.53) 0.801 Three times a day 37 144 181 4.87(3.00–7.91) 0.000 Four times a day 21 49 70 2.92(1.60–5.35) 0.000 Multivariate analysis The method used was backward stepwise in order to get maximum significant variables. The results of multivariate model indicated that female headed households practice water treatment 1.24 times more likely than male headed households (AOR = 1.80, 95 % CI = 1.24–2.62), educational status of being literate were more than double to practice small scale water treatment at household level than those illiterate head of households (AOR = 2.07, 95 % CI = 1.51–2.83), dipping fetching water was associated with good practice of water treatment than pouring (AOR = 4.11, 95 % CI = 2.89–5.85) and frequency of fetching water more than three time a day was also positively associated with water treatment compared to less frequent (<3 times) a day (AOR = 4.90, 95 % CI = 2.92–8.22) furthermore, those fetch water four or more times a days were also prating water treatment almost 4 times than those fetch only once (AOR = 3.76, 95 % CI = 1.97–7.18) were found to be significantly associated with small scale water treatment practice at household level with P-value <0.05 (Table 4).Table 4 Bivariate and Multivariable Logistic Regression results on factors associated with small scale water treatment practice and associated factor at house hold level at Burie zuria woreda rural HHs, west Gojjam zone, Northwest Ethiopia, 2015 (N = 797) Variable Category Water treatment status COR (95 % CI) AOR (95 % CI) P-value Yes No Sex Male 289 308 1 1 Female 68 132 1.82(1.30–2.54) 1.80(1.24–2.62) 0.002 Educational status of a respondent Illiterate 219 191 1 1 Literate 138 249 2.06(1.55–2.75) 2.07(1.51–2.83) .000 Occupational status of a respondent Farmer 342 395 1 1 Daily laborer 6 25 3.60(1.46–8.89) 2.06(0.72–5.58) 0.183 Merchant 9 20 1.92(0.86–4.28) 1.25(0.49–3.15) 0.630 The way of fetching the water Pouring 158 83 1 1 Dipping 199 357 3.41(2.48–4.69) 4.11(2.89–5.85) .000 Timing for fetching the water Once a day 84 67 1 1 Twice a day 215 180 1.05(0.72–1.53) 1.17 (0.78–1.74) 0.438 Three times a day 37 144 4.87(3.00–7.91) 4.90 (2.92–8.22) 0.000 Four times a day 21 49 2.92(1.60–5.35) 3.76 (1.97–7.18) .000 The result is interpreted as female respondents were 1.8 times more likely to practice small scale water treatment at household level compared to their counterparts males (AOR = 1.80, 95 % CI = 1.24–2.62) and literate respondents were 2.07 times more likely to practice small scale water treatment at household level compared to those who were illiterate (AOR = 2.07, 95 % CI = 1.51–2.83). Similarly, respondents who draw their water by dipping their container were 4.11 times more likely to practice small scale water treatment at household level compared to those who fetched their water by pouring their container (AOR = 4.11, 95 % CI = 2.89–5.85) and those respondents who fetched their water three times a day (AOR = 4.90, 95 % CI = 2.92–8.22) and four times a day (AOR = 3.76, 95 % CI = 1.97–7.18) were 4.90 and 3.76 times more likely to practice small scale water treatment at household level compared to those who fetched their water once a day. Discussion Among the total study participants, 357(44.8 %) of them practiced small scale water treatment at household level. This finding is lower than MDG strategy that was planned to reduce the proportion of people without sustainable access to safe drinking water and proper sanitation to half of its number by 2015 [11] but higher than the findings from WHO estimate of China, middle and low income countries 20 % and 33 % respectively [12], Zambia 35.2 % [13] and Ethiopia where, 80 % of the rural and 20 % of urban population have no access to safe water; which is the least among the continent [14]. The possible explanations for this finding being lower might be related with sample size, study design and study period but for that of the study being higher might be related with sample size, study design and differences in year of study. In this study about 59.7 % of the households used boiling as treatment strategy. About 20.7 % used settle and stand and 19.6 % used chlorine as domestic water treatment options. Majority of them used boiling this might be due to the method is easy to practice, mostly the households have the required material to do so and there is water boiling practice for other purposes like for coffee, washing heavily soiled utensils. This was in line with the suggestion given by CDC [15]. On the other hand none of them use solar system for water treatment. It can be due to non-availability of the technology and the population is from the rural Ethiopia. Some used chlorine since it is costly and available only in the urban market where most of the residents visit market rarely. There is also evidence of discomfort from change in taste and odor following the utilization of chlorine [16] that might contribute for less utilization compared to boiling. Even though there is a practice of settle and stand for household water treatment, it smaller relative to boiling. This might be due to little amount of water in the house to settle and wait till settlement. Additionally there was lack of appropriate water storage material in the house. Female respondents were 1.8 times more likely to practice small scale water treatment at household level compared to their counterparts (AOR = 1.80, 95 % CI = 1.24–2.62). This finding was in line with the finding by Maria Elena Figueroa and D. Lawrence Kincaid [17]. The possible justification for the finding might be due to the fact that in most communities fetching and storing water at household level are the responsibilities of females and among the cares given to the family providing water treated at home is one of the critical cares. Literate respondents were 2.07 times more likely to practice small scale water treatment at household level compared to those who were illiterate (AOR = 2.07, 95 % CI = 1.51–2.83). This finding was in line with the finding by Maria Elena Figueroa and D. Lawrence Kincaid [17]. The possible explanation for this finding might be due to the fact that literates might read leaflets and brushers and may better understand health risks of drinking contaminated water. Respondents who draw their water by dipping their container were 4.11 times more likely to practice small scale water treatment at household level compared to those who draw their water by pouring their container (AOR = 4.11, 95 % CI = 2.89–5.85). This may be due to the fact that they might think that dipping the container for fetching may be liable to contaminants and to avoid those contaminants, respondents may employ either of the methods for water treatment at household level. Those respondents who fetched their water three times a day (AOR = 4.90, 95 % CI = 2.92–8.22) and four times a day (AOR = 3.76, 95 % CI = 1.97–7.18) were 4.90 and 3.76 times more likely to practice small scale water treatment at household level compared to those who fetched their water once a day. The possible reasons for this may be those who fetched the water most frequently may have a chance to store their water which in turn enables them to treat their water by storing. Limitations of the study ✓ Cross-sectional nature of the study design could not show cause effect relationship Conclusion Small scale water treatment at household level is still low. Female respondents were better practicing in small scale water treatment at household level than males. Educational status was also factor for water treatment practice in which, literate were better practicing small scale water treatment at household level than those who were illiterate. Who had an experience of drawing water by dipping were better practicing small scale water treatment at household level better than those who draw by pouring and those who were fetching the water more than two times a day were better practicing small scale water treatment at household level than those who were fetching once a day. Recommendation ➢ According to the results of this research, Woreda Health office of Burie Zuria Woreda should:-✓ Give attention for those who were illiterate about small scale water treatment at household level ✓ Scale up experience of small scale water treatment at household level by females and literates to their counter parts ➢ Governmental and non-governmental organizations should:-✓ Advocate small scale water treatment practice at household level for males, illiterates and for those who fetched their water by pouring and once a day ➢ Households who were not practicing small scale water treatment at household level should:-✓ Treat water at their house before consumption ✓ Learn on how to treat water from households with educational literate and females Abbreviations AORAdjusted odds ratio CORCrude odds ratio HHHousehold MDGMillennium Development Goal WHOWord Health Organization Acknowledgements We would like to express our heartfelt gratitude to Debre Markos University for allowing conducting this study. Burie Zuria Woreda administrators, data collectors and respondents also deserve special acknowledgments for their support to the reality of the study. Funding It is partially funded by Debre Markos University for stationary and from the Authors for data collection. Availability of data and material We have soft copy of the data in SPSS and can be check if needed. Authors’ contributions HB contributed to proposal development, pre-testing the questionnaires, data cleaning, data analysis, and manuscript preparation. ZD and NA contributed to proposal development, pre-testing the questionnaire, supervising the data collectors and data entry. All the authors have read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate The proposal was approved by Ethical Review Committee of College of Medicine and Health Science, Debre Markos University. All the study participants were informed about the purpose of the study and finally their oral consent was obtained before collecting data. The respondents had the right to refuse or terminate at any point of the data collecting. The information provided by each respondent was kept confidential. The dissemination of the finding could not refer specific respondent. ==== Refs References 1. World Health organization. Households water treatment and save storage 2013. Western Pacific Region. Geneva; 2013. 2. World Health organization: Meeting the MDG drinking water and sanitation target. WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation (JMP); a mid-term assessment of progress. Geneva; 2004. 3. African Development Bank Infrastructure Development in Africa, African Development Report 1999 New York Oxford University Press 4. World Health organization. The Right to Water, Health and Human Rights, Publication Series − 3, France; 2003. 5. United States Agency for International Development. Ethiopia – Complex food security crisis, Situation Report 1, Washington D.C, 1 − 4; 2007. 6. Getachew B. Integrated water and land management research and capacity building priorities for Ethiopia. Proceedings of MoWR/EARO/IWMI/ILRI international workshop held at ILRI, Addis Ababa, Ethiopia; 2002. 7. AMCOW Country Status Overview. Water Supply and Sanitation in Ethiopia Turning Finance into Services for 2015 and Beyond. www.wsp.org/sites/wsp.org/files/accessed on 21 July 2016. 8. Rosa G, Clasen T. Estimating the scope of household water treatment in low- and medium-income countries. Am J Trop Med Hyg. 2010;82(2):289-300. 9. Daniel WW A Foundation For Analysis In The Health Sciences: Biostatistics eighth edition 1978 USA Laurie Rosa tone 10. World Health Organization. A toolkit for monitoring and evaluating household water treatment and safe storage programmers. Geneva 27, Switzerland. 2012. 11. United Nations The Millennium Development Goals Report 2005 New York United Nations Department of Public Information 12. WHO Household water treatment and safe storage manual for the participant 2013 13. Quick RE Kimura A Thevos A Tembo M Shamputa I Hutwagner L Mintz E Diarrhea Prevention through Household-Level Water Disinfection and Safe Storage in Zambiam 2002 14. Ministry of Health: Need Assessment to achieve Universal Access to Improved Sanitation and Hygiene. Unpublished Document, Addis Ababa, Ethiopia;2007. 15. CDC/UNAIDS. Household Water Treatment Options in Developing Countries: Boiling; 2009. 16. Awwa Research Foundation Long-Term Effects of Disinfection Changes on Water Quality 2007 17. Figueroa ME Kincaid DL Social, Cultural and Behavioral Correlates of Household Water Treatment and Storage 2010

PMC005xxxxxx/PMC5000506.txt

==== Front BMC GenomicsBMC GenomicsBMC Genomics1471-2164BioMed Central London 299910.1186/s12864-016-2999-1Research ArticleThe transcriptional and splicing landscape of intestinal organoids undergoing nutrient starvation or endoplasmic reticulum stress Tsalikis Jessica j.tsalikis@mail.utoronto.ca 1Pan Qun sandypan2010@gmail.com 2Tattoli Ivan ivan.tattoli@utoronto.ca 13Maisonneuve Charles charles.maisonneuve@mail.utoronto.ca 3Blencowe Benjamin J. b.blencowe@utoronto.ca 2Philpott Dana J. dana.philpott@utoronto.ca 3Girardin Stephen E. 1-416-978 7507stephen.girardin@utoronto.ca 131 Department of Laboratory Medicine and Pathobiology, Toronto, Canada 2 Department of Molecular Genetics, Donnelly Centre, Toronto, Canada 3 Department of Immunology, University of Toronto, Toronto, Canada 26 8 2016 26 8 2016 2016 17 1 68021 3 2016 5 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The intestinal epithelium plays a critical role in nutrient absorption and innate immune defense. Recent studies showed that metabolic stress pathways, in particular the integrated stress response (ISR), control intestinal epithelial cell fate and function. Here, we used RNA-seq to analyze the global transcript level and alternative splicing responses of primary murine enteroids undergoing two distinct ISR-triggering stresses, endoplasmic reticulum (ER) stress and nutrient starvation. Results Our results reveal the core transcript level response to ISR-associated stress in murine enteroids, which includes induction of stress transcription factors, as well as genes associated with chemotaxis and inflammation. We also identified the transcript expression signatures that are unique to each ISR stress. Among these, we observed that ER stress and nutrient starvation had opposite effects on intestinal stem cell (ISC) transcriptional reprogramming. In agreement, ER stress decreased EdU incorporation, a marker of cell proliferation, in primary murine enteroids, while nutrient starvation had an opposite effect. We also analyzed the impact of these cellular stresses on mRNA splicing regulation. Splicing events commonly regulated by both stresses affected genes regulating splicing and were associated with nonsense-mediated decay (NMD), suggesting that splicing is modulated by an auto-regulatory feedback loop during stress. In addition, we also identified a number of genes displaying stress-specific splicing regulation. We suggest that functional gene expression diversity may arise during stress by the coordination of alternative splicing and alternative translation, and that this diversity might contribute to the cellular response to stress. Conclusions Together, these results provide novel understanding of the importance of metabolic stress pathways in the intestinal epithelium. Specifically, the importance of cellular stresses in the regulation of immune and defense function, metabolism, proliferation and ISC activity in the intestinal epithelium is highlighted. Furthermore, this work highlights an under-appreciated role played by alternative splicing in shaping the response to stress and reveals a potential mechanism for gene regulation involving coupling of AS and alternative translation start sites. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2999-1) contains supplementary material, which is available to authorized users. http://dx.doi.org/http://dx.doi.org/10.13039/501100000019Crohn's and Colitis Foundation of Canadaissue-copyright-statement© The Author(s) 2016 ==== Body Background The cellular stress response represents a universal mechanism by which cells can sense and adapt to a variety of environmental changes. Several cellular stresses use related kinases to trigger the phosphorylation of a key residue (Ser51) in eIF2α, a translation initiation factor, resulting in global translation arrest. This cellular process is conserved from yeast to humans and is named the Integrated Stress Response (ISR). In humans, four related kinases induce eIF2α phosphorylation. General controlled nonderepressible 2 (GCN2) senses amino acid (AA) starvation, heme-regulated inhibitor (HRI) responds to oxidative stress, protein kinase R (PKR) detects viral RNA, and PKR-like endoplasmic reticulum kinase (PERK) is activated in response to endoplasmic reticulum (ER) stress [1]. A number of studies associated the pathology of severe inflammatory bowel diseases (IBD) such as Crohn’s disease and ulcerative colitis with an inability to properly adapt to the ‘stressful’ intestinal environment, resulting in unresolved mucosal inflammation. For example, studies in mice displaying a nonphosphorylatable Ser51Ala mutant eIF2α in intestinal epithelial cells (IECs) revealed that eIF2α phosphorylation is essential for proper Paneth cell function, and mutant mice displayed increased susceptibility to oral Salmonella infection and dextran sulfate sodium (DSS)-induced colitis [2]. Furthermore, Hamilton et al. report a marked improvement in recovery upon DSS treatment in mice lacking the transcription factor cEBP homologous protein (CHOP) – a key mediator in the ER stress-mediated apoptosis pathway induced by eIF2α phosphorylation, whereas deletion of the eIF2α kinase GCN2, which modulates T cell responses during amino acid starvation, worsened disease progression [3]. Many IBD patients present with elevated levels of ER stress markers and significant impairments within components of the unfolded protein response (UPR), which facilitates protein folding during ER stress through upregulation of molecular chaperones. In fact, variants of the UPR transcription factor gene XBP1 have been identified as risk factors for the development of Crohn’s disease and ulcerative colitis. In addition to triggering increased autophagy and activation of ER stress markers PERK/eIF2α and ATF4, IEC-specific deletion of Xbp1 in mice results in spontaneous enteritis, as well as Paneth cell dysfunction and hyper-inflammation in response to bacterial products such as flagellin [4]. One model for studying the link between cellular stress and gut homeostasis is premised on the remarkable capacity for self-renewal possessed by intestinal stem cells (ISCs). Clevers et al. demonstrated that a single adult ISC positive for the marker Lgr5 could generate a self-organizing stratified epithelium consisting of all the major cell lineages of the gut when cultured on a glycoprotein substratum (MatrigelTM) in condition media supplemented with appropriate growth factors [5]. Specifically, ISCs differentiate into 3D organ-resembling structures or ‘organoids’, which are comprised of villi and crypts, with crypt-residing Lgr5+ stem cells, highly proliferative undifferentiated transit-amplifying (TA) cells and differentiated cells (Paneth, enterocytes, goblet, enteroendocrine and tuft cells). Recently, the link between ER stress and ISC self-renewal was highlighted by the finding that differentiated villus cells display high levels of ER stress, measured by expression of various UPR components, and that this induction of ER stress causes a rapid loss of the stem cell signature in a PERK/eIF2α-dependent manner [6]. In addition to changes in the landscape of transcript expression upon stress, there is increasing evidence that alternative splicing (AS) enhances the ability of cells to cope with various stresses. In plants, genome-wide RNA sequencing (RNA-seq) based approaches have highlighted a role for AS as a key mode of generating genome plasticity during abiotic stresses such as osmotic shock, thermal shock and drought (Reviewed in [7]). Interestingly, many stress-regulated AS events in both plants and mammals are associated with genes encoding splicing factors and various RNA processing proteins [8–10]. Furthermore, several studies have shed light on the effect of cellular localization of core spliceosomal factors such as hnRNP A1 on pre-mRNA splicing during oxidative stress and heat shock [11, 12]. Despite expanding knowledge in the field, a comprehensive global analysis of how the AS landscape is modulated during stress in mammalian systems is lacking. Here, we provide the first genome-wide characterization of the impact of ER stress and nutrient starvation on both the steady-state transcript levels and AS landscape in primary murine organoid cultures. Our results highlight the core response to ISR-associated stress, which includes the prominent induction of stress transcription factors and inflammatory genes. Furthermore, we observed that ER stress and nutrient starvation surprisingly had opposite effects on ISC reprogramming and proliferation. Our analysis of AS highlighted the common role of ER stress and nutrient starvation in regulating splicing of detained introns in splicing genes, likely revealing a homeostatic level of feedback control of the splicing machinery. In addition, many of the reported AS events were stress-specific. Our analysis revealed that stress-specific pools of genes might be regulated by the coordination of alternative splicing and alternative translation to generate functional diversity, and this mechanism might represent a previously unrecognized mechanism of cellular response to stress. Because these analyses were performed in primary intestinal organoids and not in a cancer cell line, our results provide a faithful analysis of the genome-wide effect of the ISR in a near-physiological context of growing intestinal crypts. Together, this study provides insights into the importance of cellular stresses in the regulation of immune and defense function, metabolism, proliferation and ISC activity in the intestinal epithelium. Methods Crypt isolation and organoid culture To generate organoid cultures, crypts from the small intestines of wildtype mice (12 total) were extracted as previously described [5]. Briefly, the villi of the small intestine were removed by scraping, followed by washing with cold PBS. The remaining tissue were then homogenized and incubated in 2 mM EDTA in PBS for 30 min at 4 °C, followed by vigorous washing in PBS several times to obtain crypt-enriched supernatant fractions. The supernatant fractions were then passed through a cell strainer, pelleted at 300 g for 5 min at 4 °C and resuspended in 50 ul Matrigel (Corning). The crypt-containing organoids were cultured by plating onto the center of a 24-well plate and grown in 500 ul crypt culture medium supplemented with growth factors (R-spondin 1, Noggin, EGF). Organoids were allowed to grow 7 days, followed by passaging onto 6-well plates for stimulation (roughly 10-15 isolated organoids). To prepare samples for RNA-seq, organoids were left either unstimulated or treated with 5 uM thapsigargin (Sigma-Aldrich) or Krebs Ringer Bicarbonate (KRB) buffer for nutrient starvation conditions (118.5 mM NaCl, 4.74 mM KCl, 1.18 mM KH2PO4, 23.4 mM NaHCO3, 5 mM glucose, 2.5 mM CaCl2, and 1.18 mM MgSO4, pH 7.6) for 4 h. Samples were then pelleted by centrifuging at 1000 RPM for 10 min and homogenized using the QIAshredder according to the manufacturer’s protocol. RNA-seq library preparation and sequencing Total RNA was then extracted from the organoid samples using the GeneJET™ RNA Purification Kit (Thermo Scientific) according to the manufacturer’s protocol. Eluted RNA was treated with DNAse I (Fermentas) at 37 °C to remove genomic DNA. Triplicate samples containing 4 ug of RNA extracted from control vs. thapsigargin treated (5 mM for 4 h) and control vs. nutrient starved (4 h) primary murine enteroids were submitted for RNA-seq at the Donnelly Sequencing Center at the University of Toronto. Illumina TruSeq V2 mRNA libraries were generated, followed by ~100 million 100-bp paired end reads via Illumina HigSeq2500. Three replicates for each condition were sequenced. Alternative splicing analysis was performed essentially as previously described [13, 14]. In brief, RNA-Seq reads were first aligned to canonical transcript sequences, and reads mapping to more than one location were removed. The remaining reads were mapped to a database of mouse splice junctions, allowing up to two mismatches/indels (insertions or deletions). The percent inclusion, or “percent spliced-in” (PSI) value, and percent intron retained (PIR) value for each internal exon and intron, respectively, was calculated as previously described [14, 15].  Gene expression analysis GO analysis was conducted to assess gene enrichment upon thapsigargin treatment or nutrient starvation, analyzed from the Sanger database for GO terms. Genome wide analysis resulted in a manually curated list of 8 groups (Group 1 – Cell Signalling, Group 2 – Channels/Transporters, Group 3 – Cytoskeleton, Group 4 – Gene Expression, Group 5 – Metabolism, Group 6 – Receptors/PM/ECM, Group 7 – Secreted, Group 8 – Uncertain), which were used for subsequent expression analyses. Scatterplot expression graphs were generated using GraphdPad Prism software, red lines designate genes expressed more or less than 2.5-fold. Proliferation assay Organoid cell proliferation was measured by flow cytometry using the Click-iT EdU AlexaFluor647 Flow Cytometry Assay Kit (Life Technologies). Semi-quantitative RT-PCR validation of AS events Following RNA extraction, genomic DNA contaminants were removed via treatment with DNAse 1 for 45 min at 37 °C. Purified RNA was then reverse transcribed to cDNA using SuperScript III MMLV reverse transcriptase (Invitrogen) with random hexamers and oligo-dT primers. The cDNA was diluted appropriately and used as template for semi-quantitative PCR using Phusion polymerase according to manufacturer’s protocol using primers specific for AS events (see Table 1). PCR products were then run on an agarose (3 %) gel and visualized using Gel Doc 2000 Gel Imaging System (BioRad).Table 1 Murine RT-PCR primers used for AS event validation in this study Gene Name Primer Sequences (5’- 3)’ Hnrnpd FW: GAAAGTATCCAGGCGAGGTG RV: GCTATTAGCAGGTGGCAGGA Hnrpdl FW: CAGACTACAGCGGTCAGCAG RV: TGGACCAATACCCCCTACAA Srsf7 FW: CGCCTTGATTCAGAATGTCA RV: TGATCTTGACCTCCGTCCTC Ogt (partial intron 4 retention) FW: ACTGTGTTCGCAGTGACCTG RV: CAAATCTCCCCTTGTGCATT Ogt (full intron 4 retention) FW: CTTGGTAGCAGCAGGTGACA RV: AATGCTCACGGTCTTGCTTT Slc35b1 FW: AAGGACCCAAACAGGAGACA RV: ATGGCACCCACATAGGAGAC Ufd1l FW: TGTTCATTTTATTTCAAAAATCGGAGC RV: AAGAACTCATCATAGTGCTCCTGC Ivnsabp1 FW: AGCATCTGGGAGAATGGAGA RV: CATCATCACTGCCAAACACC Casp4 FW: TGCTGAACGCAGTGACAAGC RV: TAAGAGCCTTTCGTGTACGGC Nnt FW: AACAGTGCAAGGAGGTGGAC RV: GTGCCAAGGTAAGCCACAAT Nt5c3 FW: GCTGGCCCAGTACATATTCA RV: GGGCATCTTTTCCCATTGTA Frrs1 FW: TTGCATTTCTCACGACCAG RV: TAGCCTCAGGAAGGGTGATG Statistical analysis Results are expressed as means ± s.e.m of data obtained in independent experiments. Significant differences between mean values were evaluated using a one-sample or unpaired t-tests. * indicates p < 0.05, ** indicates p < 0.01 and *** indicates p < 0.001. Results RNA-seq data collection of primary intestinal epithelial organoids undergoing ER stress or nutrient starvation In order to gain a global understanding of how IECs are regulated by stress, RNA-seq analysis was first conducted on mRNA extracted from small intestinal organoid cultures from six mice either left unstimulated or treated with thapsigargin, a molecule that induces ER stress (Fig. 1a). In a second set of experiments, intestinal organoids from six other mice were used to analyze by RNA-seq the impact of nutrient starvation on IEC gene expression programs. For both stresses, we chose to analyze an early response (4 h stimulation), to concentrate on immediate cellular responses to these stresses and limit the impact of potential regulatory feedback loops that could alter gene expression programs in these organoids in a paracrine or autocrine-dependent manner. Moreover, analyzing early responses to these stresses limited the potential impact of cell death, which was undetectable under our experimental conditions at this early time of stimulation (data not shown).Fig. 1 RNA-seq analysis of transcript levels in thapsigargin-stimulated and nutrient-starved murine enteroids. a Experimental design of samples submitted for RNA-seq. Intestinal organoid cultures were derived from three separate mice per condition. RNA was purified from organoids stimulated with either thapsigargin or nutrient-starved for 4 h and sent for RNA-seq. b Overview of the total number of genes analyzed (average over three replicates), including the adjusted total number of genes excluding those which had RPKM values >0. c, d Scatterplot analysis of the log10 changes in expression of the total (adjusted for RPKM values >0) number of genes in thapsigargin versus control enteroids (c) and nutrient starved versus control enteroids (d). e Violin scatter boxplot analysis of the genes induced and repressed more than 2.5 fold upon thapsigargin treatment and nutrient starvation. f Average fold change overall in the genes analyzed upon thapsigargin and nutrient starvation Gene expression analysis was performed using the RPKM (Read Per Kilobase of transcript per Million) normalization method. A total of 21,553 genes were analyzed per condition, of which approx. 16,000 had detectable (>0) expression in organoids in the experimental conditions analyzed (Fig. 1b and Additional file 1: Table S1). In agreement with the role of the intestinal epithelium in nutrient absorption and host defense, the genes most expressed in our organoid cultures were associated with metabolism (including Aldoa, Aldob, Mt1, Mt2, Apoa1, Ldha) and innate immunity (Gm15284, Defa24, Lyz1) (Additional file 2: Table S2). Global analysis showed that, for each experimental condition, the triplicate cultures of organoids displayed overall very robust consistency in gene expression, with average correlation coefficients (standard deviation between triplicates divided by the mean for each gene analyzed) ranging between 0.338 to 0.455 (Fig. 1b). The coefficient of determination (R2) for both datasets (CTR_1 versus Thapsi_1 and CTR_2 versus Starv_2) was close to 1 (0.9956 and 0.9982, respectively), thus indicating that little experimental noise was generated in our assays and that most genes were not extensively altered at the transcript level by the stimulations (Fig. 1b-d). Nevertheless, 651 and 245 genes were found to be upregulated (>2.5x) and down-regulated (<0.4x) in thapsigargin-stimulated organoids, respectively, while 240 and 165 genes were found to be upregulated (>2.5x) and down-regulated (<0.4x) in nutrient starved organoids, respectively (Fig. 1e and Additional file 2: Table S2). On average, genes expressed in intestinal organoids were upregulated 1.35x and 1.10x by thapsigargin and nutrient starvation, respectively (Fig. 1f). Transcript level analysis of murine intestinal epithelial organoids undergoing ER stress We first analyzed the transcriptional response to thapsigargin in primary intestinal organoids. As expected, the transcriptional landscape shaped by thapsigargin treatment displayed a very strong (p = 1.6 × 10-12) ER stress-associated signature, and Gene Ontology (GO) analysis revealed that GO #0034976 (“Response to endoplasmic reticulum stress”) was the most significantly associated GO group among genes upregulated >2.5 fold by thapsigargin. ER stress related genes such as Atf3, Chac1, Thbs1, Ddit3, Derl3, Herpud1 and Hspa5 were upregulated more than 2.5 fold (Fig. 2a). Furthermore, the ER stress and UPR-associated transcription factor Xbp1, which is alternatively spliced upon ER stress, clearly underwent splicing to generate the exon 4 Δ26bp ER stress-specific isoform (Fig. 2b), and its expression was upregulated 2.5 fold. Thus, thapsigargin stimulation resulted in a strong induction of ER stress-associated responses in intestinal organoids.Fig. 2 Induction of an ER stress transcriptional program in thapsigargin-stimulated enteroids. a Scatterplot of the expression of ER stress response classified genes. Genes above the top red line represent a 2.5-fold increase in expression, while genes below the bottom red line represent genes down-regulated 2.5-fold. b Alternative splicing of transcription factor gene Xbp1 upon thapsigargin treatment, visualized via integrated genome browser (IGV). c Venn diagram analysis of 651 genes upregulated more than 2.5 fold upon 4 h of thapsigargin treatment, categorized by gene function. d Gene list manually curated based on gene function from the group of 651 upregulated genes. e Venn diagram analysis of 245 genes down-regulated more than 2.5 fold upon 4 h of thapsigargin treatment, categorized by gene function. f Gene list manually curated based on gene function from the group of 245 downregulated genes Analysis of the 651 genes induced by thapsigargin over 2.5 fold revealed that, in addition to the core ER stress reprogramming at the transcript level, genes associated with cellular signaling (Group 1), gene expression regulation (Group 4), metabolism (Group 5) and the cytoskeleton (Group 3) were upregulated, as well as genes encoding channels and transporters (Group 2), cell surface molecules, receptors and extracellular matrix proteins (Group 6) and secreted factors (Group 7) (Fig. 2c). Therefore, ER stress induction by thapsigargin triggers a global transcriptional adaptation in intestinal organoids that affects multiple cellular processes and pathways. Interestingly, a number of inflammation-associated genes were upregulated and were found mainly in Groups 6-7. These include the chemokines Cxcl10, Cxcl5, Cxcl1 and Ccl20, the cytokines Il23a and Tnf, the acute-phase response factor Saa3 and other genes encoding secreted mediators associated with inflammation, such as Fgf21 and Lcn2, as well as genes associated with the cellular adaptation to an inflammatory milieu (Hmox1) or innate immunity (Ifitm1, Nos2, Mx2, Defb40) (Fig. 2d). Thapsigargin stimulation also upregulated the expression of Fut1, a gene responsible for the fucosylation of extracellular matrix glycoproteins, an event that has recently been shown to play a major protective role in the response to bacterial pathogens in the small intestine [15]. Thus, in the intestinal epithelium, the cellular response to the ER stress inducer thapsigargin bears striking similarities to the inflammatory response against microbial infection. Thapsigargin stimulation also upregulated genes associated with chemotaxis, migration and locomotion as well as genes encoding growth factors or growth factors receptors (Fig. 2d), which were found in Groups 6-7. Such growth factors included Hgf, Egf, Ctgf, Gdf15, Manf, Vegfa, Vegfc and Vgf. This might be of physiological importance given the known contribution of ER stress in the modulation of cancer microenvironment and tumor growth [16]. Global transcriptional reprogramming commonly requires upregulation of a core group of transcription factors (TFs) as part of the first induction wave of so-called “immediate early genes”. In agreement, genes associated with Gene Expression Regulation (Group 4) represented the largest group of genes up-regulated by thapsigargin (N = 145) and among those genes, a remarkable number (N = 46) of TFs were identified (Fig. 2d). Moreover, TFs were also found among the genes that are down-regulated by thapsigargin, including Mycn and Myb as well as the Notch target Hes5. Interestingly, Notch-dependent genes and in particular Hes family members play key roles in intestinal cell fate decision and proliferation, suggesting a potential role of ER stress signaling in IEC lineage commitment through Hes5 down-regulation (see also below). Together, these immediate-early TFs likely play a critical role in shaping the global cellular transcriptional adaptation to ER stress. Thapsigargin stimulation also down-regulated the expression of a number of genes in intestinal organoids (N = 245 for genes down-regulated >2.5 fold = regulated <0.4 fold) (Fig. 2e). Of particular significance, we noticed that genes involved in metabolism (Group 5) were over-represented when compared to upregulated genes, suggesting that thapsigargin stimulation results in potent down-regulation of major cellular metabolic pathways (Fig. 2f). Moreover, among the genes associated with cellular signaling (Group 1), we noticed that a number encode for proteins associated with cell cycle regulation (Fig. 2f), suggesting a direct impact of thapsigargin on cellular proliferation (see also below, Fig. 4). Together, this analysis identified the core transcriptional program regulated by ER stress in primary intestinal organoids. Transcript level analysis of murine intestinal epithelial organoids undergoing nutrient starvation Primary murine organoids require a complex mixture of growth factors and nutrients to proliferate and to undergo differentiation of their stem cells into the different absorptive or secretory lineages of a functional intestinal epithelium. We chose to perform a short-term nutrient starvation by replacing the normal organoid culture medium with a Krebs-Ringer bicarbonate (KRB) buffer that lacks growth factors and AAs, which should result in acute inhibition of mTOR signaling and induction of the GCN2-dependent arm of the ISR. Under these conditions, although starvation resulted in the regulation of substantially fewer genes than thapsigargin (see above Fig. 1e), we noticed that the relative proportions of upregulated genes from Groups 1 to 7 were comparable between the thapsigargin and nutrient starved organoids (Additional file 3: Figure S1A). Similar to thapsigargin-treated organoids, a number of TFs, genes associated with inflammation, chemotaxis and growth factor signaling were identified in nutrient starved organoids (Additional file 3: Figure S1B). GO #0006935 (chemotaxis) was the most significantly associated GO term for genes upregulated >2.5 fold by nutrient starvation. With regards to genes down-regulated by nutrient starvation, 41.8 % (69/165) were genes whose function was uncharacterized (Additional file 3: Figure S1C), which is much greater than the percentage of uncharacterized thapsigargin-repressed genes (22.9 %) (Additional file 3: Figure S1D), suggesting that a significant portion of the cellular response to nutrient starvation in intestinal organoids involves poorly characterized pathways and processes. Nevertheless, among the genes with an attributed function, we noticed that much fewer were associated with cell cycle regulation as compared to genes down-regulated by thapsigargin (Additional file 3: Figure S1E), suggesting that ER stress and nutrient starvation affect cell cycle regulation in a distinct manner (see also Fig. 4 below). Finally, we observed that a number of genes associated with cellular innate immunity (Card11, Ifitm6, Mx2, Nlrp10, Nlrp1b, Nos3 and Noxa1) were downregulated by nutrient starvation, which contrasts with results obtained in thapsigargin-stimulated cells. Together, we provide a comprehensive analysis of the modulation of the transcriptional landscape by nutrient starvation and reveal global similarity/dissimilarity patterns as compared to the regulation occurring in cells undergoing ER stress. Identification of a common transcriptional signature for ER stress and nutrient starvation We aimed to take our analysis one step further and to identify the common transcriptional signature associated with these two ISR-triggering cellular stresses. Focusing first on upregulated genes, we found that a core group of 90 genes were upregulated by both stresses (Fig. 3a). Considering the pool sizes (N = 651 and N = 240 for thapsigargin stimulation and nutrient starvation, respectively), this intersection was found highly significant (p = 1.44×10-101), thus showing that a strong common transcriptional signature exists for genes upregulated by these two stresses. It must be noted that these common genes represented a smaller fraction of the thapsigargin upregulated pool (90/651 = 13.8 %) than the nutrient starvation upregulated pool (90/240 = 37.5 %), thus showing that in our experimental conditions, thapsigargin induced a wider spectrum of stress-specific genes than nutrient starvation. Consistent with this, a large majority of the genes induced by thapsigargin were not significantly modulated by nutrient starvation (Fig. 3b).Fig. 3 Nutrient starvation and ER stress induce a common transcriptional landscape in murine enteroids. a Venn diagram comparison of the genes commonly upregulated more than 2.5 fold upon nutrient starvation and thapsigargin treatment. Hypergeometric tests were used to calculate the P values for significance of overlaps. Scatterplot analysis of the genes transcriptionally upregulated (cutoff >2.5 fold) upon thapsigargin and nutrient starvation. Plots are displayed analyzing of the total number of genes (801) (b) or categorized by gene function (c). d Analysis of the gene function of the 90 genes commonly upregulated upon thapsigargin and nutrient starvation. e Expression profiles of genes encoding transcription factors and genes involved in inflammation/chemotaxis, manually picked from the 90 genes upregulated more than 2.5 fold upon thapsigargin/nutrient starvation. Expression profiles of three biological replicates per stimulation are shown (lanes a, b and c) When upregulated genes were separated in functional categories, it appeared that most of the genes upregulated by both stresses were found in Groups 4 (“Gene expression”), 6 (“Cell surface molecules, receptors and extracellular matrix proteins”), 7 (“Secreted”) and 1 (“Cellular signaling”) (Fig. 3c-d). Among the 90 common genes, those that were most upregulated by both conditions included TFs (found in Group 4) and factors associated with inflammation and/or chemotaxis (in Groups 6/7) (Fig. 3c and e). The analysis of down-regulated genes revealed that few genes (N = 18) were found to be down-regulated by both stresses (Additional file 4: Figure S2A-B), and these genes were either of uncertain function (7/18) or had unrelated functions (Additional file 4: Figure S2C-D). Together, these results demonstrate the existence of a common transcriptional signature associated with two distinct ISR-inducing stresses. While a core group of 11 TFs likely promotes this transcriptional reprogramming, genes associated with inflammation and chemotaxis were unexpectedly also part of this common transcriptional signature. Effect of cellular stress on intestinal stem cells and proliferation In primary intestinal organoids, cell proliferation is dependent on the activity of ISCs and ISC-derived transit-amplifying cells that express the marker Lgr5 and occupy an important fraction of the intestinal crypt [17]. The above results suggested that ER stress and nutrient starvation affected the expression of cell cycle and/or proliferation genes differentially in intestinal organoids (see Fig. 2 and Additional file 3: Figure S1). Therefore, to identify the overall impact of thapsigargin versus nutrient starvation on ISCs, we analyzed how these stresses affected the transcript levels of the 151 ISC-enriched genes identified recently by sorting Lgr5+ intestinal epithelial cells [18]. Interestingly, the majority of ISC genes displayed reduced expression following thapsigargin treatment (fold induction <1), while the opposite result was observed in nutrient starved cells (Fig. 4a). Overall, expression of ISC genes was not upregulated (1.06 fold) by thapsigargin while this treatment upregulated gene expression 1.34 fold genome-wide (Figs. 1f and 4b). In contrast, ISC genes were significantly more upregulated (1.41 fold) than all genes (1.1 fold) by nutrient starvation (Figs. 1f and 4b). Despite these differences, we observed that a group of seven genes were similarly modulated by both stresses: Tnfrsf19, Wwtr1, Vav3, Esrrg and Notch1 were down-regulated by thapsigargin and nutrient starvation, while Car12 and Rasa3 were upregulated. These seven genes might thus represent the core group of genes involved in the cellular adaptation of ISCs to stress.Fig. 4 Metabolic stress affects the expression profile of intestinal stem cell genes. a Scatterplot analysis of the fold expression profiles of 151 intestinal stem cell (ISC) genes upon thapsigargin and nutrient starvation. b Overall fold induction of ISC genes compared to the total gene induction upon thapsigargin treatment and nutrient starvation. c List of ISC genes upregulated and downregulation more than 2 fold upon stress. d Cell proliferation was analyzed by flow cytometry by monitoring EdU incorporation during the last 2 h of the 4 h treatment. Representative profiles of thapsigargin-treated (blue), nutrient-starved (green) and untreated control organoids (black) are shown. e Quantification of cell proliferation is presented as mean fluorescence intensity (MFI) Finally, we aimed to directly test the differential effect of thapsigargin and nutrient starvation on cellular proliferation in intestinal organoids by measuring EdU incorporation in organoids undergoing stress for 4 h. In agreement with the ISC gene expression data, we observed that thapsigargin stimulation resulted in potent reduction of EdU incorporation in organoids, indicative of a block in proliferation, while nutrient starvation had the opposite effect (Fig. 4d-e). Thus, while ER stress affects ISC gene expression and proliferation in a way that is expected for a cellular stress and is in line with previous results [6], short-term nutrient starvation appeared to trigger an apparently paradoxical pro-proliferative response. Analysis of the AS landscape in enteroids undergoing ER stress and nutrient deprivation One key aim of this study was to gain insight into the role of AS on gene regulation during metabolic stress – an idea that has been understudied in mammalian systems. In order to investigate global changes in AS occurring upon nutrient starvation and ER stress, AS events were analyzed from the RNA-seq dataset using criteria that has previously been described [13]. Applying a stringent cutoff (p ≥ 0.90, DBS = 0.1, RN = 5, SeeMethods) to identify high confidence AS events, we identified a group of 85 AS events that were significantly upregulated by thapsigargin treatment and 42 AS events induced by nutrient starvation (Fig. 5a, Additional file 5: Figure S3A and Additional file 6: Table S3). When classifying the AS events by type of splicing event, the largest group during ER stress corresponded to exon skipping (S/I) events, followed by an approximately 25 % proportion being alternative 5’ or 3’ donor/acceptor changes, with complex events (C3, C2, IR-C) representing the smallest percentage. During nutrient starvation however, we observed a more even distribution among S/I events and events involving full intron retention (IR-S), as IR-S and complex intron retention (IR-C) events comprised more than half of the observed AS events. To rule out that the increase in AS events could be attributed to simply an upregulation in transcription, we analyzed the expression levels of the genes found to undergo AS upon ER stress or nutrient starvation. Only a handful of genes were found to be upregulated at the transcript level (Casp4, Clk4, Cdkn2aip, Gpcpd1, Alg12, Taf1a, and 1110021L09Rik for ER stress and Glipr1 and Maff for nutrient starvation), while the rest of the genes underwent no significant change in expression (Fig. 5b, Additional file 5: Figure S3B).Fig. 5 Analysis of the alternative splicing landscape in murine enteroids upon thapsigargin treatment. a Classification of AS events induced upon thapsigargin based on type of splicing event (skipping(S)/inclusion(I), complex 1 (C1), complex 3 (C3), alternative 3’ (Alt3), intron retention simple (IR-S), intron retention complex (IR-C), complex 2 (C2), alternative 5’ (Alt5)). Examples of both skipping and inclusion events are shown. b Scatterplot of the expression of the genes found to undergo AS upon thapsigargin treatment. Genes above the top red line represent a 2.5-fold increase in expression, while genes below the bottom red line represent genes down-regulated 2.5-fold. c Comparison of the proportion of frameshifting vs. non-frameshifting events within each category of AS type. d Examples of frameshifting AS events in Srsf7 (S) and Smndc1 (Alt3). Gene schematics showing the AS events in blue, as well as the Sashimi plots obtained by IGV showing the total read numbers for each junction. e GO analysis of the gene group enrichment among the genes that underwent AS during thapsigargin treatment Interestingly, closer examination of the thapsigargin-regulated AS events displaying the highest confidence score in our analysis (p ≥ 0.95, DBS = 0.15, RN = 10) revealed that the vast majority of those events were predicted to produce a reading frame shifting caused by exon inclusion, skipping or alternative 5’/3’ splice site usage (Fig. 5c). Upon nutrient starvation conditions however, we observed that the proportion of AS events that resulted in frame shifted reading frames (29 out of 42 events = 69 %) was roughly that which would be expected by chance (2/3 = 66.6 %) (Additional file 5: Figure S3C). The predicted stress-induced AS events that met our cutoff criteria were visualized using Integrated Genome Viewer (IGV) (Fig. 5d and Additional file 5: Figure S3D). Gene ontology analysis of the most enriched gene family among the genes undergoing AS during both ER stress and nutrient deprivation revealed a significant enrichment for genes involved in mRNA splicing (p = 1.4x10-8), including the U snRNA maturation-associated factor Lsm7, the SR protein Srsf7 and the Smn paralog Smndc1 (Fig. 5e and Additional file 5: Figure S3E), providing further support for our results that identified a key role for metabolic stress stimuli in the dynamic regulation of the splicing machinery [19]. Increased expression of PTC-containing AS isoforms of RNA processing/splicing genes upon metabolic stress As mentioned above, GO analysis of the genes undergoing both thapsigargin- and nutrient deprivation-upregulated AS revealed a significant enrichment in genes associated with mRNA splicing regulation. Using the cut-off criteria outlined earlier, we observed a significant overlap (p = 9.6 × 10-8) of the AS events in splicing factors during nutrient starvation and ER stress and found five genes (Hnrnpd, Ogt, Srsf7, Ivns1abp and Hnrpdl) to be spliced identically during either stress (Fig. 6A). These events were analyzed by compared percent spliced-in (PSI) values, as well as Sashimi plots generated via IGV, and were all validated by RT-PCR analysis RNA splice variant specific primer pairs (Fig. 6B and primer list in Table 1). Interestingly, all of these events involved the partial or full retention of intronic sequences that resulted in the introduction of an in-frame premature stop codon, producing a transcript to be degraded by nonsense mediated decay (NMD) according to the 55-bp rule [20]. Furthermore, these NMD-inducing events are evolutionarily conserved, as identified by other groups [9].Fig. 6 ER stress and amino acid starvation induce a common alternative splicing signature. a Venn diagrams demonstrating the overlap between the AS events occurring during thapsigargin treatment and nutrient starvation. The overlap p value was calculated using a hypergeometric test. b Validation of AS events for Hnrnpd, Ogt, Srsf7, Ivns1abp, Hnrpdl. Gene schematics highlighting the AS events along with approximate location of the premature termination codon (PTC), along with PSI value plots for each event. Semi-quantitative RT-PCR validations for each event are shown, with the spliced PCR product labeled by an arrow. IGV plots of RNA-seq read for each AS event and adjacent sequence reads, with AS events highlighted accordingly Splicing of detained introns functions to regulate gene expression during cellular stress A recent study identified a pool of mRNAs containing retained introns (referred to as detained introns or DIs in this study) that were spliced post-transcriptionally under stress conditions [21]. Interestingly, splicing of these DIs often resulted in a frameshifting event that generated potential NMD splice variants. Strikingly, several DI-containing genes reported in human cells by Boutz et al. were orthologs of genes found in our list (Eny2, Ogt, Srsf7, Rbm39, Zfp326, Tra2a, Cdc16, Ivns1abp, Tex10, Hnrpdl, Slc35b1, Ufd1l and Clk4), suggesting that ER stress might represent a physiological means to regulate splicing of DIs. Notably, all five of the AS events mentioned above occurring upon both ER stress and nutrient deprivation represented DIs identified by Boutz et al. to flank premature termination codon (PTC)-containing cassette sequences. Furthermore, extended manual analysis using IGV software revealed that this trend was consistent in RNA-binding proteins (Rbm39), U1 snRNP related (Snrnp70), U2 snRNP related (Sf3b1), core SR proteins (Srsf3, Srsf6, Srsf5), and other SR proteins (Srrm1, Tra2a), among others (Additional file 7: Figure S4). In agreement with the hypothesis that thapsigargin-regulated AS events corresponded to DIs, several AS events identified were predicted to generate potential NMD variants. Boutz et al. identified that the SR protein kinase CLK4 and its homologue CLK1 possess PTC-containing DIs (introns 3 and 4) that are spliced out to generate a functional translated protein (Fig. 7a). This provides a means of autoregulation and serves as the upstream regulator of splicing of the downstream DIs, as treatment with the CLK inhibitor CB19 affected the splicing of >300 DIs [21]. Consistent with the previous observations that the “fully spliced” (DI-lacking) CLK1/4 transcripts encode a stable mRNA transcript, we observed an increase in expression of both CLK4 and CLK1 upon thapsigargin treatment (Fig. 7b). Furthermore, we observed an increase in CLK4 protein upon both thapsigargin and nutrient starvation (Fig. 7c). Interestingly, we observed significant splicing of introns 3 and 4 in both CLK1 and CLK4 upon thapsigargin treatment, analyzed by both PSI values and IGV Sashimi plots (Fig. 7d-e). Notably, there was no significant increase in CLK1/4 mRNA expression, nor did we observe any change in PSI levels of intron 3 or 4 upon nutrient starvation, suggesting the presence of another upstream mechanism to regulate DI splicing upon starvation.Fig. 7 Splicing of retained introns in CLK4/1 upon ER stress. a Gene schematic showing splicing of detained introns (introns 3 and 4) upon control conditions vs. stress conditions (red dotted line). b Plots of expression values for CLK1/4 upon thapsigargin treatment and nutrient starvation. c Western blot analysis of CLK4 protein upon thapsigargin and KRB stimulation for 6 or 20 h, as compared to tubulin loading control (d) PSI values for splicing of introns 3 and 4 of CLK1/4. e Sashimi plots representing the splicing of introns 3 and 4 of CLK1/4. Values in red represented the amount of DI splicing, calculated by taking the value of exon 4 skipped / (average of intron 3 retained, intron 4 retained), taken as an average of three biological replicates, with the standard deviation values. A higher value corresponds to more splicing of introns 3 and 4 and consequently, more retention of exon 4 Nutrient starvation and ER stress induce a subset of distinct AS events In addition to a common signature of AS induced in enteroids during nutrient deprivation and ER stress, we noticed that most AS events (80/85 and 37/42 for ER stress and nutrient starvation, respectively) were stress-specific. Notably, the vast majority of these AS events that were unique to ER stress or nutrient starvation occurred in genes involved in diverse biosynthetic pathways. For example, AS events induced by stress occurred in various families of enzymes, such as cysteine-type peptidases (ie. Usp15, Usp40), mannosyltransferases (ie. Alg9, Alg12), isomerases (ie. Rpe, Trub2) and serine/threonine kinases (ie. Bco2, Pla2g2a). Interestingly, 3 of the identified AS targets in thapsigargin-stimulated cells are factors previously associated with ER stress response, including Casp4, Slc35b1 and Ufd1l [22–24] (Fig. 8a, Additional file 8: Figure S5A). Furthermore, among the genes observed to undergo AS upon nutrient deprivation, several were involved enzymatic processes. Examples of these genes include the ferric-chelate reductase Frrs1 and the NAD(P) transhydrogenase Nnt, which both undergo increased exon skipping upon starvation, and the 5’-nucleotidase Nt5c3, a gene for which we observed increased retention of a portion of intronic sequence (Fig. 8b, Additional file 8: Figure S5B). These results suggest that AS of genes involved in the response to stress contributes to a regulatory program associated with the cellular response to ER stress and nutrient deprivation.Fig. 8 Validation of various alternative splicing events and in silico prediction of alternative ATG usage in splice variants induced upon cellular stress. a-b Six selected AS events induced upon thapsigargin treatment (Casp4, Slc35b1, Ufdl1) (a) and nutrient starvation (Frrs, Nnt, Nt5c3) (b). The type of AS event is indicated beside the gene name in parenthesis (S – skipping, Alt3 – alternative 3’, Alt5 – alternative 5’, C3 – complex type 3). Plots depicting the percent spliced-in (PSI) values for the AS events are shown. c-d Gene structures of full-length Casp4, Slc35b1, Nt5c3, Tinag, and Ufd1l using the canonical translation start sites (cATG) and their predicted splice variants induced by cellular stress (AS event highlighted in red). The alternative ATG (aATG) utilized by these variants were previously annotated by Aceview. The different protein domains encoded by the full-length and splice variants were analyzed using Simple Modular Architecture Research Tool (SMART) (c) and changes in protein localization were analyzed using PSORT (d) In silico prediction of the use of alternative translation start sites to generate novel isoforms We noticed that many AS events induced by thapsigargin affected exons towards the 5’ end of the mRNAs, and database search (Aceview) identified the existence of potential alternative ATG (aATG) as potential translation initiation sites for 12 genes (Casp4, Zfp326, Acot8, Ivns1abp, Tra2a, Rpl27a, G630016D24Rik, Slc35b1, Tex10, Rbm39, U2af1, BC024814) among the 32 genes with the highest confidence AS (p ≥ 0.95, DBS = 0.15, RN = 10, data not shown), which could support the expression of shorter variants with truncated N-terminal ends (Additional file 9: Figure S6). All of these genes have been reported by Wilson et al. to utilize a novel aATG in both mouse and humans to maintain the proper frame of reading. Interestingly, many of the isoforms that would be generated upon usage of an alternative aATG have prominent changes in either protein domains (Fig. 8c) or protein localization (Fig. 8d). For example, upon skipping of the Casp4 98 bp exon 3, a novel variant using a previously annotated aATG just after the splicing event would generate an isoform lacking the entire caspase activation and recruitment domain (CARD domain). Splicing of the solute carrier Slc35b1 in a manner that generates a 25 bp alternative 3’ event induced by thapsigargin and the 5’-nucleotidase Nt5c3, which undergoes an intron retention event of 55 bp upon nutrient starvation, resulted in the loss of 1 or more transmembrane domains and likely affects the subcellular localization of these proteins. Lastly, we predict that the thapsigargin-induced Alt3’ splicing of the ER stress gene Ufd1l and Alt5’ splicing of C1 family peptidase family gene Tinag would also utilize previously annotated aATGs to generate protein isoforms that are re-localized from the mitochondria to the cytosol, and the extracellular space to the nucleus, respectively [25]. Discussion Here we provide the first genome-wide snapshot of both the transcript level and AS reprogramming in response to cellular stress in primary IECs. The analysis presented here, which was conducted in an organoid model system derived from murine intestinal epithelial cells stimulated with two independent stresses – nutrient depletion and ER stress, provides a near-physiologically relevant investigation into the global response to metabolic stress in the gut. None of the top GO terms associated with genes upregulated by nutrient starvation were directly related to a response to the starvation itself. Instead, our analysis revealed that a large number of metabolic genes were down-regulated by nutrient starvation, suggesting that short-term nutrient starvation does not turn on major stress response programs but, rather, slows down metabolic processes. This contrasts with the results obtained with ER stress, for which a clear upregulation of a transcriptional ER stress response program was identified. It should be noted that the results presented in this study are representative of the effect of thapsigargin and further investigation with additional ER stress inducing drugs such as tunicamycin would reaffirm these data in the global response to ER stress. The transcriptional landscape regulated upon stress in primary intestinal cells reported here highlights a key link between cell stress and inflammatory immune responses. This likely stems from the fact that mucosal inflammation and chemokine-mediated recruitment of immune cells are both essential for the adaptation to stress within the intestinal epithelium. Indeed, the intestinal epithelium represents the first line of defense against pathogenic microbes and toxins infecting orally, and induction of an immune response during stress is essential for maintaining epithelial barrier integrity [26, 27]. Thus, our results highlight the importance of the ISR in the immune response of the intestinal epithelium, which is in agreement with reports linking stress signaling, such as XBP1-dependent pathways, with inflammatory bowel disease. Because the intestinal epithelium contains a population of actively proliferating stem cells along with differentiated secretory/absorptive cells, we analyzed whether cellular stress affects proliferation and/or the stem-cell profile in epithelial organoids. Strikingly, we observed an overall decrease in proliferation measured by EdU incorporation and expression of proliferation genes (ie. Wnt signaling), as well as decreased ISC gene expression in thapsigargin treated samples. Interestingly, the opposite effect was observed during nutrient starvation and there was a significant increase in proliferation measured by EdU incorporation. While initially surprising, this finding likely highlights a transient response by the intestinal epithelium to increase proliferation in order to absorb more nutrients during short periods of nutrient deprivation via expansion of the intestinal absorptive surface. This explanation could explain the opposite effects of thapsigargin treatment and nutrient deprivation on proliferation. It is possible that this characteristic is specific to the intestinal epithelium and may not necessarily reflect cellular responses to nutrient starvation in other tissues. Additionally, consistent with previous reports that ER stress results in a loss of “stemness” in organoid cultures, we observed decreased expression of stem cell markers such as Olfm4, Fzd2 and Msi1 upon thapsigargin treatment, highlighting the fact that ER stress plays a key role in maintaining stem cell homeostasis in the intestinal epithelium [6]. Our analyses also identified a group of seven intestinal stem cell (ISC) genes that were regulated similarly by both stimulations, suggesting that these genes might represent the core group of genes involved in the cellular adaptation of ISCs to stress. One prominent means of gene expression regulation among splicing factors is achieved by coupling AS with nonsense-mediated decay (NMD) [28, 29]. Specifically, highly conserved AS events promote inclusion of PTC-containing cassettes that consequently target transcripts for NMD; those AS events have been identified in SR proteins and various other RNA processing proteins [8, 9, 30]. We highlight in this study that these NMD-inducing AS events occur primarily in splicing-associated genes (ie. Hnrnpd, Srsf7, Srsf3, Hnrpdl, U2af1, Tra2a) and accumulate upon both nutrient starvation and ER stress. Consistent with our findings, a recent study reported that dozens of the mRNAs we report here contain detained introns flanking “NMD switch exons” that were spliced post-transcriptionally under stress conditions [21]. Furthermore, we report that expression of the NMD switch exon-containing transcript of the SR protein kinase CLK1/4, which was identified to be an upstream regulator of DI splicing, was also increased specifically upon ER stress [21, 31]. Notably, while ER stress and nutrient starvation induced identical AS events in various splicing genes, we believe that these events are regulated via a CLK1/4-independent mechanism upon nutrient starvation, as we did not observe splicing of CLK1/4 DIs. The stabilization of NMD target isoforms of various splicing and RNA processing genes can likely be attributed to translational blockade observed upon metabolic stress, which is known to inhibit NMD, as well as increased nuclear accumulation of unspliced transcripts upon stress [32, 33]. Nonetheless, these findings validate the existence of “NMD switch exons” AS events in intestinal organoids and are consistent with previous findings suggesting that the coupling of AS-NMD represents a key mechanism by which splicing genes are regulated. In addition to the common signature of AS events leading to the generation of previously identified NMD targets transcripts, we observed a number of events specific to each stress that are instead predicted to use an alternative ATG in order to maintain the reading frame of the transcript, according to previous annotations [25]. These events were frequently located at the 5’ end of the transcript and often occurred in genes involved in specific responses to the presented stress, rather than splicing factors or RNA-processing proteins. The concept of frameshifting splice variants with alternative start codons is a largely overlooked form of AS that likely contributes significantly to transcriptome diversity. Future studies should aid in confirming the existence and functional significance of translated aATG isoforms to validate their role in the cellular response to stress. Conclusions In summary, this study provides a genome-wide analysis on the gene expression patterns induced by metabolic stress in a murine intestinal organoid model. Cellular stresses like ER stress and nutrient starvation regulate the expression of genes involved in immune and defense, metabolism, proliferation and ISC activity. Additionally, we highlight a role for alternative splicing in shaping the stress response in the intestinal epithelium and reveal a potential mechanism for gene expression involving the coupling of AS to alternative translation start sites. Abbreviations AA, amino acid; aATG, alternative start site; AS, alternative splicing; CHOP, cEBP homologous protein; DI, detained intron; ER, endoplasmic reticulum; GCN2, general controlled non-derepressible 2; GO, gene ontology; IGV, integrated genome viewer; ISC, intestinal stem cell; ISR, integrated stress response; KRB, Krebs-Ringer bicarbonate; NMD, nonsense mediated decay; PERK, PKR-like endoplasmic reticulum kinase; PKR, protein kinase R; PTC, premature stop codon; TA, transit-amplifying; UPR, unfolded protein response Additional files Additional file 1: Table S1 cFPKM values for the global analysis of gene expression in murine enteroids upon either ER stress or nutrient starvation. (XLSX 5705 kb) Additional file 2: Table S2 Analysis of expression patterns of various genes upregulated or downregulated during metabolic stress, including those associated with metabolism and innate immunity. (XLS 60 kb) Additional file 3: Figure S1. Induction of a nutrient starvation-associated transcriptional program in intestinal organoids. (A) Venn diagram analysis of 240 genes upregulated more than 2.5 fold upon 4 h of nutrient starvation, categorized by gene function. (B) Gene list manually curated based on gene function from the group of 240 upregulated genes. (C) Venn diagram analysis of 165 genes downregulated more than 2.5 fold upon 4 h of nutrient starvation, categorized by gene function. (D) Total percent of genes with “unknown” function either upregulated or downregulated upon thapsigargin treatment or nutrient starvation. (E) Gene list manually curated based on gene function from the group of 165 downregulated genes. (PDF 381 kb) Additional file 4: Figure S2. Metabolic stress induces a downregulation of a common gene subset. (A) Venn diagram comparison of the genes commonly downregulated more than 2.5 fold upon nutrient starvation and thapsigargin treatment. Hypergeometric tests were used to calculate the P values for significance of overlaps. Scatterplot analysis of the genes transcriptionally downregulated (cutoff >0.4 fold) upon thapsigargin and nutrient starvation. Plots are displayed analyzing of the total number of genes (391) (B) or categorized by gene function (C). (D) Analysis of the gene function of the 18 genes commonly downregulated upon thapsigargin and nutrient starvation (cutoff >0.4 fold). (PDF 262 kb) Additional file 5: Figure S3. Analysis of the alternative splicing landscape in murine enteroids upon nutrient starvation. (A) Classification of AS events induced upon nutrient deprivation based on type of splicing event (skipping(S)/inclusion(I), complex 1 (C1), complex 3 (C3), alternative 3’ (Alt3), intron retention simple (IR-S), intron retention complex (IR-C), complex 2 (C2), alternative 5’ (Alt5)). Examples of both skipping and inclusion events are shown. (B) Scatterplot of the expression of the genes found to undergo AS upon nutrient starvation. Genes above the top red line represent a 2.5-fold increase in expression, while genes below the bottom red line represent genes down-regulated 2.5-fold. (C) Comparison of the proportion of frameshifting vs. non-frameshifting events within each category of AS type. (D) Examples of non-frameshifting AS events in Frrs1 (S) and 2410002O22Rik (S). Gene schematics showing the AS events in green, as well as the Sashimi plots obtained by IGV showing the total read numbers for each junction. (E) GO analysis of the gene group enrichment among the genes that underwent AS during nutrient starvation. (PDF 341 kb) Additional file 6: Table S3 Alternative splicing events in murine enteroids upon either ER stress or nutrient starvation. (XLSX 933 kb) Additional file 7: Figure S4. Metabolic stress promotes inclusion of PTC-containing poison cassettes in splicing factors/RNA processing genes. IGV plots displaying the alternative splicing events (highlighted) induced by nutrient starvation and ER stress. (PDF 180 kb) Additional file 8: Figure S5. Validation of AS events induced upon metabolic stress. Further validation of six selected AS events induced upon thapsigargin treatment (Casp4, Slc35b1, Ufdl1) (A) and nutrient starvation (Frrs, Nnt, Nt5c3) (B). Semi-quantitative RT-PCR analysis and sashimi plots generated via IGV are shown. (PDF 632 kb) Additional file 9: Figure S6. Overview of proposed mechanism of splicing events upon metabolic stress. Various splicing/RNA processing genes contain PTC-containing exons flanked by DIs, which can undergo splicing events resulting in the transcript being targeted to NMD. These NMD targets are stabilized during stress. Genes that are specific during stress may undergo AS coupled to the usage of an out of frame alternative translation start site (aATG) rather than the canonical start site (cATG), resulting in an N-terminal protein variant. (PDF 172 kb) Funding This work was supported in part by grants (to S.E.G. and B. J. B)) from the Canadian Institutes of Health Research, The Nick Natale Innovation Grant of the Canadian Cancer Society (grant #702392) and the Crohn’s and Colitis Canada. Availability of data and materials The data discussed in this publication have been deposited in NCBI’s Gene Expression Omnibus [34] and are accessible through GEO Series accession number GSE84989 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84989). Authors’ contributions Conceptualization, JT and SEG; Methodology & Software, QP and BJB; Validation, JT and QP; Investigation, JT, IT, and CM; Resources, SEG, DJP, and BJB; Writing – Original Draft, Reviewing & Editing, JT and SEG; Visualization, JT and SEG; Supervision, SEG and DJP; Funding Acquisition, SEG and DJP. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate All mice were bred and housed at the Division of Clinical Medicine (DCM) of the University of Toronto and experiments were performed according to guidelines of the DCM and following protocols approved by the University of Toronto Committee on Use and Care of Animals. ==== Refs References 1. Donnelly N Gorman AM Gupta S Samali A The eIF2alpha kinases: their structures and functions Cell Mol Life Sci 2013 70 19 3493 3511 10.1007/s00018-012-1252-6 23354059 2. Cao SS Wang M Harrington JC Chuang BM Eckmann L Kaufman RJ Phosphorylation of eIF2alpha is dispensable for differentiation but required at a posttranscriptional level for paneth cell function and intestinal homeostasis in mice Inflamm Bowel Dis 2014 20 4 712 722 10.1097/MIB.0000000000000010 24577114 3. Datta S Barrera N Pavicic PG Jr Zhao C Freeman M Min B Hamilton T cEBP Homologous protein expression in macrophages regulates the magnitude and duration of IL-6 expression and dextran sodium sulfate colitis J Interferon Cytokine Res 2015 35 10 785 794 10.1089/jir.2014.0204 26134251 4. Kaser A Lee AH Franke A Glickman JN Zeissig S Tilg H Nieuwenhuis EE Higgins DE Schreiber S Glimcher LH XBP1 links ER stress to intestinal inflammation and confers genetic risk for human inflammatory bowel disease Cell 2008 134 5 743 756 10.1016/j.cell.2008.07.021 18775308 5. Sato T Vries RG Snippert HJ van de Wetering M Barker N Stange DE van Es JH Abo A Kujala P Peters PJ Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche Nature 2009 459 7244 262 265 10.1038/nature07935 19329995 6. Heijmans J van Lidth de Jeude JF Koo BK Rosekrans SL Wielenga MC van de Wetering M Ferrante M Lee AS Onderwater JJ Paton JC ER stress causes rapid loss of intestinal epithelial stemness through activation of the unfolded protein response Cell Rep 2013 3 4 1128 1139 10.1016/j.celrep.2013.02.031 23545496 7. Filichkin S Priest HD Megraw M Mockler TC Alternative splicing in plants: directing traffic at the crossroads of adaptation and environmental stress Curr Opin Plant Biol 2015 24 125 135 10.1016/j.pbi.2015.02.008 25835141 8. Lareau LF Brenner SE Regulation of splicing factors by alternative splicing and NMD is conserved between kingdoms yet evolutionarily flexible Mol Biol Evol 2015 32 4 1072 1079 10.1093/molbev/msv002 25576366 9. Lareau LF Inada M Green RE Wengrod JC Brenner SE Unproductive splicing of SR genes associated with highly conserved and ultraconserved DNA elements Nature 2007 446 7138 926 929 10.1038/nature05676 17361132 10. Saltzman AL Pan Q Blencowe BJ Regulation of alternative splicing by the core spliceosomal machinery Genes Dev 2011 25 4 373 384 10.1101/gad.2004811 21325135 11. Guil S Long JC Caceres JF hnRNP A1 relocalization to the stress granules reflects a role in the stress response Mol Cell Biol 2006 26 15 5744 5758 10.1128/MCB.00224-06 16847328 12. van der Houven van Oordt W Diaz-Meco MT Lozano J Krainer AR Moscat J Caceres JF The MKK(3/6)-p38-signaling cascade alters the subcellular distribution of hnRNP A1 and modulates alternative splicing regulation J Cell Biol 2000 149 2 307 316 10.1083/jcb.149.2.307 10769024 13. Barbosa-Morais NL Irimia M Pan Q Xiong HY Gueroussov S Lee LJ Slobodeniuc V Kutter C Watt S Colak R The evolutionary landscape of alternative splicing in vertebrate species Science 2012 338 6114 1587 1593 10.1126/science.1230612 23258890 14. Robinson JT Thorvaldsdottir H Winckler W Guttman M Lander ES Getz G Mesirov JP Integrative genomics viewer Nat Biotechnol 2011 29 1 24 26 10.1038/nbt.1754 21221095 15. Pickard JM Maurice CF Kinnebrew MA Abt MC Schenten D Golovkina TV Bogatyrev SR Ismagilov RF Pamer EG Turnbaugh PJ Rapid fucosylation of intestinal epithelium sustains host-commensal symbiosis in sickness Nature 2014 514 7524 638 641 10.1038/nature13823 25274297 16. Giampietri C Petrungaro S Conti S Facchiano A Filippini A Ziparo E Cancer microenvironment and endoplasmic reticulum stress response Mediators Inflamm 2015 2015 417281 10.1155/2015/417281 26491226 17. Barker N van Es JH Kuipers J Kujala P van den Born M Cozijnsen M Haegebarth A Korving J Begthel H Peters PJ Identification of stem cells in small intestine and colon by marker gene Lgr5 Nature 2007 449 7165 1003 1007 10.1038/nature06196 17934449 18. Munoz J Stange DE Schepers AG van de Wetering M Koo BK Itzkovitz S Volckmann R Kung KS Koster J Radulescu S The Lgr5 intestinal stem cell signature: robust expression of proposed quiescent ' + 4' cell markers EMBO J 2012 31 14 3079 3091 10.1038/emboj.2012.166 22692129 19. Tsalikis J Tattoli I Ling A Sorbara MT Croitoru DO Philpott DJ Girardin SE Intracellular bacterial pathogens trigger the formation of U small nuclear RNA bodies (U Bodies) through metabolic stress induction J Biol Chem 2015 290 34 20904 20918 10.1074/jbc.M115.659466 26134566 20. Scofield DG Hong X Lynch M Position of the final intron in full-length transcripts: determined by NMD? Mol Biol Evol 2007 24 4 896 899 10.1093/molbev/msm010 17244600 21. Boutz PL Bhutkar A Sharp PA Detained introns are a novel, widespread class of post-transcriptionally spliced introns Genes Dev 2015 29 1 63 80 10.1101/gad.247361.114 25561496 22. Dejima K Murata D Mizuguchi S Nomura KH Gengyo-Ando K Mitani S Kamiyama S Nishihara S Nomura K The ortholog of human solute carrier family 35 member B1 (UDP-galactose transporter-related protein 1) is involved in maintenance of ER homeostasis and essential for larval development in Caenorhabditis elegans FASEB J 2009 23 7 2215 2225 10.1096/fj.08-123737 19270184 23. Hitomi J Katayama T Eguchi Y Kudo T Taniguchi M Koyama Y Manabe T Yamagishi S Bando Y Imaizumi K Involvement of caspase-4 in endoplasmic reticulum stress-induced apoptosis and Abeta-induced cell death J Cell Biol 2004 165 3 347 356 10.1083/jcb.200310015 15123740 24. Ye Y Meyer HH Rapoport TA The AAA ATPase Cdc48/p97 and its partners transport proteins from the ER into the cytosol Nature 2001 414 6864 652 656 10.1038/414652a 11740563 25. Wilson LO Spriggs A Taylor JM Fahrer AM A novel splicing outcome reveals more than 2000 new mammalian protein isoforms Bioinformatics 2014 30 2 151 156 10.1093/bioinformatics/btt668 24262213 26. Kagnoff MF The intestinal epithelium is an integral component of a communications network J Clin Invest 2014 124 7 2841 2843 10.1172/JCI75225 24983425 27. Zimmerman NP Vongsa RA Wendt MK Dwinell MB Chemokines and chemokine receptors in mucosal homeostasis at the intestinal epithelial barrier in inflammatory bowel disease Inflamm Bowel Dis 2008 14 7 1000 1011 10.1002/ibd.20480 18452220 28. Lareau LF Brooks AN Soergel DA Meng Q Brenner SE The coupling of alternative splicing and nonsense-mediated mRNA decay Adv Exp Med Biol 2007 623 190 211 10.1007/978-0-387-77374-2_12 18380348 29. Ni JZ Grate L Donohue JP Preston C Nobida N O'Brien G Shiue L Clark TA Blume JE Ares M Jr Ultraconserved elements are associated with homeostatic control of splicing regulators by alternative splicing and nonsense-mediated decay Genes Dev 2007 21 6 708 718 10.1101/gad.1525507 17369403 30. Lewis BP Green RE Brenner SE Evidence for the widespread coupling of alternative splicing and nonsense-mediated mRNA decay in humans Proc Natl Acad Sci U S A 2003 100 1 189 192 10.1073/pnas.0136770100 12502788 31. Ninomiya K Kataoka N Hagiwara M Stress-responsive maturation of Clk1/4 pre-mRNAs promotes phosphorylation of SR splicing factor J Cell Biol 2011 195 1 27 40 10.1083/jcb.201107093 21949414 32. Braunschweig U Barbosa-Morais NL Pan Q Nachman EN Alipanahi B Gonatopoulos-Pournatzis T Frey B Irimia M Blencowe BJ Widespread intron retention in mammals functionally tunes transcriptomes Genome Res 2014 24 11 1774 1786 10.1101/gr.177790.114 25258385 33. Gardner LB Hypoxic inhibition of nonsense-mediated RNA decay regulates gene expression and the integrated stress response Mol Cell Biol 2008 28 11 3729 3741 10.1128/MCB.02284-07 18362164 34. Edgar R Domrachev M Lash AE Gene Expression Omnibus: NCBI gene expression and hybridization array data repository Nucleic Acids Res 2002 30 1 207 10 10.1093/nar/30.1.207 11752295

PMC005xxxxxx/PMC5000507.txt

==== Front Cancer Cell IntCancer Cell IntCancer Cell International1475-2867BioMed Central London 2757049033110.1186/s12935-016-0331-4Primary ResearchMiR-145 functions as a tumor suppressor via regulating angiopoietin-2 in pancreatic cancer cells Wang Hao wanghaosurg@163.com 1Hang Cheng davy0231@sina.com 2Ou Xi-Long ouxilong@126.com 3Nie Jin-Shan doctornjs@126.com 2Ding Yi-Tao yitaoding@hotmail.com 1Xue Shi-Gui sidney2009@163.com 2Gao Hua 756187924@qq.com 2Zhu Jian-Xin +86-18621540037tczjx8040@126.com 21 Department of General Surgery, DrumTower Clinical Medical College of Nanjing Medical University, Nanjing, 210008 Jiangsu Province China 2 Department of Gastroenterology, The First People’s Hospital of Taicang, Suzhou, 215400 Jiangsu Province China 3 Department of Gastroenterology, Zhongda Hospital, Southeast University, Nanjing, 210009 Jiangsu Province China 25 8 2016 25 8 2016 2016 16 6519 3 2015 23 6 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Pancreatic cancer is currently one of the leading causes of cancer deaths without any effective therapies. Mir-145 has been found to be tumor-suppressive in various types of cancers. The aim of this study is to investigate the role of miR-145 in pancreatic cancer cells and explore its underlying mechanism. Methods Quantitative real time PCR was used to determine the expression level of miR-145 and angiopoietin-2 (Ang-2) mNRA, and the expression level of Ang-2 protein was measured by western blotting. The anti-cancer activities of miR-145 were tested both in in vitro by using cell invasion and colony formation assay and in vivo by using xenograft assay. The direct action of miR-145 on Ang-2 was predicted by TargetScan and confirmed by luciferase report assay. The vascularization of xenografts were performed by immunohistochemical analysis. Results The expression level of miR-145 was significantly lower and the expression levels of Ang-2 mRNA and protein was significantly higher in the more aggressive pancreatic cancer cells (MiaPaCa-2 and Panc-1) when compared to that in BxPC3 cells. Overexpression of miR-145 in the BxPC3, MiaPaCa-2 and Panc-1 cells suppressed the cell invasion and colony formation ability, and the expression level of Ang-2 protein in MiaPaCa-2 and Panc-1 cells was also suppressed after pre-miR-145 transfection. Intratumoral delivery of miR-145 inhibited the growth of pancreatic cancer xenografts and angiogenesis in vivo, and also suppressed the expression level of angiopoietin-2 protein. Luciferase report assay showed that Ang-2 is a direct target of miR-145, and down-regulation of angiopoietin-2 by treatment with Ang-2 siRNA in the BxPC3, MiaPaCa-2 and Panc-1 cells suppressed cell invasion and colony formation ability. The reverse transcription PCR results also showed that Tie1 and Tie2 were expressed in BxPC3, MiaPaCa-2 and Panc-1 cells. Conclusion MiR-145 functions as a tumor suppressor in pancreatic cancer cells by targeting Ang-2 for translation repression and thus suppresses pancreatic cancer cell invasion and growth, which suggests that restoring of miR-145 may be a potential therapeutic target for pancreatic cancer. Keywords miR-145Ang-2Pancreatic cancerAngiogenesisissue-copyright-statement© The Author(s) 2016 ==== Body Background Pancreatic cancer was the fourth leading cause of cancer-related deaths and more than 45,000 new cases were estimated in 2013 [1]. Recent studies showed that tumor suppressor loci were mutated or down-regulated in human pancreatic tumors, which accelerated tumor progression and resulted in invasive and metastatic malignancies [2]. However, the role of tumor suppressors in pancreatic tumors are still largely unknown. MicroRNAs (miRNAs) are a family of non-coding RNAs with a short length of 19–25 nucleotides. MiRNAs functioned as oncogene or tumour suppressor by binding to the 3′-untranslated region (UTR) of target genes to regulate their expression [3–5]. MiRNAs play an important role in many physiological and pathological processes, including in almost all aspects of cancer biology, such as cell proliferation, apoptosis, invasion/metastasis, and angiogenesis [6]. Studies have shown that miR-145 has important implications in etiology, treatment and pathogenesis of cancer, including pancreatic cancers. Previous studies demonstrated the tumor suppressive role of miR-145 in caners, in which miR-145 suppressed liver and head and neck cancer cell invasion by targeting on ADAM metallopeptidase domain 17 [7, 8]. MiR-145 was also reported to repress pluripotency in human embryonic stem cells via regulating the expression of octamer-binding transcription factor 4, sex determining region Y-box 2 and Kruppel-like factor 4 [9]. Moreover, in many other types of cancers, miR-145 and its direct target were also reported, for example, miR-145 directly targets AKT3 in thyroid cancer [10], and miR-145 also targets Mucin 1, cell surface associated in metastatic breast cancer [11], p70S6K1 in colon cancer [12], insulin-like growth factor receptor 1 in human bladder cancer cells [13], c-Myc in non-small cell lung cancer [14] and the transcription factor signal transducer and activator of transcription 1 in colon cancer [15]. Recently, Khan et al. [16] reported that miR-145 targeted Mucin 13, cell surface associated to suppress growth and invasion of pancreatic cancer cells. Angiopoietin-2 (Ang-2) is the ligand for an endothelial cell-specific tyrosine kinase receptor, and plays a key role in angiogenesis and tumor progression [17, 18]. Previous study reported that Ang-2 played a significant role in pancreatic carcinoma angiogenesis, and knockdown of Ang-2 induced anti-angiogenesis effect both in vitro and in vivo [19, 20]. Up to date, there is no evidence showing that expression of Ang-2 is linked with miRNAs in pancreatic cancers. In the present study, by using bioinformatics analytic tool (Targetscan), the 3′UTR of Ang-2 gene was found to be a target of miR-145. Here, we documented the tumor suppressive role of miR-145 in pancreatic cell lines. Subsequent analyses further established the relationship between miR-145 and Ang-2 in pancreatic cancer cells. Methods Cell culture The human pancreatic cancer cells (MiaPaCa-2 and Panc-1) were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM, Life Technologies, Inc., Gaithersburg, MD) and BxPC-3 cells were cultured in RPMI-1640 medium (Life Technologies, Inc., Gaithersburg, MD), and both medium were supplemented with 10 % FBS (Life Technologies, Inc.) and 100 units/ml penicillin and 100 units/ml streptomycin. The BxPC-3, MiaPaCa-2 and Panc-1 cells were seeded to be 60–80 % confluent in 6-well plates 24 h before the cells were transfected with 30 pmol of either precursor of miR-145 (pre-miR-145; Ambion; P/N: AM17100, Product ID: PM11480) or scramble miRNA (Pre-miR™ miRNA Precursor Negative Control #1, P/N: AM17110); and angiopoietin-2 siRNA (siAng-2) or scramble (RiboBio, Guangzhou) using the Lipofectamine RNAiMAX reagent (Invitrogen, Carlsbad, CA) according to the manufacturer’s instructions. Forty-eight hours after transfection, cells were processed for further experiments as described below. In vitro invasion assay The invasion assays in the pancreatic cancer cell lines were performed in a modified two-chamber assay. 2 × 105 cells were seeded on the upper chamber of 6-well Transwell plates (Costar; Cambridge, MA) coated with Matrigel (Becton–Dickinson, Heidelberg, Germany) diluted at a 1:2 ratio with medium and incubated for 24 h. The lower chamber was filled with DMEM containing 10 % FBS. After 24 h incubation, cells on the upper side of the membrane were wiped off and the membrane was fixed with 4 % paraformaldehyde and 0.25 % glutaraldehyde. Cells on the lower side of the membrane were stained with 0.5 % methylene blue in 50 % methanol and invaded cells were counted under a microscope. All invasion assays were done in triplicate. Quantitative real-time PCR (qRT-PCR) analysis Total RNA was extracted from cultured cells using TRIzol® reagent (Invitrogen). DNaseI-treated RNA was used for first strand cDNA synthesis using M-MLV reverse transcriptase (Promega) and oligo (dT) 15 according to the manufacture’s protocols and 1 μl cDNA samples were used for conventional PCR amplifications. QRT-PCR analysis was performed in a real-time PCR system (StepOne, Applied Biosystems) and the expression levels of Ang-2 were normalized to GAPDH determined by a SYBR Green-based comparative cycle threshold CT method. Real-time PCR primers were: Ang-2-F: 5′-AGA TTT TGG ACC AGA CCA GTG A-3′, Ang-2-R: 5′-GGA TGA TGT GCT TGT CTT CCA T-3′; GAPDH-F: 5′-TGT GGG CAT CAA TGG ATT TGG-3′, GAPDH-R: 5′-ACA CCA TGT ATT CCG GGT CAA T-3′; miR-145-F: 5′-AAG GGA GTC CAG TTT TCC CAG GAA TCC-3′, miR-145-R: 5′-GTC GTA TCC AGT GCA GGG TCC GAG GTA TTC GCA CTG GAT ACG AC-3′; U6-F: 5′-CTC GCT TCG GCA GCA CA-3′, U6-R: 5′-AAC GCT TCA CGA ATT TGC GT-3′. Western blotting The expression of Ang-2 was measured in pancreatic cancer cell lines (BxPC-3, MiaPaCa-2 and Panc-1) or tumor tissue by western blotting. Protein extraction was performed using the extraction buffer containing 10 mM Tris HCl (pH 7.5), 2 M urea, 2 mM EDTA, 2 mM EGTA, and protease inhibitors. Thirty micrograms of protein were loaded onto SDS–polyacrylamide gels, size fractionated on SDS-PAGE gels, and transferred to a nitrocellulose membrane using the semidry technique. The membranes were blocked with 5 % milk powder in TBST for 1 h. Specific monoclonal anti-Ang-2 (ab8452) and monoclonal anti-β-actin (ab3280) primary antibodies (Abcam Biotechnology, Cambridge, MA, USA) were used, and HRP conjugated immunoglobulin was used as a secondary antibody (Jackson ImmunoResearch Laboratories). West Pico Chemiluminescent (Pierce) was used as the substrate to visualize protein bands, which were quantified using densitometry image analysis software (Image Master VDS; Pharmacia Biotech). Normalization was made against β-actin expression. ELISA Ang-2 concentrations in BxPC3, MiaPaCa-2 and Panc-1 cell culture supernatant were determined after transfection with pre-miR-145 for 48 h. Measurements were made with a commercially available enzyme-linked immunosorbent assay (ELISA) (R&D Systems, Minneapolis, USA) according to the manufacturers’ instructions. Soft agar assay Colony formation and cell growth rate in soft agar were tested by plating 2.5 × 104 of BxPC3, MiaPaCa-2 and Panc-1 cells transfected with scramble or pre-miR-145 in 0.4 ml DMEM, supplemented with 100 units/ml penicillin, 100 g/ml streptomycin, 100 g/ml amphotericin B, 3 % FBS, and 0.3 % low melting temperature agarose (Seaplaque) in 12-well plates (6 wells for each) coated with 0.8 ml 0.6 % low melting temperature agarose. Platelet-derived growth factor-bb (50 ng/ml) was added to half of the wells of each type of transfected cells. Colony formation was monitored for 5 days in 37 °C incubator, and colony number was counted under a microscope. In vivo study Female nude mice (4–6 weeks, 18–20 g) were purchased from the Model Animal Research Center of Nanjing University. 5 × 106 of Panc-1 cells (resuspended in 100 μl saline) were injected subcutaneously into the right flank of each mouse. Tumor volumes were determined every 5 days after injection as described previously [21]. Mice with xenografts volume lager than 500 mm3 were treated with intratumoral injection of saline twice a week (saline group), scramble (saline plus scramble group) or pre-miR-145 (saline plus pre-miR-145 group) for 4 weeks. Each treatment group has eight animals. At the end of the experiment, mice were sacrificed and tumors were dissected for immunohistochemistry and western blot analysis. All the animal study was carried out in strict accordance with Institutional Animal Ethics Care and Use Committee of the Jiangsu Cancer Hospital (approved number 21040608). All surgery was performed under sodium pentobarbital anesthesia, and efforts were made to minimize suffering. Immunohistochemistry Immunohistochemical analysis of vascularization was performed using the analySIS system and the monoclonal antibody against Factor VIII (ab41186, abcam Biotechnology, Cambridge, MA, USA). Briefly, 5 µm thick FFPE sections were cut, placed on slides coated with 3-triethoxysilylpropylamine (Sigma, St. Louis, Missouri, USA), and then fixed overnight at 37 °C. After deparaffinization in xylene and rehydrating through graded alcohols, the slides were incubated in H2O2 to block endogenous peroxidase activity. Then sections were incubated with primary monoclonal antibody against Factor VIII (5 µg/ml) at 4 °C overnight. After overnight incubation, the sections were washed with PBS for 5 min × 3 times, and the sections were then incubated with biotinylated goat anti-rabbit immunoglobulin (dilution 1:300; Vector Laboratories, Burlingame, California, USA). The peroxidase activity was visualized by 3,3′-diaminobenzidine tetrahydrochloride. Hematoxylin was used as a counter stain. The degree of vascularization was measured by the average number of Factor VIII-positive microvessels in three different areas at 200-fold magnification and recorded as microvessel density (MVD). Briefly, the Factor VIII stained sections were initially scanned at low power (100-fold magnification) and the areas having the highest number of microvessels were selected. Subsequently, microvessel counting was performed in three different areas at 200-fold magnification and the mean value was used for further analysis. Any clearly stained endothelial cells or cell clusters were considered as a single countable microvessel, regarding the presence of lumen and large vessels were automatically excluded from the analysis. Constructs and luciferase assay To determine whether Ang-2 is a downstream mediator of miR-145, the entire human Ang-2 3′-untranslated region (UTR) segment was amplified by PCR using mouse genomic DNA as a template. The PCR products were inserted into the p-MIR-report plasmid (Ambion). For luciferase reporter assay, 1 μg of firefly luciferase reporter plasmid, 0.5 μg of β-galactosidase expression vector (Ambion), and equal amount (200 pmol) of pre-miR-145 or scrambled negative control miRNA were transfected into cells in 6-well plates. The β-galactosidase vector was used as a transfection control. Twenty-four hours after transfection, cells were assayed using luciferase assay kits (Promega). Statistics All results were expressed as mean ± SEM from at least three independent experiments. Significance analysis of normal distributed data were performed using two-tail Student’s t test, One-Way ANOVA, or Two-way ANOVA, as appropriate and P values of less than 0.05 were considered statistically significant. Results The expression of miR-145 is reduced in more aggressive pancreatic cancer cell lines and accompanied with increased expression of Ang-2 To elucidate whether the expression level of miR-145 are correlated with the cell invasion ability of pancreatic cancer, three well-studied human pancreatic cancer cell lines, BxPC3, MiaPaCa-2 and Panc-1 were investigated in the present study. In vitro invasion assay results showed that MiaPaCa-2 and Panc-1 were more aggressive than BxPC3, and our qRT-PCR results demonstrated that the expression levels of miR-145 were lower in MiaPaCa-2 and Panc-1 cells when compared to that in BxPC3 cells (Fig. 1a, b). Moreover, qRT-PCR and western blotting analysis showed that the mRNA and protein levels of anigopoietin-2 were also found to be higher in both Panc-1 and MiaPaCa-2 when compared to that in less invasive BxPC3 cells (Fig. 1d). These findings indicates that the expression of miR-145 and Ang-2 might be correlated with the invasive capacity of pancreatic cancer cells.Fig. 1 Down-regulation of miR-145 accompanied with up-regulation of Ang-2 in more aggressive pancreatic cancer cells. a, b The invasion ability of BxPC3, MiaPaca-2 and Panc-1 cells was measured by in vitro invasion assay; c the expression level of miR-145 in BxPC3, MiaPaca-2 and Panc-1 cells was measured by qRT-PCR; d the expression levels of Ang-2 mRNA and protein in BxPC3, MiaPaca-2 and Panc-1 cells were measured by qRT-PCR and western blotting, respectively. Data represents the mean ± SEM, n = 3, significant differences compared to BxPC3 group are indicated as *P < 0.05, **P < 0.01, ***P < 0.001 (one-way ANOVA followed by Bonferroni test) MiR-145 suppressed cell invasion via decreasing the expression of Ang-2 in vitro The role of miR-145 in pancreatic cancer cells was further investigated by using miR-145 gain-of-function study in the human pancreatic cancer cell lines. The results shown that ectopic expressed miR-145 in BxPC3, MiaPaCa-2 and Panc-1 cells (Fig. 2a) significantly decreased thecell invasion and colony formation ability (Fig. 2b, c). Moreover, western blotting results showed that lower protein expression levels of Ang-2 were found in miR-145-overexpressing Panc-1 and MiaPaCa-2 cells, but not in BxPC3 cells when compared with control group transfected with scramble miRNA (Fig. 2d). In addition, down-regulation of Ang-2 were also found in the supernatant of culture media of miR-145-overexpressing Panc-1 and MiaPaCa-2 cells, but not in BxPC3 cells (Fig. 2e). These findings implicated that down-regulation of miR-145 might enhance the in vitro cell invasion and colony formation of pancreatic cancer cells via enhancing the expression of Ang-2.Fig. 2 MiR-145 suppressed cell invasion and colony formation via decreasing the expression of Ang-2 in vitro. a Ectopic expression of miR-145 increased expression levels of miR-145 in BxPC3, MiaPaCa-2 and Panc-1 cells; b, c ectopic expression of miR-145 decreased the cell invasion and colony formation ability of BxPC3, MiaPaCa-2 and Panc-1 cells; d overexpression of miR-145 decreased Ang-2 protein levels in MiaPaCa-2 and Panc-1 cells but not in BxPC3 cells; e the expression of Ang-2 was lower in the supernatant of culture media of miR-145 over-expressing MiaPaCa-2 and Panc-1 cells when compared to control groups. Data represents the mean ± SEM, n = 3, significant differences between groups are indicated as *P < 0.05, **P < 0.01, ***P < 0.001 (unpaired t test) MiR-145 inhibited tumor growth and angiogenesis in vivo To further elucidate the significance of miR-145 in the tumor growth capacity of pancreatic cancer in vivo, miR-145 were delivered intratumorally in xenografts formed by relative more invasive pancreatic cancer cell line Panc-1. The results showed that treatment of miR-145 significantly inhibited the growth of xenografts formed by Panc-1 when compared to that treated with saline or vector control (Fig. 3a, b). Moreover, MiR-145 treatment also decreased microvessels density as well as expression levels of Ang-2 in xenografts when compared to that treated with saline or vector control (Fig. 3c, d). These findings indicate that miR-145 might inhibit cell growth of pancreatic cancer cells via its anti-angiogenesis effect mediated by down-regulation of Ang-2.Fig. 3 MiR-145 inhibited tumor growth and angiogenesis in vivo. a, b MiR-145 significantly inhibited the growth of xenografts formed by Panc-1 when compared with saline or vector control group; c miR-145 treatment decreased microvessels density in xenografts isolated 45 days after subcutaneous injection when compared to saline or vector control group; d the expression levels of Ang-2 in xenografts treated with miR-145 were lower than that in the saline or vector control group. Data represents the mean ± SEM, n = 8, significant differences between groups are indicated as ***P < 0.001 (one-way ANOVA followed by Bonferroni test) MiR-145 directly regulated the expression of Ang-2 in pancreatic cancer cells To further elucidate whether miR-145 could directly regulate the expression of Ang-2 in pancreatic cancer cells, the effect of miR-145 on the luciferase activity of Ang-2 gene 3′-UTR were investigated. The luciferase report assay demonstrated that transiently transfected with pre-miR-145 decreased the luciferase activity of Ang-2 3′-UTR in BxPC3, MiaPaCa-2 and Panc-1 cells (Fig. 4a). Transfection with siAng-2 in BxPC3, MiaPaCa-2 and Panc-1 cells significantly decreased cell invasion and colony formation ability (Fig. 4b, c). Further reverse transcription PCR results demonstrated that Tie1 and Tie2 are presented in BxPC3, MiaPaCa-2 and Panc-1 cells. These findings indicate that miR-145 might regulate the expression of Ang-2 in pancreatic cancer cells directly.Fig. 4 MiR-145 directly regulated the expression of Ang-2 in pancreatic cancer cells. a The effect of miR-145 on the luciferase activity of Ang-2 promoter were measured, the luciferase activity of Ang-2 promoter were all decreased in BxPC3, MiaPaCa-2 and Panc-1 cells; b, c down-regulation of Ang-2 by treatment with siAng-2 decreased the invasion and colony formation ability of BxPC3, MiaPaCa-2 and Panc-1 cells; d the expression of Tie1 and Tie2 in BxPC3, MiaPaCa-2 and Panc-1 was determined by reverse transcription PCR. Data represents the mean ± SEM, n = 3, significant differences between groups are indicated as *P < 0.05, **P < 0.01, ***P < 0.001 (unpaired t test) Discussion Antiangiogenic therapy targeting the vascular endothelial growth factor (VEGF) pathway has been considered as a standard cancer therapy strategy in the past decade [22, 23]. Ang-2-targeting therapies are now regarded as second-generation antiangiogenic drugs that combine with anti-VEGF to improve the hitherto limited clinical efficacy of established antiangiogenic therapy [24–26]. Recently, Ang-2 antibody treatment combines well with low-dose metronomic chemotherapy showed the effective anti-inflammatory and anti-angiogenic response of endothelial cells [27], provided a potential target of antiangiogenic drug development. We here reported that miR-145 suppressed the cell invasion via directly regulating the expression of Ang-2 in pancreatic cancer cells and ectopic expression of miR-145 inhibited tumor growth and angiogenesis in vivo. This study not only provided the information that Ang-2 may involve in pancreatic cancer cell invasion for the first time, but also provided a new strategy to develop antiangiogenic drug by targeting on miR-145. The role of miR-145 in cancer have been extensively studied in various types of cancers. Most of the studies were focused on effect of miR-145 on cancer cell proliferation and metastasis. However, its role in tumor angiogenesis remains poorly defined. One study demonstrated miR-145 inhibited tumor angiogenesis and growth by neuroblastoma RAS and VEGF in breast cancers [28]. The role of miR-145 on tumor angiogenesis is also found in osteosarcoma cells as well as colon cancer cells by targeting on VEGF and p70S6K1, respectively [12, 29]. Our study was consistent with previous studies showing the tumor suppressive roles in pancreatic cancer. In the present study, we demonstrated that miR-145 suppressed cell invasion via directly regulating the expression of Ang-2 in pancreatic cancer. Ang-2 has been found to play an important role in angiogenesis and tumor progression. However, we also found that the mRNA expression level of Ang-2 in Panc-1 cells was significantly higher than that in MiaPaCa-2 cells; though there was no significant difference in Ang-2 protein levels between MiaPaCa-2 and Panc-1 cells. The possible reason could be that the difference of Ang-2 protein levels was very small and the semi-quantitative western blotting assay was not sensitive enough to detect the significant difference; and more sensitive assay be required in the future study. Recent study also showed that Ang-2 mediated beta-1-integrin activation as promoter of endothelial destabilization by enhancing β1-integrin-positive elongated matrix adhesions and actin stress fibers [30]. Because of complexity of Ang-2 signaling pathway, its role still requires further investigation [31]. Based on literature research and bioinformatics analysis (TargetScan), Ang-2 was predicted to be a down-stream mediator of miR-145. The present study showed Ang-2 is regulated by miR-145 in pancreatic cancer cells, which has been confirmed by examining the expressing levels of Ang-2 mRNA and protein as well as the luciferase report assay. As miR-145 have multiple targets, whether Ang-2 being specific for pancreatic cancer cell proliferation and invasion is still questionable. In the future study, we may restore the expression levels of Ang-2 to investigate the specific role of Ang-2 on tumor progression in pancreatic cancer. In addition, Ang-2 exerting its effect by interacting with Tie 1/2 receptor [32], but there is no evidence showing the existence of Tie 1/2 receptor in the pancreatic cancer cells. Therefore, it is necessary for us to determine the distribution and expression of these receptors in the future study, which may help us further understand the mechanistic action of Ang-2 in pancreatic cancer. The study of miRNA-based therapies is still in its infancy. The first miRNA-based therapy specifically for cancer is using miRNA mimics or miRNA inhibitor, such as using synthetic miR-34a mimic loaded in liposomal nanoparticles to suppress liver cancer [33]. Till now, the most advanced miRNA trial involves use of anti-miR-122 for hepatitis C therapy [34], which can reduce miR-122 expression by complementary binding to miR-122 sequence to lock nucleic acid structure. Meanwhile, several studies have focused on small-molecule compound’s modulation on microRNA expression. So far, the small-molecule modulators of miR-21, miR-122 and miR-34a have been identified with potent biologic activities [6, 35, 36]. In conclusion, our in vitro and in vivo studies suggest that miR-145 had a tumor suppressive effect on the pancreatic cancer cells. Therefore, miR-145 mimics or the small molecular modulators of miR-145 may provide the promising strategy to explore Ang-2 targeting antiangiogenic drugs in the future. Authors’ contributions WH carried out further experiments for manuscript revision, and also revised the manuscript significantly. HC carried out the in vitro and in vivo studies and drafted the manuscript. OXL and NJS carried out the luciferase report assay. XSG and GH participated in the design of the study and performed the statistical analysis. ZJX conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript. Acknowledgements We thank Dr. Su from Southeast University (Nanjing, Jiangsu, China) for the kindly help on ELISA and immunohistochemistry techniques. This project was supported by the Science Development Program of Suzhou City, 2013 (Basic research for medical sciences and public health, Project No. SYSD2013033) Competing interests The authors declare that they have no competing interests. Ethical approval All the animal study was carried out in strict accordance with Institutional Animal Ethics Care and Use Committee of the Jiangsu Cancer Hospital (approved number 21040608). Informed consent Informed consent was obtained from all individual participants included in the study. ==== Refs References 1. Siegel R Naishadham D Jemal A Cancer statistics, 2013 CA Cancer J Clin 2013 63 1 11 30 10.3322/caac.21166 23335087 2. Hezel AF Genetics and biology of pancreatic ductal adenocarcinoma Genes Dev 2006 20 10 1218 1249 10.1101/gad.1415606 16702400 3. Bartel DP MicroRNAs: genomics, biogenesis, mechanism, and function Cell 2004 116 2 281 297 10.1016/S0092-8674(04)00045-5 14744438 4. He L Hannon GJ MicroRNAs: small RNAs with a big role in gene regulation Nat Rev Genet 2004 5 7 522 531 10.1038/nrg1379 15211354 5. Zamore PD Haley B Ribo-gnome: the big world of small RNAs Science 2005 309 5740 1519 1524 10.1126/science.1111444 16141061 6. Xiao Z A small-molecule modulator of the tumor-suppressor miR34a inhibits the growth of hepatocellular carcinoma Cancer Res 2014 74 21 6236 6247 10.1158/0008-5472.CAN-14-0855 25217526 7. Yang XW miR-145 suppresses cell invasion in hepatocellular carcinoma cells: miR-145 targets ADAM17 Hepatol Res 2014 44 5 551 559 10.1111/hepr.12152 23621665 8. Yu CC miR145 targets the SOX9/ADAM17 axis to inhibit tumor-initiating cells and IL-6-mediated paracrine effects in head and neck cancer Cancer Res 2013 73 11 3425 3440 10.1158/0008-5472.CAN-12-3840 23548270 9. Xu N MicroRNA-145 regulates OCT4, SOX2, and KLF4 and represses pluripotency in human embryonic stem cells Cell 2009 137 4 647 658 10.1016/j.cell.2009.02.038 19409607 10. Boufraqech M miR-145 suppresses thyroid cancer growth and metastasis and targets AKT3 Endocr Relat Cancer 2014 21 4 517 531 10.1530/ERC-14-0077 24781864 11. Sachdeva M Mo YY MicroRNA-145 suppresses cell invasion and metastasis by directly targeting mucin 1 Cancer Res 2010 70 1 378 387 10.1158/0008-5472.CAN-09-2021 19996288 12. Xu Q MiR-145 directly targets p70S6K1 in cancer cells to inhibit tumor growth and angiogenesis Nucleic Acids Res 2012 40 2 761 774 10.1093/nar/gkr730 21917858 13. Zhu Z MicroRNA-145 directly targets the insulin-like growth factor receptor I in human bladder cancer cells FEBS Lett 2014 588 17 3180 3185 10.1016/j.febslet.2014.06.059 24999188 14. Kavanagh T Process evaluation of appreciative inquiry to translate pain management evidence into pediatric nursing practice Implement Sci 2010 5 90 10.1186/1748-5908-5-90 21092118 15. Gregersen LH MicroRNA-145 targets YES and STAT1 in colon cancer cells PLoS One 2010 5 1 e8836 10.1371/journal.pone.0008836 20098684 16. Khan S MicroRNA-145 targets MUC13 and suppresses growth and invasion of pancreatic cancer Oncotarget 2014 5 17 7599 7609 10.18632/oncotarget.2281 25277192 17. Hu B Cheng SY Angiopoietin-2: development of inhibitors for cancer therapy Curr Oncol Rep 2009 11 2 111 116 10.1007/s11912-009-0017-3 19216842 18. Lewis CE De Palma M Naldini L Tie2-expressing monocytes and tumor angiogenesis: regulation by hypoxia and angiopoietin-2 Cancer Res 2007 67 18 8429 8432 10.1158/0008-5472.CAN-07-1684 17875679 19. Zhou J Anti-angiogenesis by lentivirus-mediated small interfering RNA silencing of angiopoietin-2 gene in pancreatic carcinoma Technol Cancer Res Treat 2011 10 4 361 369 21728393 20. Zhang ZX Knockdown of angiopoietin-2 suppresses metastasis in human pancreatic carcinoma by reduced matrix metalloproteinase-2 Mol Biotechnol 2013 53 3 336 344 10.1007/s12033-012-9532-9 22457202 21. Xiao Z Role of microRNA-95 in the anticancer activity of Brucein D in hepatocellular carcinoma Eur J Pharmacol 2014 728 141 150 10.1016/j.ejphar.2014.02.002 24530415 22. Carmeliet P Jain RK Molecular mechanisms and clinical applications of angiogenesis Nature 2011 473 7347 298 307 10.1038/nature10144 21593862 23. Ferrara N Kerbel RS Angiogenesis as a therapeutic target Nature 2005 438 7070 967 974 10.1038/nature04483 16355214 24. Holopainen T Effects of angiopoietin-2-blocking antibody on endothelial cell-cell junctions and lung metastasis J Natl Cancer Inst 2012 104 6 461 475 10.1093/jnci/djs009 22343031 25. Kienast Y Ang-2-VEGF-A CrossMab, a novel bispecific human IgG1 antibody blocking VEGF-A and Ang-2 functions simultaneously, mediates potent antitumor, antiangiogenic, and antimetastatic efficacy Clin Cancer Res 2013 19 24 6730 6740 10.1158/1078-0432.CCR-13-0081 24097868 26. Koh YJ Double antiangiogenic protein, DAAP, targeting VEGF-A and angiopoietins in tumor angiogenesis, metastasis, and vascular leakage Cancer Cell 2010 18 2 171 184 10.1016/j.ccr.2010.07.001 20708158 27. Srivastava K Postsurgical adjuvant tumor therapy by combining anti-angiopoietin-2 and metronomic chemotherapy limits metastatic growth Cancer Cell 2014 26 6 880 895 10.1016/j.ccell.2014.11.005 25490450 28. Zou C MiR-145 inhibits tumor angiogenesis and growth by N-RAS and VEGF Cell Cycle 2012 11 11 2137 2145 10.4161/cc.20598 22592534 29. Fan L MicroRNA-145 targets vascular endothelial growth factor and inhibits invasion and metastasis of osteosarcoma cells Acta Biochim Biophys Sin (Shanghai) 2012 44 5 407 414 10.1093/abbs/gms019 22472569 30. Hakanpaa L Endothelial destabilization by angiopoietin-2 via integrin beta1 activation Nat Commun 2015 6 5962 10.1038/ncomms6962 25635707 31. Thurston G Daly C The complex role of angiopoietin-2 in the angiopoietin-tie signaling pathway Cold Spring Harb Perspect Med 2012 2 9 a006550 10.1101/cshperspect.a006650 22951441 32. Singh N Angiotensin-(1-7) reverses angiogenic dysfunction in corpus cavernosum by acting on the microvasculature and bone marrow-derived cells in diabetes J Sex Med 2014 11 9 2153 2163 10.1111/jsm.12620 24953642 33. Bouchie A First microRNA mimic enters clinic Nat Biotechnol 2013 31 7 577 10.1038/nbt0713-577 23839128 34. Janssen HL Treatment of HCV infection by targeting microRNA N Engl J Med 2013 368 18 1685 1694 10.1056/NEJMoa1209026 23534542 35. Gumireddy K Small-molecule inhibitors of microrna miR-21 function Angew Chem Int Ed Engl 2008 47 39 7482 7484 10.1002/anie.200801555 18712719 36. Young DD Small molecule modifiers of microRNA miR-122 function for the treatment of hepatitis C virus infection and hepatocellular carcinoma J Am Chem Soc 2010 132 23 7976 7981 10.1021/ja910275u 20527935

PMC005xxxxxx/PMC5000508.txt

==== Front Lipids Health DisLipids Health DisLipids in Health and Disease1476-511XBioMed Central London 31010.1186/s12944-016-0310-8ResearchThe role of active brown adipose tissue (aBAT) in lipid metabolism in healthy Chinese adults Shao Xiaoliang xl_shao@126.com Yang Wei vivi19920712@sina.com Shao Xiaonan scorey@sina.com Qiu Chun seabiscuity@163.com Wang Xiaosong wxs1732@163.com Wang Yuetao +86013852040196yuetao-w@163.com Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, Changzhou, 213003 China 26 8 2016 26 8 2016 2016 15 1 1385 6 2016 16 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background The prevalence of dyslipidemia in China was increased over the last several years. Studies have shown that the activity of aBAT is related to the lipid metabolism. In this study, we analyzed blood lipid level in tumor-free healthy Chinese adults in order to determine the role of aBAT in lipid metabolism. Methods We retrospectively analyzed the factors that affect the blood lipid level in 717 tumor-free healthy adults who received blood lipid measurement and PET/CT scan by multivariate regression analysis. We also determined the role of aBAT on lipid profile by case–control study. Results (1) Our results showed that 411 (57.3 %) subjects had dyslipidemia. The prevalence of the subjects with hypercholesteremia, hypertriglyceridemia, low high-density lipoprotein cholesterol and high low-density lipoprotein cholesterol was 9.5 %, 44.4 %, 30.8 % and 1.4 %, respectively. Multivariate logistic regression analysis with dyslipidemia as the dependent variable showed that body mass index (BMI) and smoking are independent risk factors for dyslipidemia (OR > 1, P < 0.05), while the presence of aBAT is the independent protective factor for dyslipidemia (OR < 1, P < 0.05). (2) The incidence of aBAT was 1.81 %. Subjects with aBAT had significantly lower serum triglyceride and higher serum high-density lipoprotein cholesterol than the subjects without aBAT. The serum total cholesterol and low-density lipoprotein cholesterol were not significantly different between the subjects with aBAT and those without aBAT. Conclusions Dyslipidemia is caused by multiple factors and the presence of aBAT is a protective factor for dyslipidemia in healthy Chinese adults. Keywords DyslipidemiaaBATChinesePositron emission tomography18F-FluorodeoxyglucoseNoNoissue-copyright-statement© The Author(s) 2016 ==== Body Background Cardiovascular disease is the primary cause of death in most countries worldwide [1, 2], including China. Dyslipidemia is a major risk factor for atherosclerosis. Dyslipidemia is also the independent risk factor for myocardial infarction [3] and ischemic stroke [4], and therefore represents a serious threat to human health. Due to the low dietary intake of fat and cholesterol, the type of dyslipidemia (mainly hypertriglyceridemia and low high-density lipoprotein cholesterol) in Chinese adult is different from those in Western countries. More importantly, evidence suggests that the prevalence of dyslipidemia in China is significantly increased over the past several years [2, 5]. Brown adipose tissue (BAT) is the main source of non-trembling heat, and it plays an important role in maintaining the body temperature and energy metabolism balance. The mitochondrial inner membrane of brown fat cells is rich in uncoupling protein 1 (UCP l), which converts chemical energy into thermal energy through the uncoupling of oxidative phosphorylation [6]. It was previously believed that BAT exists only in the fetal and infancy period of rodents and humans. However, recent PET/CT studies [7, 8] showed that BAT with high capacity of 18F-fluorodeoxyglucose (18F-FDG, an analogue of glucose which is used for PET/CT scan) uptake also exists in adult humans, which is recognized as active brown adipose tissue (aBAT). Studies have also shown that the occurrence of aBAT is correlated with age, gender, degree of obesity and outdoor temperature when PET/CT scan was performed. Most of the previous studies used experimental animals or patients with tumors to investigate the effect of aBAT on lipid metabolism [9–11]. These studies showed that aBAT plays an important role in clearing the triglyceride in the blood. However, cancer patients may have lipid abnormalities when treated with anticancer drugs [12], such as Everolimus, Tamoxifen, Goserelin, which increases the complexity to study the effect of aBAT on lipid metabolism. In this study, we performed multivariate regression analysis to identify the factors that contribute to dyslipidemia in the tumor-free Chinese adults to explore the role of aBAT in dyslipidemia. Methods Subjects The subjects receiving 18F-FDG PET/CT scan due to elevated tumor markers of unknown reasons, family history of tumors, and suspected contact with carcinogen from October 2010 to December 2015 were obtained from our Medical Center. For the present analysis, the inclusion criteria were as follows: 1) adult (older than 18 years), 2) no history of cancer, 3) receiving blood lipid measurement at the same day when 18F-FDG PET/CT scans were performed. The exclusion criteria were: 1) subjects who had been diagnosed as dyslipidemia and took oral lipid-lowering drugs, 2) subjects who took oral β-receptor blockers, 3) subjects who took hormone drugs (such as thyroid hormone, estrogen, steroids), 4) subjects who had acute and chronic liver and kidney dysfunction, 5) subjects who had disorders that may lead to malabsorption (such as chronic atrophic gastritis, anorexia, etc.). A total of 717 subjects met the inclusion criteria and we recorded the gender, age, height, weight, body mass index (BMI), smoking status (not including passive smoking), alcohol (drinking at least once a week), fasting plasma glucose concentrations, blood lipid levels (including total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C)), and the outdoor temperature of the day when PET/CT scans were performed. According to Chinese control of overweight and obesity guidelines [13], subjects with BMI between 24 and 27.9 kg/m2 are considered overweight, and subjects with BMI ≥ 28 kg/m2 are considered obese. According to the American Diabetes Association guidelines [14], subjects with the fasting plasma glucose concentration ≥ 7.0 mmol/L or subjects who were previously diagnosed with diabetes and are being treated are considered as diabetic. Blood lipid analysis and criteria for dyslipidemia Blood samples (5 ml, obtained after minimal 8 h of fasting) were collected before 18F-FDG PET/CT scan. The concentrations of serum TC, TG, HDL-C and LDL-C were measured by enzymatic methods using Hitachi 7600–120 automatic biochemical analyzer. Internal quality control was performed at the same time and all operations were in strict accordance with the instructions. Subjects with at least one of the following criteria: serum TC ≥ 6.22 mmol/L (240 mg/dl), serum TG ≥ 2.26 mmol/L (200 mg/dl), serum HDL-C < 1.04 mmol/L (40 mg/dl), and serum LDL-C ≥ 4.14 mmol/L (160 mg/dl) can be considered as dyslipidemia. Factors, such as age, sex, BMI, smoking, drinking, diabetes, and the presence of aBAT that may have an impact on blood lipids were analyzed. PET/CT scan and definition of aBAT PET/CT scan was performed using 18F-FDG (radiochemical purity > 95 %) as the imaging agent (Siemens Biograph mCT (64) type PET/CT instrument). Before PET/CT scan, the subjects underwent minimal 8 h of fasting. Subjects with the fasting plasma glucose below 11.1 mmol/L were intravenously injected with 18F-FDG at the average dose of 4.74 ± 0.93 MBq/kg. Following 45–60 min of rest in a quiet, warm and dark environment and urination, PET/CT scan was performed. Syngo Ture D system was used for image reconstruction, which forms cross-sectional, coronal, sagittal tomographic image and three-dimensional projection image. According to the literature [7], tissues that are located at the neck and supraclavicular region, mediastinum and both armpits, on both sides of the spine, kidney and other peripheral regions are considered as aBAT if CT value is at the adipose tissue density (CT value of −250 ~ −50HU), the diameter is larger than 4 mm, and maximum standardized uptake value of 18F-FDG in PET imagings is at least 2 (SUVmax ≥ 2) (Fig. 1). Active BAT was detected in 13 subjects with an occurrence of 1.8 % (13/717). To reduce the impact of sampling error and to observe the effect of aBAT on blood lipids more intuitively, 1:3 ratio between the number of the subjects in aBAT group and that in control group was used because 1:3 or 1:4 ratio can obtain higher statistics power [15]. The gender, age, BMI, fasting blood glucose and the outdoor temperature were not significantly different between the two groups. In order to reduce subjective bias, lipid profiles were not considered when the control group was selected.Fig. 1 (a and b) Distribution of aBAT in one subject included in this study One subject (34 years old) was a female with a BMI of 20.2 kg/m2 and fasting blood glucose of 5.0 mmol/L. Due to a family history of tumor, the subject requested 18F-FDG PET/CT whole body scan. The outdoor temperature at the day when the scan was performed was 8 °C. Active BAT was distributed on both sides of neck, armpits, supraclavicular region, mediastinum, and the spine. Statistical analysis Statistical analyses were performed using SPSS 23.0 software. Measurement data were expressed as mean ± standard deviation (± s). Kolmogorov-Smirnov test was first performed to determine whether the measurement data follow a normal distribution. The normally distributed data were compared using independent t-test. The non-normally distributed data were compared using Mann–Whitney u rank sum test. The percentage data were compared using χ2 test. When the theoretical frequency in a linked list was less than 1, Fisher exact test was used. Logistic regression analysis with two categorical variables was performed to determine the factors that can affect dyslipidemia. The regression coefficient, odds ratio (OR) and 95 % confidence intervals were calculated. P <0.05 (two-sided) was considered statistically significant. Results Characteristics of the subjects The general characteristics of studied subjects are listed in Table 1.Table 1 Baseline characteristics of studied subjects Parameters Subjects (n = 717) Age (years) 49.8 ± 9.7 Male (%) 66.4 BMI (kg/m2) 24.8 ± 3.2  Normal weight (%) 39.8  Overweight (%) 45.6  Obesity (%) 14.6 Current Smoker (%) 38.4 Current Drinker (%) 34.3 Diabetes (%) 12.7 Outdoor temperature (°C) 21.6 ± 9.1 °C aBAT (%) 1.81 BMI body mass index, aBAT active brown adipose tissue Normal weight: BMI < 24 kg/m2, Overweight: BMI between 24 and 27.9 kg/m2, Obesity: BMI ≥ 28 kg/m2 Outdoor temperature was the outside temperature of the day when PET/CT scan was performed Univariate and multivariate logistic regression analysis of dyslipidemia Among 717 subjects included in this study, 411 subjects (57.3 %) had dyslipidemia. The average serum TC, TG, HDL-C, and LDL-C levels were 5.20 ± 1.08 mmol/L, 3.57 ± 2.55 mmol/L, 1.08 ± 0.25 mmol/L, and 2.52 ± 0.69 mmol/L, respectively. The percentages of the subjects with hypercholesteremia, hypertriglyceridemia, low HDL-C and high LDL-C were 19.5 %, 44.4 %, 30.8 % and 1.4 %, respectively. Lipid level was designated as variable (abnormal y = 1, normal y = 0), and univariate analysis was performed to identify factors (age, sex, BMI, smoking, drinking, diabetes, aBAT) that may affect dyslipidemia (Table 2). The statistically significant factors in univariate analysis were further analyzed by multivariate logistic regression analysis. These results showed that high BMI and smoking were independent risk factors for dyslipidemia (OR > 1, P < 0.05), and the presence of aBAT was an independent protective factor for dyslipidemia (OR < 1, P < 0.05) (Table 3).Table 2 Univariate analysis of factors contributing to dyslipidemia Dyslipidemia (n = 411) Normal (n = 306) P value Age (years) 49.8 ± 9.4 49.9 ± 10.1 0.942 Male (%) 74.2 55.9 <0.001* BMI (kg/m2) 25.5 ± 2.9 23.8 ± 3.2 <0.001*  Normal weight (%) 30.7 52.0 <0.001*  Overweight (%) 49.9 39.9  Obesity (%) 19.4 8.1 Current Smoker (%) 45.7 28.4 <0.001* Current Drinker (%) 38.2 29.1 0.011* Diabetes (%) 15.3 9.2 0.014* aBAT (%) 0.2 3.9 <0.001* BMI body mass index, aBAT active brown adipose tissue Normal weight: BMI < 24 kg/m2, Overweight: BMI between 24 and 27.9 kg/m2, Obesity: BMI ≥ 28 kg/m2 *Significant difference Table 3 Multivariate and Logistic regression analysis of factors contributing to dyslipidemia Variables Regression coefficient OR 95 % CI P value Gender −0.271 0.762 0.497 ~ 1.170 0.215 BMI 0.162 1.175 1.112 ~ 1.234 <0.001* Smoke 0.521 1.684 1.134 ~ 2.501 0.010* Drink −0.158 0.854 0.577 ~ 1.265 0.432 Diabetes 0.236 1.266 0.769 ~ 2.085 0.353 aBAT −2.575 0.076 0.010 ~ 0.610 0.015* OR odds ratio, CI confidence index, aBAT active brown adipose tissue *Significant difference Comparison of the blood lipids between the aBAT group and the control group The 13 subjects with the presence of aBAT were defined as aBAT group. The aBAT-negative subjects with similar age, gender ratio, BMI, fasting glucose level and outdoor temperature were selected as control group (Table 4). The levels of TC, TG, HDL-C and LDL-C were compared between the two groups. The results showed that serum TG level in aBAT group was significantly lower than that in the control group (1.41 ± 0.54 vs. 2.70 ± 2.88 mmol/L, P = 0.024). The level of serum HDL-C in the aBAT group was significantly higher than that in the control group (1.46 ± 0.26 vs. 1.26 ± 0.30 mmol/L, P = 0.032). The levels of serum TC and LDL-C in aBAT group were lower (but not significantly) than those in the control group (TC: 4.79 ± 0.93 vs. 4.96 ± 1.0 mmol/L and LDL-C: 2.28 ± 0.61 vs. 2.36 ± 0.52 mmol/L) (P = 0.587 and P = 0.620, respectively) (Fig. 2A-2D). The ratio TC/HDL-C in the aBAT group was significantly lower than that in the control group (3.36 ± 0.78 vs. 4.19 ± 1.40 mmol/L, P = 0.047).Table 4 Characteristics of subjects in aBAT and control groups aBAT group (n = 13) Control (n = 39) P value Age (years) 41.9 ± 6.5 41.8 ± 6.4 0.950 Male /Female 5/8 15/24 BMI (kg/m2) 22.9 ± 2.6 23.7 ± 2.3 0.286 Fasting plasma glucose (mmol/L) 5.08 ± 0.59 5.45 ± 0.60 0.062 Outdoor temperature (°C) 12.5 ± 7.1 12.7 ± 7.3 0.947 aBAT active brown adipose tissue, BMI body mass index Outdoor temperature was the outside temperature of the day when PET/CT scan was performed Fig. 2 Comparison of the blood lipid level between aBAT and control groups. Comparison of blood TG between aBAT and control groups (a); Comparison of blood HDL-C between aBAT and control groups (b); Comparison of blood TC between aBAT and control groups (c); Comparison of blood LDL-C between aBAT and control groups (d) Discussion Dyslipidemia often includes hypercholesteremia, hypertriglyceridemia, high LDL-C and low HDL-C [16]. The types of dyslipidemia in Asian countries including China are mainly manifested as hypertriglyceridemia and low HDL-C, which is different from those in the United States and Europe [2, 5, 17]. In this study, the occurrence of dyslipidemia was 57.3 %, with the incidence of hypertriglyceridemia and low HDL-C at 44.4 % and 30.8 %, respectively, which is slightly higher than the recent epidemiological findings [5], but basically reflects the abnormal status of blood lipids in this region. PET/CT scan showed that the occurrence of aBAT in 717 subjects was 1.8 %, which was similar to that in other neighboring cities with similar latitude. Zhang et al. [18] showed that aBAT occurrence was 1.58 % in 31,088 subjects receiving PET/CT scan. Univariate analysis showed that dyslipidemia was correlated with multiple factors including gender, BMI (overweight and obesity), smoking, alcohol consumption, and diabetes, suggesting that dyslipidemia is not caused by a single factor, but rather caused by multiple factors. Furthermore, multivariate regression analysis showed that BMI and smoking are independent risk factors for dyslipidemia, which is consistent with the results of previous studies [19, 20]. More importantly, we found that aBAT is a protective factor for dyslipidemia in the healthy Chinese adults (OR = 0.076, P < 0.05). There were relatively few clinical studies examining the effect of aBAT on lipid metabolism. Zhang et al. [21] showed that aBAT was positive in 62 out of 3329 subjects receiving PET/CT scans. Furthermore, HDL-C is higher, while TC/HDL-C is lower in the subjects with positive aBAT compared to the subjects with negative aBAT. However, in that study, BMI was significantly different between aBAT-positive group and the aBAT-negative group. Studies have demonstrated that BAT level and activity were negatively correlated with BMI [7]. Van Marken et al. [22] showed that subjects with BMI of 38.7 kg/m2 did not exhibit BAT imaging even the subjects were exposed to a cold environment. In a retrospective study of 5,907 cases of cancer patients (Caucasian), Ozguven et al. [11] showed that 25 subjects were aBAT-positive with a positive rate of 0.4 %. Based on the 1:3 ratio between the number of subjects in aBAT-positive group and that in the control group, the study showed that blood TC and LDL-C in the aBAT-positive group were significantly lower than that in the control group. However, blood TG and HDL-C were not significant different between the two groups. These findings suggested that different population (e.g., physical exam group, tumor group), or population in different regions had different types of dyslipidemia (Chinese population mainly had high TG and low HDL-C, while Europeans and Americans mainly had high TC and high LDL-C). The effect of aBAT on different lipid components is different. The results of this study were partially consistent with previous studies [21]. However, we also showed that serum TG level in aBAT group was lower than that of the control group, which is different from other studies [11, 21]. Animal studies [10, 23] have indicated that increasing BAT activity can increase TG clearance in plasma. Bartelt et al. [23] found that increasing the BAT activity in vivo in mice by cold stimulation can modulate the clearance of triglyceride-rich lipoproteins (TRLs), resulting in decreased levels of serum TG and increased levels of HDL-C. This process is dependent on the increased vascular endothelial permeability to lipoprotein, local lipoprotein lipase activity and transmembrane receptor CD36. Khedoe et al. [10] found that BAT takes up plasma TG preferentially by means of lipolysis-mediated uptake of fatty acids. These animal studies revealed the mechanisms of low TG and high HDL-C in the aBAT group in this study. These studies also demonstrated the important value of aBAT in lipid metabolism. Statins are the most widely used drugs to treat hyperlipidemia and can reduce the cholesterol concentration by 30 % [24]. However, statin treatment only prevents 25 % to 45 % of all cardiovascular events [25]. One potential factor limiting further reduction in cardiovascular events is the residual elevation in serum TG levels [26]. aBAT was demonstrated as a key player in triglyceride metabolism in our study. Furthermore, aBAT decreases cholesterol levels as well [9, 11]. Our results provide a new therapeutic target to prevent hyperlipidemia and atherosclerosis. Limitations The study was not a large-scale multicenter epidemiological survey and the occurrence of dyslipidemia only reflects the area that we studied. The occurrence of aBAT is similar to other cities at the same latitude [18]. However, only 717 subjects met the inclusion criteria and there were only 13 aBAT-positive subjects. Although we have strict control by setting the standard and blind selection (concealing the status of subjects in the control group and hyperlipidemia during selection), subjective factors leading to the selection bias cannot be completely avoided. Conclusions Dyslipidemia is not caused by a single factor. In contrast, it is the result of multiple factors. This study demonstrated that obesity and smoking are risk factors for dyslipidemia, and a healthy lifestyle is the basis for the prevention and control of dyslipidemia. More importantly, this study demonstrated that aBAT has a protective effect against dyslipidemia, which is mainly manifested by lower levels of serum TG and TC/HDL-C, and higher HDL-C level in the aBAT group. Clinical studies have verified that aBAT can increase plasma TG clearance, indicating the value of aBAT the prevention of dyslipidemia and cardiovascular and cerebrovascular diseases. At the same time, it provides a new target for the development of lipid-lowering drugs. Abbreviations 18F-FDG18F-fluorodeoxyglucose aBATActive brown adipose tissue BATBrown adipose tissue BMIBody mass index HDL-CHigh-density lipoprotein cholesterol LDL-CLow-density lipoprotein cholesterol OROdds ratio TCTotal cholesterol TGTriglycerides UCP lUncoupling protein 1 Acknowledgements None. Authors’ contributions Conceived and designed the experiments: XLS YTW. Analyzed the data: XLS WY. Contributed reagents/materials/analysis tools: XLS. Wrote the paper: XLS. Supervised clinical assessment: XNS. Supervised PET/CT scan: XSW, Supervised blood lipid analysis: CQ. Performed statistical analysis: XLS YTW. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication No applicable. Ethical approval and consent to participate This research was reviewed and approved by the Institutional Review Board of the Third Affiliated Hospital of Soochow University. The research design and methods are in accordance with the requirements of regulations and procedures regarding to human subject protection laws such as GCP and ICH-GCP. ==== Refs References 1. Mozaffarian D Benjamin EJ Go AS Arnett DK Blaha MJ Cushman M Heart disease and stroke statistics-2016 update: a report from the American Heart Association Circulation 2016 133 e38 e360 10.1161/CIR.0000000000000350 26673558 2. He J Gu D Reynolds K Wu X Muntner P Zhao J Serum total and lipoprotein cholesterol levels and awareness, treatment, and control of hypercholesterolemia in China Circulation 2004 110 405 11 10.1161/01.CIR.0000136583.52681.0D 15238453 3. Yusuf S Hawken S Ounpuu S Dans T Avezum A Lanas F Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case–control study Lancet 2004 364 937 52 10.1016/S0140-6736(04)17018-9 15364185 4. Yaghi S Elkind MS Lipids and cerebrovascular disease: research and practice Stroke 2015 46 3322 8 10.1161/STROKEAHA.115.011164 26451029 5. Pan L Yang Z Wu Y Yin R-X Liao Y Wang J The prevalence, awareness, treatment and control of dyslipidemia among adults in China Atherosclerosis 2016 248 2 9 10.1016/j.atherosclerosis.2016.02.006 26978581 6. Cannon B Nedergaard J Brown adipose tissue: function and physiological significance Physiol Rev 2004 84 277 359 10.1152/physrev.00015.2003 14715917 7. Cypess AM Lehman S Williams G Tal I Rodman D Goldfine AB Kuo FC Identification and importance of brown adipose tissue in adult humans N Engl J Med 2009 360 1509 17 10.1056/NEJMoa0810780 19357406 8. Virtanen KA Lidell ME Orava J Heglind M Westergren R Niemi T Functional brown adipose tissue in healthy adults N Engl J Med 2009 360 1518 25 10.1056/NEJMoa0808949 19357407 9. Berbée JFP Boon MR Khedoe PPSJ Bartelt A Schlein C Worthmann A Brown fat activation reduces hypercholesterolaemia and protects from atherosclerosis development Nat Commun 2015 6 6356 10.1038/ncomms7356 25754609 10. Khedoe PPSJ Hoeke G Kooijman S Dijk W Buijs JT Kersten S Brown adipose tissue takes up plasma triglycerides mostly after lipolysis J Lipid Res 2015 56 51 9 10.1194/jlr.M052746 25351615 11. Ozguven S Ones T Yilmaz Y Turoglu T Imeryuz N The role of active brown adipose tissue in human metabolism Eur J Nucl Med Mol Imaging 2016 43 355 61 10.1007/s00259-015-3166-7 26283505 12. Dy GK Adjei AA Understanding, recognizing, and managing toxicities of targeted anticancer therapies CA Cancer J Clin 2013 63 249 79 10.3322/caac.21184 23716430 13. Division of Disease Control, Ministry of Health of the People’s Republic of China The guideline for prevention and control of overweight and obesity in Chinese adults 2006 Beijing People’s Medical Publishing House 14. American Diabetes Association. American diabetes association, standards of medical care in diabetes 2016. Diabetes Care. 2016;39 Suppl 1:S1-S112. 15. Hong EP Park JW Sample size and statistical power calculation in genetic association studies Genomics Inform 2012 10 117 22 10.5808/GI.2012.10.2.117 23105939 16. Joint Committee for Developing Chinese guidelines on Prevention and Treatment of Dyslipidemia in Adult Chinese guidelines on prevention and treatment of dyslipidemia in adults Zhonghua Xin Xue Guan Bing Za Zhi 2007 35 390 419 17711682 17. Bilen O Kamal A Virani SS Lipoprotein abnormalities in South Asians and its association with cardiovascular disease: Current state and future directions World J Cardiol 2016 8 247 57 10.4330/wjc.v8.i3.247 27022456 18. Miao Q Zhang Z Cypess A Ye H Liew CW Zhang Q The prevalence and predictors of active brown adipose tissue in Chinese adults Eur J Endocrinol 2014 170 359 66 10.1530/EJE-13-0712 24288355 19. Erem C Hacihasanoglu A Deger O Kocak M Topbas M Prevalence of dyslipidemia and associated risk factors among Turkish adults: Trabzon lipid study Endocrine 2008 34 36 51 10.1007/s12020-008-9100-z 19003544 20. Bays HE Toth PP Kris-Etherton PM Abate N Aronne LJ Brown WV Obesity, adiposity, and dyslipidemia: a consensus statement from the National Lipid Association J Clin Lipidol 2013 7 304 83 10.1016/j.jacl.2013.04.001 23890517 21. Zhang Q Ye H Miao Q Zhang Z Wang Y Zhu X Differences in the metabolic status of healthy adults with and without active brown adipose tissue Wien Klin Wochenshr 2013 125 687 95 10.1007/s00508-013-0431-2 22. van Marken Lichtenbelt WD Vanhommerig JW Smulders NM Drossaerts JMAFL Kemerink GJ Bouvy ND Cold-activated brown adipose tissue in healthy men N Engl J Med 2009 360 1500 8 10.1056/NEJMoa0808718 19357405 23. Bartelt A Burns OT Reimer R Hohenberg H Ittrich H Peldschus K Brown adipose tissue activity controls triglyceride clearance Nat Med 2011 17 200 5 10.1038/nm.2297 21258337 24. Chan DC Barret PH Watts GF The metabolic and pharmacology bases for treating atherogenic dyslipidaemia Best Pract Res Clin Endocrinol Metab 2014 28 369 85 10.1016/j.beem.2013.10.001 24840265 25. Jukema JW Cannon CP de Craen AJ Westendorp RG Trompet S The controversies of statin therapy: weighing the evidence J Am Coll Cardiol 2012 60 875 81 10.1016/j.jacc.2012.07.007 22902202 26. Baigent C Keech A Kearney PM Blackwell L Buck G Pollicino C Efficacy and safety of cholesterol lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins Lancet 2005 366 1267 78 10.1016/S0140-6736(05)67394-1 16214597

PMC005xxxxxx/PMC5000509.txt

==== Front BMC Sports Sci Med RehabilBMC Sports Sci Med RehabilBMC Sports Science, Medicine and Rehabilitation2052-1847BioMed Central London 5210.1186/s13102-016-0052-yResearch ArticleAn empirical study of race times in recreational endurance runners http://orcid.org/0000-0003-1525-6503Vickers Andrew J. 646-888-8233vickersa@mskcc.org Vertosick Emily A. vertosie@mskcc.org Memorial Sloan Kettering Cancer Center, 485 Lexington Avenue, New York, NY 10017 USA 26 8 2016 26 8 2016 2016 8 1 2610 3 2016 17 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Studies of endurance running have typically involved elite athletes, small sample sizes and measures that require special expertise or equipment. Methods We examined factors associated with race performance and explored methods for race time prediction using information routinely available to a recreational runner. An Internet survey was used to collect data from recreational endurance runners (N = 2303). The cohort was split 2:1 into a training set and validation set to create models to predict race time. Results Sex, age, BMI and race training were associated with mean race velocity for all race distances. The difference in velocity between males and females decreased with increasing distance. Tempo runs were more strongly associated with velocity for shorter distances, while typical weekly training mileage and interval training had similar associations with velocity for all race distances. The commonly used Riegel formula for race time prediction was well-calibrated for races up to a half-marathon, but dramatically underestimated marathon time, giving times at least 10 min too fast for half of runners. We built two models to predict marathon time. The mean squared error for Riegel was 381 compared to 228 (model based on one prior race) and 208 (model based on two prior races). Conclusions Our findings can be used to inform race training and to provide more accurate race time predictions for better pacing. Electronic supplementary material The online version of this article (doi:10.1186/s13102-016-0052-y) contains supplementary material, which is available to authorized users. Keywords PerformanceRunningSports trainingPrediction modelinghttp://dx.doi.org/10.13039/100000054National Cancer InstituteP30-CA008748issue-copyright-statement© The Author(s) 2016 ==== Body Background Many millions of recreational runners compete in long-distance races each year. One key question for such runners concerns factors associated with performance. Modifiable factors, such as training, may suggest changes that a runner might make to improve race times; factors that cannot be modified, such as age or sex, can be used to make fair comparisons between different runners. A second important question for long-distance runners concerns race time prediction, critical for pacing during the early stages of a race. Race time predictors are widely available on the Web, and typically predict time of a future race on the basis of previous race of a different distance [1]. For instance, a user might be asked to enter the time of a recent 10 km race in order to predict the time of a forthcoming marathon. Factors associated with race time and race time prediction are related but quite distinct scientific questions. It may be, for instance, that interval training is associated with race time, but does not help predict time for a longer race on the basis of time for a shorter race, because interval training improves velocity at both distances. There are reasons to believe that both sets of questions – factors related to performance and race time prediction – have been poorly addressed for the recreational runner. The first problem is that much of the literature has focused on elite runners. For instance, several studies on the effects of sex on long-distance running performance have been based on world record times [2, 3]. A study assessing the relationship between training volume and marathon times was based on athletes who qualified for the US Olympic marathon trials [4]. In a an expansive literature review of the value of interval, threshold and “long slow distance training”, Seiler et al. evaluated numerous studies on elite athletes before asking whether the findings could be applied to recreational athletes, concluding that “there are almost no published data addressing this question” [5]. Most race time predictors are based on the Riegel formula, derived from a paper that analyzed world record times for a variety of endurance sports [6]. The recreational runner faces a second problem with the literature, which is that many studies report on measures that require special expertise or equipment. While these are of value for understanding mechanisms of training effects and for predicting race times, they are of less use for recreational runners who lack access to these tools. Typical studies have predicted race time based on the results of cycle ergometry [7], skinfold assessment of body fat [8], or ventilatory threshold determined from an incremental treadmill test [9]. Other studies are weakened by limited sample sizes. Studies on race time prediction have included sample sizes such as 84 [10], 29 [11], or in two cases, as low as 12 [9, 12]. We aimed to collect routinely available data from a large sample of recreational runners in order to understand factors associated with race performance, and to develop a prediction model to aid race pacing for the marathon and other races. Methods Experimental approaches to the problem We explored factors associated with race performance and methods for race time prediction. One approach would have been to download databases of race times from large races. However, this would have allowed us to examine only sex and age, and not other predictors such as training, body mass index or history of injury. Accordingly, we developed a questionnaire that was implemented via the Internet to collect routinely available data from a large sample of recreational runners. Since our goal was to predict race performance, we used race velocity in meters per second (m/s) as the dependent variable. Independent variables were runner characteristics (sex, age and BMI) and training characteristics (typical training mileage and the use of sprint and tempo runs) that are known to be associated with race time. Subjects The study questionnaire included items about age, sex, height and weight, training, injury, type of runner (on a 10 point scale from 1 - “endurance runner” - to 10 - “speed demon”), and type of running shoe (normal running shoe, minimalist, or Vibrams/sandals/barefoot). Questions on training specifically concerned the typical number of miles run per week and the maximum number of miles run in a single week leading up to the longest race, and whether the runner did interval training or tempo runs most weeks during training. Interval training involves short and intense periods at maximal effort followed by equal length or longer recovery periods of less strenuous exercise. Tempo runs are done at a steady pace at or slightly above the anaerobic threshold [13]. Participants were then asked to enter data for two or three recent races: distance and time plus subjective assessments of course difficulty (wind, hills, temperature) and fitness on race day. The questionnaire was implemented via the Web on the news website Slate.com attached to a news story about race time prediction. Readers of an article criticizing the current approach to race time prediction were encouraged to “help Slate build a better predictor” and clicked on a link to the questionnaire. The text of the article made it completely clear that the deidentified data entered by participants would be used for data analysis by the study PI (AV). The project was discussed with the chair of the Memorial Sloan Kettering Cancer Center Institutional Review Board. Given that the project involved analysis of deidentified data and there was no potential for harm, it was deemed that no oversight was required. A copy of the questionnaire is included in the Additional file 1 (see “Questionnaire Text” on page 5- 8). Use of the Internet to distribute a survey naturally raises questions as to two key aspects of survey validity: representativeness and selection bias. As regards representativeness, we planned to compare our sample with data on sex, age and race time from 50,266 participants in the 2013 New York Marathon and also with US national figures from Running USA [14]. We do not think that there is an important risk of selection bias in this study: there is no reason to believe that, say, a runner whose marathon time was faster than average given a certain 10 km time was any more or less likely to complete the questionnaire than a runner whose velocity slowed more dramatically from 10 km to marathon distance. Statistical analyses Procedures for data inclusion, for instance, if a respondent included more than one race at a given distance, are given in the Additional file 1. We aimed to assess the association between race velocity (in m/s) and age, sex, BMI, and training (average mileage, intervals, tempo runs) [15, 16]. Since velocity varies by race distance, we created separate linear regression models for each variable of interest for each race distance. A change in velocity of the same magnitude has different implications based on initial velocity, so we explored modeling the logarithm of velocity, representing relative change in velocity. However, this model was found to explain less variation than using velocity untransformed. We tested for non-linearity in age, BMI and typical weekly mileage, and included cubic splines for these three covariates to account for non-linearity. We used BMI as a correlate of body fat. Body fat likely affects race time directly – additional weight reduces run velocity over long distances – but is itself affected by training, with intense training leading to fat loss [17]. In addition, for individuals who are not overweight – about 80 % of the current sample – women tend to have lower BMI than men. Hence, we took a slightly different approach for examining the influence of BMI on race time. We modeled the association between velocity and age, velocity and BMI, and velocity and typical weekly mileage. The models were adjusted for age, typical weekly mileage, sex, intervals and tempo runs. Since BMI is highly correlated with weekly mileage and race training, the models for the association between velocity and age and between velocity and weekly mileage were calculated with and without BMI. Since the models with and without BMI produced comparable results, we included BMI in our descriptive models. We also sought to develop a prediction model for race time. We first split the data 2:1 into a training (n = 1443) and validation set (n = 721), using a randomization algorithm that ensured a similar distribution of marathon runners and marathon times in each cohort. We then used the training cohort to explore multiple models for race time prediction using linear regression. The survey asked runners to tell us the difficulty of each race for which they reported a race time (very difficult, difficult, average, fast, or very fast). Very difficult or very fast races (5.6 % of the data) were not included in the data used to build the prediction models on the grounds that few runners reported race difficulty at the extremes. For difficult and fast races, we adjusted times to be more representative of a runner’s time for an “average” difficulty race of that distance. To do so, we created a model to predict race velocity in m/s for each race distance separately, adjusted for race difficulty (difficult, average or fast), sex, age, typical weekly mileage, intervals and tempo runs. The differences in velocity between difficult and average races, and between fast and average races, calculated in these models were used to adjust reported race times for difficult and fast races by adding the model coefficient to the runner’s true velocity, and then calculating a difficulty-adjusted time using the difficulty-adjusted velocity. The coefficients used to adjust for fast and difficult races for each race distance are reported in the Additional file 1 along with the prediction models. A common formula for predicting race time for a longer race y based on a shorter race x was published by Riegel and is of the form: time for race y ÷ time for race x = (distance of race y ÷ distance of race x)k [6]. The constant k represents the amount a runner’s velocity decreases as race distance increases (a “fatigue factor”). The models we tested included k as both a predictor, using a constant of k = 1.07, [6] and as the dependent variable, that is, using variables such as mileage to predict the correct value of k. Riegel cited a k of 1.08 for elite runners and 1.05 to 1.06 for male recreational runners aged 40 to 70 [6], while the Runner’s World online calculator uses a constant of 1.06 [1]. We chose a constant of 1.07 as an average, and performed sensitivity analyses using k = 1.06 and k = 1.08. Models were compared using two metrics: mean squared error (MSE) and penalized mean squared error. Since overestimation of a runner’s velocity is more detrimental than underestimation – a runner who starts too slow can speed up during a race whereas a runner to starts too fast will slow dramatically - the penalized mean squared error was calculated by adapting the mean squared error formula, so that an overestimate of velocity had double the weight of an underestimate. All statistical analyses were two-sided, and significance was defined as p < 0.05. All analyses were conducted using Stata 13 (Stata Corp., College Station, TX). The full data set used in the analysis is provided as Additional file 2. Results Participant characteristics The survey opened on April 24, 2014 and was closed for analysis on June 16, 2014. There were 2,497 responses. Runners were excluded if all races reported were the same distance (n = 171), if they were duplicates (n = 8), if they had only one unique race with full data (n = 7), as data from these participants cannot be used in a race time predictor. Participants were also excluded if they reported running a longer race in a shorter time than a race of a shorter distance (n = 6), or if the responses were obviously erroneous or falsified (n = 2). Erroneous data also lead to exclusion of race times from individual races reported by a participant (see Additional file 1 for details). The final cohort included 2,303 runners, with all runners having full data on at least two races of different distances. Only 3 men and 4 women reported a time that met Olympic qualifying standards for at least one race distance, hence our sample consists almost completely of recreational runners. Characteristics of the study cohort are given in Table 1. Time and training data are given in Table 2. A detailed comparison of our cohort to US national data and the New York marathon is given in the Additional file 1. The average age and male:female ratio of our sample is similar. Although running velocities are faster on average, we did have good representation of slower runners, with over 300 runners in our cohort reporting marathon times longer than 4 h.Table 1 Characteristics of study participants (N = 2,303) Age 35 (29, 42) Sex  Female 890 (39 %)  Male 1,413 (61 %) BMI 23.4 (21.7, 25.2) Type of runner  Strictly endurance 706 (31 %)  Generally endurance 1287 (56 %)  Generally speed 297 (13 %)  Strictly speed 13 (<1 %) Typical weekly training mileage 30 (20, 42) Any injury during training?  Nothing that stopped me running 1564 (68 %)  Yes, I had to take a few days off 532 (23 %)  Yes, I had to take more than a week off from running 207 (9 %)  Ran intervals most weeks 1181 (51 %)  Did tempo runs most weeks 1328 (58 %) Type of footwear  Minimalist 465 (20 %)  Normal running shoe 1805 (78 %)  Vibrams, sandals, or barefoot 33 (1.4 %) Given as median (IQR) or frequency (%). Data for all participants were available for all predictors listed in the table Table 2 Age, sex, race training, velocity and time, by race distance 5 km 5 mile 10 km 10 mile Half-marathon Marathon (N = 1,387) (N = 313) (N = 946) (N = 357) (N = 1,579) (N = 1,022) Age 34 (29, 42) 34 (28, 41) 35 (30, 43) 34 (29, 42) 35 (30, 43) 35 (30, 43) Female 532 (38 %) 106 (34 %) 339 (36 %) 137 (38 %) 686 (43 %) 366 (36 %) Typical Mileage 28 (18, 40) 25 (16, 40) 25 (18, 40) 28 (20, 40) 30 (20, 40) 40 (30, 50) Intervals 716 (52 %) 165 (53 %) 462 (49 %) 177 (50 %) 839 (53 %) 579 (57 %) Tempo Runs 773 (56 %) 164 (52 %) 535 (57 %) 208 (58 %) 942 (60 %) 684 (67 %) Race Time Male 00:20:35 (00:18:20, 00:23:28) 00:34:59 (00:29:44, 00:41:04) 00:44:51 (00:39:48, 00:51:30) 01:14:21 (01:03:41, 01:23:08) 01:39:06 (01:28:00, 01:52:10) 03:28:02 (03:03:23, 03:57:36) Race Time Female 00:26:01 (00:22:41, 00:29:09) 00:43:34 (00:37:32, 00:49:19) 00:54:58 (00:48:12, 01:02:08) 01:32:00 (01:20:11, 01:44:00) 01:56:32 (01:44:02, 02:12:16) 03:54:36 (03:31:40, 04:30:00) Race Velocity Male 06:37 (05:54, 07:33) 07:00 (05:57, 08:13) 07:13 (06:24, 08:17) 07:26 (06:22, 08:19) 07:33 (06:43, 08:33) 07:56 (07:00, 09:04) Race Velocity Female 08:22 (07:18, 09:23) 08:43 (07:30, 09:52) 08:51 (07:45, 10:00) 09:12 (08:01, 10:24) 08:53 (07:56, 10:05) 08:57 (08:04, 10:18) Given as median (IQR) or frequency (%). Note that data from an individual runner will appear in two or three different columns. Race velocity is given as minutes per mile Characteristics associated with velocity We first examined multivariable associations between runner characteristics and race time, both overall and separately by sex. We excluded data from the 5 and 10 mile distance due to the relatively limited number of runners at these distances. Sex, age, BMI, typical training mileage, interval training and tempo runs were all statistically significant predictors of race time at p < 0.0005. Results adjusted for BMI were very similar to those without BMI. Interaction analyses were used to determine whether the effect of these characteristics differed between males and females. Significant interactions were found between sex and age, typical mileage, BMI and interval training (p = 0.001, p = 0.004, p = 0.025 and p = 0.024, respectively), although differences were small. Men who ran intervals had a marathon time faster by 4:46 min on average, compared to 3:07 for females. For a one unit in BMI, increase in marathon time was about 40 s more for men. The difference in marathon time for training 50 vs. 30 miles per week was 25:32 for men and 31:41 for women; for age 50 vs. 30 the difference in time was 16:18 for men and 21:37 for women. If these associations are seen to be causal, then we could say that interval training has a greater effect on men, training volume has a greater effect on women, BMI has a greater effect on men and aging has a greater effect on women. When typical training mileage was replaced by maximum training mileage in the models, results were similar, with maximum training mileage being significantly associated with race time for all race distances (p < 0.0001). However, maximum and typical weekly mileage were highly correlated (ρ > 0.9) and we decided to retain only typical weekly mileage for all analyses. Fewer than 2 % of our cohort reported wearing Vibrams, sandals, or running barefoot. We excluded those runners from analyses of footwear. After adjustment for sex, age, BMI and training, runners wearing minimalist shoes had significantly faster race velocity than those reporting conventional footwear (p < 0.0001). Difference in race time was close to 0.5, 1.5, 2 and 3 min for 5 km, 10 km, half-marathon and full marathon respectively. There was no evidence that the association between footwear and velocity differed by race distance (p = 0.4 for interaction term). An additional question is whether the associations between race velocity and runner characteristics or training depend on race distance. For instance, we wanted to know whether the difference between male and female runners is greater for shorter compared to longer races. The results of these analyses are shown in Table 3 and Fig. 1a, b and c. Females do relatively better at longer distances, whereas tempo runs are associated with faster times more strongly for shorter distances. The association between interval training and race velocity was not found to differ by race length. Adjusting for BMI did not importantly influence these interactions. Differences between men and women were larger with adjustment for BMI, on the grounds that men are generally heavier; differences by intervals and tempo runs are smaller, suggesting that these types of training lower BMI. There was no significant interaction between race distance and age (p = 0.13) or between race distance and BMI (p = 0.4). Although there was a significant interaction between race distance and typical weekly mileage (p = 0.025), the magnitude was small, and the effect of typical weekly mileage on velocity did not differ importantly between race distances. These effects can be seen in Fig. 1a, b and c, where the curves for each race distance are approximately parallel.Table 3 Multivariable analysis of race time Covariate Marathon % change Half Marathon % change 10 km % change 5 km % change Interaction p-value Without adjustment for BMI  Male 03:47:46 01:39:48 00:44:42 00:20:46  Female 04:11:56 10.6 % 01:54:42 14.9 % 00:52:58 18.5 % 00:25:06 20.9 % <0.0001  No tempo runs 04:02:55 01:48:17 00:49:59 00:23:15  Tempo runs 03:52:50 −4.2 % 01:43:34 −4.4 % 00:46:22 −7.2 % 00:21:51 −6.0 % 0.002  No intervals 04:01:28 01:47:35 00:48:32 00:22:53  Intervals 03:52:57 −3.5 % 01:43:39 −3.7 % 00:47:18 −2.5 % 00:22:01 −3.8 % 0.5 Adjusting for BMI  Male 03:43:06 01:37:40 00:43:32 00:20:18  Female 04:13:23 13.6 % 01:55:43 18.5 % 00:53:12 22.2 % 00:25:12 24.2 % <0.0001  No tempo runs 03:59:38 01:46:52 00:49:05 00:22:49  Tempo runs 03:51:15 −3.5 % 01:43:01 −3.6 % 00:45:56 −6.4 % 00:21:44 −4.7 % 0.005  No intervals 03:58:21 01:46:18 00:47:32 00:22:29  Intervals 03:51:26 −2.9 % 01:43:04 −3.0 % 00:47:01 −1.1 % 00:21:55 −2.5 % 0.6 The model used here was adjusted for sex, intervals, tempo runs, age, and typical mileage, and separately with and without adjustment for BMI. After creating the model, all covariates except the covariate of interest were set to the mean, velocity was predicted and velocity converted to time in minutes Fig. 1 Race velocity in minutes per mile by age (a, adjusted for BMI and typical training mileage), BMI (b, adjusted for age and typical training mileage) and typical training mileage (c, adjusted for age and BMI). All models were also adjusted for sex and whether the runner trained with intervals or tempo runs. The tables underneath each figure represent the number of runners within the given age, BMI or mileage categories who ran a race of that distance. Yellow line: 5 km velocity; green line: 10 km velocity; red line: half-marathon velocity; blue line: marathon velocity Race time prediction We found evidence that the Riegel formula predicted race time reasonably well for distances up to a half marathon (see Additional file 1: Figure S1 and S2), but was poor for marathon prediction. Using a linear regression model for each race distance with the intercept set to 0, we tested whether the coefficient for the Riegel race time predictions was equal to 1, which would indicate good calibration. The coefficient for Riegel marathon predictions was significantly different than 1 (p < 0.0001) and therefore poorly calibrated, while there was no evidence of a difference for half marathon and 10 k times, implying good calibration (p = 0.3 and p = 0.9, respectively). We explored various models for marathon time prediction using the training set. We settled on two approaches. Model 1 was used for runners who provided data from only one prior non-marathon race. Model 1 predicted marathon velocity in m/s using typical weekly mileage and the predicted marathon velocity calculated using the Riegel formula where k = 1.07 and that runner’s longest non-marathon race. For runners who provided data from two prior non-marathon races, we calculated k between the two races provided. Model 2 used k between the two shorter races and typical weekly mileage to predict k between the longer reported race distance and a marathon. Variables strongly associated with velocity on univariate analysis were not found to improve prediction after controlling for training mileage and prior races times. Hence our models included only prior race time and typical weekly mileage. Both velocity and k were then converted to time in minutes so that mean squared error and penalized mean squared error could be calculated. We also compared the error in these models to the predicted times using the Riegel model where k = 1.07 and the predictor time is from the runner’s longest reported non-marathon race. The formula for both models is given in the Additional file 1 (see “Formulae for Prediction Models” on pages 3 – 4). All mean squared errors were calculated on the same sample of runners in the validation data (N = 156) who reported running a marathon and two other races of differing non-marathon distances. Mean squared errors for model 1, 2 and Riegel were 227.6, 208.3 and 380.7, respectively. MSEs penalizing underestimation of race time were 646.1, 525.0 and 1429.8. Figure 2a, b and c show calibration plots. Calibration of the novel models (Fig. 2a and b) is excellent; in contrast, the Riegel formula (Fig. 2c) shows clear miscalibration with actual running times considerably slower than those predicted. Table 4 shows the distribution of differences between predicted and observed times. Predicted marathon times from Riegel are 10 min or more too fast for about half of all runners; for the new models, this drops to about 25 % of runners. Sensitivity analyses using different coefficients did not change our conclusion. Using the Riegel formula with k = 1.08 did improve estimates slightly, but MSEs were much higher than those from the novel models with marathon velocity overestimated for about 75 % of runners.Fig. 2 Calibration plots comparing observed marathon times to those predicted by Model 1 (a, using information from one prior race), Model 2 (b, using information from two prior races), and the Riegel formula (c, where k = 1.07 and the shorter race is the longest reported non-marathon race) Table 4 Distribution of residuals Centile Model 1 Model 2 Riegel 5th −23:53 −21:38 −36:17 10th −18:25 −16:47 −30:24 25th −9:55 −7:31 −19:47 33rd −7:18 −4:53 −16:50 50th −1:47 0:23 −10:09 67th 3:21 4:46 −5:08 75th 6:28 7:20 −2:48 90th 11:49 15:01 2:53 95th 15:23 21:05 5:12 The table shows differences between predicted and observed race times. A negative time indicates that predicted race time is shorter than observed, that is, predicted velocity is too fast. The table shows that, for instance, nearly 25 % of runners have a predicted race time from the Riegel formula greater than 20 min too fast Discussion We obtained data on over 2000 recreational runners using an Internet based survey. Using this unique data set, we studied predictors of endurance running performance in terms of runner characteristics and training. We also built a novel statistical model to predict marathon time based on race performance at shorter distances. Our study is distinguished by its size and its focus on recreational rather than elite athletes. In addition, we avoided predictors such as VO2max that require laboratory measurement, and only included predictors, such as typical weekly mileage, that would be readily known by any runner. Some of our findings concerning training and race time go somewhat against conventional wisdom. For instance, it is typically believed that training volume is more important for distances such as the marathon than for the 5 and 10 km (km) distance [18–20]. In contrast, we found that the association between training mileage and race velocity is similar across race distances. Similarly, interval training is thought to be of most benefit for shorter distances, with tempo runs seen to be of particular value for long races: typical training plans include more frequent interval training, but less emphasis on tempos, for 10 km races than for marathons [21–23]. We found that tempo runs were more strongly associated with velocity for short distances and that interval training had a similar association with velocity irrespective of distance. The conventional wisdom that women do relatively better as race distance increases [24] was supported by our findings: women were about 20 % slower than men for the 5 km distance; this difference dropped to 10 % for the marathon. On the other hand, the conventional wisdom that race velocity for longer distances is less affected by age than for short distances was not supported, as reductions in velocity with age were similar across distances. Our other major finding was that although standard race prediction tools based on the Riegel formula work well for distances up to a half marathon, they substantially underestimate time for the marathon. Given the importance of pacing for marathon distance, this finding has considerable implications. Our novel marathon prediction model is straightforward and could easily be implemented on any website. A version of our model which uses a more simple adjustment for race difficulty is currently available at Slate.com [25]. The model presented in this paper has been slightly updated using a more specific adjustment for race difficulty. Given the observational nature of the data, it is worth reflecting on whether it is reasonable to make causal attributions between training and velocity. We believe that it is in fact justifiable to draw conclusions such as that a runner who incorporates interval training should expect about a 3 % decrease in race time (Table 3). Not only do our findings have biologic plausibility – there is an extensive literature on the biology of interval training [5] – and an appropriate dose-response gradient (such as that shown in Fig. 1c), but alternative explanations for our findings would appear to be unconvincing. In theory, runners whose training includes, say, tempo runs, might be more likely to have muscular or metabolic factors that increase velocity, but such an effect would seem unlikely, and there is certainly no direct evidence for it. There are two limitations of our study. First, although the sample size is up to 200 times larger than some previous studies, numbers are limited in some subgroups. For instance, only 21 of our marathon runners are aged over 60 and only 3 are aged over 70. This limits our ability to make confident predictions in these age groups. Second, concerns may be raised over the representativeness of our sample. As argued above, we have no reason to believe that use of the Internet to obtain data would lead to selection bias for the questions of interest in this study. For instance, the relationship between interval training and race velocity is highly unlikely to differ by Internet access or propensity to complete Internet surveys. Our cohort was younger and faster than participants in the New York marathon, but reasonable representation of slower and older runners, and the use of modeling techniques that are based on the full data set, limit the influence of this aspect of our study. It might be argued that the use of participant self-report is a weakness of our approach. However, the objective of this study was to use information easily available to the recreational runner. Further, it is unclear that results would have been importantly affected had alternative sources of information been used. Take, for instance, tempo runs during training. The alternative to self-report would be to have had a running coach visit participants, watch a tempo run and verify a running log to determine whether the participant ran a tempo most weeks during training. Not only would such an approach be of highly doubtful feasibility, but there are no obvious reasons to doubt that trainer evaluation and participant self-report would be markedly different. Self-report of tempo runs – indeed, all aspects of runners and training we recorded – were associated with race time in the anticipated direction. This lends support to our study methodology. We note that were a single big city marathon to conduct a similar Internet-based survey as part of entry requirements, a sample size perhaps 10 times larger than ours could be achieved, and there could be little question about representativeness. The questionnaire we used is relatively short, and so questionnaire completion would not incur an undue burden on participants. We encourage others to repeat our study using such an approach. Conclusions We obtained data on a large number of recreational runners in order to develop predictors of endurance race time. Our findings can be used to make fair comparisons between runners of different ages and sexes, inform training regimens and make better prediction of race times, allowing better pacing. Additional files Additional file 1: BMC Supplementary materials. Figure S1. Calibration plot comparing times predicted using Riegel formula where k = 1.07 and the shorter race is the longest reported non-half-marathon race to observed half-marathon times. Figure S2. Calibration plot comparing times predicted using Riegel formula where k = 1.07 and the shorter race is the longest report non-10Km race to observed 10 K times. (DOCX 33 kb) Additional file 2: Master Data Predicting Races Times Final. (XLSX 377 kb) Acknowledgements We would like to thank Christie Aschwanden for her help with the Slate story. Funding This work was supported in part by the NIH/NCI Cancer Center Support Grant to MSKCC under Grant P30-CA008748. There are no conflicts of interest to disclose. Availability of data and materials The dataset supporting the conclusions of this article is included within the article and its additional files. Authors’ contributions The study was conceived by AV. The statistical analyses were conducted by EV under the supervision of AV. The manuscript was written by AV and EV with both authors approving the final analysis. Competing interests There are no conflicts of interest to disclose. Consent for publication Not applicable. Ethics approval and consent to participate The project was discussed with the chair of the Memorial Sloan Kettering Cancer Center Institutional Review Board. Given that we were asking runners to voluntarily complete an anonymous survey, we considered completion of the survey as consent to participate in the study. Given that the project involved analysis of deidentified data and there was no potential for harm, it was deemed that no oversight was required. ==== Refs References 1. Race Time Predictor [http://www.runnersworld.co.uk/general/rws-race-time-predictor/1681.html] Last Accessed 28 June 2016. 2. Coast JR Blevins JS Wilson BA Do gender differences in running performance disappear with distance? Can J Appl Physiol 2004 29 2 139 145 10.1139/h04-010 15064423 3. Cheuvront SN Carter R Deruisseau KC Moffatt RJ Running performance differences between men and women:an update Sports Med 2005 35 12 1017 1024 10.2165/00007256-200535120-00002 16336006 4. Karp JR Training characteristics of qualifiers for the U.S. Olympic Marathon Trials Int J Sports Physiol Perform 2007 2 1 72 92 10.1123/ijspp.2.1.72 19255456 5. Seiler S Tønnessen E Intervals, Thresholds, and Long Slow Distance: the Role of Intensity and Duration in Endurance Training Sportscience 2009 13 32 53 6. Riegel PS Athletic Records and Human Endurance Am Sci 1981 69 285 290 7235349 7. Takeshima N Tanaka K Prediction of endurance running performance for middle-aged and older runners Br J Sports Med 1995 29 1 20 23 10.1136/bjsm.29.1.20 7788211 8. Knechtle B Relationship of anthropometric and training characteristics with race performance in endurance and ultra-endurance athletes Asian J Sports Med 2014 5 2 73 90 25834701 9. Florence S Weir JP Relationship of critical velocity to marathon running performance Eur J Appl Physiol Occup Physiol 1997 75 3 274 278 10.1007/s004210050160 9088849 10. Rust CA Knechtle B Knechtle P Barandun U Lepers R Rosemann T Predictor variables for a half marathon race time in recreational male runners Open Access J Sports Med 2011 2 113 119 24198577 11. Schmid W Knechtle B Knechtle P Barandun U Rust CA Rosemann T Lepers R Predictor variables for marathon race time in recreational female runners Asian J Sports Med 2012 3 2 90 98 10.5812/asjsm.34704 22942994 12. Helgerud J Ingjer F Stromme SB Sex differences in performance-matched marathon runners Eur J Appl Physiol Occup Physiol 1990 61 5-6 433 439 10.1007/BF00236064 2079063 13. What's the Difference Between Fartlek, Tempo, and Interval Runs? [http://www.runnersworld.com/ask-coach-jenny/whats-the-difference-between-fartlek-tempo-and-interval-runs] Last Accessed 20 June 2016. 14. Annual Marathon Report [http://www.runningusa.org/marathon-report-2014] Last Accessed 28 June 2016. 15. Kenney WL Hodgson JL Variables predictive of performance in elite middle-distance runners Br J Sports Med 1985 19 4 207 209 10.1136/bjsm.19.4.207 4092141 16. March DS Vanderburgh PM Titlebaum PJ Hoops ML Age, sex, and finish time as determinants of pacing in the marathon J Strength Cond Res 2011 25 2 386 391 10.1519/JSC.0b013e3181bffd0f 20224445 17. Jakicic JM Marcus BH Gallagher KI Napolitano M Lang W Effect of exercise duration and intensity on weight loss in overweight, sedentary women: a randomized trial Jama 2003 290 10 1323 1330 10.1001/jama.290.10.1323 12966123 18. Marathon Advanced 1 Training Program [http://www.halhigdon.com/training/51141/Marathon-Advanced-1-Training-Program] Last Accessed 28 June 2016. 19. 10 K Advanced Training Program [http://www.halhigdon.com/training/51124/10K-Advanced-Training-Program] Last Accessed 28 June 2016 20. Marathon Training [http://www.jeffgalloway.com/training/marathon-training/] Last Accessed 28 June 2016. 21. Advanced 10 K Program [http://www.coolrunning.com/engine/2/2_4/136.shtml] Last Accessed 28 June 2016. 22. Advanced Marathon Program [http://www.coolrunning.com/engine/2/2_4/129.shtml] Last Accessed 28 June 2016. 23. Your Perfect Tempo [http://www.runnersworld.com/running-tips/your-perfect-tempo] Last Accessed 28 June 2016. 24. Bam J Noakes TD Juritz J Dennis SC Could women outrun men in ultramarathon races? Med Sci Sports Exerc 1997 29 2 244 247 10.1097/00005768-199702000-00013 9044230 25. Introducting Slate's Marathon Time Predictor [http://www.slate.com/articles/sports/sports_nut/2014/10/running_calculator_introducing_slate_s_marathon_time_predictor_a_better.html] Last Accessed 28 June 2016.

PMC005xxxxxx/PMC5000510.txt

==== Front Biomed Eng OnlineBiomed Eng OnlineBioMedical Engineering OnLine1475-925XBioMed Central London 22410.1186/s12938-016-0224-8ReviewHeart blood flow simulation: a perspective review Doost Siamak N. Sndoost@swin.edu.au 1Ghista Dhanjoo d.ghista@gmail.com 2Su Boyang su.boyang@nhcs.com.sg 3Zhong Liang Zhong.liang@nhcs.com.sg 34Morsi Yosry S. ymorsi@swin.edu.au 11 Biomechanics and Tissue Engineering Lab, Faculty of Science, Engineering and Technology, Swinburne University of Technology, Melbourne, Australia 2 University 2020 Foundation, Northborough, MA USA 3 National Heart Research Institute Singapore, National Heart Centre Singapore, 5 Hospital Drive, 169609 Singapore, Singapore 4 Duke-NUS Medical School, Singapore, Singapore 25 8 2016 25 8 2016 2016 15 1 10122 4 2016 15 8 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Cardiovascular disease (CVD), the leading cause of death today, incorporates a wide range of cardiovascular system malfunctions that affect heart functionality. It is believed that the hemodynamic loads exerted on the cardiovascular system, the left ventricle (LV) in particular, are the leading cause of CVD initiation and propagation. Moreover, it is believed that the diagnosis and prognosis of CVD at an early stage could reduce its high mortality and morbidity rate. Therefore, a set of robust clinical cardiovascular assessment tools has been introduced to compute the cardiovascular hemodynamics in order to provide useful insights to physicians to recognize indicators leading to CVD and also to aid the diagnosis of CVD. Recently, a combination of computational fluid dynamics (CFD) and different medical imaging tools, image-based CFD (IB-CFD), has been widely employed for cardiovascular functional assessment by providing reliable hemodynamic parameters. Even though the capability of CFD to provide reliable flow dynamics in general fluid mechanics problems has been widely demonstrated for many years, up to now, the clinical implications of the IB-CFD patient-specific LVs have not been applicable due to its limitations and complications. In this paper, we review investigations conducted to numerically simulate patient-specific human LV over the past 15 years using IB-CFD methods. Firstly, we divide different studies according to the different LV types (physiological and different pathological conditions) that have been chosen to reconstruct the geometry, and then discuss their contributions, methodologies, limitations, and findings. In this regard, we have studied CFD simulations of intraventricular flows and related cardiology insights, for (i) Physiological patient-specific LV models, (ii) Pathological heart patient-specific models, including myocardial infarction, dilated cardiomyopathy, hypertrophic cardiomyopathy and hypoplastic left heart syndrome. Finally, we discuss the current stage of the IB-CFD LV simulations in order to mimic realistic hemodynamics of patient-specific LVs. We can conclude that heart flow simulation is on the right track for developing into a useful clinical tool for heart function assessment, by (i) incorporating most of heart structures’ (such as heart valves) operations, and (ii) providing useful diagnostic indices based hemodynamic parameters, for routine adoption in clinical usage. Keywords HemodynamicsLeft ventricle (LV)Computational fluid dynamics (CFD)Fluid structure interaction (FSI)Cardiovascular diseases (CVDs)http://dx.doi.org/10.13039/501100001781Swinburne University of TechnologyNational Heart Research Institute Singaporeissue-copyright-statement© The Author(s) 2016 ==== Body Background Cardiovascular disease (CVD) refers to abnormalities and/or the malfunction of cardiovascular components that affect the functionality of the heart. It is well known that CVD is the leading cause of mortality and morbidity in the world, particularly in developed countries. The diagnosis and prognosis of CVD in the early stage can help to reduce its high mortality and morbidity rate. Therefore, it is essential to develop various tools to enhance our knowledge of cardiovascular physiological phenomena and processes that contribute to the initiation and progression of various CVDs. The flow-induced (i.e. hemodynamic) loads are vital keys to cardiovascular structural development during the embryonic period and the formation of any change in the shape or functionality of the cardiovascular system after birth [1]. Therefore, analyzing the hemodynamic flow patterns and parameters of patient-specific heart models using various clinical tools can provide physicians with useful insights into the indicators leading to CVD, and can also assist in the diagnosis of CVD. One clinical cardiovascular assessment tool is the catheter, an invasive medical instrument that measures blood flow or pressure. The main challenge when using traditional invasive medical tools is the occurrence of complications during and/or after operation [2]. Another robust set of clinical cardiovascular assessment tools is non-invasive medical imaging techniques, such as magnetic resonance imaging (MRI), echocardiography (ECG), and computed tomography (CT), which are able to provide valuable information on the cardiac system without the associated risks posed by traditional clinical tools. Despite the frequent use of medical imaging methods, there are some limitations and difficulties associated with heart pathology prognosis and detection in clinical practice. For instance, computed tomography (CT) is unable to provide some essential hemodynamics of blood flow patterns that can aid the early diagnosis of CVD [3]. Magnetic resonance image (MRI) images have fair spatiotemporal resolution to capture the small scale and temporal hemodynamic features of the heart. 4D MRI is a cutting edge tool to visualize the three-dimensional (3D) flow evolution over cardiac cycles by combining 3D spatial encoding and the 3D velocity-encode phase contrast method [4]. As stated in [4], the scan time is relatively long, of the order of 20 min or more, with spatial and temporal resolutions of 2–3 mm and 40–50 ms, respectively. One major drawback of 4D MRI, however, is that this technique fails to capture accurately the hemodynamic parameters, such as WSS, due to the low resolution [5], while they can be measured by computational fluid dynamics (CFD) simulation with sufficient accuracy. CFD has been widely used in the assessment of cardiac functionality, in combination with medical imaging techniques and even invasive medical tools. CFD is a branch of fluid mechanics that utilizes different computational techniques to analyze fluid flow behavior and patterns. CFD is capable of providing valuable hemodynamics which is useful in the clinical assessment of heart performance and the early diagnosis of heart dysfunction [3, 6, 7]. In the cardiovascular system, the left ventricle (LV) constitutes one of the most challenging domains in the application of CFD, due to its significance in the initiation and propagation of CVD, leading to heart failure (HF). It is believed that early cardiac dysfunction can be detected by analyzing the hemodynamics within the LV chamber, due to the fact that abnormal LV flow patterns are associated with reduced myocardial contractility which causes the heart to be incapable of ejecting adequate cardiac output leading to heart failure (HF) [8]. Accordingly, enormous investigations have been carried out to computationally and/or experimentally analyze the hemodynamics of the human heart and specifically of the LV. The history of attempts to analyze LV hemodynamics dates back to 1970, when Bellhouse [9] studied blood flow dynamics in the LV. However, more recently, several investigations have been performed by the numerical simulation of intraventricular blood flow using idealized models [10, 11] or by using normal-subject LV (physiological) [2, 12] and patient-subject LV (pathological) [7, 13]. Some of the problematic challenges faced by the numerical simulation of the LV are the complexity of heart morphology, the large deformation of the heart wall during the cardiac cycle, the effect of heart valves opening and closing on the heart geometry, the electrical-fluid-structure interaction (EFSI) phenomenon involved in developing intraventricular blood flow, and finally, the transitional blood flow between the laminar and the turbulent flows during the cardiac cycle [14]. Consequently, despite the extensive investigations that have been done in this area over the last couple of decades, the numerical simulation of intraventricular blood flow in patient-specific hearts is still clinically unavailable, and needs further investigation to provide reliable and realistic results [15]. Patient-specific LV CFD simulation aims to mimic realistic cardiovascular hemodynamics to evaluate the intraventricular hemodynamics for different purposes, such as for diagnostic analysis [2], analysis of preoperative and postoperative LVs to evaluate surgical outcomes [13], preoperative LV analysis to examine various surgical alternatives to choose the best option [16], and finally, the analysis of pathological LVs to assess their physiological conditions [17]. Table 1 summarizes the works published over the past 15 years on the simulation of human patient-specific LVs. The purpose of this review paper is to comprehensively discuss and explain recent CFD investigations of human patient-specific LVs. In this review paper, we discuss the different CFD methodologies employed to simulate intraventricular flows as well as elucidate the numerical investigations and findings of the published works. Moreover, the clinical implications of this research are also discussed in our paper. Finally, we discuss CFD shortcomings and the future direction of CFD simulations of patient-specific LVs.Table 1 Summary of the published papers that simulate patient-specific LVs First author Year Geometry Imaging technique CFD methodb Phasec Validation resultsd CFD Solver Conditiona Type Number of case studies Normal Patient Doost  [18] 2016 Normal 3D 1 – MRI GP FCC N/A ANSYS-fluent Su [19] 2016 Normal and PAH 3D 1 1 MRI GP FCC N/A ANSYS-fluent Nguyen[20] 2015 Normal person and patients with diastolic dysfunction 3D 4 2 MRI GP FCC Blood flow pattern is qualitatively validated using echocardiography PIV In-house CFD solver Muehlhausen [21] 2015 Normal 3D 1 – MRI GP FCC N/A Coupled fluent, MpCCI, and Abaqus Su [22] 2014 HCM 3D 1 1 MRI GP FCC N/A ANSYS-fluent 14 Su [23] 2014 Normal 2D 1 – MRI GP FCC N/A ANSYS-fluent 14 Khalafvand [13] 2014 Before and after SVR and normal 3D 1 2 MRI GP FCC N/A ANSYS-fluent 12 Moosavi [2] 2014 Normal 3D 1 – MRI GP FCC N/A ADINA v8.6 Seo [12] 2014 Normal 3D 1 – CT scan GP FCC N/A N/A Chnafa [14] 2014 Not specified 3D 1 – MRI GP,LES FCC N/A YALES2BIO Corsini [16] 2014 SV 3D 1 – MRI Multi-scale FCC The flow obtained from the multi-scale analysis is validated using the clinical MR and echo-Doppler data Simnon Vecchi [24] 2014 Normal and HLHS 3D 1 1 ECG GP FP N/A CHeart Seo [25] 2013 Normal 3D 1 – CT scan GP FCC N/A N/A Mangual [7] 2013 DCM and Normal 3D 20 8 ECG IBM FCC N/A N/A Vecchi [26] 2013 HLHS 3D 1 2 MRI GP FP Myocardial shape parameters is validated using dual phase MRI N/A Nguyen [27] 2013 Normal 3D 1 – MRI GP FCC N/A N/A Le [28] 2013 Normal 3D 1 – MRI IBM FP N/A FSI-CURVIB flow solver Dahl [29] 2012 Normal 2D 1 – Ultrasound GP FP N/A ANSYS-fluent 6.3.26 Lassila [30] 2012 Mild mitral regurgitation, MI and stroke 3D – 1 MRI GP, Multi-scale FCC The flow rate and pressure obtained from the multi-scale analysis are validated using a closed loop hydraulic system Open-source LifeV code Khalafvand [17] 2012 MI 2D 3 3 MRI GP FCC N/A ANSYS-CFX12 Khalafvand [31] 2012 Before and after SVR 3D – 1 MRI GP FCC N/A ANSYS-CFX12 Le [32] 2012 Normal 3D – 1 MRI IBM FCC N/A FSI-CURVIB flow solver Mihalef [33] 2011 Normal 3D 1 – CT scan GP FCC N/A N/A Krittian [34] 2010 Normal 3D 1 – MRI GP, coupled-FSI FCC The flow pattern predicted by CFD simulation is qualitatively validated using a circulatory system Coupled fluent, MpCCI, and Abaqus Doenst [35] 2009 Before and after SVR 3D – 1 MRI GP FCC The flow pattern predicted by CFD simulation is qualitatively validated using a circulatory system Coupled Fluent, MpCCI, and Abaqus Schenkel [36] 2009 Normal 3D 1 – MRI GP FCC The flow pattern predicted by CFD simulation is qualitatively validated using MRI velocity mapping Star-CD Long [8] 2007 Normal 3D 6 – MRI GP FCC The flow pattern predicted by CFD simulation is qualitatively validated using MRI velocity mapping ANSYS-CFX4 Liang [37] 2007 LHF and normal 3D 1 1 N/A GP, Multi-scale FCC The flow obtained from multi-scale analysis is validated using echo-Doppler data In-house C ++ code Long [38] 2003 Normal 3D 1 – MRI GP FCC N/A ANSYS-CFX4 Saber [39] 2001 Normal 3D 1 – MRI GP FCC N/A STAR–CD Saber [40] 2001 Normal 3D 1 – MRI GP FCC N/A STAR–CD aCondition (DCM dilated cardiomyopathy, HCM hypertrophic cardiomyopathy, HLHS hypoplastic left heart syndrome, LHD left heart failure, MI myocardial infarction, PAH pulmonary arterial hypertension, SV single ventricle, SVR surgical ventricular reconstruction) bSolution method (GP geometry-prescribed, FSI fluid-structure interaction, IBM immersed boundary method, LES large eddy simulation) cPhase (FCC full cardiac cycle, filling phase) dValidation (PIV particle image velocimetry) Computational fluid dynamics (CFD) Approaches Generally, each CFD simulation has three main components: a pre-processor, solver, and post-processor. In the IB-CFD method, generally, each step consists of different substeps, as illustrated in Fig. 1. The details of the substeps depend on the numerical approach chosen to perform the simulation of the patient-specific LV. Typically, there are two main approaches for the numerical simulation of LV using CFD techniques: (i) the geometry-prescribed method that solves only the fluid domain by prescribing the movement of the LV myocardial wall as the fluid domain boundary condition; (ii) the fluid-structure interaction (FSI) method that numerically solves the governing equations of both the fluid and structure domains by coupling the CFD and structural solver. The FSI method is further subdivided into two different approaches: fictitious FSI [32] and realistic FSI [34]. Fig. 1 Main stages required to perform IB-CFD simulation in general The geometry-prescribed method is based on the assumption that the flow-induced load on the LV wall is negligible in comparison to the structural-induced load on the fluid flow [36]. In this approach, the LV myocardium motion is prescribed to the numerical solver by using two different approaches: directly by extracting wall motion data from medical images [13], and indirectly by setting up some mathematical equations to formulate wall motion [41]. The latter method can be used in idealized models, but is not applicable to patient-specific models. To date, the geometry-prescribed method using medical images to define wall motion is the most popular approach to simulate LV hemodynamics due to its convenience and the available computing resources. The fictitious FSI method or the immersed boundary method (IBM) is primarily appropriate to simulate flow in heart valves, although in some of the published literature [6, 32] this method has also been successfully employed in LV CFD simulation. In this method, because the wall is not fitted to the coordinate curve, the boundary layer information is not accurate enough for use in clinical decision making. The realistic FSI method, on the other hand, couples both the CFD and structural solver (mostly the finite element solver), to simulate both the fluid and structure domains simultaneously. This method is hence more complicated and also more numerically expensive (both time-consuming and requiring more sophisticated computing recourse) for the CFD modeling of the intra-LV blood flow. The Lagrangian and Eulerian are the two methodologies that describe material kinematics. In the Lagrangian approach, the observer tracks the individual particles of the material as they move through space and time. In the Eulerian approach, the observer stands at a fixed point, and the kinematic quantities of the physical properties of the material at the fixed point are described as functions of time, as the time is passing regardless of the specific particles of the material; in the Eulerian method, the continuum mechanics framework is used to formulate the material kinematics. However, the Lagrangian and Eulerian methods are mainly used to numerically simulate the kinematics of fluid and solid materials, respectively. To numerically simulate FSI-applied problems (such as to numerically simulate intraventricular flow), neither the Eulerian nor the Lagrangian formulation is applicable to simulate the structure and fluid domains [42, 43]. To formulate the governing equations of the fluid and structure domains, an arbitrary description of the boundary is required to follow the motion of the boundary, with the mesh motion neither spatially fixed similar to the Eulerian method nor attached to the material to follow the boundary particles similar to the Lagrangian method [44]. The new technique to describe material kinematics is called the arbitrary Lagrangian–Eulerian (ALE) description, which is considered to be one of the most effective ways to analyze FSI problems involving both small and large structural deformations. In this approach, the flow domain is time-dependent, and the interface boundaries can be changed as the structure deforms [42]. In both the geometry-prescribed and the FSI approaches, the ALE approach is used for the formulation of the governing equations. The integral forms of continuity and momentum equations (Navier–Stokes equation) of the fluid domain are written as [23]: 1 ∂∂t∫VρdV+∫Sρv→-vb→·n→dS=0 2 ∂∂t∫Vρv→dV+∫Sρv→v→-vb→+pI-τ→·n→dS=0 where ρ is the fluid density; v→ is the velocity vector of fluid; vb→ is the velocity vector of the moving boundary; n→ is the outwardly directed vector normal to dS; S is the boundary of the control volume, V; p is the pressure; I is the unit tensor; and τ→ is the viscous stress tensor. The blood viscosity has been mostly assumed to be constant (ρ = 1050 kg/m3) in all published papers, owing to blood incompressibility. Moreover, blood viscosity has been assumed to be constant in most published papers by using the dynamic viscosity of μ = 0.0035 Pa.s, but in some papers blood has been assumed to be a non-Newtonian fluid by utilizing the Carreau–Yasuda model [36] and the Carreau [34] model. In many publications [45–51], it has been shown that blood significantly possesses the non-Newtonian properties, such as shear thinning, viscoelasticity, and thixotropic. In our most recent publications [18, 52], the effect of the non-Newtown assumption on the flow dynamics was analyzed by using different blood rheological models under the physiological condition. In this publication, it was demonstrated that the non-Newtonian assumption has quite a significant importance to the intraventricular hemodynamics, such as the wall shear stress (WSS). Therefore, the accuracy of the numerical analysis of the blood flow dynamics can be affected by neglecting the non-Newtonian property of the blood. Geometry reconstruction methods The physiological/pathological patient-specific LV geometry must be reconstructed in order to analyze the complex intraventricular blood flow. In so doing, medical images of the patient’s heart need to be captured during a cardiac cycle and used to reconstruct the geometry by employing different image segmentation and image processing techniques. For carrying out intra-LV blood flow modeling, we are employing non-invasive medical images to reconstruct the anatomical heart models in order to use them in CFD simulation, which is called imaged-based CFD (IB-CFD) simulation. In this method, however, the LV geometry quality strongly depends on the medical imaging techniques, the spatiotemporal resolution of the obtained medical images, and the segmentation and image processing technique employed to reconstruct the geometry. Moreover, due to the insufficient time resolution of the extracted medical images during one cardiac cycle to employ in the numerical simulation, extra intermediate images between the main images must be produced by using an appropriate interpolation method. In several papers, such as [36], this interpolation approach for obtaining more information has been thoroughly explained. The number of intermediate images must be such that the courant number be close to one for the convergence/stability criteria of numerical simulation [31]. However, generally patient-specific geometry reconstruction is cumbersome and time consuming. The IB-CFD simulation needs various operator-dependent steps that include image acquisition, image segmentation, geometry reconstruction, mesh generation, and finally numerical simulation [27]. The operator-dependent steps of IB-CFD could probably be sources of error that can impact on the result accuracy [27]. Boundary conditions Different types of boundary conditions In order to conduct numerical simulation, a proper set of boundary conditions should be imposed on all boundaries. The numerical results significantly depend on the type and the accuracy of the boundary conditions. Therefore, any incorrect boundary conditions will lead to the reproduction of incorrect results which can affect a clinical decision based on the numerical results. In the numerical simulation of the LV, the geometry is mainly divided into two parts with different types of boundary conditions: Myocardial wall The moving wall and no-slip boundary conditions are required to be imposed on the myocardial wall with different strategies, depending on the simulation approach. In coupled FSI [21], the myocardial wall motion should be set to be automatically derived from coupling the structural and CFD solvers. In the geometry-prescribed [13] and immersed-boundary [53] methods, the myocardial wall motion should be prescribed to the CFD solver. In this case, the spatiotemporal node positions should be derived after geometry reconstruction in order to import into the CFD solver. Mitral and aortic annulus The combination of inflow or outflow with the wall boundary conditions needs to be imposed on the mitral and aortic annulus, regardless of the presence or absence of the valve leaflets in the simulation. The wall boundary conditions (i.e., completely closed) should be defined in the mitral and aortic orifices during systole and diastole, respectively. Additionally, the inflow and outflow boundary conditions should be selected in the mitral and aortic orifices during diastole and systole, respectively. For the inflow or outflow period of the cycle, time-variant pressure [34], velocity [39], or flux [53] should be imposed on the mitral/aortic orifices. However, different types of mitral/aortic orifices have been implemented in the literature, such as an orifice with a simple boundary condition [40], a hybrid orifice with a combination of a pressure and velocity profile [38], and an orifice with a different opening area over the cycle [34, 36]. The hybrid boundary condition could be an effective approach to overcome the mass conservation equation unbalance during the numerical solution involving using velocity as the inlet and outlet boundary conditions. In the case of using velocity/flux as inflow or outflow [14], because blood is an incompressible fluid, the time-variant velocity/flux profile can be obtained from the temporal variation of the LV volume (or the surface area in 2D simulation). In [25], an expression has been derived for the blood flux through the aortic and mitral orifices by dividing the cardiac cycle into five distinct phases: E-wave, diastasis, A-wave, iso-volumetric contraction, and systole. The pressure waveform boundary condition could be also be assumed to be constant [40] or a time-varying waveform [2], for using the multi-scale analysis of the entire cardiovascular system [37] or a simplified model such as the 3-element Windkessel model [21]. However, as mentioned in [40], varying the magnitude of pressure in the boundary condition will not affect the intraventricular flow dynamic due to the nature of the Navier–Stokes equations; hence, constant pressure can be used if the acquisition of intraventricular pressure is not the desirable output. Despite many investigations having been conducted by using different types of boundary conditions, it remains unclear as to which type is more appropriate in order to more accurately simulate the LV flow dynamics [27]. Long et al. [38] used different types of boundary conditions in the inlet and outlet orifices in order to evaluate the impact of choosing different boundary conditions for the intraventricular flow dynamics, by utilizing: (i) the pressure boundary condition, (ii) the hybrid boundary condition, or a combination of the imposed pressure and velocity at valve opening, (iii) different pressure patch locations, and (iv) different orifice opening sizes. The velocity at the valves in the hybrid case was assumed to be uniform during the valve opening phase. Moreover, zero pressure was imposed on the pressure patch area in the hybrid boundary condition. However, it has been demonstrated that the intra-ventricular flow highly depends on the boundary condition. In this regard, Lassila et al. [30] examined the influence of the boundary conditions on the intraventricular flow pattern by using a combination of multi-scale and IB-CFD. In their research, they used a different boundary condition in the valve orifice. The ideal diode is used to model the valve in the multi-scale method, which allows blood flow through the valve during the positive pressure difference and prevents flow in the reverse direction during the negative pressure difference. Incorporating the valve leaflets In only a few publications [12, 14, 19, 23, 28, 29, 54], valve leaflet motions have been incorporated into the patient-specific LVs. In most publications, valves have been simply modeled as fully open or fully closed orifices. However, neglecting the valve leaflet motion can affect the accuracy of the results, which may thereby influence clinical decision making based on the CFD approach. Neglecting the valve leaflet is due to the low spatiotemporal resolution of the medical images and the high-speed opening and closing of the leaflets [40]. In some researches, valves have been simulated by utilizing the rigid leaflets in both the mitral and aortic valves [19, 23], or only in mitral valves [12, 29, 54] or only in aortic valves [28]. Moreover, in [14], the valve leaflets have been reconstructed in another way by extracting the valve annulus from the visual inspection of medical images. Two different approaches have been implemented in order to derive the motion of valve leaflets: (i) prescribing the leaflet motion to the CFD solver, and (ii) predicting the valve leaflet motion by using the FSI approach. In the first approach, the physiological leaflet kinematics should be extracted over the cardiac cycle by using images such as echocardiographic data and then prescribed to the CFD solver [12, 55]. In the second approach, the partitioned or monolithic methods can be implemented to predict leaflet motion automatically [54]. In the partitioned method, the moment equation of the leaflets and the Navier–Stokes equations are solved simultaneously to obtain the angular position of each leaflet and the moment exerted onto the leaflet interface. Then, these two equations are coupled into each other to iteratively update the moment obtained in both equations until convergence is achieved. In the monolithic method, the total moment exerted from the blood to the leaflet surface is calculated for each time-step. Subsequently, the angular acceleration and the leaflet positions are computed by substituting the exerted moment in the moment equation, without coupling to each other or the iteration. The monolithic method has not been used so far to simulate the valve leaflet motion incorporated with the LV, as it is unable to accurately predict leaflet motion in comparison to the partitioned method. Therefore, the partitioned method will be discussed briefly in the following paragraphs. The general form of the leaflet moment equation which should be solved separately in each leaflet to predict the angular position has the following form [23]: 3 θ¨+ζθ=MI where θ refers to the leaflet angular position, ζ damping coefficient, I moment of inertia, and M the moment. The damping coefficient has been neglected in all the aforementioned papers owing to the fact that the friction force is negligible in comparison to the force exerted by the blood flow to the leaflet interface. The moment of inertia also depends on the leaflet length and thickness. However, Eq. (3) is an ordinary differential equation which can be numerically solved by using different numerical approaches, such as the first order Euler implicit discretization in [23]. The leaflet moment obtained from this equation (Iθ¨) and the CFD simulation (MCFD) should be compared to each other in order to check the convergence criteria (ε=MCFD-Iθ¨). The iteration will stop once it meets the convergence criteria; otherwise, the angular position of the leaflet should be updated and the abovementioned cycle should be performed again until the convergence criterion is met. A similar framework was developed by Dahl et al. [29] to integrate the motion of only the mitral valve leaflets during the diastolic phase in 2D simulation. They used ultrasound imaging to extract the angular positions of both leaflets during the filling phase in order to validate the results obtained from FSI. Their results show that both the anterior leaflet opening dynamics (with low angular velocity) and the posterior leaflet opening dynamics (with high angular velocity) are consistent with the in vivo ultrasound measurements. This framework was completed in [23] by incorporating both aortic and mitral valve leaflet motions in the entire cardiac cycle. As shown in Fig. 2, this work [23] illustrated the initiation and propagation of vortex contours within the LV and the aorta region during the cardiac cycle. The numerical results show that the opening angle of both the mitral and aortic valve leaflets is not similar during the cardiac cycle due to the asymmetric intraventricular flow pattern and non-uniform upstream flow, respectively. The mitral valve leaflet starts opening rapidly in early diastole, but is partially closed in mid-diastole and then reopens during the late diastole as the left atrium (LA) contracts. On the other hand, the aortic valve leaflet opens rapidly with the onset of systole and then closes slowly until the end of systole.Fig. 2 Effect of valves opening and closing on the intra-ventricular flow pattern: Both mitral and aortic valve leaflets are simulated using the rigid leaflets during the entire cardiac cycle. Despite the vortices in LA and AO, the flow field in LV is relatively uniform at the onset of diastole (a). Two vortices are formed in the vicinity of the mitral valve leaflet once diastole starts (b). As mitral valves open more, the boundary layer separation on the tip of both mitral leaflets generates two vortices (c, d). Similarly, two large vortices are formed inside the aorta after boundary separation on the tip of both aortic leaflets (e–g). The vortices are rolled up inside the LV and dissipated at the end of diastole (h–j). During aortic valve openings, a similar boundary separation is formed on the tip of leaflets (k). Finally, the vortices get separated and rolled up to the aorta during the aortic valve closure (l) [23] (Reprinted from [23], with permission from Elsevier) In order to investigate the effect of integrating valve leaflet motion into blood flow dynamics, Seo et al. [12] integrated the mitral valve leaflets into the LV geometry and compared the results for the case without valves. As shown in Fig. 3, the incorporation of the mitral valve leaflet helps to develop the circulatory and asymmetry vortex rings during diastole. Figure 4 illustrates how the blood penetrates deeply toward the LV apex in the model including the mitral valves, in comparison with the model without the mitral leaflets. Bileaflet mechanical heart valve (BMHV) has also been incorporated into the LV in [28]. The main drawback of this research is that the authors ignored the mitral valve motion, which is more important to the intraventricular flow pattern in comparison to the aortic valve leaflet motion, because the key vortices are initiated during the diastolic phase. The evidence from this study suggests that implanting a prosthetic heart valve leads to a more complex flow pattern and causes turbulent flow inside the LV cavity which could enhance clinical complications after BMHV implantation [28]. In this investigation, the numerical results show the valve opening kinematics to be mostly symmetrical, while the closing kinematics is highly asymmetrical.Fig. 3 Comparison of the development of intraventricular flow with and without incorporating valve leaflets: The intraventricular vortex structure formation during the early filling phase is compared in two different conditions: a without the mitral valve, b physiological leaflet. a The circular major vortex ring starts to form during early diastole in the mitral annulus (t = 0.1). The vortex ring then is pinched off to the middle of LV during mid-diastole (t = 0.15 and 0.2). The major vortex rings start breaking down and propagate towards the middle of the LV at the end of diastole. The distorted vortex then penetrates up to two-thirds of the LV (t = 0.25). b The vortex starts breaking even in the early stage of diastole and reaches to the middle of LV (t = 0.1). As time passes, the major vortex ring propagates deeply toward the middle of LV (t = 0.15) and then starts disintegrating (t = 0.2). The distorted vortex reaches close to the LV apex at the end of diastole (t = 0.25) [12] (Reprinted from [12], with permission from AIP Publishing) Fig. 4 Comparison of the pressure drop in a normal subject and MI patient. a The velocity magnitude at the mitral and the pressure drop during diastole. b The velocity magnitude at the aortic orifice and the pressure drop during systole in one normal (N2) and one MI patient (A2). The pressure drop is defined as the difference in the pressure between the apex pressure and mitral orifice (during diastole) or aortic orifice (during systole) pressure. The maximum pressure occurs after A-wave and E-wave during diastole and peak of ejection during systole due to flow acceleration and deceleration [17] (Reprinted from [17], with permission from Elsevier) Patient-specific study subjects Physiological patient-specific LV models The physiological patient-specific LV is the subject of most published papers. In these publications, the geometry has been reconstructed by using medical images of the physiological heart in order to investigate the development of the intraventricular blood flow pattern and different hemodynamic parameters. In 2001, Saber et al. [40] proposed a methodology for IB-CFD simulation of the patient-specific human heart, and showed that this approach is able to capture the intraventricular hemodynamic parameters, such as the blood flow pattern as well as the formation and propagation of vortices during the cardiac cycle. Even though their methodology had some shortcomings by assuming a simplified LV chamber geometry, their methodology was a significant step in the simulation of the human patient-specific LV based on the IB-CFD approach. Later, they [39] improved their previous simplistic LV geometry by adding the proximal LA and ascending aorta to the geometry, improving the MRI data acquisition technique, and employing an improved interactive segmentation technique to obtain more realistic time-varying LV geometry. It should be mentioned that a small part of the aorta and LA needs to be added into the LV in order to minimize the possible inaccuracy associated with the boundary condition assumption in the aortic and mitral orifices. Analyzing the development of intraventricular blood flow patterns or vortex propagation can produce beneficial results for use in the clinical assessment of the cardiovascular function. The qualitative and quantitative analysis of the intraventricular flow pattern by using different LV models not involving any disease is quite similar, with only a few discrepancies over the cardiac cycle. Another significant issue in the LV simulation is determining how many cycles need to be simulated to perform the post-processing step. The results in some early cycles of the simulation are unreliable owing to the inaccuracy of initial condition assumptions. Even though it was discussed in [14] that the flow is highly variable from cycle to cycle due to the intraventricular turbulent flow, it is well accepted in most publications that the flow is repeatable after a few cycles. Also, it has been shown that the flow pattern is repeated with only a small variation after the third cycle [18]. However, small variations in the flow pattern or other hemodynamic parameters can be expected in the subsequent cycles. Ventricular blood mixing refers to the mixing of fresh blood in each cycle with the residue of blood from previous cycles [56]. In the literature, ventricular blood mixing has been found to be highly dependent on intraventricular blood dynamics [25]. Intraventricular blood mixing is an important key in providing valuable information for clinical practice to evaluate cardiac pumping performance [25]. Blood mixing also provides further information by which to evaluate the ventricular washout, which indicates the fraction of residual ventricular blood present after each cardiac cycle. A ventricle with a low washout [57] and apical stagnant flow [58] is prone to a high risk of thrombosis formation. For this purpose, Lagrangian particle tracking can be used to determine intraventricular blood mixing. Therefore, this index is significant in the clinical assessment of heart functionality utilizing the IB-CFD technique. For example, it has been shown that incorporating valve leaflet motion in the simulation can lead to better blood mixing and apical washout [12]. Pathological heart patient-specific models Early cardiac pumping dysfunction can be detected by analyzing LV intraventricular hemodynamics during the diastolic phase [59]. The CVD survival rate due to LV diastolic dysfunction and subsequently HF can be enhanced by early diagnosis [27]. The results of a large volume of published literature indicate that IB-CFD is potentially a promising non-invasive tool for the early diagnosis of LV dysfunction. However, the main challenging issue of IB-CFD in the prognosis of heart dysfunction is finding the correlation between the hemodynamic parameters and the risk factors that initiate heart dysfunction. For instance, it is believed that the formation of the mitral vortex ring during the filling phase is linked with different diastolic dysfunctions [32]; therefore, studying the formation and propagation of the mitral vortex ring could assist physicians in the early diagnosis of CVDs. In this section, we briefly present the different heart dysfunctions that have been simulated in pathological patient-specific LVs, and then discuss their numerical findings. However, it must be noted that up to now, there is a limited number of published papers that have attempted to simulate human patient-specific hearts, especially with pathological conditions. Myocardial infarction (MI): ventricular remodeling and surgical restoration Coronary atherosclerosis causes MI proceeding to decreased ventricular contractility, progressive heart remodeling and heart attack, which can lead to HF and sudden cardiac death. However, even for survivors of MI [8], the heart’s natural functionality continues to deteriorate during the progressive ventricular remodeling process. Therefore, analyzing the MI heart functionality and the alteration of the hemodynamic parameters during the remodeling process (to a more spherical heart shape due to reduced cardiac contractility) could assist physicians in understanding the consequences of MI. Moreover, in some cases, surgical ventricular reconstruction (SVR) is performed to treat the heart remodeling caused by MI [60, 61]. The purpose of SVR is to repair the heart functionality by reducing the enlarged heart volume and restoring the heart’s normal ellipsoidal shape (from its more spherical remodeling shape). The preoperative CFD simulation of the patient-specific heart can assist clinicians to achieve the desired outcome by analyzing the intraventricular flows in different heart shapes and sizes prior to SVR surgery in order to determine the optimal SVR procedure to obtain optimum intraventricular hemodynamics leading to improved cardiac output. Then, the postoperative CFD simulation of the patient-specific heart can also be utilized to investigate the SVR outcome [61, 62]. Even though the 3D model of the LV can reveal more realistic cardiovascular hemodynamic characteristics, it is accepted that 2D modeling is also quite capable of capturing the main hemodynamic characteristics during the cardiac cycle. In this regard, Khalafvand et al. [17] studied three different normal LVs and three different patient LVs after MI, to investigate the effect of heart remodeling on the hemodynamic parameters. In this simulation, they thoroughly demonstrated the formation and propagation of vortices, and compared the flow patterns of all cases during the entire cardiac cycle. Also, as shown in Fig. 4, they plotted the pressure difference (between the mitral and aortic orifices and the LV apex) in the LV for all the cases. In this research, it is shown that the blood flow pattern in MI LV is significantly different from that in the normal LV. For instance, as shown in Fig. 5, the number and strength of the main vortices of normal LV models are larger and stronger than MI models at the peak of systole. Also, more small vortices are generated in a normal LV at end-diastole, as shown in Fig. 5. The results show that the flow momentum in MI models is lower than in the normal models due to the enlarged volume. Contrary to normal cases, the pressure difference (and pressure gradient) is considerably lower in the patient models due to the low stroke volume. Based on these obtained results, the researchers observed that a quantitative assessment of the blood flow pattern and vortices could assist the early diagnosis of heart dysfunction.Fig. 5 Comparison of intraventricular flow patterns in a normal subject and MI patient. The figure illustrates the streamlines at the end of diastole for normal cases (N1, N2, N3) and abnormal cases (A1, A2, A3). It can be noted that more vortices are generated in the normal LVs. It is seen that the inside of the LV cavity is dominated by a big vortex in the N3 case and all other abnormal cases [17]. ​(Reprinted from [17], with permission from Elsevier) Subsequently, Khalafvand et al. [31] compared the hemodynamic parameters of one patient LV before and 4 months after SVR surgery, to observe the surgery outcome from a hemodynamic point of view. In this research, unlike in their previous study, they used 3D models of the preoperative and postoperative LV to compute the blood flow dynamics. They illustrated that SVR surgery enhanced the strength of the intraventricular vortices that led to a higher ejection fraction during the cardiac cycle. Later, they [13] further investigated the influence of the SVR and coronary artery bypass grafting (CABG) surgery in the patient-specific model before and after the surgery. The flow patterns in both the LV models before and after the SVR are shown in Figs. 6 and 7. The results show that the vortices in the preoperative model are weak in comparison to the postoperative model. The results also show that the maximum velocities at the inlet and outlet orifices in the preoperative model are less than postoperatively. The results demonstrate that during diastole, stronger vortices are generated in the postoperative model, which improves blood recirculation. Vortices are noted to disappear quickly after their formation in the preoperative case, but stay longer in the postoperative model. In both cases, the direction of the main vortex enables efficient ejection during the systolic phase. Likewise, the ejection fraction shows improvement from 34 to 48 % after SVR. These results demonstrate the effectiveness of SVR to improve intraventricular flow patterns and produce (i) stronger vortices during the cardiac cycle, and (ii) a higher ejection fraction. Therefore, these results illustrate that CFD can be utilized to investigate surgery outcomes.Fig. 6 Flow patterns of an MI patient before surgery: The flow patterns are shown during diastole (a–f) and during systole (g–j) respectively. Vortices during diastole disappear quickly after their formation in the preoperative case [13] (Adapted from [13], with permission from Wiley) Fig. 7 Flow patterns of an MI patient after surgery: Flow pattern during diastole (a–f) and systole (g–m), respectively. Strong vortices are formed during diastole in comparison to the pre-operative model (Fig. 6), which demonstrates the improvement in blood flow circulation after SVR. Improvement of the outflow jet direction through the aortic orifice demonstrates more efficient blood pumping after operation [13] (Adapted from [13], with permission from Wiley) Likewise, Doenst et al. [35] numerically studied the intraventricular hemodynamics of preoperative and postoperative patient-specific LVs, to investigate the effectiveness of SVR surgery on the remodeled LV. The result shows that the postoperative LV geometry is more spherical in comparison to the preoperative LV and normal LV. The intraventricular flow pattern after SVR is significantly different from the flow pattern before surgery, but is still not as good as that of the healthy LV. The flow patterns after surgery and in the normal LV are topologically similar during the diastolic phase. The streamlines before surgery show a stagnation point in the apex region; also, the vortices are not expanding asymmetrically inside the LV cavity, which prevents blood flow redirection toward the aortic outflow track. The numerical results demonstrate that the washout volume of the normal LV after four cardiac cycles is 2 %, but the value for the preoperative LV is 35 % and for the postoperative LV is just slightly less than 35 %. This shows that the LV washout after surgery is not considerably improved in comparison to the preoperative LV in spite of the large shape modification. The ejection fractions in the normal, preoperative and postoperative LV are 0.61, 0.15, and 0.18, respectively. Therefore, the intraventricular hemodynamics improvement contributes to the enhanced postoperative ejection fraction. Dilated cardiomyopathy (DCM) Dilated cardiomyopathy (DCM) is another pathological heart condition causing ventricular dilatation and heart enlargement. The DCM condition progressively reduces the contractility of the LV by changing the natural heart shape and size. This pathological condition reduces the development of adequate systolic pressure due to decreased LV contractility, and thereby leads to reduced cardiac output [63]. As in the MI condition, the heart’s hemodynamic parameters change in the DCM condition due to heart remodeling. In the DCM condition, the intraventricular vortices become weaker and smaller due to flow momentum reduction in the enlarged LV. Hence, CFD simulation by patient-specific models and comparison with healthy LV models, and finding the correlation between the hemodynamic parameters and the ventricular performance can enhance our knowledge about the progress and severity of DCM. To characterize intraventricular flows in DCM patients, Mangual et al. [7] numerically and statistically analyzed the hemodynamic parameters of 20 normal subjects and 8 DCM patients by using a combination of 3D echocardiography and Direct Numerical Simulation methods. Statistical results show that the ejection fraction in DCM patients (17.8 ± 6.4 %) is significantly lower than in a normal heart (55.4 ± 3.5 %). The numerical finding indicates that, during mid-diastole, a counter-clockwise vortex is developed in the entire LV cavity for the normal subject; however, for the DCM patient, a small vortex ring is generated on the upper side of the LV cavity. Moreover, at end-diastole, the large vortex ring in the normal subject is redirected to the outflow track; in the DCM patient, a weak vortex is formed and is located in the middle of the LV cavity. The results also show that the vortex formation time in the normal LV is considerably greater than in the case of the DCM patient. Moreover, the kinematic energy dissipation in the normal LV during diastole and systole is more than in the normal LV. Hypertrophic cardiomyopathy (HCM) Hypertrophic cardiomyopathy (HCM) is a myocardial defect that refers to an excessive thickening of a portion of the LV myocardium that causes sudden HF. The HCM condition and the resulting LV stiffness interferes with the ability of the LV to expand and fill before the onset of systole, due to the LV size and myocardium elasticity reduction [64]. The myocardium thickening and the flow obstruction in the HCM pathological condition have a strong impact on LV performance and the intraventricular blood flow. Therefore, the CFD simulation of the HCM LV can provide useful insights for understanding the variation of the intraventricular blood flow dynamics in this disease condition. To study the effect of HCM, Su et al. [22] simulated the flows in a normal subject and a HCM LV, in order to compare the intraventricular flow patterns of the HCM LV and healthy LVs. In this study, they thoroughly compared the formation and propagation of the intraventricular vortices in different cardiac stages. As shown in Fig. 8, larger and stronger vortices are developed in the healthy LV in comparison to the HCM LV at the end of diastole. Also, the vortex ring growth is disrupted in the HCM LV in comparison with the healthy LV due to the narrowing of the LV chamber. As seen in Fig. 8, vortices are pumped deeply into the apex part in the HCM LV. Moreover, as shown in Fig. 9, a comparison of the vortex structures in the two models shows that a cirrostratus-like cloud is formed in the HCM LV, while a normal major vortex ring is formed in the healthy LV.Fig. 8 Comparison of intraventricular flow patterns in a normal subject and a HCM patient: Intraventricular streamline distributions at the end of diastole in a healthy subject model (left) and a HCM patient model (right). It is seen that larger and stronger vortices are developed in the healthy LV. Also, the vortices are pumped deeply into the apex part in the HCM LV [22] (Reprinted from [22], with permission from IEEE) Fig. 9 Comparison of end-diastolic vortex formation in a normal subject and a DCM patient. The vortex structures of one healthy (left) and HCM (right) model are compared. The major vortex structure remains strong, like a cirrostratus cloud, at the end of diastole. The major vortex in the disease model is rolled up deeply toward the apex, and it is dissipated into connected small vortices [22] (Reprinted from [22], with permission from IEEE) Hypoplastic left heart syndrome (HLHS) The hypoplastic left heart syndrome (HLHS) is a congenital heart disorder that refers to an underdeveloped LV before birth. In the HLHS condition, the RV supports both pulmonary and systemic circulations. This heart defect is a fatal condition that needs surgery in the first days after birth. As shown in Fig. 10, complex multistage surgery must be performed to isolate the pulmonary and systemic blood circulations. Usually, there are three stages in the operation, these being Norwood, Glenn, and Fontan [65]. In the first stage of the operation, the Norwood operation, the ascending aorta and aortic arch is reconstructed by using the pulmonary artery to create systemic circulation. Subsequently, a shunt is inserted between the pulmonary artery and subclavian vessel in order to maintain pulmonary circulation. In the second stage, the Glenn operation, the pulmonary circulation is isolated from the systemic circulation by connecting the superior vena cava to the pulmonary artery. However, the deoxygenated blood received from the inferior vena cava still mixes with the oxygenated blood in systemic circulation. Finally, both superior and inferior vena cave arteries are connected to the pulmonary artery in the third stage, the Fontan operation, in order to completely isolate the pulmonary and systemic circulations. At the end of the third operation, the RV pumps only oxygenated blood to the systemic circulation [26, 66, 67]. This multistage operation is complex and has high risk; therefore, numerical simulations of each stage prior to surgery can be a useful and promising tool. Some numerical investigations [65, 68] have been carried out to evaluate the ventricular workload of the single ventricle by using different types of arch reconstruction and calculating the hemodynamic factors, such as energy loss and WSS. For instance, the numerical findings of utilizing various Norwood arch reconstruction in [68] suggested that using a smooth aortic arch angle with the large anastomotic space lead to the reduction of WSS and energy loss, meaning the improvement of postoperative cardiac performance.Fig. 10 Different stages of operations performed on patients with HLHS: a The general schematic of the heart in the HLHS condition; RV supports both pulmonary and systemic circulations. b Stage I (Norwood): the ascending aorta and aortic arch is reconstructed, and a shunt is inserted between the pulmonary artery and subclavian vessel, c Stage II (Glenn): the superior vena cava is connected to the pulmonary artery to isolate the pulmonary circulation, d Stage III (Fontan): both superior and inferior vena cave arteries are connected to the pulmonary to completely isolate the pulmonary and systemic circulations [67] (Reprinted from [67], with permission from Macmillan Publishers Ltd) In order to investigate the effect of aortic arch reconstruction on the functionality of the postoperative RV, Vecchi et al. [26] numerically studied intraventricular blood flows in two different patient-specific HLHS cases after aortic arch reconstruction and compared them with the flow in the normal LV. The numerical findings show that the filling streamlines and the myocardial displacements of the two HLHS RV cases and a healthy normal LV are significantly different at the peak of E-wave. The numerical results demonstrate that the shape and propagation of the vortex are completely different in the two HLHS cases in comparison with the normal case. The high velocity difference between the basal and apical region reduces the diastolic process efficiency due to the reduced pressure gradient. Thereby, it can be seen that the reduced and/or delayed early pressure gradient is associated with LV diastolic dysfunction. In 2013, Corsini et al. [16] numerically simulated preoperative and postoperative patient-specific models to study the outcome of the stage two single ventricle (SV) surgery. The 3D virtual surgery was performed with two different surgical options (hemi-Fontan operation and bi-directional Glenn) in the preoperative model, to investigate the performance of both surgeries from a hemodynamic point of view. Even though the numerical post-operative results show little difference in the local hemodynamics between the two surgery options, the study shows the capability of CFD in selecting the optimal surgical option before the operation. Validation of numerical findings Verification can be defined as “solving the equations right”, which in turn assesses the accuracy of the numerical data by using analytical solutions. Computational method validation on the other hand can be defined as “solving the right equations”, and validating the numerical predictions with real or experimental data [69]. The validity of the cardiovascular CFD simulation results widely depends on the selection of appropriate geometry, boundary conditions, fluid and solid domain material property, mesh qualities, and the numerical approach. Due to the many simplifications and assumptions taken into account in the numerical simulation of LV, the degree of accuracy of the results needs to be assessed prior to utilizing them for applications in clinical practice. However, because of the difficulty in measuring the hemodynamics parameters of the cardiovascular system, only a few papers have validated their numerical findings. In some publications, such as [8], only a qualitative validation is available by utilizing in vivo magnetic resonance velocity imaging. A quantitative comparison of CFD results and magnetic resonance measurements in LV simulation is challenging in comparison with flow simulation in large arteries, due to the complex nature of the intraventricular flow pattern and large deformation of the LV geometry [8]. Also, a circulatory system with a pressurized chamber to reproduce physiological flow, similar to the LV, has been used in [34, 35] to qualitatively validate the numerical findings of the intraventricular flow dynamics. Saber et al. [39] have quantitatively compared the intraventricular blood flow patterns obtained by CFD simulation with the in vivo measured data in previous work [70, 71] obtained by magnetic resonance velocity mapping. Long et al. [8] have qualitatively validated their numerical simulation results, using a similar technique. The MRI images detected small vortices close to the inflow tract and papillary muscles, which were not observed in the CFD simulation due to geometry simplifications. Another qualitative validation of numerical results using in vivo flux mapping was performed by Schenkel et al. [36]; in vivo flux mapping was performed by using the MRI phase coded flux scan with 3-directional flow velocity encoding. Overall, the velocity contours extracted from CFD simulation were found to be in good agreement with the MRI flux measurements. Krittian et al. [34] developed an artificial ventricular setup to validate the numerical simulation of the LV, which was performed by using two different approaches: (1) geometry-prescribed (KaHMo MRT), and (2) the coupled-FSI (KaHMo FSI). The experimental setup consists of a simplified LV sac that is integrated with biological heart valves. The LV sac was placed in a pressurized chamber to reproduce physiological flow, and the flow pattern was captured by using the Particle Image Velocimetry (PIV) technique. In this study, it has been shown that the blood flow pattern was in good qualitative agreement with the experimental results. The experimental results represented the capability of numerical simulation to reproduce an approximately similar flow pattern formed in the experimental setup. Moreover, the numerical and experimental results show that other hemodynamic and structural parameters, such as the LV cavity spatiotemporal structural volume deformation, LV pump characteristics (such as the pressure–volume work, performance, mixing coefficients, and ejection fraction) and the cardiac cyclic pressure–volume relationship are in a good agreement. Conclusion In this review paper, we have presented the various investigations that have been conducted to numerically simulate patient-specific human LVs over the past 15 years by using IB-CFD methods. CFD hemodynamic parameters utilization for detailed characterization CFD is considered to be a robust tool that can be used to evaluate the hemodynamic parameters of intraventricular blood flow, such as WSS, pressure distribution, pressure gradient or other intraventricular blood flow parameters, to facilitate the detailed characterization of LV pathologies. The recent advancement of blood flow modeling can provide a detailed understanding of the blood flow dynamics, which cannot be achieved solely through invasive modalities, such as characterization, or medical imaging. The computer modeling of the intraventricular flow fulfills the capability of hemodynamic parameters to serve as non-invasive clinical diagnostic indices, to facilitate diagnosis of LV dysfunction [72]. Vascular hemodynamics, involving numerical simulation of blood flow in arteries, is now widely accepted for use in clinical practices. Now it is a welcome news that HeartFlow® FFRCT software (HeartFlow Inc., USA) has received the FDA approval for clinical applications [73]; however, we still need to take care of the heart flow simulation challenges, such as incorporating heart valve motion. In the meantime, we can be in the process of deciding which hemodynamic parameters can be best utilized to assist physicians in the early diagnosis and prognosis of CVDs. Benefits of IB-CFD patient-specific intraventricular flow modeling Patient-specific LV models can be used for various purposes, such as for (i) hemodynamic evaluation of physiological and pathological LVs, and (ii) assessment of surgery outcomes by analyzing preoperative LVs and simulating the hemodynamics associated with the various surgical alternatives prior to performing surgery, i.e. the virtual surgical planning. Objectively speaking, IB-CFD patient-specific intraventricular flow modeling has the potential to become a viable tool for: (i) assessing LV pathologies for clinical practice, and (ii) determining how reconstructive surgical procedures can improve cardiac functional performance. This study has notably revealed that different targets have been selected by authors to numerically simulate the LV flow dynamics, such as (i) characteristics analysis [2], (ii) analysis of preoperative and postoperative LVs to evaluate surgical outcomes [13], (iii) preoperative LV analysis to examine various surgical alternatives to choose the best option [16], and finally (iv) analysis of pathological LVs to assess their physiological conditions [17]. Some concerns in relation to IB-CFD patient-specific modeling For the purpose of further improvements in diagnostics, prognosis and surgical outcomes, it is worthwhile mentioning some limitations of and concerns in relation to IB-CFD patient-specific LV modeling and analysis. The IB-CFD requires high operator-dependent steps, such as image acquisition, image segmentation, geometry reconstruction, mesh generation, and finally numerical simulation [27]; these steps can be potential sources of error that can impact the results. In addition, other CFD errors can arise, such as the round-off error, iterative error, convergence error, as well as the possibility of defining inappropriate boundary conditions. Moreover, the numerical instability and the convergence criteria of the CFD problem are other concerns relating to numerical simulations. Additionally, an LV CFD simulation study usually needs parallel processing and more computing facilities, which makes it somewhat expensive and time-consuming. Also, most of the available models include some geometrical and/or physical approximations/assumptions that can affect the computational results. Further improvements in LV CFD simulation A more precise model to mimic realistic hemodynamics of patient-specific LVs needs to include the following elements: More realistic geometry, including the physiological inner endocardium surface, papillary muscles, and chordae tendineae, Simulation of the actual heart mitral and aortic valves motion, Incorporation of realistic blood properties (non-Newtonian properties) and myocardium structural properties, EFSI of the LV, Reconstruction of other associated cardiovascular components, such as the LA, aortic root, and valves in order to provide a more realistic boundary condition. LV CFD Simulation could constitute a promising clinical tool, with the inclusion of the following several improvements in the future researches (i) data acquisition techniques to capture high spatiotemporal resolution images, (ii) image processing techniques to reconstruct precise geometry, (iii) computing facilities to simulate the model in a short time period, and (iv) more rigorous correlation of the hemodynamic parameters with the clinical quantification of heart dysfunctional assessment and its improvement by surgical procedures. Finally, as stated in [74], a multidisciplinary collaboration between clinicians and engineers is required to understand the approximations, assumptions, and limitations of the numerical simulations in order to utilize CFD findings in clinical decisions. Altogether, we can say that heart flow simulation is on the right track for developing into a useful clinical tool for heart function diagnosis. Heart flow simulation now needs to determine some diagnostic indices based hemodynamic parameters, which we can start adopting in clinical usage. In the meantime, we also need to work on incorporating most of heart structures’ (such as heart valves) operations into our heart hemodynamics modeling, so as to most closely simulate intraventricular flow. Abbreviations BMHVbileaflet mechanical heart valve CABGcoronary artery bypass grafting CFDcomputational fluid dynamics CTcomputed tomography CVDcardiovascular disease DCMdilated cardiomyopathy ECGechocardiography EFSIelectrical-fluid-structure interaction FSIfluid-structure interaction HFheart failure HCMhypertrophic cardiomyopathy HLHShypoplastic left heart syndrome IB-CFDimaged-base computational fluid dynamics IBMimmersed boundary method LAleft atrium LESlarge eddy simulation LHFleft heart failure LVleft ventricle MImyocardial infarction MRImagnetic resonance image PIVparticle image velocimetry PAHpulmonary arterial hypertension RVright ventricle SVsingle ventricle SVRsurgical ventricular reconstruction WSSwall shear stress Authors’ contributions SND: collecting, organizing, and reviewing the literature and then preparing the manuscript. DG: reviewing, modifying, and critically revising the manuscript. BS, LZ, and YSM: reviewing and modifying the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors would like to acknowledge the financial support received from the Swinburne University of Technology and National Heart Research Institute Singapore to carry out this research. Competing interests The authors declare that they have no competing interests. Funding This work was funded by Swinburne University of Technology and National Heart Research Institute Singapore. We declare that funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Note All figures are reprinted/ adapted with the written permission of the copyright provided by owners/publishers. ==== Refs References 1. Bermejo J Martínez-Legazpi P del Álamo JC The clinical assessment of intraventricular flows Annu Rev Fluid Mech 2015 47 1 315 342 10.1146/annurev-fluid-010814-014728 2. Moosavi M-H Fatouraee N Katoozian H Pashaei A Camara O Frangi AF Numerical simulation of blood flow in the left ventricle and aortic sinus using magnetic resonance imaging and computational fluid dynamics Comput Methods Biomech Biomed Eng 2012 17 7 740 749 10.1080/10255842.2012.715638 3. Chan BT Lim E Chee KH Abu Osman NA Review on CFD simulation in heart with dilated cardiomyopathy and myocardial infarction Comput Biol Med 2013 43 4 377 385 10.1016/j.compbiomed.2013.01.013 23428371 4. Markl M Frydrychowicz A Kozerke S Hope M Wieben O 4D flow MRI J Magn Reson Imaging 2012 36 5 1015 1036 10.1002/jmri.23632 23090914 5. Callaghan FM Karkouri J Broadhouse K Evin M Fletcher DF Grieve SM Thoracic aortic aneurysm: 4D flow MRI and computational fluid dynamics model Comput Methods Biomech Biomed Eng 2015 18 sup1 1894 1895 10.1080/10255842.2015.1069559 6. Tay W-B Tseng Y-H Lin L-Y Tseng W-Y Towards patient-specific cardiovascular modeling system using the immersed boundary technique Biomed Eng Online 2011 10 1 52 10.1186/1475-925X-10-52 21682851 7. Mangual JO Kraigher-Krainer E De Luca A Toncelli L Shah A Solomon S Comparative numerical study on left ventricular fluid dynamics after dilated cardiomyopathy J Biomech 2013 46 10 1611 1617 10.1016/j.jbiomech.2013.04.012 23664278 8. Long Q Merrifield R Xu X Kilner P Firmin D Yang G Subject-specific computational simulation of left ventricular flow based on magnetic resonance imaging. Proceedings of the Institution of Mechanical Engineers, Part H J Eng Med 2008 222 4 475 485 10.1243/09544119JEIM310 9. Bellhouse BJ Fluid mechanics of a model mitral valve and left ventricle Cardiovasc Res 1972 6 2 199 210 10.1093/cvr/6.2.199 5034234 10. Arefin MS Morsi YS Fluid structure interaction (FSI) simulation of the left ventricle (LV) during the early filling wave (E-wave), diastasis and atrial contraction wave (A-wave) Australas Phys Eng Sci Med 2014 37 2 1 11 10.1007/s13246-014-0250-4 24668521 11. Nakamura M Wada S Yamaguchi T Computational analysis of blood flow in an integrated model of the left ventricle and the aorta J Biomech Eng 2006 128 6 837 843 10.1115/1.2400864 17154683 12. Seo JH Vedula V Abraham T Lardo AC Dawoud F Luo H Mittal R Effect of the mitral valve on diastolic flow patterns Phys Fluids 2014 26 12 121901 10.1063/1.4904094 13. Khalafvand SS Zhong L Ng EYK Three-dimensional CFD/MRI modeling reveals that ventricular surgical restoration improves ventricular function by modifying intraventricular blood flow Int J Numer Methods Biomed Eng 2014 30 10 1044 1056 10.1002/cnm.2643 14. Chnafa C Mendez S Nicoud F Image-based large-eddy simulation in a realistic left heart Comput Fluids 2014 94 173 187 10.1016/j.compfluid.2014.01.030 15. Pedrizzetti G Domenichini F Left ventricular fluid mechanics: the long way from theoretical models to clinical applications Ann Biomed Eng 2015 43 1 26 40 10.1007/s10439-014-1101-x 25186434 16. Corsini C Baker C Kung E Schievano S Arbia G Baretta A An integrated approach to patient-specific predictive modeling for single ventricle heart palliation Comput Methods Biomech Biomed Eng 2013 17 14 1572 1589 10.1080/10255842.2012.758254 17. Khalafvand SS Ng EYK Zhong L Hung TK Fluid-dynamics modelling of the human left ventricle with dynamic mesh for normal and myocardial infarction: preliminary study Comput Biol Med 2012 42 8 863 870 10.1016/j.compbiomed.2012.06.010 22795507 18. Doost SN Zhong L Su B Morsi YS The numerical analysis of non-Newtonian blood flow in human patient-specific left ventricle Comput Methods Programs Biomed 2016 127 232 247 10.1016/j.cmpb.2015.12.020 26849955 19. Su B Tan RS Tan JL Guo KWQ Zhang JM Leng S Cardiac MRI based numerical modeling of left ventricular fluid dynamics with mitral valve incorporated J Biomech 2016 49 7 1199 1205 10.1016/j.jbiomech.2016.03.008 26993615 20. Nguyen VT Wibowo SN Leow YA Nguyen HH Liang Z Leo H A patient-specific computational fluid dynamic model for hemodynamic analysis of left ventricle diastolic dysfunctions Cardiovasc Eng Technol 2015 45 1 18 21. Muehlhausen M-P Janoske U Oertel H Implicit partitioned cardiovascular fluid-structure interaction of the heart cycle using non-newtonian fluid properties and orthotropic material behavior Cardiovasc Eng Technol 2014 6 1 8 18 10.1007/s13239-014-0205-7 26577098 22. Su B, Zhang J-M, Tang HC, Wan M, C. C. W. L, Su Y, et al. Patient-specific blood flows and vortex formations in patients with hypertrophic cardiomyopathy using computational fluid dynamics. In: Biomedical engineering and sciences (IECBES). Sarawak: IEEE; 2013. 23. Su B Zhong L Wang X-K Zhang J-M Tan RS Allen JC Numerical simulation of patient-specific left ventricular model with both mitral and aortic valves by FSI approach Comput Methods Programs Biomed 2014 113 2 474 482 10.1016/j.cmpb.2013.11.009 24332277 24. de Vecchi A Gomez A Pushparajah K Schaeffter T Nordsletten DA Simpson JM Towards a fast and efficient approach for modelling the patient-specific ventricular haemodynamics Prog Biophys Mol Biol 2014 116 1 3 10 10.1016/j.pbiomolbio.2014.08.010 25157924 25. Seo JH Mittal R Effect of diastolic flow patterns on the function of the left ventricle Phys Fluids 2013 25 11 1 21 10.1063/1.4819067 26. de Vecchi A Nordsletten DA Razavi R Greil G Smith NP Patient specific fluid-structure ventricular modelling for integrated cardiac care Med Biol Eng Comput 2013 51 11 1261 1270 10.1007/s11517-012-1030-5 23340962 27. Nguyen V-T Loon CJ Nguyen HH Liang Z Leo HL A semi-automated method for patient-specific computational flow modelling of left ventricles Comput Methods Biomech Biomed Eng 2013 18 4 1 13 28. Le TB Sotiropoulos F Fluid-structure interaction of an aortic heart valve prosthesis driven by an animated anatomic left ventricle J Comput Phys 2013 244 41 62 10.1016/j.jcp.2012.08.036 23729841 29. Dahl SK Vierendeels J Degroote J Annerel S Hellevik LR Skallerud B FSI simulation of asymmetric mitral valve dynamics during diastolic filling Computer Methods Biomech Biomed Eng 2010 15 2 121 130 10.1080/10255842.2010.517200 30. Lassila TM, Malossi ACI, Stevanella M, Deparis S, Votta E, Redaelli A. Multiscale fluid-structure interaction simulation of anatomically correct left ventricle fluid dynamics with fictitious elastic structure regularization. Wiley InterScience; 2012. 31. Khalafvand SS, Ng EY-K, Zhong L. Three-dimensional MRI-based computational fluid modeling of the left ventricle for patient before and after surgical ventricular restoration. In: Biomedical engineering and biotechnology (iCBEB) international conference on 2012. IEEE; 2012. 32. Le TB Sotiropoulos F On the three-dimensional vortical structure of early diastolic flow in a patient-specific left ventricle Eur J Mech B Fluids 2012 35 20 24 10.1016/j.euromechflu.2012.01.013 22773898 33. Mihalef V Ionasec RI Sharma P Georgescu B Voigt I Suehling M Comaniciu D Patient-specific modelling of whole heart anatomy, dynamics and haemodynamics from four-dimensional cardiac CT images Interface Focus 2011 1 3 286 296 10.1098/rsfs.2010.0036 22670200 34. Krittian S Janoske U Oertel H Böhlke T Partitioned fluid-solid coupling for cardiovascular blood flow Ann Biomed Eng 2010 38 4 1426 1441 10.1007/s10439-009-9895-7 20058187 35. Doenst T Spiegel K Reik M Markl M Hennig J Nitzsche S Fluid-dynamic modeling of the human left ventricle: methodology and application to surgical ventricular reconstruction Ann Thorac Surg 2009 87 4 1187 1195 10.1016/j.athoracsur.2009.01.036 19324149 36. Schenkel T Malve M Reik M Markl M Jung B Oertel H MRI-based CFD analysis of flow in a human left ventricle: methodology and application to a healthy heart Ann Biomed Eng 2009 37 3 503 515 10.1007/s10439-008-9627-4 19130229 37. Liang F Taniguchi H Liu H A multi-scale computational method applied to the quantitative evaluation of the left ventricular function Comput Biol Med 2007 37 5 700 715 10.1016/j.compbiomed.2006.06.011 16914132 38. Long Q Merrifield R Yang GZ Xu XY Kilner PJ Firmin DN The influence of inflow boundary conditions on intra left ventricle flow predictions J Biomech Eng 2004 125 6 922 927 10.1115/1.1635404 14986421 39. Saber N Wood N Gosman AD Merrifield R Yang G-Z Charrier C Progress towards patient-specific computational flow modeling of the left heart via combination of magnetic resonance imaging with computational fluid dynamics Ann Biomed Eng 2003 31 1 42 52 10.1114/1.1533073 12572655 40. Saber N Gosman AD Wood N Kilner P Charrier C Firmin D Computational flow modeling of the left ventricle based on in vivo MRI data: initial experience Ann Biomed Eng 2001 29 4 275 283 10.1114/1.1359452 11339325 41. Nakamura M Wada S Mikami T Kitabatake A Karino T Computational study on the evolution of an intraventricular vortical flow during early diastole for the interpretation of color M-mode Doppler echocardiograms Biomech Model Mechanobiol 2003 2 2 59 72 10.1007/s10237-003-0028-1 14586809 42. Souli M, Benson DJ. Arbitrary Lagrangian Eulerian and fluid-structure interaction: numerical simulation. Wiley; 2013. 43. Axisa F, Antunes J. Modelling of mechanical systems: fluid-structure interaction: fluid-structure interaction. Elsevier Science; 2006. 44. Wang X. Fundamentals of fluid-solid interactions: analytical and computational approaches. In: Luo G, Zaslavsky AC, editors. Monograph series on nonlinear science and complexity. Elsevier Science; 2008. 45. Yilmaz F Gundogdu MY A critical review on blood flow in large arteries; relevance to blood rheology, viscosity models, and physiologic conditions Korea-Aust Rheol J 2008 20 4 197 211 46. Nezamidoost S Sadeghy K Askari V Pulsatile flow of thixotropic fluids through a partially-constricted tube Nihon Reoroji Gakkaishi 2013 41 2 45 52 10.1678/rheology.41.45 47. Baskurt OK Meiselman HJ Blood rheology and hemodynamics Semin Thromb Hemost 2003 29 5 435 450 10.1055/s-2003-44551 14631543 48. Nezamidoost S Sadeghy K Peristaltic pumping of thixotropic fluids: a numerical study Nihon Reoroji Gakkaishi 2012 40 1 1 9 10.1678/rheology.40.1 49. Karimi S Dabagh M Vasava P Dadvar M Dabir B Jalali P Effect of rheological models on the hemodynamics within human aorta: CFD study on CT image-based geometry J Non-Newton Fluid Mech 2014 207 42 52 10.1016/j.jnnfm.2014.03.007 50. Tazraei P Riasi A Takabi B The influence of the non-Newtonian properties of blood on blood-hammer through the posterior cerebral artery Math Biosci 2015 264 119 127 10.1016/j.mbs.2015.03.013 25865933 51. Tazraei P Riasi A Quasi-two-dimensional numerical analysis of fast transient flows considering Non-Newtonian effects J Fluids Eng 2015 138 1 011203 10.1115/1.4031093 52. Doost S, Zhong L, Su B, Morsi Y. The influence of non-Newtonian characteristics of blood on the patient-specific left ventricle. In: Australian biomedical engineering conference (ABEC 2015). Melbourne Engineers Australia; 2015. 53. Seo JH Vedula V Abraham T Mittal R Multiphysics computational models for cardiac flow and virtual cardiography Int J Numer Methods Biomed Eng 2013 29 8 850 869 10.1002/cnm.2556 54. Su B Kabinejadian F Phang HQ Kumar GP Cui F Kim S Numerical modeling of intraventricular flow during diastole after implantation of BMHV PLoS ONE 2015 10 5 e0126315 10.1371/journal.pone.0126315 25961285 55. Gharaie SH Morsi Y A novel design of a polymeric aortic valve Int J Artif Organs 2015 38 5 259 270 10.5301/ijao.5000413 26044657 56. Zheng X Seo JH Vedula V Abraham T Mittal R Computational modeling and analysis of intracardiac flows in simple models of the left ventricle Eur J Mech B Fluids 2012 35 31 39 10.1016/j.euromechflu.2012.03.002 57. Nakamura M Wada S Yamaguchi T Influence of the opening mode of the mitral valve orifice on intraventricular hemodynamics Ann Biomed Eng 2006 34 6 927 935 10.1007/s10439-006-9127-3 16783649 58. Domenichini F Pedrizzetti G Baccani B Three-dimensional filling flow into a model left ventricle J Fluid Mech 2005 539 179 198 10.1017/S0022112005005550 59. Baccani B Domenichini F Pedrizzetti G Vortex dynamics in a model left ventricle during filling Eur J Mech B Fluids 2002 21 5 527 543 10.1016/S0997-7546(02)01200-1 60. Zhong L Su Y Gobeawan L Sola S Tan R-S Navia JL Impact of surgical ventricular restoration on ventricular shape, wall stress, and function in heart failure patients Am J Physiol Heart Circ Physiol 2011 300 5 H1653 H1660 10.1152/ajpheart.00021.2011 21357513 61. Su Y Zhong L Lim C-W Ghista D Chua T Tan R-S A geometrical approach for evaluating left ventricular remodeling in myocardial infarct patients Comput Methods Programs Biomed 2012 108 2 500 510 10.1016/j.cmpb.2011.03.008 21507502 62. Zhong L, Tan R, Su Y, Yeo S, Chua T, Koh T, et al. Noninvasive assessment of left ventricular remodeling: geometry, wall stress, and function. In: Guccione JM, Kassab GS, Ratcliffe MB, editors. Berlin: Springer; 2010. pp. 179–196. 63. Bozkurt S Safak KK Evaluating the hemodynamical response of a cardiovascular system under support of a continuous flow left ventricular assist device via numerical modeling and simulations Comput Math Methods Med 2013 2013 12 10.1155/2013/986430 64. Salvo SG. Mosby’s pathology for massage therapists. Mosby/Elsevier; 2008. 65. Qian Y Liu JL Itatani K Miyaji K Umezu M Computational hemodynamic analysis in congenital heart disease: simulation of the Norwood procedure Ann Biomed Eng 2010 38 7 2302 2313 10.1007/s10439-010-9978-5 20195758 66. Liu J Qian Y Sun Q Liu J Umezu M Use of computational fluid dynamics to estimate hemodynamic effects of respiration on hypoplastic left heart syndrome surgery: total cavopulmonary connection treatments Sci World J 2013 2013 12 67. Albers EL Bichell DP McLaughlin B New approaches to neuroprotection in infant heart surgery Pediatr Res 2010 68 1 1 9 10.1203/PDR.0b013e3181df5402 20351657 68. Itatani K Miyaji K Qian Y Liu JL Miyakoshi T Murakami A Influence of surgical arch reconstruction methods on single ventricle workload in the Norwood procedure J Thorac Cardiovasc Surg 2012 144 1 130 138 10.1016/j.jtcvs.2011.08.013 21907359 69. Taylor CA Figueroa CA Patient-specific modeling of cardiovascular mechanics Annu Rev Biomed Eng 2009 11 1 109 134 10.1146/annurev.bioeng.10.061807.160521 19400706 70. Kim WY Walker PG Pedersen EM Poulsen JK Oyre S Houlind K Yoganathan AP Left ventricular blood flow patterns in normal subjects: a quantitative analysis by three-dimensional magnetic resonance velocity mapping J Am Coll Cardiol 1995 26 1 224 238 10.1016/0735-1097(95)00141-L 7797756 71. Kilner PJ Yang G-Z Wilkes AJ Mohiaddin RH Firmin DN Yacoub MH Asymmetric redirection of flow through the heart Nature 2000 404 6779 759 761 10.1038/35008075 10783888 72. Merrifield R, Long Q, Xu XY, Kilner PJ, Firmin DN, Yang GZ. In: Yang GZ, Jiang TZ, editors. Combined CFD/MRI analysis of left ventricular flow, in medical imaging and augmented reality: Proceedings of Second International Workshop, MIAR 2004, Beijing, China, August 19-20. Berlin: Springer; 2004. pp. 229–236. 73. Mittal R Seo JH Vedula V Choi YJ Liu H Huang HH Computational modeling of cardiac hemodynamics: current status and future outlook J Comput Phys 2016 305 1065 1082 10.1016/j.jcp.2015.11.022 74. Cebral JR Meng H Counterpoint: realizing the clinical utility of computational fluid dynamics—closing the gap Am J Neuroradiol 2012 33 3 396 398 10.3174/ajnr.A2994 22282452

PMC005xxxxxx/PMC5000511.txt

==== Front Biomark ResBiomark ResBiomarker Research2050-7771BioMed Central London 7010.1186/s40364-016-0070-7Short ReportA novel three-way rearrangement involving ETV6 (12p13) and ABL1 (9q34) with an unknown partner on 3p25 resulting in a possible ETV6-ABL1 fusion in a patient with acute myeloid leukemia: a case report and a review of the literature Tirado Carlos A. carlostirado@hotmail.com 12Siangchin Ken Ksiangchin30@gmail.com 1Shabsovich David S. dshabsovich@gmail.com 1Sharifian Maryam msharifian@mednet.ucla.edu 1Schiller Gary gschiller@mednet.ucla.edu 31 Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095 USA 2 Department of Pathology and Laboratory Medicine, UCLA, West Medical Building, 1010 Veteran Ave, Second Floor room 2212F, Los Angeles, CA 90024 USA 3 Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095 USA 25 8 2016 25 8 2016 2016 4 1 1622 5 2016 2 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Acute myeloid leukemia (AML) is commonly characterized by several chromosomal abnormalities resulting in the formation of chimeric genes that play various roles in leukemogenesis. Translocations resulting in the ETV6-ABL1 fusion gene are rare in AML and other hematologic malignancies with only thirty-two previously reported cases in the literature, five of which were AML. Findings Herein, we report the case of a 73-year-old male with acute myeloid leukemia arising from MDS, negative for PDGFRA and PDGFRB, positive for bone marrow eosinophilia, rash, and marked fluid retention, which improved dramatically with imatinib therapy. Conventional cytogenetics revealed a t(3;9)(p25;q34), t(5;18)(q13;p11.2), and additional material of unknown origin at 12p11.2 in 2 out of 10 metaphases analyzed. Interphase FISH studies showed evidence of ETV6 (12p13) and ABL1 (9q34) rearrangements in 41.3 % and 5.7 % of the cells respectively. FISH studies on previously G-banded metaphases showed colocalization of ABL1 and ETV6 signals to the short arm of chromosome 3 at 3p25 suggesting a possible ETV6-ABL1 fusion. Subtelomeric metaphase FISH studies also showed the presence of a subtelomere 3p signal on the long arm of the derivative 9, and no subtelomere 3p signal on the derivative chromosome 12. Conclusions These findings suggest a complex rearrangement involving an insertion of ETV6 into 3p25 followed by a reciprocal translocation involving 3p25 and 9q34, resulting in a possible ETV6-ABL1 fusion. This case highlights the importance of FISH to characterize complex rearrangements in myeloid malignancies, particularly those resulting in clinically significant chimeric genes. Keywords CytogeneticsFISHAMLMDSETV6-ABL1Imatinibissue-copyright-statement© The Author(s) 2016 ==== Body Introduction The ETV6-ABL1 fusion gene is uncommon in hematological malignancies, including chronic myeloid leukemia (CML), acute myeloid leukemia (AML), and acute lymphoblastic leukemia (ALL), and has been reported in only thirty-two patients [1]. Six reported cases of hematological malignancies bearing ETV6-ABL1 in the context of complex rearrangements involving additional translocation partners have been reported, resulting in the translocation of the fusion gene to a third derivative chromosome [2–7]. The rarity of this event is due in part to the opposite transcriptional orientation of ETV6 and ABL1 relative to the centromere, which requires at least three separate chromosomal breaks to form a functional fusion gene [8]. The structure and function of the ETV6-ABL1 oncoprotein is very similar to that of the BCR-ABL1 protein with the ETV6 helix loop helix domain (HLH) deregulating the kinase activity of ABL1 leading to activation of a non-receptor tyrosine kinase that initiates downstream pathways affecting growth rate, cellular survival, and independence as well as transforming capacity [1, 3]. Because of the common functional activity with the BCR-ABL1 fusion protein, ETV6-ABL1 positive patients have been observed to respond to therapy with tyrosine kinase inhibitors, albeit at varying degrees and with high likelihood of relapse [1]. Herein, we present the case of a 73-year-old male diagnosed with acute myeloid leukemia. Cytogenetic analysis revealed a t(5;18) and a t(3;9), as well as additional material of unknown origin on the short arm of chromosome 12. Additional interphase and metaphase FISH studies revealed an insertion of ETV6 into 3p and translocation of ABL1 to the same locus on 3p, resulting in a possible ETV6-ABL1 fusion gene. The patient responded transiently to imatinib therapy, but eventually relapsed and expired. Case presentation The patient was a 73-year-old male with acute myeloid leukemia (AML) and hypereosinophilia, arising from antecedent myelodysplastic syndrome (MDS). He was initially found to have thrombocytopenia fifteen months prior to transfer during a pre-surgical workup for surgery to treat carpal tunnel syndrome. A bone marrow biopsy performed six months later had findings consistent with myelodysplastic syndrome with fewer than 5 % blasts in the bone marrow. He subsequently received three cycles of decitabine: the first dose was given in February 2015, the second dose was given in May 2015, and the third dose was given in July 2015. Eight months after bone marrow biopsy, he presented to an outside hospital with a fever and was found to have leukocytosis with circulating blasts, and a repeat bone marrow biopsy identified AML, possibly acute eosinophilic leukemia, with 20 % blasts identified in the bone marrow. Broad-spectrum antibiotics were started and the patient was transferred to UCLA for escalation of care. Shortly after transfer, he developed progressive renal failure requiring dialysis. Persistent blasts were treated with azacytidine, but he developed severe pancytopenia. In addition, eosinophilia, rash and marked fluid retention led his clinical team to consider therapy with imatinib, which promptly led to resolution of those findings. A follow-up bone marrow aspiration and biopsy one month later identified a hypercellular marrow showing marked eosinophilia with increased atypical immature forms, markedly reduced myeloid precursors other than the eosinophilic series including increased atypical immature eosinophils, reduced erythropoiesis and megakaryopoiesis, and increased blasts (10-11 % of the marrow elements). The overall marrow histology was consistent with acute myeloid leukemia possibly, acute myelocytic leukemia. Material and methods Conventional cytogenetics Chromosome analysis was performed using standard cytogenetic techniques on the bone marrow samples from this patient. The karyotypes were prepared using the Applied Imaging CytoVision software (Applied Imaging, Genetix, Santa Clara, CA) and described according to the ISCN 2013 nomenclature [9]. FISH Fluorescence in situ hybridization (FISH) was performed on interphase nuclei using the Vysis BCR/ABL1/ASS1 Tri-color DF FISH Probe Kit, Vysis LSI BCR/ABL Dual Color, Dual Fusion Probe Kit, and Vysis ETV6 Break Apart FISH Probe Kit from Abbott Molecular (Des Plaines, Illinois 60018) on interphase nuclei. Additionally, metaphase FISH was performed with the TotelVysion 3p, Spectrum Green, TotelVysion 3q Spectrum Orange probes, as well as the previously mentioned probes on previously G-banded metaphases. Results Conventional cytogenetics Conventional cytogenetics revealed a t(3;9)(p25;q34), t(5;18)(q13;p11.2), and additional material of unknown origin at 12p11.2 in 2 out of 10 metaphases analyzed. The remaining 8 metaphases were cytogenetically normal (Fig. 1).Fig. 1 G-banded karyotype showing a three-way rearrangement involving 3, 9, and 12 as well as reciprocal translocation between chromosomes 5 and 18 FISH Interphase FISH studies confirmed a rearrangement in 41.3 % (124/300) of nuclei examined involving ETV6 using the Vysis ETV6 Break Apart FISH Probe Kit and a rearrangement involving ABL1 in 5.7 % (17/300) nuclei examined using Vysis BCR/ABL1/ASS1 Tri-color DF FISH Probe Kit. These findings were described as (Figs. 2 and 3):nuc ish(ASS1x2,ABL1x3,BCRx2)[17/300] nuc ish(ETV6x2)(5'ETV6 sep 3'ETV6x1)[124/300] Fig. 2 Interphase FISH showing ABL1 rearrangement (evidenced by additional red ABL1 signal) Fig. 3 Interphase FISH showing ETV6 rearrangement (evidenced by split red and green ETV6 signals) Metaphase FISH studies using the same probes on previously G-banded metaphases showed colocalization of ABL1 and ETV6 signals to the short arm of chromosome 3, suggesting the presence of an ETV6-ABL1 fusion gene. Subtelomeric metaphase FISH studies also showed the presence of a subtelomere 3p signal on the derivative 9q, and no subtelomere 3p signals on the derivative 12. In light of conventional cytogenetic findings, the karyotype was conveyed as follows (Figs. 4, 5 and 6):46,XY,der(3)ins(3;12)(p25;p13p13)t(3;9)(p25;q34),t(5;18)(q13;p11.2),der(9)t(3;9),der(12)ins(3;12)(p25;p13p13)add(12)(p13)[2]/46,XY[8] Fig. 4 Metaphase FISH showing localization of 5’ ETV6 red signal to the short arm of the derivative chromosome 3. The derivative chromosome 12 only shows the 3’ ETV6 green signal Fig. 5 Metaphase FISH showing colocalization of ABL1 (red signal) and 5’ ETV6 (red signal) signals to the short arm of chromosome 3 using the BCR/ABL1/ASS1 Tri-color DF FISH Probe Kit and ETV6 Break Apart FISH Probe Kit Fig. 6 Metaphase FISH showing localization of subtelomere 3p signal on the derivative chromosome 9 and no subtelomeric 3 signals on the derivative chromosome 12 Discussion This case highlights the formation of a potential ETV6-ABL1 fusion gene as a result of a complex, three-way rearrangement. The conventional and molecular cytogenetic findings in this case suggest an insertion of ETV6 in the short arm of the derivative chromosome 3 followed by a reciprocal translocation involving the same derivative chromosome 3 and ABL1 (9q34), resulting in the potential fusion gene. The breakpoint on chromosome 3 at which the aforementioned rearrangements occurred - 3p25 - harbors ANKRD28 (3p25.1), which has been implicated in AML in the context of t(3;11)(p25;p15) involving NUP98 (11p15) [10]. In other studies, 3p25 was found to be the most frequently deleted chromosomal band on 3p in AML [11]. Given this information, the involvement of 3p25 in this three-way rearrangement may result in deregulation of particular target genes relevant to leukemogenesis in this region. The translocation that occurred concomitant to the three-way rearrangement - t(5;18)(q13;p11.2) - has not been observed in AML and has not been associated with any clinical or hematopathologic features. In total, there have been thirty-two reported cases of ETV6-ABL1 fusion gene in numerous hematologic malignancies including eleven cases of acute lymphoblastic leukemia, five cases of acute myeloid leukemia, and sixteen cases of myeloproliferative neoplasms (including CML) (Table 1). The rarity of this chromosomal rearrangement is thought to be due in part to the opposite transcriptional orientation of two genes relative to the centromere, which requires at least three break-and-join events for an in-frame fusion transcript to be formed. The rearrangement is often not detected using conventional cytogenetic techniques because of its cryptic nature due to the similar G-banding pattern of the distal long arm of chromosome 9 and the distal short arm of chromosome 12 [12]. Additionally, it has been observed that commercially available ABL1 FISH probes may not detect aberrations in the gene in this context, suggesting that the abnormality may remain undetected in a number of cases. In interphase cells, for example, the resulting ABL1 signal can be disproportionately small and can potentially be considered as noise and disregarded [1]. Thus, the rarity of the ETV6-ABL1 fusion is not only due to the multi-step mechanism required for its formation, but also because of technological limitations of FISH probes and molecular cytogenetic analysis.Table 1 Reported cases of ETV6-ABL1 fusion in acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), and myeloproliferative neoplasm (MPN), including chronic myelogenous leukemia (CML) Reference Age/Sex Karyotype FISH Transcript Acute lymphoblastic leukemia (ALL)  [23] 22 mo/F N/A N/A Type A  [24] 4 yo/M 47,XXYc,del(6)(q15q23)[35]/47,XXYc[7] Intact ETV6 (5’ and 3’) on derivative 9 Type A and B  [25] 30 yo/M 45,XY,der(1)t(1;9)(q41;q?),der(9)t(9;13)(q?;q12.3),del(9p21.1 ~ p23),-13,der(16)t(16;22)(p13.3;q11.2) ABL1 signal on apparently normal chromosome 12 Type A and B  [26] 8 yo/F N/A N/A Type A and B  [7] 8 yo/M 46,XY, der(1)inv(1) (p11p34.2)t(1;9)(p11;p21)del(1)(q41),der(9)t(9;12) (q34.3;p13.3),der(9)t(1;9)(p11;p21),der(12)t(1;9;12) (q41?;q34.3;p13.3)[14]/46,XY)[5] Normal signal patterns Type A and B  [7] 5 yo/M 46,XY[20] Normal signal patterns Type A and B  [7] 33 yo/F 46,XX,t(8;9;12)(p12;q34;p13)[22] ABL1 signal on 12p Type A and B  [13] 25 yo/F 46,XX,del(9)(p22),der(10)t(9;10)(q22; p15)[12]/46,XX[8] N/A Type A and B  [27] 58 yo/M 46,XY,t(9;12)(q34;p13)[2]/45,XY, −2,−14,+17[2]/46,XY[16] N/A Type A and B  [27] 49 yo/F 46,XY,t(9;12)(q34;p13)[10] N/A Type A and B  [12] 30 yo/F 47,XX,+5[19]/46,XX[1] Extra ETV6 and ABL1 signals in interphase nuclei Type A and B Acute myeloid leukemia (AML)  [3] 81 yo/M t(9;12;14)(q34;p13;q22) in the context of complex karyotype ETV6 signal on derivative 14 with concomitant deletion of other ETV6 allele Type B  [4] 29 yo/F 46,XY,t(8;12)(p21;p13)[15] 5’ ETV6 and ABL1 signals on derivative 8 Type A  [4] 48 yo/F 46,XY,t(9;12)(q34;p13)[18/20]/51,XY,+8,+9,t(9;12)(q34;p13),+12,+14,+17[2] 5’ ETV6 signal on derivative 9 Type B  [14] 38 yo/M 49,XY,+11,t(9;12)(q34;p1?), +der(12)t(9;12),+19,der(22)t(1;22)(q21;q11) ETV6-ABL1 fusion signals on 2 homologues of chromosome 12 Type A and B  [13] 52 yo/M 46,XY[20] ABL1 signal on apparently normal chromosome 12 Type B Myeloproliferative neoplasm (MPN), including chronic myeloid leukemia (CML)  [28] 49 yo/M N/A N/A Type B  [2] 32 yo/M t(12;14)(p12;q11-13)[24]/46,XY[1] 5’ ETV6 on apparently normal chromosome 9 Type B  [24] 59 yo/M 46,XY,del(6)(p21),?t(9;12)(q34;p12)[16] 5’ ETV6 on derivative 9q Type A and B  [29] 44 yo/F 46,XX,t(9;12)(q34;p13)[16]/46,XX[4] 5’ ETV6 on derivative 9q N/A  [30] 53 yo/M 46,XY[20] Normal signal patterns Type A and B  [20] 36 yo/M 45,XY,-7,t(9;12)(q34;q13)[2]/45,idem,t(12;13)(p12;q13)[10]/46,XY[13] ABL1 signal on derivative 12 Type A  [6] 72 yo/M 46,XY,t(12;17) (p11.2;p11.2) ABL1 and ETV6 signals on derivative 17 Type B  [31] 65 yo/F 46,XX,t(5;9)(q13;q34) 3’ ABL1 on 12p Type B  [32] 57 yo/M 46,XY 3’ ABL1 on 12p N/A  [18] 24 yo/F 46,XX ETV6 signal on apparently normal chromosome 9 Type A and B  [33] 61 yo/F 46,XX,add(9)(q34) ETV6 signal on derivative chromosome 9 N/A  [21] 79 yo/M 46,XY ABL1 signal on apparently normal chromosome 12 N/A  [22] 36 yo/M 46,XY,t(9;12)(q34;p13) Extra ABL1 signal (interphase FISH) Type B  [1] 46/F 46,XY,t(9;12)(q34;p13)[10] Extra ETV6 and ABL1 signals (interphase FISH) Type B  [5] N/A Complex rearrangement involving chromosomes 6, 9, and 12 Suggestive of ETV6-ABL1 fusion N/A  [34] 31 yo/M 46,XY,der(9)t(9;12)(q34;p13), del(12)(p13)[1] ETV6 signal on derivative 9 Type A and B Age/sex of patient, karyotype, salient FISH findings, and type of ETV6-ABL1 fusion transcript detected are provided To date, five cases of AML bearing a possible ETV6-ABL1 fusion have been reported (Table 1). Two of the cases were designated M1, two were M6, and one was not reported. One of the cases showed a straightforward t(9;12)(q34;p13) with concurrent FISH studies showing the 3’ ABL1 signal on the 12p, albeit in the context of a complex karyotype [4]. Two of the cases showed rearrangements involving a third chromosome - Golub et al. reported a case of AML (M6) with a t(9;12;14)(q34;p13;q22) without additional FISH studies, and La Starza et al. reported a case of AML (M1) with a t(8;12)(p21;p13) that showed colocalization of 5’ ETV6 and 3’ ABL1 signals on 8p21 by FISH [3, 4]. The two remaining cases showed normal karyotypes by conventional cytogenetics, but showed 3’ ABL1 signals on 12p [13, 14]. Among all of these cases, reported secondary abnormalities observed included gains of chromosomes 8, 9, 11, 12, 14, 17, and 19, as well as a t(1;22) [4, 14]. The ETV6-ABL1 fusion includes a helix loop helix (HLH) domain of ETV6 and tyrosine kinase domain of ABL1, and each domain is necessary for constitutive phosphorylation to occur [4]. Millon et al. found that mice transplanted with ETV6-ABL1-positive hematopoietic stem cells developed CML-like myeloproliferative disease, and that the TEL pointed homology oligomerization domain was essential to ETV6-ABL1-driven leukemogenesis [15]. It is well known that the ABL1 kinase has altered catalytic specificity in human leukemia. Co-immunoprecipitation studies show that the ETV6-ABL1 fusion protein tends to form complexes with CrkL in Ba/F3 cells, and this interaction phosphorylates CrkL and possibly CrkII [16]. However, it is known that the in vitro studies tend to have a wider range of substrates than the cellular forms [16]. Further analysis of Crk and CrkL adaptor proteins show that they play an essential role in integrating signals from a wide variety of sources such as apoptotic cells, extracellular matrix molecules, and growth factors, and there is mounting evidence to indicate that these proteins are associated with human diseases including susceptibility to pathogens and cancer [17]. ETV6 along with five other genes, BCR, ZMIZ, EML, and Nup21 form chimeric transcripts with ABL1. There must be a joining of the 3’ sequence of ABL1 with the 5’ end of the partner genes, and most of these genes are associated with a wide spectrum hematologic malignancies. Despite this heterogeneity, there is likely a common pluripotent stem cell that gives rise to similar transduction pathways and transforming activity [1]. Due to diagnostic, prognostic, and treatment-related implications, these cases further underscore the use of FISH along with routine chromosome analysis to properly characterize rare, albeit clinically significant fusion genes. Eosinophilia is a recurrent morphologic finding in ETV6-ABL1-positive myeloid malignancies [4]. Of the five known AML ETV6-ABL1 positive cases, three out of the five were reported to have an increased abnormal eosinophil count, consistent with the findings in the present case. Another finding common to most of the patients was leukocytosis and out of those three cases, two had both leukocytosis and eosinophilia [3, 4, 13, 14]. Each patient was treated with chemotherapy including, cytosine-arabinoside, idarubicin, etoposide, mitoxantrone, and cytarabine. The two patients treated with imatinib responded transiently with resolved fluid retention, eosinophilia, and leukocytosis; however, full remission was not achieved [14]. There was only one patient who achieved full cytogenetic and hematological remission 20 months after undergoing allogeneic hematopoietic stem cell transplantation, which suggests its effectiveness in the treatment of ETV6-ABL1-positive AML patients with eosinophilia and leukocytosis [4]. Although there is limited information about the pathogenesis of myeloid neoplasms positive for ETV6-ABL1, chronic myeloid leukemia (CML) positive for BCR-ABL1 has been well studied and the molecular mechanisms of leukemogenesis and courses of clinical management are established. Tyrosine kinase inhibitors (TKI) such as imatinib are effective agents for inhibiting the constitutively activated BCR-ABL1 tyrosine kinase in CML [18]. Similarly, ETV6-ABL1 is also known to constitutively activate the ABL1 tyrosine kinase, leading to cell cycle deregulation and leukemogenesis [19]. Due to the similar molecular pathogenesis of BCR-ABL1 and ETV6-ABL1 driven leukemogenesis, TKIs have also been considered in the treatment of patients bearing the ETV6-ABL1 fusion. Six out of eleven CML patients positive for ETV6-ABL1 reported in the literature were treated with imatinib: three patients showed a transient favorable response followed by relapse, one patient showed significantly decreased levels of leukemic clones, and two patients treated with 400 mg/day during the chronic phase achieved complete remission [1, 6, 18, 20–22]. Of the three that relapsed, Gancheva et al. reported a case in which the patient was administered an additional TKI, nilotinib, and the patient was able to sustain a positive response following the relapse [1]. Perna et al. did further analysis on another patient who achieved complete remission post-treatment which showed that the ETV6-ABL1 transcript became undetectable, the white blood count normalized, and expression of C-MYC, ID1, BCL-XL, and NUP-98 had decreased significantly [22]. All in all, the molecular targets of ETV6-ABL1 and BCR-ABL1 have significant overlaps that warrant further investigation to elucidate the effectiveness of TKIs on ETV6-ABL1 positive hematologic malignancies. All in all, this is the sixth reported case of AML bearing the ETV6-ABL1 fusion gene and provides additional insight into the pathogenesis of this subset of malignancies. It is particularly important to utilize complimentary cytogenetic methodologies - namely conventional cytogenetics and FISH - in order to elucidate cryptic abnormalities, which occur more frequently in this context, and to properly characterize karyotypic changes. Additionally, screening using RT-PCR as well as other methodologies has proven useful when cytogenetic analysis is unavailable or yields negative results and in the context of broad molecular screening to identify previously unreported cases. Finally, the consideration of tyrosine kinase inhibitors, particularly second-generation ones, in the treatment of ETV6-ABL1-positive hematological malignancies has shown varying responses, and further investigation of its utility and clinical efficacy is warranted. Abbreviations ALL, acute lymphoblastic leukemia; AML, acute myeloid leukemia; CML, chronic myelogenous leukemia; FISH, fluorescence in situ hybridization; HLH, helix loop helix; MDS, myelodysplastic syndrome; MPD, myeloproliferative disorder; RT-PCR, reverse transcriptase-polymerase chain reaction; TKI, tyrosine kinase inhibitor Acknowledgements Thank you to the UCLA Clinical Cytogenetics Laboratory. Funding This work was supported by the UCLA Clinical and Molecular Cytogenetics Laboratory in the UCLA Department of Pathology and Laboratory Medicine. Availability of data and materials All data utilized to complete this manuscript is provided in the manuscript – there are no supporting materials. Authors’ contributions CAT, KS, and DSS contributed equally and led drafting, conducted survey of relevant literature, and edited and revised all drafts. GS and MS provided clinical presentation/findings, revised the manuscript, and provided numerous comments. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Written informed consent was obtained from the patient. Ethics approval and consent to participate The experiments with human samples included in this work were performed in accordance with the Declaration of Helsinki. No ethics committee approval was required for these experiments. Written informed consent was obtained from the patient. ==== Refs References 1. Gancheva K Virchis A Howard-Reeves J Cross NC Brazma D Grace C Kotzampaltiris P Partheniou F Nacheva E Myeloproliferative Neoplasm with ETV6-ABL1 Fusion: A Case Report and Literature Review Mol Cytogenet 2013 6 1 39 10.1186/1755-8166-6-39 24053143 2. Andreasson P Johansson B Carlsson M Jarlsfelt I Fioretos T Mitelman F Höglund M BCR/ABL-negative chronic myeloid leukemia with ETV6/ABL fusion Genes Chromosomes Cancer 1997 20 3 299 304 10.1002/(SICI)1098-2264(199711)20:3<299::AID-GCC11>3.0.CO;2-K 9365838 3. Golub TR Goga A Barker GF Afar DE Mclaughlin J Bohlander SK Rowley JD Witte ON Gilliland DG Oligomerization of the ABL Tyrosine Kinase by the Ets Protein TEL in Human Leukemia Mol Cell Biol 1996 16 8 4107 116 10.1128/MCB.16.8.4107 8754809 4. La Starza R Trubia M Testoni N Ottaviani E Belloni E Crescenzi B Martelli M Flandrin G Pelicci PG Mecucci C Clonal eosinophils are a morphologic hallmark of ETV6/ABL1 positive acute myeloid leukemia Haematologica 2002 87 8 789 94 12161353 5. Pelly T, Harvey Y, Brookwell R, Wordsworth H, Keng TB. A case report of an ETV6-ABL1 [t(6;9;12)] positive myeloproliferative neoplasm. Pathology. 2012;45(1):S95. 6. Tirado CA Sebastian S Moore JO Gong JZ Goodman BK Molecular and Cytogenetic Characterization of a Novel Rearrangement Involving Chromosomes 9, 12, and 17 Resulting in ETV6 (TEL) and ABL Fusion Cancer Genet Cytogenet 2005 157 1 74 77 10.1016/j.cancergencyto.2004.06.001 15676152 7. Zuna J Zaliova M Muzikova K Meyer C Lizcova L Zemanova Z Brezinova J Votava F Marschalek R Stary J Trka J Acute leukemias with ETV6/ABL1 (TEL/ABL) fusion: poor prognosis and prenatal origin Genes Chromosomes Cancer 2010 49 10 873 84 10.1002/gcc.20796 20589932 8. De Braekeleer E Douet-Guilbert N Rowe D Bown N Morel F Berthou C Férec C De Braekeleer M ABL1 fusion genes in hematological malignancies: a review Eur J Haematol 2011 86 5 361 71 10.1111/j.1600-0609.2011.01586.x 21435002 9. Shaffer LG McGowan-Jordan J Schmid M An International System for Human Cytogenetic Nomenclature 2013 Basel International Standing Committee on Human Cytogenetic Nomenclature, Karger 10. Ishikawa M Yagasaki F Okamura D Maeda T Sugahara Y Jinnai I Bessho M A novel gene, ANKRD28 on 3p25, is fused with NUP98 on 11p15 in a cryptic 3-way translocation of t(3;5;11)(p25;q35;p15) in an adult patient with myelodysplastic syndrome/acute myelogenous leukemia Int J Hematol 2007 86 3 238 45 10.1007/BF03006927 17988990 11. Johansson B Billström R Kristoffersson U Åkerman M Garwicz S Ahlgren T Malm C Mitelman F Deletion of Chromosome Arm 3p in Hematologic Malignancies Leukemia 1997 11 8 1207 213 10.1038/sj.leu.2400718 9264371 12. Song JS Shin SY Lee ST Kim HJ Kim SH A Cryptic ETV6/ABL1 Rearrangement Represents a Unique Fluorescence In Situ Hybridization Signal Pattern in a Patient with B Acute Lymphoblastic Leukemia Ann Lab Med 2014 34 6 475 10.3343/alm.2014.34.6.475 25368826 13. Park J Kim M Lim J Kim Y Han K Kim JS Lee S Kim HJ Min WS Variant of ETV6/ABL1 Gene Is Associated with Leukemia Phenotype Acta Haematologica Acta Haematol 2013 129 2 78 82 10.1159/000342490 23171811 14. O'Brien SG Vieira SA Connors S Bown N Chang J Capdeville R Melo JV Transient response to imatinib mesylate (STI571) in a patient with the ETV6-ABL t(9;12) translocation Blood 2002 99 9 3465 7 10.1182/blood.V99.9.3465 11964320 15. Million RP Aster J Gilliland DG Van Etten RA The Tel-Abl (ETV6-Abl) tyrosine kinase, product of complex (9;12) translocations in human leukemia, induces distinct myeloproliferative disease in mice Blood 2002 99 12 4568 77 10.1182/blood-2001-12-0244 12036890 16. Voss J Posern G Hannemann JR Wiedemann LM Turhan AG Poirel H Bernard OA Adermann K Kardinal C Feller SM The Leukaemic Oncoproteins Bcr-Abl and Tel-Abl (ETV6/Abl) Have Altered Substrate Preferences and Activate Similar Intracellular Signalling Pathways Oncogene 2000 19 13 1684 690 10.1038/sj.onc.1203467 10763825 17. Birge RB Kalodimos C Inagaki F Tanaka S Crk and CrkL Adaptor Proteins: Networks for Physiological and Pathological Signaling Cell Commun Signal 2009 7 1 13 10.1186/1478-811X-7-13 19426560 18. Kawamata N Dashti A Lu D Miller B Koeffler HP Schreck R Moore S Ogawa S Chronic Phase of ETV6-ABL1 Positive CML Responds to Imatinib Genes Chromosomes Cancer 2008 47 10 919 21 10.1002/gcc.20593 18615681 19. Greuber EK Smith-Pearson P Wang J Pendergast AM Role of ABL family kinases in cancer: from leukaemia to solid tumours Nat Rev Cancer 2013 13 8 559 71 10.1038/nrc3563 23842646 20. Barbouti A Ahlgren T Johansson B Höglund M Lassen C Turesson I Mitelman F Fioretos T Clinical and Genetic Studies of ETV6/ABL1-positive Chronic Myeloid Leukaemia in Blast Crisis Treated with Imatinib Mesylate Br J Haematol 2003 122 1 85 93 10.1046/j.1365-2141.2003.04391.x 12823349 21. Kelly JC Shahbazi N Scheerle J Jahn J Suchen S Christacos NC Mowrey PN Witt MH Hostetter A Meloni-Ehrig AM Insertion (12;9)(p13;q34q34): A Cryptic Rearrangement Involving ABL1/ETV6 Fusion in a Patient with Philadelphia-negative Chronic Myeloid Leukemia Cancer Genet Cytogenet 2009 192 1 36 39 10.1016/j.cancergencyto.2009.02.012 19480935 22. Perna F Abdel-Wahab O Levine RL Jhanwar SC Imada K Nimer SD ETV6-ABL1-positive "chronic Myeloid Leukemia": Clinical and Molecular Response to Tyrosine Kinase Inhibition Haematologica 2010 96 2 342 43 10.3324/haematol.2010.036673 21193423 23. Papadopoulos P Ridge SA Boucher CA Stocking C Wiedemann LM The novel activation of ABL by fusion to an ets-related gene, TEL Cancer Res 1995 55 1 34 8 7805037 24. Van Limbergen H Beverloo HB van Drunen E Janssens A Hählen K Poppe B Van Roy N Marynen P De Paepe A Slater R Speleman F Molecular cytogenetic and clinical findings in ETV6/ABL1-positive leukemia Genes Chromosomes Cancer 2001 30 3 274 82 10.1002/1098-2264(2000)9999:9999<1::AID-GCC1089>3.0.CO;2-1 11170285 25. Baeumler J Szuhai K Falkenburg JH van Schie ML Ottmann OG Nijmeijer BA Establishment and cytogenetic characterization of a human acute lymphoblastic leukemia cell line (ALL-VG) with ETV6/ABL1 rearrangement Cancer Genet Cytogenet 2008 185 1 37 42 10.1016/j.cancergencyto.2008.05.001 18656692 26. Malone A Langabeer S O'Marcaigh A Storey L Bacon CL Smith OP A doctor(s) dilemma: ETV6-ABL1 positive acute lymphoblastic leukaemia Br J Haematol 2010 151 1 101 2 10.1111/j.1365-2141.2010.08323.x 20618334 27. Zhou MH Gao L Jing Y Xu YY Ding Y Wang N Wang W Li MY Han XP Sun JZ Wang LL Yu L Detection of ETV6 gene rearrangements in adult acute lymphoblastic leukemia Ann Hematol 2012 91 8 1235 43 10.1007/s00277-012-1431-4 22373549 28. Brunel V Sainty D Carbuccia N Mazzicconacci M Fernandez F Simonetti J Gabert J Debreuil P Lafage-Pochitaloff M Birg F A TEL/ABL fusion gene on chromosome 12p13 in a case of Ph-. BCR- atypical CML Leukemia 1996 10 2003 29. Keung YK Beaty M Steward W Jackle B Pettnati M Chronic myelocytic leukemia with eosinophilia, t(9;12)(q34;p13), and ETV6-ABL1 gene rearrangement: case report and review of the literature Cancer Genet Cytogenet 2002 138 2 139 42 10.1016/S0165-4608(02)00609-X 12505259 30. Lin H Guo JQ Andreeff M Arlinghaus RB Detection of dual TEL-ABL transcripts and a Tel-Abl protein containing phosphotyrosine in a chronic myeloid leukemia patient Leukemia 2002 16 2 294 7 10.1038/sj.leu.2402353 11840298 31. Meyer-Monard S Mühlematter D Streit A Chase AJ Gratwohl A Cross NC Jotterand M Tichelli A Broad molecular screening of an unclassifiable myeloproliferative disorder reveals an unexpected ETV6/ABL1 fusion transcript Leukemia 2005 19 6 1096 9 10.1038/sj.leu.2403697 15789067 32. Mozziconacci MJ Sainty D Chabannon C A fifteen-year cytogenetic remission following interferon treatment in a patient with an indolent ETV6-ABL positive myeloproliferative syndrome Am J Hematol 2007 82 7 688 9 10.1002/ajh.20873 17366548 33. Nand R Bryke C Kroft SH Divgi A Bredeson C Atallah E Myeloproliferative disorder with eosinophilia and ETV6-ABL gene rearrangement: efficacy of second-generation tyrosine kinase inhibitors Leuk Res 2009 33 8 1144 6 10.1016/j.leukres.2009.03.011 19394693 34. Yamamoto K Yakushijin K Nakamachi Y Miyata Y Sanada Y Tanaka Y Okamura A Kawano S Hayashi Y Matsuoka H Minami H Extramedullary T-lymphoid blast crisis of an ETV6/ABL1-positive myeloproliferative neoplasm with t(9;12)(q34;p13) and t(7;14)(p13;q11.2) Ann Hematol 2014 93 8 1435 8 10.1007/s00277-013-1975-y 24318592

PMC005xxxxxx/PMC5000512.txt

==== Front J NeuroinflammationJ NeuroinflammationJournal of Neuroinflammation1742-2094BioMed Central London 68310.1186/s12974-016-0683-7ResearchType-1 angiotensin receptor signaling in central nervous system myeloid cells is pathogenic during fatal alphavirus encephalitis in mice Blakely Pennelope K. penneyblakely@gmail.com Huber Amanda K. hubera@med.umich.edu Irani David N. (734) 615-5635davidira@med.umich.edu Holtom-Garrett Program in Neuroimmunology, Department of Neurology, University of Michigan Medical School, Room 4007, A. Alfred Taubman Biomedical Sciences Research Building, 109 Zina Pitcher Place, Ann Arbor, MI 48109-2200 USA 25 8 2016 25 8 2016 2016 13 1 19615 2 2016 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Alphaviruses can cause fatal encephalitis in humans. Natural infections occur via the bite of infected mosquitos, but aerosol transmissibility makes some of these viruses potential bioterrorism agents. Central nervous system (CNS) host responses contribute to alphavirus pathogenesis in experimental models and are logical therapeutic targets. We investigated whether reactive oxygen species (ROS) generated by nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (Nox) activity within the CNS contributes to fatal alphavirus encephalitis in mice. Methods Infected animals were treated systemically with the angiotensin receptor-blocking drug, telmisartan, given its ability to cross the blood-brain barrier, selectively block type-1 angiotensin receptors (AT1R), and inhibit Nox-derived ROS production in vascular smooth muscle and other extraneural tissues. Clinical, virological, biochemical, and histopathological outcomes were followed over time. Results The importance of the angiotensin II (Ang II)/AT1R axis in disease pathogenesis was confirmed by demonstrating increased Ang II levels in the CNS following infection, enhanced disease survival when CNS Ang II production was suppressed, increased AT1R expression on microglia and tissue-infiltrating myeloid cells, and enhanced disease survival in AT1R-deficient mice compared to wild-type (WT) controls. Systemic administration of telmisartan protected WT mice from lethal encephalitis caused by two different alphaviruses in a dose-dependent manner without altering virus replication or exerting any anti-inflammatory effects in the CNS. Infection triggered up-regulation of multiple Nox subunits in the CNS, while drug treatment inhibited local Nox activity, ROS production, and oxidative neuronal damage. Telmisartan proved ineffective in Nox-deficient mice, demonstrating that this enzyme is its main target in this experimental setting. Conclusions Nox-derived ROS, likely arising from CNS myeloid cells triggered by AT1R signaling, are pathogenic during fatal alphavirus encephalitis in mice. Systemically administered telmisartan at non-hypotensive doses targets Nox activity in the CNS to exert a neuroprotective effect. Disruption of this pathway may have broader implications for the treatment of related infections as well as for other CNS diseases driven by oxidative injury. Electronic supplementary material The online version of this article (doi:10.1186/s12974-016-0683-7) contains supplementary material, which is available to authorized users. Keywords Angiotensin IIType-1 angiotensin II receptorsAngiotensin receptor blockersAlphavirusesViral encephalitisNoxOxidative injuryhttp://dx.doi.org/10.13039/100000060National Institute of Allergy and Infectious DiseasesAI057505Irani David N. issue-copyright-statement© The Author(s) 2016 ==== Body Background Alphaviruses cause acute and sometimes fatal encephalomyelitis in humans. Most infections are spread via infected mosquito vectors, although some can be transmitted as aerosols making them potential bioterrorism agents [1]. The intentional release of an alphavirus amidst a large population center is a public health concern because antiviral agents effective against these pathogens are not available. One alphavirus, neuroadapted Sindbis virus (NSV), causes fatal encephalomyelitis in mice and closely reproduces many features of neurotropic alphavirus infections in humans [2, 3]. Like other alphaviruses, NSV targets neurons of the brain and spinal cord without causing direct infection of glial cells [3, 4]. The fate of neurons then determines disease outcome [5]. Not only does NSV cause direct virus-induced neuronal cell death [5], but substantial bystander injury to uninfected neurons also occurs [6, 7]. This bystander injury suggests that host responses contribute to alphavirus pathogenesis [8, 9], and recent investigations show that therapies targeting innate immune responses in the central nervous system (CNS) can protect infected hosts without altering virus tropism, replication, or clearance [7, 10, 11]. Microglia and astrocytes are both implicated in this bystander injury [11–14], but the molecular pathways through which innate host responses lead to neuronal injury during CNS alphavirus infections remain incompletely understood. Among the numerous host responses known to promote neuronal injury in the CNS are reactive oxygen species (ROS) generated by activation of the nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (Nox) enzyme complex [15, 16]. Indeed, aberrant activation of Nox in microglial cells is now implicated in a variety of neurodegenerative disease models [17–20]. The contributions of Nox-derived ROS generated as part of the host response to CNS viral infection are less clear; on one hand, these ROS may directly damage virus particles or lower the permissiveness of cells for virus replication, while on the other, their generation as a part of the respiratory burst by innate immune cells can produce significant collateral tissue damage [21]. A growing body of histochemical data show that oxidative neuronal injury occurs with CNS viral infections [21], suggesting that blockade of Nox activation could have therapeutic benefits in these diseases. The vasoconstricting effects of angiotensin II (Ang II) on peripheral blood vessels occur via Nox-mediated production of superoxide anions by vascular smooth muscle cells [22, 23]. As a result, selective non-peptide antagonists of type-1 angiotensin II receptors (AT1R) that potently inhibit Nox activation have been developed as anti-hypertensive therapies for humans. More recently, several angiotensin II receptor blockers (ARB) have been shown to exert neuroprotective effects in animal disease models [24–27]. One ARB, telmisartan, is highly blood-brain barrier (BBB) penetrant and produces near complete and sustained blockade of AT1R without affecting type-2 angiotensin II receptor (AT2R) signaling [28]. Given the expanding use of ARB to suppress Nox-mediated ROS production in other non-vascular tissues [29], we considered telmisartan a useful reagent to test the hypothesis that Nox-mediated ROS production within the CNS is an important pathogenic event during experimental alphavirus encephalitis in mice. Our data show that systemically administered telmisartan blocks CNS Nox activity and ROS production induced by NSV infection, protects infected hosts, and suppresses oxidative neuronal damage. These findings suggest a broader potential applicability of ARB to target Nox activity in the setting of infectious, inflammatory, and even degenerative disorders of the human CNS. Methods Animals Inbred C57BL/6 mice, mice heterozygous for deficiencies of the individual Nox subunits, p47phox or gp91phox, both bred on a C57BL/6 background, mice expressing green fluorescent protein (GFP) in one allele of the CX3C chemokine receptor-1 (CX3CR1 or fractalkine receptor) bred on a C57BL/6 background (hereafter referred to as CX3CR1GFP/+ mice) and mice deficient in AT1R bred on a C57BL/6 background (hereafter referred to as AT1R knockout (KO) mice) were all obtained from Jackson Laboratories (Bar Harbor, ME). Double KO gp91phox/p47phox mice (hereafter referred to as gp91/p47 double knockout (DKO) mice) were generated de novo and bred on site. Animals were housed under specific pathogen-free, barrier facility conditions on a 10-h/14-h light/dark cycle with food and water available ad libitum. All animal procedures were completed using isoflurane anesthesia (Abbott Laboratories, Chicago, IL). All animal experiments, including those incorporating paralysis or death as study endpoints, were conducted in strict accordance with protocols approved by the University of Michigan Committee on Use and Care of Animals as well as with federal guidelines. Induction of NSV encephalomyelitis and NSV-related animal manipulations NSV viral stocks were grown and assayed for plaque formation on BHK-21 cells. Stock titers of 107 plaque-forming units (pfu)/ml were stored at −80 °C until use. To induce encephalomyelitis, mice were injected with 1000 pfu of NSV or NSV-GFP suspended in 20 μl of phosphate-buffered saline (PBS) directly into the right cerebral hemisphere. For those experiments where tissue samples were not being collected for ex vivo analyses, each infected animal was scored by a blinded examiner into one of the following groups: (1) normal or minimally affected, (2) mild paralysis (some weakness of one or both hind limbs), (3) moderate paralysis (weakness of one hind limb, paralysis of the other hind limb), (4) severe paralysis (complete paralysis of both hind limbs), or (5) moribund/dead. Moribund mice were euthanized immediately and were considered to have died the following day for all statistical comparisons, as prior studies demonstrated that all animals reaching this disease stage never survived more than another 24 h [7, 10, 13]. Animals also received intraperitoneal (i.p.) injections of telmisartan (Sigma-Aldrich, St. Louis, MO) or a vehicle control twice daily in a volume of 200 μl of 0.9 % sodium chloride solution, pH 9.0. Such an alkalinized diluent was both necessary for and capable of maintaining full drug solubility. Doses up to 100 mg/kg/day were administered starting 12 h after viral challenge. Other mice received twice daily i.p. injections of captopril (10 mg/kg/day, Sigma-Aldrich) suspended in 200 μl of PBS or a PBS vehicle control. All of these experiments were conducted in strict accordance with protocol # PRO00005049 approved by the University of Michigan Committee on Use and Care of Animals. At predetermined disease stages, some mice were euthanized via transcardiac perfusion with PBS under anesthesia. For animals where in vivo labeling of ROS production was desired, mice were first injected i.p. with 50 mg/kg dihydroethidium (DHE, Sigma-Aldrich) 1 h prior to perfusion. For all tissue enzyme immunoassays (EIA), bead-based multi-analyte cytokine and chemokine assays, Western blots, flow cytometry-based sorting of immune cell subsets, virus titration assays, and biochemical assays of tissue superoxide production, brains and spinal cords were quickly dissected for further processing. For immunohistochemical and immunofluorescence studies, animals were perfused a second time with chilled PBS containing 4 % paraformaldehyde (PFA) before dissection. Induction of western equine encephalitis virus encephalitis The Cba 87 strain of western equine encephalitis virus (WEEV) was generated from the complementary DNA (cDNA) clone pWE2000 as previously described [30, 31]. A low passage stock of infectious virus generated in Vero cells was expanded twice in C6/36 mosquito cells to produce viral stocks containing 107 pfu/ml. All virus aliquots were stored at −80 °C until use. Experiments using infectious WEEV were conducted in an animal-compatible, federally certified biosafety level 3 (BSL3) containment facility in strict accordance with standard operating procedures and protocols approved by both the University of Michigan Institutional Biosafety Committee and the University of Michigan Committee on Use and Care of Animals (animal protocol # PRO00005204). Mice were housed in our animal BSL3 facility on a 10-h/14-h light/dark cycle with food and water available ad libitum. For WEEV infections, recipient mice were inoculated subcutaneously with 104 pfu of Cba 87 suspended in a total volume of 50 μl of PBS. Cohorts of infected mice were weighed and scored daily using a clinical rating scale previously established for WEEV infection: 0, normal; 1, slightly ruffled fur, no visible signs of infection; 2, very ruffled fur, definite signs of infection with reduced cage activity; 3, very ruffled fur, hunched posture, reduced mobility; 4, very ruffled fur, hunched posture, little to no mobility, rapid breathing (moribund); and 5, dead [32]. All animals also received i.p. injections of telmisartan (Sigma-Aldrich) or a vehicle control twice daily in a total volume of 200 μl of 0.9 % sodium chloride solution, pH 9.0, at a dose of 100 mg/kg/day starting 12 h after viral challenge. Animals reaching a disease score of 4 were euthanized immediately and were considered to have died the following day for all statistical comparisons, as prior disease progression studies demonstrated that moribund mice never survived more than an additional 24 h [32]. Measurement of Ang II levels and cytokine and chemokine concentrations in tissue extracts Control and NSV-infected mice were perfused with PBS, and brains and spinal cords extracted, snap-frozen on dry ice, and stored at −80 °C until use. Thawed tissues were minced and homogenized in 0.5 ml of PBS containing a protease inhibitor cocktail (Roche Life Science, Indianapolis, IN). Homogenates were centrifuged to pellet all remaining tissue debris. The total protein content in each tissue supernatant was measured using the Pierce Coomassie Protein Assay Reagent (Thermo Fisher Scientific, Rockford, IL). Ang II levels were measured in each sample using a commercially available EIA kit (Cayman Chemical Company, Ann Arbor, MI). The results presented reflect pg Ang II/mg of total protein extracted from tissue of four to six animals at each time point examined. The Milliplex mouse cytokine detection system (EMD Millipore, Billerica, MA) was used according to the manufacturer’s instructions to quantify cytokine and chemokine levels directly in tissue extracts. Plates were read on a Luminex 200 instrument (EMD Millipore), and cytokine and chemokine concentrations (pg/ml) calculated by the BioPlex manager software (Bio-Rad, Hercules, CA) using standard curves. Results presented reflect the mean ± standard error of the mean (SEM) of cytokine or chemokine quantities per milliliter of plasma or per milligram of total extracted tissue protein from five animals at each time point. The lower limit of detection for these assays was 1.6 pg/ml. Tissue Western blots Brains and spinal cords were homogenized in a tissue lysis buffer (10 mM Tris, 1 % sodium dodecyl sulfate (SDS), 1 mM sodium orthovandate, pH 7.6) supplemented with a commercial protease inhibitor cocktail (Roche Life Science). Lysates were centrifuged to remove undigested tissue debris and the total protein concentration of each supernatant was determined using the Pierce Coomassie Protein Assay Reagent (Thermo Fisher Scientific). Samples were boiled in 4× protein sample buffer and 20 μg/well run on SDS-polyacrylamide gels. Proteins were transferred to PVDF membranes and blocked overnight at 4 °C in a 5 % non-fat skim milk solution in Tris-buffered saline (TBS) containing 0.5 % Tween 20. Membranes were then incubated with one of the following primary antibodies: polyclonal goat anti-AT1R (1:500, Santa Cruz Biotechnology, Santa Cruz, CA), polyclonal rabbit anti-gp91 (1:1000, Abcam, Cambridge, MA), or polyclonal rabbit anti-p47 (1:500, EMD Millipore) for 1 h at room temperature. All primary antibodies were raised against synthetic peptides derived from the corresponding human gene sequence, and both cross-reactivity and specificity with the corresponding mouse protein previously established [33–35]. Following five washes, membranes were then incubated with either rabbit anti-goat horseradish peroxidase (HRP)-conjugated secondary antibody or goat anti-rabbit HRP-conjugated secondary antibody (both used at 1:10,000, EMD Millipore) for 1 h at room temperature. Membranes were washed five times again, and the HRP signal detected using ECL Western blotting detection reagent (GE Healthcare Life Sciences, Pittsburgh, PA) on X-ray film. Membranes were then stripped using Western blot stripping buffer (Thermo Fisher Scientific) and relabeled with β-actin loading control antibody (1:5000, Thermo Fisher Scientific) using the same steps described above. Once all the β-actin signals were obtained, all band densities were quantified using the ImageJ software package (NIH, Bethesda, MD). The band density for each protein was first normalized to the β-actin signal detected in the same lane, and the mean of the uninfected samples were then set to an arbitrary expression level of 1.0. Relative protein expression across the full course of acute NSV infection was determined compared to uninfected controls, and relative expression in five samples at each disease stage was analyzed for statistical significance. Tissue staining and imaging procedures Unless otherwise specified, all tissues used for histological studies were post-fixed for 6 h in 4 % PFA in PBS, cryopreserved overnight in 30 % sucrose in PBS, and snap-frozen in CRYO-OCT Compound (Thermo Fisher Scientific). Eight micron frozen sections were cut, collected on SuperFrost Plus slides (Thermo Fisher Scientific) and stored at −20 °C until staining. Fluorescence Sections of NSV-GFP-infected tissues prelabeled with DHE were imaged without further manipulation. Other sections were brought to room temperature, washed in PBS, and boiled for 20 min in 0.01 M citric acid in PBS (pH 6.0) to unmask tissue antigens. Tissue sections were then permeabilized for 5 min in 0.1 % Triton X-100 in PBS and blocked for 30 min in 5 % normal goat serum (NGS). Sections from NSV-infected CX3CR1GFP/+ mice were incubated for 1 h at room temperature with polyclonal rabbit anti-AT1R (1:100, Santa Cruz Biotechnology), washed three times in PBS, incubated with rhodamine-conjugated goat anti-rabbit secondary antibody (1:200, eBioscience, San Diego, CA) for 1 h at room temperature, and washed again prior to coverslipping with Fluoromount G (eBiosciences) and imaging. Neuronal damage in the brain was assessed in sections prepared through the hippocampal formations of naïve and NSV-infected C57BL/6 mice. Before staining, each section was incubated in 0.1 % Triton X-100 for 15 min to expose intracellular antigens. Slides were then stained in 0.0001 % Fluoro-Jade C compound (EMD Millipore) in 1 % acetic acid for 10 min. After further washing, slides were dried, counterstained with hematoxylin, dehydrated in xylene, and coverslipped using VectaMount permanent mounting media (Vector Laboratories, Burlingame, CA). Fluorescence was imaged using a Nikon Ti-U inverted microscope equipped with a CoolSNAP EZ CCD digital camera (Photometrics, Tucson, AZ) supported by the NIS-Elements Basic Research acquisition and analysis software package (Nikon Instruments Inc., Melville, NY). To quantify neuronal damage, Fluoro-Jade C-positive cells (degenerating neurons) and hematoxylin-positive cells (all neurons) were counted on duplicate slides from each hippocampus of triplicate mice for each experimental condition to calculate the proportion of Fluoro-Jade-positive neurons. Immunoperoxidase staining For immunoperoxidase staining, permeabilized sections were first treated with 1 % hydrogen peroxide in methanol to block endogenous tissue peroxidase, and then blocked in 2 % NGS. Slides were washed, incubated with polyclonal rabbit anti-4-hydroxynonenal (4-HNE, 1:250, Abcam) for 1 h at room temperature, washed again, and then treated with biotin-labeled goat anti-rabbit IgG (Vector Laboratories) at a 1:200 dilution for another hour at room temperature. These steps were followed by sequential incubations with avidin-DH-biotin complex (Vector Laboratories) and then 0.5 mg/ml 3,3′-diaminobenzidine (Sigma-Aldrich) in PBS containing 0.01 % hydrogen peroxide. All slides were counterstained with hematoxylin and mounted with coverslips using Permount mounting medium (Thermo Fisher Scientific) for light microscopy. Slides were imaged using a Nikon Ti-U inverted microscope equipped with a Nikon DS-Fi-1 digital camera and supported by the NIS-Elements Basic Research acquisition and analysis software package (Nikon Instruments Inc.). Silver staining Neuronal damage in the spinal cord during NSV infection was assessed by quantifying the axonal processes of lumbar ventral spinal nerve roots as these all originate from motor neurons in the lumbar spinal cord that innervate the hind limb musculature. These assays were conducted according to our published methods [36]. In brief, sections of the entire lumbar spinal column at the L4–L5 level were first decalcified (Immunocal, Decal Corporation, Tallman, NY) and embedded in paraffin. Sections were then stained using a modified Bielchowsky silver staining method to label neurofilament proteins in each nerve axon, as described [36]. Slides were imaged using a Nikon Ti-U inverted microscope equipped with a Nikon DS-Fi-1 digital camera and supported by the NIS-Elements Basic Research acquisition and analysis software package (Nikon Instruments Inc.). Axonal density (the number of intact axons per cross-sectional area of each nerve root) was determined for the right and left L4 and L5 ventral nerve roots from a minimum of four animals in each experimental group. Flow cytometry-based analysis and separation of CNS myeloid cell subsets Six days after NSV challenge, ten anesthetized C57BL/6 mice underwent transcardiac perfusion with chilled PBS. A parallel cohort of five mice were infected and also treated with 100 mg/kg/day of telmisartan for 6 days followed by transcardiac perfusion. Brains and spinal cords were collected from each mouse and homogenized into small fragments. Tissue was suspended in Hank’s balanced salt solution (HBSS) containing 28 U/ml DNase (Sigma-Aldrich) for 30 min at 37 °C. Infiltrating mononuclear cells (MNC) were isolated from tissue digests of five telmisartan-treated and five untreated mice by centrifugation over 30 %/70 % Percoll gradients (GE Healthcare Life Sciences), counted, washed extensively with PBS containing 2 % fetal bovine serum (FBS), and stained with fluorescently conjugated anti-CD45, anti-CD11b, anti-Ly6C, anti-Ly6G, and anti-CD11c antibodies for myeloid cell phenotyping, as well as anti-CD40 and anti-CD86 to assess myeloid cell activation (all from eBiosciences). The following staining patterns defined each myeloid cell subset: CD45low/CD11b + (microglia), CD45high/CD11b+/CD11c-/Ly6C+/Ly6G- (macrophages), CD45high/CD11b+/CD11c-/Ly6C-/Ly6G- (monocytes), CD45high/CD11b+/CD11c-/Ly6C-/Ly6G+ (neutrophils), and CD45high/CD11b+/CD11c + (dendritic cells). In the remaining five NSV-infected mice, CNS mononuclear cells were pooled and the endogenous and recruited myeloid cell subsets were physically separated from one another into CD45low/CD11b + (microglia) and CD45high/CD11b + (all infiltrating myeloid cells) populations using a BD FACSAria high-speed cell sorter (BD Biosciences, San Jose, CA). Cells were stored in PrepProtect RNA stabilization solution (Miltenyi Biotec, Auburn, CA) at −20 °C until RNA isolation could be performed. Quantitative PCR determination of agtr1a expression in CNS myeloid cell subsets Flow sorted cell subsets were thawed, pelleted, and carefully removed from the PrepProtect solution. Total RNA was isolated from each cell population and cDNA generated using a high-capacity cDNA reverse transcription kit according to the manufacturer’s instructions (Thermo Fisher Scientific). Quantitative PCR (qPCR) was performed to measure agtr1a and β-actin mRNA transcripts using the MyiQ Single Color Real-Time PCR Detection System and a Bio-Rad iQ5 cycler (Bio-Rad, Hercules, CA). TaqMan® gene expression assays for both agtr1a and β-actin were obtained from Thermo Fisher Scientific. Levels of agtr1a transcripts were calculated relative to β-actin using the following formula: 2^[Ct (β-actin) − Ct (target gene)] × 1000, where Ct is the threshold cycle at which the fluorescent signal became significantly higher than background. Results presented reflect relative agtr1a mRNA expression in each cell population done in three experimental replicates. Tissue viral titrations To measure the amount of infectious virus present in CNS tissues, animals were perfused extensively with chilled PBS and brains and spinal cords were extracted, weighed, snap-frozen on dry ice, and stored at −80 °C until virus titrations assays were performed. At that time, 20 % (w/v) homogenates of each sample were prepared in Dulbecco’s modified Eagle’s medium (DMEM, Sigma-Aldrich), and serial tenfold dilutions of each homogenate were assayed for plaque formation on monolayers of BHK-21 cells. Results presented are the mean ± SEM of the log10 of viral pfu per gram of tissue derived from a minimum of three animals at each time point. Measurement of tissue superoxide-generating activity The capacity of CNS tissues to generate ROS was measured directly ex vivo using the well-established cytochrome c reduction assay on fresh tissue membrane extracts, as described [37, 38]. Briefly, animals were perfused with chilled PBS, and brains and spinal cords were extracted, weighed, and homogenized to a final concentration of 1 mg/ml total tissue protein in DMEM. One hundred-eighty microliters of each homogenate was then added to 96-well, flat-bottom plates in duplicate. Purified superoxide dismutase (SOD, Sigma-Aldrich) was then added to half the wells at a final concentration of 200 U/ml, while DMEM was added to the remaining wells as a control. All wells then received 500 μmol/l purified cytochrome c (Sigma-Aldrich) and 100 μmol/l purified NADPH (Sigma-Aldrich) as a specific electron donor, and plates were incubated at 37 °C for 30 min. Immediately thereafter, the absorbance of each well was read at 540, 550, and 560 nm using a PowerWave HT spectrophotometer (BioTek, Winooski, VT). Tissue O2− production by each sample was calculated by first subtracting the average optical density (OD) readings at 540 and 560 nm from the average OD reading at 550 nm (ΔOD). The difference in ΔOD value in the absence and presence of SOD was then divided by the extinction coefficient of cytochrome c using the following formula: (ΔOD without SOD – ΔOD with SOD)/21.1. Results are presented as nmol O2− produced/mg tissue protein. Statistical comparisons The Prism 5.0 software package (GraphPad Software, La Jolla, CA) was used for all statistical analyses. Student’s t test was applied when comparing a single group under two experimental conditions, a one-way analysis of variance (ANOVA) with a post hoc Bonferroni’s multiple comparison test was used to investigate the significance of a single group’s change over time, while a two-way ANOVA with a post hoc Bonferroni’s multiple comparison test was utilized to compare experimental findings between two groups over time. Differences in outcome among individual cohorts of infected mice were determined using a log-rank (Mantel-Cox) test. In all cases, differences at a p < 0.05 level were considered significant. Results Role of the Ang II-AT1R axis in the CNS during NSV encephalomyelitis To explore whether Ang II-AT1R signaling influences disease outcome in mice with NSV encephalomyelitis, we measured Ang II concentrations directly in CNS tissues over time. These assays showed that Ang II levels increased in both the brains and spinal cords of mice over the first few days following NSV infection (Fig. 1a, b). Furthermore, local Ang II production was suppressed via systemic administration of captopril (Fig. 1c), an angiotensin converting enzyme (ACE) inhibitor that prevents Ang II cleavage from its precursor, angiotensinogen (AGT). Importantly, mice treated with this drug showed enhanced survival compared to animals receiving a vehicle control (Fig. 1d). These data suggest that local Ang II production could be an important early event that triggers CNS damage and leads to fatal disease in mice with NSV infection.Fig. 1 Ang II levels increase in both the brains (a) and spinal cords (b) of mice with NSV encephalomyelitis, while treatment of NSV-infected mice with the ACE inhibitor, captopril, suppresses Ang II induction in the CNS (c) and enhances disease survival (d). Tissue Ang II levels were measured by EIA in homogenates collected from uninfected (day 0) or NSV-infected animals and normalized to the total extracted protein content of each sample. Values measured in individual mice (n = 4–6 samples per time point) and mean concentrations at each time point are shown. One-way ANOVA confirmed that Ang II levels change significantly in both CNS tissue compartments over time (p = 0.0005 for brain, p = 0.0132 for spinal cord). Treatment of mice with captopril (10 mg/kg/day) suppressed Ang II induction on day 3 post-infection compared to mice given a vehicle control (n = 5 samples per group, *p < 0.05 by Student’s t test). This same treatment regimen enhanced overall disease survival compared to mice given a vehicle control (n = 7 mice per group, p = 0.002 using a log-rank (Mantel-Cox) test) We next characterized CNS AT1R expression, demonstrating that tissue receptor levels increased steadily in both the brains and spinal cords of NSV-infected animals (Fig. 2a, b). A representative Western blot is shown (Additional file 1: Figure S1). Using CX3CR1GFP/+ mice with constitutively green microglia [39], AT1R expression was identified by histochemical staining on a subset of these cells in the brains of naïve animals (Fig. 2c). Because CX3CR1-positive cells could also represent GFP-positive monocytes infiltrating from the periphery [39], these two cell populations were separated from the brains of NSV-infected animals by flow sorting for ex vivo analysis. Using this approach, anti-AT1R antibodies proved unreliable to detect surface expression by flow cytometry, but agtr1a transcripts were found at equivalent levels in CD45low/CD11b + microglia and CD45high/CD11b + infiltrating myeloid cells at peak disease (Fig. 2d). No AT1R expression was detected by histochemical staining on CX3CR1-negative cells in either control or NSV-infected tissues (Fig. 2c and data not shown). Finally, AT1R KO mice challenged with NSV demonstrated improved survival compared to wild-type (WT) controls (Fig. 2e). These results confirm that AT1R signaling contributes to NSV pathogenesis. Furthermore, local pharmacological blockade of AT1R in the CNS, if achieved, would act mainly on the endogenous and recruited myeloid cell populations in this disease setting.Fig. 2 AT1R levels progressively increase in both the brains (a) and spinal cords (b) of mice with NSV encephalomyelitis; receptor expression remains restricted to microglia (c) and infiltrating monocytes (d) in infected mice and receptor deletion confers significant protection against lethal disease (e). Normalized AT1R expression in whole tissue extracts (n = 5 samples per time point) was determined by Western blot. One-way ANOVA confirmed that AT1R levels changed significantly in both CNS compartments over time (p < 0.0001 for both brain and spinal cord). Using transgenic mice selectively expressing GFP in CX3CR1+ cells, AT1R expression was found on a subset of microglia from the hippocampal formations of uninfected animals (c). AT1R staining was not detected on any CX3CR1− cells. Bar = 20 μm. At peak inflammation (day 6), CD45low/CD11b + microglia and CD45high/CD11b + infiltrating monocytes expressed equivalent levels of agtr1a mRNA (n = 5 samples per group) (d). Finally, global AT1R KO mice survived NSV infection more readily than WT controls (n = 7 mice per group, p = 0.0148 using a log-rank (Mantel-Cox) test) (e) Effects of a systemically administered AT1R antagonist on the course of lethal alphavirus encephalomyelitis in mice We next investigated the effects of telmisartan on the course of NSV encephalomyelitis, a drug known to effectively penetrate the BBB and cause sustained AT1R blockade without affecting AT2R signaling [28]. Cohorts of mice were treated twice daily with the drug beginning 12 h after viral challenge. Escalating doses up to 100 mg/kg/day were used, below those previously shown to lower systemic arterial blood pressure in rodents [40]. Analyses of disease outcomes in these cohorts showed that drug treatment attenuated the development of severe hind limb paralysis and prevented death in a dose-dependent manner compared to animals given a vehicle control (Fig. 3). These data further support a role for AT1R signaling in NSV pathogenesis.Fig. 3 Telmisartan protects mice against both moderate or severe hind limb paralysis (a) and death (b) following NSV challenge in a dose-dependent manner. Cohorts of animals (n = 15–23 mice per group) were inoculated with NSV and treated twice daily with either telmisartan or a vehicle control at the daily doses indicated. Blinded examiners scored each animal daily as described. The proportion of mice in each group that remained either normal/mildly affected (a) or alive (b) was calculated over time. Statistical differences between drug-treated groups and vehicle-treated controls were determined using a log-rank (Mantel-Cox) test. Individual p values are as follows: *p < 0.0001; **p = 0.0002; ***p = 0.0244; †p < 0.0001; ††p = 0.0148; †††p = 0.1514 Virus titrations were performed on tissues derived from vehicle- and telmisartan-treated animals to investigate whether the drug had any effect on CNS virus replication or spread. These assays showed that virus replication was completely unaltered in both the brains and spinal cords of NSV-infected mice treated with the highest protective dose of telmisartan examined (Fig. 4). Furthermore, infection with NSV-GFP demonstrated that drug treatment did not change virus tropism for neurons or reduce the number of infected cells in heavily targeted CNS regions such as the hippocampus or the lumbar spinal cord (data not shown). These results show that telmisartan produces benefits in mice with NSV encephalomyelitis through a mechanism other than one involving direct antiviral activity.Fig. 4 Telmisartan has no effect on the replication or clearance of NSV from the brains (a) or spinal cords (b) of NSV-infected animals. Mice were inoculated with NSV and treated with telmisartan (100 mg/kg/day) or a vehicle control. Replicate mice were sacrificed at predetermined intervals, and viral titers were measured in each tissue sample by plaque titration assay. Mean ± SEM of the log10 of tissue plaque-forming units (pfu) per gram of tissue are shown. Two-way ANOVA confirmed that the virus replication curves from vehicle- and telmisartan-treated mice are not different from each other (p = 0.74 for brain, p = 0.31 for spinal cord) To investigate whether telmisartan exerted any anti-inflammatory effects in NSV-infected animals, we measured total MNC infiltration into the CNS, the recruitment of individual myeloid cell subsets into the brain, the cellular activation status of these CNS myeloid cells, and circulating and CNS levels of myeloid cell-related immune factors after 6 days of treatment. Ex vivo analyses of CNS isolates from infected animals showed that total tissue MNC were not reduced in telmisartan- compared to vehicle-treated mice (Fig. 5a). The proportions of five distinct myeloid cell subsets were equivalent between the two groups (Fig. 5b), and telmisartan had no effect on expression levels of the activation markers, CD40 and CD86, on any of these cell types (Fig. 5c, d). When a panel of myeloid factors was measured in both plasma and brain tissue from NSV-infected animals, telmisartan had minimal effects on the production of any of these mediators in either tissue compartment (Fig. 6). We conclude that telmisartan does not exert a global anti-inflammatory effect in either the periphery or the CNS during NSV infection.Fig. 5 Telmisartan has no effect on the local CNS inflammatory response induced following NSV infection. At peak inflammation (day 6), total MNC infiltration was not suppressed in either the brains or spinal cords of mice (n = 5 mice per group) treated with telmisartan (100 mg/kg/day) compared to a vehicle control (a). By flow cytometry, the proportions of different brain-infiltrating myeloid cell subsets (CD45+/CD11b+) were not different between these two groups (b). Likewise, expression of CD40 (c) and CD86 (d) were not changed on any resident or CNS-infiltrating myeloid cell subset in the setting of drug treatment as assessed by the mean fluorescence intensity (MFI) of staining for the two activation markers Fig. 6 Telmisartan has no effect on the systemic or local CNS production of myeloid-related immune factors following NSV challenge. At peak inflammation (day 6), plasma and brain tissue was collected from mice (n = 5 mice per group) treated with telmisartan (100 mg/kg/day) compared to a vehicle control. Plasma samples were assayed without further manipulation. Tissue homogenates were first normalized to the total extracted protein content of each sample. Plasma and brain levels of myeloid-related immune factors were measured using a commercial assay according to the manufacturer’s instructions. Plasma (pg/ml) or brain (pg/mg total tissue protein) concentrations are shown. No differences in any vehicle- versus telmisartan-treated brain concentrations were identified To determine the broader relevance of telmisartan as a treatment for alphavirus encephalitis, separate cohorts of mice were challenged with the known human pathogen, WEEV. Much like what was observed in NSV-infected animals, systemic administration of telmisartan at a similar dose caused reduced disease severity in WEEV-infected mice compared to vehicle-treated controls (Fig. 7a). Half of the treated animals survived infection compared to what was uniformly lethal without the drug (Fig. 7b). These data confirm that telmisartan can protect a significant proportion of mice using a lethal challenge model of a clinically relevant alphavirus. As ARB drugs are in widespread human use, and as antiviral drugs effective against the alphaviruses still remain a long way from human application [41, 42], blockade of this signaling pathway might be considered for testing in both equine and human cases of acute alphavirus encephalitis.Fig. 7 Mice treated with telmisartan developed milder disease (a) and were protected from death (b) following challenge with the human alphavirus, WEEV. Mice were inoculated with WEEV and treated with either telmisartan (100 mg/kg/day) or a vehicle control. Blinded examiners scored each animal daily for both disease severity and survival. The mean ± SEM disease score (a) and the proportion of animals surviving (b) are shown (n = 8 mice/group). A two-way ANOVA confirmed that drug treatment lessened disease severity (p < 0.0001), while a log-rank (Mantel-Cox) test confirmed that telmisartan enhanced disease survival (p = 0.0139) Effects of telmisartan on Nox activation, ROS production, and oxidative neuronal injury in the CNS during NSV encephalomyelitis Given the known capacity of ARBs to suppress Nox-mediated ROS production in both vascular smooth muscle and renal podocytes [22, 23, 29], we next sought to determine whether telmisartan suppresses tissue ROS production and oxidative neuronal injury as a potential mechanism through which it protected NSV-infected animals. To investigate Nox activity in the CNS during disease, tissue subunit expression and tissue enzyme activity were measured ex vivo. Via Western blot, multiple Nox subunits were induced in both the brains and spinal cords of NSV-infected animals over time (Fig. 8a, b). A representative blot is shown (Additional file 2: Figure S2). Using an established method to quantify superoxide production in tissue extracts via ex vivo reduction of cytochrome c and exogenous NADPH as an electron donor [37, 38], we found clear biochemical evidence that enzymes capable of generating ROS were induced in both the brains and spinal cords of animals 72 h following NSV challenge (Fig. 8c, d). Furthermore, this enzyme activity was potently suppressed in tissues derived from infected mice treated with telmisartan, and it was ablated in samples collected from infected gp91/p47 DKO animals not treated with the drug (Fig. 8c, d). On the other hand, telmisartan had no effect on the induction of Nox subunits in the CNS by Western blot (data not shown). We conclude that Nox is the principal enzymatic source of tissue ROS in this disease setting, and that telmisartan suppresses Nox activity in the CNS without inhibiting expression of the enzyme complex itself.Fig. 8 Nox subunits are upregulated in the CNS following NSV challenge (a, b), and enzymatic activity capable of generating ROS is both induced in the brains (c) and spinal cords (d) of infected animals and inhibited by telmisartan as well as by genetic deletion of Nox subunits. Normalized gp91 and p47 expression in whole tissue extracts was determined by Western blot as described in the “Methods” section. One-way ANOVA confirmed that levels of both Nox subunits changed significantly in both CNS regions over time (p < 0.0001). ROS-generating enzyme activity was measured directly in tissue extracts as described in the “Methods” section. Values derived from individual mice as well as mean enzyme activity levels are shown for each experimental condition (n = 5 mice/group). Student’s t test was used to analyze the degree to which telmisartan (100 mg/kg/day) or Nox subunit deletion suppressed enzyme activity in tissues derived from NSV-infected animals compared to those from vehicle-treated controls (*p = 0.0009 in brain and p = 0.0026 in spinal cord; **p = 0.0005 in brain and p = 0.0004 in spinal cord) To investigate the spatial expression of ROS directly in CNS tissues, animals were infused with DHE immediately prior to sacrifice. This cell-permeable dye gets oxidized to the fluorescent compound, ethidium, by intracellular ROS and trapped within cells [43]. We found that DHE labeling was increased in the spinal cord 96 h after viral challenge when compared to labeled tissue derived from uninfected animals. This ROS signal remained largely confined to gray matter regions where infected cells were also found (Fig. 9a, b). Systemic treatment with telmisartan at protective doses largely abolished this DHE staining (Fig. 9c). Similar patterns of DHE labeling suppressed by telmisartan treatment were also observed in the brain, and no DHE labeling above background was found in tissues from NSV-infected but otherwise untreated gp91/p47 DKO mice (data not shown). Since drug treatment did not inhibit virus replication in either the brain or spinal cord (Fig. 4), we conclude that ROS do not exert any antiviral effect during alphavirus encephalitis.Fig. 9 In vivo labeling shows that ROS are induced in ventral gray matter of the lumbar spinal cord (outlined) following NSV challenge and that ROS induction is suppressed in infected animals treated with telmisartan. ROS-containing cells (red) were labeled by injecting mice with DHE just prior to sacrifice as described in the “Methods” section. A GFP-expressing virus was used to identify NSV-infected neurons (green). Negligible ROS staining was observed in uninfected control animals (a). Four days after NSV challenge, ROS were detected in relative proximity to, but not necessarily within, infected neurons (b). Telmisartan administration (100 mg/kg/day) abolished nearly all ROS labeling in infected animals at this time point (c). Calibration bar = 75 μm for all panels ROS generated as part of an inflammatory response can damage cellular lipids, proteins, and nucleic acids. A lipid peroxidation product detectable in cell membranes, 4-HNE, is both a validated marker for, as well as a direct mediator of, oxidative injury to neurons [44, 45]. We found that CNS tissues derived from NSV-infected animals showed prominent 4-HNE immunoreactivity in spinal gray matter within 72 h of viral challenge compared to uninfected controls (Fig. 10a, b). At higher magnification, heavy labeling of neuronal cell bodies, with moderate staining of gray matter neuropil, was observed (Fig. 10c). Treatment with telmisartan visibly reduced 4-HNE staining observed in infected tissue samples (Fig. 10d). Similar patterns of 4-HNE immunoreactivity were also identified in the hippocampus (data not shown).Fig. 10 Telmisartan blocks oxidative changes to neurons in the spinal cords of NSV-infected mice. Immunohistochemical staining for 4-HNE, a lipid peroxidation product that accumulates in cell membranes following ROS exposure, is induced 4 days after NSV infection (b) compared to expression in uninfected control animals (a). Higher magnification views show prominent staining of neuronal cell membranes with less intense labeling of neuropil in ventral gray matter of infected animals (c). Treatment of NSV-infected mice with telmisartan (100 mg/kg/day) for 4 days blocks most of the observed 4-HNE immunoreactivity (d). Calibration bar = 250 μm in panels a, b and d; 20 μm in panel c Based on this distribution of staining, the effects of telmisartan on the survival of hippocampal and lumbar ventral spinal motor neurons were quantified following NSV infection. Using Fluoro-Jade C labeling, an established histochemical marker of irreversible neuronal injury [46], damaged hippocampal neurons were easily identified on day 7 post-infection compared to naïve controls (Fig. 11a), and quantification of these cells showed that the drug exerted a measurable neuroprotective effect compared to vehicle-treated controls (Fig. 11b). Likewise, silver staining of sections through the lumbar spinal columns of these mice allowed the identification of lumbar ventral nerve roots carrying axons from lumbar ventral motor neurons (Fig. 11c); quantification of these axons showed that survival of these cells was also enhanced by telmisartan (Fig. 11d). Together, these findings demonstrate that a systemically administered ARB can penetrate the CNS to inhibit Nox activity and local ROS production, thereby limiting oxidative neuronal damage during NSV encephalomyelitis.Fig. 11 Telmisartan prevents irreversible neuronal damage and loss in the brains and spinal cords of NSV-infected mice. Fluoro-Jade C staining shows extensive labeling of hippocampal neurons in a mouse 7 days after NSV infection (right panel, a) compared to an uninfected control (left panel, a). Bar = 75 μm for both panels. Quantification of staining at this stage of infection as described in the “Methods” section shows that telmisartan (100 mg/kg/day) reduces damage to these neurons compared to animals treated with a vehicle control (b). In the lumbar spinal cord, silver staining shows prominent axonal loss in individual ventral nerve roots (each marked with an *) on day 7 post-infection (right panel, c) compared to an uninfected control (left panel, c). Bar = 100 μm for both panels. Quantification of axonal density in these ventral nerve roots as described in the “Methods” section shows that telmisartan treatment (100 mg/kg/day) reduces damage to lumbar motor neurons from which these axons arise compared to animals treated with a vehicle control (d). Student’s t test was used to analyze both the degree of cell damage in vehicle-treated versus naïve mice (†p < 0.0001 in both the hippocampus and spinal cord) as well as the degree to which drug treatment suppressed neuronal damage compared to those from vehicle-treated controls (*p = 0.0006 in the hippocampus; *p = 0.0005 in the spinal cord) Effects of Nox subunit deletion on telmisartan-mediated protection during NSV encephalomyelitis in vivo Although multiple enzymes could theoretically be generating ROS in the CNS following NSV infection, Nox appears to be their primary source given the results of both our biochemical assays (Figs. 8c, d) as well as the absence of DHE staining in infected gp91/p47 DKO mice (data not shown). When gp91/p47 DKO mice were challenged with NSV, these hosts survived infection significantly better than WT controls (Fig. 12a). Furthermore, when telmisartan was given to cohorts of NSV-infected gp91/p47 DKO hosts, the survival benefit conferred by the drug was abolished compared to DKO animals treated with a vehicle control (Fig. 12b). These data confirm that Nox activity is pathogenic during NSV infection, and that Nox is the main therapeutic target of telmisartan in this alphavirus encephalitis model.Fig. 12 Nox-deficient mice are protected from NSV infection compared to WT controls, while telmisartan has no protective effect in Nox-deficient hosts. In the absence of any drug treatment, gp91/p47 DKO mice survived NSV infection much better than WT control animals (a). When gp91/p47 DKO mice were treated with either telmisartan (100 mg/kg/day) or a vehicle control, no survival difference between the two groups was observed (b). Statistical differences in outcome between these cohorts (n = 22 mice/group) were determined using a log-rank (Mantel-Cox) test. Individual p values are shown Discussion Although natural outbreaks of mosquito-borne encephalitis caused by alphaviruses remain rare events, aerosol transmissibility makes some of these pathogens potential bioterrorism agents [1]. Other dangerous features of alphaviruses include their potential to cause incapacitating disease, their relatively high infectivity for humans, the ease with which they can be mass produced, and the lack of effective countermeasures for disease prevention or control [1]. Studies undertaken in murine alphavirus encephalitis models have demonstrated that blocking host responses arising from activated microglial cells can protect infected hosts, often without suppressing CNS virus replication or spread [7, 10–14]. Although the molecular pathways leading to neuronal damage in infected mice are incompletely understood, strategies to subvert these injurious host responses remain fertile areas of investigation. Here, we implicate a novel injury mechanism in the CNS–ROS production via Nox activation—as an important contributor to alphavirus pathogenesis. We also demonstrate that an existing ARB capable of penetrating the BBB can effectively inhibit CNS Nox activity, prevent oxidative neuronal damage, and reduce disease morbidity and mortality in diseased animals without having any effect on local virus replication or clearance. This raises questions as to whether these drugs could have broader uses in the treatment of neurologic disorders where oxidative injury is known or hypothesized to occur. Broadly defined, oxidative stress results from the increased production of both ROS and reactive nitrogen species (RNS) to an extent that cellular antioxidant defenses get overwhelmed. Both acute infections caused by herpes simplex virus and chronic infections caused by human immunodeficiency virus and measles virus are known to cause oxidative damage to neurons and glial cells within the CNS [21]. On the other hand, the extent to which the oxidative burst can benefit the infected host by limiting virus replication is unknown. Furthermore, ROS are known to participate in normal intracellular signaling, and Nox activation has now been shown to facilitate cellular Toll-like receptor (TLR) responses and augment type-1 interferon production following engagement of the cytoplasmic viral sensor, retinoic acid-inducible gene I (RIG-I) [47, 48]. Thus, local Nox activation could in theory either positively or negatively influence the outcome of CNS viral infection. We find that systemic administration of the ARB, telmisartan, potently suppresses Nox activity in both the brains and spinal cords of mice with NSV encephalomyelitis, effectively blocking local ROS production and preventing oxidative neuronal injury without altering virus replication or clearance. Evidence that the drug confers protection through a Nox-dependent pathway and not via some off-target effect comes from our observation that gp91/p47 DKO mice that do not generate any oxidative burst in the CNS following virus challenge, have improved disease outcomes compared to WT controls, and are completely unresponsive to telmisartan following NSV infection. Taken together, our data show that Nox activation is pathogenic in this disease setting and that this enzyme complex can be effectively targeted to benefit the host via systemic administration of a compound already widely used in humans. While originally developed for use in treating hypertension and more recently shown to exert neuroprotective effects in stroke models [24–27], ARBs are now confirmed to have benefits during experimental neuroinflammation. In experimental autoimmune encephalomyelitis (EAE), the principal mouse model of multiple sclerosis (MS), systemically administered ARBs can suppress disease severity [49–51]. One study showed that ARB treatment disrupted local astrocyte and microglial production of the inflammatory factor, transforming growth factor-beta (TGF-β), and suppressed myeloid cell recruitment to the CNS [51]. The authors of this study inferred that actions on these glial cells were primary and that suppressed inflammatory cell infiltration into diseased CNS tissue was a secondary effect [51]. In a mouse model of traumatic brain injury, a single dose of telmisartan given 6 h after injury caused reduced perilesional staining for CD68, ionized calcium binding adaptor molecule 1 (Iba-1), and myeloperoxidase (MPO) at 72 h, while a similar treatment 24 h after injury had no such effect [52]. In this setting, however, the cells targeted by telmisartan were not specifically identified, and its effects proved largely dependent on peroxisome proliferator-activated receptor gamma (PPARγ) agonism as opposed to AT1R blockade [52]. Other in vitro studies have also shown that the anti-inflammatory actions of ARBs on myeloid cells correlate with their PPARγ agonist potency [53]. Although our work does not specifically address the role of PPARγ in NSV pathogenesis, we found no evidence that telmisartan conferred benefit in the setting of Nox deficiency or exerted a more global anti-inflammatory effect. This variability in response might be explained by its capacity to act on multiple targets in different disease models. Indeed, in some settings telmisartan may directly enter target cells and scavenge intracellular ROS fully independent of its AT1R blocking effects [54]. The renin-angiotensin system (RAS) has now been recognized to exert direct actions within the CNS and to serve roles beyond the neural control of cardiovascular function [55, 56]. These observations have spawned many studies to examine the cellular localization of RAS components within the brain. There is some consensus, for example, that AGT and the cleaving enzymes needed for Ang II synthesis exist in distinct neural cell types [55]; this would imply that a network of cells contributes to the final production of this mediator. As for Ang II receptors, most reports validate that both AT1R and AT2R are found at varying levels throughout the brain, although debate still rages surrounding their relative localization to neurons versus glial cells [55, 56]. While some genetic models suggest that Ang II receptors are found primarily on neurons under steady state conditions [57, 58], co-localization using glial-specific reporter mice has not been described until now. Furthermore, AT1R are found on peripheral immune cells [59] and are abundant on CNS-infiltrating myeloid cells during both EAE and MS [50]. Using CX3CR1GFP/+ mice that label both microglia and peripheral monocytes [39], histochemical staining of tissue sections as well as direct physical separation of CNS myeloid cell subsets by flow cytometry allowed us to confirm that AT1R localizes principally to CX3CR1+ and to CD45+/CD11b+ cells during NSV infection. Ongoing studies will use WT and AT1R KO mice to create bone marrow chimeras in order to confirm that hematopoietic cells are the main target of telmisartan in this disease, with a longer-term goal being the creation of a conditional AT1R KO mouse. Nonetheless, our current findings fit with other studies showing that aberrant host responses arising from activated myeloid cells contribute to NSV pathogenesis [7, 10, 13], even if they do not yet shed any light on the source or mechanism of local Ang II production following NSV infection. Finally, it bears considering that another group recently studied the role of Ang II and ARB signaling in a closely related infection model caused by another alphavirus, Venezuelan equine encephalitis virus (VEEV), in rats. These investigators found that Ang II expression increased rapidly in the CNS following VEEV infection, but that daily treatment of animals with losartan (30 mg/kg) actually accelerated death compared to rats given a vehicle control [60]. In their hands, losartan suppressed VEEV-mediated induction of the pro-inflammatory mediators, IL-1α and CCL2, as well as the anti-inflammatory compound, IL-10, but had no effect on IL-6 levels in the brain [60]. Drug treatment also reduced vascular pathology in the CNS of VEEV-infected animals, but had no quantitative effects on cellular infiltration into the brain. They concluded that Ang II-driven neuroinflammation could be a host defense mechanism that limits virus damage and favors survival [60]. Unfortunately, however, their conclusions contradict numerous other studies showing that host responses actually drive VEEV pathogenesis and directly contribute to mortality [61–63]. We otherwise remain unable to explain why our results differ so dramatically from these investigators’ conclusions using a related encephalitis model. Conclusions Our data show that components of the RAS are induced in the CNS during the early stages of alphavirus encephalitis, and that the ARB, telmisartan, acts in a highly targeted manner to suppress Nox activity in both endogenous and CNS-infiltrating myeloid cells and protect infected hosts from lethal disease. Impaired ROS production reduces neuronal injury, and the abrogation of clinical protection in Nox-deficient hosts confirms that these enzymes are the main target of this drug in this setting. Given widespread use in humans, this ARB may also confer benefit in treating neurologic disorders where oxidative injury is known or hypothesized to occur. Additional files Additional file 1: Figure S1. Representative Western blots show induction of AT1R in both the brain and spinal cord over the course of acute NSV infection relative to the expression of a β-actin loading control in each tissue sample (TIF 352 KB). (TIF 297 kb) Additional file 2: Figure S2. Representative Western blots show induction of the Nox subunits, gp91 and p47, in both the brain and spinal cord over the course of acute NSV infection relative to the expression of a β-actin loading control in each tissue sample (TIF 492 KB). (TIF 424 kb) Abbreviations 4-HNE4-Hydroxynonenal ACEAngiotensin converting enzyme AGTAngiotensinogen Ang IIAngiotensin II ANOVAAnalysis of variance ARBAngiotensin II receptor blocker AT1RType-1 angiotensin II receptors AT2RType-2 angiotensin II receptors BBBBlood-brain barrier BSL3Biosafety level 3 CNSCentral nervous system cDNAcomplementary DNA CX3CR1CX3C chemokine receptor-1 DHEDihydroethidium DKODouble knockout DMEMDulbecco’s modified Eagle’s medium EAEExperimental autoimmune encephalomyelitis EIAEnzyme immunoassay FBSFetal bovine serum GFPGreen fluorescent protein HBSSHank’s balanced salt solution HRPHorseradish peroxidase i.p.Intraperitoneal KOKnockout MFIMean fluorescence intensity MNCMononuclear cells MPOMyeloperoxidase MSMultiple sclerosis NADPHNicotinamide adenine dinucleotide phosphate NGSNormal goat serum NoxNADPH oxidase NSVNeuroadapted Sindbis virus ODOptical density PBSPhosphate-buffered saline PFAParaformaldehyde pfuplaque forming units PPARγPeroxisome proliferator-activated receptor gamma qPCRQuantitative PCR RASRenin-angiotensin system RIG-IRetinoic acid-inducible gene I RNSReactive nitrogen species ROSReactive oxygen species SDSSodium dodecyl sulfate SEMStandard error of the mean SODSuperoxide dismutase TBSTris-buffered saline TGF-βTransforming growth factor-beta TLRToll-like receptor VEEVVenezuelan equine encephalitis virus WEEVWestern equine encephalitis virus WTWild type Acknowledgements None. Funding This work was funded by the United States National Institutes of Health grant, AI057505, awarded to DNI. The funding agency had no role in the design of the study, in the collection, analysis, and interpretation of data, or in the preparation of this manuscript. Availability of data and materials All of the data described in this manuscript are freely available to anyone wishing to use them for non-commercial purposes. All of the research materials used in these studies are likewise freely available to any research scientist upon request. Authors’ contributions PKB, AKH, and DNI designed the experiments. PKB and AKH performed all the experiments. DNI conceived the idea, secured the funding, supervised all the experiments and data analyses, and wrote the manuscript. All authors have read and approved the final version of this manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval All animal experiments, including those incorporating paralysis or death as study endpoints, were conducted in strict accordance with protocols approved by the University of Michigan Committee on Use and Care of Animals (protocol #PRO00005049, protocol #PRO00005204) as well as with federal guidelines. ==== Refs References 1. Sidwell RW Smee DF Viruses of the Bunya- and Togaviridae families: potential as bioterrorism agents and means of control Antiviral Res 2003 57 101 11 10.1016/S0166-3542(02)00203-6 12615306 2. Jackson AC Moench TR Trapp BD Griffin DE Basis of neurovirulence in Sindbis virus encephalomyelitis of mice Lab Invest 1988 58 503 9 3367635 3. Jackson AC Moench TR Griffin DE Johnson RT The pathogenesis of spinal cord involvement in the encephalomyelitis of mice caused by neuroadapted Sindbis virus infection Lab Invest 1987 56 418 23 3031369 4. Johnson RT McFarland HF Levy SE Age-dependent resistance to viral encephalitis: studies of infections due to Sindbis virus in mice J Infect Dis 1972 125 257 62 10.1093/infdis/125.3.257 4552644 5. Lewis J Wesselingh SL Griffin DE Hardwick JM Alphavirus-induced neuronal apoptosis in mouse brains correlates with neurovirulence J Virol 1996 70 1828 35 8627707 6. Nargi-Aizenman JL Griffin DE Sindbis virus-induced neuronal death is both necrotic and apoptotic and is ameliorated by N-methyl-D-aspartate receptor antagonists J Virol 2001 75 7114 21 10.1128/JVI.75.15.7114-7121.2001 11435592 7. Irani DN Prow NA Neuroprotective interventions targeting detrimental host immune responses protect mice from fatal alphavirus encephalitis J Neuropathol Exp Neurol 2007 66 533 44 10.1097/01.jnen.0000263867.46070.e2 17549013 8. Liang XH Goldman JE Jiang HH Levine B Resistance of interleukin-1 beta-deficient mice to fatal Sindbis virus encephalitis J Virol 1999 73 2563 7 9971844 9. Kimura T Griffin DE The role of CD8+ T cells and major histocompatibility complex class I expression in the central nervous system of mice infected with neurovirulent Sindbis virus J Virol 2000 74 6117 25 10.1128/JVI.74.13.6117-6125.2000 10846095 10. Prow NA Irani DN The opioid receptor antagonist, naloxone, protects spinal motor neurons in a murine model of alphavirus encephalomyelitis Exp Neurol 2007 205 461 70 10.1016/j.expneurol.2007.03.013 17459376 11. Darman J Backovic S Dike S Maragakis NJ Krishnan C Rothstein JD Viral-induced spinal motor neuron death is non-cell-autonomous and involves glutamate excitotoxicity J Neurosci 2004 24 7566 75 10.1523/JNEUROSCI.2002-04.2004 15329404 12. Nargi-Aizenman JL Havert MB Zhang M Irani DN Rothstein JD Griffin DE Glutamate receptor antagonists protect from virus-induced neural degeneration Ann Neurol 2004 55 541 9 10.1002/ana.20033 15048893 13. Prow NA Irani DN The inflammatory cytokine, interleukin-1 beta, mediates loss of astroglial glutamate transport and drives excitotoxic motor neuron injury in the spinal cord during acute viral encephalomyelitis J Neurochem 2008 105 1276 86 10.1111/j.1471-4159.2008.05230.x 18194440 14. Greene IP Lee E-Y Prow N Ngwang B Griffin DE Protection from fatal viral encephalomyelitis: AMPA receptor antagonists have a direct effect on the inflammatory response to infection Proc Natl Acad Sci U S A 2008 105 3575 80 10.1073/pnas.0712390105 18296635 15. Babior BM NADPH oxidase Curr Opin Immunol 2004 16 42 7 10.1016/j.coi.2003.12.001 14734109 16. Bedard K Krause K-H The NOX family of ROS-generating NADPH oxidases: physiology and pathophysiology Physiol Rev 2007 87 245 313 10.1152/physrev.00044.2005 17237347 17. Choi SH Lee DY Chung ES Hong YB Kim SU Jin BK Inhibition of thrombin-induced microglial activation and NADPH oxidase by minocycline protects dopaminergic neurons in the substantia nigra in vivo J Neurochem 2005 95 1755 65 10.1111/j.1471-4159.2005.03503.x 16219027 18. Li J Baud O Vartanian T Volpe JJ Rosenberg PA Peroxynitrite generated by inducible nitric oxide synthase and NADPH oxidase mediates microglial toxicity to oligodendrocytes Proc Natl Acad Sci U S A 2005 102 9936 41 10.1073/pnas.0502552102 15998743 19. Wu DC Re BC Nagai M Ischiropoulos H Przedborski S The inflammatory NADPH oxidase enzyme modulates motor neuron degeneration in amyotrophic lateral sclerosis mice Proc Natl Acad Sci U S A 2006 103 12132 7 10.1073/pnas.0603670103 16877542 20. Harraz MM Marden JJ Zhou W Zhang Y Williams A Sharov VS SOD1 mutations disrupt redox-sensitive Rac regulation of NADPH oxidase in a familial ALS model J Clin Invest 2008 118 659 70 18219391 21. Valyi-Nagy T Dermody TS Role of oxidative damage in the pathogenesis of viral infections of the nervous system Histol Histopathol 2005 20 957 67 15944946 22. Rajagopalan S Kurz S Munzel T Tarpey M Freeman BA Griendling KK Angiotensin II-mediated hypertension in the rat increases vascular superoxide production via membrane NADH/NADPH oxidase activation. Contribution to alterations of vasomotor tone J Clin Invest 1996 97 1916 23 10.1172/JCI118623 8621776 23. Pagano PJ Clark JK Cifuntes-Pagano ME Clark SM Callis GM Quinn MT Localization of a constitutively active, phagocytic-like NADPH oxidase in rabbit aortic adventitia: enhancement by angiotensin II Proc Natl Acad Sci U S A 1997 94 14483 8 10.1073/pnas.94.26.14483 9405639 24. Dai WJ Funk A Herdegen T Unger T Culman J Blockade of central angiotensin AT(1) receptors improves neurological outcome and reduces expression of AP-1 transcription factors after focal cerebral ischemia in rats Stroke 1999 30 2391 8 10.1161/01.STR.30.11.2391 10548676 25. Kusaka I Kusaka G Zhao C Ishikawa M Nanda A Granger DN Role of AT1 receptors and NAD(P)H oxidase in diabetes-aggravated ischemic brain injury Am J Physiol Heart Circ Physiol 2004 286 H2442 51 10.1152/ajpheart.01169.2003 15148062 26. Lou M Blume A Zhao A Gohlke P Deuschl G Herdegen T Sustained blockade of brain AT1 receptors before and after focal cerebral ischemia alleviates neurologic deficits and reduces neuronal injury, apoptosis, and inflammatory responses in the rat J Cereb Blood Flow Metab 2004 24 536 47 10.1097/00004647-200405000-00008 15129186 27. Jung KH Chu K Lee ST Kim SJ Song EC Kim EH Blockade of AT1 receptor reduces apoptosis, inflammation, and oxidative stress in normotensive rats with intracerebral hemorrhage J Pharm Exp Ther 2007 322 1051 8 10.1124/jpet.107.120097 28. Gohlke P Weiss S Jansen A Wienen W Stangler J Rascher W AT1 receptor antagonist telmisartan administered peripherally inhibits central responses to angiotensin II in conscious rats J Pharm Exp Ther 2001 298 62 70 29. Tojo A Asaba K Onozato ML Suppressing renal NADPH oxidase to treat diabetic nephropathy Expert Opin Ther Targets 2007 11 1011 8 10.1517/14728222.11.8.1011 17665974 30. Castorena KM Peltier DC Peng W Miller DJ Maturation-dependent responses of human neuronal cells to western equine encephalitis virus infection and type I interferons Virology 2008 372 208 20 10.1016/j.virol.2007.10.025 18022665 31. Peltier DC Lazear HM Farmer JR Diamond MS Miller DJ Neurotropic arboviruses induce interferon regulatory factor 3-mediated neuronal responses that are cytoprotective, interferon-dependent, and inhibited by western equine encephalitis virus capsid J Virol 2013 87 1821 33 10.1128/JVI.02858-12 23192868 32. Blakely PK Delekta PC Miller DJ Irani DN Manipulation of host factors optimizes the pathogenesis of western equine encephalitis virus infections in mice for antiviral drug development J Neurovirol 2015 21 43 55 10.1007/s13365-014-0297-8 25361697 33. Gao J Chao J Parbhu KJ Yu L Xiao L Gao F Gao L Ontogeny of angiotensin type 2 and type 1 receptor expression in mice J Renin Angiotensin Aldosterone Syst 2012 13 341 52 10.1177/1470320312443720 22526820 34. Heiserman JP Chen L Kim BS Kim SC Tran A Siebenborn N Knowlton AA TLR4 mutation and HSP60-induced cell death in adult mouse cardiac myocytes Cell Stress Chaperones 2015 20 527 35 10.1007/s12192-015-0577-0 25716072 35. Wang Q Zhou H Gao H Chen SH Chu CH Wilson B Hong JS Naloxone inhibits immune cell function by suppressing superoxide production through a direct interaction with gp91phox subunit of NADPH oxidase J Neuroinflammation 2012 9 32 22340895 36. Sindac JA Yestrepsky BD Barraza SJ Bolduc KL Blakely PK Keep RF Novel inhibitors of neurotropic alphavirus replication that improve host survival in a mouse model of acute viral encephalitis J Med Chem 2012 55 3535 45 10.1021/jm300214e 22428985 37. Dikalov S Griendling KK Harrison DG Measurement of reactive oxygen species in cardiovascular studies Hypertension 2007 49 717 27 10.1161/01.HYP.0000258594.87211.6b 17296874 38. Maghzal GJ Krause KH Stocker R Jaquet V Detection of reactive oxygen species derived from the family of NOX NADPH oxidases Free Rad Biol Med 2012 53 1903 18 10.1016/j.freeradbiomed.2012.09.002 22982596 39. Jung S Aliberti J Graemmel P Sunshine MJ Kreutzberg GW Sher A Analysis of fractalkine receptor CX(3)CR1 function by targeted deletion and green fluorescent protein reporter gene insertion Mol Cell Biol 2000 20 4106 14 10.1128/MCB.20.11.4106-4114.2000 10805752 40. Mogi M Li JM Tsukuda K Iwanami J Min LJ Sakata A Telmisartan prevents cognitive decline partly due to PPAR-gamma activation Biochem Biophys Res Comm 2008 375 446 9 10.1016/j.bbrc.2008.08.032 18715543 41. Raveh A Delekta PC Dobry CJ Peng W Schultz PJ Blakely PK Discovery of potent broad spectrum antivirals derived from marine actinobacteria PLoS One 2013 8 e82318 10.1371/journal.pone.0082318 24349254 42. Delekta PC Dobry CJ Sindac JA Barraza SJ Blakely PK Xiang J Novel indole-2-carboxamide compounds are potent broad-spectrum antivirals active against western equine encephalitis virus in vivo J Virol 2014 88 11199 214 10.1128/JVI.01671-14 25031353 43. Rothe G Valet G Flow cytometric analysis of respiratory burst activity in phagocytes with hydroethidine and 2’,7’-dichlorofluorescein J Leukoc Biol 1990 47 440 8 2159514 44. Braughler JM Hall ED Central nervous system trauma and stroke. I. Biochemical considerations for oxygen radical formation and lipid peroxidation Free Radic Biol Med 1989 6 289 301 10.1016/0891-5849(89)90056-7 2663662 45. Kruman I Bruce-Keller AJ Bredesen D Waeg G Mattson MP Evidence that 4-hydroxynonenal mediates oxidative stress-induced neuronal apoptosis J Neurosci 1997 17 5089 100 9185546 46. Schmued LC Albertson C Slikker W Jr Fluoro-Jade: a novel fluorochrome for the sensitive and reliable histochemical localization of neuronal degeneration Brain Res 1997 751 37 46 10.1016/S0006-8993(96)01387-X 9098566 47. Ogier-Denis E Mkaddem BM Vandewalle A NOX enzymes and Toll-like receptor signaling Semin Immunopathol 2008 30 291 300 10.1007/s00281-008-0120-9 18493762 48. Soucy-Faulkner A Mukawera E Fink K Martel A Jouan L Nzengue Y Requirement of NOX2 and reactive oxygen species for efficient RIG-I-mediated antiviral response through regulation of MAVS expression PLoS Pathog 2010 6 e1000930 10.1371/journal.ppat.1000930 20532218 49. Stegbauer J Lee DH Seubert S Ellrichmann G Manzel A Kvakan H Role of the renin-angiotensin system in autoimmune inflammation of the central nervous system Proc Natl Acad Sci U S A 2009 106 14942 7 10.1073/pnas.0903602106 19706425 50. Platten M Youssef S Hur EM Ho P Han MH Lanz T Blocking angiotensin-converting enzyme induces potent regulatory T cells and modulates Th1- and Th17-mediated autoimmunity Proc Natl Acad Sci U S A 2009 106 14948 53 10.1073/pnas.0903958106 19706421 51. Lanz TV Ding Z Ho PP Luo J Agrawal AN Srinagesh H Angiotensin II sustains brain inflammation in mice via TGF-beta J Clin Invest 2010 120 2782 94 10.1172/JCI41709 20628203 52. Villapol S Balarezo MG Affram K Saavedra JM Symes AJ Neurorestoration after traumatic brain injury through angiotensin II receptor blockage Brain 2015 138 3299 315 10.1093/brain/awv172 26115674 53. Pang T Benicky J Wang J Orecna M Sanchez-Lemus E Saavedra JM Telmisartan ameliorates lipopolysaccharide-induced innate immune response through peroxisome proliferator-activated receptor gamma activation in human monocytes J Hypertens 2012 30 87 96 10.1097/HJH.0b013e32834dde5f 22124178 54. Shao J Nangaku M Inagi R Kato H Miyata T Matsusaka T Receptor-independent intracellular radical scavenging activity of an angiotensin II receptor blocker J Hypertens 2007 25 1643 9 10.1097/HJH.0b013e328165d159 17620961 55. de Kloet AD Liu M Rodriguez V Krause EG Sumners C Role of neurons and glia in the CNS actions of the renin-angiotensin system in cardiovascular control Am J Physiol Regul Integr Comp Physiol 2015 309 R444 58 10.1152/ajpregu.00078.2015 26084692 56. Villapol S Saavedra JM Neuroprotective effects of angiotensin receptor blockers Am J Hypertens 2015 28 289 99 10.1093/ajh/hpu197 25362113 57. Gonzalez AD Wang G Waters EM Gonzales KL Speth RC Van Kempen TA Distribution of angiotensin type 1a receptor-containing cells in the brains of bacterial artificial chromosome transgenic mice Neuroscience 2012 226 489 509 10.1016/j.neuroscience.2012.08.039 22922351 58. de Kloet AD, Wang L, Ludin JA, Smith JA, Pioquinto DJ, Hiller H, et al. Reporter mouse strain provides a novel look at angiotensin type-2 receptor distribution in the central nervous system. Brain Struct Funct. 2014. doi:10.1007/s00429-014-0943-1 [Epub ahead of print] 59. Rasini E Cosentino M Marino F Legnaro M Ferrari M Guasti L Angiotensin II type 1 receptor expression on human leukocyte subsets: a flow cytometric and RT-PCR study Regul Pept 2006 134 69 74 10.1016/j.regpep.2006.01.007 16530863 60. Bermudez J Valero N Mosquera J Vargas R Hernandez-Fonseca JP Quiroz Y Role of angiotensin II in experimental Venezuelan equine encephalitis in rats Arch Virol 2015 160 2395 405 10.1007/s00705-015-2521-0 26156105 61. Sharma A Bhomia M Honnold SP Maheshwari RK Role of adhesion molecules and inflammation in Venezuelan equine encephalitis virus infected mouse brain Virol J 2011 8 197 10.1186/1743-422X-8-197 21529366 62. Kehn-Hall K Narayanan A Lundberg L Sampey G Pinkham C Guendel I Modulation of GSK-3 activity in Venezuelan equine encephalitis virus infection PLoS One 2012 7 4 e34761 10.1371/journal.pone.0034761 22496857 63. Taylor K Kolokoltsova O Patterson M Poussard A Smith J Estes DM Natural killer cell mediated pathogenesis determines outcome of central nervous system infection with Venezuelan equine encephalitis virus in C3H/HeN mice Vaccine 2012 30 4095 105 10.1016/j.vaccine.2012.03.076 22525795

PMC005xxxxxx/PMC5000513.txt

==== Front Vet ResVet. ResVeterinary Research0928-42491297-9716BioMed Central London 37210.1186/s13567-016-0372-7Research ArticlePyruvate kinase is necessary for Brucella abortus full virulence in BALB/c mouse Gao Jianpeng gjp_veterinary@163.com Tian Mingxing tianmx530@126.com Bao Yanqing hunterzap@sina.com Li Peng 1067276714@qq.com Liu Jiameng 792900163@qq.com Ding Chan shoveldeen@shvri.ac.cn Wang Shaohui shwang@shvri.ac.cn Li Tao litao@shvri.ac.cn Yu Shengqing yus@shvri.ac.cn Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Shanghai, People’s Republic of China 25 8 2016 25 8 2016 2016 47 1 8721 4 2016 13 8 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Brucellosis, caused by a facultative intracellular pathogen Brucella, is one of the most prevalent zoonosis worldwide. Host infection relies on several uncanonical virulence factors. A recent research hotpot is the links between carbon metabolism and bacterial virulence. In this study, we found that a carbon metabolism-related pyruvate kinase (Pyk) encoded by pyk gene (locus tag BAB_RS24320) was associated with Brucella virulence. Determination of bacterial growth curves and resistance to environmental stress factors showed that Pyk plays an important role in B. abortus growth, especially under the conditions of nutrition deprivation, and resistance to oxidative stress. Additionally, cell infection assay showed that Pyk is necessary for B. abortus survival and evading fusion with lysosomes within RAW264.7 cells. Moreover, animal experiments exhibited that the Pyk deletion significantly reduced B. abortus virulence in a mouse infection model. Our results elucidated the role of the Pyk in B. abortus virulence and provided information for further investigation of Brucella virulence associated carbon metabolism. the Scientific and Technical Innovation Project of the Chinese Academy of Agricultural ScienceSHVRI-ASTIP-2014-8Yu Shengqing the First-class General Financial Grant from the China Postdoctoral Science Foundation2015M570184Tian Mingxing Shanghai Sailing Program16YF1414600Tian Mingxing National Basic Fund for Research Institutes, which is supported by Chinese Academy of Agricultural Sciences2016JB06Tian Mingxing issue-copyright-statement© The Author(s) 2016 ==== Body Introduction Brucellosis, which is characterized by a febrile disease and infectious abortion in animals, is caused by Brucella spp, and remains one of the most common zoonotic diseases worldwide [1]. As the threat of Brucella to human health and animal husbandry has continued to increase in recent years, this disease has attracted ever more attention from scientific community and governments in affected areas throughout the world [2]. Moreover, Brucella strains have the potential to be used in biological warfare [3]. Therefore, in-depth research of Brucella virulence is truly pressing and meaningful. Brucella, a genus of gram-negative bacteria, can grow in vitro and multiply in both phagocytic cells and non-phagocytic cells. Besides, it has evolved an amazing ability to evade host immunity and establish chronic infection. However, Brucella has no classic virulence factors, such as exotoxins, cytolysins, capsules, fimbria, and endotoxic lipopolysaccharide (LPS) [4]. Up to date, several virulence-associated factors have been identified, which are indispensable for the survival of Brucella in host cells, including a type IV secretion system, a two-component regulatory system composed of regulatory (BvrR) and sensory (BvrS) proteins, cyclic β-1,2-glucans, superoxide dismutase, catalase and urease [4]. Recently, much progress has been made in the study of possible links between carbon metabolism and intracellular bacterial virulence, especially in model intracellular pathogens, such as Listeria monocytogenes, Shigella flexneri, Salmonella entericaserovar typhimurium and Mycobacterium tuberculosis [5–8]. After entering the host cells, intracellular pathogens have to adjust their metabolism to the environmental conditions encountered in its intracellular replicative niche, including low oxygen and nutrient levels, acidic pH and so on [9]. In this process, the regulation of carbon metabolism may directly or indirectly influence the expression of the virulence genes within the host cell and, hence, pathogen virulence [5]. In Brucella, many genes reportedly associated with carbon metabolism are necessary for virulence, such as 6-phosphogluconate dehydrogenase (gnd), phosphoglucose isomerase (pgi), pyruvate carboxylase (pyc) and some erythritol catabolism genes (e.g., eryB, eryC) [9–11]. According to the previous reports, it has been accepted that glucose is mainly catabolized in Brucella through the pentose phosphate pathway in conjunction with the tricarboxylic acid (TCA) cycle [12, 13]. Of these, pyruvate is one of the more important substances that connects the glucose catabolism pathway with TCA cycle, in which several related genes have been shown to be necessary for Brucella virulence. Pyruvate phosphate dikinase (Ppdk), which is involved in classical gluconeogenesis, is required for full virulence in B. abortus [14]. Pyc is an enzyme of the ligase class that catalyzes the irreversible carboxylation of pyruvate to oxaloacetate, which was identified as a virulence-related gene by random mutagenesis [9]. It has been suggested that pyruvate catabolism plays an essential role in the full virulence of Brucella. Our recent study found that pyruvate kinase, which is encoded by the pyk gene (gene locus BAB_RS24320) is associated with B. abortus virulence by PCR-based on signature-tagged mutagenesis (data unpublished). Pyk catalyzes the synthesis of pyruvate from phosphoenolpyruvate (PEP), that is, adenosine diphosphate + phosphoenolpyruvate = adenosine triphosphate + pyruvate, which is required for glucose catabolism through the glycolysis pathway. In this study, we further investigated the role of Pyk on B abortus virulence and found that Pyk plays important roles on the bacterial resistance to oxidative stress, escaping from fusion with lysosome within macrophages, and establishing infection in BALB/c mouse. Materials and methods Ethic statement This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the Institutional Animal Care and Use Committee guidelines set by Shanghai Veterinary Research Institute, the Chinese Academy of Agricultural Sciences (CAAS). Mice (SLAC Experimental Animal Inc., Shanghai, China) were housed in cages with water and food ad libitum under biosafety conditions. Animal handling and procedures were approved by the Committee on the Ethics of Animal Experiments of Shanghai Veterinary Research Institute, CAAS (permit number: SHVRI-mo-0175). Bacterial strains and growth conditions B. abortus strain S2308 was obtained from the Chinese Veterinary Culture Collection Center (Beijing, China) and routinely grown in tryptic soy broth (TSB) (Difco™, BD BioSciences, Franklin Lakes, NJ, USA) or tryptic soy agar (TSA). Escherichia coli strain DH5α was grown on Luria–Bertani medium. When appropriate, 100 μg/mL of ampicillin or 20 μg/mL of chloramphenicol (Sigma–Aldrich Corporation, St. Louis, MO, USA) respectively, were added. All strains and plasmids used in the study are listed in Table 1.Table 1 Strains and plasmids used in the study Strains and plasmids Characteristics Source Brucella abortus S2308 Wild type strain; Smooth phenotype ATCC ∆pyk pyk gene deletion mutant strain; Smooth phenotype This study ∆pyk(Pyk-3 × Flag) Cmr; complementation strain; ∆pyk carrying the complementation plasmid pBBR-pyk-3 × Flag; Smooth phenotype This study Escherichia coli DH5α F− φ80lacZ∆M15 ∆(lacZYA-argF)U169 recA1 endA1 hsdR17(rk−, mk+) phoA supE44 thi-1 gyrA96 relA1 λ− Invitrogen Plasmids pBBR1MCS1 Cmr; Broad-host-range cloning vector [17] pSC Ampr; pUC19 plasmid containing SacB gene [16] pSC-∆pyk Ampr; pSC plasmid containing the ∆pyk fragment; used to construct deletion strain This study p3 × Flag-CMV-14 Ampr; eukaryotic expression plasmid Sigma-Aldrich pBBR-pyk-3 × Flag Cmr; pBBR1MCS1 containing the pyk gene flanked by its upstream and downstream regions containing a C-terminal 3 × flag tag. This study Construction of suicide and complementation plasmids Suicide plasmids were constructed using an overlap PCR assay, as previously reported [15]. Briefly, efficient primers were designed for amplification of a 947-bp upstream fragment and a 995-bp downstream fragment of the pyk gene by a first round of PCR. After purification by gel extraction, the recovered products containing joined flanking sequences were used as templates for a second round of overlap PCR. Then, the PCR product was gel purified, digested with XbaI, and cloned into the XbaI-digested pSC plasmid [15, 16]. The recombinant suicide plasmid pSC-Δpyk was transformed into competent DH5α cells (Invitrogen Corporation, Carlsbad, CA, USA) for propagation and then extracted to construct the mutants. In order to construct the complementation plasmid, the pyk gene was amplified by PCR using the primer pair Cpyk-F/Cpyk-R, the product was recovered, digested with the restriction enzymes KpnI and BamHI, and inserted into the p3 × Flag-CMV-14 plasmid (Sigma-Aldrich) to construct the recombinant plasmid p3 × Flag-pyk, and then the inserted pyk fragment with a 3 × Flag tag fragment was amplified by PCR using the primers Cpyk-F and 3 × Flag-R from the p3 × Flag-pyk plasmid, the fragment was digested with KpnI and XbaI, and inserted into the pBBR1-MCS1 plasmid [17]. The complementation plasmid was designated as pBBR-pyk-3 × Flag. Construction of the pyk mutant and the complementation strain The pyk mutant was constructed by allelic replacement using a two-step strategy, as previously reported [18]. Briefly, competent B. abortus strain S2308 cells were prepared through two washes with ice-cold sterile water and suicide plasmid (0.5–1.0 μg) was transformed into competent cells by electroporation. The single exchanged recombinants were selected by plating on TSA containing ampicillin, and then colonies were inoculated into TSB without antibiotics. The second exchanged recombinants were selected by plating on TSA containing 5% sucrose. All colonies were selected and verified by PCR amplification. The complementation strain was constructed by transforming the plasmid pBBR-pyk-3 × Flag by electroporation, as described above, and the recombinant strain was designated as Δpyk(Pyk-3 × Flag). Western blotting analysis Western blotting analysis was performed to verify the complementation strain Δpyk(Pyk-3 × Flag). The fresh cultural Δpyk(Pyk-3 × Flag) and S2308 strains were harvested, respectively, by centrifugation 8000 × g for 5 min, the pellets were suspended in a mixture of deionized water and 2 × SDS-PAGE loading buffer (Beyotime Institute of Biotechnology, Shanghai, China), and boiled for 5 min. Proteins were separated on a 12.5% SDS polyacrylamide gel and transferred onto nitrocellulose membrane (Whatman®; Sigma-Aldrich). The membrane was blocked for 2 h at room temperature with phosphate-buffered saline (PBS; hyclone) contained 5% skim milk, and then incubated with mouse anti-Flag monoclonal antibody (Sigma-Aldrich) in PBST (PBS containing 0.2% tween-20) overnight at 4 °C. After washing five times with PBST, the membrane was incubated with IRDye 680RD-conjugated donkey anti-mouse polyclonal antibody (LI-COR Biosciences, Lincoln, NE, USA) in PBST for 1 h at room temperature. After washing five times with PBST, protein bands were detected using the Odyssey Infrared Imaging System (LI-COR Biosciences). RNA isolation and real-time qRT-PCR To verify the transcriptional level of the pyk upstream gene bab_RS24315 and the downstream gene bab_RS24325, total RNA was extracted from both S2308 and the pyk mutant by TRlzol reagent (invitrogen), and the bacterial genomic contamination was removed by the TURBO DNA-free kit (Ambion®; Invitrogen). The RNA was quantified by absorption at 260 nm using a NanoVue™ plus spectrophotometer (GE Healthcare Life Sciences, Logan, UT, USA). Then, qRT-PCR was carried out using GoTaq qPCR Master Mix (Promega, Fitchburg, WI, USA) and the Mastercycler ep realplex Real-Time PCR system (Eppendorf, Hamburg, Germany). For each gene, PCRs were performed in triplicate and relative transcription levels were determined by the 2−∆∆Ct method using glyceraldehyde phosphate dehydrogenase (gapdh) as an internal control for data normalization. All primers used for real-time qRT-PCR are listed in Table 2.Table 2 Primers used in the study Primers Oligonucleotide sequence (5′ to 3′) Target genes Products (bp) Cpyk-F GGGGTACCTTGTCCAATATAAAGCGATGAC KpnI, underlined The pyk containing the promoter region 1934 Cpyk-R CGGGATCCAATGCCGGATTTTCCGTCAGCG BamHI, underlined 3 × Flag-R GCTCTAGACAGGGATGCCACCCGGGATC XbaI, underlined The 3 × Flag tag of p3 × Flag-CMV-14 pyk-UF CGGGATCCCGGGGGTTATGGAAAGCAACT The upstream fragment of pyk 947 pyk-UR TGACGACGCAATGCAGGCTCGAGGGTGAAGGTCTGG pyk -DF CCAGACCTTCACCCTCGAGCCTGCATTGCGTCGTCA The downstream fragment of pyk 995 pyk- DR CGGGATCCCGTACGGGTGCGGGTGTTTC In-pyk-F ATGCCGTGCTGAAGGAAGAG The inside fragment of pyk gene 493 In-pyk-R GCGTCAATGATGGTCGAATAGG Out-pyk-F GGGGTACCCCGACGGTGGGAAGGCAAAG The outside fragment of pyk gene 1885 Out-pyk-R CGGGATCCCGGAGCGGCTCCAGAAATCG RT-pyk-F AAAACTGCATCTGGTGGCTG pyk 207 RT-pyk-R GGGCGCTGGATAAAGGAAAG RT-upstream-F ATGACATCAATCGCACGCTG bab_RS24315 161 RT-upstream-R GAAATTCTTTTGGGCGTCGC RT-downstream-F AAGCTGCAAAACCCTGATCG bab_RS24325 209 RT-downstream-R AGCTTGATTGTTCCCCGGTA RT-GAPDH-F GACATTCAGGTCGTCGCCATCA gapdh 188 RT-GAPDH-R TCTTCCTTCCACGGCAGTTCGG Growth curve in TSB and minimal medium Bacterial growth was measured at an optical density at 600 nm (OD600). For growth curve analysis, bacterial strains were incubated in TSB for 24 h, and then diluted with TSB to an OD600 value of 0.01 and cultured in a rotary shaker (200 rpm) at 37 °C. Cultures were taken at appropriate interval and OD600 values were recorded. Bacterial growth in minimal medium was measured as described above except minimal medium was used as the diluting solution. Components of the minimal medium were glucose (10 g/L), yeast extract (1 g/L), (NH4)2SO4 (13.2 g/L), Na2S2O3·5H2O (0.1 g/L), MgSO4 (10 mg/L), MnSO4 (0.1 mg/L), NaCl (5 g/L) and KH2PO4 (3 g/L). The pH was adjusted to 6.8 to 7 [19]. In order to further evaluate the effect of metabolic product (sodium pyruvate) by Pyk catalysis, sodium pyruvate was added into the minimal medium with concentrations of 1, 5 or 10 mM or glucose was replaced by pyruvate as sole carbon source at final concentration of 200 mM in minimal medium. Cell infection assay RAW 264.7 macrophages were used to assess the ability of the pyk mutant to survive intracellularly. The experiment was performed as previously reported [20]. Briefly, the cells were seed in 24-well plates and grown in Dulbecco’s Modified Eagle Medium (DMEM) (Hyclone™; GE Healthcare) supplemented with 10% fetal bovine serum (FBS) (Gibco®; Invitrogen) at 37 °C with 5% CO2 for 24 h. The cell monolayer was washed twice with DMEM and infected with B. abortus S2308 or the pyk mutant at a multiplicity of infection of 100. Bacteria were centrifuged onto the cells at 400 × g for 10 min and the cells were then incubated at 37 °C for 1 h. Non-adherent bacteria were removed by rinsing the wells twice with PBS. To kill extra-cellular bacteria, the cells were incubated with DMEM containing gentamicin (100 μg/mL) for an additional 1 h, washed twice with PBS and the medium was replaced with DMEM containing 2% FBS and 20 μg/mL gentamicin. At 2, 8, 24 and 48 h post-infection, the macrophages were lysed with 0.2% Triton X-100 in sterile water and the live bacteria were enumerated by plating on TSA plate. All assays were performed in triplicate and repeated at least three times and the results are the averages from at triplicate infection samples. Immunofluorescence assay RAW264.7 cells cultured on glass coverslips (Thermo Fisher Scientific, Waltham, MA, USA) were infected with Brucella at a multiplicity of infection of 100. The infected cells were fixed with 3.7% (w/v) paraformaldehyde at 4 °C for 24 h post-infection. The immunofluorescence assay was performed as previously described [15] using rabbit anti-Brucella serum (diluted 1:1000) and Rat anti-LAMP-1 monoclonal antibody [1D4B] (diluted 1:500, Abcam, Cambridge, MA, USA) as the primary antibody, and Alexa Fluor 488-conjugated goat anti-rabbit IgG (diluted 1:1000) and Alexa Fluor 555-conjugated goat anti-rat lgG (diluted 1:1000) (Invitrogen) as the secondary antibody. The coverslips were mounted onto glass slides using Eukitt quick-hardening mounting medium for microscopy (Sigma-Aldrich) and the cells were observed under a Nikon Eclipse 80i microscope (Nikon Corporation, Tokyo, Japan) with 100× oil immersion objective. Images were saved in TIFF format and imported to Adobe Photoshop CS4 (Adobe Systems Incorporated, San Jose, CA, USA), where they were merged using RGB format. To determine the percentage of bacteria positive for the lysosome marker LAMP-1, 100 intracellular bacteria were counted randomly. The assays were performed in triplicate. Stress resistance assay The S2308 strain and the pyk mutant were cultured to mid-logarithmic phase (the value of OD600 ≈ 1.0) at 37 °C in TSB medium, and then the bacterial suspension was diluted with PBS and adjusted to a concentration to 4 × 105 colony-forming units (CFU)/mL. Afterward, 50 μL of bacterial suspension was mixed with 50 μL of the appropriate reagent. The effects of various stress factors were tested as follows. H2O2 was used to determine sensitivity to oxidative stress and added at final concentrations of 0.5, 1 or 1.5 mM. Polymyxin B at concentrations of 50, 100 or 200 μg/mL was used to test sensitivity to cationic bactericidal peptides. Bovine serum and heat-inactivated bovine serum were used to assess resistance to natural serum killing with a bactericidal activity assay. In all tested groups, a negative-control group was introduced by adding 50 μL of PBS to the same bacterial suspension. After exposure for 1 h at 37 °C, the mixtures were rapidly diluted and plated on TSA plates to determine viability. Results are expressed as the mean percentage of the negative control from independent triplicate samples. To determine the ability of the pyk mutant to resist acidic pH, an acid tolerance assay was performed as previously described with some modifications [20]. Briefly, the bacterial suspension of the S2308 strain and the pyk mutant were cultured and diluted to 2 × 107 CFU/mL in TSB with pH of 7.3, 5.5 or 4.5. After 1 h of incubation at 37 °C, cells were serially diluted and plated on TSA to determine the number of bacterial CFU. The percentage of surviving bacteria was calculated with respect to CFU obtained from bacteria incubated in TSB at pH 7.3 (100% survival). Infection of mice Virulence assay using BALB/c mice was performed as reported previously with some modifications [16]. Briefly, 6-week-old female BALB/c mice (n = 6 per group) were intraperitoneally inoculated with 0.1 mL of suspension containing 1 × 106 CFU of the S2308 strain, the pyk mutant or the complementation strain. The survival of the bacteria in mice was evaluated by bacterial enumeration in the spleens at different time points post-infection. At 1 or 5 weeks post-infection, mice were sacrificed by cervical dislocation. The spleens were harvested, and homogenized in 5 mL of PBS-0.2% Triton X-100. After that, serial dilutions of the homogenates were made and plated on TSA plates to determine the bacterial loads. The data are expressed as the log10 CFU per spleen. Besides, spleen weight was measured to evaluate splenomegaly. Statistical analysis Statistical analysis was performed using GraphPad Prism software 5.0 (GraphPad Software Inc., La Jolla, CA, USA). Statistical significance was determined by either an unpaired or two-tailed Student’s t test, or in the case of groups, a one-way analysis of variance followed by the Tukey’s test. A probability (p) values of ≤0.05 were considered significant. Results The pyk mutant and the complementation strain were successfully constructed The pyk mutant was verified by PCR amplification of the inside and outside fragments using respective primers (Figure 1A). The results indicated that a 493-bp inside fragment and a 1885-bp outside fragment were amplified from the S2308 strain, respectively. However, the inside fragment was not amplified from the pyk mutant and the size of outside fragment was obviously shorter than that of S2308 due to deletion of the pyk gene (Figure 1B). In order to further identify the mutant and exclude the possible polar effects of pyk deletion, qRT-PCR was performed to quantify the expression of pyk and its flanking genes at the transcriptional level. The results showed that the pyk gene was not transcribed in the pyk mutant, and transcription of the upstream and downstream genes was not affected (Figure 1C). In addition, the complementation strain Δpyk(Pyk-3 × Flag) was verified by western blotting, as shown in Figure 1D, Pyk-3 × Flag was successfully expressed in the pyk mutant.Figure 1 Identification of the pyk mutant and the complementation strain. A A schematic of the pyk gene and its flanking genes. The inside and outside fragments amplified using respective primers are indicated. B PCR amplification confirmed deletion of the pyk gene in the pyk mutant. Lane M: DNA marker DL2000 (Takara Bio, Inc., Shiga, Japan). Lanes 1–6: amplification of the inside fragment. Lanes 1–4: four different clones of the pyk mutant, no fragment was amplified. Lane 5: the S2308 strain (positive control), a 493-bp fragment was amplified; Lane 6: sterile water (negative control). Lanes 7 and 8: amplification of the outside fragment. Lane 7: the S2308 strain (positive control), a 1885-bp fragment was amplified; Lane 8: the pyk mutant, a 935-bp fragment was amplified. C Real-time qRT-PCR confirmed the deletion of the pyk gene at the transcriptional level. The pyk deletion did not affect expression of the flanking genes. The gene transcriptional level of the pyk mutant was compared with that of the S2308 strain. ***p ≤ 0.001, ns: no significant difference. D Western blotting confirmed expression of pyk in the complementation strain Δpyk(Pyk-3 × Flag). Lane M: prestained protein ladder (Thermo Fisher Scientific); Lane 1: the S2308 strain (negative control), no flag expression was detected; Lane 2: the complementation strain Δpyk(Pyk-3 × Flag), about 55 kDa of the flag expression product was shown. Pyk is required for intracellular replication and trafficking of B. abortus To determine the effect of the pyk gene in intracellular survival, the ability of the pyk mutant to survive within macrophages was assessed at 2, 8, 24 and 48 h post-infection. As shown in Figure 2 there was no significant difference in intracellular survival between the S2308 strain and the pyk mutant at 2 and 8 h post-infection, indicating a similar ability of both strains to invade macrophages. However, a marked decrease in bacterial recovery from RAW264.7 cells infected with the pyk mutant, as compared with that of S2308 infected cells at 24 and 48 h post-infection (Figure 2). These results encouraged us to determine if the difference observed in the intracellular viable counts was a consequence of increased degradation or inactivation of the mutant. To this end, we determined the number of LAMP-1-positive Brucella-containing vacuoles (BCVs) at 4 and 24 h post-infection of RAW264.7 cells with the pyk mutant and the S2308 strain. As shown in Figure 3, the mutant showed a reduced capacity to exclude the lysosome marker LAMP-1 at 24 h post-infection (about 45% co-localization), as compared with the S2308 strain (about 20% co-localization), indicating that deletion of pyk decreased the ability of the Brucella to avoid the fusion of the BCV with lysosome.Figure 2 Intracellular survival within RAW 264.7 macrophages of the S2308 strain and the pyk mutant. Values are means ± standard errors for triplicate infection samples, and the experiments were repeated three times with similar results. **p ≤ 0.01, ***p ≤ 0.001. Figure 3 The pyk mutant was not able to efficiently exclude lysosome-associated membrane protein-1 within RAW264.7 cells. A Representative images of LAMP-1-positive and -negative BCVs. B Determination of the LAMP-1 positive BCVs at 4 and 24 h post-infection of the S2308 strain and the pyk mutant. The percentage of positive BCVs per 100 random BCVs is shown. ***p ≤ 0.001. ns: no significant difference. Deletion of pyk in Brucella impaired its growth in TSB and in minimal medium The Pyk is an important protein in glycolysis, and catalyzation of PEP to pyruvate, accompanied by the release of ATP. To further confirm the role of pyruvate in Brucella growth, we compared the bacterial growth of the pyk mutant with that of the S2308 strain in rich TSB and in minimal medium. As shown in Figure 4A, growth of the pyk mutant was slightly reduced at the logarithmic phase, but reached a similar stationary phase in rich TSB in comparison with the S2308 strain. However, in minimal medium the pyk mutant exhibited a significant growth defect throughout the growth stage, as compared with the S2308 strain (Figure 4B), suggesting that Pyk plays an important role in Brucella growth, especially under the condition of nutrition deprivation. To further assess the effect of pyruvate synthesis on Brucella growth, we assessed the ability of the Brucella to growth in minimal medium containing different concentrations of pyruvate. As shown in Figure 4B, growth of the pyk mutant restored to a similar level of the S2308 strain supplemented with pyruvate at final concentration of 1 mM, when supplemented with 5 or 10 mM of pyruvate, the growth of the mutant was faster than that of the S2308 strain. To further confirm the role of pyruvate in Brucella growth, we replaced glucose by pyruvate as sole carbon source in minimal medium at the concentration of 200 mM, no significant difference was found between the growth of the mutant and the S2308 strain (Figure 3C). These results revealed that the Pyk is necessary for Brucella growth, especially under the condition of nutrition deprivation, and the growth defect was due to the loss of pyruvate synthesis catalyzed by Pyk.Figure 4 Bacterial growth was affected by pyk deletion and recovered by supplementation with sodium pyruvate. A Growth curves in TSB. B Growth curves in minimal medium with or without sodium pyruvate. C Growth curves in minimal medium without glucose or replaced glucose by pyruvate as sole carbon source at concentration of 200 mM. Each point represents the mean for triplicate samples (error bars are within the size of the symbols). The experiment was repeated three times with similar results. *p ≤ 0.05; ***p ≤ 0.001. The pyk mutant exhibited greater sensitivity to H2O2 For Brucella spp. to successfully infect and establish chronic infection in their preferred host, the bacteria must have the ability to resist host bactericidal activity from the innate immune response, such as reactive oxygen and nitrogen species, bactericidal peptides, and low PH within macrophages. To this end, we assessed the ability of the pyk mutant to resist environmental stress factors. The results showed that the pyk mutant displayed higher sensitivity to different concentrations of H2O2, as compared with the S2308 strain. At 1.5 mM H2O2 exposure for 1 h, the mutant exhibited about 50% survival in comparison with 80% survival of the S2308 strain, and the mutant harboring the complementation plasmid pBBR-pyk-3 × Flag recovered resistance to H2O2 (Figure 5A). However, the mutant and the S2308 strain showed similar sensitivity to polymyxin B, bovine serum and low PH (Figures 5B–D).Figure 5 Stress resistance assays. A Sensitivity to H2O2 at concentrations of 0.5, 1 or 1.5 mM. B Sensitivity to polymyxin B at concentrations of 50, 100 or 200 μg/mL. C Sensitivity to bovine serum (BS) and heat inactivated bovine serum (HIBS). D Resistance to low pH. Values are means ± standard errors for triplicate samples. * p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001; ns: no significant difference. The pyk mutant was attenuated in mice The main manifestation of Brucella virulence is the ability to establish chronic infection in the host, therefore, we investigated the capacity of the pyk mutant to establish chronic infection in BALB/c mice. As shown in Figure 6A, the mutant exhibited significantly reduced level of spleenic colonization at 1 and 5 week post-infection. Similarly, the splenomegaly in mice infected with the mutant was less severe than that infected with the S2308 strain (Figure 6B). Besides, when harboring the pBBR1-pyk-3 × Flag plasmid, the pyk complementation strain restored the ability of splenic colonization and induced splenomegaly in infected BALB/c mice at 1 week post-infection (Figures 6C and D). These data suggested that the Pyk plays an important role in Brucella virulence.Figure 6 Pyk is crucial for the virulence of B. abortus in mouse model of infection. A Bacterial loads of the S2308 strain, the pyk mutant in the spleens of BALB/c mouse at 1 and 5 weeks post-infection. B Spleen weight of the S2308 strain and the pyk mutant infected mice at 1 and 5 weeks post-infection. C Bacterial loads of the S2308 strain, the pyk mutant and the complementation strain in the spleens of BALB/c mouse at 1 week post-infection. D Spleen weight of the S2308 strain, the pyk mutant and the complementation strain infected mice at 1 week post-infection *p ≤ 0.05; ***p ≤ 0.001. Discussion Pyk in the glycolysis pathway converts PEP to pyruvate and releases one molecule of ATP. In minimal medium, the pyk mutant was not able to reach a similar level at stationary phase like the S2308 strain, and showed a marked growth defect (Figure 4B). However, in TSB, the mutant exhibited a slight growth defect at the exponential phase, but finally achieved a similar level at the stationary phase (Figure 4A). The growth of the pyk mutant was restored when pyruvate was added, which suggested that the loss of the metabolic product pyruvate is the main reason for defective Brucella growth. It was suggested that Pyk plays an important role in Brucella growth, especially under the condition of nutrition deprivation. In Brucella, it has been reported that gluconeogenesis pathway is very important for full virulence of Brucella, and the classical genes involved in this pathway, ppdk and mae, are responsible for the markedly reduced multiplication of the mutant within macrophages and virulence in mouse model [14]. These observations confirmed the deduction that amino acids could be the preferred carbon source in vivo, which requires a gluconeogenic mechanism [21]. However, some studies suggested the availability of sugars in the replicative niche of intracellular Brucella. Xavier et al. observed that glucose uptake is crucial for increased replication of B. abortus in alternatively activated macrophages and for chronic infection in a mouse model [22]. These results indicated that the glycolytic pathway may also play an important role in metabolism and virulence of intracellular Brucella. Pyk, as an important enzyme for the pyruvate-TCA cycle node, catalyzes PEP to pyruvate irreversibly as the last step of the glycolytic pathway, which plays a significant role in Brucella virulence. Our results are consistent with those reported for other pathogens, such as the enteric pathogen Yersinia pseudotuberculosis, as Pyk resulted in significantly reduced virulence of a Yersinia mutant in a mouse infection model [23]. In order to further explain the attenuated mechanism of the pyk mutant, we analyzed other biological properties of the mutant and found that the pyk mutant was more sensitive to H2O2 than the S2308 strain. In a further study, we used real-time qRT-PCR to analyze transcription levels of genes associated with antioxidant mechanisms, including katA, sodC and oxyR, but found no significant difference in expression levels between the pyk mutant and the S2308 strain (data not shown), suggesting that reduced resistance to oxidative stress of the pyk mutant was barely attributable to the conventional antioxidant mechanism. The change in the outer membrane was also shown to affect sensitivity to oxidative stress [24–26], so the liposaccharide integrity of the mutant was confirmed by silver-staining, but no difference was found between the mutant and the S2308 strain (data not shown). The role of Pyk in B. abortus to resist oxidative stress warrants further investigation. Another manifestation of Brucella virulence is the ability of intracellular survival within target cells. Once taken up, Brucella resides in a vacuole, designated as BCV. BCVs initially fuse with endosome, and then fuse with lysosome to some extent, acquire the lysosome marker LAMP-1. Meanwhile, the BCVs are acidified by lysosome, which is a key step the Brucella needs to express the important virulence components such as Type IV secretion system, to help it to escape the fusion of BCV and lysosome, and then the BCVs re-localize to endoplasmic reticulum, forming permissive replicative Brucella vacuole. Co-localization of BCV and LAMP-1 is a key marker for determining the efficiency of BCV excluding lysosome [27]. At late stage of Brucella trafficking within host cell, the pyk mutant barely excluded the lysosomal marker LAMP-1 (Figure 3), which explained the reason why the mutant was not able to replicate efficiently within macrophages. Therefore, we speculated the mechanism of virulence attenuation for the pyk mutant as defected growth ability under a condition of nutrition deprivation, reduced resistance to oxidative response, and enhanced fusion efficiency with lysosome within host cells. In summary, this study illuminated that the carbon metabolism gene pyk plays important roles on B. abortus growth, especially under the condition of nutrition deprivation, intracellular survival, and establishment of chronic infection in mice. This study provides further insight into the role of Pyk on B. abortus virulence. Jianpeng Gao and Mingxing Tian contributed equally to this work Competing interests The authors declare that they have no competing interests. Authors’ contributions JG and MT participated in design of the study, analyzed the data and prepared the manuscript. JG, MT, YB, PL, JL, CD, SW and TL carried out the experiments. SY designed the study, revised the manuscript and coordinated the research. All authors read and approved the final manuscript. Acknowledgements This work was supported by the Scientific and Technical Innovation Project of the Chinese Academy of Agricultural Science (SHVRI-ASTIP-2014-8), the First-class General Financial Grant from the China Postdoctoral Science Foundation (2015M570184), Shanghai Sailing Program (16YF1414600) and National Basic Fund for Research Institutes, which is supported by Chinese Academy of Agricultural Sciences (2016JB06). ==== Refs References 1. Corbel MJ Brucellosis: an overview Emerg Infect Dis 1997 3 213 221 10.3201/eid0302.970219 9204307 2. Ratushna VG Sturgill DM Ramamoorthy S Reichow SA He Y Lathigra R Sriranganathan N Halling SM Boyle SM Gibas CJ Molecular targets for rapid identification of Brucella spp BMC Microbiol 2006 6 13 10.1186/1471-2180-6-13 16504063 3. Moreno E Moriyon I Brucella melitensis : a nasty bug with hidden credentials for virulence Proc Natl Acad Sci U S A 2002 99 1 3 10.1073/pnas.022622699 11782541 4. Seleem MN Boyle SM Sriranganathan N Brucella : a pathogen without classic virulence genes Vet Microbiol 2008 129 1 14 10.1016/j.vetmic.2007.11.023 18226477 5. Eisenreich W Dandekar T Heesemann J Goebel W Carbon metabolism of intracellular bacterial pathogens and possible links to virulence Nat Rev Microbiol 2010 8 401 412 10.1038/nrmicro2351 20453875 6. Eylert E Schar J Mertins S Stoll R Bacher A Goebel W Eisenreich W Carbon metabolism of Listeria monocytogenes growing inside macrophages Mol Microbiol 2008 69 1008 1017 10.1111/j.1365-2958.2008.06337.x 18627458 7. Munoz-Elias EJ McKinney JD Carbon metabolism of intracellular bacteria Cell Microbiol 2006 8 10 22 10.1111/j.1462-5822.2005.00648.x 16367862 8. Ray K Marteyn B Sansonetti PJ Tang CM Life on the inside: the intracellular lifestyle of cytosolic bacteria Nat Rev Microbiol 2009 7 333 340 10.1038/nrmicro2112 19369949 9. Kohler S Foulongne V Ouahrani-Bettache S Bourg G Teyssier J Ramuz M Liautard JP The analysis of the intramacrophagic virulome of Brucella suis deciphers the environment encountered by the pathogen inside the macrophage host cell Proc Natl Acad Sci U S A 2002 99 15711 15716 10.1073/pnas.232454299 12438693 10. Foulongne V Bourg G Cazevieille C Michaux-Charachon S O’Callaghan D Identification of Brucella suis genes affecting intracellular survival in an in vitro human macrophage infection model by signature-tagged transposon mutagenesis Infect Immun 2000 68 1297 1303 10.1128/IAI.68.3.1297-1303.2000 10678941 11. Kim S Watarai M Kondo Y Erdenebaatar J Si Makino Shirahata T Isolation and characterization of mini-Tn5Km2 insertion mutants of Brucella abortus deficient in internalization and intracellular growth in HeLa cells Infect Immun 2003 71 3020 3027 10.1128/IAI.71.6.3020-3027.2003 12761078 12. Robertson DC McCullough WG The glucose catabolism of the genus Brucella . I. Evaluation of pathways Arch Biochem Biophys 1968 127 263 273 10.1016/0003-9861(68)90225-7 4972340 13. Robertson DC McCullough WG The glucose catabolism of the genus Brucella . II. Cell-free studies with B. abortus (S-19) Arch Biochem Biophys 1968 127 445 456 10.1016/0003-9861(68)90249-X 4235225 14. Zuniga-Ripa A Barbier T Conde-Alvarez R Martinez-Gomez E Palacios-Chaves L Gil-Ramirez Y Grillo MJ Letesson JJ Iriarte M Moriyon I Brucella abortus depends on pyruvate phosphate dikinase and malic enzyme but not on Fbp and GlpX fructose-1,6-bisphosphatases for full virulence in laboratory models J Bacteriol 2014 196 3045 3057 10.1128/JB.01663-14 24936050 15. Tian M Qu J Han X Zhang M Ding C Ding J Chen G Yu S Microarray-based identification of differentially expressed genes in intracellular Brucella abortus within RAW264.7 cells PLoS One 2013 8 e67014 10.1371/journal.pone.0067014 23950864 16. Zhang M Han X Liu H Tian M Ding C Song J Sun X Liu Z Yu S Inactivation of the ABC transporter ATPase gene in Brucella abortus strain 2308 attenuated the virulence of the bacteria Vet Microbiol 2013 164 322 329 10.1016/j.vetmic.2013.02.017 23507429 17. Kovach ME Phillips RW Elzer PH Roop RM 2nd Peterson KM pBBR1MCS: a broad-host-range cloning vector Biotechniques 1994 16 800 802 8068328 18. Kahl-McDonagh MM Ficht TA Evaluation of protection afforded by Brucella abortus and Brucella melitensis unmarked deletion mutants exhibiting different rates of clearance in BALB/c mice Infect Immun 2006 74 4048 4057 10.1128/IAI.01787-05 16790778 19. Gourley CR (2012) Virulence effects and signaling partners modulated by Brucella melitensis light-sensing histidine kinase. PHD thesis, University of Wisconsin-Madison, Department of Pathobiological Sciences, Madison 20. Tian M Qu J Han X Ding C Wang S Peng D Yu S Mechanism of Asp24 upregulation in Brucella abortus rough mutant with a disrupted O-antigen export system and effect of Asp24 in bacterial intracellular survival Infect Immun 2014 82 2840 2850 10.1128/IAI.01765-14 24752516 21. Lamontagne J Forest A Marazzo E Denis F Butler H Michaud JF Boucher L Pedro I Villeneuve A Sitnikov D Trudel K Nassif N Boudjelti D Tomaki F Chaves-Olarte E Guzman-Verri C Brunet S Cote-Martin A Hunter J Moreno E Paramithiotis E Intracellular adaptation of Brucella abortus J Proteome Res 2009 8 1594 1609 10.1021/pr800978p 19216536 22. Xavier MN Winter MG Spees AM den Hartigh AB Nguyen K Roux CM Silva TM Atluri VL Kerrinnes T Keestra AM Monack DM Luciw PA Eigenheer RA Baumler AJ Santos RL Tsolis RM PPARgamma-mediated increase in glucose availability sustains chronic Brucella abortus infection in alternatively activated macrophages Cell Host Microbe 2013 14 159 170 10.1016/j.chom.2013.07.009 23954155 23. Bucker R Heroven AK Becker J Dersch P Wittmann C The pyruvate-tricarboxylic acid cycle node: a focal point of virulence control in the enteric pathogen Yersinia pseudotuberculosis J Biol Chem 2014 289 30114 30132 10.1074/jbc.M114.581348 25164818 24. Corbeil LB Blau K Inzana TJ Nielsen KH Jacobson RH Corbeil RR Winter AJ Killing of Brucella abortus by bovine serum Infect Immun 1988 56 3251 3261 3141287 25. Eisenschenk FC Houle JJ Hoffmann EM Serum sensitivity of field isolates and laboratory strains of Brucella abortus Am J Vet Res 1995 56 1592 1598 8599519 26. Allen CA Adams LG Ficht TA Transposon-derived Brucella abortus rough mutants are attenuated and exhibit reduced intracellular survival Infect Immun 1998 66 1008 1016 9488389 27. von Bargen K Gorvel JP Salcedo SP Internal affairs: investigating the Brucella intracellular lifestyle FEMS Microbiol Rev 2012 36 533 562 10.1111/j.1574-6976.2012.00334.x 22373010

PMC005xxxxxx/PMC5000514.txt

==== Front BMC Health Serv ResBMC Health Serv ResBMC Health Services Research1472-6963BioMed Central London 169410.1186/s12913-016-1694-xResearch ArticleWorking relationships between obstetric care staff and their managers: a critical incident analysis http://orcid.org/0000-0002-7925-3443Chipeta Effie echipeta@medcol.mw 1Bradley Susan Susan.Bradley@city.ac.uk 2Chimwaza-Manda Wanangwa wanangwachi@yahoo.com 1McAuliffe Eilish Eilish.McAuliffe@ucd.ie 31 College of Medicine-Centre for Reproductive Health, Private bag 360, Blantyre 3, Malawi 2 Centre for Maternal and Child Health Research, School of Health Sciences, City University London, 1 Myddelton Street, London, EC1R 1UW UK 3 School of Nursing, Midwifery and Health Systems, University College Dublin, Belfield, Ireland 26 8 2016 26 8 2016 2016 16 1 44126 2 2016 19 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Malawi continues to experience critical shortages of key health technical cadres that can adequately respond to Malawi’s disease burden. Difficult working conditions contribute to low morale and frustration among health care workers. We aimed to understand how obstetric care staff perceive their working relationships with managers. Methods A qualitative exploratory study was conducted in health facilities in Malawi between October and December 2008. Critical Incident Analysis interviews were done in government district hospitals, faith-based health facilities, and a sample of health centres’ providing emergency obstetric care. A total of 84 service providers were interviewed. Data were analyzed using NVivo 8 software. Results Poor leadership styles affected working relationships between obstetric care staff and their managers. Main concerns were managers’ lack of support for staff welfare and staff performance, lack of mentorship for new staff and junior colleagues, as well as inadequate supportive supervision. All this led to frustrations, diminished motivation, lack of interest in their job and withdrawal from work, including staff seriously considering leaving their post. Conclusions Positive working relationships between obstetric care staff and their managers are essential for promoting staff motivation and positive work performance. However, this study revealed that staff were demotivated and undermined by transactional leadership styles and behavior, evidenced by management by exception and lack of feedback or recognition. A shift to transformational leadership in nurse-manager relationships is essential to establish good working relationships with staff. Improved providers’ job satisfaction and staff retentionare crucial to the provision of high quality care and will also ensure efficiency in health care delivery in Malawi. Electronic supplementary material The online version of this article (doi:10.1186/s12913-016-1694-x) contains supplementary material, which is available to authorized users. Keywords Working relationshipsLeadershipJob satisfactionStaff motivationWork performanceDanish Ministry of Foreign Affairshttp://dx.doi.org/10.13039/100009099Irish Aidissue-copyright-statement© The Author(s) 2016 ==== Body Background Malawi is currently facing a severe shortage of human resources for health as it operates with only 33 % of the health care workers needed to effectively deliver health care services to the population [1]. The nurse to population ratio is currently at 1:3,680 compared to the World Health Organisation’s recommended ratio of 1:1,000 [2]. Nurse/midwives provide the bulk of primary health care services, but many rural health centres’ have no full-time nurse or midwife despite the fact that 85 % of Malawi’s population resides in rural areas [3]. Delivery of maternal health care is a particular concern, with maternal mortality rates at 578 per 100,000 live births [4]. Working conditions for nurse/midwives have been characterized by infrequent supervision and support, high and uneven workloads, and inequitable access to training, which have all contributed to low morale and frustration [5–8]. The resulting loss of health care workers undermines health system capacity, as more experienced workers migrate and remaining staff face increased workloads, stress and demotivation, with obvious consequences for standards of care [9, 10]. A growing body of evidence demonstrates the importance of effective working relationships on nurses’ job satisfaction [11, 12]. The effect of job satisfaction on staff retention, patient satisfaction and organizational commitment has been documented [11, 13–15], while positive working relationships between nurses, their colleagues and managers, are among factors perceived to directly affect motivation and performance [16]. Studies have also shown the importance of interpersonal skills and managers’ relational competencies to improve the satisfaction of nurses. Communication, teamwork, conflict resolution and interpersonal skills are important management skills that can help improve manager/employee relationships, employee job satisfaction, quality care and work environments [17]. Chen et al. [18] also observed that work relationships between unit managers and staff promote organizational citizenship behaviours and can lead to low turnover intent in nurses. Further evidence relates the development of burnout to the interpersonal environment of the organization [19]; while organizational commitment to promote staff welfare is linked to decreased staff burnout. Leadership practices are key determinants of staff motivation and organizational performance, with strong and supportive leadership as a strong predictor of staff motivation and morale [16, 20]. It has increasingly been recognized that transformational leadership is a predictor of quality outcomes in health care settings. The key dimensions of transformational leadership are idealized influence, inspirational motivation, intellectual stimulation and individual consideration [21]. This style of leadership involves stimulating followers to perform beyond the level of expectations [21], establishing leadership authority and integrity, and motivating and inspiring subordinates to pursue a shared vision of the future. These directly influence organizational citizenship behaviour and performance, staff well-being, patient safety and staff satisfaction [22]. Managers who use transformational leadership styles recognise and appreciate staff efforts, identify and reward good performance, ensure equal access to opportunities and promote good interpersonal relationships. These actions demonstrate that hospital management are interested in providing a good working environment and promoting staff welfare [23, 24]. This in turn influences staff motivation, increases job satisfaction and results in low staff turnover [25–28]. In contrast, the key elements of transactional leadership are contingent reward, management by exception and laissez-faire leadership [29]. Transactional leadership assumes that punishments and rewards are necessary to motivate people, leading to a manager-subordinate working relationship based on ‘give and take’ if staff meet expected levels of performance [21]. The leader’s focus is on monitoring how well tasks have been accomplished, identifying and correcting problems to maintain desired performance levels [29, 30]; often the leader avoids making any decisions at all. This leadership style is associated with increasedstaff dissatisfaction and turnover. Staff are left feeling unsupported due to a lack of meaningful interaction with their managers, whichinfluences staff decisions on whether or not to stay in their job [13, 25]. Staff burnout, job dissatisfaction, staff turnover and absenteeism are important variables in understanding the impact of transactional leadership on organizational performance. Analysis of these factors is crucial to understanding manager-staff relations and their impact on staff development and delivery of high quality care. Poor or inefficient working relationships are associated with mistrust, chronic stress, and dissatisfaction among nurses, which have a negative impact on organisational performance. Attention to positive working relationships is essential for the development of work environments with low staff burnout or reduced turnover and also where safe and excellent care can be provided to patients and their families [31]. Recent studies on human resources for health in low-income settings have focused on motivation and retention of health care workers in general [13, 32–34]. The impact of health care manager and staff relationships on retention and performance has been mentioned in very few studies [24]. In Malawi, there is little evidence to highlight the impact of the working relationship between managers and nursing staff, despite reports that poor relationships cause distress [35] and many qualified nurses continue to leave the health service. Along with clinical officers, the enrolled and technician cadres of nurse/midwife are the mainstay of the Malawian health service at the primary care level [8, 36]. This study was part of a larger project, Health Systems Strengthening for Equity (HSSE), whose goal was to expand the evidence base in support of effective use of mid-level providers (MLPs) in maternal and neonatal health. HSSE aimed to increase recognition and effective use of MLPs, and advocate for an enabling environment that optimizes their performance in order to strengthen health systems. Improving human resource management (HRM) is a crucial issue for Malawi’s Ministry of Health (MOH). To date, there are limited data on health workers’ perceptions of the impact of their relationships with health facility managers on retention and performance. Understanding the work environment for nurses/midwives and how they relate with their managers is crucial to ensure that they are well supported and enabled to deliver a good standard of service, especially to the rural population. This can assist in the development of realistic strategies to retain nurse/midwives working in primary care facilities or districts and improve their performance. This study therefore sought to understand how nurse/midwives perceive their relationship with their managers. Methods Study design This qualitative exploratory research study was part of the larger HSSE study. In-depth interviews with facility-based health care providers were done using Critical Incident Analysis (CIA). The critical incident technique [37] is a flexible tool that uses probing questions to elicit events that have particular importance for participants. This methodology is often used to explore events that respondents feel have been critical to their experience of their job [38]. Study setting and population This was a near national study that cut across Malawi and involved 25 of Malawi’s 28 districts. Participants were selected from government district hospitals, Christian Health Association of Malawi (CHAM) health facilities, and a sample of health centres providing emergency obstetric care. Information circulars were sent out to facilities a week in advance, inviting participation. Nurse/midwives were often located in the maternity unit, but maternity and/or facility in-chargesalso assisted in identifying other staff involved in obstetric care who were located elsewhere in the facility. A purposive sample was used to recruit eligible respondents. These had to have performed at least one of the Emergency Obstetric Care (EmOC) Signal Functions1 in the last 3 months and to have experienced an incident within those 3 months that had made them seriously consider leaving their job. A total of 84 eligible health care personnel within selected facilities participated in this study. Data collection Data collection took place from October-December 2008. The CIA interview (Additional file 1) was an anonymous, semi-structured interview designed to identify specific incidents or moments of high salience that had a pivotal impact on a person’s experience of their job. To avoid confusing the word ‘critical’ with clinical emergencies or medical errors, participants were simply asked, “In the past 3 months has there ever been a time when something happened to make you seriously consider leaving your job?” A series of probing questions were then used to invite participants to:Describe the incident; Identify the events/factors leading up to it; Recount how the incident had made them feel; Describe any impact it had on their performance; and Discuss where they would go if they did leave the facility. Most interviews were in English and were recorded and transcribed verbatim in Microsoft Word. A few were conducted in Chichewa, a common local language, at the participant’s request. These interviews were transcribed in Chichewa then translated into English by researchers who were fluent in both languages. Data analysis Data were analyzed using NVivo 8 qualitative software [39] by a team of experienced researchers familiar with the context and the existing literature. A process of inductive and deductive coding was used to identify emerging themes [40]. The main emerging thematic areas were further expanded into sub-nodes during data analysis. Detailed descriptors of each node allowed the analysis teams to validate the content of nodes and discuss their coding and interpretations of the data in detail to improve inter-coder reliability and enhance dependability of the analysis. Results Demographics of the study population Eighty-four health workers participated in this study. Table 1 outlines participating cadres as categorized in the Malawi Health Service Strategic Plan [36].Table 1 Health worker participation in the study, by cadre Cadre Total Female Male Nurse-Midwife Technicians (NMT) 40 35 (88 %) 5 (12 %) Enrolled Nurse/Midwives (ENM) 12 12 (100 %) 0 Registered Nurse/Midwives (RN/M) 11 10 (91 %) 1 (9 %) Clinical Officers (CO) 13 2 (15 %) 10 (77 %) 1 unknown Medical Assistants (MA) 8 1 (12.5 %) 7 (87.5 %) Total 84 60 (71%) 24 (29%) The majority of respondents (69 %) had seriously considered leaving their post as a result of the incident they described. The most common factors reported were related to issues with managers. Themes identified within this category were challenges in the working relationship with managers and lack of managerial support for staff performance and welfare. Underlying these were problems in communication between managers and staff. This paper reports on those respondent’s who felt pushed to the brink of leaving their posts. However, it is worth noting that the remaining participants (31 %) who were demotivated, but had not seriously considered leaving, described similar experiences when they talked about interactions with their managers. Challenges in working relationships Open criticism and a negative, fault-finding attitude were dominant themes in the relationship between management and MLPs. Many respondents were frustrated by management behavior and supervision practices that looked for mistakes and accused them. They felt demotivated and their work performance was affected. “I don’t work well because I am always in hot soup everyday…Everyday she finds a mistake to shout at me without any proper reason.” (NMT, 3142) Others reported unwillingness to report for duties because they received threats from their managers each time they made a slight mistake. “What they look on are the mistakes you do, not the good things you have done.” (ENM, 4122) This negatively affected morale and for some MLPs meant they had no desire for work. The hierarchy between management and staff led to incidences of poor treatment, particularly of junior staff and new recruits. This left staff feeling they were not treated like human beings, while other colleagues had been driven to leave. “People have left the hospital, people have joined NGOs, because of the attitudes towards new recruits…the way they speak and the way they supervise you is more of a picking somebody…or picking on your personal weaknesses…they want to show their superiority by intimidating others.” (CO, 3032) Others reported incidences of managers shouting at junior staff instead of helping them. This degrading treatment in their interactions with managers included being shouted at in front of colleagues and patients, or being treated harshly, making staff feel their work was not being appreciated “…because when they shout at me, it’s like I have done nothing…to their patients.” (NMT, 1031). Others reported how this impacted on retention. “If these people are really willing to retain their health worker they need to change their attitudes towards their juniors or their subordinates. That is very important.” (NMT, 3012) Favoritism by management was reported as a significant demotivating factor. MLPs complained that management showed overt preferences regarding who accessed in-service training (upgrading or refresher courses), even when trainings were not relevant to them. “…there’s segregation…I have been working here for 4 years and if there are trainings like PMTCT, which most of it is for maternity, they were taking other people whom they know…I have gone only once to attend a course.” (NMT, 1061) The same was reported for participation in workshops or seminars. “No, no…I don’t go for workshops. She [Matron] doesn’t consider me in any other field. I can say that when I go for training this month I should expect 6 months or more than that to go for another training, yet my fellow friends can go for training every week, and every time the workshops are advertised.” (NMT, 3142) This unfairness led to frustrations and negatively affected work performance. Favoritism in the way salary top-up allowances were administered was also reported. MLPs complained that these are not paid equally, especially in CHAM hospitals. “We were told that those who started work earlier will get higher top-up allowances than those who just started. However, the allowances were increased and those who have worked for 2 years received more than those who have worked for many years.” (NMT, 4073) Unfairness was also described in the unequal disbursement of salary advances or loans, giving the impression that some cadres were less important than others. “I was looking for a loan to pay for school fees…she [administrator] said…we do not have the loan to give to people…barely a week [later] some clinical officers went there to ask for the loans and she gave them.” (Community ENM, 4072) This lack of transparency generated distrust towards management among nurse/midwives, but some staff also described incidents where their leaders openly demonstrated lack of trust in them, affecting their hard working spirit and confidence. Some reported feeling insecure and afraid in case their boss sent bad reports to their employer, which might even lead to their suspension from duty. “…my job being at stake now. Each time I carry out my job I only think of may be somebody is going to report such a thing. So I am really working under pressure. Working under such circumstances is very dangerous.” (CO, 3032) Lack of managerial support for staff performance and welfare MLPs were acutely aware of their need for supportive supervision, particularly in maternal care, as “…labor ward is a delicate area…” (NMT, 4121) Staff commented on overwhelming workloads in maternity wards and fear of maternal death. These difficulties were most apparent when they found themselves alone on the wards with no one else to help them, or struggling to find senior staff to assist and mentor them. “So not only when something has happened then the management should come in, but we want them supervising and supporting us always. But because of this maternal death, it’s when they came saying that we didn’t care for this woman…but we were already complaining that this management team isn’t supporting us, so we really felt bad.” (NMT, 4121) Junior staff also reported that they did not get the necessary support from seniors when problems arose. In addition, some managers were thought to have insufficient appreciation of the particular challenges involved in maternity care. “This matron is not a midwife so he doesn’t understand what happens in maternity. So mostly…he is fond of pointing out mistakes.” (RN/M in-charge, 1011) Respondents described the impact they felt supportive supervision would have across a range of measures. These included identifying weaknesses, facilitating skills improvement and performance, and providing a mechanism for junior staff to learn from more experienced colleagues. “With good support, then we can be a performer.”(RN/M, 1011) Others tried to be proactive in patient care but were demoralized when management did not take action on their decisions or requests, or failed to act upon suggestions fast enough to impact on patient outcomes. “…if I want something to be done to a certain patient, an idea that can benefit the patient, and then management cannot act or provide what is needed, I feel like I have not helped the patient and I am doing nothing.” (NMT, 1091) MLPs reported working for many months without hearing from their managers or supervisors on how they were performing. “…I have worked for 10 months…but they do not say anything like ‘you are doing your work well’ so you don’t know your weaknesses.” (ENM, 4091) Staff felt they would benefit from being told if they were doing well, instead of their managers just keeping quiet. Others complained that their managers did not recognize or acknowledge good services or performance. They also mentioned the critical impact of not being appreciated by their managers for the work they do, and how motivating it would be to receive even a small recognition of how hard they try in difficult circumstances. “Everyone needs to be appreciated when you have done a good job.” (NMT, 4121) Appraisal that only offered negative feedback was reported to have a detrimental effect on performance, leaving some MLPs demotivated and lacking enthusiasm for work. “…it really affected my performance. I would say for about 2 days I didn’t touch a patient…If you are demotivated, you don’t have a feeling to work and at the end you find out that the patients are the sufferers.” (RN/M, 3041) Managers’ failure to consider personal needs left nurses feeling unvalued and unsupported. If staff approached management about problems at home many were rebuffed. Managers would often say that they were not responsible for staff welfare. “…if my welfare is not taken care of, I don’t think I will be at work place attending to patients while I have a problem at home. I will not work because I want to solve my problem at home. This definitely affects my work performance.” (CO, 3091) Many of the concerns reported by MLPs were linked to a perceived lack of management skills, particularly in terms of communication. There were frequent references to the need for open communication and for management to listen to staff concerns, as staff should have a voice. The lack of respectful communication, such as shouting, harshness and lack of attention to staff ideas, was thought to have an impact on nurses’ intentions to leave the facility. “I have seen some staff running away from the hospital going for another one. Because there has not been good communication or relationship between the boss and the nurse…the way they communicate to the subordinate.” (RN, 3041) The same individual suggested that, “…Ministry [of Health] should make the opportunities to have managers go through such a process…leadership skills, conflict management, team management, these kind of things, they would be helpful.” Discussion Efforts to improve health service leadership are crucial to the provision of high quality care. Attention must be paid to equip nurse managers with effective leadership skills and tools that would help them to build an effective leadership style appropriate for their contextual environments. However, the findings from this study show a negative picture of the management and staff relationship in Malawian health facilities. Despite considerable evidence on the benefits of transformational leadership, such as staff motivation, stimulating creativity and innovation, improved retention and decreased burnout [41–43], transactional leadership styles and behavior were a common feature of health workers’ narratives. Management by exception, which is significantly correlated with nursing turnover, was commonplace and staff were demoralized by open criticism and fault-finding attitudes. The hierarchical nature of the health care system was reflected in the harsh treatment of junior staff, as well as other disrespectful interactions, such as being shouted at by managers. Many managers were perceived to display a lack of concern for people and demonstrated poor relationship behaviors. It is clear that the current leadership model in Malawi is not based on existing theoretical understandings and causes considerable distress to staff, including pushing them to consider leaving their posts. The MOH needs to urgently reconsider its HRM policy and set in motion focused and explicit efforts to train managers at all levels in the requisite skills, knowledge and, most importantly, attitudes, to support, motivate and engage the health workforce. Respondents reported unfairness in the way managers interacted with them including overt favoritism, a lack of confidence or trust in staff and unfairness in allocation benefits, such as training or allowances. These were key drivers of staff dissatisfaction and are destructive to the working relationship between manager and staff [32, 44, 45]. They generate a lack of trust that has implications for workplace relationships and organizational commitment [46] and may have consequences for patient care [47]. These findings are consistent with other studies conducted in sub-Saharan Africa, which have shown that health system favoritism enhanced feelings of injustice leading to staff demotivation [44, 48], but add to them by showingthe potential impact on staff attrition. Unless this hidden behavioral aspect of the work environment is addressed, nurses are likely to continue to leave the health sector for more attractive employment opportunities elsewhere. A manager who wants to have an effective and cohesive team needs to be honest, realistic, and fair when it comes to interactions and expectations. This could be achieved by adopting a more transformative leadership style, based on fairness, empathy, trust and empowerment of health workers, to build staff confidence and treat staff equally [22, 49]. Healthy practice environments, where nurses feel respected and valued, positively impact on staff satisfaction, retention and organisational performance [50]. Staff retention improves when staff feels supported by their nurse manager and this is often linked to a manager’s approachability, openness and balance when dealing with problems that arise during work [51]. The lack of positive contributions from nurse managers affects junior staff since they operate in a context where they suffer accusations for making mistakes. This problem has been largely attributed to inadequate supervision and mentoring. Effective clinical learning environments are characterized by their non-hierarchical nature [52, 53] and positive mentoring supervisory relationships [49]. Mentoring promotes interaction between staff and managers and facilitates the acquisition of skills and knowledge. Promoting the growth and development of junior staff is a major issue in light of the Malawi government’s efforts to alleviate the human resources crisis in the health sector. The Emergency Human Resources Program and any further new plans to boost nurse/midwife numbers will be undermined if the growing cohort of newly qualified health professionals remain dissatisfied due to a lack of supervisory support [7] or find themselves without supportive HRM when they reach their posts. Supervisory support assures health workers of someone who is on their side and can help resolve problems they encounter in their work environment. In Malawi, nurse/midwives are the mainstay of maternal and newborn health care service provision [54]. Supporting their performance and advancing their knowledge and skills is crucial and is one of the strongest predictors of nursing staff satisfaction in the workplace [51]. However, in Malawian health care settings, transactional leadership characteristics and behavior commonly manifest through managers’ minimal support for these cadres, staff reporting lack of feedback on performance, as well as staff concerns, lack of recognition and appreciation of staff, and unequal access to training opportunities that were based on favoritism, rather than need. Supportive leadership is a key element of transformational leadership. A leader should provide practical support for staff and promote development of knowledge, skills and abilities to improve quality of patient care, as well as paying attention to staff concerns and offering helpful, positive feedback on performance and appreciation [22]. Effective leadership skills will have a positive impact on staff morale, job satisfaction and turnover, and in the delivery of safe and high-quality patient care [55]. For supervisory support to improve, training to build the capacity of managers in mentorship, coaching and role modeling is crucial. This would help create a stable and supportive environment for professional growth and development, and encourage junior staff to learn from senior ones [20]. An additional challenge identified by participants was the lack of appreciation or understanding that nurse managers have of the difficulties staff face in their current work environment. The stress of working in maternity wards without adequate management support and management’s failure to take action on requests or make timely decisions on patient care had an impact on staff retention and was reported as a major concern. The importance of supportive leadership behavior for job satisfaction and the intention to stay in nursing has been described previously [56–58]. Stress and leadership factors continue to impact on nursing staff’s turnover intentions [25] while support from supervisors and leaders can have demonstrable effects. These include decreased turnover intent [59], moderation of the stress-satisfaction relationship [60], reduction of emotional exhaustion and buffering of the negative effects of the job environment [61]. Apart from stress and inadequate management support, the experience of maternal and neonatal deaths, or fear of being involved in a maternal death, were reported to be significant factors in staff demotivation and caused some staff to seriously consider leaving [62]. This is a particular concern in the context of extreme staff shortages. Health care managers with effective leadership skills are an essential component of the solution for ending the staff shortage, but explicit attention to training of these cadres in leadership skills and behaviours is currently inadequate. Implementing strategies to ensure effective leadership is paramount. It is crucial that policy makers take steps to develop and promote viable health service leadership, based on existing theoretical understandings and evidence, to achieve the goal of providing quality care for health care consumers especially in resource constrained settings like Malawi. A core perception of staff in this study was that management did not care about their welfare. Requests for assistance were often rebuffed or some cadres were helped while others were not, leaving some staff feeling unvalued and unimportant. This is typical of a transactional, laissez-faire style of leadership, where leaders demonstrate uncaring attitudes and avoid making decisions or taking any responsibility for staff personal needs [30]. The resource-poor context and low salaries in the Malawian health system force many health care workers to depend on salary advances and loans. Paying attention to how these are awarded is important to improving performance and retention of health workers. Employees in an organization evaluate the extent to which the organization values their contributions or cares about their well-being and is ready to help them. When perceived organizational support is high, employees are happier, more engaged and more committed to the organization [51]. As such, nurse managers need to treat employees fairly with regards to distribution of resources and outcomes since employees constantly check how they are treated in comparison to their colleagues [63]. This is important, especially in the health care context and culture in Malawi, where inter-professional rivalry is a strong feature [64, 65]. It is the comparison with others that leads to a sense of being treated unfairly, suggesting inequity in the distribution of resources and opportunities. The extent to which the nurse manager demonstrates empathy, consideration and ability to meet the needs of the team members has been emphasized as an important element of supportive supervision [66]. Limitations The main purpose of this study was to identify tipping points that made participants feel demotivated or seriously think about leaving their jobs. As such, the incidents recounted were necessarily of a negative nature and it may be the case that a different focus would have revealed instances of positive leadership behaviour in this context. Generalizability of the findings is a concern due to uncertainty whether these individual narratives are representative of the larger MLP population. Future research into positive examples of nurse-manager relationships could be used to identify transformational leadership behaviours in this context and to describe factors enabling or blocking this management style. In Malawi, rural health centres are often understaffed resulting in more severe workloads than in hospitals. However, only a small percentage (10 %) of participants from health centres’ were interviewed in this study and yet their work conditions are different from those working in hospitals. In addition, the topic under discussion was sensitive and some of the MLP were not very comfortable to reveal their concerns to outsiders for fear of reprisals or even risk of losing their job. Others considered this as an opportunity to air their concerns and find solutions to their problems. This put the interviewers in an awkward position since they had to maintain their position and integrity as a researcher and not a counsellor/adviser. Another limitation was that this study focussed only on views of staff. Nevertheless, similar concerns were voiced across a range of nursing and clinical cadres, enhancing confidence in the trustworthiness of the results and indicating that poor relationships were commonplace. It would, however, be interesting to explore managers’ perceptions of their working relationships with health facility staff. It would also be preferable to triangulate qualitative data on staff allegations of unfair access to training or loans with a review of facility records. However, record keeping and information system challenges in Malawi would have made this impossible at the time the study was undertaken. Conclusion Findings from this qualitative analysis identified several factors that influenced obstetric care providers’ demotivation and intention to leave. The pervasive and negative impact of poor management-staff relations and lack of support for staff performance and welfare were compounded by a lack of transparency in HRM practices, particularly in access to training and resources. A model of transactional leadership behavior prevailed, evidenced by management by exception and lack of feedback or recognition from managers. These factors demotivate health workers and undermine their efforts. The importance of transformational leadership in nurse-manager relationships cannot be overemphasized. A shift to this style of leadership in Malawi is urgently needed in order to improve the working relationships between managers and staff. This will not only improve providers’ job satisfaction and staff retention, but will also ensure efficiency in health care delivery in Malawi. Additional file Additional file 1: Critical Incident Analysis Instrument. (DOC 30 kb) Abbreviations CHAMChristian health association of Malawi CIACritical incident analysis COClinical officer EmOCEmergency obstetric care ENMEnrolled nurse-midwife HRMHuman resource management HSSEHealth systems strengthening for equity MLPMid-level providers MOHMinistry of health NMTNurse-midwife technician PMTCTPrevention of mother to child transmission RN/MRegistered nurse- midwife 1 Basic EmOC-administer parenteral antibiotics; administer uterotonic drugs; administer parenteral anticonvulsants for pre-eclampsia and eclampsia; perform manual removal of placenta; perform removal of retained products of conception (e.g., manual vacuum aspiration, dilation and curettage); perform assisted vaginal delivery (e.g., vacuum extractor); perform neonatal resuscitation (with bag and mask). Comprehensive EmOC-all the above, plus perform surgery (e.g., caesarean section); perform blood transfusion. Acknowledgements We would like to thank all service providers who participated in this study. We specifically recognize the contributions made by Dr. Francis Kamwendo and Dr. Frank Taulo in the overall management of this study in Malawi. Dr. Kamwendo was lead PI in Malawi and played a key role in the design of this study, collection of data and analysis. Dr. Taulo was the overall overseer of the Malawi HSSE team as Director of the Centre for Reproductive Health, which housed this project. He participated in the design of this study and was supportive throughout its implementation. Funding The Health Systems Strengthening for Equity project was funded by the Advisory Board of Irish Aid and the Danish Ministry of Foreign Affairs. The sponsors were not directly involved in the conduct of this study and no external support has been received for publishing this article. Availability of data and materials The qualitative data upon which this analysis was conducted are not publicly available due to ethical concerns regarding confidentiality of participants and the sensitive nature of some of the areas of enquiry. Further, consent was not obtained from participants to share information from interview transcripts with third parties not involved in the research and none of the research ethics committees who oversaw this study approved the sharing of such information. Authors’ contributions All authors listed on this manuscript have made substantial contributions to this work. The following are the contributions made by the authors: EC drafted this paper and participated in field work, data analysis/interpretation and submission of this manuscript. SB participated in the study design, data analysis, drafting/revision of the paper and its final approval. WC supported field coordination of this study and participated in the data collection/analysis and revised this paper. EM participated in the study design, data analysis and interpretation of data, extensively revised the paper and approved the final manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate The study was approved by the College of Medicine Research and Ethics Committee (COMREC), Malawi; and by the Institutional Review Boards of Trinity College, Dublin, and Columbia University, New York. All participants were fully apprised of the purpose of the research, assured of confidentiality and asked to provide written informed consent. All data and records were rendered anonymous by the use of a unique identity number. ==== Refs References 1. Palmer D Tackling Malawi’s Human Resources Crisis Reprod Health Matters 2006 14 27 27 39 10.1016/S0968-8080(06)27244-6 16713877 2. Ngoma D Human Resources for Health (HRH) in Malawi 2012 Lilongwe National Organisation of Nurses and Midwives of Malawi 3. National Statistical Office of Malawi Population and Housing Census 2008 Zomba National Statistical Office 4. National Statistical Office of Malawi Malawi MDG Endline Survey 2014 Zomba National Statistical Office 5. Bradley S District health managers’ perceptions of supervision in Malawi and Tanzania Hum Resour Health 2013 11 43 10.1186/1478-4491-11-43 24007354 6. Chimwaza W What makes staff consider leaving the health service in Malawi? Hum Resour Health 2014 12 17 10.1186/1478-4491-12-17 24641840 7. Manafa O Retention of health workers in Malawi: perspectives of health workers and district management Hum Resour Health 2009 7 65 10.1186/1478-4491-7-65 19638222 8. Ministry of Health Blantyre M Human Resources in the Health Sector: Towards a Solution Government of Malawi 2004 9. Aitken JM Kemp J HIV/AIDS, Equity and Health Sector Personnel in Southern Africa. EQUINET Discussion Paper 12 2003 Harare Regional Network for Equity in Health in Southern Africa (EQUINET) and Oxfam, GB 10. Troy P Wyness L McAuliffe E Nurses’ experiences of recruitment and migration from developing countries: a phenomenological approach Hum Resour Health 2007 5 1 10.1186/1478-4491-5-15 17224048 11. Adams A Bond S Hospital nurses’ job satisfaction, individual and organizational characteristics J Adv Nurs 2000 32 3 536 543 10.1046/j.1365-2648.2000.01513.x 11012794 12. Force VM The relationship between effective nurse management and nursing retention J Nurs Manag 2005 35 7–8 336 341 13. Abualrub RF Alghamdi MG The impact of leadership styles on nurses’ satisfaction and intention to stay among Saudi nurses J Nurs Manag 2012 20 5 668 678 10.1111/j.1365-2834.2011.01320.x 22823223 14. AL-Hussami M Study of nurses’ job satisfaction: The relationship to organizational commitment, perceived organizational support, transactional leadership, transformational leadership, and level of education Eur J Sci Res 2008 22 2 286 295 15. Zaghloul AA Al-Hussaini MF Al-Bassam NK Intention to stay and nurses’ satisfaction dimensions J Multidiscip Healthc 2008 1 51 10.2147/JMDH.S3804 21197333 16. Germain PB Cummings G The Influence of nurse leadership on nurse performance: a systematic review J Nurs Manag 2010 18 4 425 439 10.1111/j.1365-2834.2010.01100.x 20609047 17. Soto Fuentes P Skills for nurses in the field of management and administration: Contemporary challenges to the profession Aquichan 2014 14 1 10.5294/aqui.2014.14.1.7 18. Chen CHV The effect of leader-member exchange, trust, supervisor support on organizational citizenship behavior in nurses J Nurs Res 2008 16 4 321 328 10.1097/01.JNR.0000387319.28010.5e 19061178 19. Leiter MP Maslach C The impact of interpersonal environment on burnout and organisational commitment J Organ Behav 1998 9 297 308 10.1002/job.4030090402 20. Frankel A What Leadership Styles Should Senior Nurses Develop? Nurs Times 2008 104 23 24 21. Bass BM Leadership and Performance Beyond Expectations 1985 New York The Free Press 22. West M Leadership and Leadership Development in Healthcare: The Evidence Base 2015 London Faculty of Medical Leadership and Management 23. Manongi RN Marchant TC Bygbjerg IC Improving motivation among primary health care workers in Tanzania: a health worker perspective Hum Resour Health 2006 4 6 10.1186/1478-4491-4-6 16522213 24. Mbindyo PM Developing a tool to measure health worker motivation in district hospitals in Kenya Hum Resour Health 2009 7 40 10.1186/1478-4491-7-40 19457237 25. Coomber B Barriball KL Impact of job satisfaction components on intent to leave and turnover for hospital-based nurses: A review of the research literature Int J Nurs Stud 2007 44 2 297 314 10.1016/j.ijnurstu.2006.02.004 16631760 26. Cowden T Cummings GG Profetto-Mcgrath J Leadership practices and staff nurses’ intent to stay: a systematic review J Nurs Manag 2011 19 4 461 477 10.1111/j.1365-2834.2011.01209.x 21569143 27. McAuliffe E Understanding job satisfaction amongst mid-level cadres in Malawi: the contribution of organizational justice Reprod Health Matters 2009 17 33 80 90 10.1016/S0968-8080(09)33443-6 19523585 28. Rad AMM Yarmohammadian MH A study of relationship between managers’ leadership style and employees’ job satisfaction Leadersh Health Serv 2006 19 2 11 28 10.1108/13660750610665008 29. Avolio BJ Bass BM Jung DI Re-examining the components of transformational and transactional leadership using the Multifactor Leadership Questionnaire J Occup Organ Psychol 1999 72 441 462 10.1348/096317999166789 30. Casida J Parker J Staff nurse perceptions of nurse manager leadership styles and outcomes J Nurs Manag 2011 19 4 478 486 10.1111/j.1365-2834.2011.01252.x 21569144 31. American Association of Critical-Care Nurses AACN Standards for establishing and sustaining healthy work environments: A journey to excellence Am J Crit Care 2005 14 3 187 197 15840893 32. Blaauw D Comparing the job satisfaction and intention to leave of different categories of health workers in Tanzania, Malawi, and South Africa Glob Health Action 2013 6 10 3402 33. Fogarty L Job satisfaction and retention of health-care providers in Afghanistan and Malawi Hum Resour Health 2014 12 11 10.1186/1478-4491-12-11 24533615 34. Mangham L Addressing the human resource crisis in Malawi’s health sector: employment preferences of public sector registered nurses ESAU Working Paper 2007 London Overseas Development Institute 35. Maluwa VM Moral distress in nursing practice in Malawi Nurs Ethics 2012 19 2 196 207 10.1177/0969733011414968 22277794 36. Ministry of Health Malawi Malawi Health Sector Strategic Plan 2011–2016 2011 Lilongwe Ministry of Health 37. Flanagan JC The Critical Incident Technique Psychol Bull 1954 51 4 327 358 10.1037/h0061470 13177800 38. MacLachlan M McAuliffe E Critical incidents for psychology students in a refugee camp Couns Psychol Q 1993 6 1 3 11 10.1080/09515079308254487 39. NVivo qualitative data analysis Software; QSR International Pty Ltd. Version 8, 2008. 40. Green J Thorogood N Qualitative Methods for Health Research 2004 London Sage 41. Nielsen K The mediating effects of team and self-efficacy on the relationship between transformational leadership, and job satisfaction and psychological well-being in healthcare professionals: a cross-sectional questionnaire survey Int J Nurs Stud 2009 46 9 1236 1244 10.1016/j.ijnurstu.2009.03.001 19345946 42. Weberg D Transformational leadership and staff retention: an evidence review with implications for healthcare systems Nurs Adm Q 2010 34 3 246 258 10.1097/NAQ.0b013e3181e70298 20562573 43. Willis-Shattuck M Motivation and retention of health workers in developing countries: a systematic review BMC Health Serv Res 2008 8 247 10.1186/1472-6963-8-247 19055827 44. Faye A Developing a tool to measure satisfaction among health professionals in sub-Saharan Africa Hum Resour Health 2013 11 30 10.1186/1478-4491-11-30 23826720 45. Thompson SA The top 10 qualities of a good nurse manager Am J Nurs 2004 104 8 64C 64D 10.1097/00000446-200408000-00053 15621973 46. Gilson L Trust in health care: theoretical perspectives and research needs J Health Organ Manag 2006 20 5 359 375 10.1108/14777260610701768 17087400 47. Gilson L Palmer N Schneider H Trust and health worker performance: exploring a conceptual framework using South African evidence Soc Sci Med 2005 61 7 1418 1429 10.1016/j.socscimed.2004.11.062 16005777 48. Mbindyo PL Gilson L Contextual influences on health worker motivation in district hospitals in Kenya Implement Sci 2009 4 43 10.1186/1748-5908-4-43 19627590 49. Sherman R Pross E Growing Future Nurse Leaders to Build and Sustain Healthy Work Environments at the Unit Level Online J Issues Nurs 2010 15 1 50. Aiken LH Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction JAMA 2002 288 16 1987 1993 10.1001/jama.288.16.1987 12387650 51. Bailey J The Effects of Hospital Unit Nurse Leaders’ Perceived Follower Support on Nursing Staff Performance Outcomes 2014 Atlanta Georgia State University 52. Fretwell JE Creating a ward learning environment: the sisters’ role Nurs Times 1983 79 34 42 44 6555746 53. Orton HD Davis BD Ward learning climate and student nurse response Research into Nurse Education 1983 London Croom Helm 54. Lobis S Expected to deliver: alignment of regulation, training, and actual performance of emergency obstetric care providers in Malawi and Tanzania Int J Gynaecol Obstet 2011 115 3 322 327 10.1016/j.ijgo.2011.09.008 22036057 55. Givens RJ Transformational Leadership: The Impact on Organizational and Personal Outcomes Emerg Leadersh J 2008 1 1 4 24 56. Albaugh J Keeping nurses in nursing: the profession’s challenge for today Urol Nurs 2003 23 3 193 199 12861736 57. Blanchard K Waghorn T Mission Possible 1997 New York McGraw-Hill 58. Taunton RL Manager leadership and retention of hospital staff nurses West J Nurs Res 1997 19 2 205 26 10.1177/019394599701900206 9078856 59. Delobelle P Job satisfaction and turnover intent of primary healthcare nurses in rural South Africa: a questionnaire survey J Adv Nurs 2011 67 2 371 383 10.1111/j.1365-2648.2010.05496.x 21044134 60. Abualrub RF Omari FH Abu A Rub AF The moderating effect of social support on the stress-satisfaction relationship among Jordanian hospital nurses J Nurs Manag 2009 17 7 870 878 10.1111/j.1365-2834.2009.01007.x 19793244 61. Constable JF Russell DW The effect of social support and the work environment upon burnout among nurses J Hum Stress 1986 12 20 26 10.1080/0097840X.1986.9936762 62. Bradley S Too few staff, too many patients: a qualitative study of the impact on obstetric care providers and on quality of care in Malawi BMC Pregnancy Childbirth 2015 15 65 10.1186/s12884-015-0492-5 25880644 63. Folger R Konovsky MA Effects of procedural justice on reactions to pay decisions Acad Manag Rev 1989 32 1 115 130 10.2307/256422 64. Bradley S McAuliffe E Mid-level providers, in emergency obstetric and newborn health care: factors affecting their performance and retention within the Malawian health system Hum Resour Health 2009 7 14 10.1186/1478-4491-7-14 19228409 65. McAuliffe E Measuring and managing the work environment of the mid-level provider-the neglected human resource Hum Resour Health 2009 7 13 10.1186/1478-4491-7-13 19228391 66. McGilton KS Development and psychometric testing of the supportive supervisory scale J Nurs Scholarsh 2009 42 2 366 372

PMC005xxxxxx/PMC5000515.txt

==== Front Genome BiolGenome BiolGenome Biology1474-75961474-760XBioMed Central London 104710.1186/s13059-016-1047-4ErratumErratum to: A survey of best practices for RNA-seq data analysis Conesa Ana aconesa@ufl.edu 12Madrigal Pedro pm12@sanger.ac.uk 34Tarazona Sonia 25Gomez-Cabrero David 6789Cervera Alejandra 10McPherson Andrew 11Szcześniak Michal Wojciech 12Gaffney Daniel J. 3Elo Laura L. 13Zhang Xuegong 1415Mortazavi Ali ali.mortazavi@uci.edu 16171 Institute for Food and Agricultural Sciences, Department of Microbiology and Cell Science, University of Florida, Gainesville, FL 32603 USA 2 Centro de Investigación Príncipe Felipe, Genomics of Gene Expression Laboratory, 46012 Valencia, Spain 3 Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA UK 4 Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, Anne McLaren Laboratory for Regenerative Medicine, Department of Surgery, University of Cambridge, Cambridge, CB2 0SZ UK 5 Department of Applied Statistics, Operations Research and Quality, Universidad Politécnica de Valencia, 46020, Valencia, Spain 6 Unit of Computational Medicine, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, 171 77 Stockholm, Sweden 7 Center for Molecular Medicine, Karolinska Institutet, 17177 Stockholm, Sweden 8 Unit of Clinical Epidemiology, Department of Medicine, Karolinska University Hospital, L8, 17176 Stockholm, Sweden 9 Science for Life Laboratory, 17121 Solna, Sweden 10 Systems Biology Laboratory, Institute of Biomedicine and Genome-Scale Biology Research Program, University of Helsinki, 00014 Helsinki, Finland 11 School of Computing Science, Simon Fraser University, Burnaby, V5A 1S6BC Canada 12 Department of Bioinformatics, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University in Poznań, 61-614 Poznań, Poland 13 Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, FI-20520 Turku, Finland 14 Key Lab of Bioinformatics/Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing, 100084 China 15 School of Life Sciences, Tsinghua University, Beijing, 100084 China 16 Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA 92697-2300 USA 17 Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697 USA 26 8 2016 26 8 2016 2016 17 1 18117 8 2016 17 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.issue-copyright-statement© The Author(s) 2016 ==== Body Erratum During editing of the article by Conesa et al. [1], an error was introduced to some of the citations, such that incorrect references were provided for some articles the second time they were cited. The following sentences are affected: Algorithms that quantify expression from transcriptome mappings include RSEM (RNA-Seq by Expectation Maximization) [40], eXpress [41], Sailfish [35] and kallisto [42] among others. These methods allocate multi-mapping reads among transcript and output within-sample normalized values corrected for sequencing biases [35, 41, 43]. The citation for Sailfish should be [34] (Patro et al., Nat Biotechnol. 2014;32:463–4) in both sentences. Additional factors that interfere with intra-sample comparisons include changes in transcript length across samples or conditions [50], positional biases in coverage along the transcript (which are accounted for in Cufflinks), average fragment size [43], and the GC contents of genes (corrected in the EDAseq package [21]). The citation for EDAseq should be [20] (Risso et al. BMC Bioinformatics. 2011;12:480) The NOISeq R package [20] contains a wide variety of diagnostic plots to identify sources of biases in RNA-seq data and to apply appropriate normalization procedures in each case. The citation for NOISeq should be [19] (Tarazona et al. Nucleic Acids Res. 2015;43:e140) These effects can be minimized by appropriate experimental design [51] or, alternatively, removed by batch-correction methods such as COMBAT [52] or ARSyN [20, 53]. The citations for ARSyN should be [19, 53] (Tarazona et al. Nucleic Acids Res. 2015;43:e140, Nueda et al. Biostatistics. 2012;13:553–66). All these approaches are generally hampered by the intrinsic limitations of short-read sequencing for accurate identification at the isoform level, as discussed in the RNA-seq Genome Annotation Assessment Project paper [30]. The citation for the RGASP article should be [29] (Engström et al. Nat Methods. 2013;10:1185–91). We refer the reader to [30] for a comprehensive comparison of RNA-seq mappers. This citation should be [29] (Engström et al. Nat Methods. 2013;10:1185–91). The online version of the original article can be found under doi:10.1186/s13059-016-0881-8. ==== Refs References 1. Conesa A Madrigal P Tarazona S Gomez-Cabrero D Cervera A McPherson A Genome Biol 2016 17 13 10.1186/s13059-016-0881-8 26813401

PMC005xxxxxx/PMC5000516.txt

==== Front Scand J Trauma Resusc Emerg MedScand J Trauma Resusc Emerg MedScandinavian Journal of Trauma, Resuscitation and Emergency Medicine1757-7241BioMed Central London 29710.1186/s13049-016-0297-1Original ResearchPosttraumatic levels of liver enzymes can reduce the need for CT in children: a retrospective cohort study Bruhn Peter James +45 42737406peterjamesbruhn@gmail.com 1Østerballe Lene lene.osterballe@gmail.com 1Hillingsø Jens jens.hillingsoe@rh.regionh.dk 1Svendsen Lars Bo lars.bo.svendsen@regionh.dk 1Helgstrand Frederik freh@regionsjaelland.dk 21 Department of Surgical Gastroenterology, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark 2 Department of Surgical Gastroenterology, Køge Hospital, University of Copenhagen, Lykkebækvej 1, 4600 Køge, Denmark 25 8 2016 25 8 2016 2016 24 1 1044 3 2016 22 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Computed tomography (CT) is the gold standard in the initial evaluation of the hemodynamically stable patient with suspected liver trauma. However, the adverse effects of radiation exposure are of specific concern in the pediatric population. It is therefore desirable to explore alternative diagnostic modalities. Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) are hepatic enzymes, which are elevated in peripheral blood in relation to liver injury. The aim of the present study was to investigate a potential role of normal liver transaminase levels in the decision algorithm in suspected pediatric blunt liver trauma. Methods Retrospective analysis of consecutively collected data from children (0–17 years) with blunt liver trauma, admitted to a single trauma centre in Denmark, between 2000 and 2013. Patients underwent abdominal CT during initial evaluation, and initial AST and/or ALT was measured. Based on local guidelines, we set the threshold for blood AST and ALT level to 50 IU/L. Nonparametric statistical tests were used. Results Sixty consecutive children with liver injury following blunt abdominal trauma were enrolled in the study. All patients with normal AST and/or ALT level were treated conservatively with success. Information on both AST and ALT was available in 47 children. Of these 47 children, three children had AST and ALT levels ≤50 IU/L. These children suffered from grade I liver injuries, and were treated conservatively with no complications. Discussion All children who presented with blunt liver injury and AST and ALT levels ≤50 IU/L did not require treatment. These findings indicate that AST and ALT could be included in an updated management algorithm as a screening method to avoid abdominal CT. Notable limitations to the study was the retrospective method of data collection, without inclusion of a control group. Conclusions CT seems superfluous in the initial evaluation of hemodynamically stable children with suspected blunt liver injury and blood AST and ALT levels ≤50 IU/L. Keywords Pediatric liver injuryLiver transaminasesComputed tomographyBlunt liver injuryissue-copyright-statement© The Author(s) 2016 ==== Body Background Blunt liver trauma is one of the most common and serious abdominal injuries [1]. Persisting hemodynamic instability in these patients, in spite of resuscitation attempts, should lead to surgical intervention [2]. However, the hemodynamically stable patient with no signs of other intraabdominal injury is usually treated conservatively, as is the case in 85 % of blunt liver injuries [2–6]. In some cases, in the hemodynamically stable patients with hepatic bleeding, surgery may yet be avoided, by arterial embolization [7]. Computed tomography (CT) of the abdomen is the gold standard in the initial evaluation of the hemodynamically stable blunt trauma patient, because it displays optimal sensitivity and specificity in diagnosing parenchymal injuries [8, 9]. Emergency CT is expensive and offers several limitations, including: risk of contrast agent allergy, contrast nephropathy, possible need for sedation, and is time consuming [9, 10]. Additionally, each abdominal CT increases the lifetime risk of cancer by 0.18 % in 1-year-old infants [9, 11]. Thus, it is desirable to find other diagnostic tools in the initial evaluation of the pediatric liver trauma patient [12, 13]. Transaminases are mitochondrial and cytoplasmic enzymes that are found in hepatocytes, neurons, pancreatic and muscle cells [14, 15]. The two most common transaminases are aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Raised blood levels of AST and ALT are found when hepatocytes are damaged from inflammation, infection, trauma or surgical intervention [14–20]. AST and ALT elevation has been known to correlate to liver injury, and have been shown to occur immediately after the trauma [16–20]. Furthermore, it has been shown that high-grade (AAST grades III-VI) liver injury results in higher AST and ALT levels than low-grade liver injury (AAST grades I-II) [5, 11]. One study has indicated that ALT is most ideal to detect liver injury, compared to AST and other haematological markers [11]. Several studies have investigated the role of liver transaminase levels and FAST (focused assessment sonography in trauma) in initial diagnostic management of pediatric blunt liver traumas [1, 21–27]. The studies have found that liver transaminase levels as well as FAST are valuable screening tools in the decision algorithm in blunt liver injury. The studies, however, vary in focus and inclusion criteria. Thus, no consensus has been reached with regard to inclusion of liver enzymes in a specific decision algorithm. The present study investigates whether liver transaminase levels are of value in the decision algorithm in pediatric blunt liver trauma, as a screening method to avoid emergency CT. Methods We retrospectively analyzed consecutively registered data in a local database from all children (0–17 years) with blunt liver injury, who were initially admitted to the same level 1 trauma centre in Denmark, between 2000 and 2013. Data from the database were supported by data from patient files. We included patients, who underwent abdominal CT during initial evaluation, and in whom initial AST and/or ALT were measured. Outcomes were: age, gender, blood AST level, blood ALT level, FAST result, CT-diagnosed liver injury grade, management approach and presence of CT-diagnosed free fluid. Liver injury grade was classified by CT according to the AAST scale [5]. Before study analyses, based on local guidelines, we set the threshold for blood AST and ALT upper margin normal reference range level to 50 IU/L. This study was exempt from approval by the Danish Capital Region Research Ethics Committee. Statistical analysis Continuous variables were presented with median and interquartile range (IQR) and compared by the Mann-Whitney U test. Continuous variables in three or more groups were compared by the Kruskal-Wallis H test. Nominal variables were presented as observed frequencies and percentages and compared by Fisher’s exact test. The level of significance was defined as p < 0.05. SPSS v19.0 for Mac was used for data analysis. Results From 2000 to 2013, 117 children were admitted to our level 1 trauma centre with blunt liver injury. In total, 57 patients were excluded due to missing CT (n = 26) and AST or ALT (n = 31). Thus, in total, 60 children with liver injury following blunt trauma were enrolled in the study. Patient characteristics are presented in Table 1.Table 1 General characteristics of the study population Age, median (IQRa), years 11 (7–15) Gender, n (%)  Female 21 (35)  Male 39 (65) FASTb, n (%)  Positive 32 (65.3)  Negative 17 (34.7) AAST liver injury grade, n (%)  Grade 1 5 (8.3)  Grade 2 18 (30)  Grade 3 22 (36.7)  Grade 4 13 (21.7)  Grade 5 2 (3.3)  Grade 6 0 (0.0) Free fluid in CTc, n (%)  Present 44 (73.3)  Absent 16 (26.7) ASTd and/or ALTe level > 50 IU/L, n (%)  Present 44 (93.6)  Absent 3 (6.4) aInterquartile range, bfocused assessment sonography in trauma, ccomputed tomography, daspartate aminotransferase, ealanine aminotransferase Blood AST and ALT were measured in 48 and 59 patients, respectively, and showed significant positive correlation to liver trauma grade (p = 0.002 for AST, and p = 0.022 for ALT), Table 2. AST as well as ALT levels were significantly higher in patients with high-grade (AAST grades III-VI) liver injury (p < 0.001 for AST, and p = 0.003 for ALT), compared to patients with low-grade liver injury (AAST grades I-II).Table 2 Liver enzyme levels in relation to liver injury grade Blood ASTa level (n = 38), median (IQRb), IU/L 379 (140–570.25) Blood ALTc level (n = 48), median (IQR), IU/L 303 (139–476) AST level, median (IQR)  Grade 1 36 (29.5–225.5)  Grade 2 136 (95–375.5)  Grade 3 515 (405.75–688.5)  Grade 4 451 (283.75–642)  Grade 5 462 (270–462)  Grade 6 - ALT level, median (IQR)  Grade 1 21 (13–191)  Grade 2 239 (124–432)  Grade 3 438 (230.5–501.75)  Grade 4 351 (255–492)  Grade 5 307.5 (285–307.5)  Grade 6 - aaspartate aminotransferase, binterquartile range, calanine aminotransferase Both enzymes were measured in 47 cases. No cases were observed where an elevated AST was not accompanied by elevated ALT, or vice versa. Descriptions of FAST were available in 49 cases, 32 of which were positive. Two patients presented with positive FAST and AST and/or ALT ≤ 50 IU/L. Positive FAST results did not show significant correlation to liver injury grade (p = 0.716). Furthermore, positive FAST results did not show significant correlation to whether patients were managed conservatively, by arterial embolization or by surgery (p = 0.997). Liver enzyme levels > 50 IU/L did not show correlation to management approach (p = 0.755), as presented in Table 3.Table 3 Liver enzyme levels in relation to management approach Conservative treatment Surgery Arterial embolization Total ASTa and ALTb ≤ 50 IU/L 3 0 0 3 AST and/or ALT > 50 IU/L 37 3 4 44 Total 40 3 4 47 aaspartate aminotransferase, balanine aminotransferase Of the 47 patients, where both liver enzyme levels were measured and CT undertaken, three (6.4 %) children with grade I liver injuries presented with AST and ALT equal to or below 50 IU/L. These children were treated conservatively and were discharged after 0 (<24 h), 1 and 3 days, respectively. There were no following complications in either case. Two of these patients initially presented with positive FAST. All patients with AST and/or ALT ≤ 50 IU/L (n = 3) were treated conservatively with success. In the 47 patients, where both AST and ALT was available, invasive treatment was performed in seven cases, either in the form of arterial embolization (n = 4) or surgery (n = 3). In all of these cases, the child had presented with AST as well as ALT levels above 250 IU/L. Of the conservatively treated patients, 60.4 % (n = 32/53) presented with AST and/or ALT levels above 250 IU/L. Discussion In this cohort of retrospectively analysed pediatric CT verified blunt liver injuries, all but three children initially presented with raised AST and/or ALT levels (>50 IU/L). These children’s liver injuries did not require treatment. All patients with normal levels of AST and/or ALT underwent conservative treatment. In addition, we found a significant correlation between AST and/or ALT levels and grade of liver injury determined by AAST levels on CT. AST and ALT were equally reliable in detecting liver injury. In many centres, contrast enhanced CT of the abdomen is presently mandatory in the diagnosis and treatment algorithm of a hemodynamically stable pediatric patient with suspected liver injury following relevant blunt abdominal trauma [28–30]. In agreement with others, we found that initial evaluation of AST and ALT might be a useful diagnostic tool to predict the need for CT. This could result in time, cost and safety benefits in relation to the initial evaluation of hemodynamically stable patients with potential blunt liver injury [31]. On the basis of our results, we propose a revised algorithm for management of pediatric blunt liver injury, which includes evaluation of AST and ALT as a screening method to avoid abdominal CT (Fig. 1). The revised algorithm introduces a possibility to omit immediate abdominal CT scan in the case of a hemodynamically stable child without abdominal pain, along with normal liver enzyme levels, leading to immediate transfer to the surgical ward. We propose an overnight observation period for these children based on the results of St Peter et al. in a prospective study [6]. It should be emphasized that any clinical suspicion of treatment requiring trauma, should lead to immediate radiological examination.Fig. 1 Revised algorithm for evaluation and treatment of pediatric blunt liver injury We applied an upper reference value of AST and ALT of 50 IU/L based on local guidelines. Clinically applied reference ranges for AST and ALT varies with sex and age [32], and therefore we set the upper reference value for both enzymes to a common value well above the locally applied values for children of both sexes. Future studies may find that our threshold is too conservative, and if so, the use of emergency CT could be reduced even more. Several studies have been performed on the diagnostic capability of evaluation of various threshold levels for AST and ALT [1, 21–27]. The previous studies analysed pediatric patient data, but had varying focus concerning primary condition leading to CT, whether or not FAST was performed, and which upper liver transaminase reference value was applied. Overall, our results are supported by these previous studies, which indicated that evaluation of liver enzyme levels could indeed be applied as an argument to abstain from emergency abdominal CT [1, 21–27]. Some of these studies showed remarkably high sensitivity and specificity in diagnosing blunt liver injury with application of varying liver enzyme reference ranges [21–23]. Our study is consistent with the existing literature in the context that the presence of significant liver injury can indeed be expected to result in raised liver enzyme levels. We did not find significant correlation between FAST result and liver injury grade or management approach. However, FAST is easy to repeat and does play an integral role in the evaluation of blunt traumas suspected for bleeding [33]. In our cohort, 6.4 % of the emergency CT scans could have been omitted by application of AST and ALT levels >50 IU/L as a screening method. However, our cohort consisted exclusively of patients with liver trauma admitted to a single level 1 trauma center, where pre-hospital selection was applied. It can be assumed that the proportion of patients with non-treatment requiring liver injuries and low liver enzyme levels, will be higher in primary centers, where wider pre-hospital selection criteria are applied. Therefore, it is our assumption that in the situation where the only indication for emergency CT scan is the suspicion of liver injury, considerably more than 6.4 % of these scans can be avoided by application of the mentioned screening method. Naturally, there is a risk of missing other organ injury; the extent and consequences of these missed injuries can only be speculated, and will probably be negligible after repeated clinical examinations. Specifically, St Peter et al. showed that an abbreviated bedrest protocol is safe in the case of low-grade blunt liver and spleen injury, without risk of complications after discharge [6]. A notable limitation of our study was in the method of data collection. Data was collected retrospectively through a local database and supported with data from patient files. Furthermore, it was not possible to obtain data on the registration rate in the database. This led to exclusion of 57 out of 117 patients in our study. It can only be speculated if the possible missed inclusions have led to selection bias. The study was conducted without inclusion of a control group. Finally, in 13 patients we only had data on either AST or ALT levels. Due to the mentioned limitations present results need to be confirmed in a prospective study setting. Conclusions In conclusion, the present study supports that emergency abdominal CT for suspected blunt liver injuries in hemodynamically stable and unaffected children can be omitted in the presence of normal liver enzyme levels, provided that no other indication for emergency CT is present. The children should be admitted for observation in the ward, and undergo CT if trauma related symptoms occur, intensify, or a later increase in AST and/or ALT is found. Acknowledgements Peter Svenningsen, Martin Sillesen and Andreas A. Rostved for critical revision, proofreading and data presentation. Authors’ contributions Peter James Bruhn contributed with literature search, study design, data collection, data analysis, data interpretation, writing and critical revision. Lene Østerballe contributed with study design, data collection, data analysis, data interpretation and critical revision. Jens Hillingsø contributed with data interpretation and critical revision. Lars Bo Svendsen contributed with data interpretation and critical revision. Frederik Helgstrand contributed with data analysis, data interpretation and critical revision. All authors read and approved the final manuscript. Competing interests Peter James Bruhn, Lene Østerballe, Jens Hillingsø, Lars Bo Svendsen and Frederik Helgstrand declare that they have no competing interests to disclose. ==== Refs References 1. Kaya U Çavuş UY Karakılıç ME Erdem AB Aydın K Işık B Is computed tomography necessary to determine liver injury in pediatric trauma patients with negative ultrasonography? Eur J Trauma Emerg S 2013 39 6 641 646 10.1007/s00068-013-0322-2 2. Notrica DM Eubanks JW 3rd Tuggle DW Maxson RT Letton RW Garcia NM Nonoperative management of blunt liver and spleen injury in children: Evaluation of the ATOMAC guideline using GRADE J Trauma Acute Care Surg 2015 79 4 683 693 10.1097/TA.0000000000000808 26402546 3. Yousaf M Diamond T Conservative management of major liver trauma Ulster Med J 2000 69 2 156 158 11196728 4. Holmes JF Sokolove PE Brant WE Palchak MJ Vance CW Owings JT Identification of children with intra-abdominal injuries after blunt trauma Ann Emerg Med 2002 39 5 500 509 10.1067/mem.2002.122900 11973557 5. Tinkoff G Esposito TJ Reed J Kilgo P Fildes J Pasquale M American Association for the Surgery of Trauma Organ Injury Scale I: spleen, liver, and kidney, validation based on the National Trauma Data Bank J Am Coll Surg 2008 207 5 646 655 10.1016/j.jamcollsurg.2008.06.342 18954775 6. St Peter SD Aguayo P Juang D Sharp SW Snyder CL Holcomb GW 3rd Follow up of prospective validation of an abbreviated bedrest protocol in the management of blunt spleen and liver injury in children J Pediatr Surg 2013 48 12 2437 2441 10.1016/j.jpedsurg.2013.08.018 24314183 7. Saltzherr TP van der Vlies CH van Lienden KP Beenen LF Ponsen KJ van Gulik TM Improved outcomes in the non-operative management of liver injuries HPB (Oxford) 2011 13 5 350 355 10.1111/j.1477-2574.2011.00293.x 21492335 8. Badger SA Barclay R Campbell P Mole DJ Diamond T Management of liver trauma World J Surg 2009 33 12 2522 2537 10.1007/s00268-009-0215-z 19760312 9. Frush DP Donnelly LF Rosen NS Computed tomography and radiation risks: what pediatric health care providers should know Pediatrics 2003 112 4 951 957 10.1542/peds.112.4.951 14523191 10. Tan KK Bang SL Vijayan A Chiu MT Hepatic enzymes have a role in the diagnosis of hepatic injury after blunt abdominal trauma Injury 2009 40 9 978 983 10.1016/j.injury.2009.02.023 19535055 11. Weishaupt D Grozaj AM Willmann JK Roos JE Hilfiker PR Marincek B Traumatic injuries: imaging of abdominal and pelvic injuries Eur Radiol 2002 12 6 1295 1311 10.1007/s00330-002-1462-7 12042933 12. Cook SH Fielding JR Phillips JD Repeat abdominal computed tomography scans after pediatric blunt abdominal trauma: missed injuries, extra costs, and unnecessary radiation exposure J Pediatr Surg 2010 45 10 2019 2024 10.1016/j.jpedsurg.2010.06.007 20920722 13. Larson DB Johnson LW Schnell BM Goske MJ Salisbury SR Forman HP Rising use of CT in child visits to the emergency department in the United States, 1995–2008 Radiology 2011 259 3 793 801 10.1148/radiol.11101939 21467249 14. Harrah JD Holmes EC Paulson DF Ketcham AS Serum enzyme alterations after extensive surgical procedures Ann Surg 1969 169 3 300 304 10.1097/00000658-196903000-00002 5380854 15. Nickell WK Allbritten FF Jr Serum transaminase content related to tissue injury Surgery 1957 42 1 240 248 13442895 16. Miller K Kou D Sivit C Stallion A Dudgeon DL Grisoni ER Pediatric hepatic trauma: does clinical course support intensive care unit stay? J Pediatr Surg 1998 33 10 1459 1462 10.1016/S0022-3468(98)90474-2 9802790 17. Nishida T Fujita N Nakao K A multivariate analysis of the prognostic factors in severe liver trauma Surg Today 1996 26 6 389 394 10.1007/BF00311924 8782295 18. Cogbill TH Moore EE Feliciano DV Jurkovich GJ Morris JA Mucha P Jr Hepatic enzyme response and hyperpyrexia after severe liver injury Am Surg 1992 58 7 395 399 1616183 19. Kaku N Short-term and long-term changes in hepatic function in 60 patients with blunt liver injury J Trauma 1987 27 6 607 614 10.1097/00005373-198706000-00004 2439702 20. Strawn T Williams HC Flint LM Jr Prognostic significance of serum biochemical changes following liver trauma Am Surg 1980 46 2 111 115 7369629 21. Oldham KT Guice KS Kaufman RA Martin LW Noseworthy J Blunt hepatic injury and elevated hepatic enzymes: a clinical correlation in children J Pediatr Surg 1984 19 4 457 461 10.1016/S0022-3468(84)80275-4 6481594 22. Hennes HM Smith DS Schneider K Hegenbarth MA Duma MA Jona JZ Elevated liver transaminase levels in children with blunt abdominal trauma: a predictor of liver injury Pediatrics 1990 86 1 87 90 2359686 23. Puranik SR Hayes JS Long J Mata M Liver enzymes as predictors of liver damage due to blunt abdominal trauma in children South Med J 2002 95 2 203 206 10.1097/00007611-200295020-00010 11846245 24. Karaduman D Sarioglu-Buke A Kilic I Gurses E The role of elevated liver transaminase levels in children with blunt abdominal trauma Injury 2003 34 4 249 252 10.1016/S0020-1383(02)00188-2 12667774 25. Bevan CA Palmer CS Sutcliffe JR Rao P Gibikote S Crameri J Blunt abdominal trauma in children: how predictive is ALT for liver injury? Emerg Med J 2009 26 4 283 288 10.1136/emj.200X.062703 19307392 26. Sola JE Cheung MC Yang R Koslow S Lanuti E Seaver C Pediatric FAST and elevated liver transaminases: An effective screening tool in blunt abdominal trauma J Surg Res 2009 157 1 103 107 10.1016/j.jss.2009.03.058 19592033 27. Lee WC Kuo LC Cheng YC Chen CW Lin YK Lin TY Combination of white blood cell count with liver enzymes in the diagnosis of blunt liver laceration Am J Emerg Med 2010 28 9 1024 1029 10.1016/j.ajem.2009.06.005 20825933 28. Leschied JR Mazza MB Davenport MS Chong ST Smith EA Hoff CN Inter-radiologist agreement for CT scoring of pediatric splenic injuries and effect on an established clinical practice guideline Pediatr Radiol 2015 46 1 8 29. Stylianos S Evidence-based guidelines for resource utilization in children with isolated spleen or liver injury J Pediatr Surg 2000 35 2 164 169 10.1016/S0022-3468(00)90003-4 10693659 30. Leinwand MJ Atkinson CC Mooney DP Application of the APSA evidence-based guidelines for isolated liver or spleen injuries: a single institution experience J Pediatr Surg 2004 39 3 487 490 10.1016/j.jpedsurg.2003.11.014 15017575 31. Ritchie AH Williscroft DM Elevated liver enzymes as a predictor of liver injury in stable blunt abdominal trauma patients: case report and systematic review of the literature Can J Rural Med 2006 11 4 283 287 17054829 32. Stirnadel-Farrant HA Galwey N Bains C Yancey C Hunt CM Children’s liver chemistries vary with age and gender and require customized pediatric reference ranges Regul Toxicol Pharmacol 2015 26190302 33. Holmes JF Brant WE Bond WF Sokolove PE Kuppermann N Emergency department ultrasonography in the evaluation of hypotensive and normotensive children with blunt abdominal trauma J Pediatr Surg 2001 36 7 968 973 10.1053/jpsu.2001.24719 11431759

PMC005xxxxxx/PMC5000517.txt

==== Front Biotechnol BiofuelsBiotechnol BiofuelsBiotechnology for Biofuels1754-6834BioMed Central London 59010.1186/s13068-016-0590-2ResearchFunctional characterization of the native swollenin from Trichoderma reesei: study of its possible role as C1 factor of enzymatic lignocellulose conversion Eibinger Manuel m.eibinger@tugraz.at 1Sigl Karin ksigl@gmx.net 1Sattelkow Jürgen juergen.sattelkow@felmi-zfe.at 2Ganner Thomas thomas.ganner@felmi-zfe.at 2Ramoni Jonas jonas.ramoni@tuwien.ac.at 3Seiboth Bernhard bernhard.seiboth@tuwien.ac.at 3Plank Harald harald.plank@felmi-zfe.at 24Nidetzky Bernd bernd.nidetzky@tugraz.at 151 Institute of Biotechnology and Biochemical Engineering, Graz University of Technology, Petersgasse 12/1, 8010 Graz, Austria 2 Institute for Electron Microscopy and Nanoanalysis, Graz University of Technology, Steyrergasse 17, 8010 Graz, Austria 3 Research Division Biochemical Technology, Institute of Chemical Engineering, TU Wien, Gumpendorferstrasse 1A/166, 1060 Vienna, Austria 4 Graz Centre for Electron Microscopy, Steyrergasse 17, 8010 Graz, Austria 5 Austrian Centre of Industrial Biotechnology, Petersgasse 14, 8010 Graz, Austria 26 8 2016 26 8 2016 2016 9 1 17830 5 2016 15 8 2016 © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Through binding to cellulose, expansin-like proteins are thought to loosen the structural order of crystalline surface material, thus making it more accessible for degradation by hydrolytic enzymes. Swollenin SWO1 is the major expansin-like protein from the fungus Trichoderma reesei. Here, we have performed a detailed characterization of a recombinant native form of SWO1 with respect to its possible auxiliary role in the enzymatic saccharification of lignocellulosic substrates. Results The swo1 gene was overexpressed in T. reesei QM9414 Δxyr1 mutant, featuring downregulated cellulase production, and the protein was purified from culture supernatant. SWO1 was N-glycosylated and its circular dichroism spectrum suggested a folded protein. Adsorption isotherms (25 °C, pH 5.0, 1.0 mg substrate/mL) revealed SWO1 to be 120- and 20-fold more specific for binding to birchwood xylan and kraft lignin, respectively, than for binding to Avicel PH-101. The SWO1 binding capacity on lignin (25 µmol/g) exceeded 12-fold that on Avicel PH-101 (2.1 µmol/g). On xylan, not only the binding capacity (22 µmol/g) but also the affinity of SWO1 (Kd = 0.08 µM) was enhanced compared to Avicel PH-101 (Kd = 0.89 µM). SWO1 caused rapid release of a tiny amount of reducing sugars (<1 % of total) from different substrates (Avicel PH-101, nanocrystalline cellulose, steam-pretreated wheat straw, barley β-glucan, cellotetraose) but did not promote continued saccharification. Atomic force microscopy revealed that amorphous cellulose films were not affected by SWO1. Also with AFM, binding of SWO1 to cellulose nanocrystallites was demonstrated at the single-molecule level, but adsorption did not affect this cellulose. SWO1 exhibited no synergy with T. reesei cellulases in the hydrolysis of the different celluloses. However, SWO1 boosted slightly (1.5-fold) the reducing sugar release from a native grass substrate. Conclusions SWO1 is a strongly glycosylated protein, which has implications for producing it in heterologous hosts. Although SWO1 binds to crystalline cellulose, its adsorption to xylan is much stronger. SWO1 is not an auxiliary factor of the enzymatic degradation of a variety of cellulosic substrates. Effect of SWO1 on sugar release from intact plant cell walls might be exploitable with certain (e.g., mildly pretreated) lignocellulosic feedstocks. Keywords SWO1SwolleninExpansinTrichoderma reeseiGlycoproteinCellulose degradationSynergismAmorphogenesisAtomic force microscopyhttp://dx.doi.org/10.13039/501100002428Austrian Science FundP24156-B21P24219Seiboth Bernhard Nidetzky Bernd issue-copyright-statement© The Author(s) 2016 ==== Body Background Through integrated developments in pretreatment technologies and cellulase engineering, much progress has been made in enhancing the efficiency of soluble sugar release from lignocellulosic feedstocks [1, 2]. However, the enzyme costs incurred in the saccharification step are still significant [2, 3]. There is high interest, therefore, in further decreasing the enzyme loading required in the process. Besides making the cellulases more effective per se, through improving their intrinsic activity [4–6] and facilitating their production [5, 7, 8], the reinforcement of existing cellulase preparations by auxiliary proteins and enzymes has attracted considerable attention [5, 9–13]. Lytic polysaccharide monooxygenase is a prominent example of an auxiliary enzyme, which is already in use to supplement cellulase preparations [10, 11, 14, 15]. Proteins lacking enzyme activity could also, in different ways, exert an auxiliary function in cellulose bioconversion. Inspired by Elwyn Reese’s early C1–Cx postulate (or updated variants thereof), invoking a non-hydrolytic, cellulose structure-disrupting C1 factor that acts in synergy with hydrolytic enzymes (the Cx factor), the discovery of a possible C1 factor of cellulose degradation has been a clear focus of interest in the research on auxiliary proteins [5, 10, 16]. Originally discovered from plants as cell wall-loosening proteins, expansins and expansin-like proteins constitute a widely distributed superfamily of proteins [17–19]. Besides plants, phylogenetically diverse microorganisms including bacteria and fungi, most of which grow in association with plants, were also found to contain expansins [20, 21]. Biologically, expansins are described to function as physical catalysts of cell wall enlargement and stress relaxation in plants. They appear to do so by promoting a rearrangement in the network of non-covalent interactions between the cell wall polysaccharides, in particular, those matrix glycans that interconnect individual cellulose microfibrils [19, 22]. By partly disrupting the bonding these glycans have to the microfibril surface and to each other, expansin action is supposed to enable the displacement of the cell wall polymers and, thus, to promote slippage in the points of their adhesion [19, 22, 23]. In microorganisms, expansins appear to be important factors of the colonization of plant tissues [24–27]. Although expansins do not weaken the cell wall or cause a lasting change in the wall structure [19] (except altering its size and shape [28]), they might, however, cause processes, sometimes referred to collectively as “amorphogenesis”, in which cellulose or lignocellulose structures become disaggregated and loosened up. This amorphogenesis, and the beneficial effect it might have on the action of hydrolytic enzymes could make expansins broadly useful in cellulosic biomass conversion [21, 29–31]. Originally discovered by Saloheimo and colleagues [25] who showed it to cause swelling of cotton fibers, swollenin is a special expansin-like protein from fungi. It differs from the canonical expansins in size (~493 compared to ~225 amino acids) and also in the arrangement of structural modules within the protein structure. Expansins are modular proteins built of two discrete domains connected by a short linker [5, 26, 32]. The N-terminal domain shows weak resemblance to the catalytic module of family GH-45 glycoside hydrolases, lacking their full catalytic machinery, however [5, 25]. We refer to this aspect later under “Results” section, but expansins are generally described to lack polysaccharide hydrolase activity. The C-terminal domain resembles certain carbohydrate-binding modules (e.g., CBM family 3 or 63) [25, 33]. Both domains are required for the full cell wall-loosening activity of the expansins [32, 33]. Swollenin deviates from the basic expansin conformation by having an additional CBM from family 1 located N-terminally [5, 18, 25]. The expansin-like domain and the family 1 CBM are connected by a putative linker and/or fibronectin-III (Fn-III)-like domain [18, 34]. Linkers, in general, serve as flexible elements in protein structures [18, 35, 36]; however, little is currently known about the actual role of the linker region in swollenin. It is noted though that multiple Ser/Thr residues for O-glycosylation are present in the linker/Fn-III-like domain of swollenin [5, 37]. Expansin/swollenin “activity” has been assayed in different ways but it is generally difficult to evaluate. A biomechanical assay measures directly the effect of the protein on the fiber strength of the cellulosic material [19, 32]. Light microscopy was used often to track fiber disaggregation and other morphological changes in cellulosic material on incubation with swollenin [18, 34, 37–39]. Cellulose crystallinity was also determined to monitor the amorphogenesis [37, 38, 40]. To identify and characterize swollenin-caused changes in the surface properties of cellulose, biological methods (e.g., adsorption of CBM [41, 42]) and high-resolution microscopy (SEM and AFM) were used [18, 37, 41]. Synergy with cellulases in releasing soluble sugars from lignocellulosic substrates presents a highly indirect but use-inspired way of expressing swollenin activity [34, 37, 40, 43–45]. Table 1 summarizes the results from different papers analyzing the possible involvement of swollenin in the degradation of lignocellulosic substrates. The studies were selected because besides synergy with cellulases, which has been the topic of numerous papers, they also examined the effect of swollenin on the morphology of the cellulosic substrate used. As it becomes clear from Table 1, the current literature does not offer a conclusive picture, thus motivating the present study to obtain clarification.Table 1 Summary of reported structural changes in lignocellulosic substrates caused by swollenin preparations obtained through different strategies of protein expression and production Native source/produced in/purification/aMm Substrates Experimental setup; employed methods Effects Ref. T. reesei/S. cerevisiae/CS/~75 kDa Mercerized cotton fibers 0.25 µgSwo/gsubstrate, 25 °C, 4 h; light microscopy Local disruption of cotton fibers, no release of sugars [18] T. reesei/S. cerevisiae/CS/~75 kDa Whatman No. 3 filter paper 5 mL CS/filter paper strip, room temperature, 15 min; paper strength test Reduction of tensile strength and average peak load (15–20 %) [18] T. reesei/A. niger/AC/~80–95 kDa Valonia sp. cell wall fragments 10 µgSwo/gsubstrate, 45 °C, 48 h; AFM, light microscopy Partial disintegration to isolated fibers, no release of sugars [18] A. fumigatus/A. oryzae/AC/~85 kDa Avicel PH-101, filter paper (603 cellulose thimbles) 0.8 µgSwo/mgAvicel, 8 µgSwo/mgfilter paper, 40 °C, 72 h; light microscopy, visual examination Avicel PH-101 particle size reduction (~50 %), effect is pH- and temperature-dependent; complete disruption of filter paper, no release of sugars [34] T. reesei/K. lactis/IMAC/~100 kDa Whatman No. 1 filter paper, α-cellulose, Avicel PH-101, sigmacell 101 20 µgSwo/mgsubstrate, 45 °C, 48 h; XRD, laser diffraction Reduction of CrI (~10 up to 22 %) and particle size (up to ~30 %) was observed for all substrates except Sigmacell [37] T. reesei/K. lactis/IMAC/~100 kDa Whatman No. 1 filter paper 20 µgSwo/mgsubstrate, 45 °C, 48 h; SEM, photography Deagglomeration of filter paper (reduction of particle size and count); SEM showed an increased surface roughness; no swelling was observed [37] T. asperellum/E. coli/refolding, AC/~35–50 kDa Avicel PH-101 5 µgSwo/mgsubstrate, 50 °C, 91 h; light microscopy Partial disruption of Avicel PH-101 particles [38] T. pseudokoningii/A. niger/HIC/~75 kDa Avicel PH-101, filter paper 5–20 µgSwo/mgAvicel, 0.5–2 µgSwo/mgfilter paper, 40 °C, 48–72 h; light microscopy, XRD No effects were observed by applying light microscopy; CrI was increased (88–90 %) [40] T. reesei/T. reesei/IMAC, IE/n.a. Mercerized cotton fibers 10 µgSwo/mgsubstrate, 50 °C, overnight; CBM adsorption assay, SEM Available surface for CBMs was increased (~38 %); SEM showed a smoothed surface upon TrSwo1 treatment [41] T. reesei/E. coli and N. tabacum/CS/n.a. Mercerized cotton fibers 0.2–2 µgSwo/mgsubstrate, 37 °C or 50 °C, 8 h; phase contrast microscopy Fiber expansion, inner fiber structure was altered independent of the TrSwo1 source [28] P. oxalicum/T. reesei/precipitation, IMAC/~90 kDa Avicel PH-101 4 µgSwo/mgsubstrate, 50 °C, 48 h; light microscopy, protein binding assay Partial disruption of Avicel PH-101 particles; B max for cellulases was increased (~20 %) [39] T. reesei/T. reesei/IMAC, IE/n.a. Dissolving pulp, various lignocellulosic pulps 50 µgSwo/mgsubstrate, 50 °C, overnight; high-resolution fiber quality analyzer Fragmentation was observed to a low extent for dissolving pulp fibers but not for lignocellulosic pulps [42] Orpinomyces sp. strain C1A/E. coli/refolding, IMAC/~67 kDa Cotton fibers 0.25–5 µgSwo/mgsubstrate, 39 °C, 12 h; ESEM, Congo red cotton assay Average cotton fiber width was increased (~56 %); dye adsorption was increased (CAE ~0.4 for 5 µgSwo/mgsubstrate) [78] aMm apparent molecular mass, CS enriched culture supernatant, AC affinity chromatography, IMAC immobilized metal adsorption chromatography (via His-tag), HIC hydrophobic interaction chromatography, IE ion exchange chromatography, n.a. not available In the absence of a clear parameter able to capture the functionality of swollenin in an alleged amorphogenesis process, it is crucially important in the search of cause-and-effect relationships that the protein preparation used is well defined in its main structural characteristics. In addition, for the purpose of rigorously establishing an intrinsic biological reference, the swollenin should be as native-like as possible. Previous studies have obtained the recombinant swollenin through heterologous expression of the coding gene in foreign hosts (e.g., Escherichia coli, Pichia pastoris, Saccharomyces cerevisiae, Aspergillus sp.) [18, 28, 37–40, 43, 45], bearing in each case the risk that non-native post-translational processing, especially glycosylation, could affect the protein function [46, 47]. Fusion tags were also used to facilitate protein purification [42, 44, 48], but whether these modifications of the native structure are functionally silent or interfere with the original function of the swollenin is not known. The yield of recombinant swollenin from heterologous production was usually in the low (≤20–100) mg/L culture range [21], and to our knowledge, proper folding of the recombinant protein was never assessed. In this study of SWO1, the major swollenin of Trichoderma reesei (anamorph Hypocrea jecorina), we addressed the urgent concern about the nativeness of recombinant swollenin by producing the protein via homologous overexpression in the native host. To largely eliminate the otherwise huge cellulase and hemicellulase background in the secretome of T. reesei, a mutant QM9414 strain was used in which, as shown in earlier work, the hydrolytic enzyme production was strongly downregulated due to xyr1 transcriptional regulator gene knockout [49]. Using the target protein thus produced and purified from culture supernatant, a detailed functional characterization of SWO1 was performed. Besides adsorption studies, this included direct measurements of a possible cellulose structure-disrupting activity of SWO1. Synergy with T. reesei cellulases was evaluated during degradation of different cellulose substrates. Results Recombinant production and purification of the native SWO1 The genetic background of T. reesei QM9414 Δxyr1 was previously shown to present a useful vehicle for the overexpression of individual secreted proteins in an overall cellulase- and hemicellulase-free environment [49]. The coding region of the swo1 gene was, therefore, integrated genomically under control of the cdna1 promoter. In positive recipient strains, the presence of the swo1 expression cassette was verified by PCR, and secretion of the target protein into the culture supernatant was also clearly indicated in SDS-PAGE. The recombinant SWO1 was produced in a 2-L bioreactor cultivation of the T. reesei integrant strain, using glucose as the carbon source. The fungal secretome comprised SWO1 as a major protein component, as shown in Fig. 1a. Prominent protein band at about 75 kDa mass which was absent from the supernatant of the control strain indicated secretion of recombinant protein. Using batch chromatography on Avicel PH-101 as an affinity adsorbent, SWO1 was isolated from the supernatant in just a single step of downstream processing, as shown in Fig. 1b. The protein yield was about 4 mg/L of culture. The apparent molecular mass of SWO1 in SDS-PAGE (~75 kDa) differed substantially from the mass of 49 kDa expected from protein’s amino acid sequence, consistent with the observations of Saloheimo et al. [18] who used Western blotting for detection of SWO1 in T. reesei culture supernatants. This unusually high molecular mass plus the fact that the purified protein migrated as a single but relatively diffuse band in SDS-PAGE suggested that the recombinant SWO1 was strongly glycosylated. There are four N-glycosylation sites in the sequence of SWO1, three of which are identified as strong candidates to become glycosylated [48]. The linker/Fn-III-like domain might be additionally O-glycosylated [18, 37, 48]. Figure 1c shows that on incubation with Endo H for removal of protein N-glycans, the apparent molecular mass of the native SWO1 was only slightly reduced (~5 kDa). This suggests that the difference between the calculated and observed molecular mass cannot be explained only as a result of N-glycosylation, and that O-glycosylation might contribute to the difference. Direct glycostaining in the gel confirmed the presence of glycans on both the native and the Endo H-treated SWO1 (Fig. 1d). We, therefore, concluded that the recombinant SWO1 was N-glycosylated but also strongly O-glycosylated.Fig. 1 Identification, purification and deglycosylation of SWO1. a SWO1 (indicated with a rectangle) was recombinantly expressed in T. reesei QM9414 ∆xyr1 (designated as RJ_SWO1) and secreted into the culture media (two independent fermentations are shown). A prominent band at about 75 kDa, which was absent in an untransformed control strain, was identified as SWO1. b Single-step batch chromatography on Avicel PH-101 as adsorbent was used to purify SWO1 (two independent purifications are shown). The purified protein migrated as a single but relatively diffuse protein band, suggesting that the recombinant SWO1 was strongly glycosylated. c Deglycosylation of SWO1 with Endo H resulted in a decrease of the apparent molecular mass by roughly 5 kDa and a more sharply focused protein band was obtained in the SDS-polyacrylamide gel. d Direct glycostaining of the same gel shown in c confirmed the presence of glycans on both the native and the Endo H-treated SWO1 Structural analysis of SWO1 using circular dichroism spectroscopy and protein modeling The far-UV CD spectrum of purified SWO1 is shown in Fig. 2a. This suggested a folded protein with a high content of β-strand relative to α-helical secondary structure. It also indicated a large portion of the protein structure to lack a discrete organization into secondary structural elements. Analysis of the spectrum with DichroWeb suggested SWO1 to be composed of just 7 % α-helices, 34 % β-strands, 18 % turns and 34 % unordered structure. Structural modeling of SWO1 (UniProt ID: Q9P8D0) was done with Phyre2 [50], analyzing the entire protein except for the amino acids 1–18, which are predicted to be cleaved off after secretion. Figure 2b shows a hypothetical structure of SWO1 rendered from the models of the two modules. Due to the amount of proteins with known three-dimensional structure (N ≥ 10) resembling either expansins or CBMs and sufficient sequence similarity, the structural models of the family 1 CBM (CBD form EG I, sequence identity: 50 %) and the expansin-like domain (e.g. β-expansin from maize, sequence identity: 28 %) appear to be plausible. In addition, a structural overlay of the modeled expansin-like domain with a crystallized bacterial expansin (EXLX1 from B. subtilis, PDB ID: 4FG2) is provided in Fig. 2c to allow a visual comparison of the related domains. Overall, 87 % of the input sequence was modeled at >90 % confidence, and 61 residues were modeled ab initio. Moreover, the relative content of secondary structure elements calculated from the structure model was reasonably similar to that determined from the CD spectrum. It was 3 % α-helices, 23 % β-strands, 41 % turns and 33 % unordered structure. Finally, the sequence-based prediction tool (JPred4) [51] suggested a similar content of α-helices (3 %) and β-strands (20 %). In summary, these results provided good evidence suggesting that the SWO1 as isolated was most likely properly folded.Fig. 2 CD spectra and homology model of native SWO1. a Smoothed CD spectrum of native SWO1 in 50 mM sodium acetate buffer, pH 5.0, at room temperature. For further details of the measurement, see the “Methods” section. b The automated protein structure homology-modeling server Phyre2 was used to predict the protein structure of SWO1 (UniProt ID: Q9P8D0). The distinct domains are colored as follows: family 1 CBM (blue); linker/Fn-III-like domain (orange); GH45 domain (red); expansin-like CBM (green). c A structural overlay of the modeled expansin-like domain from SWO1 with EXLX1 from B. subtilis (PDB ID: 4FG2) was made to allow visual comparison. The distinct domains are colored as follows: EXLX1 (blue); GH45 domain (red); expansin-like CBM (green). Overall, 87 % of the input sequence was modeled at >90 % confidence, and 61 residues were modeled ab initio. The depicted model was used to calculate the percentage of secondary structure elements Adsorption of SWO1 to insoluble polysaccharides Isotherms for the adsorption of SWO1 to Avicel PH-101, birchwood xylan and kraft lignin were determined at 25 °C and pH 5.0 employing the insoluble substrate in a concentration of 1.0 mg/mL. Using Avicel PH-101 under comparable conditions, preliminary experiments showed that most of the SWO1 was bound rapidly within 30 min and that apparent adsorption equilibrium was reached after 60 min. In accordance with an earlier study from Jäger et al. [37], isotherms were, therefore, obtained from incubations for 120 min, and the results are shown in Fig. 3. With each substrate, the binding of SWO1 appeared to correspond to a simple Langmuir adsorption isotherm. Note that Avicel PH-101 contains minor fractions of xylan (<2 %) and lignin (<1 %) [52, 53]. However, nothing is known about their localization and structural organization. For this reason and also supported by the seemingly appropriate fit (R2 ≥ 0.98), we do not consider the use of an alternative multiple binding site isotherm for Avicel PH-101. The corresponding fit of the data gave the binding constants summarized in Table 2. Remarkably, the binding capacity (Bmax) of SWO1 was much higher (≥12-fold) on xylan and lignin than it was on Avicel PH-101. The binding affinity in terms of the reciprocal dissociation constant (Kd) was also higher (11-fold) on xylan than on Avicel PH-101. In terms of Bmax/Kd, therefore, the specificity of SWO1 for binding to xylan exceeded that for binding to Avicel PH-101 almost 120-fold. The specificity for binding to lignin lay in between the two (Table 2). Based on Kd values reported, recombinant SWO1 obtained by heterologous expression in Kluyveromyces lactis bound to Avicel PH-101 with similar affinity as the natively produced SWO1 does. This result could be interpreted to mean that the binding affinity of SWO1 on Avicel PH-101 is not majorly affected by the degree of nativeness its glycosylation has. Interestingly, expansin-like proteins of bacterial origin bound to Avicel PH-101 with Kd values similar to that of SWO1, suggesting perhaps that the glycosylation is not a crucial element of binding as far as the Kd is concerned. Only to note, cellulases harboring a family 1 carbohydrate-binding module showed Kd values of Avicel PH-101 binding agreeing with the Kd of SWO1 within the same order of magnitude [37, 54, 55].Fig. 3 Adsorption isotherms of purified native SWO1 on lignocellulose components. Experiments were done at 25 °C in 50 mM sodium acetate, pH 5.0, over 2 h with shaking (500 rpm). Substrate concentration was 1 mg/mL in a total reaction volume of 200 µL. Symbols show the measured data and error bars show the SD from three independent experiments. Insets present a zoomed view on the initial data points for SWO1 adsorption on xylan and kraft lignin. The fitted Langmuir isotherms are shown as dashed lines and the corresponding parameters, maximum binding capacity related to the unit mass of substrate (B max) and the dissociation constant K d, are summarized in Table 2 Table 2 Summarized adsorption parameters of SWO1 on Avicel PH-101, birchwood xylan and lignin Substrate Avicel PH-101 Lignin Xylan B max (µmol/g) 2.11 ± 0.39 25.1 ± 1.48 22.3 ± 3.13 K d (µM) 0.89 ± 0.30 0.53 ± 0.11 0.08 ± 0.04 Absolute specificity (L/g)a 2.4 47.4 279 Relative specifityb 1.00 20.0 118 SWO1 showed the highest affinity and specificity for xylan followed by lignin and pure cellulose. B max maximum binding capacity, K d dissociation constant a B max/K d bAbsolute specificities normalized on Avicel PH-101 Is the native SWO1 active on its own in the depolymerization of glycan substrates? Andberg et al. [48] reported a His-tagged preparation of SWO1 to promote the release of reducing sugars from different substrates, in particular, barley β-glucan, whose conversion involved a remarkably high specific activity of SWO1 of 7 U/mg. The SWO1 produced and purified from Aspergillus niger var. awamori showed a similar specific activity on β-glucan substrate. As these findings implied SWO1 to be active enzymatically, with certain substrates at least, we also examined the native SWO1 for its ability to degrade different insoluble glycans via soluble sugar release. Figure 4a shows the results. Compared to incubations in which BSA was used as an inactive control, incubations with SWO1 caused a slightly enhanced sugar formation. However, only a tiny amount of soluble sugars was produced in comparison to the total sugar available from the substrates in polymeric form. Sugars released from cellulose were detected as glucose, because β-glucosidase was added to the reaction samples later. The product released from the β-glucan was shown to be mainly cellobiose (≥90 %). We calculated that the sugar release from the β-glucan (Fig. 4a) would correspond to a specific activity of only around 0.1 mU/mg, equivalent to just six turnovers of SWO1 within 24 h. Andberg et al. [48] observed a comparable conversion (≤1.2 mg/g) when studying the conversion of β-glucan. However, their reported specific activity of SWO1 was increased by orders of magnitude (7 U/mg). The apparent conflict in these findings is resolved by considering that the kinetics of sugar formation by SWO1 was completely unlike a “normal” enzymatic reaction. They reported a rapid accumulation of sugar in the supernatant initially (≤10 min) but no further release on prolonged incubation up to 24 h.Fig. 4 Activity of SWO1 on various glycan substrates. a The substrates used were Avicel PH-101, CNC and β-glucan (1 mg/mL each) in 50 mM sodium acetate buffer, pH 5.0. Incubation was for 24 h at 40 °C with shaking (500 rpm). Avicel PH-101 and CNC were incubated with 0.4 µM SWO1 (black bars) or an equimolar amount of BSA (grey bars). Reactions were stopped by heating and incubated with β-glucosidase. The glucose released was measured with an enzymatic assay. Error bars show SD from four independent experiments. Barley β-glucan was incubated with either 0.2 µM SWO1 or BSA. The liberated sugars were assayed with HPAEC-PAD, and cellobiose was identified as the main product of SWO1 activity. Error bars are from two independent experiments. b Cellotetraose (0.5 mg/mL) was incubated with either 0.5 µM SWO1 or BSA in 50 mM sodium acetate buffer, pH 5.0, for 24 h at 40 °C with shaking (500 rpm). The product distribution (G2 cellobiose, G3 cellotriose, G4 cellotetraose) was determined with HPAEC-PAD. Error bars were estimated from two independent experiments In our view, therefore, these effects of SWO1 appear inconsistent with its action as a true cellulase, however, weakly active. An alternative explanation is that the observable SWO1 “activity” on Avicel PH-101 and CNC resulted from the release into solution of sugars (e.g., short oligosaccharides) that were initially tightly associated with the solid material but became detached on binding of the SWO1. Note: even BSA, which we assume to interact completely unspecifically with the cellulose preparations used, caused release of trace amounts of soluble sugars as reported previously [44] (Fig. 4a). The sugar release from barley β-glucan (Fig. 4a) might, however, reflect a tiny intrinsic hydrolase activity of SWO1. BSA does not produce detectable sugars from this substrate. Following Andberg et al., we, therefore, also examined cellotetraose as a substrate of SWO1 and show the results in Fig. 4b. While being absent from the controls, cellobiose was clearly formed in the incubation with SWO1. The amount of cellobiose released (200 µM) was explained by the cellotetraose converted (100 µM). Since no glucose was formed, the cleavage of cellotetraose appeared to have been quite specific. Utilization of the oligosaccharide substrate was also specific because cellotriose, which was present in the reaction from the beginning due to the composition of the commercial cellotetraose preparation, was not attacked at all by the SWO1. The turnover of the cellotetraose substrate by SWO1 was extremely low (0.14 min−1). It is called in remembrance that the C-terminal domain of SWO1 resembles structurally the catalytic modules of family GH-45 glycoside hydrolases but lacks their full active-site machinery due to the absence of a catalytic base. Therefore, considering the low level of activity that family GH-45 enzymes retain on substitution of their catalytic base by a non-functional residue [5, 26], one would not expect SWO1 to be a proficient catalyst of the hydrolysis of glycosides. We also assayed the hydrolysis of 4-methylumbelliferyl-β-d-cellobioside, a suitable substrate for various cellulases [5, 56], but did not observe activity of the purified SWO1 in any of the possible cleavage modes, releasing 4-methylumbelliferone or 4-methylumbelliferyl-β-d-glucoside. Effect of SWO1 on cellulose crystallinity measured by wide-angle x-ray scattering Avicel PH-101 was incubated for 72 h in the presence of an SWO1 concentration, which according to the adsorption isotherm (Fig. 3; Table 2) was “catalytic” (0.05 mol %) relative to the available binding sites on this substrate. We considered that a possible amorphogenesis, caused by the dynamic action of SWO1, might be detectable as a decrease in the overall crystallinity of Avicel PH-101 which we measured by wide-angle x-ray scattering (WAXS) [57–59]. The results are shown in Fig. 5. A lowering of the crystallinity index would show in the WAXS profile as an intensity decrease in the major scattering peak at about 22.7°. Changes in the peak’s shape and position would also indicate transformations of the original crystalline cellulose (allomorph Iβ) into another allomorph or into amorphous material [58, 60]. Figure 5 is clear in showing that SWO1 had no effect on Avicel PH-101 structure to the extent detectable with the WAXS method used. This result contrasts, to some extent, with the findings of Jäger et al. [37] who reported changes in Avicel PH-101 crystallinity index on incubation with a TrSWO1 produced recombinantly in K. lactis.Fig. 5 Stacked WAXS profiles of SWO1-treated and untreated Avicel PH-101. Avicel PH-101 (10 mg/mL) was incubated in 50 mM sodium acetate buffer, pH 5.0, with 0.01 µM SWO1 (red) or without enzyme (blue), for 72 h at 40 °C with agitation (150 rpm). Relevant peaks for cellulose Iβ were resolved and indexed with Miller indices. No changes in intensity or peak’s shape and position were observed Effect of SWO1 on fully amorphous and highly crystalline cellulose preparations measured by atomic force microscopy in a liquid environment We considered that while global parameters of cellulose structural organization such as the crystallinity index (see Fig. 5) might not be suitable to capture the relevant components of an SWO1-caused amorphogenesis, a method able to reveal even subtle changes in cellulose surface morphology, and to do so in a time and laterally resolved manner, could be very useful for the identification and characterization of hidden SWO1 functions. Like in our previous studies of cellulases [57, 61, 62] and LPMO [12], atomic force microscopy (AFM) in a liquid environment was used, because the protein function could, thus, be analyzed in a setting modeled on the natural process. To contrast the effect of two completely different types of cellulose, we examined a fully amorphous cellulose film (ATFC) and cellulose nanocrystals (CNC), both spin-cast on silicon wafers [57]. Figure 6 shows the analysis of the amorphous cellulose treated with SWO1. The cellulose film provides a homogeneous and nanoflat surface for SWO1 to act upon (Fig. 6a, b). The overall surface roughness was below 5 nm. Height profiles were recorded from the surface at two representative regions of 1 µm2 area before and after treatment with SWO1. The results did not reveal changes in the surface topography as result of SWO1 action. Local effects of SWO1 on swelling or disruption of the cellulose surface, both of which would change the height, would have been clearly detectable with the method used (Fig. 6c, d). It appears, therefore, that on the amorphous cellulose used, SWO1 was inactive as a structure-loosening factor.Fig. 6 AFM imaging of SWO1 action on ATFC. a A three-dimensional representation of the experimental setup. ATFC of defined height is placed on a silicon wafer, which can be used as reference. b The ATFC surface is homogenous and nanoflat with a mean surface roughness below 5 nm. c ATFC substrates on a single silicon wafer (~1 cm2) were incubated in 50 mM sodium acetate buffer, pH 5.0, at 40 °C with mild agitation in a total reaction volume of 2 mL. Two exemplary height profiles from ATFC substrates after incubation with (blue) or without 0.4 µM SWO1 (red) after 24 h are shown. No significant changes induced by SWO1 incubation were found. Note that the edges of amorphous cellulose films were slightly deformed due to a cutting process prior to the addition of SWO1. Thus, only the surface with a certain distance (~1.0 µm) to the edge was analyzed. d Height distribution profiles of spots on the ATFC surface after incubation with (blue) or without SWO1 (red) using the same experimental conditions as stated above. A broadening of the peak, which would indicate degradation or swelling, is not visible. Analyzed areas were at least 1 µm2 CNCs present a highly recalcitrant form of cellulose. From the herein applied method of their preparation [57, 63], the CNCs appeared as needle-like structures of about 100–200 nm length and about 3–70 nm width, as shown in Fig. 8. The CNCs were incubated with SWO1 and also with BSA as a control, and a representative area of each specimen (>1 µm2) was analyzed with AFM. In spite of extensive data analysis that involved the characterization of numerous CNCs in each image (N ≥ 20) at different levels of their structure, significant changes in the substrate were recognized neither in the SWO1 incubation nor in the BSA control. To examine the samples in more detail, they were washed after 24 h of incubation, dried and again analyzed with AFM. Results in Fig. 7A, B served to localize single BSA molecules, showing that they were attached mostly to the surface of the silicon wafer, apparently in a random fashion, and only occasionally to the CNCs. The situation was notably different when SWO1 was used, as shown in panels C and D of Fig. 7. Despite unspecific binding to the wafer surface to some degree, SWO1 showed the clear trend to become enriched around the CNCs (panel C). Imaging of single CNCs at a resolution down to single protein particles revealed multiple sphere-like SWO1 molecules bound at both sides of the cellulose rod (panel D). Specific adsorption of SWO1 to CNCs is, therefore, suggested to surpass a mere adhesion of the protein to the hydrophobic surface of the wafer. Analysis of the distribution of height and width in multiple CNCs after the incubation and comparison of the result with the corresponding distribution of the untreated sample reveal that BSA really had no effect whatsoever on the size properties of the cellulosic substrate (Fig. 7E). SWO1, by contrast, caused the width distribution to shift by about 3 nm to an elevated mean value (Fig. 7E). Adsorption of SWO1 along the sides of the nanocrystals is likely to have caused this effect.Fig. 7 AFM imaging of SWO1 action on CNCs. CNCs on a single silicon wafer (~1 cm2) were incubated with either 0.4 µM BSA (A, B) or SWO1 (C, D) in 50 mM sodium acetate buffer, pH 5.0, at 40 °C with mild agitation. Incubation was done over 24 h in a total reaction volume of 2 mL. AFM imaging was done on dried silicon wafers at room temperature. No evidence for BSA- or SWO1-induced structural changes were found by visual examination. However, the presence of molecules attached to either CNCs or the silicon wafer can be observed (A–D). Most of the BSA molecules are positioned randomly on the silicon wafer (A). An exemplary amplified section is shown in B. Multiple BSA molecules are visible (green circles), and only one BSA molecule seems to be associated with a crystallite (red circle). Contrary, SWO1 showed a clear trend to become attached to CNCs (C). An exemplary amplified CNC confirmed that the ratio of molecules attached to crystals (red circles) and particles on the surface (green circles) has significantly increased (D). Note that for an easier viewing, not all BSA/SWO1 molecules are highlighted (D). E Statistical analysis of the size distribution showed an apparent increase in the width of CNCs upon incubation with SWO1. However, this effect is attributed to the size of the adsorbed protein and the presence of a hydration shell (see Fig. 8). Scale bars 100 nm Interesting observation from these AFM analyses was that despite having a similar apparent mass like BSA (~66 kDa), SWO1 particles appeared distinctly larger (10–30 nm diameter) in the images than BSA particles, as recognized clearly when comparing panels B and D in Fig. 7. We think that the high glycosylation of SWO1 and the consequently pronounced hydration of the protein could explain the effect. Features of the cellulose nanocrystals recorded from the SWO1 experiment appear strongly blurred in comparison to the BSA experiment, which is most likely related to hydration. Figure 8 illustrates the effect in more detail, comparing height (panel A) and phase (panel B) images from the experiment with SWO1. Phase imaging depicts the dissipative interaction energy density and allows a clear distinction between materials with different characteristics (e.g., CNCs and enzymes). By comparison with the height data, the phase image reveals the presence of multiple structural features, which are convoluted and blurred in the height image. First, CNCs appear to be thinner in phase imaging, and second, CNCs are surrounded by a bright layer with a unique phase signal, which represents most likely a hydration shell. In addition, SWO1 molecules, either free or attached to CNCs, embedded in the hydration shell can be observed, which are not readily visible in the height image (Fig. 8). The hydration shell is contributing to the apparent broadening of the CNCs and is not present or significantly reduced upon incubation with BSA.Fig. 8 Details of SWO1 binding to CNCs revealed by AFM phase imaging. CNCs on a single silicon wafer (~1 cm2) were incubated with 0.4 µM SWO1 in 50 mM sodium acetate buffer, pH 5.0, at 40 °C with agitation. Incubation was done over 24 h in a total reaction volume of 2 mL. AFM imaging was done on dried silicon wafers at room temperature. A Recorded height images of CNCs are blurred, and structural features or proteins are not readily visible. B Phase imaging allowed the visualization of features like CNC-attached proteins (green dashed ellipse) covered by a hydration shell (bright layer enveloping CNCs). By comparison with the height image (cyan dashed ellipse), it is clear that the hydration shell is also, at least, partly responsible for the apparent broadening of the CNCs (Fig. 7E). The hydration shell is not present or significantly reduced upon incubation with BSA. Scale bars 30 nm Synergy between SWO1 and T. reesei cellulases in releasing soluble sugars from different lignocellulosic substrates Ability of SWO1 to boost the hydrolysis of different lignocellulosic substrates by the complete T. reesei cellulase system was analyzed. Figure 9 shows time courses of reducing sugar release from Avicel PH-101 and CNCs under conditions in which the celluloses were pre-incubated with SWO1 or BSA for 24 h and cellulases were then added to initiate the hydrolysis. The results are clear in showing that SWO1 did not enhance the substrate conversion. We also examined the effect of SWO1 on the hydrolysis of filter paper but found none. Note: using light microscopy, we further analyzed if incubation with SWO1 alone caused disintegration of the fibrous filter paper material. This did not occur. Wheat straw, that had been pretreated by steam explosion, and birchwood xylan were also tested as substrates of enzymatic hydrolysis in the absence and presence of SWO1. Again, there was no boosting effect by SWO1 within the limits of experimental error, and the SWO1 lacked sugar-releasing activity on its own.Fig. 9 Effect of SWO1 pretreatment on the enzymatic hydrolysis of cellulosic substrates. The substrates used were Avicel PH-101 (○/●) and CNCs (Δ/▼). The substrate concentration was 1 mg/mL. All reactions were done in 50 mM sodium acetate buffer, pH 5.0, at 40 °C with shaking (500 rpm) in a total reaction volume of 1.5 mL. Prior to the addition of cellulase, the substrate preparation was incubated with 0.4 µM SWO1 (●/▼) or BSA (○/Δ) for 24 h. T. reesei cellulase and β-glucosidase were then added in a small volume (60 µL) to a final enzyme loading of 20 µg/mg substrate and 4 µg/mg substrate, respectively. The mixture was incubated for another 24 h using the same conditions as stated above. The liberated glucose was measured with an enzymatic assay. Error bars show SD from four independent experiments Finally, we examined a lignocellulose substrate, which, except for drying, had not been pretreated at all. A sample of cock’s-foot grass (Dactylis glomerata) was used. Figure 10 compares the sugar release and also the visual appearance of the substrate after incubation with cellulases in the presence and absence of SWO1. Compared to the BSA control, the reaction containing the SWO1 showed a 1.5-fold improved sugar formation and appeared more completely degraded. The untreated material is shown for reference.Fig. 10 Effect of SWO1 supplementation on the enzymatic hydrolysis of cock’s-foot grass. A Reactions were done in 50 mM sodium acetate buffer, pH 5.0, at 40 °C with shaking (500 rpm) in a total reaction volume of 1 mL over 164 h. Substrate concentration was 5.0 mg/mL, and cellulase was added to a final protein loading of 2 µg/mg substrate. SWO1 was present at 0.02 µM (black bar), and the reference experiment used an equimolar amount of BSA (grey bar) instead of SWO1. The amount of reducing sugars released was measured colorimetrically with the 3,5-DNS assay calibrated against glucose. Error bars were estimated from two independent experiments. B By comparison with the BSA-containing control reaction (left panel), cock’s-foot grass appeared to be more completely degraded in the presence of SWO1 (central panel) after 164 h. The remaining substrate parts are highlighted for an easier viewing. The untreated material is shown as reference (right panel) Discussion Preparation of recombinant native-like SWO1 via homologous expression in T. reesei Despite different approaches tried, as shown in Table 1, preparation of the T. reesei SWO1 in a recombinant form is currently not well established. Most studies seem to agree, at least implicitly, that recombinant production of SWO1 is highly problematical due to the very low protein titers formed in different host organisms. There is, however, good evidence already from the seminal discovery of Saloheimo et al. [18] that the native SWO1 is strongly post-translationally modified. The protein is glycosylated [37, 43, 48] and its carbohydrate-binding module likely involves multiple disulfide bonds [39]. Since it is not known in which way the post-translational modifications affect the function of SWO1, we considered it crucial to prepare the protein in its native host and additionally avoided the use of purification tags, which also bear the risk of affecting the function in an unpredictable fashion. The native-like SWO1 so obtained was purified to apparent homogeneity from T. reesei culture supernatant. The isolated protein was shown to be heavily glycosylated. From analysis of the apparent molecular mass before and after treatment with endo-N-glycosylase, we concluded that N-glycans constituted only a small portion of the total protein-linked glycans present. SWO1, thus, appeared to be O-glycosylated in substantial amount. From its CD spectrum, the protein seemed to be properly folded. Its functional characterization was considered to be of a general interest as it could provide basic evidence to advance the current debate about a possible role of SWO1 as C1 factor of enzymatic lignocellulose degradation. Interpretation of any C1-like activity that a certain recombinant form of SWO1 may show, as such or relative to another form produced differently, hinges essentially on an assessment of the nativeness of the protein used. This, in turn, requires knowledge about the behavior of the canonical (native) form of SWO1. Characteristics of function of the native-like SWO1 Although SWO1 binds to crystalline cellulose, as we have shown here in equilibrium adsorption studies and for the first time at single-molecule resolution by AFM, it has a much higher specificity for binding to xylan as compared to cellulose. Differences in binding specificity are not only a consequence of a different binding affinity, which is higher for xylan, but also reflect a substantially larger binding capacity of SWO1 on xylan than cellulose (Avicel PH-101). Adsorption experiments with lignin demonstrate the ability of SWO1 to bind also to the non-carbohydrate residue of lignocellulose with relatively high specificity. Interestingly, a recombinant swollenin from A. fumigatus produced in A. oryzae was reported not to bind to xylan [34]. Contrarily, most bacterial expansins are reported to bind on xylan [21, 26, 54, 64, 65]. By employing assays and analytical techniques able to capture even subtle effects of an SWO1-caused structural disintegration of amorphous and crystalline cellulose, we gathered a considerable body of evidence coherent in the overall suggestion that the native-like SWO1 was essentially inactive as an “amorphogenesis” factor on pure celluloses. Neither did SWO1 loosen or roughen up the cellulose surface [18, 34, 37] nor did it cause swelling of the cellulose material [18, 28, 37]. But also the opposite effect, that SWO1 smoothens an otherwise rough cellulose surface [41], was not observed. However, a noticeable effect from the incubation of CNCs with SWO1 was that after drying, there remained an apparent hydration shell, which surrounded the absorbed SWO1 molecules and the CNCs. It is known from molecular dynamics simulations [66] and low-field nuclear magnetic resonance studies [67, 68] that the surface hydration is a key parameter in enzymatic cellulose hydrolysis, affecting both the enzyme adsorption and the conversion. In general, a higher degree of hydration is beneficial; however, the availability of “free” water [67, 68] and the water activity [69] seem to be particularly important. A protein retaining its hydration shell even after drying is quite unlikely to increase the amount of readily available water at the cellulose surface, for activity of the hydrolytic enzymes or structural changes in the substrate requiring penetration of water. Thus, the evidence from the AFM imaging also suggests that SWO1 is probably not an “amorphogenesis” factor on pure cellulose. However, the use of a protein with a substantial hydration layer could be of interest when using high solid loadings. In recent studies, it was hypothesized that constrained low-entropy water significantly contributes to the biomass recalcitrance in polymer suspensions (≥10 % dry solid, w/w) [68]. A proposed mechanism includes the release of energetically unfavorable water, so revealing hydrophobic spots on the substrate surface and, thus, facilitating unproductive binding of the cellulases. In addition, the formation of steric hindrances due to polymer–polymer junction zones might be possible as a result [68]. It is conceivable that SWO1 with its substantial hydration layer could cover these energetically unfavorable hydrophobic spots and thereby affect the conversion yield positively. However, it is worth noticing that even BSA is reported to exert a similar function in lignocellulose pretreatment by reducing the unproductive adsorption of cellulases to lignin [70]. However, we have to emphasize strongly that those images were recorded under non-physiological conditions. These findings are clearly at variance, and appear difficult to reconcile, with a number of recent papers and also the original work of Saloheimo et al. [18], reporting a cellulose structure-altering activity of the respective SWO1 preparation used. The question of how much of the difference in the findings can be attributed to the varying SWO1 preparations used is difficult to answer. Significant variations in the experimental conditions used are noted. However, even experiments with a comparable setup gave widely differing results. For instance, using Avicel PH-101, which is a commonly applied and well-characterized model substrate for crystalline cellulose [58, 71, 72], a number of studies reported a reduction in particle size after incubation with SWO1 [34, 37, 38, 40]. Furthermore, three studies using Avicel PH-101 from the same manufacturer, comparable enzyme loadings, incubation time and temperature also tried to quantify the particle size reduction [34, 37, 40] (see Table 1). Despite high similarity of the experimental setup used, the size reduction varied between ~50 % [34], ~25 % [37] and even nil in one study [40]. Thus, we think that SWO1 is probably a prime source of variability in the different studies. Georgelis et al. [20] examined several expansin-like proteins from different microorganisms, including Aspergillus niger. They found all proteins to be active in a cell wall extension assay, whereas none of them showed synergy with individual T. reesei cellulases or the complete enzyme complex hydrolyzing filter paper. The picture emerging from several studies of expansin synergy with cellulases is that expansin exhibits highest effectiveness when lignocellulosic feedstocks, not pure celluloses, are used as the substrates [44, 54, 73]. This notion is in agreement with our finding that SWO1 prefers to bind to xylan and that synergy with cellulases was detectable on an untreated lignocellulosic substrate. Gourlay et al. [44] reported large factors of synergy between individual xylanases and SWO1 in the release of xylose from steam-pretreated corn stover. Summing up, these findings fit quite well together and already suggest a potential structural target for synergistic interplay of SWO1 with cellulases and hemicellulases, respectively. Moreover, in earlier studies, xylan and xylooligomers [68, 74, 75] were recognized as potent inhibitors for cellulases. Thus, understanding and overcoming inhibition caused by xylans and xylooligomers eventually would be highly interesting from a scientific and applied point of view. However, we did not observe synergy between SWO1 and T. viride β-xylanase M1 (data not shown) in the conversion of xylan into reducing sugars. Overall, the effectiveness of SWO1 in acting in synergy with cellulases and hemicellulases deserves further systematic investigation. Ultimately, our results suggest that SWO1 is not a C1 factor of degradation of pure cellulose. Still, there is a possibility that unknown proteins or co-factors (e.g., metals) are necessary to fully unlock the potential of SWO1 in that function. Although, according to our knowledge, there is no evidence in the literature for additional proteins or factors required to promote the activity of SWO1 or expansins in general, this possibility might inspire promising future investigations. Conclusions In summary, some basic biochemical characteristics of the native SWO1 were presented. The protein is strongly glycosylated. O-glycosylation appeared to predominate over N-glycosylation. Results of CD spectroscopic characterization agree with evidence from molecular modeling, suggesting a folded protein with a high relative content of β-strands. Although SWO1 binds to crystalline cellulose, its adsorption to xylan is much stronger. A role of isolated SWO1 as a factor of amorphogenesis of pure cellulose was not supported. According to the classical C1–Cx postulate, SWO1 is not a C1 factor of degradation of the pure cellulosic substrates examined herein, neither in regard to affecting their morphology on adsorption, nor to acting in synergy with the cellulases in their hydrolysis. However, the release of sugar from barley β-glucan and cellotetraose might reflect a weak intrinsic hydrolase activity of SWO1. Synergy with T. reesei cellulases strongly depended on the substrate used. While absent with pure celluloses, a slight beneficial effect of SWO1 on soluble sugar release from untreated biomass sample with intact plant cell walls was observed. This might be relevant, with certain (e.g., mildly pretreated) lignocellulosic substrates, and even exploitable if the effect is preserved at increased substrate loadings. Methods Enzymes and substrates Complete T. reesei cellulase was from fungal culture (strain SVG17) on wheat straw. TrCBH I was purified from the cellulase mixture using a reported ion exchange protocol [76]. Serum albumin fraction V (BSA) was bought from Roth (Karlsruhe, Germany), β-glucosidase from Aspergillus niger and β-xylanase M1 from T. viride were obtained from Megazyme International (Wicklow, Ireland). Avicel PH-101 and lignin (alkali, low sulfonate content) were obtained from Sigma-Aldrich (St. Louis, MO, USA), barley β-glucan (high viscosity > 100 cST) from Megazyme International (Wicklow, Ireland), birch xylan from Roth (Karlsruhe, Germany), cellotetraose and 4-methylumbelliferyl-β-d-cellobioside from Carbosynth (Compton, UK). CNC was prepared from Whatman® qualitative filter paper (Sigma-Aldrich, St. Louis, MO, USA) using H2SO4 according to Lu et al. [63]. Amorphous thin film cellulose (ATFC) was prepared from trimethylsilyl cellulose by a reported procedure [57]. Construction of a T. reesei expression strain for SWO1 production, and culture conditions used T. reesei Δxyr1 was used as the recipient strain for the swo1 expression plasmid and maintained on potato dextrose agar at 28 °C. The strain is deleted in the major cellulase and xylanase regulator xyr1 and derived from strain QM9414 (ATCC 26921). Fermentations were carried out in Biostat® A Plus bioreactors (Sartorius, Göttingen, Germany) in a 2-L working volume. One liter of fermenter medium comprised 4.6 g (NH4)2SO4, 3 g KH2PO4, 0.3 g MgSO4·7H2O, 0.4 g CaCl2, 20 mL of 50× trace elements solution (250 mg/L FeSO4·7H2O, 80 mg/L MnSO4·H2O, 70 mg/L ZnSO4·7H2O, 100 mg/L CoCl2·2H2O), 0.5 mL Tween 80 and 50 g d-glucose. The fermenter was inoculated with a preculture. Therefore, about 106 spores/mL were added to 250 mL minimal medium [49] in a 1-L Erlenmeyer flask and grown for about 24 h at 28 °C in a rotary shaker at 250 rpm. Fermentation conditions were 28 °C, 500 rpm, an air flow rate of 2–3 L/min and pH 5.0 adjusted with 1 M NH4OH or 1 M HCl. Supernatants were separated from fungal biomass by centrifugation for 20 min at 4 °C and 4200 rpm followed by filtration of the supernatants through a Miracloth sheet (Calbiochem, San Diego, CA, USA). Samples were stored at −20 °C prior to purification. Construction of swo1-expressing T. reesei strains The swo1 coding region (XP_006969225.1) including 575 bp of its terminator region was PCR-amplified with primers infuse_swo1_fw (5′-caacttctctcatcgatgaactgttagacgggatggc-3′) and infuse_swo1_rv (5′-tgcaggtcgacatcgatgcgtgcctgtgtatcaattg-3′) from genomic DNA of T. reesei QM6a (ATCC13631) and cloned into the ClaI-digested pLH_hph_Pcdna1 expression plasmid using the InFusion® HD Cloning Kit (Clontech Laboratories, Inc., Mountain View, CA, USA). This swo1 expression plasmid (p_swo1oe) contains the hygromycin B phosphotransferase (hph) expression cassette as fungal selection marker and 930 bp of the T. reesei cdna1 promoter region [49] to drive swo1 expression. DNA fragments were purified using the QIAquick gel extraction kit (QIAGEN GmbH, Hilden, Germany). The circular p_swo1oe was used to transform T. reesei QM9414Δxyr1 via electroporation. Conidia of a fully sporulated PDA Petri dish (Difco, Detroit, MI, USA) were harvested, filtered through glass wool and inoculated in 100 mL of YPD (10 g/L yeast extract, 20 g/L peptone) +2 % d-glucose followed by incubation in a rotary shaker for 4 h at 30 °C and 300 rpm. Then, the conidia were pelleted, washed three times with cold 1.1 M d-sorbitol (Alfa Aesar GmbH & Co KG, Karlsruhe, Germany), and resuspended in 300 µL of cold 1.1 M d-sorbitol. Seventy-five-microliter aliquots were mixed with 10–15 µL (10–30 µg) of p_swo1oe and electroporated at 1.8 kV using 0.1-cm cuvettes in a MicroPulser (Biorad, Hercules, CA, USA). Thereafter, cells were recovered in a premixed solution of 400 µLöö 1.1 M d-sorbitol + 125 µL YPD and incubated in a Thermomixer (Eppendorf, Hamburg, Germany) for 1 h at 28 °C and 800 rpm before plated on selection medium (PDA + 100 mg/L hygromycin B (Carl Roth + Co KG, Karlsruhe, Germany). Transformants were purified by single spore isolations on selection medium containing 0.1 % v/v Triton X-100. From the transformants, genomic DNA was extracted, and the presence of the swo1 expression cassette was verified by diagnostic PCR using the primer swo1_conf_for (5′-GCCGGCTTCAAAACACACAG-3′) and swo1_conf_rev (5′-GTTGTGTGGAATTGTGAGCGG-3′) resulting in a 2.2-kb fragment in positive transformants. Expression of SWO1 in positive strains was examined using SDS-PAGE. The culture supernatant was analyzed, and the strain designated as RJ_SWO1 was used for further studies. Purification of SWO1 from T. reesei culture supernatant The supernatant was thawed and centrifuged (5 min, 5000 rpm, 4 °C). About 50 mL of supernatant (~2 mg total protein) was mixed with 50 mL of sodium acetate buffer (50 mM; pH 5.0), and Avicel PH-101 (2 g) was added. The suspension was stirred for 2 h at room temperature. Avicel PH-101 was first separated from the supernatant by sedimentation and then washed three times with 50 mL of the same sodium acetate buffer. The Avicel PH-101 was recovered by centrifugation (5 min, 5000 rpm, 4 °C) and then packed under gravity into a disposable 10-mL polypropylene gravity flow column (Thermo Fisher Scientific, Waltham, MA, USA). The column was washed twice in each case with adsorption buffer and doubly distilled H2O to remove non-specifically adsorbed protein. SWO1 was eluted with 1 % triethylamine (TEA) in doubly distilled H2O and collected in an excess of gently mixed adsorption buffer. The eluted fraction was concentrated using ultrafiltration concentrator tubes (Vivaspin®6, MWCO 10 kD) from Sartorius (Goettingen, Germany). SDS-PAGE with Coomassie Brilliant Blue staining showed a single, slightly diffusive protein band with the expected apparent molecular mass. Note that a minor fraction (≤20 %) of partly purified SWO1 was already eluted during the washing step with water. We conducted preliminary adsorption experiments using Avicel PH-101 as adsorbent with both SWO1 fractions. The SWO1 eluted with 1 % TEA showed a slightly higher affinity to Avicel PH-101, however, within the range of experimental error (data not shown). To avoid ambiguities, we only used the SWO1 fraction eluted with TEA in all experiments reported from this study. The protein concentration of solutions of purified SWO1 was determined by intrinsic UV-absorption on a DeNovix DS-11 spectrophotometer (DeNovix Inc., Wilmington, DE, USA). The molar extinction coefficient of SWO1 was determined from the protein sequence from UniProt using ProtParam (ε_SWO1 (Q9P8D0) = 88,655 M−1 cm−1). The purified and concentrated SWO1 was stored at 4 °C. Deglycosylation of SWO1 Deglycosylation of SWO1 was performed according to a standard Endo H protocol (New England Biolabs, Frankfurt, Germany). The purified protein (10 µg) was mixed with 10× denaturation buffer (5 % SDS, 400 mM DTT) up to 40 µL of total volume and incubated at 95 °C for 10 min. Subsequently, one-tenth volume of 10× G7 reaction buffer (500 mM sodium phosphate buffer, pH 7.5) was added. The mixture was incubated with 300 U Endo H at 37 °C for 90 min. Reaction was stopped by heating for 10 min to 95 °C. Deglycosylated samples and untreated controls were analyzed by SDS-PAGE (NuPAGE® Bis–Tris 4–12 %) with glycostaining and subsequent Coomassie Brilliant Blue staining (Thermo Fisher Scientific, Waltham, MA, USA). Glycostaining was done with the Pro-Q Emerald 300 glycostain kit (Invitrogen, Carlsbad, CA) according the manufacturer’s protocol. Circular dichroism and modeling of reference data Circular dichroism spectra were acquired on a Jasco J-175 spectropolarimeter (Jasco Analytical Instruments, Groß-Umstadt, Germany) using a 10-mm cylindrical quartz cell. SWO1 was used at a concentration of 0.1 mg/mL in 50 mM sodium acetate buffer, pH 5.0, at room temperature. The baseline of the spectra was obtained from pure buffer. The standard parameters for protein evaluation were chosen with a sensitivity of 100 mdeg, a start wavelength of 250–320 nm, an end wavelength of 190–250 nm and a data pitch of 1 nm. For good data quality, a slow scanning mode with a continuous scanning speed of 10 nm/min was chosen. The combined spectra were evaluated online with DichroWeb, which calculated the secondary structure elements of SWO1. To obtain reference date for SWO1, the automated protein structure homology-modeling server Phyre2 was used to predict the protein structure of SWO1 [50]. The sequence of SWO1 from UniProt (ID: Q9P8D0) was used except for the amino acids 1–18, which are predicted to be cleaved off after secretion. The obtained protein model was used to calculate the percentage of secondary structure elements. A second set of reference data was obtained using the sequence-based JNet algorithm (JPred4) (http://www.compbio.dundee.ac.uk/jpred4/index.html) to calculate the percentage of secondary structure elements as described elsewhere [51]. Characterization of SWO1 binding affinity All adsorption isotherm measurements were carried out in 1.5-mL Eppendorf tubes containing serial dilutions of SWO1 (0.2–25 µM) mixed with an equal volume of an aqueous suspension of substrate (Avicel PH-101, birchwood xylan and lignin) to a final concentration of 1 mg/mL in 50 mM sodium acetate buffer (pH 5.0) in a total reaction volume of 200 µL. All adsorption experiments were conducted in triplicates at 25 °C with orbital shaking (500 rpm) over 2 h using an Eppendorf Thermomixer comfort (Eppendorf AG, Hamburg, Germany). An incubation time of 2 h was sufficient to reach adsorption equilibrium according to previously published articles [37] and preliminary experiments on Avicel PH-101 (data not shown). The samples were then centrifuged (5 min, 13,000 rpm, 25 °C) to remove solids. The clear supernatant was collected, and protein concentration was determined by BCA (Thermo Fisher Scientific, Waltham, MA, USA) (Avicel PH-101) and Roti-Nanoquant assay (Carl Roth + Co KG, Karlsruhe, Germany) (xylan and lignin). TrCBH I was used as standard. The equilibrium association constants (Kd) were determined by nonlinear regression of bound versus free protein concentrations to Langmuir model as described previously. A control showed that unspecific binding of SWO1 to the reaction tubes was negligible. Activity of SWO1 on crystalline cellulose substrates SWO1 was incubated with Avicel PH-101 or CNC in 50 mM sodium acetate buffer, pH 5.0, in a total reaction volume of 500 µL at 40 °C and 500 rpm using an Eppendorf Thermomixer comfort (Eppendorf AG, Hamburg, Germany). Experiments were done in four replicates, and the substrate concentration was 1.0 mg/mL (Avicel PH-101 or CNC). Samples were incubated with either 0.4 µM SWO1 or an equimolar amount BSA. Samples were taken after 12 and 24 h, respectively. About 100 µL of the supernatant was withdrawn and heated to 95 °C for 10 min to stop the reaction. Subsequently, the samples were centrifuged (13,000 rpm, 1 min, 25 °C), and β-glucosidase was added to a final concentration of 2 µg/mL to the cleared supernatant. The reaction mixture was incubated for 1 h at 37 °C to convert of released cello-oligosaccharides to glucose. Finally, the amount of released glucose in the supernatant was assayed colorimetrically with glucose oxidase and peroxidase as described in earlier works [12]. Hydrolysis of β-glucan and cellotetraose by SWO1 Hydrolysis of soluble glucans was studied at 1 mg/mL (β-glucan) or 0.5 mg/mL (cellotetraose), respectively. All experiments were carried out as duplicates in 50 mM sodium acetate buffer, pH 5.0, in a total reaction volume of 400 µL at 40 °C and 500 rpm. The reaction was started with the addition of SWO1 or an equimolar amount of BSA. The final enzyme concentration was 0.2 (β-glucan) or 0.5 µM (cellotetraose), respectively. The reaction was stopped after 24 h by adding an equal volume of 100 mM NaOH. Precipitated material was removed by centrifugation (3 min, 13,000 rpm, 25 °C). The cleared supernatant was analyzed with high-performance anion-exchange chromatography coupled to pulsed-amperometric detection (HPAEC-PAD) (Dionex BioLC, Thermo Fisher Scientific, Waltham, MA) as described elsewhere [57]. Identity and amount of released sugars were assayed using authentic standards. Enzymatic hydrolysis of crystalline cellulose pretreated with SWO1 The impact of SWO1 supplementation on the hydrolysis of a typical fungal cellulase set was assayed in 50 mM sodium acetate buffer, pH 5.0 at 40 °C and 500 rpm in an Eppendorf Thermomixer comfort (Eppendorf AG, Hamburg, Germany). Substrate concentration was 1.0 mg/mL of cellulose (Avicel PH-101 or CNC) in a total reaction volume of 1.5 mL. Reactions were repeated four times. Pretreatment was done over 24 h with 0.4 µM SWO1 or BSA as reference. Afterward, T. reesei cellulase and β-glucosidase were added in a small volume (60 µL) to a final enzyme loading of 20 µg and 4 µg/mg substrate, respectively. Sampling was performed at suitable time points. In brief, 150 μL of the well-mixed supernatant was withdrawn and heated to 95 °C for 10 min to stop the reaction. Subsequently, the samples were centrifuged (13,000 rpm, 1 min, 25 °C), and the amount of released glucose in the supernatant was assayed colorimetrically with glucose oxidase and peroxidase as described above. Enzymatic hydrolysis of lingocellulosic material with supplementation of SWO1 Hydrolysis experiments with Dactylis glomerata grass were conducted in duplicates in a parallel assay. Fifty mM sodium acetate buffer, pH 5.0, was used in a total volume of 1 mL at 40 °C. The samples were shaken at 500 rpm in an Eppendorf Thermomixer comfort (Eppendorf AG, Hamburg, Germany). Prior to hydrolysis experiments, Dactylis glomerata grass was dried at 80 °C overnight. Substrate concentration was 5.0 mg/mL, and cellulase was added to a final protein loading of 2 µg/mg substrate. SWO1 was present at 0.02 µM, and the reference experiment used an equimolar amount of BSA instead of SWO1. Sampling was performed at suitable times. About 100 µL of the well-mixed supernatant was withdrawn and mixed with 100 μL of 100 mM NaOH to stop the reaction. Subsequently, the samples were centrifuged (13,000 rpm, 1 min, 25 °C), and the amount of released sugars in the cleared supernatant was assayed colorimetrically with the 3,5-dinitrosalicylic acid-based assay calibrated against glucose [77]. Atomic force microscopy (AFM) imaging of SWO1 activity Investigations of the incubated samples were carried out on a FastScan Bio AFM (Bruker AXS, CA, USA), operated by a NanoScope V controller and FastScan A cantilevers (Bruker AXS, CA, USA) at room temperature. Setpoints, scan rates and controlling parameters were chosen carefully to ensure lowest possible energy dissipation to the sample and to exclude tip-driven artifacts. Prior to AFM investigation, fully amorphous (ATFC) and highly crystalline cellulose (CNC) preparations were spin-casted on silicon wafers as described previously. Experiments were conducted as duplicates at 40 °C in a water bath with mild agitation. A single silicon wafer covered with cellulosic material was used as the substrate in a total reaction volume of 2 mL of 50 mM sodium acetate buffer (pH 5.0). Cellulosic material was equilibrated in buffer for 30 min prior to the addition of enzyme. The respective enzyme, SWO1 or BSA (only CNC) as negative control, was added to a final concentration of 0.4 µM. The reaction was conducted over 24 h and stopped by removing the silica wafers from the reaction mixture and rinsing them with 15 mL doubly distilled H2O to remove salt crystals. Afterward, CNC-coated silica wafers were dried for 24 h up to 48 h at room temperature prior to AFM investigations. Silica wafers coated with ATFC were stored at 4 °C in doubly distilled H2O and examined in a laboratory-built liquid cell. The storage time did not exceed 6 h. AFM image processing and analysis was performed using NanoScope Analysis 1.50 (Build R2.103555, Bruker AXS, CA, USA) and Gwyddion 2.31 (Released 2013-02-01, http://gwyddion.net/). Wide-angle x-ray scattering (WAXS) Wide-angle x-ray scattering analysis (WAXS) was carried out on a Siemens D 5005 diffractometer (Siemens, Berlin, Germany) using CuKα (0.154 nm) radiation at 40 kV and 40 mA. 10 mg/mL Avicel PH-101 was incubated with 0.01 µM SWO1 for 72 h in a shaking water bath (GFL 1083) at 50 rpm. As a reference, Avicel PH-101 without SWO1 incubation was used. The probes were dried at 60 °C overnight, and were put on a zero-diffraction silicon crystal holder (Bruker AXS, CA, USA). All samples were characterized in locked coupled Θ/2Θ mode from 10° to 60° (Θ/2Θ) with an angle increment of 0.05° in 6 s. Data analysis was performed using Origin 9.0 (OriginLab Corp., Northampton, MA, USA). Abbreviations ATFCamorphous thin film cellulose BSAbovine serum albumin CAEcongo red adsorption enhancement CBHcellobiohydrolase CBMcarbohydrate-binding module CNCcellulose nanocrystals EGendoglucanase ESEMenvironmental scanning electron microscope Fn-IIIfibronectin-III HPAEC-PADhigh performance anion exchange chromatography coupled to pulsed-amperometric detection SDstandard deviation SEMscanning electron microscope TEAtriethylamine WAXSwide-angle x-ray scattering analysis Manuel Eibinger and Karin Sigl should be considered equal first authors Authors’ contributions ME, KS and BN designed the research. JR and BS constructed the T. reesei strain and produced the culture supernatant containing SWO1. KS and ME planned and performed the biochemical experiments and analyzed the data. JS, TG and ME carried out the AFM and WAXS measurements and analyzed the data under the guidance of HP. All authors contributed to drafting of the manuscript. ME and BN wrote the paper with assistance from KS. All authors read and approved the final manuscript. Acknowledgements Dr. Christian Berg (Institute of Plant Sciences, University of Graz) provided the sample of cock’s foot grass. Christian Fercher (Institute of Molecular Biosciences, University of Graz) supported the CD measurements. Natascha Loppitsch (Institute of Biotechnology and Biochemical Engineering, Graz University of Technology) assisted in SWO1 purification. Competing interests The authors declare that they have no competing interests. Funding Financial support was from the Austrian Science Fund, projects P24156-B21 (to BN) and P24219 (to BS). BS further acknowledges support from the European Regional Development Fund: Regio 13—Impulse für Oberösterreich. ==== Refs References 1. Chundawat SPS Beckham GT Himmel ME Dale BE Deconstruction of lignocellulosic biomass to fuels and chemicals Annu Rev Chem Biomol Eng 2011 2 121 145 10.1146/annurev-chembioeng-061010-114205 22432613 2. Himmel ME Ding SY Johnson DK Adney WS Nimlos MR Brady JW Foust TD Biomass recalcitrance: engineering plants and enzymes for biofuels production Science 2007 315 804 807 10.1126/science.1137016 17289988 3. Sims REH Mabee W Saddler JN Taylor M An overview of second generation biofuel technologies Bioresour Technol 2010 101 1570 1580 10.1016/j.biortech.2009.11.046 19963372 4. Kari J Olsen J Borch K Cruys-Bagger N Jensen K Westh P Kinetics of cellobiohydrolase (Cel7A) variants with lowered substrate affinity J Biol Chem 2014 289 32459 32468 10.1074/jbc.M114.604264 25271162 5. Payne CM Knott BC Mayes HB Hansson H Himmel ME Sandgren M Ståhlberg J Beckham GT Fungal cellulases Chem Rev 2015 115 1308 1448 10.1021/cr500351c 25629559 6. Wu I Arnold FH Engineered thermostable fungal Cel6A and Cel7A cellobiohydrolases hydrolyze cellulose efficiently at elevated temperatures Biotechnol Bioeng 2013 110 1874 1883 10.1002/bit.24864 23404363 7. Wilson DB Cellulases and biofuels Curr Opin Biotechnol 2009 20 295 299 10.1016/j.copbio.2009.05.007 19502046 8. Peterson R Nevalainen H Trichoderma reesei RUT-C30—thirty years of strain improvement Microbiology 2012 158 58 68 10.1099/mic.0.054031-0 21998163 9. Horn SJ Vaaje-Kolstad G Westereng B Eijsink VG Novel enzymes for the degradation of cellulose Biotechnol Biofuels 2012 5 45 10.1186/1754-6834-5-45 22747961 10. Hu J Chandra R Arantes V Gourlay K van Dyk JS Saddler JN The addition of accessory enzymes enhances the hydrolytic performance of cellulase enzymes at high solid loadings Bioresour Technol 2015 186 149 153 10.1016/j.biortech.2015.03.055 25812819 11. Müller G Várnai A Johansen KS Eijsink VGH Horn SJ Harnessing the potential of LPMO-containing cellulase cocktails poses new demands on processing conditions Biotechnol Biofuels 2015 8 187 10.1186/s13068-015-0376-y 26609322 12. Eibinger M Ganner T Bubner P Rošker S Kracher D Haltrich D Ludwig R Plank H Nidetzky B Cellulose surface degradation by a lytic polysaccharide monooxygenase and its effect on cellulase hydrolytic efficiency J Biol Chem 2014 289 35929 35938 10.1074/jbc.M114.602227 25361767 13. Harris PV Xu F Kreel NE Kang C Fukuyama S New enzyme insights drive advances in commercial ethanol production Curr Opin Chem Biol 2014 19 162 170 10.1016/j.cbpa.2014.02.015 24681544 14. Cannella D Jørgensen H Do new cellulolytic enzyme preparations affect the industrial strategies for high solids lignocellulosic ethanol production? Biotechnol Bioeng 2014 111 59 68 10.1002/bit.25098 24022674 15. Cannella D Hsieh C-WC Felby C Jørgensen H Production and effect of aldonic acids during enzymatic hydrolysis of lignocellulose at high dry matter content Biotechnol Biofuels 2012 5 26 10.1186/1754-6834-5-26 22546481 16. Hu J Arantes V Pribowo A Saddler JN Gourlay K Saddler JN Substrate factors that influence the synergistic interaction of AA9 and cellulases during the enzymatic hydrolysis of biomass Energy Environ Sci 2014 7 2308 2315 10.1039/c4ee00891j 17. Sampedro J Cosgrove DJ The expansin superfamily Genome Biol 2005 6 242 10.1186/gb-2005-6-12-242 16356276 18. Saloheimo M Paloheimo M Hakola S Pere J Swanson B Nyyssönen E Bhatia A Ward M Penttilä M Swollenin, a Trichoderma reesei protein with sequence similarity to the plant expansins, exhibits disruption activity on cellulosic materials Eur J Biochem 2002 269 4202 4211 10.1046/j.1432-1033.2002.03095.x 12199698 19. Cosgrove DJ Loosening of plant cell walls by expansins Nature 2000 407 321 326 10.1038/35030000 11014181 20. Georgelis N Nikolaidis N Cosgrove DDJ Biochemical analysis of expansin-like proteins from microbes Carbohydr Polym 2014 100 17 23 10.1016/j.carbpol.2013.04.094 24188833 21. Liu X Ma Y Zhang M Research advances in expansins and expansion-like proteins involved in lignocellulose degradation Biotechnol Lett 2015 37 1541 1551 10.1007/s10529-015-1842-0 25957563 22. Cosgrove DJ New genes and new biological roles for expansins Curr Opin Plant Biol 2000 3 73 78 10.1016/S1369-5266(99)00039-4 10679451 23. McQueen-Mason S Cosgrove DJ Disruption of hydrogen bonding between plant cell wall polymers by proteins that induce wall extension Proc Natl Acad Sci USA 1994 91 6574 6578 10.1073/pnas.91.14.6574 11607483 24. Brotman Y Briff E Viterbo A Chet I Role of swollenin, an expansin-like protein from Trichoderma , in plant root colonization Plant Physiol 2008 147 779 789 10.1104/pp.108.116293 18400936 25. Georgelis N Nikolaidis N Cosgrove DJ Bacterial expansins and related proteins from the world of microbes Appl Microbiol Biotechnol 2015 99 3807 3823 10.1007/s00253-015-6534-0 25833181 26. Yennawar NH Li L-C Dudzinski DM Tabuchi A Cosgrove DJ Crystal structure and activities of EXPB1 (Zea m 1), a beta-expansin and group-1 pollen allergen from maize Proc Natl Acad Sci USA 2006 103 14664 14671 10.1073/pnas.0605979103 16984999 27. Kerff F Amoroso A Herman R Sauvage E Petrella S Filée P Charlier P Joris B Tabuchi A Nikolaidis N Cosgrove DJ Crystal structure and activity of Bacillus subtilis YoaJ (EXLX1), a bacterial expansin that promotes root colonization Proc Natl Acad Sci USA 2008 105 16876 16881 10.1073/pnas.0809382105 18971341 28. Verma D Jin S Kanagaraj A Singh ND Daniel J Kolattukudy PE Miller M Daniell H Expression of fungal cutinase and swollenin in tobacco chloroplasts reveals novel enzyme functions and/or substrates PLoS One 2013 8 e57187 10.1371/journal.pone.0057187 23451186 29. Arantes V Saddler JN Access to cellulose limits the efficiency of enzymatic hydrolysis: the role of amorphogenesis Biotechnol Biofuels 2010 3 4 10.1186/1754-6834-3-4 20178562 30. Seki Y Kikuchi Y Yoshimoto R Aburai K Kanai Y Ruike T Iwabata K Goitsuka R Sugawara F Abe M Sakaguchi K Promotion of crystalline cellulose degradation by expansins from Oryza sativa Planta 2014 241 83 93 10.1007/s00425-014-2163-6 25218793 31. Kim ES Lee HJ Bang W-G Choi I-G Kim KH Functional characterization of a bacterial expansin from Bacillus subtilis for enhanced enzymatic hydrolysis of cellulose Biotechnol Bioeng 2009 102 1342 1353 10.1002/bit.22193 19058186 32. Georgelis N Tabuchi A Nikolaidis N Cosgrove DJ Structure-function analysis of the bacterial expansin EXLX1 J Biol Chem 2011 286 16814 16823 10.1074/jbc.M111.225037 21454649 33. Georgelis N Yennawar NH Cosgrove DJ Structural basis for entropy-driven cellulose binding by a type-A cellulose-binding module (CBM) and bacterial expansin Proc Natl Acad Sci USA 2012 109 14830 14835 10.1073/pnas.1213200109 22927418 34. Chen X Ishida N Todaka N Nakamura R Maruyama J Takahashi H Kitamoto K Promotion of efficient Saccharification of crystalline cellulose by Aspergillus fumigatus Swo1 Appl Environ Microbiol 2010 76 2556 2561 10.1128/AEM.02499-09 20173066 35. Beckham GT Bomble YJ Bayer EA Himmel ME Crowley MF Applications of computational science for understanding enzymatic deconstruction of cellulose Curr Opin Biotechnol 2011 22 231 238 10.1016/j.copbio.2010.11.005 21168322 36. Kostylev M Wilson D A distinct model of synergism between a processive endocellulase (TfCel9A) and an exocellulase (TfCel48A) from Thermobifida fusca Appl Environ Microbiol 2014 80 339 344 10.1128/AEM.02706-13 24162578 37. Jäger G Girfoglio M Dollo F Rinaldi R Bongard H Commandeur U Fischer R Spiess ACC Büchs J How recombinant swollenin from Kluyveromyces lactis affects cellulosic substrates and accelerates their hydrolysis Biotechnol Biofuels 2011 4 33 10.1186/1754-6834-4-33 21943248 38. Wang Y Tang R Tao J Gao G Wang X Mu Y Feng Y Quantitative investigation of non-hydrolytic disruptive activity on crystalline cellulose and application to recombinant swollenin Appl Microbiol Biotechnol 2011 91 1353 1363 10.1007/s00253-011-3421-1 21732246 39. Kang K Wang S Lai G Liu G Xing M Characterization of a novel swollenin from Penicillium oxalicum in facilitating enzymatic saccharification of cellulose BMC Biotechnol 2013 13 42 10.1186/1472-6750-13-42 23688024 40. Zhou Q Lv X Zhang X Meng X Chen G Liu W Evaluation of swollenin from Trichoderma pseudokoningii as a potential synergistic factor in the enzymatic hydrolysis of cellulose with low cellulase loadings World J Microbiol Biotechnol 2011 27 1905 1910 10.1007/s11274-011-0650-5 41. Gourlay K Arantes V Saddler JN Use of substructure-specific carbohydrate binding modules to track changes in cellulose accessibility and surface morphology during the amorphogenesis step of enzymatic hydrolysis Biotechnol Biofuels 2012 5 51 10.1186/1754-6834-5-51 22828270 42. Gourlay K Hu J Arantes V Penttilä M Saddler JN The use of carbohydrate binding modules (CBMs) to monitor changes in fragmentation and cellulose fiber surface morphology during cellulase- and swollenin-induced deconstruction of lignocellulosic substrates J Biol Chem 2015 290 2938 2945 10.1074/jbc.M114.627604 25527502 43. Wang M Cai J Huang L Lv Z Zhang Y Xu Z High-level expression and efficient purification of bioactive swollenin in Aspergillus oryzae Appl Biochem Biotechnol 2010 162 2027 2036 10.1007/s12010-010-8978-0 20446057 44. Gourlay K Hu J Arantes V Andberg M Saloheimo M Penttilä M Saddler J Swollenin aids in the amorphogenesis step during the enzymatic hydrolysis of pretreated biomass Bioresour Technol 2013 142C 498 503 10.1016/j.biortech.2013.05.053 23759433 45. Wang W Liu C Ma Y Liu X Zhang K Zhang M Improved production of two expansin-like proteins in Pichia pastoris and investigation of their functional properties Biochem Eng J 2014 84 16 27 10.1016/j.bej.2013.12.018 46. Payne CM Resch MG Chen L Crowley MF Himmel ME Taylor LE Sandgren M Ståhlberg J Stals I Tan Z Beckham GT Glycosylated linkers in multimodular lignocellulose-degrading enzymes dynamically bind to cellulose Proc Natl Acad Sci USA 2013 110 14646 14651 10.1073/pnas.1309106110 23959893 47. Jeoh T Michener W Himmel ME Decker SR Adney WS Implications of cellobiohydrolase glycosylation for use in biomass conversion Biotechnol Biofuels 2008 1 10 10.1186/1754-6834-1-10 18471276 48. Andberg M Penttilä M Saloheimo M Swollenin from Trichoderma reesei exhibits hydrolytic activity against cellulosic substrates with features of both endoglucanases and cellobiohydrolases Bioresour Technol 2015 181 105 113 10.1016/j.biortech.2015.01.024 25643956 49. Uzbas F Sezerman U Hartl L Kubicek CP Seiboth B A homologous production system for Trichoderma reesei secreted proteins in a cellulase-free background Appl Microbiol Biotechnol 2012 93 1601 1608 10.1007/s00253-011-3674-8 22080343 50. Kelley LA Sternberg MJE Protein structure prediction on the web: a case study using the Phyre server Nat Protoc 2009 4 363 371 10.1038/nprot.2009.2 19247286 51. Drozdetskiy A Cole C Procter J Barton GJ JPred4: a protein secondary structure prediction server Nucleic Acids Res 2015 43 389 394 10.1093/nar/gkv332 52. Várnai A Siika-aho M Viikari L Restriction of the enzymatic hydrolysis of steam-pretreated spruce by lignin and hemicellulose Enzym Microb Technol 2010 46 185 193 10.1016/j.enzmictec.2009.12.013 53. Rowe RC McKillop AG Bray D The effect of batch and source variation on the crystallinity of microcrystalline cellulose Int J Pharm 1994 101 169 172 10.1016/0378-5173(94)90087-6 54. Bunterngsook B Eurwilaichitr L Thamchaipenet A Champreda V Binding characteristics and synergistic effects of bacterial expansins on cellulosic and hemicellulosic substrates Bioresour Technol 2015 176 129 135 10.1016/j.biortech.2014.11.042 25460993 55. Kim IJ Ko HJ Kim TW Nam KH Choi IG Kim KH Binding characteristics of a bacterial expansin (BsEXLX1) for various types of pretreated lignocellulose Appl Microbiol Biotechnol 2013 97 5381 5388 10.1007/s00253-012-4412-6 23053073 56. Sharrock KR Cellulase assay methods: a review J Biochem Biophys Methods 1988 17 81 105 10.1016/0165-022X(88)90040-1 3063738 57. Ganner T Roŝker S Eibinger M Kraxner J Sattelkow J Rattenberger J Fitzek H Chernev B Grogger W Nidetzky B Plank H Tunable semicrystalline thin film cellulose substrate for high-resolution, in-situ AFM characterization of enzymatic cellulose degradation ACS Appl Mater Interfaces 2015 7 27900 27909 10.1021/acsami.5b09948 26618709 58. Park S Baker JO Himmel ME Parilla PA Johnson DK Cellulose crystallinity index: measurement techniques and their impact on interpreting cellulase performance Biotechnol Biofuels 2010 3 10 10.1186/1754-6834-3-10 20497524 59. Goacher RE Selig MJ Master ER Advancing lignocellulose bioconversion through direct assessment of enzyme action on insoluble substrates Curr Opin Biotechnol 2014 27 123 133 10.1016/j.copbio.2014.01.009 24525082 60. Ganner T Aschl T Eibinger M Bubner P Meingast A Chernev B Mayrhofer C Nidetzky B Plank H Tunable mixed amorphous—crystalline cellulose substrates (MACS) for dynamic degradation studies by atomic force microscopy in liquid environments Cellulose 2014 21 3927 3939 10.1007/s10570-014-0419-8 61. Ganner T Bubner P Eibinger M Mayrhofer C Plank H Nidetzky B Dissecting and reconstructing synergism—in situ visualization of cooperativity among cellulases J Biol Chem 2012 287 43215 43222 10.1074/jbc.M112.419952 23118223 62. Eibinger M Bubner P Ganner T Plank H Nidetzky B Surface structural dynamics of enzymatic cellulose degradation, revealed by combined kinetic and atomic force microscopy studies FEBS J 2014 281 275 290 10.1111/febs.12594 24320702 63. Lu P Hsieh Y-L Preparation and properties of cellulose nanocrystals: rods, spheres, and network Carbohydr Polym 2010 82 329 336 10.1016/j.carbpol.2010.04.073 64. Kim IJ Ko HJ Kim TW Choi IG Kim KH Characteristics of the binding of a bacterial expansin (BsEXLX1) to microcrystalline cellulose Biotechnol Bioeng 2013 110 401 407 10.1002/bit.24719 22949138 65. Lee HJ Kim IJ Kim JF Choi I-G Kim KH An expansin from the marine bacterium Hahella chejuensis acts synergistically with xylanase and enhances xylan hydrolysis Bioresour Technol 2013 149 516 519 10.1016/j.biortech.2013.09.086 24140897 66. Chundawat SPS Bellesia G Uppugundla N da Costa Sousa L Gao D Cheh AM Agarwal UP Bianchetti CM Phillips GN Langan P Balan V Gnanakaran S Dale BE Restructuring the crystalline cellulose hydrogen bond network enhances its depolymerization rate J Am Chem Soc 2011 133 11163 11174 10.1021/ja2011115 21661764 67. Selig MJ Thygesen LG Johnson DK Himmel ME Felby C Mittal A Hydration and saccharification of cellulose Iβ, II and IIII at increasing dry solids loadings Biotechnol Lett 2013 35 1599 1607 10.1007/s10529-013-1258-7 23881312 68. Selig MJ Thygesen LG Felby C Correlating the ability of lignocellulosic polymers to constrain water with the potential to inhibit cellulose saccharification Biotechnol Biofuels 2014 7 159 10.1186/s13068-014-0159-x 25426165 69. Selig MJ Hsieh CWC Thygesen LG Himmel ME Felby C Decker SR Considering water availability and the effect of solute concentration on high solids saccharification of lignocellulosic biomass Biotechnol Prog 2012 28 1478 1490 10.1002/btpr.1617 22915470 70. Yang B Wyman CE BSA treatment to enhance enzymatic hydrolysis of cellulose in lignin containing substrates Biotechnol Bioeng 2006 94 611 617 10.1002/bit.20750 16673419 71. Zhang Y Lynd L A functionally based model for hydrolysis of cellulose by fungal cellulase Biotechnol Bioeng 2006 94 888 898 10.1002/bit.20906 16685742 72. Bubner P Plank H Nidetzky B Visualizing cellulase activity Biotechnol Bioeng 2013 110 1529 1549 10.1002/bit.24884 23456755 73. Bunterngsook B Mhuantong W Champreda V Thamchaiphenet A Eurwilaichitr L Identification of novel bacterial expansins and their synergistic actions on cellulose degradation Bioresour Technol 2014 159 64 71 10.1016/j.biortech.2014.02.004 24632627 74. Qing Q Yang B Wyman CE Xylooligomers are strong inhibitors of cellulose hydrolysis by enzymes Bioresour Technol 2010 101 9624 9630 10.1016/j.biortech.2010.06.137 20708404 75. Qing Q Wyman CE Supplementation with xylanase and β-xylosidase to reduce xylo-oligomer and xylan inhibition of enzymatic hydrolysis of cellulose and pretreated corn stover Biotechnol Biofuels 2011 4 18 10.1186/1754-6834-4-18 21702938 76. Medve J Lee D Tjerneld F Ion-exchange chromatographic purification and quantitative analysis of Trichoderma reesei cellulases cellobiohydrolase I, II and endoglucanase II by fast protein liquid chromatography J Chromatogr A 1998 808 153 165 10.1016/S0021-9673(98)00132-0 77. Xiao Z Storms R Tsang A Microplate-based filter paper assay to measure total cellulase activity Biotechnol Bioeng 2004 88 832 837 10.1002/bit.20286 15459905 78. Morrison JM Elshahed MS Youssef NH Defined enzyme cocktail from the anaerobic fungus Orpinomyces sp. strain C1A effectively releases sugars from pretreated corn stover and switchgrass Sci Rep 2016 6 29217 10.1038/srep29217 27381262

PMC005xxxxxx/PMC5000518.txt

==== Front OncogeneOncogeneOncogene0950-92321476-5594Nature Publishing Group onc201551110.1038/onc.2015.51126853465Original ArticleInhibition of cholesterol metabolism underlies synergy between mTOR pathway inhibition and chloroquine in bladder cancer cells Mechanism of synergy between CQ and AKT/mTORiKing M A 1*Ganley I G 2Flemington V 3*1 AstraZeneca Oncology, Alderley Park, Macclesfield, Cheshire, UK2 MRC Protein Phosphorylation and Ubiquitylation Unit, University of Dundee, Dundee, UK3 AstraZeneca Oncology, CRUK Cambridge Institute, Li Ka Shing Centre, Cambridge CB2 0RE, UK* Oncology iMED, AstraZeneca, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK. E-mail: matthew.king@astrazeneca.com (MAK) or vikki.flemington@astrazeneca.com (VF)25 08 2016 08 02 2016 35 34 4518 4528 28 07 2015 12 11 2015 04 12 2015 Copyright © 2016 Macmillan Publishers Limited2016Macmillan Publishers LimitedThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Mutations to fibroblast growth factor receptor 3 (FGFR3) and phosphatase and tensin homologue (PTEN) signalling pathway components (for example, PTEN loss, PIK3CA, AKT1, TSC1/2) are common in bladder cancer, yet small-molecule inhibitors of these nodes (FGFR/PTENi) show only modest activity in preclinical models. As activation of autophagy is proposed to promote survival under FGFR/PTENi, we have investigated this relationship in a panel of 18 genetically diverse bladder cell lines. We found that autophagy inhibition does not sensitise bladder cell lines to FGFR/PTENi, but newly identify an autophagy-independent cell death synergy in FGFR3-mutant cell lines between mTOR (mammalian target of rapamycin) pathway inhibitors and chloroquine (CQ)—an anti-malarial drug used as a cancer therapy adjuvant in over 30 clinical trials. The mechanism of synergy is consistent with lysosomal cell death (LCD), including cathepsin-driven caspase activation, and correlates with suppression of cSREBP1 and cholesterol biosynthesis in sensitive cell lines. Remarkably, loss of viability can be rescued by saturating cellular membranes with cholesterol or recapitulated by statin-mediated inhibition, or small interfering RNA knockdown, of enzymes regulating cholesterol metabolism. Modulation of CQ-induced cell death by atorvastatin and cholesterol is reproduced across numerous cell lines, confirming a novel and fundamental role for cholesterol biosynthesis in regulating LCD. Thus, we have catalogued the molecular events underlying cell death induced by CQ in combination with an anticancer therapeutic. Moreover, by revealing a hitherto unknown aspect of lysosomal biology under stress, we propose that suppression of cholesterol metabolism in cancer cells should elicit synergy with CQ and define a novel approach to future cancer treatments. ==== Body Introduction Bladder cancer has a worldwide incidence of roughly 400 000 cases and 150 000 deaths per year, yet there are currently no targeted therapeutics available to patients.1 The disease is genetically complex and presents with a predominance of activating mutations to fibroblast growth factor receptor 3 (FGFR3) and the phosphatidylinositol 3-kinase/AKT/mammalian target of rapamycin (PI3K/AKT/mTOR) (phosphatase and tensin homologue (PTEN)) pathway, highlighting therapeutic opportunities at these nodes.1, 2, 3, 4 Nevertheless, small-molecule inhibitors to these kinases have so far proven ineffective in preclinical models and there is considerable interest in determining the modes of resistance to FGFR and PTEN pathway inhibitors (FGFR/PTENi) in bladder cancer. There is a direct and well-characterised link between AKT/mTOR signalling and macroautophagy (autophagy), which may promote cancer cell survival under PTEN pathway inhibition.5, 6, 7, 8, 9 Specifically, the efficacy of AKT inhibitors in bladder and prostate cancer models, and EGFR/HER2 inhibition in breast and lung carcinomas, is promoted by inhibiting autophagy with chloroquine (CQ).10, 11, 12, 13 Autophagy describes the bulk sequestration of cytosol into double-membraned vesicles and its fusion to the lysosome, wherein substrates are degraded and recycled to support homeostasis under stress.14 Under normal conditions, mTOR represses autophagy via the ATG13/ULK/FIP200 complex, which in turn directs the nucleation of autophagosomes through the Beclin/VPS34 complex.15, 16, 17, 18 Following activation of autophagy, two ubiquitin-like systems regulated by ATG7 mediate autophagosome maturation and completion by LC3 lipidation.19, 20, 21 We have investigated a function for autophagy in a panel of 18 bladder cancer cell lines treated with small-molecule inhibitors targeting nodes of potential therapeutic relevance: FGFR, PI3Kβ/δ, AKT and mTOR (FGFR/PTENi). Modulation of cell death was quantified under these conditions and a function for autophagy was assayed by knockdown of multiple essential components (ATG13, ULK1/2, VPS34, ATG7, ATG3, ATG16L1 and ATG14), CRISPR/Cas9 ATG7 knockout (KO) and chemical inhibitors including CQ, bafilomycin A1 (BafA1) and 3-methyladenine (3MA). Our data reveal little evidence for autophagy in the promotion of survival under FGFR/PTENi, but highlight an autophagy-independent synergistic cell death between AKT or mTOR inhibition and CQ in FGFR-dependent cell lines. Synergistic cell death showed features of lysosome-initiated apoptosis, including cathepsin-dependent caspase activation. We show that inhibition of FGFR/PI3Kα/AKT/mTOR nodes suppress the expression of enzymes regulating cholesterol metabolism in FGFR-dependent cell lines, correlating with the degree to which these compounds potentiate CQ-induced cell death. This form of CQ-driven synergistic cell death is profoundly inhibited by saturating cellular membranes with cholesterol, or recapitulated by inhibiting cholesterol metabolism with atorvastatin (Ato) and knockdown of cholesterol biosynthesis enzymes. Moreover, we found that all FGFR3-mutant cell lines regulate cSREBP1 expression in an mTORC1/2-dependent manner, sensitising these—but not FGFR-wild type (FGFR-WT)—cell lines to CQ-induced cell death under mTORi. These results elucidate how CQ, which is currently being used as a cancer therapy adjuvant in over 30 clinical trials, synergises with inhibitors of mTOR signalling and defines a patient cohort predicted to respond to this combination. This work also highlights a fundamental feature of lysosomal membrane biology, suggesting that cancer therapeutics that impact cholesterol metabolism should combine with CQ and provide an innovative approach to cancer treatment. Results Genetic inhibition of autophagy does not increase the sensitivity of bladder cancer cell lines to FGFR/PTENi Autophagy is reported to promote survival under RTK and AKT inhibition in multiple preclinical cancer models. We therefore used a selection of highly selective and potent kinase inhibitors targeting relevant genetic aberrations along these pathways in bladder cancer cell lines: FGFRi (AZD4547), PI3Kβ/δi (AZD8186), AKTi (AZD5363) and mTORi (AZD2014); and assayed cell death over 5 days.22, 23, 24, 25 Data relating to RT112, which express constitutively active FGFR3 (FGFR3-TACC3), are shown in Figure 1 and used throughout this study to represent our major findings.26 RT112 cultures showed marked sensitivity to both FGFRi and mTORi, but tolerated AKTi and PI3Kβi (Figure 1a). This pattern of cell death was also observed in MGH-U3—defining these two cell lines as FGFR-dependent—but absent across all other cell lines (Supplementary Figure S1A). Nevertheless, FGFRi significantly reduced proliferation in all FGFR3-mutant cell lines, whereas mTORi reduced proliferation across the panel (Supplementary Figure S1C). Western blotting confirms target engagement, also showing that chronic AKT/mTOR inhibition increases the efficiency of LC3 lipidation, but suppresses the volume of LC3 flux (Figure 1b and Supplementary Figures S1B–D).27 The contribution of autophagy to survival under FGFR/PTENi was assayed by small interfering RNA (siRNA)-mediated knockdown of key signalling components coupling mTOR to autophagy activation: ATG13, ULK1/2 and VPS34; and the core autophagy protein ATG7 (Figure 1c). Considerable suppression of protein expression and autophagic flux was achieved in RT112 cells (Figure 1d), and validated across six bladder cancer cell lines (ATG13: 95% knockdown, 68% flux inhibition; ULK: 97% knockdown, 61% flux inhibition; VPS34: 94% knockdown, 56% flux inhibition; and ATG7: 96% knockdown, 51% flux inhibition). A functional consequence of autophagy inhibition by siRNA is demonstrated by the exacerbation of cell death following starvation in Earle's balanced salt solution (EBSS) for 24 h (Figure 1e). Importantly, in combination with FGFR/PTENi, inhibiting the activation of autophagy (ATG13, ULK and VPS34 siRNAs) did not increase cell death in RT112 or any other bladder cell line, irrespective of genetic aberrations to the PTEN pathway, although proliferation was moderately suppressed (Figure 1f and Supplementary Figures S2A–C). RT112 cells showed some evidence for the potentiation of FGFR/mTORi-induced cell death by ATG7 siRNA (Figure 1f); however, on deconvolving the SMARTpool, we found significant variability in cytotoxicity despite similar ATG7 knockdown (Supplementary Figure S2D). We therefore assayed the role of core autophagy components downstream of ATG7 by siRNA knockdown of ATG3, ATG16L1 and ATG14. Again, however, we show that these components do not contribute to the innate resistance of RT112 cells to FGFR/PTENi (Figures 1g and h). To assay directly a function for ATG7, we generated ATG7 KO clones from RT112 cultures using CRISPR/Cas9. RT112 ATG7 KO cultures were disabled for LC3 lipidation and autophagy (Figure 1i), yet showed no increase in sensitivity to FGFR/PTENi (Figure 1j). Conversely, ATG7 KO cells showed increased tolerance for FGFRi and mTORi, similar to that observed under ATG13, ULK and VPS34 knockdown (Figure 1f). Thus, neither the activation of autophagy nor core autophagic processes contribute to the innate resistance of bladder cancer cell lines to FGFR/PTENi. Potentiation of CQ-induced cell death by AKTi is limited to FGFR-dependent cell lines As previous studies reported synergistic cell death between CQ and AKTi, we next screened the bladder panel for combinations of chemical autophagy inhibitors and AKTi or mTORi. CQ, BafA1 and 3MA were used to block autophagy, whereas rapamycin (Rapa) was included to inhibit mTORC1. Over 4 days, a clear difference emerged in the pattern of cell death across the bladder panel, dividing the cell lines into three types (Figure 2a and Supplementary Figure S3). Type-I cells displayed no evidence for the potentiation of CQ-, BafA1- or 3MA-induced cell death with AKT or mTOR inhibitors. Conversely, most lines showed significant protection against BafA1 or CQ cytotoxicity with mTORi (for example, UM-UC-3 and SW1710), correlating with an inhibition of BNIP3 induction, BID cleavage and caspase-3 (CASP3) activation (Figure 2b). This protection was recapitulated by blocking cell cycle progression with the CDK4/6 inhibitor palbociclib, indicating that BafA1-induced cell death is compounded by proliferation (Supplementary Figures S3B and C). Type-II cells are defined by the moderate potentiation of CQ-induced cell death with mTORi, all of which express activating FGFR3 mutations (for example, J82, 97-7). Finally, type-III cells show substantial potentiation of CQ-induced cell death with both AKT and mTOR inhibitors. This response was only observed in FGFR-dependent cell lines—MGH-U3 and RT112—and correlated with BID cleavage and caspase-3 activation (Figures 2a and b). These cells also show moderate potentiation of 3MA-induced cell death with AKTi and mTORi; however, when compared with the exquisite selectivity of BafA1, it is unlikely that this effect is related to inhibition of autophagic flux (Supplementary Figures S3F and G). Rapa treatment demonstrates that type-III cells tolerate mTORC1 inhibition alone, but that targeting this node is sufficient to potentiate cell death with CQ. In contrast, CQ-induced cell death is significantly abated by palbociclib, indicating that similar to BafA1, proliferation exacerbates CQ toxicity (Supplementary Figure S3H). Disruption to autophagy by BafA1 and CQ is confirmed by the accumulation of LC3-II by immunoblotting and immunocytochemistry, revealing that lysosomes swell to 2–5 times their original size under these conditions (Figures 2b–d). In contrast, 3MA showed little effect on LC3-II by immunoblotting, which is reported for other VPS34 inhibitors, yet prevented LC3 punctation by immunocytochemistry.28 Overall, this screen shows that chemical autophagy inhibitors do not generally increase the sensitivity of bladder cell lines to AKT or mTOR inhibitors, yet highlights an intriguing response to these compounds in combination with CQ in FGFR-dependent cells. AKTi and mTORi enhance CQ-induced LCD We reproduced the potentiation of CQ-induced cell death by AKTi and mTORi in RT112 ATG7 KO cells, to demonstrate conclusively that autophagy is unrelated to this cytotoxicity (Figure 3a). Although RT112 ATG7 KO cells showed a small increase in CQ tolerance (cell death EC50 (cdEC50)=48 μm; P=0.003) versus wild-type (WT) (cdEC50)=30 μm), their ultimate sensitivity also confirms that CQ-induced cell death is autophagy-independent. CQ is known to cause lysosomal membrane permeabilisation, cathepsin leakage and activation of BID and caspases.29, 30 We therefore investigated the role of cathepsins in caspase activation and cell death induced by CQ in combination with AKTi and mTORi. We find that CASP3 activity is only observed when AKTi or mTORi are combined with CQ, whereas treatment with AKTi, mTORi or CQ alone is not sufficient to induce its activation (Figures 3c and d). Moreover, CASP3 activation under these conditions is completely suppressed by co-treatment with a cathepsin B/L inhibitor (Ca-074Me) and partially suppressed by the pancathepsin inhibitors E64D and pepstatinA.31 This assay clearly positions cathepsins upstream of caspase activation in this mode of cell death. Cathepsin inhibition by Ca-074Me also considerably inhibited RT112 cell death with CQ and mTORi (from 74%, ±s.e. 4% to 31%, ±s.e. 6% P=0.004; Figure 3e), supporting the relevance of cathepsin-mediated caspase activation to cell death. Additionally, both Ca-074Me and the pancaspase inhibitor zVAD rescued the number of viable cells under mTORi+CQ treatment to roughly the same value as that measured for mTORi treatment alone: from 35% (±s.e. 13%) to 96% (±s.d. 13%) with Ca-074Me and to 84% (±s.d. 28%) with zVAD. That E64D and pepstatinA did not robustly protect against cell death or CASP3 activation under mTORi-induced potentiation of CQ toxicity is likely due to the hydrolysis of E64d—which inhibits cathepsins B, H and L—in the culture medium.31, 32, 33 To assay directly the role of CTSB in this model of cell death and clarify the involvement of BID, we knocked down these components by siRNA. Figure 3f shows that both BID and CTSB siRNA robustly inhibited cell death induced by CQ in combination with both AKTi and mTORi. The mechanism of synergistic cell death is therefore autophagy-independent, showing characteristics of apoptosis cross-talk activated by lysosomal membrane permeabilisation.29 Suppression of cholesterol biosynthesis by AKTi and mTORi underlies synergy with CQ Given that AKTi and mTORi only potentiate CQ-induced cell death in FGFR-dependent cell lines, we investigated how FGFR3 signalling might regulate lysosomal cell death (LCD). A possible link between these two pathways was found in reports showing that (i) FGFR3 maintains the expression of genes required for fatty acid and cholesterol biosynthesis via SREBP1; and (ii) lysosomal cholesterol can regulate membrane integrity and LCD.34, 35 FGFRi is known to induce cell death by suppressing SCD1 (stearoyl-CoA desaturase-13) expression, which we now found to also underlie mTORi cytotoxicity. Both FGFRi- and mTORi-induced cell death is rescued by oleic acid, the product of SCD1 activity (Supplementary Figure S4A), and correlates with complete suppression of SCD1 expression. However, as a lower dose of mTORi (0.25 μm) does not induce cell death, but potentiates CQ-induced cell death, we used this concentration for subsequent experiments.34 Immunoblotting shows that FGFRi and mTORi fully suppress the expression of cSREBP1 and cholesterol enzymes in RT112 cultures, whereas AKTi and PI3Kαi partially suppress this pathway (Figures 4a and b). Remarkably, suppression of cSREBP1 by FGFR/PTENi significantly correlates with the exacerbation CQ-induced cell death; Pearson's r (R2)=0.871 (P=0.0065; Figures 4b–c). Thus, CQ-induced cell death is not modulated by PI3Kβi (P=0.9657 to ctrl), but similarly exacerbated by PI3Kαi (P=0.0008 to ctrl) and AKTi (P=0.0002 to ctrl; P=0.9013 to PI3Kαi). However, inhibition of mTOR (P<0.0001 to ctrl) and FGFR (P=0.0003 to ctrl) further potentiate CQ-induced cell death, although the curve for FGFRi is clearly different to the other conditions, suggesting interference by additional factors. To further investigate cholesterol biosynthesis in CQ-induced LCD, we inhibited HMGCR—a rate-limiting enzyme in cholesterol biosynthesis—with Ato, or saturated cellular membranes with water-soluble cholesterol.36, 37 Figure 4d shows that Ato exacerbates CQ-induced cell death, whereas cholesterol is significantly protective. Furthermore, we could recapitulate the effects of AKTi on CQ toxicity by knocking down the expression of HMGCS1 or DHCR7 (Figures 4e and f). Importantly, at low doses of CQ, a clear synergy is observed with mTORi and AKTi, which is robustly (mTORi) or completely (AKTi) suppressed by cholesterol (Figures 4g and h). However, cholesterol did not protect against the monotherapy toxicity of either FGFR or mTORi, nor other apoptotic insults including staurosporine, TRAIL (tumour necrosis factor-related apoptosis-inducing ligand) and proteasome inhibition, showing that it is not generally protective against apoptosis (Supplementary Figures S4B and C). Furthermore, cholesterol did not inhibit lysosomal neutralization by CQ or BafA1, demonstrating that protection is conferred downstream of the function of these compounds (Supplementary Figures S4D and E). Suppression of cSREBP1 and cholesterol biosynthesis enzymes by FGFRi, mTORi and AKTi was also confirmed in the other type-III line, MGH-U3, wherein cholesterol again significantly protects against synergistic cell death induced by CQ and AKTi (Figures 4i and j). However, MGH-U3 cultures do not show suppression of cSREBP1 or potentiation of CQ-induced cell death with PI3Kα inhibition, likely due to the expression of a downstream AKT1(E17K)-activating mutation, which sustains AKT activation and PRAS40 phosphorylation under PI3Kαi. Thus, suppression of cSREBP1 and cholesterol biosynthesis pathway correlates with the potentiation of CQ-induced cell death, which is robustly inhibited by saturation of cellular membranes with cholesterol. Cholesterol depletion by AKTi sensitises lysosomes to CQ-induced membrane permeabilisation We used filipin to visualise cellular cholesterol and show that whereas AKTi and Ato alone cause little measureable change to cellular cholesterol, both compounds combine with CQ to deplete severely intracellular cholesterol (Figure 5a). Under these conditions, cholesterol treatment rescues cellular cholesterol, saturating intracellular vesicle-like structures throughout the cell. These observations were also quantified by fluorometric detection of free cellular cholesterol (Supplementary Figure S4F). To assay lysosomal membrane permeabilisation, we quantified the loss of cathepsin immunoreactivity from punctate cytosolic structures and the formation of galectin-3 foci, a marker for damaged endomembranes.38 Figure 5b shows that the combination of CQ with AKTi results in the substantial loss of punctate cathepsin staining and a significant increase in galectin-3 aggregates. Remarkably, these changes were almost completely prevented by cholesterol. Furthermore, lysosomal swelling induced by CQ alone or in combination with AKTi is also robustly blocked by cholesterol (Figure 5c). However, we could not detect the cytosolic translocation of lysosomal cathepsins by microscopy or fractionation (indicating a short half-life once released). Nevertheless, we found that the combination of CQ with AKTi causes lysosomal cathepsin depletion, correlating with cytochrome c release, before the onset of caspase activation (Supplementary Figure S4G). Taken together, our data show that cellular cholesterol depletion and lysosomotropic stress by AKTi+CQ causes lysosomal swelling, damage, cathepsin release and cell death, which are profoundly rescued by saturating cellular membranes with cholesterol. Cholesterol availability is a general determinant to CQ sensitivity Figure 6 shows that type-I and -II bladder cancer cell lines do not show the same regulation of SREBP1 by FGFRi, PI3Ki and AKTi as type-III cells (RT112 and MGH-U3), despite the presence (top) or absence (bottom) of FGFR3 mutations. However, all cell lines carrying FGFR3 mutations showed suppression of cSREBP1 expression by mTORi, which correlated with a significant exacerbation of CQ-induced cell death in four out of five cell lines. All cell lines showed robust protection against CQ toxicity with cholesterol, whereas Ato exacerbated cell death. We also found that cholesterol significantly protects against BafA1-induced cholesterol loss, cell death and lysosomal swelling across the bladder panel (Supplementary Figures S5A–D). However, Ato did not potentiate BafA1 toxicity, indicating that maximal cell death is elicited at normal cellular cholesterol concentrations; a feature that mitigates its use as a therapeutic (Supplementary Figure S5E).39 Moreover, cholesterol significantly protects against both CQ and BafA1 cytotoxicity in primary human fibroblasts, suggesting that a widespread mode of cell death induced by these compounds is lysosomal destabilisation, as opposed to the inhibition of autophagy (Supplementary Figure S5F).40, 41, 42, 43 Overall, this study indicates a general role for cholesterol homeostasis in maintaining lysosomal membrane integrity under stress, which supports a rationale for combinations of CQ with targeted therapeutics that block cholesterol metabolism in cancer cells. Discussion Despite the increasing number of reports suggesting a role for autophagy in the response of cancers to therapeutics, little detail has emerged to account for the molecular mechanisms that elicit either prosurvival or prodeath autophagy.9 Nevertheless, CQ is currently being used as an adjuvant to anticancer therapies in over 30 clinical trials.9 Herein, we have shown across a genetically diverse range of bladder cancer lines that synergy between mTOR pathway inhibition and CQ is restricted to FGFR3-mutant cancers, and that suppression of cholesterol metabolism, not autophagy, underlies lysosomal destabilisation and cell death. Role of autophagy in bladder cancer Our knockdown of numerous autophagy-targeting genes convincingly demonstrates that the activation of autophagy does not contribute to the innate resistance of bladder cancers to FGFR/PTENi. These experiments highlight the differential requirements for autophagy under genuine starvation, where autophagy inhibition exacerbates cell death, compared with inhibitors of mitogenic signalling, where suppression of autophagy does not enhance cell death. Our data do however support a role for autophagy in the optimal growth of bladder cancer cells, which may underlie the trend for autophagy siRNAs or ATG7 KO to mildly protect against FGFRi and mTORi.44, 45 Furthermore, by robustly blocking autophagosome degradation and recycling with CQ and BafA1, we also rule out a role for constitutive bulk autophagic flux as a cytoprotective pathway under AKTi and mTORi in bladder cancers. These experiments did, however, identify a synergy between CQ and AKT or mTOR inhibitors in FGFR-dependent cancers. Our subsequent work brings together recent findings describing the regulation of cholesterol biosynthesis by FGFR3 and the function of cholesterol in regulating LCD.34, 35, 43 Modulation of CQ-induced cell death by inhibition of cholesterol biosynthesis The induction of LCD by CQ has been well characterised in HeLa cells and recently shown to be potentiated by a dual PI3K/AKT inhibitor in neuroblastomas.29, 30, 46, 47 Our model shares significant similarities with these reports, as synergistic cell death is unrelated to autophagy and requires cathepsin and BID activity upstream of caspase activation. However, we further show that the degree to which FGFR/PTENi potentiate CQ cytotoxicity correlates with suppression of cSREBP1 and loss of cellular cholesterol. Importantly, both FGFRi and mTORi lower the EC50 of CQ to therapeutically relevant concentrations (~6 μm), indicating that CQ may considerably improve the efficacy of these compounds in vivo.42, 48, 49 The finding that PI3Kαi or AKTi partially suppresses cSREBP1 expression, whereas FGFRi and mTORi completely suppress this pathway, suggests that FGFR regulates mTORC1/2-cSREBP1 through both PI3K/AKT-dependent and -independent (for example, PLCγ or RAS/MAPK) signalling. This is consistent with reports that SREBP1 is regulated by multiple pathways and indicates that the complete suppression of cSREBP1 is required to maximally potentiate CQ-induced cell death.50, 51, 52 Moreover, we found that all FGFR3-mutant cell lines stabilise cSREBP1 via mTORC1/2, yet do not show the same regulation of cSREBP1, or potentiation of CQ-induced cell death, with FGFRi or AKTi (Figure 6). Since S6 phosphorylation is also maintained under these conditions, we interpret this data to indicate that other mTORC1/2 signalling pathways are activated in these cells, which are sufficient to promote SREBP1 activation in the FGFR3 mutant background. Interestingly, the presence of FGFR3 mutations correlates with the potentiation of CQ-induced cell death in only six of the seven cell lines. RT4 cells do not fit this trend, possibly due to a coincident RhoA(A161V) mutation that may alter cholesterol or membrane dynamics.53 In contrast, FGFR3-WT cell lines regulate cSREBP1 expression independently of mTORC1/2 and therefore do not show potentiation of CQ-induced cell death with mTORi. Rather, many of these lines show significant protection against CQ toxicity with mTORi, suggesting that whether mTORi potentiates or inhibits CQ-induced cell death may be determined by the balance of its effects on cholesterol availability versus inhibition of proliferation. As activating FGFR3 mutations are found in up to 80% of low-grade noninvasive bladder tumours, the combination of CQ with mTOR pathway inhibitors may therefore benefit a substantial population of patients.26 Other transforming RTK mutations may similarly control cholesterol biosynthesis and present opportunities for eliciting synergistic cell death between relevant inhibitors and CQ. We provide proof of principle for this approach by showing that inhibition of cholesterol metabolism with a statin, or knockdown of key cholesterol biosynthesis enzymes, recapitulates synergistic cell death in numerous cell lines. However, in RT112 cells, knockdown of HMGCS1 and DHCR7, or Ato treatment, exacerbated cell death to a similar extent as AKTi, rather than to the level observed with mTORi. Additionally, the suppression of cSREBP1 by mTORi in FGFR3-mutant lines only partially inhibited the expression of cholesterol enzymes, yet resulted in a similar potentiation of CQ toxicity to Ato. Conversely, some FGFR3-WT cells showed mTORi-induced suppression of cholesterol enzyme expression in the absence of changes to cSREBP1 expression and CQ-induced cell death. Thus, additional mechanisms may regulate the expression of these enzymes and the availability of cellular cholesterol, which will require further elucidation. Role of cholesterol in regulating lysosomal membrane integrity Our data conclusively demonstrate a key role for cholesterol biosynthesis in regulating lysosomal integrity and cell death under lysosomotropic stress. These results can be explained by known features of cholesterol homeostasis and lysosomal membrane biology: (i) neutralisation of the endo/lysosomal system blocks the processing of extracellularly derived cholesterol esters, rendering cells dependent on the biosynthesis pathway; and (ii) lysosomal membrane cholesterol decreases permeability to water and ions, suppressing swelling and destabilization under osmotic stress.54, 55, 56 Thus, under inhibition of both cholesterol uptake (for example, CQ) and cholesterol biosynthesis (for example, AKTi), osmotic stress is enhanced, resulting in accelerated membrane permeabilisation, cathepsin release and cell death (Figure 7; blue text).57 In contrast, saturation of cellular membranes with cholesterol blocks CQ- and BafA1-induced LCD upstream of swelling and membrane permeabilisation. Given the efficacy by which water-soluble cholesterol prevents both BafA1- and CQ-induced LCD, we propose that this method can be used as a novel assay to clarify the contribution of LCD versus autophagy inhibition in cell death studies combining CQ with other therapeutics in vitro.38 Concluding remarks Our results delineate for the first time the mechanistic basis for synergy between CQ and a targeted anticancer therapeutic and stress caution in the interpretation of studies reporting enhanced drug efficacy in combination with CQ. These data also highlight the exciting therapeutic potential for CQ in combination with mTOR pathway inhibitors in patients with activating FGFR3 mutations. Finally, by revealing a role for cholesterol biosynthesis in maintaining lysosomal integrity under stress, we propose that therapeutics which suppress cholesterol metabolism in other cancer types may present similar opportunities for eliciting synergistic cell death with CQ, thereby defining a novel approach to future cancer treatments. Materials and methods Cell culture Reagents were obtained from Sigma (St Louis, MO, USA), except where indicated. Cell lines were sourced from: RT112/84 (ECACC, Salisbury, UK); TCC-SUP, J82, SW780, T24, 1A6, UM-UC-3, HT-1197, HT-1376, 5637, RT4, SCaBER (ATCC, Manassas, VA, USA); VM-CUB-1, 647-V, BFTC-905, KU-19-19, SW1710 (DSMZ, Braunschweig, Germany); MGH-U3 and 97-7 (LIMM, Leeds, UK); and human fibroblasts (Promocell, Heidelberg, Germany). All cell lines tested mycoplasma negative by Chan test. Cells were cultured in DMEM (Dulbecco's modified Eagle's medium) containing 10% fetal calf serum and 1% l-glutamine at 37 °C (5% CO2) and passaged weekly. For nutrient starvation, cells were washed three times in prewarmed EBSS (Gibco, Grand Island, NY, USA). AZD4547, AZD8186, AZD8835, AZD5363, AZD2014 and Ato were made by AstraZeneca (Macclesfield, UK) and resuspended in dimethyl sulfoxide to 10 mm. All other reagents were reconstituted in dimethyl sulfoxide except: CQ (200 mm phosphate-buffered saline (PBS)); 3MA (20 mm DMEM); cycloheximide (10 mg/ml water), cholesterol (10 mg/ml PBS); and N-acetyl-l-cysteine (100 mm DMEM). CA-074Me was obtained from Calbiochem (San Diego, CA, USA). Free cholesterol was quantified using ab65359 Kit (Abcam, Cambridge, UK). SmartPOOL ON-TARGET siRNAs (Dharmacon, Lafayette, CO, USA) were resuspended in water at 10 μm and reverse transfected by adding nine volumes of cell suspension to one volume of siRNA (10 nm final concentration) premixed with Lipofectamine RNAiMAX (Invitrogen, Carlsbad, CA, USA) in OPTI-MEM (Gibco). Microscopy and cell death assays Cells were seeded at a density of 5 000/ml in 96-well plates and stained with SYTOX Green Nucleic Acid Stain (Molecular Probes, Eugene, OR, USA) and Hoechst 33342 (1 μg/ml) following treatment. Total and dead cells were quantified using a Cellomics ArrayScan XTI (ArrayScan; 12 fields; >1000 cells) with appropriate filter settings. cdEC50s were calculated using Origin 7.5 SR6 (OriginLab Corporation, Northampton, MA, USA). For CASP3 activation assays, NucView-488 Caspase-3 substrate (Biotum, Hayward, CA, USA) was incubated with cells at 1 μm in an IncuCyte ZOOM (Essen Bioscience, Ann Arbor, MI, USA) for 5 days. The frequency of NucView-488 signals was quantified using ZOOM GUI version 2014A, and normalised for cell confluency using processing definitions adapted for each cell line. Immunocytochemistry Cells were seeded in 96-well plates at a density of 0.5–5x104/ml and formalin-fixed for 20 min following treatment. Cultures were washed three times in PBS and blocked (3% bovine serum albumin, 0.1% Triton) for 1 h before overnight incubation (4 °C) with primary antibodies and 1 h incubations with secondary antibodies. For LC3 and LAMP-I immunostaining, cultures were postfixed in 100% ice-cold methanol for 15 min. Antibodies were purchased from Cell Signalling Technologies (Danvers, MA, USA) except: anti-galectin-3 (BD Biosciences, San Jose, CA, USA), anti-cathepsin L (Abcam). Secondary antibodies from Molecular Probes were used at a 1:500 and visualised by ArrayScan. LAMP-I puncta were quantified using ImageJ (NIH, Bethesda, MD, USA) by measuring the area of the three largest and clearly defined immunopositive structures per cell (three fields; three independent experiments). Galectin-3-positive cells were defined by the presence of three or more cytosolic aggregates. For filipin staining, fixed cultures were quenched in glycine (1.5 mg/ml PBS; 10 min), rinsed and incubated with 25 μg/ml filipin-PBS (60 min) washed and visualised by ArrayScan. Immunoblotting Cells were seeded at 0.5–2x105/ml and lysed in sodium dodecyl sulphate-based buffer following treatment. Lysates were normalised for protein concentration (BCA assay; Pierce, Rockford, IL, USA), boiled in sample buffer (NuPage+DTT; Life Technologies, Grand Island, NY, USA) and loaded at 10 μg per lane on Criterion gels (4–20%). Gels were transferred to nitrocellulose, blocked (5% milk-TBS-T) and incubated overnight (4 °C) with primary antibodies. All antibodies were from Cell Signaling Technology except: cathepsin B (Calbiochem), HMGCS1 (Sigma), FRS-2 (R&D Systems) and HMGCR, IDI-I and DHCR7 (Abcam). Horseradish peroxidase-conjugated secondary antibodies were incubated for 1 h and visualised by ECL (Perkin-Elmer, Waltham, MA, USA) using film (GE Healthcare, Uppsala, Sweden) or CCD (Chemigenius; Syngene, Frederick, MD, USA). Films were scanned at 600 dpi and analysed for densitometry using ImageJ (NIH). Cellular fractionation was performed using Kit No. 9038 from Cell Signalling. CRISPR A sequence targeting ATG7 exon 1 (5′-AAGCTGAACGAGTATCGGC-3′) was synthesised (Sigma) within a guide RNA plasmid also encoding Cas9-GFP. The Cas9/gRNA was purified by Endo-free maxi prep (Qiagen, Germantown, MD, USA), transfected using FuGENE HD (Promega, Fitchburg, WI, USA). Cells were sorted for GFP fluorescence after 48 h (BD FACSAria Ilu, BD Biosciences) and seeded at 1 cell per well in 96-well plates. Cultures were monitored for single clones until confluency, passaged and assayed for ATG7 and LC3-II expression by western blotting. Statistics Data were analysed for statistical significance using one-way analysis of variance followed by Dunnett's post hoc test to compare treatment means to control means (JMP12.0.1; SAS, Cary, NC, USA). Where indicated, Student's t-test was used to compare means from at least three independent experiments. We thank AM Tolkovsky, S Cosulich and ST Barry for their input during preparation of the manuscript. AZD5363 was discovered by AstraZeneca subsequent to a collaboration with Astex Therapeutics (and its collaboration with the Institute of Cancer Research and Cancer Research Technology Limited). Supplementary Information accompanies this paper on the Oncogene website (http://www.nature.com/onc) MAK and VF are full-time employees of AstraZeneca. IGG declares no conflict of interest. Supplementary Material Supplementary Figure S1 Click here for additional data file. Supplementary Figure S2 Click here for additional data file. Supplementary Figure S3 Click here for additional data file. Supplementary Figure S4 Click here for additional data file. Supplementary Figure S5 Click here for additional data file. Figure 1 Activation of autophagy does not contribute to survival under FGFR/PTENi. (a) RT112 cells were treated with the indicated inhibitors at 1 μm for 5 days and assayed for cell death. Histogram shows the number of dead cells (SYTOX Green-positive) as a proportion of total cell number (Hoechst-positive; n⩾7; mean±s.e.). (b) RT112 were incubated with kinase inhibitors for 22 h before the addition of BafA1 (20 nm), where indicated, for the last 2 h. A representative immunoblot confirms target engagement for FGFRi (FRS-2 bandshift), AKTi (hyperphosphorylated in catalytically inactive state), mTORi (S6 dephosphorylation) and BafA1 (LC3B; n=3). (c) Schematic to illustrate mTOR regulation of autophagy. (d–h) RT112 cultures were reverse transfected with the indicated autophagy-targeting siRNAs (10 nm) for 48 h before analysis. (d) Efficiency of protein knockdown and inhibition of autophagic LC3 flux (−/+BafA1) was assayed by immunoblotting at 72 h (n=3). (e and f) Histograms show the quantification of cell death in cultures starved of amino acids and serum (EBSS) for 24 h (e; n=5; mean±s.e.) or treated with the indicated kinase inhibitors for 5 days (n=4; mean±s.e.). (g) Immunoblot confirms knockdown of the indicated autophagy-essential proteins and inhibition of LC3 lipidation. (h) Histogram shows quantification of cell death after treatment with FGFRi or mTORi for 5 days (n=3; mean±s.e.). (i) An ATG7 KO cell line was engineered by CRISPR/Cas9 and immunoblotted to confirm loss of ATG7 expression and LC3 lipidation. (j) ATG7 KO RT112 cultures were assayed for cell death as in (a) (n=4; mean±s.e.). *P<0.05, **P<0.01, ***P<0.001. Figure 2 Potentiation of CQ-induced cell death by AKTi or mTORi is restricted to FGFR3-dependent cell lines. Bladder cancer cell lines were preincubated with AKTi (1 μm), mTORi (1 μm) or Rapa (100 nm) for 30 min before the addition of BafA1 (Baf; 20 nm), CQ (20 μm) or 3MA (10 mm). (a) Histograms show quantification of cell death at day 4 in two representative cell lines of the three major response types described in the text (n=4; mean±s.e.). (b) UM-UC-3 and RT112 cells were treated as in (a), lysed and immunoblotted for the indicated autophagic, lysosomal and apoptotic proteins. (c and d) Immunocytochemistry for LC3 (c) and LAMP-I (d) in RT112 cells treated as in (a) reveals autophagosome accumulation (c) and lysosomal swelling (d), quantified using ImageJ in (e; mean±s.e.; n=3). *P<0.05, **P<0.01, ***P<0.001. Figure 3 Synergy between CQ and AKTi or mTORi is autophagy-independent and driven by cathepsins. RT112 ATG7 KO cells were incubated with AKT/mTORi (1 μm) before the addition of CQ (20 μm). (a) Histogram shows quantification of cell death at day 4, revealing synergy in autophagy-disabled cells (n=4; mean±s.e.). (b) RT112 WT and ATG7 KO cells were incubated with CQ (1–80 μm) for 4 days and quantified for cell death. Line graph shows OriginLab curve fitting from nine independent experiments, from which cdEC50 and statistics (see text) were calculated. (c and d) RT112 cells were treated with the AKTi (c) or mTORi (d) and CQ (20 μm) in combination with Ca-074Me (10 μm), E64D and pepstatinA (E/P; 30 μm/30 μm) and zVAD (20 μm) for 3 days. Cultures were incubated with the caspase-3 fluorogenic substrate NucView-488 and imaged every 6 h for fluorescence (λ475(40)/535(45)) and cellular confluency. Data are plotted as the number of fluorescent nuclei divided by cellular confluence (data from one experiment is shown, representative of three independent experiments; mean±range). (e) RT112 cells were treated as in (c and d) for 4 days and assayed for cell death (n=3; mean±s.d.). (f) RT112 cells were reverse transfected with Ctrl, BID or CTSB siRNA for 48 h before treatment with CQ (40 μm). Histogram shows cell death quantification at 24 h (n=3; mean±s.e.). *P<0.05, **P<0.01, ***P<0.001. Figure 4 Inhibition of cholesterol metabolism underlies synergy between CQ and AKTi or mTORi. (a) RT112 were treated with FGFR/PTENi for 3 days and immunoblotted for the expression of enzymes regulating cholesterol and fatty acid biosynthesis pathways and quantified in (b) (n=3; mean±s.e.). (c) RT112 cells were treated with inhibitors to FGFR (0.25 μm), AKT (1 μm) and mTOR (0.25 μm) for 5 days in combination with CQ (1–40 μm). Line graph shows OriginLab curve fitting based on data points generated in >3 independent experiments. Inset text shows EC50 values and statistical analysis for each treatment. (d) RT112 cells were preincubated with Ato (5 μm) or water-soluble cholesterol (Chol, 10 μg/ml) for 6 h before the addition of CQ (1–80 μm). Line graphs were curve-fitted using cell death data from three independent experiments at each data point. (e) RT112 cultures were reverse transfected with siRNA targeting HMGCS1 or DHCR7 for 72 h or Ctrl siRNA and incubated with or without Ato for 24 h. Immunoblotting shows expected protein knockdown by siRNA (n=2). (f) Cells were transfected as in (e) and treated with CQ (1–80 μm) from days 2 to 7. Line graph shows curve-fitted data from three independent experiments. (g and h) RT112 cultures were preincubated with Chol (10 μg/ml) for 6 h before the addition of mTORi (0.25 μm; g) or AKTi (1 μm; h) and CQ (1–40 μm) for 5 days. Histograms show the quantification of cell death from four independent experiments. Statistical analysis on blue (mTORi+CQ) or red (AKTi+CQ) bars reflects comparison of means to CQ control (black). Statistics on gold bars (+Chol) reflects significance to red and blue bars at each concentration of CQ (i.e. protection by Chol against combination treatment) (i). MGH-U3 cells were treated and immunoblotted as in (a). (j) MGH-U3 cells were treated as indicated and cell death quantified and curve-fitted to generate EC50 values (data from one experiment is shown; n=3; statistical analysis by Student's t-test on data at 10 μm CQ). *P<0.05, **P<0.01, ***P<0.001. Figure 5 Water-soluble cholesterol saturates intracellular membranes under CQ treatment and rescues loss of cathepsin release, lysosomal damage and swelling. (a) RT112 cells were treated with AKTi (1 μM), Ato (5 μM), Chol (10 μg/mL) and CQ (20 μM) as indicated for 3 days, fixed and stained with filipin to visualise cholesterol (green; Hoechst staining in blue; n=3). High-magnification imaging reveals that Chol saturates numerous punctate vesicle-like structures throughout the cytosol, consistent with endo/lysosomal localisation (right). (b and c) RT112 cells were treated as in (a) and stained for cathepsin L (CTSL; green, b), LAMP-I (green, c) and galectin-3 (Gal-3; red; b and c). Representative immunomicrographs are shown alongside the quantification of punctate CTSL/Gal-3 staining (b; n=3) and lysosomal area (c; n=3; *P<0.05, ***P<0.001 to control, +++P<0.001 to CQ+AKTi). Scale bars represent 10 μM. Figure 6 Potentiation of CQ-induced cell death is linked to the suppression of cSREBP1 expression and recapitulated with atorvastatin (Ato), or inhibited by water-soluble cholesterol (Chol), across the bladder cell line panel. Bladder cancer cell lines carrying FGFR3 mutations (top row), or WT for FGFR3 (bottom row), were treated as indicated (1 μm) for 5 days before lysis and immunoblotting for the indicated proteins (n=2). Line graphs show curve-fitted cell death quantifications in response to CQ alone (black lines; 0–80 μm) or in combination with FGFRi (grey), AKTi (red), mTORi (blue), Ato (green) or Chol (gold; data from one representative experiment is shown; n=3). EC50 values are shown inset with corresponding indication of statistical significance (n⩾3; *P<0.05 indicates where the difference between treatment and control means reaches significance at any concentration of CQ). Figure 7 FGFR signalling and model for the role of cholesterol biosynthesis in the maintenance of lysosomal membrane integrity under CQ- and BafA1-induced stress. (a) FGFR-dependent (blue text) and FGFR3-mutant (light blue text only) bladder cancer cell lines maintain cSREBP1 expression in an mTORC1/2-dependent manner (left). In contrast, FGFR3-WT cells (green text) maintain cSREBP1 independently of mTORC1/2 signalling. (b) CQ is a weak base that diffuses into lysosomes (grey circles), neutralises the pH and becomes trapped by protonation, inducing osmotic stress, lysosomal swelling, cathepsin release and lysosomal cell death (LCD). Inhibition of FGFR, AKT or mTOR signalling in FGFR-dependent cell lines or HMGCR (Ato) in all cell lines, depletes cellular cholesterol and accelerates LCD (Fast LCD). In contrast, saturation of cellular membranes with water-soluble cholesterol (+Chol) prevents CQ-induced lysosomal swelling, cathepsin loss and cell death (Slow LCD). Lysosomal membrane cholesterol is known to regulate permeability to water and ions; however, this is the first study to demonstrate that inhibition of cholesterol biosynthesis underlies the potentiation of CQ-induced LCD in cancer cells. Furthermore, we propose that water-soluble cholesterol can be used to determine the relative contribution of LCD versus autophagy inhibition in future studies examining the potentiation of therapeutic-induced cell death with lysosomal inhibitors. ==== Refs Cancer Genome Atlas Research Network.. Comprehensive molecular characterization of urothelial bladder carcinoma . Nature 2014 ; 507 : 315 –322.24476821 Wu XR. Biology of urothelial tumorigenesis: insights from genetically engineered mice . Cancer Metast Rev 2009 ; 28 : 281 –290. Puzio-Kuter AM, Castillo-Martin M, Kinkade CW, Wang X, Shen TH, Matos T et al. Inactivation of p53 and Pten promotes invasive bladder cancer . Genes Dev 2009 ; 23 : 675 –680.19261747 Sun CH, Chang YH, Pan CC. Activation of the PI3K/Akt/mTOR pathway correlates with tumour progression and reduced survival in patients with urothelial carcinoma of the urinary bladder . Histopathology 2011 ; 58 : 1054 –1063.21707707 Degtyarev M, De Maziere A, Orr C, Lin J, Lee BB, Tien JY et al. Akt inhibition promotes autophagy and sensitizes PTEN-null tumors to lysosomotropic agents . J Cell Biol 2008 ; 183 : 101 –116.18838554 Fan QW, Cheng C, Hackett C, Feldman M, Houseman BT, Nicolaides T et al. Akt and autophagy cooperate to promote survival of drug-resistant glioma . Sci Signal 2010 ; 3 : ra81 .21062993 Xu CX, Zhao L, Yue P, Fang G, Tao H, Owonikoko TK et al. Augmentation of NVP-BEZ235's anticancer activity against human lung cancer cells by blockage of autophagy . Cancer Biol Ther 2011 ; 12 : 549 –555.21738008 Mirzoeva OK, Hann B, Hom YK, Debnath J, Aftab D, Shokat K et al. Autophagy suppression promotes apoptotic cell death in response to inhibition of the PI3K-mTOR pathway in pancreatic adenocarcinoma . J Mol Med 2011 ; 89 : 877 –889.21678117 Sui X, Chen R, Wang Z, Huang Z, Kong N, Zhang M et al. Autophagy and chemotherapy resistance: a promising therapeutic target for cancer treatment . Cell Death Dis 2013 ; 4 : e838 .24113172 Dickstein RJ, Nitti G, Dinney CP, Davies BR, Kamat AM, McConkey DJ. Autophagy limits the cytotoxic effects of the AKT inhibitor AZ7328 in human bladder cancer cells . Cancer Biol Ther 2012 ; 13 : 1325 –1338.22895070 Lamoureux F, Thomas C, Crafter C, Kumano M, Zhang F, Davies BR et al. Blocked autophagy using lysosomotropic agents sensitizes resistant prostate tumor cells to the novel Akt inhibitor AZD5363 . Clin Cancer Res 2013 ; 19 : 833 –844.23258740 Zou Y, Ling YH, Sironi J, Schwartz EL, Perez-Soler R, Piperdi B. The autophagy inhibitor chloroquine overcomes the innate resistance of wild-type EGFR non-small-cell lung cancer cells to erlotinib . J Thorac Oncol 2013 ; 8 : 693 –702.23575415 Cufi S, Vazquez-Martin A, Oliveras-Ferraros C, Corominas-Faja B, Cuyas E, Lopez-Bonet E et al. The anti-malarial chloroquine overcomes primary resistance and restores sensitivity to trastuzumab in HER2-positive breast cancer . Scientific Rep 2013 ; 3 : 2469 . Feng Y, He D, Yao Z, Klionsky DJ. The machinery of macroautophagy . Cell Res 2014 ; 24 : 24 –41.24366339 Jung CH, Jun CB, Ro SH, Kim YM, Otto NM, Cao J et al. ULK-Atg13-FIP200 complexes mediate mTOR signaling to the autophagy machinery . Mol Biol Cell 2009 ; 20 : 1992 –2003.19225151 Russell RC, Tian Y, Yuan H, Park HW, Chang YY, Kim J et al. ULK1 induces autophagy by phosphorylating Beclin-1 and activating VPS34 lipid kinase . Nat Cell Biol 2013 ; 15 : 741 –750.23685627 Ganley IG, Lam du H, Wang J, Ding X, Chen S, Jiang X. ULK1.ATG13.FIP200 complex mediates mTOR signaling and is essential for autophagy . J Biol Chem 2009 ; 284 : 12297 –12305.19258318 Hosokawa N, Hara T, Kaizuka T, Kishi C, Takamura A, Miura Y et al. Nutrient-dependent mTORC1 association with the ULK1-Atg13-FIP200 complex required for autophagy . Mol Biol Cell 2009 ; 20 : 1981 –1991.19211835 Mizushima N, Noda T, Yoshimori T, Tanaka Y, Ishii T, George MD et al. A protein conjugation system essential for autophagy . Nature 1998 ; 395 : 395 –398.9759731 Ichimura Y, Kirisako T, Takao T, Satomi Y, Shimonishi Y, Ishihara N et al. A ubiquitin-like system mediates protein lipidation . Nature 2000 ; 408 : 488 –492.11100732 Romanov J, Walczak M, Ibiricu I, Schuchner S, Ogris E, Kraft C et al. Mechanism and functions of membrane binding by the Atg5-Atg12/Atg16 complex during autophagosome formation . EMBO J 2012 ; 31 : 4304 –4317.23064152 Gavine PR, Mooney L, Kilgour E, Thomas AP, Al-Kadhimi K, Beck S et al. AZD4547: an orally bioavailable, potent, and selective inhibitor of the fibroblast growth factor receptor tyrosine kinase family . Cancer Res 2012 ; 72 : 2045 –2056.22369928 Barlaam B, Cosulich S, Degorce S, Fitzek M, Green S, Hancox U et al. Discovery of (R-8-(1-(3,5-difluorophenylamino)ethyl)-N,N-dimethyl-2-morpholino-4-oxo-4H-chrom ene-6-carboxamide (AZD8186): a potent and selective inhibitor of PI3Kbeta and PI3Kdelta for the treatment of PTEN-deficient cancers . J Med Chem 2015 ; 58 : 943 –962.25514658 Davies BR, Greenwood H, Dudley P, Crafter C, Yu DH, Zhang J et al. Preclinical pharmacology of AZD5363, an inhibitor of AKT: pharmacodynamics, antitumor activity, and correlation of monotherapy activity with genetic background . Mol Cancer Ther 2012 ; 11 : 873 –887.22294718 Pike KG, Malagu K, Hummersone MG, Menear KA, Duggan HM, Gomez S et al. Optimization of potent and selective dual mTORC1 and mTORC2 inhibitors: the discovery of AZD8055 and AZD2014 . Bioorg Med Chem Lett 2013 ; 23 : 1212 –1216.23375793 Williams SV, Hurst CD, Knowles MA. Oncogenic FGFR3 gene fusions in bladder cancer . Hum Mol Genet 2013 ; 22 : 795 –803.23175443 Klionsky DJ, Abdalla FC, Abeliovich H, Abraham RT, Acevedo-Arozena A, Adeli K et al. Guidelines for the use and interpretation of assays for monitoring autophagy . Autophagy 2012 ; 8 : 445 –544.22966490 Dowdle WE, Nyfeler B, Nagel J, Elling RA, Liu S, Triantafellow E et al. Selective VPS34 inhibitor blocks autophagy and uncovers a role for NCOA4 in ferritin degradation and iron homeostasis in vivo . Nat Cell Biol 2014 ; 16 : 1069 –1079.25327288 Boya P, Gonzalez-Polo RA, Poncet D, Andreau K, Vieira HL, Roumier T et al. Mitochondrial membrane permeabilization is a critical step of lysosome-initiated apoptosis induced by hydroxychloroquine . Oncogene 2003 ; 22 : 3927 –3936.12813466 Seitz C, Hugle M, Cristofanon S, Tchoghandjian A, Fulda S. The dual PI3K/mTOR inhibitor NVP-BEZ235 and chloroquine synergize to trigger apoptosis via mitochondrial–lysosomal cross-talk . Int J Cancer 2013 ; 132 : 2682 –2693.23151917 Montaser M, Lalmanach G, Mach L. CA-074, but not its methyl ester CA-074Me, is a selective inhibitor of cathepsin B within living cells . Biol Chem 2002 ; 383 : 1305 –1308.12437121 Shoji-Kasai Y, Senshu M, Iwashita S, Imahori K. Thiol protease-specific inhibitor E-64 arrests human epidermoid carcinoma A431 cells at mitotic metaphase . Proc Natl Acad Sci USA 1988 ; 85 : 146 –150.3422411 McGowan EB, Becker E, Detwiler TC. Inhibition of calpain in intact platelets by the thiol protease inhibitor E-64d . Biochem Biophys Res Commun 1989 ; 158 : 432 –435.2537073 Du X, Wang QR, Chan E, Merchant M, Liu J, French D et al. FGFR3 stimulates stearoyl CoA desaturase 1 activity to promote bladder tumor growth . Cancer Res 2012 ; 72 : 5843 –5855.23019225 Wang BT, Ducker GS, Barczak AJ, Barbeau R, Erle DJ, Shokat KM. The mammalian target of rapamycin regulates cholesterol biosynthetic gene expression and exhibits a rapamycin-resistant transcriptional profile . Proc Natl Acad Sci USA 2011 ; 108 : 15201 –15206.21876130 Roth BD. The discovery and development of atorvastatin, a potent novel hypolipidemic agent . Progr Med Chem 2002 ; 40 : 1 –22. Christian AE, Haynes MP, Phillips MC, Rothblat GH. Use of cyclodextrins for manipulating cellular cholesterol content . J Lipid Res 1997 ; 38 : 2264 –2272.9392424 Aits S, Jaattela M, Nylandsted J. Methods for the quantification of lysosomal membrane permeabilization: a hallmark of lysosomal cell death . Methods Cell Biol 2015 ; 126 : 261 –285.25665450 Lee CM, Tannock IF. Inhibition of endosomal sequestration of basic anticancer drugs: influence on cytotoxicity and tissue penetration . Br J Cancer 2006 ; 94 : 863 –869.16495919 Graham RM, Thompson JW, Webster KA. Inhibition of the vacuolar ATPase induces Bnip3-dependent death of cancer cells and a reduction in tumor burden and metastasis . Oncotarget 2014 ; 5 : 1162 –1173.24811485 Appelqvist H, Sandin L, Bjornstrom K, Saftig P, Garner B, Ollinger K et al. Sensitivity to lysosome-dependent cell death is directly regulated by lysosomal cholesterol content . PLoS One 2012 ; 7 : e50262 .23166840 Ch'ng JH, Lee YQ, Gun SY, Chia WN, Chang ZW, Wong LK et al. Validation of a chloroquine-induced cell death mechanism for clinical use against malaria . Cell Death Dis 2014 ; 5 : e1305 .24967967 von Schwarzenberg K, Wiedmann RM, Oak P, Schulz S, Zischka H, Wanner G et al. Mode of cell death induction by pharmacological vacuolar H+-ATPase (V-ATPase) inhibition . J Biol Chem 2013 ; 288 : 1385 –1396.23168408 Yang S, Wang X, Contino G, Liesa M, Sahin E, Ying H et al. Pancreatic cancers require autophagy for tumor growth . Genes Dev 2011 ; 25 : 717 –729.21406549 Guo JY, Chen HY, Mathew R, Fan J, Strohecker AM, Karsli-Uzunbas G et al. Activated Ras requires autophagy to maintain oxidative metabolism and tumorigenesis . Genes Dev 2011 ; 25 : 460 –470.21317241 Laforge M, Petit F, Estaquier J, Senik A. Commitment to apoptosis in CD4(+) T lymphocytes productively infected with human immunodeficiency virus type 1 is initiated by lysosomal membrane permeabilization, itself induced by the isolated expression of the viral protein Nef . J Virol 2007 ; 81 : 11426 –11440.17670831 Stoka V, Turk B, Schendel SL, Kim TH, Cirman T, Snipas SJ et al. Lysosomal protease pathways to apoptosis. Cleavage of bid, not pro-caspases, is the most likely route . J Biol Chem 2001 ; 276 : 3149 –3157.11073962 Rosenfeldt MT, O'Prey J, Morton JP, Nixon C, MacKay G, Mrowinska A et al. P53 status determines the role of autophagy in pancreatic tumour development . Nature 2013 ; 504 : 296 –300.24305049 Amaravadi RK, Yu D, Lum JJ, Bui T, Christophorou MA, Evan GI et al. Autophagy inhibition enhances therapy-induced apoptosis in a Myc-induced model of lymphoma . J Clin Invest 2007 ; 117 : 326 –336.17235397 Yecies JL, Manning BD. Transcriptional control of cellular metabolism by mTOR signaling . Cancer Res 2011 ; 71 : 2815 –2820.21487041 Li S, Oh YT, Yue P, Khuri FR, Sun SY. Inhibition of mTOR complex 2 induces GSK3/FBXW7-dependent degradation of sterol regulatory element-binding protein 1 (SREBP1) and suppresses lipogenesis in cancer cells . Oncogene 2016 ; 35 : 642 –650.25893295 Ye J, DeBose-Boyd RA. Regulation of cholesterol and fatty acid synthesis . Cold Spring Harbor Perspect Biol 2011 ; 3 : pii: a004754. Medina MW, Theusch E, Naidoo D, Bauzon F, Stevens K, Mangravite LM et al. RHOA is a modulator of the cholesterol-lowering effects of statin . PLoS Genet 2012 ; 8 : e1003058 .23166513 Ikonen E. Cellular cholesterol trafficking and compartmentalization . Nat Rev Mol Cell Biol 2008 ; 9 : 125 –138.18216769 Johansson AC, Appelqvist H, Nilsson C, Kagedal K, Roberg K, Ollinger K. Regulation of apoptosis-associated lysosomal membrane permeabilization . Apoptosis 2010 ; 15 : 527 –540.20077016 Hao SJ, Hou JF, Jiang N, Zhang GJ. Loss of membrane cholesterol affects lysosomal osmotic stability . Gen Physiol Biophys 2008 ; 27 : 278 –283.19202201 Poole B, Ohkuma S. Effect of weak bases on the intralysosomal pH in mouse peritoneal macrophages . J Cell Biol 1981 ; 90 : 665 –669.6169733

PMC005xxxxxx/PMC5000519.txt

==== Front BMC Med GenomicsBMC Med GenomicsBMC Medical Genomics1755-8794BioMed Central London 21710.1186/s12920-016-0217-2Research ArticleWithin-pair differences of DNA methylation levels between monozygotic twins are different between male and female pairs Watanabe Mikio nabe@sahs.med.osaka-u.ac.jp 12Honda Chika honda-ch@sahs.med.osaka-u.ac.jp 2The Osaka Twin Research Group Iwatani Yoshinori Yorifuji Shiro Iso Hiroyasu Kamide Kei Hatazawa Jun Kihara Shinji Sakai Norio Watanabe Hiroko Makimoto Kiyoko Watanabe Mikio Honda Chika Iwatani Yoshinori iwatani@sahs.med.osaka-u.ac.jp 121 Department of Biomedical Informatics, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka 565-0871 Japan 2 Center for Twin Research, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, 565-0871 Osaka Japan 26 8 2016 26 8 2016 2016 9 1 5528 3 2016 14 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background DNA methylation levels will be important for detection of epigenetic effects. However, there are few reports showing sex-related differences in the sensitivity to DNA methylation. To evaluate their sex-related individual differences in the sensitivity to methylation rigorously, we performed a systematic analysis of DNA methylation in monozygotic twins, an optimal model to evaluate them because the genetic backgrounds are the same. Results We examined 30 male and 43 female older monozygotic twin pairs recruited from the registry established by the Center for Twin Research, Osaka University. Their methylation levels were determined using the Infinium HumanMethylation450 BeadChip Kit (Illumina), which interrogated 485577 highly informative CpG sites at the single-nucleotide resolution, and the median methylation level was calculated for each of the 25657 CpG islands. Within-pair differences of methylation levels (WPDMs) were greater in male pairs than female pairs for 86.0 % of autosomal CpG islands, but were higher in female pairs than male pairs for 76.7 % of X chromosomal CpG islands. Mean WPDMs of CpG islands in each autosomal chromosome were significantly higher in male pairs than in female whereas that in X chromosome was significantly higher in female pairs than in male. Multiple comparison indicated that WPDMs in three autosomal and two X-chromosomal CpG islands were significantly greater in male pairs, whereas those in 22 X-chromosomal CpG islands were significantly greater in female pairs. Conclusion Sex-related differences were present in the WPDMs of CpG islands in individuals with the same genetic background. These differences may be associated with the sexual influences in susceptibility of some diseases. Electronic supplementary material The online version of this article (doi:10.1186/s12920-016-0217-2) contains supplementary material, which is available to authorized users. Keywords MethylationMonozygotic twinIndividual differenceEpigenetic changehttp://dx.doi.org/10.13039/501100001691Japan Society for the Promotion of Science24590695Watanabe Mikio Charitable Trust Laboratory Medicine Research Foundation of JapanUniversity Grants from the Japanese Ministry of Education, Culture, Sports, Science and Technologyissue-copyright-statement© The Author(s) 2016 ==== Body Background Human phenotypes, such as physical characteristics, abilities, and disease susceptibility, are determined by both genetic and environmental factors [1–4]. Environmental factors affect human phenotypes by changing the epigenetic modification of the genome, such as by DNA methylation and histone modification [5]. Epigenetic modification changes impact cellular behavior by regulating the chromatin status and gene expression [6] and so the evaluation of epigenetic changes will be used as new laboratory tests. One of the most important epigenomic modifications is the methylation of genomic DNA, which is the covalent addition of a methyl group to the cytosine at CpG dinucleotides. The CpG sites present in the regions containing high numbers of CpG dinucleotides (CpG islands) are generally unmethylated, although those in the majority of other genomic regions are methylated. CpG islands overlap the promoter regions of 60–70 % of genes and are generally protected from methylation, allowing for the expression of downstream genes, the transcription of which is further regulated by histone modification [7]. Many reports show the within-pair differences of methylation levels (WPDMs) in discordant monozygotic twins for several disorders and traits because the aberrant DNA methylation of CpG islands may be an important epigenetic change that affects the developmental process of diseases or traits [8–19]. To identify the association of DNA methylation with the development of disease, general WPDMs in monozygotic twin pairs should be assessed. However, they have not yet been elucidated. In this study, we examined the methylation levels of CpG islands in 113 monozygotic twins, calculated the WPDMs of genomic DNA, and compared the WPDMs between men and women to identify the sex difference in the WPDMs. WPDM of monozygotic twins can reflect the difference of the sensitivity to DNA methylation under the condition of the same genetic background. This study will be able to clarify the sex-related differences in the sensitivity to DNA methylation. Subjects and Methods Subjects A total of 113 healthy Japanese monozygotic twin volunteers (35 male and 78 female pairs) were recruited from the registry established by the Center for Twin Research, Osaka University (Table 1) [20]. Blood was sampled at 9 am after a 12 h fast. A clinical examination was performed, and the twins completed health-related questionnaires. The twins in each pair were examined on the same day. Genomic DNA was isolated from peripheral blood mononuclear cells using a commercial kit (QIAamp DNA Mini Kit, QIAGEN, Germany). The zygosity of subjects was confirmed by the perfect matching of 15 short tandem repeat (STR) loci using the PowerPlex® 16 System (Promega, Madison, WI, USA).Table 1 Character of examined twins Gender Male Female all twins n (pair) 35 78 age (mean ± SD) 67.4 ± 15.0 55.5 ± 17.0 (range) 22–87 21–87 elder n (pair) 30 43 subset age (mean ± SD) 71.8 ± 9.6 68.1 ± 8.6 (range) 57–87 55–87 Methylation level of CpG islands Analysis of the methylation level was performed using an Infinium HumanMethylation450 BeadChip Kit (Illumina), which interrogated 485577 highly informative CpG sites at the single-nucleotide resolution for each sample using the standard manufacturer's protocol. The experiment was performed with 0.5 μg of high-quality genomic DNA. There were 2 bead types for each CpG site per locus on the chip. The raw data were analyzed using the Genome Studio software (Illumina), and the fluorescence intensity ratios between the 2 bead types were calculated. A ratio value of 0 was equal to the nonmethylation of the locus, and a ratio of 1 was equal to total methylation. These raw data were corrected to normalize the differences in detection ranges between the two probes of the Infinium Assay using a peak-based correction method [21]. Normalized data were filtered to exclude invalid probes, such as null probes and probes with low reliability. After filtering, the data were categorized to each of 25657 CpG islands according to the registration of UCSC [22, 23], and a median methylation level was calculated when there were two or more probes in a CpG island. We used the statistical software R (ver.2.15.1) to perform these data analyses. Within-pair differences of the methylation level (WPDM) We calculated the absolute values of differences in each CpG island methylation level between individuals in each pair as follows: WPDM=ML1−ML2 where ML1 is the methylation level of one of each twin pair and ML2 is that of the other twin. We also calculated the gender difference index of WPDMs in each CpG island as follows Genderdifferenceindex=meanofmaleWPDMs−meanoffemaleWPDMs This index is positive when the mean WPDM of a CpG island is higher in a male pair than a female pair. Statistical analysis Student’s t test was used to compare WPDMs between males and females. Statistical analysis was performed using the JMP10 software (SAS Institute, Inc., Tokyo, Japan). Results Within-pair differences in the methylation levels (WPDMs) of CpG islands As shown in Additional file 1: Figure S1, we could find that the WPDMs were larger in many autosomal CpG islands for male pairs than female pairs, whereas the WPDM in many X chromosomal CpG islands were larger in female pairs than male pairs. When we performed the same analysis using only an older subset (>55 years old) (Table 1), we obtained similar results (Fig. 1). As shown in Table 2, means WPDM of CpG islands in each autosomal chromosome were significantly higher in male than in female pairs, whereas that in X chromosome was significantly higher in female than in male pairs. In addition, median of WPDM were also showed the same significances (Table 2).Fig. 1 Within-pair differences in methylation levels for each CpG island (older pairs). Red circles indicate male pairs, and blue circles indicate female pairs. Within-pair differences in older male pairs are also greater in most autosomal CpG islands Table 2 WPDMs of CpG islands in each chromosomes Chromosome number of analyzed CpG island Mean ± SD of WPDM Median (range) of WPDM Male Female P value (student's t test) Male Female P value (MannWhitney test) 1 2327 0.014 ± 0.013 0.009 ± 0.009 1.17 × 10–47 0.009 (0.002–0.093) 0.005 (0.0005–0.067) 0 2 1618 0.015 ± 0.013 0.010 ± 0.009 7.42 × 10–43 0.010 (0.002–0.079) 0.006 (0.0009–0.061) 0 3 1132 0.013 ± 0.011 0.008 ± 0.009 2.18 × 10–28 0.008 (0.002–0.086) 0.005 (0.0006–0.077) 0 4 982 0.015 ± 0.013 0.010 ± 0.009 1.40 × 10–24 0.011 (0.002–0.080) 0.008 (0.0008–0.055) 0 5 1177 0.016 ± 0.014 0.011 ± 0.010 1.37 × 10–27 0.011 (0.002–0.093) 0.007 (0.0006–0.073) 0 6 1220 0.015 ± 0.013 0.009 ± 0.009 3.13 × 10–30 0.010 (0.002–0.113) 0.006 (0.0004–0.066) 0 7 1460 0.015 ± 0.013 0.010 ± 0.009 3.27 × 10–30 0.010 (0.001–0.090) 0.007 (0.0010–0.063) 0 8 959 0.015 ± 0.013 0.010 ± 0.009 1.30 × 10–22 0.010 (0.002–0.075) 0.007 (0.0007–0.070) 0 9 786 0.016 ± 0.014 0.009 ± 0.009 1.75 × 10–35 0.011 (0.002–0.080) 0.006 (0.0011–0.052) 0 10 1092 0.016 ± 0.013 0.010 ± 0.009 1.95 × 10–26 0.010 (0.002–0.079) 0.007 (0.0007–0.058) 0 11 1343 0.014 ± 0.013 0.010 ± 0.009 9.44 × 10–26 0.009 (0.001–0.082) 0.006 (0.0007–0.062) 0 12 1185 0.014 ± 0.012 0.009 ± 0.009 3.99 × 10–23 0.009 (0.002–0.080) 0.006 (0.0010–0.061) 0 13 556 0.016 ± 0.013 0.011 ± 0.009 8.51 × 10–13 0.010 (0.002–0.092) 0.007 (0.0010–0.046) 1.60 × 10–14 14 742 0.014 ± 0.013 0.009 ± 0.008 8.36 × 10–21 0.009 (0.001–0.083) 0.006 (0.0008–0.070) 0 15 725 0.014 ± 0.012 0.009 ± 0.008 1.61 × 10–20 0.009 (0.002–0.075) 0.006 (0.0009–0.055) 0 16 1363 0.014 ± 0.012 0.010 ± 0.009 2.72 × 10–24 0.010 (0.002–0.096) 0.008 (0.0008–0.056) 0 17 1558 0.014 ± 0.012 0.009 ± 0.009 3.91 × 10–28 0.009 (0.002–0.082) 0.006 (0.0007–0.064) 0 18 487 0.016 ± 0.014 0.011 ± 0.010 7.45 × 10–13 0.011 (0.002–0.103) 0.008 (0.0009–0.078) 4.00 × 10–15 19 2441 0.015 ± 0.013 0.011 ± 0.010 4.56 × 10–39 0.010 (0.002–0.087) 0.007 (0.0008–0.081) 0 20 784 0.016 ± 0.013 0.011 ± 0.090 7.60 × 10–19 0.011 (0.002–0.125) 0.008 (0.0008–0.065) 0 21 334 0.014 ± 0.011 0.011 ± 0.009 1.64 × 10–6 0.010 (0.002–0.085) 0.008 (0.0013–0.052) 1.55 × 10–8 22 661 0.014 ± 0.012 0.010 ± 0.009 1.50 × 10–10 0.010 (0.002–0.080) 0.007 (0.0011–0.067) 3.77 × 10–15 X 725 0.015 ± 0.013 0.022 ± 0.009 0 0.010 (0.002–0.078) 0.022 (0.0022–0.056) 0 Boldface types indicate significanlty higher WPDM values The WPDMs of CpG islands in older male and female pairs are shown in Additional file 2: Table S1 in ranking order. Table 3 shows the top-rank 50 CpG islands, which have large WPDMs in older male and female pairs, and the common CpG islands, which are included in the top-rank 50 CpG islands of both genders. These are shown in Table 4.Table 3 Rank order within-pair differences in methylation levels of CpG islands in elder men and women pairs (Top-rank 50, in descending order) Elder male pairs Elder female pairs CpG Islands MEAN ± SD CpG Islands MEAN ± SD chr19:15833733–15833983 0.169 ± 0.171 chr3:128215212–128216905 0.108 ± 0.119 chr20:54824312–54824584 0.167 ± 0.150 chr7:138348962–138349444 0.107 ± 0.115 chr5:140255158–140255450 0.151 ± 0.150 chr19:15833733–15833983 0.104 ± 0.128 chr12:312591–313331 0.138 ± 0.134 chr20:54824312–54824584 0.101 ± 0.119 chr5:1494853–1495287 0.136 ± 0.129 chr4:74847528–74847830 0.098 ± 0.127 chr13:112627428–112627642 0.133 ± 0.117 chr11:67052394–67053110 0.097 ± 0.097 chr19:5074591–5074814 0.133 ± 0.118 chr17:70120139–70120442 0.095 ± 0.092 chr11:62314761–62315054 0.130 ± 0.115 chr19:5074591–5074814 0.094 ± 0.090 chr20:22567453–22567880 0.130 ± 0.129 chr18:77552401–77552603 0.092 ± 0.076 chr5:140764301–140764680 0.129 ± 0.148 chr8:43131177–43131487 0.092 ± 0.081 chr17:7492314–7492945 0.129 ± 0.125 chr17:80346597–80347050 0.092 ± 0.097 chr17:6797429–6797724 0.128 ± 0.135 chr1:149162389–149162615 0.090 ± 0.110 chr10:105428505–105428713 0.128 ± 0.124 chr19:4950670–4950940 0.090 ± 0.068 chr8:72753874–72754755 0.127 ± 0.128 chr4:40752691–40752896 0.090 ± 0.097 chr18:47825069–47825325 0.127 ± 0.154 chr19:39993357–39993765 0.089 ± 0.096 chrX:65041896–65042304 0.125 ± 0.134 chr2:208546082–208546562 0.089 ± 0.102 chr7:27134097–27134303 0.125 ± 0.122 chr8:1321232–1321638 0.089 ± 0.101 chr3:14597400–14597651 0.125 ± 0.141 chr19:57276614–57276942 0.088 ± 0.082 chr8:142219197–142219445 0.125 ± 0.120 chrX:70316349–70316671 0.088 ± 0.107 chr7:73118500–73118749 0.125 ± 0.114 chr6:27482888–27483089 0.088 ± 0.095 chr17:40700164–40700859 0.125 ± 0.141 chr22:25081850–25082112 0.088 ± 0.083 chr19:48047796–48049162 0.124 ± 0.122 chr18:13641584–13642415 0.086 ± 0.083 chr15:27212902–27213396 0.124 ± 0.120 chr22:27834425–27834630 0.086 ± 0.115 chr11:67052394–67053110 0.124 ± 0.112 chr2:131010510–131010764 0.085 ± 0.089 chr1:38200919–38201200 0.124 ± 0.123 chrX:139521561–139521897 0.085 ± 0.105 chr17:18575709–18576477 0.123 ± 0.125 chr18:74114551–74114791 0.085 ± 0.072 chr1:47899125–47899398 0.123 ± 0.118 chr7:57270847–57271464 0.084 ± 0.101 chr5:140221007–140221381 0.123 ± 0.117 chr12:125003217–125003482 0.084 ± 0.097 chr6:27482888–27483089 0.123 ± 0.100 chr6:139116946–139117469 0.084 ± 0.102 chr6:139116946–139117469 0.123 ± 0.112 chr10:101824961–101825186 0.084 ± 0.081 chr9:139715663–139716441 0.122 ± 0.116 chr13:112627428–112627642 0.083 ± 0.102 chr9:135361992–135362481 0.122 ± 0.133 chr3:99594969–99595215 0.083 ± 0.076 chr2:232526666–232527777 0.122 ± 0.125 chr1:156261199–156261425 0.082 ± 0.086 chr19:8397958–8400461 0.122 ± 0.121 chr2:157184389–157184632 0.082 ± 0.082 chr9:69500968–69501225 0.121 ± 0.149 chr1:2082314–2082529 0.082 ± 0.066 chr19:44860657–44860928 0.121 ± 0.128 chr19:21265164–21265433 0.082 ± 0.106 chr2:121279842–121280183 0.120 ± 0.120 chr5:140181888–140183014 0.082 ± 0.083 chr2:131186145–131186496 0.120 ± 0.129 chr9:137252115–137252451 0.082 ± 0.083 chr1:149162389–149162615 0.120 ± 0.121 chr9:135361992–135362481 0.081 ± 0.090 chr11:35965642–35966454 0.119 ± 0.103 chr4:174421347–174421559 0.081 ± 0.087 chr1:75590817–75591354 0.119 ± 0.122 chr13:88329394–88329885 0.081 ± 0.130 chrX:8751285–8751608 0.119 ± 0.138 chr4:74719087–74719339 0.080 ± 0.095 chr1:43472867–43473334 0.119 ± 0.113 chrX:40064743–40064993 0.080 ± 0.100 chr12:125003217–125003482 0.119 ± 0.112 chr6:170589411–170590085 0.079 ± 0.101 chr19:4059917–4060131 0.119 ± 0.115 chr1:75590817–75591354 0.079 ± 0.105 chr1:149230771–149231197 0.119 ± 0.130 chr22:46658397–46659332 0.079 ± 0.092 chr4:41749184–41749811 0.118 ± 0.098 chr15:31689500–31689707 0.079 ± 0.074 chr6:35754713–35754914 0.118 ± 0.130 chr3:151178623–151178984 0.079 ± 0.119 chr14:103604539–103605504 0.118 ± 0.121 chr19:940723–942490 0.079 ± 0.069 chr1:240656253–240656720 0.118 ± 0.123 chr1:41119852–41120136 0.078 ± 0.099 Table 4 CpG islands whose within-pair difference in methylation rates were wide in both men and women CpG Islands RefGene chr19:15833733–15833983 chr20:54824312–54824584 MC3R chr13:112627428–112627642 chr19:5074591–5074814 KDM4B chr11:67052394–67053110 ADRBK1 chr6:27482888–27483089 chr6:139116946–139117469 CCDC28A chr9:135361992–135362481 C9orf171 chr1:149162389–149162615 chr1:75590817–75591354 LHX8 chr12:125003217–125003482 NCOR2 RefGene Reference gene mainly according to UCSC database Gender difference index of WPDMs As shown in Additional file 3: Figure S2, the gender difference indices of WPDMs were positive for 86.0 % (21439/24932) of autosomal CpG islands, but negative for 76.7 % (556/725) of X-chromosomal CpG islands. Comparison of each WPDM between older male and female pairs Of the 25657 CpG islands analyzed, 11461 CpG islands showed low P values (<0.05) for WPDMs between male and female pairs using Student’s t test. Among these significant CpG islands, WPDMs in the male pairs were higher in 11027 CpG islands (10975 were autosomal and 52 were X chromosome), whereas those in female pairs were higher in the other 434 islands (51 were autosomal and 383 were X chromosome) (Additional file 4: Table S2). To perform multiple comparisons, we corrected the P values using the Bonferroni method and found 27 significant CpG islands. Of them, 3 were in autosomal chromosomes (2, 8, 12 chromosomes) and 24 were in the X chromosomes (Table 5). The WPDM in male pairs was significantly higher in all 3 autosomal CpG islands (Fig. 2a–c) and 2 of 24 X chromosomal island (Figs. 2d, 2e). Those in the female pairs were significantly higher in 22 of 24 X chromosomal CpG islands (Figs. 3a-v).Table 5 CpG islands with signigicant difference in WPDMs between men and women pairs Diff (M-F): The difference of mean WPDM between men and women pairs. Mean WPDM of shaded CpG islands were higher in male pairs. Pc: Corrected P using Bonferroni method. RefGene: Reference gene mainly according to UCSC database. WPDM in each pair is shown in the appropriate figures Fig. 2 CpG islands showing greater within-pair differences in methylation levels for older male pairs. See "Scatter chart" column of Table 5 for explanation of each panel Fig. 3 CpG islands showing greater within-pair differences in methylation levels for older female pairs. See "Scatter chart" column of Table 5 for explanation of each panel Discussion We clarified in this study that some CpG islands show large WPDMs both in men and women (Table 4), WPDMs of autosomal CpG islands are generally large in men and those of X-chromosomal CpG islands are generally large in women (Fig. 1, Additional file 1: Figure S1 and Table 2), and multiple comparison indicated the significant differences in WPDMs of some CpG islands between men and women (Table 5) (Figs. 2 and 3). We suppose that these may be caused by the sex-related differences in sensitivity to the DNA methylation or the sex-related difference in the exposure to environment. Therefore, it will be required extra attention to sex-related individual differences when we analyze DNA methylation. According to the UCSC database [22, 23], the CpG islands with large WPDMs common to both male and female pairs (Table 4) are located near the genes encoding the MC3R (melanocortin 3 receptor), KDM4B (lysine (K)-specific demethylase 4B), ADRBK1 (adrenergic beta receptor kinase 1, also known as GRK2), CCDC28A (coiled-coil domain containing 28A), C9orf171 (chromosome 9 open reading frame 171), LHX8 (LIM homeobox 8), NCOR2 (nuclear receptor corepressor 2), and so on (Table 4). Two of the genes, MC3R and ADRBK1, are related to the regulation of energy homeostasis [24, 25]. Such genes may be susceptible epigenetic changes by environmental factors in both men and women. In addition, these results will serve the data as controls when interpreting the biological relevance of sex-related CpG islands. In the present study, we found that the WPDMs of most X chromosomal CpG islands are larger in female pairs. This may be due to the random inactivation of the X chromosome, which is specific for females [26]. Interestingly, the WPDMs of most autosomal CpG islands were larger in male pairs. We confirmed these data using older twins because the WPDMs increase with age [27–30]. These indicate that individual differences in most autosomal methylation levels are greater in men than women and suggest that epigenetic changes of DNA in autosomal chromosomes may be more dynamic in men, indicating that men may be more sensitive to environmental factors or may encounter more opportunities to interact with environmental factors compared to women. It is possible that the large differences in WPDMs of particular gene between men and women may be related to the sex differences in the disease susceptibility of acquired diseases which affected by DNA methylation in that gene. In the present study, statistical analyses indicate that WPDMs were significantly greater in 3 autosomal (Figs. 2a-c) and 2 X chromosomal CpG islands in men (Figs. 2d and e), but were significantly greater in 22 X chromosomal CpG islands in women (Figs. 3a-v). Two of these autosomal CpG islands are located near known genes, ADGRB1 (adhesion G protein-coupled receptor B1) and SLC6A12 (solute carrier family 6 (neurotransmitter transporter) member 12) (Table 5). Interestingly, glioblastoma [31], gastric cancer [32], and colorectal cancer [33], which are dominant in males [34–36], are associated with ADGRB1, and schizophrenia [37] and autism [38], which are also dominant in males [39, 40], are associated with SLC6A12. By contrast, although the WPDMs of the majority of CpG islands in the X chromosome are greater in women, the WPDMs of the two CpG islands in the X chromosome were significantly greater in male pairs. These CpG islands are located near known genes, including ARSD (arylsulfatase D), KCNE1L known as KCNE5 (potassium channel voltage gated subfamily E regulatory beta subunit 5), GYG2 (glycogenin 2), and IRS4 (insulin receptor substrate 4) (Table 5). KCNE1L and ARSD are associated with atrial fibrillation [41] and gastric dilatation [42], respectively, both of which are also male dominant [43, 44]. GYG2 is involved in blood glucose homeostasis [45] and IRS4 encodes the insulin receptor substrate. The CpG sites in such glucose-related genes may be easily influenced by glucose levels, which are higher in men than in women [46]. On the other hand, HCFC1 (host cell factor C1), which has a higher WPDMs in women, is associated with herpes simplex infection [47], which is female dominant [48]. Because one of the limitations of this study may be the sample size, which is not enough for high statistical power, there may be some other minor significances we could not find. Another limitation may be a lack of replication study because it is difficult to collect healthy twin data for another cohort. It will be important to analyze the age as co-factor to explore whether the pattern of sex difference changes with age although we could not because of the small sample size. In future, when DNA methylation levels are used as new laboratory tests, our data will be important to know the physiological difference and may also supply significances for diagnosis or prognosis of some sex-related disorders. Conclusion In conclusion, sex-related differences were present in the WPDMs of autosomal and X-chromosomal CpG islands, which were greater in men and women, respectively for individuals with the same genetic background. These differences may be associated with the sexual influences in susceptibility of some diseases. Additional files Additional file 1: Figure S1. Within-pair differences for the methylation levels (WPDMs) of each CpG island. Red circles indicate male pairs, and blue circles indicate female pairs. Within-pair differences in male pairs are greater in most autosomal CpG islands. (TIF 2145 kb) Additional file 2: Table S1. Rank order within-pair differences in methylation levels (WPDMs) of CpG islands in older male and female pairs (in descending order). (XLSX 2065 kb) Additional file 3: Figure S2. Comparison of within-pair differences in methylation levels (WPDMs) between older male and older female pairs. The gender difference index is positive when the mean within-pair differences in the methylation levels are higher in male pairs than female pairs. (TIF 298 kb) Additional file 4: Table S2. Results of statistical test comparing within-pair difference of methylation levels (WPDMs) between older male and female twin pairs. WPDMs in the male pairs were higher in 11027 CpG islands (10975 were autosomal and 52 were X chromosome), whereas those in female pairs were higher in the other 434 islands (51 were autosomal and 383 were X chromosome). (XLSX 1758 kb) Additional file 5: Table S3. Data supporting the findings in this study. (XLSX 6571 kb) Abbreviations CpGCytosine-phosphodiester bond-Guanine MLMethylation level STRShort tandem repeat WPDMWithin-pair differences of the methylation level Acknowledgements The authors are thankful to all of the consultants from the Osaka Twin Research Group (Yoshinori Iwatani (lead author, iwatani@sahs.med.osaka-u.ac.jp), Shiro Yorifuji, Hiroyasu Iso, Kei Kamide, Jun Hatazawa, Shinji Kihara, Norio Sakai, Hiroko Watanabe, Kiyoko Makimoto, Mikio Watanabe, and Chika Honda, Center for Twin Research, Osaka University Graduate School of Medicine) and all of the technical and secretarial staff of the Center for Twin Research, Osaka University Graduate School of Medicine. The authors are also thankful to Beckman Coulter, Inc. (Tokyo, JAPAN) for collaborative studies. Funding This project was supported by University Grants from the Japanese Ministry of Education, Culture, Sports, Science and Technology, and also by JSPS KAKENHI Grant Number 24590695, and also by the Charitable Trust Laboratory Medicine Research Foundation of Japan. Availability of data and material The data supporting our findings can be found in Additional file 5: Table S3. Authors’ contributions MW, CH, and YI conceived and designed the experiments. MW analyzed the data. MW and YI interpreted the results and wrote the paper. All authors reviewed and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Written consent for publication was obtained from all of the twins. Ethics approval and consent to participate Written informed consent was obtained from all of the twins, and the Ethics Committee of Osaka University approved the study protocol (No. 506). ==== Refs References 1. Bouchard TJ Jr McGue M Genetic and environmental influences on human psychological differences J Neurobiol 2003 54 4 45 10.1002/neu.10160 12486697 2. Ellis JA Kemp AS Ponsonby AL Gene-environment interaction in autoimmune disease Expert Rev Mol Med 2014 16 e4 10.1017/erm.2014.5 24602341 3. Martin GM Constitutional, somatic genetic and environmental aspects of the phenotypic diversity of aging in human subjects Basic Life Sci 1988 43 183 90 3284519 4. McGue M Bouchard TJ Jr Genetic and environmental influences on human behavioral differences Annu Rev Neurosci 1998 21 1 24 10.1146/annurev.neuro.21.1.1 9530489 5. Meyer P Epigenetic variation and environmental change J Exp Bot 2015 66 3541 8 10.1093/jxb/eru502 25694547 6. Esteller M Epigenetics in cancer N Engl J Med 2008 358 1148 59 10.1056/NEJMra072067 18337604 7. Jones PA Baylin SB The epigenomics of cancer Cell 2007 128 683 92 10.1016/j.cell.2007.01.029 17320506 8. Castellani CA Melka MG Diehl EJ Laufer BI O'Reilly RL Singh SM DNA methylation in psychosis: insights into etiology and treatment Epigenomics 2015 7 67 74 10.2217/epi.14.66 25687467 9. Dempster EL Wong CC Lester KJ Burrage J Gregory AM Mill J Eley TC Genome-wide methylomic analysis of monozygotic twins discordant for adolescent depression Biol Psychiatry 2014 76 977 83 10.1016/j.biopsych.2014.04.013 24929637 10. Kratz CP Edelman DC Wang Y Meltzer PS Greene MH Genetic and epigenetic analysis of monozygotic twins discordant for testicular cancer Int J Mol Epidemiol Genet 2014 5 135 9 25379132 11. Liu F Sun Q Wang L Nie S Li J Bioinformatics analysis of abnormal DNA methylation in muscle samples from monozygotic twins discordant for type 2 diabetes Mol Med Rep 2015 12 351 6 25760736 12. Nilsson E Jansson PA Perfilyev A Volkov P Pedersen M Svensson MK Altered DNA methylation and differential expression of genes influencing metabolism and inflammation in adipose tissue from subjects with type 2 diabetes Diabetes 2014 63 2962 76 10.2337/db13-1459 24812430 13. Ollikainen M Ismail K Gervin K Kyllonen A Hakkarainen A Lundbom J Genome-wide blood DNA methylation alterations at regulatory elements and heterochromatic regions in monozygotic twins discordant for obesity and liver fat Clin Epigenetics 2015 7 39 10.1186/s13148-015-0073-5 25866590 14. Ottini L Rizzolo P Siniscalchi E Zijno A Silvestri V Crebelli R Marcon F Gene promoter methylation and DNA repair capacity in monozygotic twins with discordant smoking habits Mutat Res Genet Toxicol Environ Mutagen 2015 779 57 64 10.1016/j.mrgentox.2015.01.006 25813726 15. Roos L Spector TD Bell CG Using epigenomic studies in monozygotic twins to improve our understanding of cancer Epigenomics 2014 6 299 309 10.2217/epi.14.13 25111484 16. Schreiner F Gohlke B Stutte S Bartmann P Hecher K Oldenburg J 11p15 DNA-methylation analysis in monozygotic twins with discordant intrauterine development due to severe twin-to-twin transfusion syndrome Clin Epigenetics 2014 6 6 10.1186/1868-7083-6-6 24678997 17. Selmi C Cavaciocchi F Lleo A Cheroni C De Francesco R Lombardi SA Genome-wide analysis of DNA methylation, copy number variation, and gene expression in monozygotic twins discordant for primary biliary cirrhosis Front Immunol 2014 5 128 24734033 18. Tan Q Frost M Heijmans BT von Bornemann HJ Tobi EW Christensen K Christiansen L Epigenetic signature of birth weight discordance in adult twins BMC Genomics 2014 15 1062 10.1186/1471-2164-15-1062 25476734 19. Yuan W Xia Y Bell CG Yet I Ferreira T Ward KJ An integrated epigenomic analysis for type 2 diabetes susceptibility loci in monozygotic twins Nat Commun 2014 5 5719 10.1038/ncomms6719 25502755 20. Hayakawa K Iwatani Y and Osaka Twin Research G An overview of multidisciplinary research resources at the Osaka University Center for Twin Research Twin Res Hum Genet 2013 16 217 20 10.1017/thg.2012.141 23298684 21. Dedeurwaerder S Defrance M Calonne E Denis H Sotiriou C Fuks F Evaluation of the Infinium Methylation 450 K technology Epigenomics 2011 3 771 84 10.2217/epi.11.105 22126295 22. The University of California. The Genome Browser. https://genome.ucsc.edu/. Accessed 22 Dec 2015 23. Kent WJ Sugnet CW Furey TS Roskin KM Pringle TH Zahler AM Haussler D The human genome browser at UCSC Genome Res 2002 12 996 1006 10.1101/gr.229102.ArticlepublishedonlinebeforeprintinMay2002 12045153 24. Begriche K Girardet C McDonald P Butler AA Melanocortin-3 receptors and metabolic homeostasis Prog Mol Biol Transl Sci 2013 114 109 46 10.1016/B978-0-12-386933-3.00004-2 23317784 25. Vila-Bedmar R Garcia-Guerra L Nieto-Vazquez I Mayor F Jr Lorenzo M Murga C Fernandez-Veledo S GRK2 contribution to the regulation of energy expenditure and brown fat function FASEB J 2012 26 3503 14 10.1096/fj.11-202267 22516294 26. Gendrel AV Heard E Noncoding RNAs and epigenetic mechanisms during X-chromosome inactivation Annu Rev Cell Dev Biol 2014 30 561 80 10.1146/annurev-cellbio-101512-122415 25000994 27. Hannum G Guinney J Zhao L Zhang L Hughes G Sadda S Genome-wide methylation profiles reveal quantitative views of human aging rates Mol Cell 2013 49 359 67 10.1016/j.molcel.2012.10.016 23177740 28. Heyn H Li N Ferreira HJ Moran S Pisano DG Gomez A Distinct DNA methylomes of newborns and centenarians Proc Natl Acad Sci U S A 2012 109 10522 7 10.1073/pnas.1120658109 22689993 29. Horvath S DNA methylation age of human tissues and cell types Genome Biol 2013 14 R115 10.1186/gb-2013-14-10-r115 24138928 30. Rakyan VK Down TA Maslau S Andrew T Yang TP Beyan H Human aging-associated DNA hypermethylation occurs preferentially at bivalent chromatin domains Genome Res 2010 20 434 9 10.1101/gr.103101.109 20219945 31. Zhu D Hunter SB Vertino PM Van Meir EG Overexpression of MBD2 in glioblastoma maintains epigenetic silencing and inhibits the antiangiogenic function of the tumor suppressor gene BAI1 Cancer Res 2011 71 5859 70 10.1158/0008-5472.CAN-11-1157 21724586 32. Lee JH Koh JT Shin BA Ahn KY Roh JH Kim YJ Kim KK Comparative study of angiostatic and anti-invasive gene expressions as prognostic factors in gastric cancer Int J Oncol 2001 18 355 61 11172604 33. Fukushima Y Oshika Y Tsuchida T Tokunaga T Hatanaka H Kijima H Brain-specific angiogenesis inhibitor 1 expression is inversely correlated with vascularity and distant metastasis of colorectal cancer Int J Oncol 1998 13 967 70 9772287 34. Kleihues P Ohgaki H Primary and secondary glioblastomas: from concept to clinical diagnosis Neuro Oncol 1999 1 44 51 11550301 35. Buas MF Vaughan TL Epidemiology and risk factors for gastroesophageal junction tumors: understanding the rising incidence of this disease Semin Radiat Oncol 2013 23 3 9 10.1016/j.semradonc.2012.09.008 23207041 36. Koo JH Leong RW Sex differences in epidemiological, clinical and pathological characteristics of colorectal cancer J Gastroenterol Hepatol 2010 25 33 42 10.1111/j.1440-1746.2009.05992.x 19874446 37. Park HJ Kim JW Lee SK Kim SK Park JK Cho AR Association between the SLC6A12 gene and negative symptoms of schizophrenia in a Korean population Psychiatry Res 2011 189 478 9 10.1016/j.psychres.2011.01.023 21367462 38. Silva IM Rosenfeld J Antoniuk SA Raskin S Sotomaior VS A 1.5Mb terminal deletion of 12p associated with autism spectrum disorder Gene 2014 542 83 6 10.1016/j.gene.2014.02.058 24613754 39. Markham JA Sex steroids and schizophrenia Rev Endocr Metab Disord 2012 13 187 207 10.1007/s11154-011-9184-2 21603930 40. Werling DM Geschwind DH Sex differences in autism spectrum disorders Curr Opin Neurol 2013 26 146 53 10.1097/WCO.0b013e32835ee548 23406909 41. Ravn LS Aizawa Y Pollevick GD Hofman-Bang J Cordeiro JM Dixen U Gain of function in IKs secondary to a mutation in KCNE5 associated with atrial fibrillation Heart Rhythm 2008 5 427 35 10.1016/j.hrthm.2007.12.019 18313602 42. Haskins ME Desnick RJ DiFerrante N Jezyk PF Patterson DF Beta-glucuronidase deficiency in a dog: a model of human mucopolysaccharidosis VII Pediatr Res 1984 18 980 4 6436780 43. Benjamin EJ Levy D Vaziri SM D'Agostino RB Belanger AJ Wolf PA Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study JAMA 1994 271 840 4 10.1001/jama.1994.03510350050036 8114238 44. Jennings PB Jr Butzin CA Epidemiology of gastric dilatation-volvulus in the military working dog program Mil Med 1992 157 369 71 1528473 45. Mu J Skurat AV Roach PJ Glycogenin-2, a novel self-glucosylating protein involved in liver glycogen biosynthesis J Biol Chem 1997 272 27589 97 10.1074/jbc.272.44.27589 9346895 46. Soeters MR Sauerwein HP Groener JE Aerts JM Ackermans MT Glatz JF Gender-related differences in the metabolic response to fasting J Clin Endocrinol Metab 2007 92 3646 52 10.1210/jc.2007-0552 17566089 47. Vogel JL Kristie TM The dynamics of HCF-1 modulation of herpes simplex virus chromatin during initiation of infection Viruses 2013 5 1272 91 10.3390/v5051272 23698399 48. Liesegang TJ Herpes simplex virus epidemiology and ocular importance Cornea 2001 20 1 13 10.1097/00003226-200101000-00001 11188989

PMC005xxxxxx/PMC5000520.txt

==== Front BMC Musculoskelet DisordBMC Musculoskelet DisordBMC Musculoskeletal Disorders1471-2474BioMed Central London 122710.1186/s12891-016-1227-0Research ArticleEffects of a DXA result letter on satisfaction, quality of life, and osteoporosis knowledge: a randomized controlled trial Edmonds Stephanie W. stephanie-edmonds@uiowa.edu 12Cram Peter peter.cram@uhn.ca 34Lou Yiyue yiyue-lou@uiowa.edu 5Jones Michael P. michael-p-jones@uiowa.edu 56Roblin Douglas W. droblin@gsu.edu 78Saag Kenneth G. ksaag@uab.edu 9Wright Nicole C. ncwright@uab.edu 10Wolinsky Fredric D. fredric-wolinsky@uiowa.edu 1211On Behalf of the PAADRN InvestigatorsCurtis Jeffrey R. Morgan Sarah L. Schlechte Janet A. Zelman David J. 1 Carver College of Medicine, Department of Internal Medicine, University of Iowa, 5231 Westlawn, IA 52242 Iowa City, IA USA 2 College of Nursing, University of Iowa, Iowa City, IA USA 3 Department of Medicine, University of Toronto Division of General Internal Medicine, Toronto, ON Canada 4 University Health Network and Mount Sinai Hospital, Toronto, ON Canada 5 College of Public Health, Department of Biostatistics, University of Iowa, Iowa City, IA USA 6 Iowa City Veterans Affairs Health System, Iowa City, IA USA 7 Kaiser Permanente, Atlanta, GA USA 8 School of Public Health, Department of Health Management and Policy, Georgia State University, Atlanta, GA USA 9 Department of Internal Medicine, Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, AL USA 10 School of Public Health, Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL USA 11 College of Public Health, Department of Health Management and Policy, University of Iowa, Iowa, IA USA 26 8 2016 26 8 2016 2016 17 1 36925 3 2016 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Undiagnosed, or diagnosed and untreated osteoporosis (OP) increases the likelihood that falls result in hip fractures, decreased quality of life (QOL), and significant medical expenditures among older adults. We tested whether a tailored dual energy x-ray absorptiometry (DXA) test result letter and an accompanying educational bone-health brochure affected patient satisfaction, QOL, or OP knowledge. Methods The Patient Activation after DXA Result Notification (PAADRN) study was a double-blinded, pragmatic, randomized trial which enrolled patients from 2012 to 2014. We randomized 7,749 patients presenting for DXA at three health care institutions in the United States who were ≥ 50 years old and able to understand English. Intervention patients received a tailored letter four weeks after DXA containing their results, 10-year fracture risk, and a bone-health educational brochure. Control patients received the results of their DXA per the usual practices of their providers and institutions. Satisfaction with bone health care, QOL, and OP knowledge were assessed at baseline and 12- and 52-weeks after DXA. Intention-to-treat analyses used multiple imputation for missing data and random effects regression models to adjust for clustering within providers and covariates. Results At 12-weeks 6,728 (86.8 %) and at 52-weeks 6,103 participants (78.8 %) completed their follow-up interviews. The intervention group was more satisfied with their bone health care compared to the usual care group at both their 12- and 52-week follow-ups (standardized effect size = 0.28 at 12-weeks and 0.17 at 52-weeks, p < 0.001). There were no differences between the intervention and usual care groups in QOL or OP knowledge at either time point. Conclusions A tailored DXA result letter and bone-health educational brochure sent to patients improved patient satisfaction with bone-related health care. Trial registration Clinical Trials.gov Identifier: NCT01507662 First received: December 8, 2011. Keywords OsteoporosisQuality of lifeQuality of health careHealth educationDual-energy x-ray absorptiometryhttp://dx.doi.org/10.13039/100000049National Institute on Agingby R01 AG033035Cram Peter issue-copyright-statement© The Author(s) 2016 ==== Body Background Although only 10 % of Americans ≥ 50 years old are currently diagnosed with osteoporosis (OP) based on dual energy x-ray absorptiometry (DXA) testing [1], the lifetime risk of a low-impact fracture is 40 % for older women and 13 % for older men [2]. Hip fractures, related to OP, are associated with increased mortality and serious adverse effects on quality of life (QOL) and health care costs [3]. Many older adults know very little about their OP risks or the rationale for screening to identify this silent disease [4, 5]. As suggested by health behavior theories, like the Health Belief Model [6], knowledge of OP, its risks and how to prevent or improve OP, is a first step for patients in making bone health-related behavior changes (i.e. getting adequate amounts of calcium, vitamin D and weight-bearing exercise, taking appropriate pharmacotherapy, preventing falls). Some randomized controlled trials (RCTs) have demonstrated that educational interventions improve OP-related knowledge [7–16]. Less is known about whether such interventions affect patient satisfaction or QOL [17, 18]. Most of these RCTs examining OP patient-education interventions have been multifaceted or lengthy [7, 12, 13, 15, 16], which are not scalable. To date, only one RCT has examined the effect of an OP education intervention on QOL, reporting a beneficial effect after both three months and one year [16]. To our knowledge only three studies have shown that patients receiving educational or quality improvement interventions were more satisfied with their bone-health care than usual care groups [16, 19, 20]. However, two of these studies were conducted only with older women with an OP diagnosis [16, 19]. The other study only saw improved satisfaction for timeliness in test result notification but not in other measures of satisfaction (e.g. understanding DXA results or treatment options) [20]. Because tailored interventions individualized to the patient’s characteristics are more effective and preferred by patients than standardized interventions [21, 22], we developed a tailored, pragmatic patient-activation intervention. We reported that 90 % of older adults wanted to receive their DXA results by mail [23]. Therefore, we developed a DXA result letter and a bone-health educational brochure. We then designed and conducted a pragmatic RCT to assess the impact of this intervention on the pathways leading to appropriate pharmacotherapy, health behavior change, and satisfaction with bone-health care, QOL, OP knowledge, and cost-effectiveness (www.ClinicalTrials.gov Identifier NCT01507662). This article describes the effects of the intervention on three patient-reported outcomes: satisfaction with bone health care, QOL, and OP knowledge at 12 and 52 weeks post-baseline. We hypothesized that the intervention would improve bone-health care satisfaction and OP knowledge at both time points, but would not change QOL. Methods Participants Patients ≥ 50 years old presenting for DXA between February 2012 and August 2014 at the University of Iowa (UI), University of Alabama at Birmingham (UAB), and Kaiser Permanente of Georgia (KPGA) were invited to participate. We excluded non–English speakers and prisoners. Twenty dollar gift cards were provided after the baseline interview. Design and randomization We used a double-blind, parallel, pragmatic RCT [24]. After patients completed their DXA and baseline interviews they were randomized based on their providers using a computer program written in R [25]. Providers were first ranked within sites based on the number of DXAs they ordered in the previous two years, and then they were randomized within sites using blocks of three into three groups (1:1:1 allocation ratio). Patients of providers in the first group were assigned to the intervention arm, patients of providers in the second group were assigned to the usual care arm, and patients of providers in the third group were randomized to either the usual care or intervention arms (1:1 allocation ratio). We selected three provider randomization groups to assess potential spill-over effects on the main outcomes for usual care patients of providers in the third group. Procedures At baseline, research assistants (RAs) at each site used REDCap™ [26] computer assisted interviewing (CAI) software to interview patients up to four weeks before or three days after their DXA. All KPGA patients and half of the UI patients completed these interviews in person. All UAB patients and the remaining UI patients completed their baseline interviews over the telephone. Three RAs at UI mailed study materials to intervention patients. Intervention Intervention materials included a letter describing results of their DXA (lowest T-score and interpretation [OP, low BMD or normal]), a graphic portrayal of their 10-year probability for a major osteoporotic fracture (using FRAX®; https://www.shef.ac.uk/FRAX/), and a bone-health educational brochure. These materials have been described elsewhere [27, 28]. Outcomes Twelve weeks and 52 weeks after their DXA, Iowa Social Science Research Center interviewers telephoned patients at all three sites to conduct follow-up interviews using WinCATI 4 · 2 and 5 · 0 CAI software (Sawtooth Technologies, Northbrook, IL). Interview questions have been described elsewhere [24]. OP Care Satisfaction. This five-item scale assesses patient satisfaction with notification and understanding DXA results, understanding OP treatments, receiving adequate information to make an informed decision, and overall satisfaction with bone-health care. Response options ranged from strongly agree to strongly disagree, with summary scores ranging from 5 (least satisfied) to 25 (most satisfied). Four of these items were used in a previous study [20], with a fifth item related to overall satisfaction added for the current study. Because this was the first use of the satisfaction with OP care scale after its development and initial publication, we used exploratory factor and reliability analyses to explore its psychometric properties. Those results revealed a simple factor structure that was unidimensional with principal factor loadings for each item ranging from 0.53 to 0.77, and an internal consistency reliability (alpha) coefficient of 0.77. At baseline, these items were only asked of patients with prior DXAs because they were irrelevant for DXA naïve patients. All patients were asked these questions at the 12- and 52-week interviews. Quality of Life. We used three QOL measures. The first was the SF-1 (“In general, would you say your health is excellent, very good, good, fair, or poor”), which was scored as 95, 90, 80, 30, and 15 to reflect the underlying health utilities [29]. The second QOL measure was the EQ-5D-3 L which has five items assessing difficulties with mobility, self-care, activities of daily living, pain, and mood (α = 0 · 70) [30, 31]. Responses (no difficulties, some, or were completely impaired) were converted to health utilities ranging from 0 (death) to 1 (best health state) [30, 31]. The third QOL measure was the EuroQol Visual Analog Scale (VAS) which asks patients to rate their health from 1 (worst health state they can imagine) to 100 (best health state they can imagine) [30, 31]. OP Knowledge. We used the 10-item “Osteoporosis and You” scale [5, 32] to measure. The five responses ranged from strongly agree (SA) to strongly disagree (SD), which were collapsed into “correct” or “incorrect” responses. Correct responses (SA or A for true or SD or D for false statements) were coded “1” with incorrect responses coded “0”. We summed the responses into a total score (α = 0 · 68). We also examined the subscales (biological, lifestyle, consequences, and prevention and treatment). Statistical considerations and analysis PAADRN was powered for guideline concordant treatment as the clinical endpoint. Therefore, for the current analysis, we calculated the statistical power that we would have to detect a standardized effect size of 0.10 with p < 0.05 and attrition from baseline as high as 20 %. Those calculations indicated that we would have 91.3 % power to detect such differences. We used multiple imputation techniques to account for missingness (lost to follow-up, patient refused a specific question or responded “don’t know”). We imputed each item separately and constructed the outcomes based on the imputed values. Our primary analysis was based on intention-to-treat (ITT). We first compared the outcome measures between the intervention and control groups at baseline and at the two follow-ups using t-tests. We then used linear random effects regression methods to adjust for patient clustering within provider and for pre-specified covariates. For patient satisfaction, we first examined differences between intervention and control groups at 12-weeks and 52-weeks (baseline patient satisfaction was only asked for those with prior DXAs). Among those with prior DXAs, we adjusted for baseline satisfaction in separate models. For QOL and OP knowledge we examined differences between baseline and 12-weeks, and baseline and 52-weeks. We used Bonferroni methods to adjust for testing at two time points (12- and 52-weeks) and for using three QOL measures. We examined minimally important differences (MIDs) defined distributionally as improvements ≥ 0.5 standard deviations (SD) [33]. For the EQ-5D utility score we also used an anchor-based approach to predict utility scores for the pairwise SF-1 comparisons (adjusting for age, gender, and race). We also investigated pre-specified heterogeneity of treatment (HTE) effects. These included median splits on preferred approaches to health care decision-making and treatments [34], those with prior DXAs vs. those without, those on OP-medications at baseline vs. those who were not, those with a history of OP or osteopenia at baseline vs. those who did not, site (UAB vs. KPGA vs. UI), age (<65 vs. 65-75 vs. > 75), men vs. women, Whites vs. non-Whites, education (high school or less vs. some college vs. graduate school), self-rated health (poor vs. fair vs. good vs. very good vs. excellent), having COPD, depression, or prior fracture at baseline (vs. not), FRAX risk (low vs. moderate vs. high), current smoker vs. former smoker vs. never smoked, heavy vs. moderate alcohol consumption, and median splits on weight-bearing exercise. In sensitivity analyses we used case-wise deletion instead of multiple imputation. Because those results were entirely consistent with the results presented below that used multiple imputation, we only report the latter here. With the Bonferroni adjustments, all p-values were 2-tailed with ≤ 0.025 deemed statistically significant for patient satisfaction and OP-related knowledge, and < 0.0083 deemed statistically significant for the three measures of QOL. Analyses were performed using SAS 9 · 4 (SAS Institute Inc., Cary, NC). Results Participant enrollment and characteristics There were 20,397 potentially eligible patients, of whom 7,782 agreed to participate, were interviewed at baseline, and were then randomized to either the intervention or usual care groups (Fig. 1). Of these, 33 patients were randomized in error and were removed from the study, leaving 7,749 patients. Of these, 6,728 (86.8 %) completed the 12-week and 6,107 (78.8 %) completed the 52-week follow-up interviews. All 7,749 randomized participants were included in the analysis using intent-to-treat principles.Fig. 1 CONSORT Flow Diagram of PAADRN Study Table 1 presents baseline characteristics for all 7,749 participants. The mean age of our participants was 66 years, 84 % were women, 77 % were White, and 67 % had previously undergone DXA. The intervention and usual care groups were similar in age, sex, race, education, and self-reported health. The usual care group, however, was more likely to have had OP prior to baseline (p = 0.001), and to have had an index DXA indicating low bone mineral density (BMD) or OP (p = 0.001).Table 1 Baseline characteristics by treatment group among the PAADRN participants (N = 7,749) Intervention (N = 3,898) Control (N = 3,851) P-Value Sociodemographics  Age, mean (SD) 66.5 (8.4) 66.7 (8.2) 0.2461  Women, N (%) 3,259 (83.6) 3,230 (83.9) 0.7502 Race/Ethnicity  White, N (%) 2,981 (76.5) 2,954 (76.7) 0.6992  Black, N (%) 842 (21.6) 814 (21.1)  Other, N (%) 75 (1.9) 83 (2.2) Education  Some high school, N (%) 161 (4.2) 140 (3.7) 0.7492  Completed high school, N (%) 819 (21.2) 836 (21.9)  Some college, N (%) 1,290 (33.4) 1,269 (33.2)  Completed college, N (%) 785 (20.3) 762 (19.9)  Graduate school, N (%) 809 (20.9) 814 (21.3) Comorbid Conditions  COPD, N (%) 259 (6.7) 265 (6.9) 0.6802  Depression, N (%) 902 (23.2) 885 (23.0) 0.8782  Prostate cancer, N (%) 117 (18.3) 88 (14.2) 0.0482  Breast cancer, N (%) 416 (10.7) 612 (15.9) <0.0012 Health Habits  Current smoker, N (%) 295 (7.6) 295 (7.7) 0.8732  Past smoker, N (%) 1,478 (37.9) 1,388 (36.1) 0.0952  Current alcohol user, N (%) 1,768 (45.4) 1,808 (47.0) 0.1572 Self-reported Health Status  Excellent, N (%) 445 (11.4) 494 (12.8) 0.3292  Very Good, N (%) 1,443 (37.1) 1,373 (35.7)  Good, N (%) 1,280 (32.9) 1,253 (32.6)  Fair, N (%) 571 (14.7) 566 (14.7)  Poor, N (%) 150 (3.9) 159 (4.1) Bone Health  Prior DXA, N (%) 2,606 (66.9) 2,590 (67.3) 0.7192  History of OP, N (%) 794 (20.6) 909 (23.8) 0.0012  History of OP treatment, N (%) 1,438 (36.9) 1,502 (39.0) 0.0552  Glucocorticoids Use, N (%) 593 (15.2) 576 (15.0) 0.7532 Study DXA Results  Normal, N (%) 1,133 (29.1) 990 (25.7) 0.0012  Low BMD, N (%) 2,052 (52.6) 2,066 (53.6)  Osteoporosis, N (%) 713 (18.3) 795 (20.6)  Lowest T-Score, mean (SD) -1.62 (1.1) -1.55 (1.1) 0.0021  10-year Fracture Risk (FRAX), mean (SD) 12.0 (9.2) 12.3 (9.1) 0.1011 1 P-value from Two-sample T-Test 2 P-value is from Pearson Chi-square Test Patient satisfaction with OP health care Intervention patients had significantly greater (better) levels of patient satisfaction with their bone-health care than the usual care group at both 12-weeks (1.0 points, standardized effect size = 0.28, p < 0.001; Table 2) and 52-weeks (0.6 points, standardized effect size = 0.21, p < 0.001). Adjustments for clustering within providers and the covariates did not alter these differences (1.02 points at 12-weeks and 0.63 at 52-weeks, p < 0.0005; Table 3). Patients in the intervention group had 58 % greater odds of having an MID improvement (AOR = 1.58, p < 0.0005) at 12-weeks and 34 % greater odds at 52-weeks (AOR = 1.34, p < 0.005). We observed comparable results in all of the HTE comparison groups (not shown).Table 2 Unadjusted means (SDs) on all 7,749 PAADRN participants at baseline, 12- and 52-weeks using intention-to-treat (ITT) Baseline 12-weeks 52-weeks Intervention Control P-value Intervention Control P-value Intervention Control P-value OP care satisfaction (5-25) 18.9 (2.7)a 19.1 (2.8)a 0.011 21.1 (3.2) 20.1 (4.0) <0.001 21.1 (3.2) 20.5 (3.8) <0.001 Quality of life  SF-1 (15/30/80/90/95; poor to excellent) 75.2 (23.8) 75.1 (24.1) 0.925 74.6 (24.2) 74.8 (24.4) 0.746 74.5 (24.1) 75.4 (23.8) 0.132  EuroQol EQ5D-3 L utility score (0-1) 0.8 (0.2) 0.8 (0.2) 0.676 0.8 (0.2) 0.8 (0.2) 0.547 0.8 (0.2) 0.8 (0.2) 0.72  EuroQol visual analog scale of Euroqol (0-100) 78.1 (16.7) 78.3 (16.7) 0.590 77.5 (17.6) 78.2 (17.2) 0.083 77.7 (17.6) 78.2 (17.1) 0.244  OPc knowledge – scale score (0-10) 7.5 (1.9) 7.5 (1.8) 0.712 7.8 (1.6) 7.8 (1.6) 0.759 7.8 (1.6) 7.8 (1.6) 0.476  Biological risk factors 2.3 (0.9) 2.3 (0.9) 0.345 2.5 (0.8) 2.4 (0.8) 0.495 2.5 (0.8) 2.5 (0.8) 0.724  Lifestyle risk factors 1.8 (0.4) 1.8 (0.4) 0.807 1.9 (0.3) 1.9 (0.4) 0.089 1.9 (0.4) 1.9 (0.4) 0.327  Consequences 1.7 (0.6) 1.7 (0.6) 0.688 1.7 (0.5) 1.7 (0.5) 0.471 1.7 (0.5) 1.7 (0.5) 0.485  Prevention and treatment 1 (0.8) 1 (0.8) 0.974 1 (0.8) 1 (0.8) 0.726 0.9 (0.8) 0.9 (0.8) 0.832 aThese are means and standard deviations among those who had a DXA prior to baseline interview Table 3 Regression coefficients for the intervention on satisfaction with OP care, QOL, and OP knowledge from the intention-to-treat (ITT) random effects models (N = 7,749) 12-weeks 52-weeks Crude Adjusted Crude Adjusted OP care satisfaction (5-25)a Estimate 1.02* 1.02* 0.61* 0.62* 95 % CI ( 0.82, 1.22) ( 0.83, 1.22) ( 0.40, 0.82) ( 0.43, 0.82) Quality of life  SF-1 (15/30/80/90/95; poor to excellent) Estimate 0.21 -0.05 -0.37 -0.66 95 % CI ( -0.74, 1.16) ( -0.93, 0.83) ( -1.33, 0.58) ( -1.52, 0.21)  EuroQol EQ5D-3 L, utility score (0-1) Estimate 0.00 0.00 0.00 0.00 95 % CI ( -0.01, 0.01) ( -0.01, 0.00) ( -0.01, 0.01) ( -0.01, 0.01)  EuroQol visual analog scale (0-100) Estimate -0.44 -0.59 -0.42 -0.47 95 % CI ( -1.13, 0.26) ( -1.23, 0.05) ( -1.18, 0.33) ( -1.18, 0.24)  OP knowledge scale score (0-10) Estimate 0.01 0.01 0.04 0.03 95 % CI ( -0.07, 0.1) ( -0.06, 0.08) ( -0.03, 0.12) ( -0.04, 0.09) *p < 0.0005 aThese are models on outcomes at 12-weeks and 52-weeks without adjustment for baseline values Additionally, we repeated the analyses at the item level. In the pooled unadjusted and adjusted analyses at both 12- and 52–weeks, the intervention group reported significantly (p ≤ 0.002) higher satisfaction for each of the five satisfaction items (data not shown). When stratified by prior DXA use, the unadjusted results were significant (p ≤ 0.03) for each of the five satisfaction items with one exception (data not shown); at 52-weeks among prior DXA users the intervention did not have a significant effect (p = 0.14) on the item related to their overall-satisfaction with bone-health care. Quality of life Intervention and control participants had similar mean scores on all three QOL measures at baseline (SF-1, p = 0.925; EQ-5D-3 L, p = 0.676; and, EuroQol VAS, p = 0.590; Table 2). Mean scores for all three QOL measures did not differ between groups at either 12- or 52-weeks (Table 2). The changes from baseline to the two follow-ups are not significant for all three QOL measures (data not shown). No significant differences were observed in the random effects models, either, for any of the three QOL measures (Table 3). Similarly, no significant differences were observed for MID improvements for any of the three QOL measures. In additional analyses at the item level, no significant (p > 0.05) effects of the intervention were observed for any of the QOL items (data not shown). OP Knowledge The intervention and usual care groups had the same mean scores for OP knowledge (7.5, SD 1.9; Table 2). OP knowledge increased significantly by 0.3 points for both the intervention and usual care groups between baseline and the 12- and 52-week follow-ups (p < 0.001), but there was no difference in the amount of the increase between the two groups (p =0.759 at 12-weeks and p = 0.479 at 52-weeks; Table 2). Adjustment for patient clustering within provider, and for the covariates did not alter these findings (Table 3). In additional analyses at the item level, no significant (p > 0.05) effects of the intervention were observed for any of the OP knowledge items (data not shown). Discussion There is growing interest in engaging patients in their own healthcare [35, 36]. Tailoring health communication to be more patient-centered is becoming more common. Yet, it is unclear whether greater access to tailored, DXA testing communication results in any measurable improvements in patient reported outcomes. We designed a, pragmatic, multi-site, RCT to evaluate the effects of a tailored DXA result letter accompanied by a bone-health educational brochure on patient satisfaction with OP care, QOL, and OP knowledge. Our results revealed significantly improved patient satisfaction with OP care in the intervention group compared to the usual care group. Intervention patients had 58 % greater odds of improving by at least an MID (0.5 SD) at 12-weeks (p < 0.0005) and 34 % greater odds off improving by at least an MID at 52-weeks (p < 0.005). However, we found no differences in terms of QOL or OP knowledge between the intervention and usual care groups. These findings are important because, to our knowledge, this is the first positive study to include a comparison group, and to include patients with and without OP. Patient satisfaction is recognized as an important dimension of healthcare quality. Medicare now evaluates patient satisfaction [37] which will soon be used in determining preventive service reimbursements for doctors and hospitals. The intervention materials were pilot tested to ensure comprehension as well as patient preferences for information and design [27, 28]. Tailoring test result communications to patients may improve their satisfaction with other types of testing as well. As important as the effect on satisfaction with OP care is, failure to improve QOL or OP knowledge in our study also must be considered. We did hypothesize that the patient-activation intervention would not affect overall QOL because OP care is a small component of the healthcare received by older adults who may have several comorbidities. Indeed, OP would likely have minimal effects on QOL in the short-term until a fracture occurs, at which point profound effects on QOL. Thus, our results are consistent with prior studies of OP patient education interventions on QOL [11, 38], in which only one reported a significant improvement among Malaysian women taking bisphosphonates [16]. Moreover, trials of OP therapies, which demonstrate reduced fracture rates, seldom are powered to detect an effect on QOL for some of the reasons noted. The absence of an effect of the patient-activation intervention on OP knowledge is surprising and contrary to our expectations. Prior OP-education interventions have reported significant improvements in knowledge [7–16]. In contrast, we found that OP knowledge significantly increased in both intervention and usual care groups, but that the magnitude of these improvements was the same. This may be due to the measure of OP knowledge. First, the reliability of the OP knowledge measure was only marginally acceptable (α = 0.68) [39]. Second, this was the first RCT to use the “Osteoporosis and You” measure, and the two prior observational studies assessing its psychometric properties included younger women and not men [5, 32]. Third, significant practice effects (about half of an additional correct answer) were observed and these may have created a ceiling effect that constrained our ability to detect short-term differences. Finally, the null effect may be due to the fact that neither the patient-activation letter nor the educational brochure were targeted to the “Osteoporosis and You” measure, although an ad hoc analysis of the four items most closely reflecting the intervention did not reveal an effect either (data not shown). Although several other measures of OP knowledge were available when our study began, we eliminated them because they were too long and cumbersome [40, 41] or were designed for younger women who did not have OP [42]. Improved measures of OP knowledge are needed, particularly among those known to have OP. Despite its strengths, our RCT had limitations. First, the patient satisfaction with OP health care scale had not been used in RCTs designed to improve bone health. Second, we did not use an OP-specific QOL measure, which might have been more responsive to our patient-activation intervention. Lastly, given the clinical centers used, our study population may not have been representative of all osteoporosis patients. Conclusion In conclusion, because of increases in the number and percentage of older Americans at risk for OP and hip fractures, there is a growing need for better OP health care and patient knowledge about the prevention, treatment, and consequences of this disease that remains silent until fracture. We developed a pragmatic and tailored patient-activation intervention that improved OP care satisfaction. Future research and quality improvement projects should examine whether patient satisfaction scores in other clinical domains or in general would increase when providing patients with their test results in a tailored manner. Abbreviations BMDBone mineral density CAIComputer assisted interviewing DXADual energy x-ray absorptiometry HTEHeterogeneity of treatment ITTIntention-to-treat KPGAKaiser permanente of Georgia OPOsteoporosis PAADRNPatient activation after DXA result notification QOLQuality of life RAsResearch assistants RCTRandomized controlled trial SAStrongly agree SDStandard deviation SDStrongly disagree UABUniversity of Alabama at Birmingham UIUniversity of Iowa VASEuroQol visual analog scale Acknowledgements We thank Sylvie Hall, BA (UI), Rebecca Burmeister, MPH (UI), Mollie Giller, MPH (UI), April Miller RT (UI), CBDT, Amna Rizvi-Toner, BA, BS (UI), Brandon Van Cleave (UI), Kara Wessels, BA (UI), Roslin Nelson (KPGA), Kathy Pines (KPGA), Aimee Khamar (KPGA), and Brandi Robinson, MPH (KPGA), and all of the staff at the Iowa Social Science Research Center for recruiting and interviewing all study participants. All except Ms. Miller were compensated from grant funds for their time. We also thank Sylvie Hall, BA (MPH), Mollie Giller, MPH (UI), Ryan Outman, MS (UAB), Marina Reynolds, BSN (UI), Brandi Robinson, MPH (KPGA), and Jessica Williams, PhD (UAB) for coordinating and facilitating recruitment of study participants. We also thank Xin Lu, MS, and Thuy Nguyen, MS (UI) for managing trial data. Finally, we thank the 7,749 patients who participated in PAADRN. Jeffrey R. Curtis, MD, MPH, Sarah L. Morgan, RD, MD, CCD, FACP, Janet A. Schlechte, MD, PhD, David J. Zelman, MD Funding This work was supported by R01 AG033035 (Cram/Wolinsky) from the NIA at NIH. Dr. Cram is supported by a K24 AR062133 award from NIAMS at the NIH. Dr. Saag is supported by a K24 AR052361 award from the NIAMS at the NIH. The NIA had no role in the design and conduct of the study; collection, management, analysis, and interpretation of data; preparation, review, or approval of the manuscript; or, decision to submit the manuscript for publication. Availability of data and materials Data will be shared at the conclusion of the study funding period (March 2017). Researchers wishing to view this data before that time may email the first author. Authors’ contributions SE served as the project coordinator of the PAADRN study, participated in the design and coordination of the study, oversaw data collection and management, and drafted the manuscript. PC was the co-principal investigator, conceived of the study, led in its design, and helped to draft the manuscript. YL was the lead data analyst and helped to draft the manuscript. MJ participated in the design of the randomization, oversaw the statistical analysis, and helped draft the manuscript. DR was a site principal investigator, participated in its design and coordination and helped to draft the manuscript. KS was a site principal investigator, participated in its design and coordination and helped to draft the manuscript. NW DR was an investigator, participated in its design and coordination and helped to draft the manuscript. FW was a co-principal investigator, led in its design and coordination and drafted the manuscript. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. We have no conflicts of interests to report on this work. KS has received consulting fees from Amgen, Eli Lilly, Merck, and Novartis and grant funding from Amgen, Merck, Novartis, and Eli Lilly unrelated to this work. Consent for publication Not applicable. Ethics and consent to participate The University of Iowa Human Subjects Office, the University of Alabama at Birmingham’s Office of the IRB, and the Kaiser Permanente of Georgia Institutional Review Board approved the study procedures. All participants provided either written (University of Iowa) or verbal (University of Alabama and Kaiser Permanente) consent as required by each site’s IRB. ==== Refs References 1. Wright NC Looker AC Saag KG Curtis JR Delzell ES Randall S Dawson-Hughes B The recent prevalence of osteoporosis and low bone mass in the United States based on bone mineral density at the femoral neck or lumbar spine J Bone Miner Res 2014 29 11 2520 2526 10.1002/jbmr.2269 24771492 2. US Department of Health and Human Services Bone health and osteoporosis: a report of the Surgeon General Office of the Surgeon General 2004 Rockville US Department of Health and Human Services 3. Wolinsky FD Fitzgerald JF Stump TE The effect of hip fracture on mortality, hospitalization, and functional status: a prospective study Am J Public Health 1997 87 3 398 403 10.2105/AJPH.87.3.398 9096540 4. Doheny MO Sedlak CA Estok PJ Zeller R Osteoporosis knowledge, health beliefs, and DXA T-scores in men and women 50 years of age and older Orthop Nurs 2007 26 4 243 250 10.1097/01.NOR.0000284654.68215.de 17882102 5. Cadarette SM Gignac MA Beaton DE Jaglal SB Hawker GA Psychometric properties of the “Osteoporosis and You” questionnaire: osteoporosis knowledge deficits among older community-dwelling women Osteoporos Int 2007 18 7 981 989 10.1007/s00198-007-0326-z 17333452 6. Bandura A Social foundations of thought and action 1986 Englewood Cliffs, NJ Prentice-Hall 7. Babatunde OT Himburg SP Newman FL Campa A Dixon Z Theory-driven intervention improves calcium intake, osteoporosis knowledge, and self-efficacy in community-dwelling older Black adults J Nutr Educ Behav 2011 43 6 434 440 10.1016/j.jneb.2010.07.004 21531178 8. Schulman JE Williams S Khera O Sahba T Michelson J Fine K Effective osteoporosis education in the outpatient orthopaedic setting J Bone Joint Surg Am 2007 89 2 301 306 10.2106/JBJS.F.00491 17272444 9. Kulp JL Rane S Bachmann G Impact of preventive osteoporosis education on patient behavior: immediate and 3-month follow-up Menopause (New York, NY) 2004 11 1 116 119 10.1097/01.GME.0000079221.19081.11 10. Qi BB Resnick B Smeltzer SC Bausell B Self-efficacy program to prevent osteoporosis among Chinese immigrants: a randomized controlled trial Nurs Res 2011 60 6 393 404 10.1097/NNR.0b013e3182337dc3 22048557 11. Majumdar SR McAlister FA Johnson JA Weir DL Bellerose D Hanley DA Russell AS Rowe BH Critical impact of patient knowledge and bone density testing on starting osteoporosis treatment after fragility fracture: secondary analyses from two controlled trials Osteoporos Int 2014 25 9 2173 2179 10.1007/s00198-014-2728-z 24803330 12. Oh EG Yoo JY Lee JE Hyun SS Ko IS Chu SH Effects of a three-month therapeutic lifestyle modification program to improve bone health in postmenopausal Korean women in a rural community: a randomized controlled trial Res Nurs Health 2014 37 4 292 301 10.1002/nur.21608 24976566 13. Wu F Laslett LL Wills K Oldenburg B Jones G Winzenberg T Effects of individualized bone density feedback and educational interventions on osteoporosis knowledge and self-efficacy: a 12-years prospective study J Clin Densitom 2014 17 4 466 472 10.1016/j.jocd.2014.07.008 25220886 14. Montori VM Shah ND Pencille LJ Branda ME Van Houten HK Swiglo BA Kesman RL Tulledge-Scheitel SM Jaeger TM Johnson RE Use of a decision aid to improve treatment decisions in osteoporosis: the osteoporosis choice randomized trial Am J Med 2011 124 6 549 556 10.1016/j.amjmed.2011.01.013 21605732 15. Francis KL Matthews BL Van Mechelen W Bennell KL Osborne RH Effectiveness of a community-based osteoporosis education and self-management course: a wait list controlled trial Osteoporos Int 2009 20 9 1563 1570 10.1007/s00198-009-0834-0 19194641 16. Lai PS Chua SS Chan SP Impact of pharmaceutical care on knowledge, quality of life and satisfaction of postmenopausal women with osteoporosis Int J Clin Pharm 2013 35 4 629 637 10.1007/s11096-013-9784-x 23677816 17. Cram P Rosenthal GE Ohsfeldt R Wallace RB Schlechte J Schiff GD Failure to recognize and act on abnormal test results: the case of screening bone densitometry Jt Comm J Qual Patient Saf 2005 31 2 90 97 15791768 18. Shibli-Rahhal A Vaughan-Sarrazin MS Richardson K Cram P Testing and treatment for osteoporosis following hip fracture in an integrated U.S. healthcare delivery system Osteoporos Int 2011 22 12 2973 2980 10.1007/s00198-011-1536-y 21271339 19. Waalen J Bruning AL Peters MJ Blau EM A telephone-based intervention for increasing the use of osteoporosis medication: a randomized controlled trial Am J Manag Care 2009 15 8 e60 e70 19659407 20. Cram P Schlechte J Christensen A A randomized trial to assess the impact of direct reporting of DXA scan results to patients on quality of osteoporosis care J Clin Densitom 2006 9 4 393 398 10.1016/j.jocd.2006.09.002 17097523 21. Noar SM Benac CN Harris MS Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions Psychol Bull 2007 133 4 673 693 10.1037/0033-2909.133.4.673 17592961 22. Ryan P Lauver DR The efficacy of tailored interventions J Nurs Scholarsh 2002 34 4 331 337 10.1111/j.1547-5069.2002.00331.x 12501736 23. Cram P Schlechte J Rosenthal GE Christensen AJ Patient preference for being informed of their DXA scan results J Clin Densitom 2004 7 3 275 280 10.1385/JCD:7:3:275 15319497 24. Edmonds SW Wolinsky FD Christensen AJ Lu X Jones MP Roblin DW Saag KG Cram P The PAADRN Study: A design for a randomized controlled practical clinical trial to improve bone health Contemp Clin Trials 2013 34 1 90 100 10.1016/j.cct.2012.10.002 23085132 25. R Core Team A language and environment for statistical computing R Foundation for Statistical Computing 2015 Vienna R Development Core Team 26. Harris PA Taylor R Thielke R Payne J Gonzalez N Conde JG Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support J Biomed Inform 2009 42 2 377 381 10.1016/j.jbi.2008.08.010 18929686 27. Edmonds SW Solimeo SL Lu X Roblin DW Saag KG Cram P Developing a bone mineral density test result letter to send to patients: a mixed-methods study Patient Preference Adherence 2014 8 827 841 10.2147/PPA.S60106 24940049 28. Edmonds SW Cram P Lu X Roblin DW Wright NC Saag KG Solimeo SL Improving bone mineral density reporting to patients with an illustration of personal fracture risk BMC Med Inform Decis Mak 2014 14 101 10.1186/s12911-014-0101-y 25743200 29. Diehr P Patrick DL Spertus J Kiefe CI McDonell M Fihn SD Transforming self-rated health and the SF-36 scales to include death and improve interpretability Med Care 2001 39 7 670 680 10.1097/00005650-200107000-00004 11458132 30. Euroqol Group. EuroQol--a new facility for the measurement of health-related quality of life. Health Policy (Amsterdam, Netherlands). 1990;16(3):199-208. 31. Brooks R EuroQol: the current state of play Health policy (Amsterdam, Netherlands) 1996 37 1 53 72 10.1016/0168-8510(96)00822-6 32. Brenneman SK Blau EM Chen Y Abbott TA Validation of a patient questionnaire, 'Osteoporosis and You', designed to assess osteoporosis-related attitudes, knowledge and behavior J Bone Miner Res 2002 17 Suppl 1 S466 33. Norman GR Sloan JA Wyrwich KW Interpretation of changes in health-related quality of life: the remarkable universality of half a standard deviation Med Care 2003 41 5 582 592 12719681 34. Krantz DS Baum A Wideman M Assessment of Preferences for self-treatment and information in health care J Pers Soc Psychol 1980 39 5 977 990 10.1037/0022-3514.39.5.977 7441487 35. Epstein RM Street RL Jr The values and value of patient-centered care Ann Fam Med 2011 9 2 100 103 10.1370/afm.1239 21403134 36. Hibbard JH Greene J What the evidence shows about patient activation: better health outcomes and care experiences; fewer data on costs Health Aff (Project Hope) 2013 32 2 207 214 10.1377/hlthaff.2012.1061 37. HCAHPS: Patients’ Perspectives of Care Survey [http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-instruments/HospitalQualityInits/HospitalHCAHPS.html]. Accessed 23 July 2015. 38. Yuksel N Majumdar SR Biggs C Tsuyuki RT Community pharmacist-initiated screening program for osteoporosis: randomized controlled trial Osteoporos Int 2010 21 3 391 398 10.1007/s00198-009-0977-z 19499272 39. Nunnally JC Psychometric theory 1978 2 New York, NY McGraw-Hill 40. Kim KK Horan ML Gendler P Osteoporosis Knowledge Test, Osteoporosis Health Belief Scale, and Osteoporosis Self-Efficacy Scale 1991 Allendale, MI Grand Valley State University 41. Pande KC de Takats D Kanis JA Edwards V Slade P McCloskey EV Development of a questionnaire (OPQ) to assess patient's knowledge about osteoporosis Maturitas 2000 37 2 75 81 10.1016/S0378-5122(00)00165-1 11137326 42. Winzenberg TM Oldenburg B Frendin S Jones G The design of a valid and reliable questionnaire to measure osteoporosis knowledge in women: the Osteoporosis Knowledge Assessment Tool (OKAT) BMC Musculoskelet Disord 2003 4 17 10.1186/1471-2474-4-17 12877751

PMC005xxxxxx/PMC5000521.txt

==== Front Front Plant SciFront Plant SciFront. Plant Sci.Frontiers in Plant Science1664-462XFrontiers Media S.A. 10.3389/fpls.2016.01233Plant ScienceOriginal ResearchFine Root Productivity and Turnover of Ectomycorrhizal and Arbuscular Mycorrhizal Tree Species in a Temperate Broad-Leaved Mixed Forest Kubisch Petra Hertel Dietrich Leuschner Christoph *Plant Ecology and Ecosystems Research, Albrecht von Haller Institute for Plant Sciences, University of GöttingenGöttingen, GermanyEdited by: Boris Rewald, University of Natural Resources and Life Sciences Vienna, Austria Reviewed by: Mengxue Xia, University of Idaho, USA; Zeqing Ma, Chinese Academy of Sciences, China *Correspondence: Christoph Leuschner, cleusch@gwdg.deThis article was submitted to Functional Plant Ecology, a section of the journal Frontiers in Plant Science 26 8 2016 2016 7 123313 4 2016 03 8 2016 Copyright © 2016 Kubisch, Hertel and Leuschner.2016Kubisch, Hertel and LeuschnerThis is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Advancing our understanding of tree fine root dynamics is of high importance for tree physiology and forest biogeochemistry. In temperate broad-leaved forests, ectomycorrhizal (EM) and arbuscular mycorrhizal (AM) tree species often are coexisting. It is not known whether EM and AM trees differ systematically in fine root dynamics and belowground resource foraging strategies. We measured fine root productivity (FRP) and fine root turnover (and its inverse, root longevity) of three EM and three AM broad-leaved tree species in a natural cool-temperate mixed forest using ingrowth cores and combined the productivity data with data on root biomass per root orders. FRP and root turnover were related to root morphological traits and aboveground productivity. FRP differed up to twofold among the six coexisting species with larger species differences in lower horizons than in the topsoil. Root turnover varied up to fivefold among the species with lowest values in Acer pseudoplatanus and highest in its congener Acer platanoides. Variation in root turnover was larger within the two groups than between EM and AM species. We conclude that the main determinant of FRP and turnover in this mixed forest is species identity, while the influence of mycorrhiza type seems to be less important. Acer CarpinusFagusFraxinusroot branching orderTiliaDeutsche Forschungsgemeinschaft10.13039/501100001659GRK 1086 ==== Body Introduction Leaves and fine roots are the organs that supply the plant with energy, water and nutrients. Because of their paramount importance for life, trees invest a large part of their annual carbon gain into the formation of new leaves (∼30%) and fine roots (∼20–40% or more, Keyes and Grier, 1981; Vogt et al., 1996; Müller-Haubold et al., 2013). While the annual production of leaf mass and the phenology of leaf formation and abscission are easily measured in temperate deciduous trees, it is much more difficult to investigate the production and turnover of fine roots (conventionally defined as roots <2 mm in diameter). This is due to the inconspicuous life of roots in the soil, but also because fine roots are not shed synchronously as defined entities at the end of their life like leaves. Rather, fine root death occurs gradually in the more distal root segments (Xia et al., 2010) and new first-, second-, and higher-order root segments produced during a subsequent flush of root growth may replace the shed root segments (Fitter, 1996). Thus, the most distal root segments of lowest root order generally are more short-lived than more proximate higher-order segments, and root turnover (and its inverse, root lifespan) varies across the fine root system, in marked contrast to foliage (Withington et al., 2006). Understanding the factors that influence fine root lifespan is important because root growth consumes a substantial amount of the annually produced carbohydrates, thereby lowering timber production (Fogel, 1983; Hertel et al., 2013). Moreover, root litter represents an important, if not the largest, source of carbon in forest soils (Fogel, 1983; Rumpel et al., 2002; Fan and Guo, 2010). Most studies on the fine root dynamics of temperate tree species were conducted with juvenile plants in common garden experiments without interspecific root system interactions (e.g., Withington et al., 2006; McCormack et al., 2014). An alternative approach is the comparison of different forest types (e.g., Guo et al., 2008b; Brunner et al., 2013), where species differences in fine root dynamics may be confounded by different site conditions. A few studies have investigated fine root lifespan and productivity in mature mixed forests (e.g., Tierney and Fahey, 2001; Meinen et al., 2009a,b), but these studies did not attempt to explain species differences in root dynamics. Eissenstat et al. (2015) were the first to relate fine root productivity (FRP) and lifespan in a mixed forest to the root morphologies and foraging strategies of the different co-occurring tree species, comparing six arbuscular mycorrhizal (AM) species of the genera Magnolia, Liriodendron, Juglans, Fraxinus, Acer, and Ulmus. In western Eurasian cool-temperate broad-leaved forests, the majority of tree species are forming ectomycorrhizae (EM) as do, for example, species of the genera Fagus, Quercus, Tilia, Carpinus, and Betula. A few AM species (genera Acer, Fraxinus, Prunus, and Ulmus) co-occur with the dominant EM species in these forests. It is not known whether the two main types of mycorrhizal symbiosis are linked to contrasting fine root traits in terms of root lifespan and growth rate, when the species are co-occurring in the same stand. Different fine root dynamic properties of EM and AM tree species, if existing, could reflect different strategies of belowground resource foraging, given that EM species are thought to be more efficient in terms of nitrogen acquisition and AM species of phosphorus acquisition. Such differences might also explain why EM tree species dominate cool-temperate and boreal forests and AM species are much more abundant in tropical and sub-tropical forests (McGuire et al., 2008; Lang et al., 2011). In this study, we examined the FRP of each three co-occurring EM and AM tree species in a natural temperate broadleaf mixed forest employing a modified ingrowth core technique according to Meinen et al. (2009b) and Hertel et al. (2013) combined with root coring for biomass determination. This allowed calculating fine root turnover in the <2 mm-diameter class and obtaining an estimate of the average lifespan of the root mass in this fraction. The six species (Fraxinus excelsior, Acer pseudoplatanus, Acer platanoides, Carpinus betulus, Tilia cordata, and Fagus sylvatica) are abundant tree species in central European woodlands and highly (or moderately) important for forestry. They differ not only with respect to mycorrhiza type, but also in terms of canopy architecture, shade tolerance, hydraulic architecture, and their role in forest succession (Köcher et al., 2009; Ellenberg and Leuschner, 2010; Legner et al., 2014). Moreover, fine root morphology differs not only between the genera but also between the closely related Acer species (Meinen et al., 2009a; Jacob et al., 2012; Kubisch et al., 2015). The species A. pseudoplatanus, A. platanoides, T. cordata, and F. sylvatica were also studied by Withington et al. (2006) in a common garden experiment, which allows comparison of results, even though tree age, stand density and also methodology (ingrowth core vs. mini-rhizotron approach) differed between the two studies. By investigating the six species’ fine root turnover in the same mixed forest in patches with contrasting species dominance, we were able to compare mature trees under natural growing conditions on similar soil. This study builds on an earlier investigation of fine root morphological traits of these species, which showed that root morphology depended mainly on species identity, while mycorrhiza type was of secondary importance (Kubisch et al., 2015). In the present study, we focus on FRP and root lifespan of the six tree species, testing the hypotheses that (i) coexisting AM and EM tree species differ in fine root turnover and root productivity, reflecting different nutrient acquisition strategies, (ii) FRP increases with decreasing mean fine root diameter of the species (Eissenstat, 1991), and (iii) FRP is higher, and root lifespan shorter, in tree species with higher aboveground productivity. The latter assumption relates to the generally higher nutrient and water demand of fast-growing species, which might be associated with thinner, more short-lived fine roots (Eissenstat et al., 2015). By comparing the two maple species A. pseudoplatanus and A. platanoides, we further tested for congeneric contrasts in fine root dynamics in two closely related tree species. Materials and Methods Study Site and Plot Design The study was conducted in Hainich National Park in Thuringia, central Germany, which protects one of the largest remaining temperate deciduous broadleaf forests in Central Europe (7500 ha). Beside large areas of monospecific European beech (F. sylvatica L.) forest, the park contains forest stands with relatively high tree species richness. During the past 50 years, this forest was exposed to only minor management activities in form of selective logging. With declaration of a national park in 1997, all activities like logging and military training, practiced in certain areas, were abandoned. The study site is located on a Triassic limestone plateau (Muschelkalk formation; 308–399 m a.s.l.; 51°04′ N, 10°30′ E) within the ‘Thiemsburg area’ in the north-east of the national park, where more than six tree species co-occur either in quasi-random mixture or in small groups consisting of 3–6 trees of a species. The species in this study, i.e., European beech (F. sylvatica), Small-leaved lime (T. cordata Mill.), European hornbeam (C. betulus L.), European ash (F. excelsior L.), Sycamore maple (A. pseudoplatanus L.) and Norway maple (A. platanoides L.), were the species with highest abundance in this Stellario-Carpinetum community (oak-hornbeam forest). Three of the six species are ectomycorrhizal (EM; C. betulus, F. sylvatica, and T. cordata), while the other species were found to form only AM in the study site (A. pseudoplatanus, A. platanoides, and F. excelsior); colonization by both AM- and EM-forming fungi as found in some Acer species (e.g., Smith and Read, 2007) was not observed (see also Meinen et al., 2009a,b; Jacob et al., 2010). Mean annual precipitation in the study region is ∼ 590 mm year-1 and mean annual temperature 7.5°C (periods 1973–2004, Deutscher Wetterdienst 2005). In the study years 2012 and 2013, mean annual air temperatures of 9.7°C (2012) and 8.5°C (2013) and precipitation totals of 603 mm (2012) and 598 mm (2013) were recorded at the nearest weather station Weberstedt/Hainich (Deutscher Wetterdienst, 2009). The soil of the study area is a base-rich Eutric Luvisol (FAO taxonomy 2006) with a profile depth of 60–70 cm developed in clay-rich Pleistocene loess that covers the limestone bedrock. Due to high clay content, the soil can dry out strongly in summer, while it may show partly stagnant properties during spring and winter. The plots were established in patches with dominance of each one of the six species which were characterized by similar soil properties. Marginal differences in soil conditions between the plots of the species were primarily caused by the specific litter properties of the species (Rothe and Binkley, 2001; Guckland et al., 2009). For example, the base saturation at the cation exchangers in the topsoil and lower mineral soil was marginally lower under Fagus (78.5%) than under the other species (Kubisch et al., 2015; Table 1). However, none of the measured properties differed significantly between the plots. Table 1 Aboveground structural characteristic of the target trees and of entire study plots; all species in a plot for the six plot types (species); important soil chemical properties of the mineral topsoil (0–10 cm) are also indicated. Variable Species F. excelsior A. pseudoplatanus A. platanoides C. betulus T. cordata F. sylvatica Target species Tree height (m) 32.3 ± 1.5 28.6 ± 0.9 23.8 ± 2.0 22.8 ± 1.1 24.2 ± 1.40 26.4 ± 0.7 AWB (Mg ha-1) 313.2 ± 47.1 182.8 ± 30.7 136.1 ± 21.8 168.7 ± 34.6 169.1 ± 24.9 207.0 ± 24.2 AWB (Mg Ind. tree-1) 1.9 ± 0.3 1.8 ± 0.1 1.4 ± 0.2 1.1 ± 0.2 0.8 ± 0.1 1.2 ± 0.1 Dbh (cm) 52.2 ± 3.5 58.1 ± 3.2 51.2 ± 3.6 43.4 ± 3.3 46.4 ± 2.3 43.5 ± 2.2 BA (m2 ha-1) 47.82 ± 4.69 27 ± 4.01 22.07 ± 3.24 26.29 ± 5.16 43.60 ± 6.12 52.32 ± 5.04 All species per plot Total BA (m2 ha-1) 57.1 ± 5.4 47.8 ± 8.8 28.7 ± 2.5 31.6 ± 6.6 50.9 ± 6.0 60.3 ± 7.8 Proportion of target species (%)1 83.6 ± 3.5 62.7 ± 7.2 77.4 ± 9.9 86.1 ± 8.0 84.8 ± 4.0 90.4 ± 5.7 Stem density (no. trees ha-1) 409 ± 71 376 ± 64 232 ± 23 232 ± 41 365 ± 35 696 ± 98 Soil chemical properties (0–10 cm) C/N g g-1 11.9 ± 0.2 11.6 ± 0.4 12.0 ± 0.4 12.5 ± 0.2 12.0 ± 0.3 12.6 ± 0.3 CEC (μmolc/g dry soil) 213.5 ± 75.5 195.8 ± 69.2 206.5 ± 73.0 178.5 ± 63.1 192.2 ± 67.9 139.2 ± 49.2 Base saturation (%) 91.2 ± 5.8 88.8 ± 4.8 87.3 ± 5.4 88.0 ± 6.8 93.4 ± 4.2 78.5 ± 8.2 pH (H2O/KCl) 5.29/4.19 5.07/4.10 5.20/4.11 5.29/4.15 5.41/4.31 5.02/3.94 Given are mean ± SE for n = 8 plots. Aboveground woody biomass (AWB) is given for spring 2012. BA, basal area of the target species; CEC, cation exchange capacity (data taken from Kubisch et al., 2015; see Materials and Methods, contact this source). 1% of BA.Circular plots (diameter 12 m; area 113 m2) containing mature trees of one of the six target species (‘tree clusters’) were randomly selected in the area. For our analysis, two neighboring trees of the target species with dominant position in the upper canopy layer, or one dominant tree of the respective species, were chosen; they formed the center of the plots. The selected trees had diameters at breast height (dbh) of 40–60 cm (Table 1). This plot scheme was chosen to minimize possible species effects on soil chemistry in the mixed forest, which would have been more pronounced in larger monospecific stands. The scheme ensures that the bulk of fine roots in the soil belonged to the target species (typically >80%). We sampled eight plots per species resulting in 48 plots in total. All stems >10 cm dbh in a ‘tree cluster’ were investigated for their species identity, dbh, basal area and tree height (Table 1). Fine Root Productivity and Root Dynamics For quantifying FRP (in g m-2 year-1), we applied a modified ingrowth core approach. To achieve more natural root growth conditions in the cores, we modified the conventional ingrowth core technique (Persson, 1980; Powell and Day, 1991; Majdi, 1996) and refrained from enclosing the core in a net in order to minimize soil disturbance. Compared to other techniques, the ingrowth core method has been found to produce rather conservative figures of FRP in temperate forests (e.g., Hertel and Leuschner, 2002; Hendricks et al., 2006). The ingrowth cores were installed in June 2011 immediately after an inventory of standing fine root biomass (FRB; diameter <2 mm) which was conducted in the same 48 plots by coring the topsoil to 30 cm depth at 150 cm distance to the stem of the central tree in the plot using a steel corer of 35 mm diameter (Kubisch et al., 2015). The sampling holes were refilled with root-free soil from a nearby place (distance ca. 30–50 cm) and used as ingrowth cores for a period of 2 years. Each refilled coring site was precisely marked with three plastic sticks inserted down to 30 cm soil depth which allowed a resampling of the core at exactly the same place after 24 months. Earlier investigations at the same forest sites had shown that re-colonization of the cores by fine roots started typically 12 months after their installation (Meinen et al., 2009b). We thus assumed that fine root growth in the cores took place from May 2012 to May 2013, i.e., over 365 days, while the period of core exposure lasted from July 1, 2011 to May 16, 2013. The cores were resampled on May 16, 2013 in the same manner as done in the initial biomass inventory in 2011 (Kubisch et al., 2015). Upon harvest, the extracted soil cores were divided into the 0–10, 10–20, and 20–30 cm soil layers and stored in plastic bags at 4°C. The root samples were subsequently analyzed in the lab within 3 months by carefully rinsing the soil cores with tap water over a sieve of 0.25 mm mesh size and extracting all fine root branches >10 mm length. Assignment of root mass to tree species was done with a morphological key that has been developed earlier in this stand using periderm properties such as color and surface structure, the mode of root branching, and mycorrhiza type as criteria (Hölscher et al., 2002; Meinen et al., 2009a; Kubisch et al., 2015). Properties like elasticity of the stele, and the cohesion of periderm and stele were used for distinguishing live from dead root mass (Persson, 1978; Hertel and Leuschner, 2002). The turnover of fine root mass (unit: year-1; i.e., the inverse of root longevity) was calculated by dividing annual FRP by standing FRB (inventory data). Turnover data are bulk values for the entire fine root biomass <2 mm in diameter, thus averaging root lifespan over all root orders. At the date of harvest, no fine root necromass was observed in the ingrowth cores and this component was thus not considered in the analysis of FRP and turnover. All extracted live fine roots from the ingrowth cores were scanned and analyzed for their specific surface area (SRA, in cm2 g-1), specific length (SRL, in m g-1), and tissue density (RTD, in g cm-3) using a flat-bed scanner and WinRhizo software (Régent Instruments, Inc., Québec City, QC, Canada). The annual production of fine root length (m per m2 ground area and year) and fine root surface area (m2 m-2 year-1) was calculated using the measured morphological characteristics of the fine roots collected in the ingrowth cores. To obtain a rough estimate of the fine root biomass produced annually in the different root orders, we used the percent distribution of fine root biomass to the root orders #1 to #4 which was determined in a detailed root order analysis of the standing FRB inventory done by Pregitzer et al. (2002), Kubisch et al. (2015). This analysis was conducted in a representative sub-sample of the FRB material of every soil sample and soil depth (>10 mm length) which had been subjected to a fractionation into root orders. The individual segments of a root branch were assigned to the first four branching orders according to the ordering system proposed by Fitter (1987) and Pregitzer et al. (2002) and dissected into the orders using a razorblade. For all species except F. excelsior, the root tip(s) was counted together with the adjacent root segment as first-order segment, as it was often not possible to clearly recognize the transition between tip and subsequent root segment. The separation was especially problematic in case of the EM tree species which often formed coralloid cluster-like structures that could not be split into first and second order segments (Valtanen et al., 2014). In contrast, in F. excelsior with AM, the individual tips were clearly recognizable and hence were counted as first root order. Root segments of the fifth or higher orders contributed with less than 5% to the fine root biomass <2 mm and were lacking in various samples; they were not considered in the subsequent analysis. The proportion of the first to fourth root orders in the total fine root mass of a root branch was detected and the ratios were applied to estimate the production of root mass in the four orders in the ingrowth cores. This extrapolation can give only a very rough number as it is based on the assumption that fine roots growing into the ingrowth cores do not differ in their branching structure from the fine roots collected in the inventory (Figure 1), and root longevity is similar in the root orders. The latter assumption is probably not valid (McCormack et al., 2015) suggesting that our calculation can only indicate the magnitude of root biomass produced in the different orders. We thus use these data only as an estimate of the production of absorptive roots (first- and second-order roots) per ground area of the six species. FIGURE 1 Photographs of typical terminal fine root branches of the six species (A–F) as collected in soil cores of the inventory (respective left columns, marked with capital letters) or in the ingrowth cores (respective right columns, marked with small letters). Images were taken with WinRhizo software. After the detailed analysis, all extracted fine root material was dried at 70°C for 48 h until constant weight. The carbon and nitrogen concentrations were analyzed by gas chromatography (vario EL, elementar, Hanau, Germany) in the ground root material of the initial FRB inventory. Aboveground Woody Biomass Production The annual production of above-ground woody biomass (ABWP in Mg ha-1 year-1; including stem and larger branches) was calculated from stem increment data obtained for every target tree using permanently installed dendrometer tapes (UMS, München, Germany) mounted at 1.50 m stem height. The height of the target trees was measured at the beginning of the study using a Vertex IV ultrasonic height meter (Haglöf, Langsele, Sweden). To calculate the total aboveground woody biomass (AWB) of the trees, we used the following allometric equations given for the respective species in Zianis et al. (2005): F. sylvatica and C. betulus: A⁢W⁢B=0.04736⋅d⁢b⁢h1.80521⋅h0.99603⁢                          (1) T. cordata: I⁢n⁢(A⁢W⁢B)=−2.6788+2.4542⋅I⁢n⁢(d⁢b⁢h)⁢                           (2) A. pseudoplatanus and A. platanoides: I⁢n⁢(A⁢W⁢B)=−2.7606+2.5189⋅I⁢n⁢(d⁢b⁢h)⁢                           (3) F. excelsior: I⁢n⁢(A⁢W⁢B)=−2.4598+2.4882⋅I⁢n⁢(d⁢b⁢h),                           (4) with AWB being total aboveground woody biomass including branches (in kg per tree), dbh diameter at breast height (in cm), and h tree height (in m). For C. betulus, no specific allometric equation was found in the literature. We thus used the equation for F. sylvatica as an approximation. For A. platanoides, we used the same equation as for A. pseudoplatanus because specific equations seem to lack for this species as well. We assumed that height growth during the relatively short (1 year) measuring period was negligible and excluded it from the calculations. Annual woody biomass production (ABWP) of the target trees in the plots was then calculated as the change in aboveground woody biomass of each tree from spring 2012 to spring 2013. Statistical Analyses All data sets were tested for normal distribution using a Shapiro–Wilk test. As normal distribution was often not given and the data sets could not sufficiently be transformed, non-parametric statistics were applied in these cases. For most variables, a Kruskal–Wallis H-test followed by a Mann–Whitney U-test for pairwise comparison between the species was conducted (p < 0.05). The relationship between ABWP, or root morphological traits, and the FRP or root turnover of the six species was explored with Spearman rank correlation analysis. ANCOVA was employed to separate between effects of mycorrhiza type and effects of various root morphological traits on fine root turnover. These tests were conducted with SAS 9.3 software. In order to analyze the inter-relationships between fine root biomass, root morphological properties, FRP, root turnover, and aboveground tree structure, biomass and wood production, we conducted a principal components analysis (PCA) using the package CANOCO, version 4.5 (Biometris, Wageningen, The Netherlands). Results Fine Root Productivity and Turnover Fine root biomass per ground area (0–30 cm profile) ranged between 140 and 300 g m-2 among the six tree species in the plots with dominance of the respective species (Supplementary Table SI1). As for biomass, annual FRP in the soil profile varied by a factor up to two among the species. Highest productivity was measured for C. betulus, F. sylvatica, and F. excelsior (∼150–170 g m-2 year-1), intermediate values for A. platanoides and T. cordata, and lowest for A. pseudoplatanus (∼80 g m-2 year-1, Figure 2). Interestingly, the six species differed not significantly in FRP in the uppermost soil layer (0–10 cm), while marked differences existed in the two deeper soil layers. Particularly high productivity was measured in the 20–30 and 10–20 cm layers for F. sylvatica, while A. pseudoplatanus reached only low values in these depths (Figure 2). When FRP was related to aboveground woody biomass production [ABWP, measured as kg biomass increment per target tree(s) per m2], C. betulus and A. pseudoplatanus reached highest ratios (>1), T. cordata, A. platanoides, and F. sylvatica intermediate ratios (0.6–0.8), and F. excelsior a very low ratio (<0.2; Figure 3). FIGURE 2 Fine root productivity (FRP) of the six tree species in the three soil depths according to the ingrowth core study (mean ± SE; n = 8 plots). Different capital letters indicate significant differences (p < 0.05) between the species in the soil profile (0–30 cm); significant differences between the soil depths for a given species are indicated by different lower case Latin letters, differences between tree species within a given soil depth by lower case Greek letters. FIGURE 3 Ratio of annual belowground (fine root) to aboveground (woody biomass) production in the six species. FRP was expressed per m2 ground area; woody biomass production is the growth of the target trees. Statistically significant differences between the species are indicated by different letters. Fine root turnover (productivity per standing biomass) in the 0–30 cm profile was highest in A. platanoides and lowest in A. pseudoplatanus (difference significant; Figure 4). However, the variation in turnover values within a species was generally large (ranging from 0.1 or 0.2 to 2.0 year-1 or higher). Consequently, in most cases, species differences in root turnover were not significant. Moreover, there was no uniform trend of fine root turnover change with soil depth across the six species (Table 2). C. betulus and T. cordata showed a decrease in turnover with depth, while F. sylvatica, F. excelsior and the two Acer species had the highest fine root turnover in the deepest (20–30 cm) layer (Table 2). However, the variation in turnover figures within a species and soil depth was also large. Neither fine root turnover nor FRP differed significantly between the EM and AM species groups (Table 3). Analysis of covariance with mycorrhiza type as independent and fine root turnover as dependent variable revealed that among several root morphological traits introduced as covariates, only SRL had a significant influence (p = 0.008; results not shown). FIGURE 4 Median fine root turnover (year-1) of the six tree species according to ingrowth core data for the 0–30 cm profile. Given are the median, the 25- and 75- percentiles and the minima and maxima. Significant differences (p < 0.05) between the species are indicated by different letters. Table 2 Median of fine root turnover (year-1) of the six species in the three different soil depths. Soil depth 0–10 cm 10–20 cm 20–30 cm Fraxinus excelsior 0.42 aAB 0.16 aAB 0.44 aA Acer pseudoplatanus 0.22 aA 0.21 aAB 0.44 aA Acer platanoides 1.14 aB 1.18 aA 1.60 aB Carpinus betulus 0.70 aAB 0.60 aAB 0.22 aA Tilia cordata 0.50 aAB 0.17 aAB 0.36 aA Fagus sylvatica 0.42 aAB 0.33 aB 0.70 aAB Significant differences (pairwise comparison; Mann–Whitney U-test; p < 0.05) between the soil depths for a species are marked with different lower case letters, those for two species at a given soil depth are marked with different capital letters.Table 3 Comparison between the EM and AM tree species in terms of fine root turnover and fine root productivity (FRP). Mycorrhiza type No. of species Turnover (year-1) FRP (g m-2 year-1) AM 3 0.72 ± 0.22 121.51 ± 20.07 EM 3 0.60 ± 0.07 146.49 ± 18.15 Given are the group mean ± SE, based on the species’ median turnover and mean FRP. Both differences were not significant at p < 0.05 according to a Mann–Whitney U-test.Annual Production of Fine Root Length and Surface Area Fine root length growth in the 0–30 cm soil profile ranged from 1359 m m-2 year-1 in T. cordata to 3303 m m-2 year-1 in F. excelsior (difference significant between the low values in T. cordata and A. pseudoplatanus, and the high values in F. excelsior and C. betulus). Most species had the highest fine root elongation rate in the upper 10 cm and a decrease to lower layers (Table 4). However, T. cordata and A. platanoides had the highest fine root length production in 10–20 cm depth and F. sylvatica showed a significant increase in fine root length production from 0–10 to 20–30 cm depth (Table 4). As expected, annual fine root surface area production revealed a similar pattern as length production; F. excelsior produced the largest root surface area per year (4.1 m2 m-2 year-1), T. cordata the lowest (1.7 m2 m-2 year-1). Fine root biomass production was positively related to root length growth in A. pseudoplatanus, F. excelsior, A. platanoides and T. cordata as expected, while this relation was not significant in C. betulus and F. sylvatica (data not shown). Table 4 Annual fine root length and surface area production (SA) per square meter ground area in 0–10 cm, 10–20 cm, 20–30 cm soil depth and for the profile (0–30 cm). Species Depth (cm) Length (m m-2 year-1) SA (cm2 m-2 year-1) Fraxinus excelsior 0–10 1455 ± 479aA 17504 ± 5604aA 10–20 1210 ± 231aA 14984 ± 2976aA 20–30 638 ± 202bABC 8660 ± 2350bABC Profile 3303 ± 639 A 41148 ± 7345 A Acer pseudoplatanus 0–10 903 ± 269aA 11617 ± 4004aAB 10–20 340 ± 73aBC 3473 ± 945aB 20–30 333 ± 72aABC 4376 ± 978aABC Profile 1576 ± 300 B 19465 ± 4759 B Acer platanoides 0–10 907 ± 248aA 11030 ± 3140aAB 10–20 933 ± 209aABC 10644 ± 2504aAB 20–30 695 ± 188aAC 7584 ± 1927aAC Profile 2535 ± 343 AB 29259 ± 4235 AB Carpinus betulus 0–10 1519 ± 567abA 13877 ± 4402aAB 10–20 1089 ± 268aAC 10213 ± 2191aA 20–30 553 ± 171bAB 5528 ± 2093bAB Profile 3161 ± 796 A 29618 ± 6408 AB Tilia cordata 0–10 545 ± 179aA 6524 ± 2263aB 10–20 615 ± 214aC 7665 ± 2666aAB 20–30 275 ± 102aB 3918 ± 1331aA Profile 1359 ± 395 B 17149 ± 5376 B Fagus sylvatica 0–10 560 ± 186aA 8036 ± 2109aAB 10–20 808 ± 216abABC 10074 ± 2622abABC 20–30 1095 ± 202bC 13589 ± 3052aC Profile 2462 ± 417 AB 31699 ± 5106 B Given are mean ± SE for eight plots. Statistically significant differences between the soil depths are indicated by different lower case letters, significant differences between the species in a soil depth by different capital letters; differences between the species in the 0–30 cm profile are indicated by bold capital letters (Mann–Whitney U-test; p < 0.05).Fine Root Dynamics in Relation to Root Properties and Aboveground Productivity To explore relationships between fine root morphology, FRP, and aboveground structure and productivity (ABWP) among the six tree species, a PCA with four axes was conducted. Fine root biomass production as well as fine root length and surface area growth were positively related to the first axis together with root nitrogen concentration and FRB. Aboveground woody biomass production and tree height were also positively associated with axis 1, while RTD was negatively related to this axis (Table 5). The SRA and SRL values of the produced fine root biomass in the ingrowth cores correlated closest with axis 2. Fine root turnover was the only variable not being associated with the other variables; it correlated with axis 3 (Table 5). The PCA plot in Figure 5 indicates that the three EM species resemble each other in terms of root morphology and root productivity, while the two Acer species (AM) group separately, and F. excelsior (AM) seems to differ from the other five species in most tested influential parameters. Table 5 Results of a principal components analysis (PCA) regarding the variables fine root biomass of the plots (FRB), root morphological properties, annual FRP and length and surface area production, fine root turnover, and aboveground tree structure, biomass and wood production (ABWP). Variables Axis 1 Axis 2 Axis 3 Axis 4 Eigenvalues 0.4809 0.2134 0.166 0.1023 FRP 0.590 -0.446 0.566 -0.359 Length production 0.771 0.099 0.555 -0.294 Surface area production 0.900 0.091 0.334 -0.121 Fine root turnover 0.398 0.351 0.586 0.585 FRB 0.627 -0.538 -0.344 -0.445 RTD -0.862 -0.233 0.350 -0.006 SRA 0.202 0.936 -0.122 -0.260 SRL -0.469 0.644 -0.111 -0.535 Root N concentration 0.935 0.181 -0.003 -0.011 BA of target species 0.542 -0.614 -0.499 0.108 Tree height 0.645 0.399 -0.607 0.137 ABWP 0.939 0.129 -0.151 0.270 High interrelations are given in bold print.FIGURE 5 Results of a Principal Components Analysis regarding the parameters fine root biomass (FRB), root morphological properties (RTD, SRA, SRL), annual production of fine root biomass (FRP), length (Length) and surface area (SA), root turnover, and tree basal area (BA) and aboveground woody biomass production (ABWP). Shown are the inter-relationships along the first two axes (axis 1 = x axis; axis 2 = y axis). Species: Fex, Fraxinus excelsior; Aps, Acer pseudoplatanus; Apl, Acer platanoides; Cbe, Carpinus betulus; Tco, Tilia cordata; Fsy, Fagus sylvatica. Contrary to expectation, species differences in FRP could not be explained by species differences in root morphological properties such as different mean fine root diameters, SRL, SRA, root tissue densities, or root N contents (Table 6). Neither root N concentration nor root tissue density correlated with FRP in any of the species (except for a negative relation between root N and FRP in A. platanoides). In A. pseudoplatanus, FRP was negatively related to SRA and SRL indicating that A. platanoides produced more fine root biomass, when the newly grown fine root branches were shorter and thicker. Similarly, species differences in root turnover could be explained neither by mean fine root diameter nor by other root morphological traits (Supplementary Table SI2). Table 6 Spearman rank correlation coefficients (rs) for the relationship between aboveground productivity and morphological properties with FRP for the pooled data set (all six species) based on species means; ABWP, aboveground woody biomass production; SRL, specific root length; SRA, specific root area; RTD, root tissue density; MD, mean diameter; root N, fine root nitrogen concentration. rs p ABWP 0.371 0.469 SRL -0.257 0.623 SRA -0.314 0.544 RTD -0.371 0.469 MD -0.143 0.787 Root N 0.600 0.208 None of the relationships were significant at p < 0.05.Aboveground productivity (ABWP) was not related to FRP in the 0–30 cm profile, neither in the sample of all species (Table 6) nor in separate correlation analyses at the species level, except for C. betulus (Table 7). Relating ABWP to root traits across the six species revealed a significant negative relation to root tissue density; this relation disappeared, when F. excelsior with particularly thick and N-rich fine roots was excluded (data not shown). The species means of ABWP were not related to the species SRL, SRA, or root N concentration means (Supplementary Table SI3). When this analysis was conducted at the species level, none of the ABWP – root trait relations were significant at p < 0.05 (in F. sylvatica, a marginally significant relation at 0.05 < p < 0.1 between ABWP and root N appeared; Supplementary Table SI4). Table 7 Spearman rank correlation coefficients (rs) for the relationship between aboveground productivity and morphological properties with FRP conducted separately for the six species. Species Fraxinus excelsior Acer pseudoplatanus Acer platanoides Carpinus betulus Tilia cordata Fagus sylvatica ABWP 0.024 0.190 -0.476 0.881∗ 0.429 -0.262 SRL -0.167 -0.929∗ -0.190 -0.143 -0.595 -0.524 SRA -0.286 -0.810∗ -0.238 -0.071 -0.524 -0.524 RTD 0.571 0.333 0.048 0.238 -0.238 0.429 MD -0.429 0.738∗ 0.048 0.119 0.524 0.167 Root N 0.429 0.143 -0.491 -0.381 -0.167 -0.357 Significant correlations at p < 0.05 are marked with an asterisk. ABWP, aboveground woody biomass production; SRL, specific root length; SRA, specific root area; RTD, root tissue density; root N, fine root N concentration.Discussion Factors Influencing Fine Root Longevity We obtained mean fine root turnover rates between 0.16 and 1.60 year-1 in the six species and three horizons for the bulked fine root biomass <2 mm, equivalent to a mean root lifespan of 0.6 year (A. platanoides) to 6.3 years (F. excelsior); this is a 10-fold difference between the species. The majority of turnover figures, however, ranged between 0.3 and 0.7 year-1 (i.e., lifespans of 1.4–3.3 years). With minirhizotron observation, Withington et al. (2006) found median fine root lifespans between 0.6 and 2.5 years for A. pseudoplatanus, A. platanoides, T. cordata and F. sylvatica, which matches well with our ingrowth core-based estimates, given that Withington et al. (2006) considered only first-order roots, while our data include also the higher root orders with longer life spans in the bulked root mass <2 mm diameter, and Withington et al. (2006) did not investigate F. excelsior. In agreement with Withington et al. (2006), we found a relatively high lifespan in A. pseudoplatanus, while our data indicate a short mean lifespan of A. platanoides roots, in contrast to their results. It has to be kept in mind that the results of minirhizotron and ingrowth core studies on fine root turnover in forests are often poorly comparable (Burke and Raynal, 1994), and turnover rates derived from minirhizotron observation typically are higher than ingrowth core estimates (e.g., Finér et al., 2011). This offers another explanation of the higher lifespan values found in our study compared to the figures of Withington et al. (2006). Further, the trees in the common garden study of Withington et al. (2006) likely were exposed to lower root competition intensity than the trees in the mixed forest of our study, which could also have influenced root longevity. Finally, climatic differences between the studies of Withington et al. (2006) and our study (Poland vs. Germany) could partly explain differences in longevity values (cf. Leppälammi-Kujansuua et al., 2014). Comparing fine root turnover among different species based on the bulked <2 mm fine root biomass instead of focusing on root orders might introduce errors, if the species differ largely in their branching patterns and the functionality of the respective segments is different (McCormack et al., 2015). Earlier root order-based morphological analyses of the six species by Kubisch et al. (2015) showed that the branching patterns of the species were relatively similar despite belonging to different families and mycorrhiza types. For example, the fine root mass <2 mm in diameter of all species consisted to about 95% of the root orders 1–4, while higher order-segments contributed always with less than 5% to fine root biomass. Further, mean diameter, fine root length fraction and root tissue density as important morphological traits influencing nutrient acquisition followed in all species a remarkably similar trend from the first to the fourth order, suggesting that root segments with either absorptive functions or storage and conductance functions occupied rather similar proportions of fine root biomass in these species. McCormack et al. (2015) assume that the fourth root order should in temperate tree species mainly be responsible for nutrient and water transport, while nutrient and water acquisition is located in the first to third root orders. Even though we do not have information on the longevity of individual root segments and orders, we assume that the observed species differences in fine root turnover of the <2 mm-class should not result from different branching patterns and contrasting proportions of first- and second-order segments in the species, but rather reflect species differences in overall fine root longevity, as the species were relatively similar with respect to fine root length fractions. Clearly, a detailed root order-based analysis of root lifespan would give a more reliable picture of species differences in the dynamic properties of the fine root system and of possible contrasts between EM and AM species. We could not detect relationships between root longevity and root morphological and chemical properties in our six-species sample. This is unexpected and does contrast with the findings of McCormack et al. (2012, 2015) who reported a positive relation between root lifespan and fine root diameter, root C/N ratio and root Ca concentration, and a negative one between lifespan and SRL for North-American tree species. However, analysis of covariance showed for our data a positive effect of SRL on fine root turnover, when separated from the influence of mycorrhiza type. This is a hint that thinner roots were shorter lived, even though mean fine root diameter was not an influential factor in our analysis. In a literature review of fine root lifespan in temperate tree species, Guo et al. (2008a) found that lifespan generally increased with root diameter. Similarly, Eissenstat et al. (2015) measured a higher median fine root lifespan in thick-rooted AM tree species. These results refer to the first two root orders. For grasses, Ryser (1996) reported higher root longevity when root tissue density was higher, while a relation to diameter did not appear. These observations indicate that root production is indeed behaving in a manner, which fits to the resource optimization concept proposed by Eissenstat and Yanai (1997). Large-diameter roots require higher investment of carbon and nutrients per unit root length or surface area, which should be coupled with greater root lifespan in order to ensure a favorable nutrient and water return on the amount of carbon and nutrients invested. In our sample, mean fine root diameter differed only moderately among the six species (means of 0.33–0.59 mm) and greater root lifespan was found not only in the species with largest diameters (F. excelsior and T. cordata) but also in A. pseudoplatanus with the thinnest fine roots. Large spatial and also temporal variation in fine root turnover (McCormack et al., 2014) together with only limited species differences in root diameter may explain our failure to detect relationships between fine root morphology and lifespan in this mixed forest. The species sample of Eissenstat et al. (2015) covered a much greater range of root diameters (0.2–1.3 mm) and referred only to AM species. Are Fine Root Productivity and Root Lifespan Different between EM and AM Tree Species? In contradiction to our first hypothesis, the three EM tree species of our sample differed not significantly from the three AM species in terms of FRP and fine root turnover when comparing the group means (see Table 3). The two groups were also similar with respect to the belowground: aboveground production ratio. We had expected that F. excelsior and the two Acer species as AM species would have longer-lived fine roots because fine root longevity has been found to increase with root diameter (McCormack et al., 2012), and F. excelsior had the thickest fine roots of the six species. Further, the minirhizotron data of Withington et al. (2006) indicate that the two Acer species have particularly long fine root lifespans (median lifespan of first and second order roots: 1.5 and 2.6 years in A. pseudoplatanus and A. platanoides, respectively). This result was only in part confirmed by our ingrowth core study which showed a very high longevity of the A. pseudoplatanus roots (means of 2.3–4.8 years for roots <2 mm in diameter), but not of the A. platanoides roots (0.6–0.9 year). In fact, mean fine root diameter was not different between AM and EM species in our sample, and A. pseudoplatanus had particularly thin roots in the first four root orders (Kubisch et al., 2015). The morphological comparison showed that systematic differences between the two mycorrhiza types did only exist with respect to SRA (higher values in AM species), but not for root diameter, RTD, SRL, or root N concentration in our sample. In an analysis of 25 North-American woody species, Comas and Eissenstat (2009) reported for the EM species a higher branching intensity (number of root tips per total root length) than for the AM species; this was not visible in our six-species sample (Kubisch et al., 2015). The long lifespan of the two Acer species observed by Withington et al. (2006) was explained with a very thick exodermis in the fine roots of the two Acer species. Our results with the diverging Acer species suggest that this explanation may not be generally valid. A shortcoming of our approach is that the root morphological and productivity measurements refer to the standard size class of fine roots <2 mm in diameter in all species, thus including a substantial fraction of non-mycorrhizal root mass in the analysis. This could have masked potential effects of mycorrhizal type on root morphology and dynamics. Experimental duration may also have influenced the results. For example, Ostonen et al. (2005) observed different contributions of roots < 1 mm and roots > 1 mm diameter to FRP over the course of a 3 years-long root production study. Despite these possible sources of bias, it appears that the type of mycorrhiza is a less important factor influencing fine root lifespan than other possibly relevant factors. Previous research has shown that plant-internal resource allocation rules (Eissenstat and Duncan, 1992) and external abiotic and biotic factors act as the main determinants of fine root lifespan, among the latter nutrient availability, drought stress, temperature extremes and the activity of root herbivores, pathogens and fungal symbionts (Wells and Eissenstat, 2002; Guo et al., 2008b; Rasmann and Agrawal, 2008; Adams and Eissenstat, 2015). Most of the abiotic factors should have been more or less similar among the study plots of the six species in Hainich forest, while differences in herbivore and pathogen activity may vary with the specific chemical and biological conditions in the rhizosphere of the species (Guckland et al., 2009; Cesarz et al., 2013; Scheibe et al., 2015). Interesting is the direct comparison of fine root dynamics in the two coexisting congeners A. pseudoplatanus and A. platanoides, which may reveal the development of different strategies of belowground resource foraging in closely related tree species. The two congeners showed marked morphological differences (more tips per root mass, a higher fine root surface area and thinner second and fourth order root segments in A. pseudoplatanus than in A. platanoides) and a higher overall fine root biomass in A. pseudoplatanus. Thus, it appears that tree species with similar fine root diameters as in the Hainich mixed forest can achieve elevated resource uptake rates either through maintaining a large surface area of first-order roots (A. pseudoplatanus) or by frequently turning over the existing fine root mass (A. platanoides) which should increase mean root uptake capacity by reducing mean root age (Eissenstat and Yanai, 1997). In our species sample, species differences in root tip frequency (tips per root mass) were the most influential fine root morphological traits (Kubisch et al., 2015). In tree species assemblages with higher phylogenetic diversity as in tropical or subtropical moist forests, fine root morphology often is more variable among different species than in the temperate mixed forest of our study. Under these conditions, nutrient foraging strategies may largely depend on fine root diameter, with thin-root species often showing greater fine root growth rates, whereas thick-root species are apparently relying more on mycorrhizal fungi with respect to nutrient acquisition. Across 14 evergreen or deciduous broad-leaf or coniferous AM trees in subtropical China, Liu et al. (2015) found much larger fine root diameter variation (0.19–0.86 mm) than in our study (0.33–0.59 mm), which was associated with differences in root growth rate and the degree of AM colonization. Aboveground – Belowground Linkages While leaf lifespan was more or less similar among the six species (6–7 months), the lifespan of fine roots (averaged over all fine root mass <2 mm) varied up to fivefold among the species (ca. 11–54 months) and up to threefold between the horizons within a species. This suggests that fine root and leaf lifespan are only poorly related to each other in this species sample, and fine root longevity is controlled by other factors than aboveground phenology. A similar conclusion was drawn by Withington et al. (2006) for their five-species broadleaf tree sample, which included four of our species. In a global literature survey, Finér et al. (2011) detected no significant influence of stand basal area or stem density on fine root turnover. We also found no relation between the species’ aboveground woody biomass production and FRP and root turnover, disproving our third hypothesis. However, across all species, wood production increased with mean fine root diameter and decreased with increased root tissue density. We speculate that, in a fertile soil with more or less stable nutrient-rich patches as in Hainich forest, species with thicker fine roots may achieve a greater nutrient return on resource investment in root mass than thin-root species; this could promote aboveground productivity. Relative Importance of First- and Second-Order Roots in Fine Root Dynamics The detailed root order-related biomass analysis showed that about 30–50% of total fine root biomass (<2 mm) referred to the first and second orders which are assumed to conduct most of nutrient and water uptake (Guo et al., 2008b) and are termed absorptive roots (McCormack et al., 2015). These segments contain the fine root tips and the directly adjacent finest root segments with generally lowest degree of suberization. Assessment of the resource foraging strategies of the six species should therefore primarily consider the amount of carbon invested into the production of first- and second-order roots. We multiplied total FRP as measured in the ingrowth cores with the biomass fractions of the first to fourth root orders as found in the FRB inventory of Kubisch et al. (2015), assuming similar root longevity in the different root orders. Extrapolating the biomass distribution key from the inventory to the ingrowth cores may be justified in our study, because we found similar branching patterns of the fine root strands in the inventory and the ingrowth core analysis for all six species (Figure 1). According to this very rough calculation, the species produced between 50 and 90 g root biomass per m2 and year in 0–30 cm soil depth in the first and second root orders, which is much less than the global FRP mean (337 g m-2 year-1, mean sampling depth 37 cm, total root biomass <2 mm) given by Finér et al. (2011) for temperate forests. To our knowledge, there are only two other studies that attempted to quantify the root order-related root production on a plot level basis (Xia et al., 2010; Fraxinus mandshurica; Sun et al., 2011: Fraxinus mandshurica and Larix gmelinii, both roughly 25 years-old plantations). No other study seems to exist, where such an approach has been applied to mature (>100 years-old) forest stands. In these two East Asian tree plantations, much lower FRP values [42 and 27 g m-2 year-1 in 0–10 cm soil depth (Xia et al., 2010) or 0–20 cm soil depth (Sun et al., 2011)] were reported than in our mature stands, even though the same methodology (ingrowth cores) was used at least in the latter study. Given that temperate trees invest about 300 g m-2 year-1 in leaf biomass, and coarse and large root production has its equivalent in twig and branch production, we draw the conclusion that temperate trees achieve nutrient and water uptake at lower cost for absorbing structures than is needed for carbon assimilation. Nevertheless, the total length of absorbing roots produced annually in the topsoil is enormous, exceeding 1 km per m2 ground area in the 0–30 cm profile in the six species investigated here. Conclusion The co-existence of EM and AM tree species in cool-temperate mixed forests raises the question about possible differences in belowground resource foraging strategies between these two tree groups. In our sample of six relatively wide-spread species, variation in root dynamics occurred mainly within the two groups and not between them, contradicting our main hypothesis. Investigation of a larger number of tree species might reveal significant group differences in fine root lifespan and root productivity, but there exist only few other AM tree species in Central Europe with wider distribution (e.g., Acer campestre and Ulmus glabra). Since many of the common species were included in our sample, our results and those of Kubisch et al. (2015) on root morphological differences suggest that species differences in fine root morphology, lifespan, and growth rate in Central European broadleaved mixed forests are primarily determined by species identity, while the influence of mycorrhiza type is only of secondary importance. Species differences manifested primarily in differences in root tip frequency, while variation in root diameter was of minor importance (Kubisch et al., 2015). Possible differences between ECM and AM species in root morphology and turnover in many cases will be overlain by effects of environmental and stand structural variation (Finér et al., 2011; Leppälammi-Kujansuua et al., 2014). In correspondence, a global analysis of measured fine root turnover rates in forests (Finér et al., 2011) seems to suggest that temperature (or growing season length), and not mycorrhiza type, is a main determinant of tree fine root lifespan and FRP, because mean turnover rate continuously increased from 0.77 to 1.21 and 1.44 year-1 and FRP from 311 to 428 and 596 g m-2 year-1 from boreal to temperate and tropical forests. Thus, a root productivity increase and root lifespan decrease is occurring with both biome transitions, i.e., from the boreal to the temperate forest and from the temperate to the tropical forest, even though a shift in predominant mycorrhiza type (from EM to AM) does occur only between temperate and tropical forests, but not between boreal and (cool) temperate forests. More data from species-rich mixed forests is needed to understand the influence of mycorrhiza type on tree fine root morphology, dynamics, and functioning. Author Contributions Study idea and design: CL and DH; field and lab work: PK; data analysis: PK and DH; paper concept and writing: PK, DH, and CL. Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. We thank all persons who helped during the lab and field work as well as Andreas Jacob and Mechthild Stange for technical support. The study was conducted in the framework of GRK 1086. Funding by the DFG (German Science Foundation) is gratefully acknowledged. We thank the administration of Hainich National Park for the research permit and the good cooperation. Supplementary material The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpls.2016.01233 Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. ==== Refs References Adams T. S. Eissenstat D. M. (2015 ). On the controls of root lifespan: assessing the role of soluble phenolics. Plant Soil 392 301 –308 . 10.1007/s11104-015-2465-x Brunner I. Bakker M. R. Björk R. G. Hirano Y. Lukac M. Aranda X. (2013 ). Fine-root turnover rates of European forests revisited: an analysis of data from sequential coring and ingrowth cores. Plant Soil 362 357 –372 . 10.1007/s11104-012-1313-5 Burke M. Raynal D. (1994 ). Fine root growth phenology, production, and turnover in a northern hardwood forest ecosystem. Plant Soil 162 135 –146 . 10.1007/BF01416099 Cesarz S. Ruess L. Jacob M. Jacob A. Schaefer M. Scheu S. (2013 ). Tree species diversity versus tree species identity: driving forces in structuring forest food webs as indicated by soil nematodes. Soil Biol. Biochem. 62 36 –45 . 10.1016/j.soilbio.2013.02.020 Comas L. H. Eissenstat D. M. (2009 ). Patterns in root trait variation among 25 co-existing North American forest species. New Phytol. 182 919 –928 . 10.1111/j.1469-8137.2009.02799.x 19383105 Eissenstat D. M. (1991 ). On the relationship between specific root length and the rate of root proliferation: a field study using citrus rootstocks. New Phytol. 118 63 –68 . 10.1111/j.1469-8137.1991.tb00565.x Eissenstat D. M. Duncan L. W. (1992 ). Root growth and carbohydrate responses in bearing citrus trees following partial canopy removal. Tree Physiol. 10 245 –257 . 10.1093/treephys/10.3.245 14969982 Eissenstat D. M. Kucharski J. M. Zadworny M. Adams T. S. Koide R. T. (2015 ). Linking root traits to nutrient foraging in arbuscular mycorrhizal trees in a temperate forest. New Phytol. 208 114 –124 . 10.1111/nph.13451 25970701 Eissenstat D. M. Yanai R. D. (1997 ). The ecology of root lifespan. Adv. Ecol. Res. 27 1 –60 . 10.1016/S0065-2504(08)60005-7 Ellenberg H. Leuschner C. (2010 ). Vegetation Mitteleuropas Mit Den Alpen in Ökologischer, Dynamischer und Historischer Sicht, 6th Edn Stuttgart : Ulmer . Fan P. Guo D. (2010 ). Slow decomposition of lower order roots: a key mechanism of root carbon and nutrient retention in the soil. Oecologia 163 509 –515 . 10.1007/s11104-012-1290-8 20058026 Finér L. Ohashi M. Noguchi K. Hirano Y. (2011 ). Fine root production and turnover in forest ecosystems in relation to stand and environmental characteristics. For. Ecol. Manage. 262 2008 –2023 . 10.1016/j.foreco.2011.08.042 Fitter A. H. (1987 ). An architectural approach to the comparative ecology of plant root systems. New Phytol. 106 61 –77 . 10.1111/j.1469-8137.1987.tb04683.x Fitter A. H. (1996 ). “Characteristics and functions of root systems ,” in Plant Roots: The Hidden Half, eds Kafkafi U. Waisel Y. Eshel A. (New York, NY : Marcel Dekker Inc. ), 15 –32 . Fogel R. (1983 ). Root turnover and productivity of coniferous forests. Plant Soil 71 75 –85 . 10.1007/BF02182643 Guckland A. Jacob M. Flessa H. Thomas F. M. Leuschner C. (2009 ). Acidity, nutrient stocks, and organic-matter content in soils of a temperate deciduous forest with different abundance of European beech (Fagus sylvatica L.). J. Plant Nutr. Soil. Sci. 172 500 –511 . 10.1002/jpln.200800072 Guo D. Li H. Mitchell R. J. Han W. Hendricks J. J. Fahey T. J. (2008a ). Fine root heterogeneity by branch order: exploring the discrepancy in root turnover estimates between minirhizotron and carbon isotopic methods. New Phytol. 177 443 –456 . 10.1111/j.1469-8137.2007.02242.x 17944827 Guo D. Xia M. Wei X. Chang W. Liu Y. Wang Z. (2008b ). Anatomical traits associated with absorption and mycorrhizal colonization are linked to root branch order in twenty-three chinese temperate tree species. New Phytol. 180 673 –683 . 10.1111/j.1469-8137.2007.02242.x 18657210 Hendricks J. J. Hendrick R. L. Wilson C. A. Mitchell R. J. Pecot S. D. Guo D. (2006 ). Assessing the patterns and controls of fine root dynamics: an empirical test and methodological review. J. Ecol. 94 40 –57 . 10.1111/j.1365-2745.2005.01067.x Hertel D. Leuschner C. (2002 ). A comparison of four different fine root production estimates with ecosystem carbon balance data in a Fagus–Quercus mixed forest. Plant Soil 239 237 –251 . 10.1023/A:1015030320845 Hertel D. Strecker T. Müller-Haubold H. Leuschner C. (2013 ). Fine root biomass and dynamics in beech forests across a precipitation gradient–is optimal resource partitioning theory applicable to water-limited mature trees? J. Ecol. 101 1183 –1200 . 10.1111/1365-2745.12124 Hölscher D. Hertel D. Leuschner C. Hottkowitz M. (2002 ). Tree species diversity and soil patchiness in a temperate broad-leaved forest with limited rooting space. Flora 197 118 –125 . 10.1078/0367-2530-00021 Jacob A. Hertel D. Leuschner C. (2012 ). On the significance of belowground overyielding in temperate mixed forests: separating species identity and species diversity effects. Oikos 122 463 –473 . 10.1111/j.1600-0706.2012.20476.x Jacob M. Leuschner C. Thomas F. M. (2010 ). Productivity of temperate broad-leaved forest stands differing in tree species diversity. Ann. For. Sci. 67 :503 10.1051/forest/2010005 Keyes M. R. Grier C. C. (1981 ). Above and below-ground net primary production in 40- year-old Douglas-fir stands on low and high productivity sites. Can. J. For. Res. 11 599 –605 . 10.1139/x81-082 Köcher P. Gebauer T. Horna V. Leuschner C. (2009 ). Leaf water status and stem xylem flux in relation to soil drought in five temperate broad-leaved tree species with contrasting water use strategies. Ann. For. Sci. 66 :101 10.1051/forest/2008076 Kubisch P. Hertel D. Leuschner C. (2015 ). Do ectomycorrhizal and arbuscular mycorrhizal temperate tree species systematically differ in root order-related fine root morphology and biomass? Front. Plant. Sci. 6 :64 10.3389/fpls.2015.00064 Lang C. Seven J. Polle A. (2011 ). Host preferences and differential contributions of deciduous tree species shape mycorrhizal species richness in a mixed Central European forest. Mycorrhiza 21 297 –308 . 10.1007/s00572-010-0338-y 20886243 Legner N. Fleck S. Leuschner C. (2014 ). Within-canopy variation in photosynthetic capacity, SLA and foliar N in temperate broad-leaved trees with contrasting shade tolerance. Trees 28 263 –280 . 10.1007/s00468-013-0947-0 Leppälammi-Kujansuua L. Aro L. Salemaa M. Hansson K. Kleja D. B. Helmisaari H.-S. (2014 ). Fine root longevity and carbon input into soil from below- and aboveground litter in climatically contrasting forests. For. Ecol. Manage. 326 79 –90 . 10.1016/j.foreco.2014.03.039 Liu B. Li H. Zhu B. Koide R. T. Eissenstat D. M. Guo D. (2015 ). Complementarity in nutrient foraging strategies of absorptive fine roots and arbuscular mycorrhizal fungi across 14 coexisting subtropical tree species. New Phytol. 208 125 –136 . 10.1111/nph.13434 25925733 Majdi H. (1996 ). Root sampling methods - applications and limitations of the minirhizotron technique. Plant Soil 185 255 –258 . 10.1007/BF02257530 McCormack M. L. Adams T. S. Smithwick E. A. Eissenstat D. M. (2014 ). Variability in root production, phenology, and turnover rate among 12 temperate tree species. Ecology 95 2224 –2235 . 10.1890/13-1942.1 25230473 McCormack M. L. Adams T. S. Smithwick E. A. H. Eissenstat D. M. (2012 ). Predicting fine root lifespan from plant functional traits in temperate trees. New Phytol. 195 823 –831 . 10.1111/j.1469-8137.2012.04198.x 22686426 McCormack M. L. Dickie I. A. Eissenstat D. M. Fahey T. J. Fernandez C. W. Guo D. (2015 ). Redefining fine roots improves understanding of below-ground contributions to terrestrial biosphere processes. New Phytol. 207 505 –518 . 10.1111/nph.13363 25756288 McGuire K. L. Henkel T. W. de la Cerda I. G. Villa G. Edmund F. Andrew C. (2008 ). Dual mycorrhizal colonization of forest-dominating tropical trees and the mycorrhizal status of non-dominant tree and liana species. Mycorrhiza 18 217 –222 . 10.1007/s00572-008-0170-9 18365256 Meinen C. Hertel D. Leuschner C. (2009a ). Biomass and morphology of fine roots in temperate broad-leaved forests differing in tree species diversity: is there evidence of below-ground overyielding? Oecologia 161 99 –111 . 10.1007/s00442-009-1352-7 19415337 Meinen C. Hertel D. Leuschner C. (2009b ). Root growth and recovery in temperate broad-leaved forest stands differing in tree species diversity. Ecosystems 12 1103 –1116 . 10.1007/s00442-009-1352-7 Müller-Haubold H. Hertel D. Seidel D. Knutzen F. Leuschner C. (2013 ). Climate responses of aboveground productivity and allocation in Fagus sylvatica: a transect study in mature forests. Ecosystems 16 1498 –1516 . 10.1007/s10021-013-9698-4 Ostonen I. Lõhmus K. Pajuste K. (2005 ). Fine root biomass, production and its proportion of NPP in a fertile middle-aged Norway spruce forest: comparison of soil core and ingrowth core methods. For. Ecol. Manage. 212 264 –277 . 10.1016/j.foreco.2005.03.064 Persson H. (1978 ). Root dynamics in a young Scots pine stand in Central Sweden. Oikos 30 508 –519 . 10.2307/3543346 Persson H. (1980 ). Fine-root dynamics in a Scots pine stand with and without near optimum nutrient and water regimes. Acta Phytogeogr. Suecica 68 101 –110 . Powell S. W. Day F. P. (1991 ). Root production in four communities in the Great Dismal Swamp. Am. J. Bot. 78 288 –297 . 10.2307/2445251 Pregitzer K. S. DeForest J. L. Burton A. J. Allen M. F. Ruess R. W. Hendrick R. L. (2002 ). Fine root architecture of nine North American trees. Ecol. Monogr. 72 293 –309 . 10.1890/0012-9615(2002)072[0293:FRAONN]2.0.CO;2 Rasmann S. Agrawal A. A. (2008 ). In defense of roots: a research agenda for studying plant resistance to belowground herbivory. Plant Physiol. 146 875 –880 . 10.1104/pp.107.112045 18316643 Rothe A. Binkley D. (2001 ). Nutritional interactions in mixed species forests: a synthesis. Can. J. For. Res. 31 1855 –1870 . 10.1139/cjfr-31-11-1855 Rumpel C. Kögel-Knabner I. Bruhn F. (2002 ). Vertical distribution, age, and chemical composition of organic carbon in two forest soils of different pedogenesis. Org. Geochem. 33 1131 –1142 . 10.1016/S0146-6380(02)00088-8 Ryser P. (1996 ). The importance of tissue density for growth and life span of leaves and roots: a comparison of five ecologically contrasting grasses. Funct. Ecol. 10 717 –723 . 10.2307/2390506 Scheibe A. Steffens C. Seven J. Jacob A. Hertel D. Leuschner C. (2015 ). Effects of tree identity dominate over tree diversity on the soil microbial community structure. Soil Biol. Biochem. 81 219 –227 . 10.1016/j.soilbio.2014.11.020 Smith S. E. Read D. J. (2007 ). Mycorrhizal Symbiosis, 3rd Edn Amsterdam : Elsevier . Sun Y. Gu J. Zhuang H. Guo D. Wang Z. (2011 ). Lower order roots are more palatable to herbivores: a case study with two temperate tree species. Plant Soil 347 351 –361 . 10.1007/s11104-011-0854-3 Tierney G. L. Fahey T. J. (2001 ). Evaluating minirhizotron estimates of fine root longevity and production in the forest floor of a temperate broadleaf forest. Plant Soil 229 167 –176 . 10.1023/A:1004829423160 Valtanen K. Eissfeller V. Beyer F. Hertel D. Scheu S. Polle A. (2014 ). Carbon and nitrogen fluxes between beech and their ectomycorrhizal assemblage. Mycorrhiza 24 645 –650 . 10.1007/s00572-014-0581-8 24756632 Vogt K. A. Vogt P. Palmiotto P. A. Boon P. O’Hara J. Asbjornsen H. (1996 ). Review of root dynamics in forest ecosystems grouped by climate, climatic forest type and species. Plant Soil 187 159 –219 . 10.1007/BF00017088 Wells C. E. Eissenstat D. M. (2002 ). Beyond the roots of young seedlings: the influence of age and order on fine root physiology. J. Plant Growth Regul. 21 324 –334 . 10.1007/s00344-003-0011-1 Withington J. M. Reich P. B. Oleksyn J. Eissenstat D. M. (2006 ). Comparisons of structure and life span in roots and leaves among temperate trees. Ecol. Monogr. 76 381 –397 . 10.1890/0012-9615(2006)076[0381:COSALS]2.0.CO;2 Xia M. Guo D. Pregitzer K. (2010 ). Ephemeral root modules in Fraxinus manshurica. New Phytol. 188 1065 –1074 . 10.1111/j.1469-8137.2010.03423.x 21058949 Zianis D. Muukkonen P. Mäkipää R. Mencuccini M. (2005 ). Biomass and stem volume equations of tree species in Europe. Silva Fenn. Monogr. 4 :63 .

PMC005xxxxxx/PMC5000522.txt

==== Front BMC Syst BiolBMC Syst BiolBMC Systems Biology1752-0509BioMed Central London 30310.1186/s12918-016-0303-2Research ArticleSignaling cascades transmit information downstream and upstream but unlikely simultaneously Catozzi Simona simona.catozzi@inln.cnrs.fr 1Di-Bella Juan Pablo juandb84@gmail.com 2Ventura Alejandra C. alejvent@gmail.com 2http://orcid.org/0000-0002-1274-0300Sepulchre Jacques-Alexandre jacques-alexandre.sepulchre@inln.cnrs.fr 11 Université Côte d’Azur, CNRS, INLN, 1361 route des lucioles, Valbonne, 06560 France 2 IFIBYNE-UBA-CONICET and Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón II, Buenos Aires, C1428EHA Argentina 25 8 2016 25 8 2016 2016 10 1 844 3 2016 30 6 2016 © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Signal transduction is the process through which cells communicate with the external environment, interpret stimuli and respond to them. This mechanism is controlled by signaling cascades, which play the role of intracellular transmitter, being able to transmit biochemical information between cell membrane and nucleus. In theory as well as in practice, it has been shown that a perturbation can propagate upstream (and not only downstream) a cascade, by a mechanism known as retroactivity. This study aims to compare the conditions on biochemical parameters which favor one or the other direction of signaling in such a cascade. Results From a mathematical point of view, we show that the steady states of a cascade of arbitrary length n are described by an iterative map of second order, meaning that the cascade tiers are actually coupled three-by-three. We study the influence of the biochemical parameters in the control of the direction of transmission – upstream and/or downstream – along a signaling cascade. A numerical and statistical approach, based on the random scan of parameters describing a 3-tier signaling cascade, provides complementary findings to the analytical study. In particular, computing the likelihood of parameters with respect to various signaling regimes, we identify conditions on biochemical parameters which enhance a specific direction of propagation corresponding to forward or retro-signaling regimes. A compact graphical representation is designed to relay the gist of these conditions. Conclusions The values of biochemical parameters such as kinetic rates, Michaelis-Menten constants, total concentrations of kinases and of phosphatases, determine the propensity of a cascade to favor or impede downstream or upstream signal transmission. We found that generally there is an opposition between parameter sets favoring forward and retro-signaling regimes. Therefore, on one hand our study supports the idea that in most cases, retroactive effects can be neglected when a cascade which is efficient in forward signaling, is perturbed by an external ligand inhibiting the activation at some tier of the cascade. This result is relevant for therapeutic methodologies based on kinase inhibition. On the other hand, our study highlights a less-known part of the parameter space where, although the forward signaling is inefficient, the cascade can interestingly act as a retro-signaling device. Electronic supplementary material The online version of this article (doi:10.1186/s12918-016-0303-2) contains supplementary material, which is available to authorized users. Keywords Signaling cascadesRetroactivityMAPK cascadesDrug designKinase inhibitorsissue-copyright-statement© The Author(s) 2016 ==== Body Background Cell signaling is responsible for the development and functioning of both unicellular and multicellular organisms. Abnormal cell signaling leads to diseases which involve at least one breakdown in cell communication [1]. Signaling pathways control and regulate the flow of biochemical information between cells and their external environment, which is essential for cell signaling. Typically, a stimulus (in most cases molecules secreted by another cell, e.g. growth factors, hormones) is detected on the surface of the plasma membrane, activating complex signaling. Covalent modification cycles are one of the major intracellular signaling mechanisms, both in prokaryotic and eukaryotic organisms [2]. Kinase cascades are a sequence of such cycles, in which the activated protein in one tier promotes the activation of the protein in the next one. The advantages of these cascades in signal transduction are multiple and the conservation of their basic structure throughout evolution suggests their usefulness. A reaction cascade may amplify a weak signal, accelerate the speed of signaling, steepen the profile of a graded input as it propagates, filter out noise in signal reception, introduce time delay, and allow alternative entry points for differential regulation [3–5]. Recent theoretical and experimental studies have demonstrated that kinase cascades exhibit bidirectional signal propagation via a phenomenon termed retroactivity [6–11]. This phenomenon arises because cycles in a cascade are coupled with both the next and the previous cycle (Fig. 1a). The cycles can be thought of as modules, where each module’s substrate sequesters a key component of the previous one, limiting the component’s ability to participate in the previous module and inducing a natural change on it. This change may then propagate upstream through one or more preceding modules. Fig. 1 A linear cascade propagates signals in different directions with a certain probability In [6, 11–14] the effect of retroactivity in kinase cascades has been investigated. Applying a perturbation at any level of the cascade (such as sequestration of the active protein or over-expression of a phosphatase) would have implications both downstream and upstream of the disturbance level due to retroactivity. This result, that was experimentally validated ([10, 15–17]), indicates that a kinase cascade is a bidirectional device regarding information transmission. However, how likely is it that a cascade transmits information upstream? If parameter conditions favor this last situation, can this coexist with standard signal propagation down the cascade? Some of the results in [6, 11–14] show evidences that favorable conditions to forward signaling are typically opposite to conditions promoting retroactive signaling. In [6], an arbitrary long cascade (with every unit in steady-state) has been considered to be locally perturbed and two different regimes have been identified (see Fig. 4 therein). The first regime (perturbation traveling mostly downstream) is achieved when both all kinases and all phosphatases are saturated by their substrates, making the amount of protein increase down the cascade. The opposite regime is attained when only the phosphatases are saturated. These two regimes involved the relaxation of a perturbation, and was actually a first evidence that separated regions in the parameter space of a cascade might characterize the propagatation of a signal downstream or upstream. In [11] it has been explored how a small perturbation in the concentration of an inhibitor of the active protein at the last level perturbs the steady-state concentrations of a relatively long linear the cascade. It has been recognized that natural cascades can amplify a perturbation (for free active protein) as it propagates upstream, but the probability of attenuation is substantially higher than that of amplification. In addition, the probability of attenuation increases with the number of stages in the cascade. Interestingly, the parameter conditions that produce an attenuation of the upstream response ensure the amplification of downstream signaling. In [12] the authors have focused on kinase inhibitors, a class of targeted therapies designed to interfere with a specific kinase molecule in a dysregulated signaling pathway. Within physiologically and therapeutically relevant ranges for all parameters, a targeting inhibitor can naturally induce an off-target effect via retroactivity, having the capacity of turning “on" an otherwise “off" parallel cascade when two cascades share an upstream activator. In that study it was mainly considered a network of three covalent modification cycles: an upstream cycle (cycle 1) activating two parallel cycles. A perturbation was applied to one of the downstream cycles (cycle 3) and the effect measured in the other one (cycle 2); this effect reaches the upper cycle via retroactivity and then is transmitted to the parallel pathway. An optimization procedure was performed to identify ranges of the parameter values that ensure a measurable effect in cycle 2. This optimization implied the combination of a good upstream transmission of information (from cycle 3 where the perturbation is applied, to cycle 1) and a good downstream signaling (from cycle 1 to cycle 2) and noticeably, the parameter ranges characterizing these two directions of signaling were not only different but somehow opposite. Similar conclusions have been experimentally observed on a two-branch MAP-Kinase cascade, allowing to activate responses of JNK and p38MAPK (equivalent to cycles 2 and 3 in the previous description) [17]. Here the authors termed the notion of retroactive signaling by retrograde propagation. They experimentally showed that retrograde propagation from JNK to p38MAPK is significantly higher than from p38MPAK to JNK. A preexisting theoretical study [13], enables to interpret such asymmetry by the fact that in this branched pathway, one side is more effective than the other for forward signaling whereas the second is more effective for retroactive signaling. In particular, for the simplest case of a bicyclic kinase cascade, that study has analyzed the conditions for which the upstream cycle was affected: either by a change of the total amount of protein in the downstream cycle, or by a variation of the phosphatase deactivating the same protein. Notably, it was revealed that when the downstream cycle was mostly deactivated, thus impeding a forward signaling, the retroactive effects on the upstream cycle were larger. In this paper, we address the question of simultaneous bidirectionality in signaling cascades, and we use both analytical and numerical approaches. Our main goal is to develop a comparative study of parameters affecting forward or retroactive responses in linear signaling cascades (Fig. 1a). In the first part we develop an analytical study of the dose-response curve, defined as the concentration of the last activated protein in the cascade as a function of the initial stimulus. We also consider that a drug can be added in the cell in order to inhibit the last activated protein in the cascade. Our aim being to examine the features of the dose-response as a function obtained from a discrete iterative map with boundary conditions, and thus optimize the forward signaling. Moreover, we define the drug-response curves, as the concentration of the intermediate activated proteins as a function of the inhibiting drug, which refer to the retroactive (backward) signaling. In the second part, we perform a numerical investigation on a 3-tier cascade in order to test the cascade for uni- and bidirectional propagation (upstream and/or downstream) along it. The cascade parameters are sampled and classified according to the signaling direction they contribute to. Some striking results are already summarized on Fig. 1b as follows: 67 % of parameters lead to no form of signaling; 19 % of parameters show forward signaling without retroactivity; 12 % of parameters enable retroactive response but no forward signaling; 2 % of parameters show both forward and retroactive signaling properties. Evidently, any estimate of such probabilities strongly depends on the assumed distribution of biochemical parameters from which the sampling is performed. Presumably, the actual parameter distribution existing in natural signaling pathways is not uniform. On the other hand, this knowledge is currently out of reach, or would be very hard to access. Therefore in this paper we choose as a reference point, a uniform distribution of biochemical parameters lying in some predefinite ranges. However, the fact that numerous efficient signaling cascades, and retroactivity effects, have been measured experimentally, suggests that the estimates reported on Fig. 1b, are likely to be lower bounds of the corresponding natural probabilities. However, the probability of mixed forward and retro-signaling is likely to remain much less probable than the non-mixed signaling regimes because, as we shall see in the following, this kind of signaling properties reckon with parameter conditions that are somehow antagonist. Indeed, in the following sections we analyze in more details how some particular parameters influence the probabilities of these signaling types. Considerable attention is provided to the interpretation of some conditions on parameters which increase the probabilities of various signaling regimes, in terms of biochemical concepts like enzyme saturation and protein sequestration. Results A n-tier signaling cascade with an inhibitor The system we deal with is a linear cascade made up of an arbitrary number n of cycles of single covalent modifications, e.g. single phosphorylation-dephosphorylation cycles. We also assume that the last level of the cascade may be altered by a kinase inhibitor, represented by a drug D, that blocks the action of the active protein by sequestering it into an inactive complex (Fig. 1a). Our overall purpose is to investigate the working principles of such a generic cascade in terms of biochemical parameters like reaction rates and total enzyme concentrations. Thus, identify which parameter ranges are associated to specific signaling behaviors, which we call regimes. A signaling regime describes the way a cascade responds (significantly or negligibly) to the stimuli it is subjected to, namely the activator signal (at the top) and the inhibiting drug (at the bottom). Practically, this means to measure two effects simultaneously: the impact of the activator on downstream proteins (dose-response curves) and the effect of the drug on the upstream proteins (drug-response curves). Specifically, we are interested in studying how the retroactive signaling propagates (from the (n−1)th to the first tier) and whether this is compatible with an efficient forward signaling relative to the nth tier. In the following, we firstly show analytical results characterizing the most “natural" direction of propagation – the forward signaling – on a generic cascade of n tiers. We will show that this analytical approach provides some useful clues on elucidating key conditions that biochemical parameters should satisfy to observe an effective forward signaling of the cascade. On the other hand, the analytical approach soon becomes cumbersome, even by considering a homogeneous cascade (where parameters are the same for each tier). Therefore, in a second part of the Results we present a statistical investigation based on numerical computations, about all forms of signaling (forward and/or retroactive), for inhomogeneous cascades but with n fixed to 3. An iterative map for the cascade response functions The system of equations describing the steady states of the n-cycle cascade depicted on Fig. 1a can be reformulated as a system of n iterative equations (details are shown in Methods) given by 1a s=x1x1+a1+b1x1(x1+a1)1−x1−e2x2x2+a2−c1x1, 1b xi−1=bieixi(xi+ai)1−xi−ei+1xi+1xi+1+ai+1−cixi,1<i<n, 1c xn−1=bnenxn(xn+an)1−xn−dTxnxn+aD−cnxn, with dimensionless variables, 1≤i≤n: xi=Yi1/YiT, where Yi1 is the active protein, and YiT is the total protein concentration, so that xi is the normalized active protein. Then the dimensionless parameters, 1≤i≤n, are defined as follows: 2 s=k10Y0Tk11E1T,ai=Ki1YiT,bi=Ki0YiT,ci=(1+ki1ki0)EiTYiT,ei=ki1EiTki0Yi−1,T,dT=DTYnT,aD=KDYnT, where ki0 and ki1 are the catalytic rates of, respectively, the phosphorylation and dephosphorylation reactions; ki0 and ki1 are the Michaelis-Menten constants associated; KD is the drug association-dissociation constant; YiT, EiT and DT represent, respectively, the total concentrations of the proteins, the phosphatases and the drug. This formulation is a generalization of the one presented for a 3-tier cascade in [18], extented to a cascade of arbitrary length n, with the addition of a drug. In a more compact form, system (1) can be rewritten as: 3 s=fˇ1(x1,x2),xi−1=fi(xi,xi+1),1<i<n,xn−1=f^n(xn,xn+1=0,dT), which represents the iterates of a second-order discrete map with boundary conditions given by signal s and xn+1. We remark that, if the drug is absent, i.e.dT=0, then f^n(xn,xn+1=0,dT) reduces to fn(xn,xn+1=0). This iterative system allows us to obtain the dose-response function xn(s) as follows, provided that all the parameters (even dT) are fixed, except s : given xn∈[0,1), from Eq. 1c one can calculate xn−1, then from Eq. 1b one gets xn−2,…,x1, with i decreasing from n−1 to 2. Finally, s is computed by using 1a and one obtains function s(xn) which has typically several branches (see Fig. 2a), along the whole interval [0,1). Nevertheless, only one branch is biologically relevant [19], namely the one such that s(0)=0. This branch is defined on the domain [0,α), with α being the minimum value of xn for which s(xn)→+∞. Thus, the biological dose-response curve is given by the restriction s(xn)|[0,α) which is continuous and injective, so invertible on this domain. We denote such an inverse function as xn(s) (omitting the codomain restriction, for the sake of notation), see Fig. 2b. Fig. 2 Examples of dose-response and drug-response functions computed from the iterative system (3) (see main text). Parameters for the dose-responses: n=3,a=1.6,b=0.8,c=0.05,e=0.7. Parameters for the drug-responses: n=3,a=2.2,b=0.0005,c=5.2,e=5.1 Moreover, one can check that system (1) is consistent with the steady-state formulation derived in [19] (providing dT=0), where the authors particularly studied the properties of s(xn) as a rational function. We also note that the maps fˇ1,fi, and f^n are analytically invertible, leading to an inverse iterative system giving explicitly the inverse of the drug-response function dT(x1) (reported in Additional file 1), for a fixed signal s, cf. Fig. 2d. Dose-response functions: analytical characterization The dose-response function xn(s) expresses how the activated protein in the last cycle of the cascade varies with the input signal s (proportional to the total enzyme Y0T activating the first cycle of the cascade), given the quantity dT fixed e.g. to zero. For a cascade of n≥3 tiers, it is not possible to explicitly invert [the restriction of] function s(xn) to obtain an analytical expression of xn(s), because this requires finding the roots of a high-degree polynomial. Nonetheless, we illustrate how to provide qualitative knowledge of the non-saturating region, and quantitative estimation of the saturation value of the dose-response function. In order to simplify the analytical expressions we assume that the parameters defined in Eq. 2 are the same for each i=1,2,…,n. We say that such a system is a homogeneous cascade, and in the rest of the paper we will omit to write the lower index i, if unnecessary. Some generalizations of our results to inhomogeneous cascades are given in Methods. The strategy consists in approximating xn(s) piecewisely by matching analytical quantities (depending on parameters) evaluated at the origin (s=0) with the ones deduced at saturation (s→+∞), as illustrated in Fig. 3. Indeed the optimization of the efficiency of the forward signaling is based on the following approach. Fig. 3 Sketch of typical dose-response functions. Dose-response curves x n(s) (dotted blue curves) and their piecewise approximations (solid black lines) The non-saturated part of the dose-response function is roughly described by a polynomial function (of first or second order according to the initial curvature sign – negative or positive, respectively), and the saturated part by a constant function. More formally, we state that if the initial curvature χ=xn″(0)<0 (Fig. 3a), then: 4 xn(s)∼σs0≤s<pαs≥p,withp=ασ, where 0<σ<∞ and 0<α<1 are defined as σ=xn′(0) and α=lims→∞xn(s). In the other case, if χ>0 (Fig. 3b), then: 5 xn(s)∼σs+12χs20≤s<qαs≥q,withq=−σ+σ2+2χαχ. Hence, a dose-response function can be sketched by a simple curve depending on the three parameters (σ,χ,α). Precisely, if xn(s) is convex (χ≤0), the dose-response only depends on its initial slope σ and on its asymptotic value α, while if xn(s) is logistic-like (χ>0), also the value of its initial curvature χ plays a role (if χ is large, the dose-response function will reach its asymptotic value for relatively low doses). An advantage of our methodology is that, as shown below, σ and χ can be analytically calculated, and α estimated, in function of the biochemical parameters of the cascade. In turn, these results can be used to connect the parameters with standard characteristics of response functions, like the half maximal effective concentration EC50, or effective Hill coefficient nH. For example, simple estimates of the EC50 can be provided by the value of s such that xn(s)=α/2 in Eqs. 4 and 5, yielding the results: 6 EC50∼α2σifχ<0−σ+σ2+χαχifχ>0 Effective Hill coefficients can be subjected to several definitions. A possible estimate may be obtained by computing twice the response coefficient sxn′(s)/xn(s) at s=EC50. Finding analytical conditions which maximize the response amplitude α=lims→+∞xn(s) is not trivial because, as mentioned before, the function xn(s) is generally speaking intractable. Nevertheless, for a homogeneous cascade, we prove that (see Methods) the asymptotic value of the dose-response curve α, is lower bounded by 7 x∗=1−a−e−c+(1−a−e−c)2+4(a−be)2, with a,b,c,e defined in (2). x∗ is a fixed point of the map f defined at Eq. 3 as fi. Thus, since x∗≤α, requiring a large x∗ is sufficient to have a large amplitude α and therefore this is a sufficient condition to fulfill the criteria to promote an efficient forward signaling. Moreover, for homogeneous parameters, the initial slope of the dose-response is 8 σ=a1+baben−1, and the initial curvature for n=3, and dT,aD fixed, is 9 χ=−b2e2a2a+b(a+c−1)−1+a(1+b)dTaD+(1+b)eaa+b(a+c−1)+(1+b)(a+c−1)a1+babe4. In Methods we derive these and more general formulas for arbitrary n and inhomogeneous parameters. Therefore we have shown how the parameters (σ,χ,x∗) characterizing the sketchy dose-response curves (Fig. 3) can be expressed as functions of the cascade parameters (a,b,c,e). Now we want to state analytical conditions on parameter sets, that enhance forward signaling. As simple criteria, we say that a parameter set provides efficient signaling if it maximizes σ and α if χ<0, or maximize χ and α if χ>0. Table 1 sorts the sufficient conditions deduced from these criteria, thus optimizing the downstream propagation in a homogeneous cascade of length 3. Table 1 Sufficient conditions to optimize the forward signaling. The second column reports combined parameter ranges able to enhance the forward response for convex (χ≤0) and logistic-like (χ>0) curves, deduced analytically from the criteria of efficient forward signaling. The third column refers to conditions obtained below, with a numerical method based on a random parameter sampling and maximizing the likelihood of these parameters with respect to the forward signaling (See Discussion section) Parameters Suff. conditions for Maximizing likelihood χ≤0 χ>0 (cf. discussion below) a=K1YT >1 ≪1 a 3≫1 b=K0YT <1 <1 b i≪1 1/e=k0YTk1ET ≫1 ≫1 1/e i>1 c−e=ETYT ≪1 ≪1 c i−e i<1 ab=K1K0 >1 ≪1 a i/b i>1 In order to interpret the results summarized in this table, let us remember that for an enzymatic reaction, the enzyme is said to be saturated by its substrate when the Michaelis-Menten constant is small compared with the total concentration substrate. On the other hand, if the total enzyme concentration is not small compared with the total substrate, the free substrate is expected to be sequestrated by the substrate-enzyme complex. Moreover, in the case of an enzymatic cycle, we call activation parameter, the ratio between the maximal reaction rates of the two enzymes phosphorylating and dephosphorylating a protein. In light of this terminology, the first line of Table 1 shows that convex and logistic-like dose-responses are characterized respectively by non-saturation and high saturation of the phosphatases. A similar observation but concerning a single enzymatic cycle was reported in [20]. So this finding turns out to be generalizable to a whole cascade. The second line of the Table indicates that a moderate saturation of the kinase is also a condition that promotes forward signaling, whatever the curvature of the dose-response is. Finally, the third and fourth lines of the same Table reveal two general features enhancing forward signaling: high activation of the enzymatic cycles as well as non-sequestration of the active proteins by the phosphatase. This latter result is in agreement with the ones discussed in [3], where the authors compare the effect of sequestration and non-sequestration on logistic-like dose-responses in a MAPK (Mitogen Activated Protein Kinase) cascade. Drug-response functions By retroactivity we mean that a perturbation, applied at a certain level of a cascade, propagates upstream, thus altering the previous tiers. In our system, this perturbation is initiated by a compound D (called drug) inhibiting the activated protein at the nth tier. Our goal is to study the effect of such a perturbation on the upstream levels as a function of some normalized drug concentration dT, assuming that the signal s at the top of the cascade is constant and fixed at a high value. We classify the retroactivity according to its maximal propagation range, so that we call retroactivity of order k (1≤k≤n−1), the variation of the activated protein at the (n−k)th level as a function of the drug concentration, described by the function xn−k(dT), which we refer to as drug-response function. In particular the highest order of retroactivity in a linear cascade corresponds to the response curve x1(dT). As shown by [19], a perturbation propagates upstream in an alternated way so that, at level n, the amount of activated protein decreases, at level n−1 it increases, then it decreases at level n−2 and so on, up to the first level. It follows that function x1(dT) is increasing if n is even and decreasing if n is odd. Moreover, retroactivity is overall attenuated in long cascades, but can propagate and amplify its effect for n sufficiently small, e.g. equal to three [11]. Here, although we derive the drug-response functions in an iterative formulation inverting the map in (3) (cf. Additional file 1), the study of the derivatives at the origin dT=0 becomes too complicated to be performed analytically, as we did for dose-response functions xi(s) for 1≤i≤n. The main drawback is that, for dT=0, we have xi(dT)≠0 for any 1≤i≤n, so that the expressions of the initial slope and curvature of function xi(dT) do not simplify, as it does in the case of the dose-response functions. Therefore, in the following, we compute the amplitude of the drug-response function by means of a numerical approach, for n=3 fixed, considering Δxi the difference between the values xi(dT=0) and limdT→+∞xi(dT), for i=1,2. In these computations xi(dT=0) corresponds to the limit of the dose-response function xi(s), for s→+∞, while limdT→+∞xi(dT) corresponds to the limit of the dose-response function xi(s), for s→+∞, for the same cascade but composed only by the first n−1 levels (as a result of the total sequestration of the last-level active protein by the drug, at steady state). Random sampling of the parameter space In this section we consider a 3-tier signaling cascade and numerically estimate the probability of finding one of the possible signaling regimes, in function of key system’s parameters. We define 8 signaling regimes and denote them by (jkl), with j,k,l∈{0,1}, where: j=1 if the amplitude of the drug-response curve x1(dT) is larger than 5 %, j=0 otherwise; k=1 if the amplitude of the drug-response curve x2(dT) is larger than 5 %, k=0 otherwise; l=1 if the amplitude of the dose-response curve x3(s) is larger than 50 %, its slope at the origin is larger than 1 or the curvature should be at least 1, and l=0 otherwise. For instance, the signaling regime (001) corresponds to parameters associated to a cascade which exclusively exhibits forward propagation, while (110) is for exclusive retroactive propagation. Signaling regimes of type (j1l) will be said to possess first order retroactivity, whereas regimes of the type (1kl) will be said to have second order retroactivity. Later, to discuss the notion of signaling motifs (cf. Fig. 5), it will be convenient to consider hybrid signaling regimes like (1k0), where k is not determined (k=0,1). Finally, (000) is the anti-signaling regime, as it denotes the absence of any type of signaling response. By performing a random sampling of the biochemical parameters, like reaction rates and total concentrations (see Methods), we have assessed the probability of each regime, Fig. 1b. Likelihoods of parameters for the signaling regimes Our numerical investigation considers dimensional and dimensionless parameters. The dimensional parameters are coefficients of the steady state Eqs. 2, such that total kinase concentrations, total phosphatase concentration, Michaelis-Menten constants, etc... In the sequel the dimensional parameters are simply called biochemical parameters. On the other hand, the dimensionless parameters, say λ, are ratios of these biochemical parameters, such as fractions of total phosphatase over total kinase concentrations, and so on. We perform a random sampling of the biochemical parameters, with 18 dimensionless parameters being computed from these first ones. Afterward, we estimate the probability distributions (histograms) of all the dimensionless parameters λ for each signaling regime (jkl) defined above. Then, using Bayes’ formula (see Methods, Eq. 20) we deduce the probability of finding a given signaling regime (jkl), provided that a given parameter value λ is picked up. This quantity, seen as a function of λ, is called likelihood. We denote the likelihood normalized by its maximum value by Ljkl(λ) (cf. Eq. 21). In order to identify the region of the parameter space enhancing a given type of signaling regime, our main strategy is to look for the values of dimensionless parameters that maximize the likelihood for the considered signaling regime. The result can generally be expressed as inequality conditions that should be satisfied between biochemical parameters. On Fig. 4 each colored band shows the normalized likelihood of one given parameter, obtained for every signaling regimes (jkl). Thus, the intensity of the color in each band is proportional to the probability that a specific regime (jkl), with j,k,l∈{0,1}, occurs, in function of a given dimensionless parameter, all the biochemical parameters being chosen at random in a log-uniform distribution. In Additional file 2, the numerically computed likelihoods are also represented as curves with estimated errorbars. Fig. 4 Normalized likelihoods of 18 dimensionless parameters (proportional to color intensities), superimposed for all signaling regimes (j k l)≠(000) We report here on our analysis of the likelihood variations relative to a cascade with inhomogeneous parameters. We mainly proceed by visual inspection of the likelihood variations. In this way we can classify the 18 dimensionless parameters into two classes. The first class corresponds to 9 parameters for which similar ranges optimize the probability of any type of signaling (jkl), (000) excluded. In the second class we put the 9 parameters left, which exhibit likelihood variations being useful to discriminate between the signaling regimes, and specifically related to the probability of a given regime. After a visual analysis of all the parameter likelihoods we conclude that the following 9 dimensionless parameters form a first class : EiT/YiT, Ki0/Ki1(i=1,2,3), Ki+10/Ki1(i=1,2), K30/Y3T. For instance, we see that the range enhancing the likelihood for any regime (jkl)≠(000) corresponds to choose K30/Y3T as small as possible. On the contrary choosing K30/Y3T large hinders any type of signaling regime. On the other hand, as discussed below, the following 9 dimensionless parameters enable to discriminate amongst the various types of signaling forms: (ki0Yi−1,T)/(ki1EiT) (i=2,3), YiT/Yi+1,T, YiT/Ki1, YiT/Ki0 (i=1,2), EiT/Ki1 and EiT/Ki0 (i=2,3). In the following two subsections we first report on conditions about the biochemical parameters that promote indistinguishably any form of signaling regimes. Then we discuss the role of other conditions on biochemical parameters specific to each regime. General parameter conditions promoting signaling Some constraints on parameters appear to be common to any signaling regimes. Moreover, when these conditions are chosen opposite, the probability of getting any type of signaling tends to be negligible. These conditions are listed as follows : (i) EiT≤YiT (i=1,2,3) : at each tier of the cascade, the sequestration of the proteins by their phosphatase is absent or moderate. (ii) Ki0≪Ki1(i=1,2,3) : enzymatic asymmetry in cycle i : the affinity of the kinase for its substrate should be larger than the one of its phosphatase. (iii) Ki+10≪Ki1(i=1,2) : enzymatic asymmetry at the junction of tiers i and i+1 : the affinity of an activated protein for its substrate, i.e. the next protein in the cascade, is larger than for its own phosphatase. (iv) K30≪Y3T : the second kinase Y21 is saturated. Regime-specific parameter conditions The various signaling regimes are actually determined by a specific combination of parameters concerning cycle activation, protein sequestration and enzyme saturation. Here we discuss the effect of the second class of parameters that specifically favor some types of regime. (v) 1/ei=(ki0Yi−1,T)/(ki1EiT)(i=2,3) : cycle deactivation (ei>1) gives rise to retroactive signaling. Notably, retroactivity appears whenever the third tier is deactivated (e3>1). In this case, its effect can be either local (limited to the second tier, cf. regimes (01l)) if the second tier is activated (e2<1 so preventing an upper propagation), or global (e2>1, affecting both the previous tiers, cf. regimes (1kl)) if also the second tier is deactivated. (vi) YiT/Yi+1,T (i=1,2) : 4 distinct protein progressions typify the retroactive regimes, i.e. 00l (no retroactivity), 01l (first order retroactivity), 10l (second order retroactivity), and 11l (first and second order retroactivity), with l∈{0,1}. This parameter is associated to sequestration. More particularly, the sequestration of the third inactive protein by its kinase (Y2T/Y3T≫1) prevents any retroactive propagation (regimes (000) and (001)). The sequestration of the second inactive protein by its kinase (Y1T/Y2T≫1) promotes first order retroactivity, i.e. regime (01l). Inversely, non-sequestration (Y1T/Y2T∼1) induces second order retroactivity, i.e. regime (1kl). (vii) Ki1/YiT(i=1,2,3) : phosphatase saturation (Ki1/YiT<1) or non-saturation (Ki1/YiT≥1) marks out the appearance of second order retroactivity and forward signaling. In particular, saturation (respectively non-saturation) of the first phosphatase is associated to negligible (respectively significative) second order retroactivity, i.e.j=0 (respectively j=1). Instead, saturation (respectively non-saturation) of the third phosphatase is associated to significative (respectively negligible) forward propagation, i.e.l=1 (respectively l=0). Moreover, saturated phosphatase at the second tier marks the complete absence of retroactivity (regimes (000) and (001)). (viii) Ki0/YiT(i=1,2) : saturation (respectively non-saturation) of the input signal, K10/Y1T<1 (respectively K10/Y1T≥1), characterizes a negligible (significative) second order retroactivity, i.e.j=0 (respectively j=1). Non-saturation of the kinase activating the second tier (K10/Y1T≥1) is typical of first order retroactivity (regimes (010) and (011)). This analysis leads to the following criteria to enhance to probability P of significant response at each stage j,k,l within a signaling regime (jkl): (I) P(j=1) is enhanced if and only if Y1T≪K11. (II) P(k=1) is enhanced if e2<1 and e3>1. (III) P(l=1) is enhanced if and only if E3T≪Y3T. Moreover we claim the following necessary conditions: (IV) If (I) holds then e2>1 (notably, e2>1 for (110) and (111), and e2≫1 for (100) and (101)). (V) If conditions of (II) holds then j=0. Graphical representation of the signaling regimes In the previous section, conditions on biochemical parameters which characterize the signaling regimes, have been deduced from the likelihoods of dimensionless parameters. At this stage it is difficult to imagine how, among the various signaling regimes, such conditions are similar or different from each other. Therefore in this section we introduce a method to graphically depict these conditions and visually link them to the cascade signaling properties. The idea is to associate a pictorial code to the parameters in such a way that their graphical representation conveys qualitatively the corresponding signaling regimes. The method is based on the visual examination of the maximal likelihoods of dimensionless parameters (Fig. 4). Its application, detailed in Additional file 3, leads to draw the 5 signaling motifs depicted on Fig. 5, which are associated respectively to signaling regimes (001), (010), (011), (1k0),(1k1). (Recall that the two latter denote hybrid signaling regimes, with non-determined k=0 or 1). The procedure, providing conditions on biochemical parameters which optimize the probability to observe such regimes, consists in 5 steps described below. Fix the size of Y2T and Y3T, then Y1T (blue ellipses) as follows. If Y2T≫Y3T then draw Y2T large and Y3T medium. Then, if Y1T≪Y2T, draw Y1T medium. If Y2T<Y3T (with a magnitude difference of 100 at most) then draw Y2T medium and Y3T large. Then if Y1T∼Y2T, draw Y1T medium and if Y1T<Y2T, draw Y1T small. If Y2T≪Y3T (with a magnitude difference larger than 100), then draw Y2T medium and Y3T large. Then if Y1T≫Y2T, draw Y1T large. Fix the size of the EiT’s (i=1,2,3). If EiT≪YiT then draw EiT small. If EiT∼YiT then draw EiT of the same size of YiT. If EiT≫YiT then draw EiT extra large. Represent signaling connectivity (i=1,2). If ei>1, draw one arrow pointing upward. If ei<1, draw one arrow pointing downward. Empty/full shapes. If YiT≫Ki0 for i=1, fill in the red triangle. If YiT≫Ki0 for i=2,3, fill in the (i−1)th blue ellipse. If YiT≫Ki1 for i=1,2,3, fill in the ith green ellipse. Draw the motif contour following the largest ellipses. Instead of a straight line, the contour will start with a cusp if the red triangle is empty while the first blue solid ellipse is full, and it will end with a cusp if step 2.a is fulfilled. Fig. 5 Motifs representing qualitatively conditions on the cascade’s main parameters (top left) optimizing the likelihood of each signaling regime. Graphical codes for the biochemical species: the triangle corresponds to input signal Y01, the ellipses to total proteins Y iT or total phosphatases E iT, and the number and direction of the arrows on the segments represent the intensity of cycle activation (if downward arrows) or cycle deactivation (if upward arrows). Color: blue is for kinase, green for phosphatase; size: total concentration of the species; texture: shaded means saturated, empty unsaturated. Drawing of motifs is detailed in Additional file 3 Using the last step of the procedure, the contour line traced around each motif follows the total proteins’ progression and start or ends with a cusp according to the presence of, respectively, second-order retroactivity or forward signaling. Moreover the flow of signal propagation is directed by arrows pointing upward or downward, according to the ei’s (i=2,3). As a matter of fact it appears that the final picture can be easily interpreted in terms of signaling regimes (jkl), with the convention that a cusp or a bottleneck in the figure contour means a successful amplitude response at the corresponding tier. Therefore one main benefit of the procedure is to automatically turn the parameter conditions analyzed in last section, into qualitative motifs which are easy to read out in terms of their signaling properties. Conversely, these patterns are easier to remember than a list of conditions, and can thus be used as a tool to recover the criteria for each of signaling schemes. In conclusion, these pictures show that retroactivity is promoted by four features: the last tier is deactivated (ei>1), the second active protein is sequestrated, the second phosphatase is non-saturated and the third inactive protein is not sequestrated. In particular, second-order retroactivity is enhanced if the first protein is saturated, and the input signal and the first phosphatase are not; inversely for first-order retroactivity. A forward response (l=1) is (most likely) negligible if the last active protein is not sequestrated by its phosphatase (E3T≪Y3T). On the other hand, regime (001) is favored by a saturated phosphatase at the second tier. Discussion Kinase cascades are a key component of the living cell systems biology. Relying on several biochemical parameters, the standard functioning of a cascade is to transmit forward signals between the top and the bottom of the pathway. Nevertheless, the possibility of transmitting information backward in the cascade, due to sequestration effects of the enzymes, has been demonstrated by several studies (see Background). However, the backward – or what we called retroactive – signaling is not considered in the current literature as a standard property that cascades should possess or avoid. Therefore our main question, that was raised at the start of this paper, was to study how cascade parameters match when promoting one or the other mode of signaling. How similar or different were the parameter sets that enabled forward or retroactive signaling? Were they incompatible? Could we characterize these parameter sets in terms of biochemical concepts such as enzymatic cycle activation, enzyme saturation or sequestration? These questions were theoretically approached with analytical and numerical methods. Both ways showed advantages and limitations. One advantage of the analytical trail was to enable a study of the dose-response function for cascades with arbitrary length n. With this general approach, however, we usually had to limit our analysis to homogeneous cascades (i.e. same parameters at each tier), although some results can be generalized to inhomogeneous parameters. Nevertheless we showed that the dose-response function could be represented as the iteration of an explicit rational function. This iterative structure allowed us to compute analytical properties of the response function, like for example its first and second derivatives at the origin. These computations, together with the determination of a lower bound of the maximal value of the response function, revealed to be invaluable in discussing conditions on the biochemical parameters that optimize forward signaling in homogeneous cascades. These results, summarized on Table 1, were corroborated later by the numerical computations, that explored also cascades with inhomogeneous parameters. However, contrary to the dose-response curve, the analytical study of the drug-response function was out of reach with our analytical tools. Thus the advantage of the considered numerical approach was to extend our analytical investigation to inhomogeneous cascades, and to study the drug-responses and retroactivity properties. As the number of parameters increases with the length of the cascade, one limitation of this approach, however, was to focus only on the case of a 3-tier cascade. The methodology was based on a random scan of the parameter space of such cascades, and a subsequent classification of parameter ranges according to their ability to produce dose-response or drug-response curves satisfying minimal criteria (e.g. regarding the response amplitudes). A bayesian analysis of a set of dimensionless parameters (ratios of two biochemical parameters) allowed us to infer biochemical conditions favoring a specific signaling regime. In what concerns the forward signaling regime, although both analytical and numerical approaches are very different, they point towards the same conditions, as reported in Table 1. In this table the second column reports analytical conditions enhancing forward signaling in a homogeneous cascade, whereas the third column describes conditions maximizing the likelihood of inhomogeneous parameters relative to the forward signaling regime. The obtained conditions are found to be compatible in all cases, sometimes with some dependence of the cascade layer. In particular: (i) the affinity of the substrate for the kinase should be larger than its affinity for the phosphatase, creating what we call enzymatic asymmetry, (ii) the phosphatases should be in small amount compared with their total substrate, and (iii) the maximal rate of phosphorylation should be larger than the maximal rate of the dephosphorylation. In the context of theoretical studies of signaling systems, the use of random scans of biochemical parameters, in order to determine parameter ranges or conditions giving a sought property, has been considered by several authors. Typically these authors uniformly scanned dimensional parameters [21–23], or dimensionless parameters [12, 24, 25]. Often, the use of dimensionless parameters is motivated by a procedure of non-dimensionalization of the kinetic or of the steady state equations. In our study, we chose a random sampling of dimensional parameters. We believe that in general it leads to a better interpretration of the results. The reason is that if we start by scanning the dimensionless parameter space then, because of the change of variables between the dimensionless and dimensional parameters, then a uniform probability distribution of the dimensionless parameters is transformed into a non-uniform density for the dimensional parameters. Then the conclusions drawn from the statistical results must be associated with some non-uniform distribution of dimensional parameters. These non-uniform distributions might be non-trivial to figure out, and overall rather arbitrary, as there exist several ways to design non-dimensionalizing procedures. Therefore, although in our methodology we statistically analyze a set of dimensionless parameters in view of biochemical interpretation, dimensional biochemical parameters were first randomly sampled (in log-uniform distribution), the dimensionless parameter being deduced afterwards from these samplings. In our study, amongst the 18 sampled biochemical parameters, 12 dimensions corresponded to chemical concentrations and 6 dimensions to reaction rates (with dimension of inverse of time). They were all chosen in the interval [10−2,102], thus considering 4 orders of magnitude [−2,2] in uniform log10 scale. The interpretation of the results depends yet on the choice of the reference unit concentration (the “0" in log scale). For example, if the reference dimensional concentration is chosen as 0.1 μM, this leads to interpreting the scanned intervals as the range [1 nM, 10 μM], which seems reasonable as intracellular concentrations [15]. However this is just an example and the choice of the reference unit concentration remains a degree of freedom in our numerical methodology. On Fig. 1b we reported estimated probabilities of four signaling modes of the cascade, i.e. no-signaling, forward signaling, retrosignaling, or simultaneous forward and retro-signaling. Obviously, the absolute value of these numbers depend on the arbitrary thresholds on response amplitudes, that we fixed to assess the occurence of these signaling modes. To give evidence of the effect of changing these thresholds on the probabilities of signaling, Table 2 reports the occurence frequency of the 8 considered signaling regimes, for two different choices of thresholds (distinguishing further amongst the four main signaling modes of the cascades, the cases of retroactivity of first and of second order). Although the actual numbers are different when the thresholds are increased, we observe constancies. Table 2 Probabilities of the signaling regimes according to criteria stated in Results, with 2 different choices of thresholds for the response amplitudes. Threshold 1: Δ x 1,Δ x 2>5 %, Δ x 3>50 %. Threshold 2: Δ x 1,Δ x 2>10 %, Δ x 3>75 % Regimes Probabilities (in %) Threshold 1 Threshold 2 (000) 66,11 ± 0.05 72,15 ± 0,04 (001) 19,74 ± 0.04 16,78 ± 0,04 (010) 11,35 ± 0.03 9,73 ± 0,03 (011) 1,89 ± 0.01 0,828 ± 0,009 (110) 0,474 ± 0.007 0,228 ± 0,004 (100) 0,383 ± 0.006 0,271 ± 0,005 (111) 0,035 ± 0.002 0,0068 ± 0,0008 (101) 0,027 ± 0.002 0,0087 ± 0,0009 Obviously, the most probable parameters are always the “non-signaling" cases (000), and the most probable non-trivial signaling regime is the pure forward signaling (001). Then the probability of signaling regimes always decreases markedly between the cases of retrosignaling of first and second order. In particular one observes that the probabilities of regimes (1k1), admitting both forward and retro-signaling of order 2, are the smallest ones, and get smaller and smaller with higher thresholds. Therefore as a whole, these numbers confirm the general tendency of our numerical results: system’s parameters enabling bidirectional signaling correspond to the most unlikely cases. This property can also be characterized in a quantitative way by computing the conditional probability that bidirectional signaling occurs, knowing that the system exhibits at least one regime of signaling (so excluding (000)). This conditional probability is found to be 6 % with the thresholds corresponding to column 1 of Table 2, and drops to 3 % with data in the second column. Moreover we checked that it decreases from 6 to 5 % when the uniform ranges of biochemical parameters are extended from [−2,2] to [−2.5,2.5] (data not shown). Therefore we can conclude that requiring both response amplitudes of direct and retrosignaling to be large leads to an antagonism in the parameter sets achieving both requirements. The overall combination of forward and retro-signaling appears to be still more rare. This conclusion answers one of the principal question addressed by this study. Another question addressed in Background was to characterize, for each signaling regimes, conditions on biochemical parameters that promote the corresponding regimes. We have achieved such characterization by looking, for each signaling regime, at the likelihood of dimensionless parameters associated with the concepts of enzyme saturation, enzyme sequestration, kinase/phosphatase affinity asymmetry, or enzymatic cycle activation. Here also the choice of thresholds on the amplitude responses has a mild importance on the conclusions we point out, since we highlighted parameter conditions that maximized the (normalized) likelihood of parameters, for each signaling regime. By considering higher thresholds, we have checked that we keep same ranges where the likelihood is maximized, even if the actual value of the likelihood is reduced (see Additional file 4). Therefore the obtained conditions on parameters, as reported in Results, could be useful to distinguish parameter sets optimizing the probability to get the various regimes of signaling. These conditions are graphically represented in Fig. 5, with a motif coding that is suggestive of the corresponding form of signaling. The motif can be drawn following an algorithm, which could be implemented in an automatic way, in order to facilitate the association between a set of parameters and the probable signaling regimes that could be observed with them. On the other hand, level-specific parameter conditions can be related to the probability for a distinct stage to respond or not to upstream or downstream perturbations, as claimed in our criteria (I)–(III). These graphs embody also a method to restrict parameter space in order to enhance the probability of the main modes of signaling, forward, or retroactive, or both. In order to control how the probability of each signaling regime is optimized by choosing parameter values around the likelihood maxima, we divided the ranges of all the 18 parameters in three intervals: high values, medium values, low values. Each parameter was restricted to one of the three intervals depending on where its likelihood was maximized. As there is one restriction for each parameter, the intersection of those restricted intervals could leave, at the end, no more than 0.1 % of the initial number of simulation sets. The new probabilities of each regime were computed and compared with the former simulation sets in order to see how likely is a given regime if we restrict the ranges of the biochemical parameters. The results are summarized on Fig. 6 (see also Additional file 5). In a consistent way, these histograms show that the probability to observe a given signaling regime, among one of the 5 motifs of Fig. 5, is maximized by choosing parameter restrictions associated with the corresponding signaling regime. In particular we see that the optimized probabilities are much higher than in the unrestricted case (top panel). Only the probability of regimes involving both forward signaling and retroactive signaling of order 2 remains relatively small (3,7 %), which evokes once again the scarcity of bidirectional signaling. Fig. 6 We consider the 5 signaling regimes corresponding to motifs of Fig. 5, as well as associated parameter restrictions characterizing each of them (see details in Discussion). Then, each panel displays the probabilities of a given signaling regime in function of the considered parameter restrictions. Consistently, the probability to get a given signaling regime is maximized by choosing the parameter restrictions characterizing it, and this maximum is significantly higher than the probability obtained from a log-uniform distribution of biochemical parameters without any restriction (cf. first bar of the histogram, NR) Conclusion Living organisms rely strongly on biochemistry. Indeed signaling pathways are meant to transduce physical or chemical stimuli of the external world, relevant to living cells, into variations of activated biochemical species. In this paper, in addition to the common dose-response of a signaling cascade, we have also considered the bottom-up drug-response that discloses, when it exists, a retroactive capability of the signaling cascade. Thus signaling cascades can be categorized into 4 modes of responses, according to the existence or not of forward or of retroactive responses. An example of this classification with estimated probabilities was given in Background in Fig. 1b. This result was further discussed in the previous section. Although the quantitative aspects of our classification depends on some arbitrariness (e.g. thresholds of the amplitude responses for categorization, or the method of random scan, discussed below in Methods), our work confirmed the initial intuition that was exposed in Background: there is an opposition between the parameter sets of the cascade that promote forward (i.e. usual) signaling, and parameters that enable retroactive regimes, i.e. backward signaling. Thus our main conclusion is that the parameter sets allowing both modes of responses, forward and retroactive, occur rarely. Actually, signaling cascades are generally studied uniquely for their forward signaling ability. For instance in cancer etiology, attention is focused on over-activation of kinases in signaling pathways involved in cell proliferation, such as Mitogen Activated Protein Kinase cascades (MAPK). When these cascade pathways are deregulated in this manner, this means that their forward signaling properties are very effective. Moreover in this case, cancer therapies are based on kinase inhibition, which is described by the drug binding term in our mathematical modeling. Therefore, our main result conforts the point of view that in using these therapies, retroactive properties of signaling cascade can be neglected most of the time, eventhough rare off-target effects should not be excluded [12]. On the other hand, henceforth our work prompts the study of those signaling pathways that are overlooked a priori, because ineffective for forward signaling. Our analysis opens the perspective that such systems possibly hide some usefulness in controlling pathways, due to their qualities of retrosignaling. These properties could prove interesting in the fields of drug design or synthetic biology. Indeed we showed that in signaling cascades, novel functionalities can appear precisely in conditions where the biochemical system seems inoperant for forward signaling. Methods The mathematical model The kinetic description of the system illustrated in Fig. 1a is deduced by applying the law of mass action to the following reaction scheme (1≤i≤n): 10a Yi0+Yi−11⇌ai0di0Ci0→ki0Yi1+Yi−11 10b Yi1+Ei⇌ai1di1Ci1→ki1Yi0+Ei 10c Yn1+D⇌aDdDC We assume that both the activation reaction (10a) and the inactivation reaction (10b) are enzymatic and irreversible. We denote Y the protein (kinase), C the enzyme-substrate complex, and E the phosphatase, in each cycle. The lower index i=1,…,n states the cascade level; while the upper indices 0 and 1 refer to variables parameters involved, respectively, in the activation and deactivation reactions. Notably, at any level i, protein Yi is found in either its inactivated or activated form, denoted by Yi0 or Yi1, respectively (the upper index can be interpreted e.g. as the absence “0” or the presence “1” of a phosphate group bound to Yi). The system of non-linear ordinary differential equations (ODEs) corresponding to the kinetic reactions in (10) is given by (1≤i≤n): 11a dCi0dt=ai0Yi0Yi−11−(di0+ki0)Ci0 11b dCi1dt=ai1Yi1Ei−(di1+ki1)Ci1 11c dCDdt=aDYn1D−dDCD 11d dYi0dt=−ai0Yi0Yi−11+di0Ci0+ki1Ci1 11e dYi1dt=−ai1Yi1Ei+di1Ci1+ki0Ci0−ai+10Yi+10Yi1+(di+10+ki+10)Ci+10, with an+10=aD, Yn+10=D, dn+10=dD, kn+10=0, and Cn+10=CD. Steady states are obtained by setting the ODEs to zero and using the conservation laws (1≤i≤n): 12a EiT=Ei+Ci1,Y0T=Y01+C10,DT=D+CD, 12b YiT=Yi0+Yi1+Ci0+Ci1+Ci+10,withCn+10=CD. From the sum of (11a) and (11d), we get ki0Ci0−ki1Ci1=0. From (11a) we have Ci0=Yi−11Yi0Ki0; from (11b) and the first equation of (12a) we obtain Ci1=EiTYi1Ki1+Yi1, where we have defined the Michaelis-Menten constants Kij=(dij+kij)/aij, for j={0,1}. In particular, for i=1, using the second conservation law of (12a), we can write C10=Y0TY10K10+Y10. Also, combining (11c) with the third equation of (12a), we get CD=DTYn1KD+Yn1, where we have defined the drug dissociation constant KD=dD/aD. Hence, we end with the following system of 2n+2 steady-state equations (1≤i≤n): 13 ki0Yi−11Yi0Ki0−ki1EiTYi1Ki1+Yi1=0YiT=Yi0+Yi1+Yi−11Yi0Ki0+EiTYi1Ki1+Yi1+Y11Yi+10Ki+10Y0T=Y01+Y0TY10K10+Y10CD(KD+Yn1)−DTYn1=0. In particular, we work out the second Eq. 13 with the aim of making it dependent on only one variable, e.g. Yi1. We replace in the order: Yi0=Ki0Yi−11Ci0, Ci0=ki1ki0Ci1, and Ci1=EiTYi1Ki1+Yi1. Then we divide by the total protein YiT to get 1=Ki0Yi−11ki1ki0EiTYiTYi1Ki1+Yi1+ki1ki0+1EiTYiTYi1Ki1+Yi1+Yi1YiT+ki+11ki+10Ei+1,TYiTYi+11Ki+11+Yi+11. We finally recover the dimensionless variables xi=Yi1/YiT (i.e. the normalized active proteins), and introduce the dimensionless parameters ai, bi, ci, and ei defined by Eq. (2). Hence, it follows 14 xi−1=bieixi(xi+ai)1−xi−ei+1xi+1xi+1+ai+1−cixi,1≤i≤n, such that: 15 x0=1−x1s(x1+a1),withs=k10Y0Tk11E1T,xn+1=xn,an+1=aD,en+1=dT. These latter equalities come from the particular cases of i=1 and i=n, to obtain which we replace, respectively, C10=Y0TY10K10+Y10 and CD=DTYn1KD+Yn1, into the second equation of system (13). Explicitly, we can express Eq. 13 as system (1), then more compactly as (3). Calculation of the first derivative of xn(s) In the two following sections, we derive the general expressions of slope and curvature of the dose-response function for arbitrary biochemical parameters and cascade length. Let us consider the following general system defined by recursion: 16 zi−1=Fi(zi), where zi=xiyi and Fi=figi, for 1≤i≤n. By iterative application, we can write z0 as a function of zn, i.e.z0=F1∘F2∘…∘Fn(zn), and in particular calculate its first derivative with respect to variable xn, according to the chain rule: 17 z0′=∏1≤i≤nJi(zi)·zn′, where zi′=dzidxn, and Ji=∂fi∂xi∂fi∂yi∂gi∂xi∂gi∂yi is the jacobian matrix associated to the general dynamical system (16). Let us now suppose that for 1<i≤n, fi:zi↦bieixi(xi+ai)1−xi−ei+1yiyi+ai+1−cixi, and gi:zi↦xi (1≤i≤n) and set z0=sx1. Thus, J1=∂f^1∂x1∂f^1∂y110 (cf. Eq. 3) and Ji=∂fi∂xi∂fi∂yi10, for 1<i≤n (assuming en+1=dT=0, so f^n coincides with fn). It follows that the first component of z0′, i.e.s′(xn)=dsdxn, is given by 18 s′(xn)=(10)·∏1≤i≤nJi(xi,xi+1)·10. The slope of the dose-response function xn(s) at the origin is simply obtained by inverting expression (18) over the biologically relevant domain [0,α), evaluating it in s=0. Hence, we get 19 xn′(0)=a11+b1∏2≤i≤naibiei=K11Y1T+K10∏2≤i≤nki0Yi−1,TKi1ki1EiTKi0. Let us note that this formula is derived for an arbitrary cascade with inhomogeneous parameters, describing the contribution of any system’s parameter to the slope of the dose-response function. In particular, for homogeneous parameters, the initial slope is given by Eq. 8. Calculation of the second derivative of xn(s) Let us assume that z0(xn) is a twice differentiable function and let Ji be the jacobian matrix and Hfi=∂2fi∂xi2∂2fi∂xi∂yi∂2fi∂xi∂yi∂2fi∂yi2andHgi=∂2gi∂xi2∂2gi∂xi∂yi∂2gi∂xi∂yi∂2gi∂yi2 the hessian matrices associated to (16). Deriving expression (17) with respect to xn once again, we find z0′′=∏1≤i≤nJi(zi)·zn′′+∑0≤j<n∏0≤i≤jJi(zi)·∏k=j+2nJk(zk)·zn′T·Hfj+1(zj+1)·∏k=j+2nJk(zk)·zn′∏k=j+2nJk(zk)·zn′T·Hgj+1(zj+1)·∏k=j+2nJk(zk)·zn′ with J0=I2 (the identity matrix 2 × 2). By selecting the first component of z0″, denoted s″(xn), we calculate the inverse function through the relation xn′′(s)=−s′′(xn)(s′(xn))3. Although the evaluation of xn″(s) at the origin makes the expression simpler, the general formula for arbitrary n still remains cumbersome, and symbolic computations (e.g. with Maple™) are necessary. As an example, for n=3 and homogeneous parameters, the initial curvature is given in Eq. 9. We remark that, with respect to the initial slope xn″(0) depends on the whole parameter set ai,bi,ci, and ei. Proof of the lower bound We demonstrate here that, for homogeneous cascades of arbitrary length n, the value of the maximum response α for large stimulus s is lower bounded by the strictly positive fixed point x∗ of the equation xi−1=f(xi,xi+1), whenever it exists, with f being defined in (1b). We firstly rewrite system (14) as 1=f(x1,x2)xi−1=f(xi,xi+1),1<i<nxn−1=f(xn,0) where we have considered s→+∞ (implying x0 tending to 1 from (15)) and dT fixed to 0 (without loss of generality). Let us suppose the claim is false, that is xn<x∗. By considering the partial derivatives of f(x,y), one can prove that f is increasing in y for all x, and increasing in x for y=0 or y=x∗. In fact, from (1b) one calculates ∂f∂y=abex(x+a)(y+a)2(x+a)(1−x−ey/(y+a))−cx2 which is always positive, and ∂f∂x=bea(1−ey/(y+a))+x2(x+a)(1−x−ey/(y+a))−cx2 which is positive if and only if a(1−ey/(y+a))+x2>0. For y=0 the proof is immediate. For y=x∗, we consider the fixed point equation x∗=bex∗(x∗+a)(1−x∗−ex∗/(x∗+a))−cx∗>0 which implies that the denominator must be positive. Thus, in particular 1−x∗−ex∗/(x∗+a)>0 is sufficient and necessary for the positiveness of ∂f∂x(x,x∗). Hence, we obtain f(xn,0)<f(xn,x∗)<f(x∗,x∗), namely xn−1<x∗. Then, f(xn−1,xn)<f(xn−1,x∗)<f(x∗,x∗), i.e.xn−2<x∗. Eventually it follows 1=x0<x∗. However, from (7) one can verify that x∗≤1. Therefore, our claim x∗≤xn must be true. □ The forward signaling regime with homogeneous parameters In this section, we derive the parameter ranges optimizing the dose-response of a homogeneous cascade, as summarized in Table 1 in Results. As shown in Fig. 3, we work on an analytical piecewise approximation of the dose-response curve (cf. (4) and (5)) based on the initial slope σ, the initial curvature χ, and the asymptotic value α which we proved to be lower bounded by the fixed point x∗ of function fn−1 (cf. system (3)). We analyze the case for n=3. In general, we remark that the forward signaling is enhanced for dT=0, namely when no fraction of the last active protein gets sequestrated by the drug. We firstly study the sign of the initial curvature χ, according to the criteria of efficient forward signaling introduced in Results. From (9) we see that the sign is controlled by the terms a+b (a+c−1)−1, a+b (a+c−1) and a+c−1. In particular, χ results to be non-positive if a>1. Furthermore, for the criterion above mentioned, the slope and the fixed point have to be as large as possible. Thus, from (8) we require a≫be and b<1, and then x∗ in (7) is maximized if it also yields e≪1 and c≪1 (from which it follows ET/YT≪1, cf. Table 1). Conversely, the positiveness of χ is assured by the condition a+b (a+c−1)<0 (i.e.a/b+a+c−1<0 implying a+b (a+c−1)−1<0 and a+c−1<0 too), which is actually satisfied if a≪b and a,c≪1. Moreover, χ has to be maximized through the term a1+babe4 in Eq. 9, namely if a≫be and b<1. Eventually, all these conditions ensure x∗ to be already maximized. Random sampling of parameters Although we could achieve some analytical results in the previous sections, these latter are mainly concerned with the regimes of forward signaling (jk1), j,k∈{0,1} in cascades with homogeneous parameters. To go further we perform numerical investigations by randomly sampling the full parameter space, and then classify statistically all the parameter sets according to some characteristics of the response functions they give rise to. The objective is to point out the typical values of parameter that favor one of the 7 signaling regimes (jkl)≠(000). The main tool which is considered below is to seek for parameter conditions that maximize the so-called likelihood of the parameters in the various regimes (cf. Eq. (21) below). As we want to look for conditions on parameters that can be formulated in terms of dimensionless parameters, we consider ratios of biochemical parameters to be analyzed. On the other hand we first sample the following 20 biochemical parameters: total phosphatases EiT, total kinases YiT, Michaelis-Menten constants ki0, ki1, catalytic rates ki0, ki1. The 20 biochemical parameters were sampled in logarithmic scale, uniformly in the range 10−2 to 102 generating 1.000.000 sets, using Latin hypercube method [26, 27]. This technique consists in dividing the hyperspace ℝ20 into 1.000.000 intervals for each parameter. A random set is formed by selecting one random interval for each parameter without replacement, and with those values, constructing one set of values for the 20 different biochemical parameters we focused on. This method guarantees an exhaustive exploration of the hyperspace. As the Michaelis-Menten constants are parameters which condense information in equilibrium for enzymatic cycles but no dynamic rates, sampling this constants means an extra degree of freedom to choose some of the dynamic rates, in this work we choose dij=1 and use Kij to compute aij=dij+kijKij, for 1≤i≤n, j∈{0,1}. Finally, with all the dynamic rates, we solved the ODEs for two different scenarios: Stimulus→+∞, Drug=0 Stimulus→+∞, Drug→+∞ To take into account the condition Stimulus→+∞ we replaced, for the first cycle, Eq. (11d) by dY10dt=0 and Eq. 11a by dC10dt=C11k11−C10k01 (see Additional file 6). Those replacements amount to remove the inactive protein in cycle 1 because, when Stimulus→+∞, this protein is either in its active state or in the complexes C1j. About the second scenario, if Drug→+∞ the protein in cycle 3 is all bound to the drug. Therefore from (11), we remove the equations for cycle 3 and set Y3j=0 on the equation for the second cycle that is coupled to Y3j. With all this information, for each set of random parameters we solved the ODEs for the two scenarios, the initial condition of the system being: Y10=0,C10=Y1T/2,C11=Y1T/2Y20=Y2TY30=Y3T We remark that for infinite stimulus, there is no Y10 and then the initial condition is equally distributed in the intermediate complex C1j. After we solved the ODEs, we computed the following dimensionless output variables: △x1=x1(dT→+∞,s→+∞)−x1(dT=0,s→+∞),△x2=x2(dT→+∞,s→+∞)−x2(dT=0,s→+∞),△x3=x3(dT=0,s→+∞)−x3(dT=0,s=0). These three dimensionless outputs are the second order retroactivity, first order retroactivity, and forward activity, respectively. The numerical simulation also computes slope, curvature, and fixed point using (19), (9), and (7), respectively. The likelihood of parameters for each signaling regime In this study we consider two types of parameters, either dimensional or dimensionless. The dimensional set involves total concentrations of kinases and phosphatases, Michaelis-Menten constants and catalytic rates for the enzymatic reactions. The dimensionless set involves combinations of parameters that appear when solving the dynamical equations for the steady-states, and also ratios of parameters with the same units (ratios of rates, ratios of concentrations, etc). For each dimensionless parameters (denoted generically by λ) and for each regime (jkl), we construct the following probability using Bayes theorem: 20 P(jkl|λ)=P(λ|jkl)P(jkl)P(λ) with P(jkl|λ) being the probability of finding the signaling regime (jkl), given some specific parameter value λ, P(λ|jkl) the probability distribution of parameter λ given a specific signaling regime, P(jkl) the probability to obtain each regime and P(λ) the probability distribution of parameter λ, whatever the regime. The last one is obtained analytically as a sum of 2 (or 4) uniform distributions. Let us note that when (jkl) is fixed, the function P(jkl|λ) is not a probability distribution over λ, but is called the likelihood of λ, for a given regime (jkl), see [28]. One main goal of our numerical simulations is to draw and to compare the curves of normalized likelihoods, defined by: 21 Ljkl(λ)=P(jkl|λ)maxλP(jkl|λ) The reason why we normalize by the the maximum is that the maximum probability of each regimes can be quite different (see Table 1 in Additional file 1, and Fig. 1b where the probability of each regime P(jkl) is shown). Therefore a rational criterion to characterize parameter values that promote a given signaling regime (jkl) is to look for values which maximize the corresponding likelihood function. Then, considering signaling cascades with inhomogeneous parameters, simulations of the dose-response curves and of the drug-response curves were done for 1.000.000 random sets of biochemical parameters. The histograms of parameters were classified according to the 8 different regimes. Then, using Eq. 20, the likelihood functions of the considered dimensionless parameters were drawn on separate graphs for all possible regimes (Fig. 4 and Additional file 2). Let us remark that, despite the large number of samplings, we observe that some signaling regimes are rare. Therefore we computed error bars for all the likelihood curves. For each specific signaling regime the error bars were constructed on the parameter histogram by using a binomial probability p of being in the i-th bin and 1−p of being in another bin. Then using error propagation formula for Bayes relation (20) we obtained the error of each parameter curve. Additional files Additional file 1 The inverse iterative map. (PDF 88.9 kb) Additional file 2 Likelihood curves and maxima. (PDF 483 kb) Additional file 3 Graphical representation of the signaling regimes. (PDF 1290 kb) Additional file 4 Threshold robustness. (PDF 249 kb) Additional file 5 Table of probabilities of signaling regimes. (PDF 56.5 kb) Additional file 6 Infinite drug and infinite stimulus limits. (PDF 77.9 kb) Abbreviations LHSLatin hypercube sampling MAPKMitogen-activated protein kinase ODEOrdinary differential equation Acknowledgements We thank Maria Eugenia Szretter and Elisabeth Pécou-Gambaudo for helpful discussions. Funding SC benefits of a PhD grant funded by the French national agency CNRS and by the program “Emploi Jeunes Doctorants" of the Région Provence-Alpes-Côte d’Azur (PACA). ACV is a member of the Carrera del Investigador Cientifico (CONICET). Work was supported by Grant PICT2013-1301 from the Argentinian Agency of Research and Technology (to ACV). The international program of scientific collaboration PICS 05922 between CNRS (France) and CONICET (Argentina) supported this work. Availability of data and materials The data corresponding to the random set of parameters can be available from the authors upon request. Authors’ contributions JAS and ACV conceived the study. SC took care of the analytical part and JPD of the numerical simulations and statistical treatment. All authors analyzed the results. SC and JAS wrote the manuscript (ACV the Background) and all authors edited and approved the manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethical approval and consent to participate Not applicable. ==== Refs References 1 Li D. A special issue on cell signaling, disease, and stem cells. Cell Res. 2012; 22(1). doi:10.1038/cr.2012.7. 2 Alberts B Johnson A Lewis J Raff M Roberts K Walter P Molecular Biology of the Cell 2002 New York Garland Science 3 Blüthgen N Bruggeman FJ Legewie S Herzel H Westerhoff HV Kholodenko BN Effects of sequestration on signal transduction cascades FEBS J 2006 273 5 895 906 10.1111/j.1742-4658.2006.05105.x 16478465 4 Ortega F Acerenza L Westerhoff HV Mas F Cascante M Product dependence and bifunctionality compromise the ultrasensitivity of signal transduction cascades Proc Natl Acad Sci U S A. 2002 99 3 1170 5 10.1073/pnas.022267399 11830657 5 Thattai M van Oudenaarden A Attenuation of noise in ultrasensitive signaling cascades Biophys J 2002 82 6 2943 50 10.1016/S0006-3495(02)75635-X 12023217 6 Ventura AC Sepulchre JA Merajver SD A hidden feedback in signaling cascades is revealed PLoS Comput Biol 2008 4 3 1000041 10.1371/journal.pcbi.1000041 7 Del Vecchio D Ninfa AJ Sontag ED Modular cell biology: retroactivity and insulation Mol Syst Biol 2008 4 161 161 18277378 8 Ventura AC, Jackson TL, Merajver SD. On the role of cell signaling models in cancer research. 2009. doi:10.1158/0008-5472.CAN-08-4422. 9 Ventura AC Jiang P Van Wassenhove L Del Vecchio D Merajver SD Ninfa AJ Signaling properties of a covalent modification cycle are altered by a downstream target Proc Natl Acad Sci U S A. 2010 107 10032 7 10.1073/pnas.0913815107 20479260 10 Kim Y Paroush Z Nairz K Hafen E Jiménez G Shvartsman SY Substrate-dependent control of MAPK phosphorylation in vivo Mol Syst Biol 2011 7 467 467 21283143 11 Ossareh HR Ventura AC Merajver SD Del Vecchio D Long signaling cascades tend to attenuate retroactivity Biophys J 2011 100 7 1617 26 10.1016/j.bpj.2011.02.014 21463574 12 Wynn ML Ventura AC Sepulchre JA Garcia HJ Merajver SD Kinase inhibitors can produce off-target effects and activate linked pathways by retroactivity BMC Syst Biol 2011 5 156 10.1186/1752-0509-5-156 21970676 13 Sepulchre JA Merajver SD Ventura AC Retroactive signaling in short signaling pathways PloS ONE 2012 7 7 40806 10.1371/journal.pone.0040806 14 Sepulchre JA Ventura AC Intrinsic feedbacks in MAPK signaling cascades lead to bistability and oscillations Acta Biotheoretica 2013 61 1 59 78 10.1007/s10441-013-9177-5 23400325 15 Huang CYF Ferrell JE Ultrasensitivity in the mitogen-activated protein kinase cascade PNAS 1996 93 19 10078 83 10.1073/pnas.93.19.10078 8816754 16 Jiang P Ventura AC Sontag ED Merajver SD Ninfa AJ Del Vecchio D Load-induced modulation of signal transduction networks Sci Signal. 2011 4 194 67 7 10.1126/scisignal.2002152 17 Jesan T Sarma U Halder S Saha B Sinha S Branched motifs enable long-range interactions in signaling networks through retrograde propagation PloS ONE 2013 8 5 1 12 10.1371/journal.pone.0064409 18 Rácz E Slepchenko BM On sensitivity amplification in intracellular signaling cascades Phys Biol 2008 5 3 36004 10.1088/1478-3975/5/3/036004 19 Feliu E Knudsen M Andersen LN Wiuf C An algebraic approach to signaling cascades with N layers, Bull Math Biol 2011 74 1 45 72 10.1007/s11538-011-9658-0 21523510 20 Gomez-Uribe C Verghese GC Mirny LA Operating regimes of signaling cycles: statics, dynamics, and noise filtering PLoS Comput Biol 2007 3 12 246 10.1371/journal.pcbi.0030246 21 Qiao L Nachbar RB Kevrekidis IG Shvartsman SY Bistability and oscillations in the huang-ferrell model of mapk signaling PLoS Comput Biol 2007 3 9 1819 26 10.1371/journal.pcbi.0030184 17907797 22 Chen C Cui J Lu H Wang R Zhang S Shen P Modeling of the role of a bax-activation switch in the mitochondrial apoptosis decision Biophys J. 2007 92 4304 15 10.1529/biophysj.106.099606 17400705 23 Chiang AWT, Liu WC, Charusanti P, Hwang MJ. Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters. BMC Syst Biol. 2014; 8(4). doi:10.1186/1752-0509-8-4. 24 Shah NA, Sarkar CA. Robust network topologies for generating switch-like cellular responses. Comput Biol. 2011; 7(6). doi:10.1371/journal.pcbi.1002085. 25 Mai Z, Liu H. Random parameter sampling of a generic three-tier mapk cascade model reveals major factors affecting its versatile dynamics. PLoS ONE. 2013; 8(1). doi:10.1371/journal.pone.0054441. 26 McKay MD Beckman RJ Conover WJ Comparison of three methods for selecting values of input variables in the analysis of output from a computer code Technometrics 1979 21 2 239 45 27 Inman RL Helson JC Campbell JE An approach to sensitivity analysis of computer models: Part i - introduction, input variable selection and preliminary variable assessment J Qual Technol 1981 13 3 174 83 28 MacKay DJC. Information Theory, Inference, and Learning Algorithms David J.C. MacKay. 2005; 100:31–3. doi:10.1198/jasa.2005.s54.

PMC005xxxxxx/PMC5000545.txt

==== Front Life SciLife SciLife Sciences0024-32051879-0631Elsevier S0024-3205(16)30119-910.1016/j.lfs.2016.02.069ArticleEvidence for biased agonists and antagonists at the endothelin receptors Maguire Janet J. jjm1003@medschl.cam.ac.ukExperimental Medicine and Immunotherapeutics, Level 6 ACCI, Box 110 Addenbrooke's Hospital, Cambridge CB2 0QQ, UK15 8 2016 15 8 2016 159 30 33 30 10 2015 22 1 2016 16 2 2016 © 2016 The Author2016This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Biased ligands represent a new strategy for the development of more effective and better tolerated drugs. To date there has been a paucity of research exploring the potential of ligands that exhibit either G protein or β-arrestin pathway selectivity at the endothelin receptors. Re-analysis of data may allow researchers to determine whether there is existing evidence that the endogenous ET peptides or currently available agonists and antagonists exhibit pathway bias in a particular physiological or disease setting and this is explored in the review. An alternative to molecules that bind at the orthosteric site of the ET receptors are cell penetrating peptides that interact with a segment of an intracellular loop of the receptor to modify signalling behaviour. One such peptide IC2B has been shown to have efficacy in a model of pulmonary arterial hypertension. Finally, understanding the molecular pathways that contribute to disease is critical to determining whether biased ligands will provide clinical benefit. The role of ETA signalling in ovarian cancer has been delineated in some detail and this has led to the suggestion that the development of ETA G protein biased agonists or β-arrestin biased antagonists should be explored. Graphical abstract Pathway bias at the ET receptors. Keywords G protein coupled receptorsEndothelinETAETBBiased agonismBiased antagonismβ-ArrestinBosentanPathway selectivityIRL1620 ==== Body 1 Introduction Our understanding of how ligands interact with G protein coupled receptors is evolving, particularly the recognition that some have the ability to preferentially activate a subset of intracellular signalling cascades – so called pathway biased ligands [1]. Additionally, it is now accepted that recruitment of β-arrestin that occurs following activation of the majority of GPCRs not only results in receptor desensitisation and subsequent internalisation but may also contribute to cellular responses involved in normal physiology and disease such as cell migration and proliferation [2]. Therefore, exploiting ligand bias is likely to lead to the development of more effective and better tolerated medicines. This has so far been most clearly demonstrated for the μ opioid receptor where the agonist TRV130, a molecule that discriminates between beneficial analgesia and detrimental adverse effects such as respiratory depression and nausea, exhibited an improved therapeutic profile compared to morphine in a randomized, double-blind, placebo-controlled, crossover study in healthy volunteers [3]. Whereas bias has been considered a property of synthetic ligands it has recently been reported that for example endogenous opioids also show bias at the μ-opioid receptor [4] indicating that the presence of multiple ligands for a receptor, rather than simply representing physiological redundancy, may allow for nuanced cell specific signalling. Distinct roles for the three endogenous endothelin (ET) peptides are emerging in development and in, for example, ovarian physiology but whether pathway bias may contribute to the physiology and pathophysiology of the endogenous peptides in the ET system has not been explored. In contrast the potential for targeting the endothelin receptors with synthetic biased ligands is starting to be considered. This brief review discusses current research on biased signalling at the ET receptors and therapeutic areas of interest. 2 ET receptors and probe dependence Some of the pharmacology of the endothelin receptors has over the last 20 years been described as atypical; not conforming to the basic tenets of receptor pharmacology. Particularly, this has been in differences in the behaviour of the endogenous peptides and synthetic agonists with respect to reversal by washout or blockade/reversal of responses by antagonists in in vitro studies [5], [6]. It is now apparent that for a particular receptor multiple active conformations, rather than just one, are possible and ligands can stabilize different conformations of a receptor that may activate subsets of available down-stream pathways. Therefore, some of the atypical pharmacology reported for ET receptors may be consistent with these agonists showing a degree of functional selectivity, although differences in ligand-receptor kinetics may also contribute to these observations. Additionally, because of the allosteric nature of the interaction of ligand–GPCR–intracellular protein (e.g. G protein) affinity measured in binding assays may differ from affinity measured in functional assays, specifically if different agonists stabilize particular receptor conformations then this allows the potential for orthosteric antagonists to demonstrate agonist specific functional affinities – consistent with previously reported atypical pharmacology of probe dependence [7]. 3 Calculating ligand bias for the endogenous ET peptides and related sarafotoxin 6b at the ETA receptor There has been at least one report in vitro that ET peptides exhibit bias at the ETA receptor with ET-1 and ET-2 suggested to elicit their long lasting constrictor responses via different mechanisms that was also vascular bed dependent [8]. We have previously published data on both the potency and efficacy of endothelin peptides and sarafotoxins as constrictors of human saphenous vein [9] and in β-arrestin recruitment assays [10]. These data highlighted differences in the relative potencies and efficacies of these agonists in the ETA mediated constrictor and β-arrestin recruitment assays indicative of bias. Several methods for determining pathway bias from such data have been reported including determination of transducer coefficients τ/KA, as described by van Westhuizen and colleagues [11]. We have applied this method to our existing data to determine whether the endogenous ET peptides and related sarafotoxin 6b (S6b) show any evidence of bias in the G protein dependent vasoconstrictor assay and G protein independent β-arrestin recruitment assay. Determining bias requires designation of a reference compound that is preferably the endogenous ligand. For the cardiovascular ETA receptor the most appropriate reference ligand is ET-1. All data are expressed as a % of the maximum ET-1 response and analysed as described [10], to obtain values of log10(τ/KA) that are used for subsequent determination of bias factors. Fig. 1 shows that whilst ET-1, ET-2 and S6b are full agonists in the constrictor assay (the ET-3 curve is incomplete at the maximum possible bath concentration) ET-3 and S6b are both partial agonists in the β-arrestin assay. Compared to ET-1, all agonists tested showed a 2–4 fold bias for the G protein constrictor assay compared to the β-arrestin assay (Table 1). This preliminary analysis indicated that at least modest pathway bias for endogenous ET peptides is possible, however the physiological significance of this, if any, requires more comprehensive analysis of data for ET-1, ET-2 and ET-3 in a broader range of relevant pathway specific assays. 4 Ligand bias at the ETB receptor There are currently no published data exploring biased agonism at the ETB receptor. There are a number of ETB agonists available for study including the endogenous peptide ET-3 and related sarafotoxin 6c (S6c) in addition to peptide agonists such as BQ3020 and IRL 1620. IRL-1620 is of particular significance as it is under investigation in a number of therapeutic areas with efficacy demonstrated in animal models of stroke [12] and as an adjunct for improved delivery of chemotherapy targeting solid tumours [13]. It would therefore be of interest to determine the relative effect of these agonists in a number of disease relevant pathways, with comparison to ET-3 responses to determine evidence of bias. These types of studies may highlight any differences between the agonists investigated that could be used either to further understand the signalling of importance to disease progression or to refine clinical efficacy of drugs by reducing on target detrimental effects through defined pathway activation. 5 Do ET receptor antagonists show pathway bias? Of perhaps more consequence for the ET system is the possibility that antagonists exhibit pathway bias. This has been reported for the dual ETA/ETB antagonist bosentan. In human cloned receptors bosentan exhibits a modest 20 fold selectivity for the ETA receptor [14] and in human heart that expresses both receptor subtypes bosentan competes for the binding of [125I]ET-1 with a single affinity (KD: 78 nM) indicating that it does not distinguish between the native receptors in this tissue [15]. In human blood vessels that express predominantly ETA receptors bosentan exhibited, as expected, 2–20 fold higher affinity than in heart with KD of 32 nM in saphenous vein [16] and 3 nM in coronary artery [17]. In contrast bosentan was a much less effective antagonist than would be predicted from its binding affinity in both ETA mediated vasoconstriction in human saphenous vein and coronary artery [15], in ETB mediated smooth muscle contraction [14] and ETB β-arrestin recruitment experiments [10] with a functional affinity of about 2 μM in all these assays. Unexpectedly, in the ETA mediated β-arrestin assay bosentan was 200 fold more effective an antagonist with KB of 10 nM [10] suggesting that bosentan is an ETA β-arrestin biased antagonist. It is interesting to speculate that the relative effectiveness of bosentan in treatment of pulmonary arterial hypertension compared to its generally low potency as an antagonist in vitro may in part be explained by the greater antagonism of detrimental ETA linked β-arrestin mediated ERK1/2 signalling [18] that could contribute to smooth muscle cell proliferation in this disease. 6 Alternative strategies: cell penetrating peptides as biased antagonists Cell penetrating peptides (CPPs) are a superfamily of peptides that interact with an intracellular segment of a G protein coupled receptor and interfere with signalling [19]. Pepducins-lipidated CPPs, have been developed for over 20 GPCRs including proteinase activated (PAR1, PAR2 and PAR4) and chemokine (CXCR1, CXCR2 and CXCR4) receptors. There has been one report of a CPP, IC2B, targeting the second intracellular loop of the ETB receptor which has been shown to attenuate pulmonary Akt and ERK signalling and to blunt the development of hypoxic pulmonary hypertension in a rat in vivo model [20] that is thought to contribute to disease progression. What was most interesting is that blockade of the ETB receptor has previously been reported to enhance development of pulmonary arterial hypertension in rodents suggesting that in the study by Green and colleagues [20] IC2B may be selectively targeting those ETB pathways contributing to muscularisation of the pulmonary arterial smooth muscle. This would leave unopposed beneficial ETB receptor functions such as release of endothelial derived dilators, although this is yet to be confirmed. 7 Clinical potential of ET receptor biased ligands Is there a clinical need for ET receptor biased ligands? Evidence is strongest from research in epithelial ovarian cancer demonstrating that ET-1 stimulated ETA-mediated β-arrestin signalling leads to activation of the oncogenic mediator NF-κB [21] and that β-arrestin-1 epigenetically regulates ET-1-induced β-catenin signalling [22], [23] both contributing to tumour cell proliferation, invasion and metastasis. A β-arrestin biased ETA antagonist would be predicted to have benefit over a non-biased ETA antagonist in ovarian cancer as ETA/Gαs/cAMP activation of protein kinase A opposes the detrimental ETA/β-arrestin stimulated expression of cancer genes. ETA/Gq signalling is also oncogenic therefore an alternative strategy that may demonstrate even greater target refinement would be to develop an ETA/Gαs biased agonist as proposed by Teoh and colleagues [24] (Fig. 2). Interestingly, pepducins have been designed for the β2-adrenoreceptor that selectively promote a Gαs biased conformation [25] therefore this may be one strategy that can be applied to biased targeting of the ETA receptor in cancer. Could selective activation or inhibition of ET signalling pathways in heart failure result in clinically efficacious drugs and explain the lack of benefit of endothelin receptor antagonists in heart failure clinical trials to date, despite promising evidence from pre-clinical studies? For the angiotensin-II system it has been demonstrated that β-arrestin mediated signalling in heart failure is beneficial and selective activation of this pathway using TRV027 (and thus inhibition of G-protein signalling) promotes both vasodilatation and improved cardiac function at least in animal models [26]. This compound is currently being investigated in a Phase IIb study in patients hospitalised for acute decompensated heart failure (ClinialTrials.gov identifier NCT01966601) with estimated completion March 2016. Conversely, β-arrestin signalling in cardiac fibroblasts has been proposed to contribute to detrimental ventricular remodelling [27]. It is not known if ET receptor mediated β-arrestin signalling is protective in heart failure, but if so it could be inferred that currently available endothelin antagonists that block G-protein and β-arrestin signalling or bosentan that may be a β-arrestin biased antagonist would not produce clinical benefit and may even be detrimental. However, the lack of efficacy in heart failure trials was predominantly owing to the development of peripheral oedema, thought to be a result of effects on endothelin mediated renal salt and water homeostasis rather than a lack of beneficial effect on haemodynamics [28]. It has also been suggested that the contribution of increased ET-1 to pathological cardiac remodelling in heart failure may be a result of ETA mediated inhibition of reuptake of noradrenaline released from cardiac sympathetic nerves [29]. Consequently endothelin antagonists would not confer additional advantage in patients already taking β-blockers enrolled in these trials. Whether the beneficial and detrimental actions of endothelin antagonists in heart failure or other conditions such as hypertension could be discerned by the development of ligands with a particular signalling profile remains mere speculation at this time but should be investigated as the field matures. In summary, compared to the development and exploitation of biased ligands for other GPCRs the identification of compounds that selectively engage or block a subset of ET receptor activated signalling is only now beginning to be explored. However, the possibility that the endogenous ET peptides and currently available agonists and antagonists may show pathway bias should be considered and investigated by all those with an interest in the role of the endothelin system in health and disease. Acknowledgements This study was supported by the Wellcome Trust (grant number WT107715). We thank Papworth Hospital NHS Trust Tissue Bank for assistance. Fig. 1 Concentration response curves to ET-1 (●), ET-2 (■), ET-3 (▲) and S6b (▼) in (A) the human endothelium-denuded saphenous vein and (B) an ETA-mediated β-arrestin recruitment assay. Data are expressed as a percent of the maximum response of ET-1 in each assay and data points are the mean ± s.e.m. of 3–13 experiments. Fig. 2 Proposed role for ET-1 activation of ETA receptors in ovarian cancer (modified from [24]) and potential beneficial effects of either a Gαs biased agonist or β-arrestin biased antagonist. Table 1 Bias analysis for the relative effectiveness of endothelin peptides in the human saphenous vein constrictor and ETA-mediated β-arrestin recruitment assays. Saphenous vein constrictor assay β-Arrestin recruitment assay Saphenous vein vs β-arrestin LogR ΔLogR RE LogR ΔLogR RE ΔΔLogR Bias factor ET-1 8.55 ± 0.15 0 ± 0.22 1 9.46 ± 0.08 0 ± 0.11 1 0 ± 0.24 1 ET-2 8.26 ± 0.21 − 0.29 ± 0.26 0.51 8.67 ± 0.03 − 0.79 ± 0.08 0.16 0.49 ± 0.27 3.1 ET-3 6.80 ± 0.37 − 1.75 ± 0.40 0.018 7.11 ± 0.03 − 2.35 ± 0.08 0.0045 0.60 ± 0.41 4.0 S6b 8.11 ± 0.12 − 0.44 ± 0.12 0.36 8.68 ± 0.06 − 0.78 ± 0.10 0.17 0.34 ± 0.15 2.2 R = (τ / KA), the transducer coefficient, where τ is an index of agonist efficacy and KA is functional affinity of the agonist. ΔLogR is the relative LogR values of test agonists compared to the reference agonist in a particular assay. ΔΔLogR is the relative ΔLogR values for particular agonists between assays. The bias factor is determined as 10ΔΔLogR. Analysis performed as described by van der Westhuizen and colleagues [11]. ==== Refs References 1 Wisler J.W. Xiao K. Thomsen A.R.B. Lefkowitz R.J. Recent developments in biased agonism Curr. Opin. Cell Biol. 27 2014 18 24 24680426 2 Shukla A.K. Xiao K. Lefkowitz R.J. Emerging paradigms of β-arrestin-dependent seven transmembrane receptor signalling Trends Biochem. Sci. 36 2011 457 469 21764321 3 Soergel D.G. Subach R.A. Burnham N. Lark M.W. James I.E. Sadler B.M. Skobieranda F. Violin J.D. Webster L.R. Biased agonism of the μ-opioid receptor by TRV130 increases analgesia and reduces on-target adverse effects versus morphine: a randomized, double-blind, placebo-controlled, crossover study in healthy volunteers Pain 155 2014 1829 1835 24954166 4 Thompson G.L. Lane J.R. Coudrat T. Sexton P.M. Christopoulos A. Canals M. Biased agonism of endogenous opioid peptides at the μ-opioid receptor Mol. Pharmacol. 88 2015 335 346 26013541 5 Maguire J.J. Kuc R.E. Rous B.A. Davenport A.P. Failure of BQ123, a more potent antagonist of sarafotoxin 6b than of endothelin-1, to distinguish between these agonists in binding experiments Br. J. Pharmacol. 118 1996 335 342 8735635 6 De Mey J.G. Compeer M.G. Lemkens P. Meens M.J. ETA-receptor antagonists or allosteric modulators? Trends Pharmacol. Sci. 32 2011 345 351 21481481 7 Kenakin T. What is pharmacological ‘affinity’? Relevance to biased agonism and antagonism Trends Pharmacol. Sci. 35 2014 434 441 25042457 8 Compeer M.G. Janssen G.M.J. De Mey J.G.R. Endothelin-1 and endothelin-2 initiate and maintain contractile responses by different mechanisms in rat mesenteric and cerebral arteries Br. J. Pharmacol. 170 2013 1199 1209 23941276 9 Maguire J.J. Davenport A.P. ETA receptor-mediated constrictor responses to endothelin peptides in human blood vessels in vitro Br. J. Pharmacol. 115 1995 191 197 7647976 10 Maguire J.J. Kuc R.E. Pell V.R. Green A. Brown M. Kumar S. Wehrman T. Quinn E. Davenport A.P. Comparison of human ETA and ETB receptor signalling via G-protein and β-arrestin pathways Life Sci. 91 2012 544 549 22480514 11 van der Westhuizen E.T. Breton B. Christopoulos A. Bouvier M. Quantification of ligand bias for clinically relevant β2 -adrenergic receptor ligands: implications for drug taxonomy Mol. Pharmacol. 85 2014 492 509 24366668 12 Leonard M.G. Gulati A. Endothelin B receptor agonist, IRL-1620, enhances angiogenesis and neurogenesis following cerebral ischemia in rats Brain Res. 1528 2013 28 41 23850649 13 Rajeshkumar N.V. Matwyshyn G. Gulati A. IRL-1620, a tumor selective vasodilator, augments the uptake and efficacy of chemotherapeutic agents in prostate tumor rats Prostate 67 2007 701 713 17342753 14 Clozel M. Breu V. Gray G.A. Kalina B. Löffler B.-M. Burri K. Cassal J.-M. Hirth G. Müller M. Neidhart W. Ramuz H. Pharmacological characterization of bosentan, a new potent orally active nonpeptide endothelin receptor antagonist J. Pharmacol. Exp. Ther. 270 1994 228 235 8035319 15 Peter M.G. Davenport A.P. Characterization of the endothelin receptor selective agonist, BQ3020 and antagonists BQ123, FR139317, BQ788, 50235, Ro462005 and bosentan in the heart Br. J. Pharmacol. 117 1996 455 462 8821534 16 Maguire J.J. Kuc R.E. Davenport A.P. Defining the affinity and receptor sub-type selectivity of four classes of endothelin antagonists in clinically relevant human cardiovascular tissues Life Sci. 91 2012 681 686 22634326 17 Bacon C.R. Davenport A.P. Endothelin receptors in human coronary artery and aorta Br. J. Pharmacol. 117 1996 986 992 8851522 18 Morris G.E. Nelson C.P. Brighton P.J. Standen N.B. Challiss R.A.J. Willets J.M. Arrestins 2 and 3 differentially regulate ETA and P2 Y2 receptor-mediated cell signaling and migration in arterial smooth muscle Am. J. Physiol. Cell Physiol. 302 2012 C723 C734 22159081 19 Dimond P. Carlson K. Bouvier M. Gerard C. Xu L. Covic L. Agarwal A. Ernst O.P. Janz J.M. Schwartz T.W. Gardella T.J. Milligan G. Kuliopulos A. Sakmar T.P. Hunt S.W. G protein-coupled receptor modulation with pepducins: moving closer to the clinic Ann. N. Y. Acad. Sci. 1226 2011 34 49 21615752 20 Green D.S. Rupasinghe C. Warburton R. Wilson J.L. Sallum C.O. Taylor L. Yatawara A. Mierke D. Polgar P. Hill N. A cell permeable peptide targeting the intracellular loop 2 of endothelin B receptor reduces pulmonary hypertension in a hypoxic rat model PLoS ONE 8 2013 e81309 21 Cianfrocca R. Tocci P. Semprucci E. Spinella F. Di Castro V. Bagnato A. Rosanò L. β-Arrestin 1 is required for endothelin-1-induced NF-κB activation in ovarian cancer cells Life Sci. 118 2014 179 184 24530737 22 Rosanò L. Cianfrocca R. Masi S. Spinella F. Di Castro V. Biroccio A. Salvati E. Nicotra M.R. Natali P.G. Bagnato A. Beta-arrestin links endothelin A receptor to beta-catenin signaling to induce ovarian cancer cell invasion and metastasis Proc. Natl. Acad. Sci. U. S. A. 106 2009 2806 2811 19202075 23 Rosanò L. Cianfrocca R. Tocci P. Spinella F. Di Castro V. Spadaro F. Salvati E. Biroccio A.M. Natali P.G. Bagnato A. β-Arrestin-1 is a nuclear transcriptional regulator of endothelin-1-induced β-catenin signalling Oncogene 32 2013 5066 5077 23208497 24 Teoh J.P. Park K.M. Wang Y. Hu Q. Kimb S. Wuc G. Huang S. Maihle N. Kima I.M. Endothelin-1/endothelin A receptor-mediated biased signaling is a new player in modulating human ovarian cancer cell tumorigenesis Cell. Signal. 26 2014 2885 2895 25194819 25 Carr R. III Du Y. Quoyer J. Panettieri R.A. Jr. Janz J.M. Bouvier M. Kobilka B.K. Benovic J.L. Development and characterization of pepducins as Gs-biased allosteric agonists J. Biol. Chem. 289 2014 35668 35684 25395624 26 Ikeda Y. Kumagai H. Motozawa Y. Suzuki J. Kimuro I. Biased agonism of the angiotensin II type I receptor Int. Heart J. 56 2015 485 488 26180022 27 Li J. Philip J.L. Xu X. Theccanat T. Razzaque M.A. Akhter S.A. β-Arrestins regulate human cardiac fibroblast transformation and collagen synthesis in adverse ventricular remodelling J. Mol. Cell. Cardiol. 76 2014 73 83 25134464 28 Kohan D.E. Cleland J.G. Rubin L.J. Theodorescu D. Barton M. Clinical trials with endothelin receptor antagonists: what went wrong and where can we improve? Life Sci. 91 2012 528 539 22967485 29 Lehmann L.H. Rostosky J.S. Buss S.J. Kreusser M.M. Krebs J. Mier W. Enseleit F. Spiger K. Hardt S.E. Wieland T. Hauss M. Lüscher T.F. Schneider M.D. Parlato R. Gröne H.-J. Haberkorn U. Yanagisawa M. Katus H.A. Backs J. Essential role of sympathetic endothelin A receptors for adverse cardiac remodeling Proc. Natl. Acad. Sci. U. S. A. 113 2014 13499 13504 25197047

PMC005xxxxxx/PMC5000546.txt

==== Front Life SciLife SciLife Sciences0024-32051879-0631Elsevier S0024-3205(16)30086-810.1016/j.lfs.2016.02.036ArticleEndothelin ETA receptors predominate in chronic thromboembolic pulmonary hypertension Southwood Mark ab1MacKenzie Ross Robert V. c1Kuc Rhoda E. bHagan Guy aSheares Karen K. aJenkins David P. aGoddard Martin aDavenport Anthony P. apd10@medschl.cam.ac.ukb⁎2Pepke-Zaba Joanna a2a Papworth Hospital, Cambridge, UK,b Experimental Medicine and Therapeutics, University of Cambridge, Cambridge, UKc Royal United Hospitals, Bath, UK⁎ Corresponding author at: Experimental Medicine and Therapeutics, University of Cambridge, Level 6, Centre for Clinical Investigation, Box 110, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK.Experimental Medicine and TherapeuticsUniversity of CambridgeAddenbrooke's HospitalLevel 6, Centre for Clinical InvestigationBox 110CambridgeCB2 0QQUK apd10@medschl.cam.ac.uk1 Contributed equally as first authors. 2 Co-senior authors. 15 8 2016 15 8 2016 159 104 110 30 10 2015 21 1 2016 9 2 2016 © 2016 The Authors2016This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Aims Endothelin-1 levels are raised in chronic thromboembolic pulmonary hypertension. Our aim in this study was to identify the presence of endothelin receptors in patients with CTEPH by analysing tissue removed at pulmonary endarterectomy. Main methods Pulmonary endarterectomy tissue cross-sections were analysed using autoradiography with [125I]-ET-1 using ligands selective for ETA or ETB to determine sub-type distribution. The precise cellular localisation of ETA and ETB receptors was determined using selective antisera to both sub-types and compared with haematoxylin and eosin, Elastic Van Gieson and smooth muscle actin labelled sections. Key findings Two patterns of ET-1 binding were found. In sections with frequent recanalised channels, ET-1 bound to the smooth muscle cells surrounding the channels. In sections where there was less organised thrombus with no obvious re-canalisation, minimal ET-1 binding was observed. Some contractile type smooth muscle cells not associated with recanalised channels and diffusely spread throughout the PEA material were associated with ET receptor antibody binding on immunohistochemistry. There was a greater expression of the ETA receptor type in the specimens. Significance The presence of ET-1 receptors in the chronic thrombus in proximal CTEPH suggests ET-1 could act not only on the distal vasculopathy in the unobstructed vessels but may also stimulate smooth muscle cell proliferation within chronic clot. The abundance of ET receptors within the tissue provides evidence that the ET pathway is involved in the pathology of chronic thrombus reorganisation leading to CTEPH providing a rationale for the repurposing of ET receptor antagonists in the treatment of this condition. Keywords Endothelin-1AutoradiographyImmunocytochemistryChronic thromboembolic pulmonary hypertensionPulmonary endarterectomy ==== Body 1 Introduction At present there is a limited understanding of the factors responsible for failure of resolution of acute pulmonary embolism and the subsequent development of chronic thromboembolic pulmonary hypertension (CTEPH). The raised pulmonary vascular resistance (PVR) in CTEPH is described by a two compartment model [20]. In some regions there are thromboembolic occlusions of the vascular lumen and a series of associated changes including clot remodelling, collagen deposition and cellular hyperplasia. The ‘closed’ arterial tree distal to these obstructions is spared from exposure to high pressures. In other regions the ‘open’ arterial tree is exposed to high pressures and demonstrates pathological changes similar to those seen in pulmonary arterial hypertension (PAH); a distal vasculopathy with muscularisation of the distal precapillary arteries and intimal hyperplasia with medial hypertrophy of some larger pulmonary arteries [20]. Currently, CTEPH is the only form of pulmonary hypertension for which there is a potential cure; pulmonary endarterectomy (PEA), through the surgical removal of proximal chronic thromboembolic material [22]. Endothelin-1 (ET-1) is a potent vasoconstrictor. High levels of circulating ET-1 or its precursor big ET-1 have been demonstrated in patients with idiopathic PAH [9], [15], [29]. The ET pathway is considered an important part of the pathology of idiopathic PAH and ET receptor antagonists such as bosentan and ambrisentan [17], [18] and more recently macitentan [7] are used to try to slow progression. To date there is no ET antagonist licenced for use in CTEPH patients, although they are used ‘off-label’. The BENEFIT study did show a significant haemodynamic improvement with reduction in PVR, but no functional improvement with bosentan [11]. ET-1 acts via two receptors, ETA and ETB, which have different effects upon pulmonary artery smooth muscle cells. The ETA receptor activation results in vasoconstriction and smooth muscle cell proliferation. The ETB receptor activation prevents apoptosis of smooth muscle cells and causes vasodilatation via nitric oxide stimulation. ET-1 is a potent vasoconstrictor but is also a promoter of pulmonary artery smooth muscle cell proliferation [8]. In agreement, Quarck et al. [5] found that pulmonary arterial smooth muscle cells isolated from patients with CTEPH have enhanced proliferative properties. In patients with CTEPH, ET-1 levels are raised and have been shown to fall after PEA surgery [24]. After an acute pulmonary embolism there is obstruction of the pulmonary arteries by acute thrombus and elevated levels of ET-1 [28], [30]. Elevated levels of ET-1 have also been observed in air embolus in animal models [25], [26] and pretreatment with an ET antagonist ameliorated the haemodynamic change after acute pulmonary embolism [25]. In addition ET-1 is increased most in the muscularised pulmonary arteries [16]. Intriguingly in human coronary arteries we have previously shown that recanalisation of thrombus is characterised by formation of new vessels which show intense endothelial ET-like immunoreactivity with ETA but not ETB receptors on the smooth muscle of recanalised vessels [2]. Crucially, ET antagonists have been shown to block proliferation of smooth muscle in the intimal layer of vessels growing in organ culture [19]. The pathogenesis of CTEPH is complex but one question that arises is how much of the disease progression is driven by changes within the unresolved thrombus in parallel to the vasculopathy in the distal arterial bed. Despite many centres offering off-label use of ET receptor antagonist in the treatment of CTEPH, little is understood concerning the presence and underlying pattern distribution of ET receptors within PEA material. Here we identify ET receptors in PEA material and provide a rationale for the ET receptor antagonists for treatment of CTEPH. 2 Material and methods 2.1 Human tissue samples Human tissues were obtained with informed consent from the Papworth Hospital Research Tissue Bank (REC 08/H0304/56) and local approval (REC 05/Q0104/142). Tissue specimens were collected from consecutive patients undergoing PEA surgery for analysis. Information was collected prospectively based on factors that were considered relevant to the interpretation of the histological appearance and any ET receptor pattern. This included the use and type of targeted therapy for pulmonary hypertension prior to surgery, haemodynamics from at the time of diagnosis, the intraoperative macroscopic surgical assessment of the type of chronic thromboembolic pulmonary arterial obstruction [12] and follow up post-operative haemodynamic measurements from assessment at least 3–6 months after PEA surgery. None of the patients had prior treatment with an ET receptor antagonist (to avoid the possible influence on ET receptor expression) [10]. During the PEA surgery the tunica intima and a superficial layer of tunica media was removed along with the luminal contents. This tissue was then preserved in ice cold Krebs solution. Cross-sections were taken from the main endarterectomy cast, normally one from the most proximal portion and other samples from smaller, more distal portions of the PEA material [Fig. 1]. These samples were kept at − 80 °C and batched for autoradiographical analysis and confocal microscopy. Serial 10 μm sections were cut using a cryostat. Adjacent formalin fixed paraffin wax embedded blocks were taken for routine histological examination and immunohistochemistry. To determine the precise type of cell expressing the ET receptors, immunohistochemistry was performed to characterise the cell types that showed strong expression of the ET receptor in the ligand binding assays. 2.2 Autoradiography Autoradiography was carried out using established techniques [6], [13]. Briefly, sections were pre-incubated for 20 min at 23 °C in assay buffer (50 mM Hepes, 5 mM MgCl2, 0.3% BSA, pH 7.4) prior t, California) to determine the distribution of all ET receptors. ET receptor subtypes were visualised by incubating adjacent sections with [125I]-ET-1 (0.1 nM) alone to measure total binding, and in the presence of either 0.2 μM BQ3020 (to detect ETA) or with 0.1 μM BQ123 (to detect ETB). Receptor occupancy curves based on the known specificity of each compound were used to determine the concentration of each ligand. Non-specific binding was defined by incubating a further adjacent section with the radioligand in the presence of 1 μM unlabelled ET-1 (Peptide Institute, Osaka, Japan). Following incubation the sections were washed (3 × 5 min) in ice-cold Tris-HCl buffer (50 mM, pH 7.4), air dried and apposed, together with [125I]-ET-1 standards, to Kodak MR-1 autoradiography film for 3 days at room temperature. The films were processed and resulting autoradiograms photographed (Wild Heerbrugg microscope with Optim digital camera and Pixel Link OEM software). 2.3 Statistical tests The degree of ET binding was assessed independently by two individuals and graded on the appearance of the autoradiogram alone. Broadly this was grouped into the following groups: none, < 25%, 25%–50%, 50%–75%, > 75%. Data were analysed using GraphPad Prism and difference between groups were assessed using a Student's t-test. A p value of < 0.05 was considered significant. 2.4 Histopathology, immunohistochemistry and confocal microscopy Slides were prepared from cutting sections from each 4 μm wax embedded tissue block. After 48 h in the oven to melt the wax and dry the tissue, the slides were put in PT modules (Dako Ltd, UK) for 1 h at 98 °C for antigen retrieval. After washing (with PBS solution) the slides were exposed to hydrogen peroxidase 3% blocking solution (Dako Ltd, UK) before being washed again with PBS. The primary antibody incubations were all for one hour at room temperature. Immunolabelling was performed using polyclonal rabbit anti-human ETA receptor antibody (ab84673, Abcam plc, Cambridge, UK); polyclonal rabbit anti-human ETB receptor antibody C– terminal (ab84182, Abcam plc, Cambridge, UK), monoclonal mouse anti-human smooth muscle actin (Dako Ltd, UK) and monoclonal mouse anti-human CD31 (Dako Ltd, UK). Negative controls were incubated with EnVision Flex antibody diluent alone. Tissue sections were washed and incubated for 30 min with goat anti-mouse/rabbit secondary antibodies EnVision Flex HRP (Dako Ltd, UK), washed and labelled using Flex DAB + Chromogen (Dako Ltd, UK), washed and counter stained with Haematoxylin. The stained tissue sections were examined by a histopathologist with a special interest in pulmonary hypertension (MG). A brief description of the histological appearance for each section was made based on the degree of obstruction of the vessel lumen, the presence of smooth muscle cells within the pulmonary artery lumen, the presence of endothelialised and recanalised channels with distinct organisation of smooth muscle cells surrounding these new channels. Serial frozen sections were also used for co-localisation studies using polyclonal rabbit anti-human ETA or polyclonal rabbit anti-human ETB receptor antibody C-terminal (ab84182, Abcam plc, Cambridge, UK), incubated with goat anti-rabbit IgG conjugated Texas red (red). Cytoskeletal actin filaments [27] were labelled using alexa488 (green) conjugated phalloidin (Invitrogen, UK) and nuclei labelled using 4′,6-diamidino-2-phenylindole (DAPI; blue). 3 Results Pulmonary endarterectomy specimens from 19 patients were collected; 14 male, 5 female. The mean age was 63 ± 9.7 years. One patient died in hospital and another patient did not return for post-operative follow-up. Table 1 shows the severity of the pulmonary hypertension and includes the surgical disease type (from the classification by [12]), haemodynamics at the time of initial diagnosis and any pre-operative drug treatment. The haemodynamic variables demonstrate reasonably severe pulmonary hypertension (pulmonary vascular resistance 763 ± 377 dyn·s·cm− 5). Ten patients had received pre-operative drug treatment with a phosphodiesterase V inhibitor, sildenafil, prior to PEA surgery. Mean pulmonary artery pressure (mPAP) was higher (p = 0.024) in the sildenafil treated group (50.90 ± 9.92 mm Hg) compared to patients not on therapy (39.33 ± 10.36 mm Hg). PVR was similar between both groups. Pre-operative drug treatment did not appear to have any significant effect on ET receptor expression (data not shown). The majority of cases were Jaimeson classification type 1 or type 2. A typical example of a PEA specimen is included in Fig. 1A. § = died following PEA surgery. # = did not return for follow-up. 3.1 Histopathology of PEA material Forty three samples of tissue were taken for examination. Microscopically, the histological specimens were found to contain regions of fresh thrombus, intimal fibrosis with some degree of medial hyperplasia and organised thrombus in keeping with previous reports [4], [23]. We observed overall appearance, approximate vessel dimensions, the degree of luminal obstruction and the number of recanalised channels. Proximal PEA material was comprised predominantly of matrix-rich fibrous tissue with little evidence of recanalization (Fig. 1B). The approximate size of the native vessels examined ranged between about 40 mm and 5 mm in diameter. 6 sections were either fragments, long strips of tissue or had no discernible intimal layer. For the remaining thirty seven sections the degree of occlusion of the lumen of the native pulmonary artery was < 50% in 8 specimens, > 50% in 8 specimens, 100% occluded in 21 specimens. Unsurprisingly the smaller diameter tissue specimens displayed more intraluminal obstruction than the larger specimens. Fresh thrombus comprised fibrous tissue and loose fibromyxoid tissue with little evidence of organisation or matrix components. In more distal PEA material frequent recanalised channels were observed in many specimens, particularly evident in those of a smaller size (Fig. 1C). We next sought to the cell morphologies and to characterise the ET binding in the organising and non-organised PEA material. 3.2 Autoradiographical ET receptor binding in PEA material Recent proximal thrombus with little evidence of neovascularization demonstrated no obvious pattern of expression for ETA or ETB receptors. In contrast, the autoradiograms showed ET binding was present in the majority of the distal pulmonary endarterectomy cross-sections. Specific ET receptor binding was observed in 32 of the 43 specimens. Autoradiography showed that ETA predominated; all thirty two specimens express this sub-type. ETB binding was detected in twenty eight specimens and was more limited within the organised thrombus where ETB receptors co-localized with ETA receptors in all but one case. The tissue specimens with 100% occlusion showed the greatest proportion of ET receptor binding. These specimens were generally smaller in diameter and displayed a greater number of recanalised channels and a higher degree thrombus organisation. We estimated the % of the PEA specimen area to be either total ET, ETA or ETB positive in organised (predominantly proximal) and non-organised (predominantly distal PEA material. We found significantly higher levels of total ET and ETA receptors in organised PEA material compared to non-organised PEA material (Fig. 2A). A highly organised PEA specimen is also included in Fig. 2 where total ET (B and C), ETA (D), ETB (E) are summarised. Serial staining of adjacent sections with H&E (F), SMA (G) and CD31 (H) suggested that ETB receptors were predominantly colocalised to areas also displaying SMA immunostaining. 3.3 Immunohistochemistry and confocal characterisation of ET receptors in PEA material To further understand the distribution of ET receptors in PEA material, we performed immunohistochemistry for ETA and ETB receptors with anti-human SMA-α (to label smooth muscle cells and myofibroblasts) and anti-human CD31 to identify endothelial cells. Basal levels of ETA and ETB expression were observed in regions populated with secretory SMCs distributed throughout the non- or loosely-organised regions of fibromyxoid connective tissue in the proximal material (Fig. 3A–D). The distal, smaller samples of PEA material commonly contained frequent recanalised neovessels surrounded by loose fibromyxoid tissue as demonstrated by H&E (Fig. 3E). An Elastic Van Gieson stain (Fig. 3F) demonstrates diffuse collagen (red) surrounded by elastin fibres (black). Immunohistochemistry revealed strong levels of ETA (Fig. 3G) receptors and the presence of ETB (Fig. 3H) to be expressed by the neovessels. Neovessel throughout the distal PEA material each recapitulated the histological architecture of an artery, being having a contractile ring of SMA-α positive fusiform myofibroblasts (Fig. 3I) with an endothelialised CD31-positive lumen (Fig. 3J). Co-localisation studies using confocal microscopy confirmed ETA and ETB expression to be associated with Actin filaments in the muscularised portion of the recanalised vessel (Fig. 4). 4 Discussion CTEPH is caused by chronic thromboembolic obstruction of the pulmonary vasculature and the more distal portions of this residual material can completely occlude the lumen and have been shown to contain frequent newly formed vascular channels [1], [31]. Our results show that ET receptors are present within the luminal obstructions removed from pulmonary artery branches during PEA surgery for patients with CTEPH. To our knowledge this is the first time this has been shown using autoradiography. A crucial advantage of using autoradiography to identify ET receptors is that the receptor must be expressed on the cell surface and functionally viable for the radiolabelled ET ligand to bind. This provides mechanistic evidence for circulating ET to play a role in the organised thrombus present in the larger pulmonary vessels. This novel observation implies that ET receptor antagonists could act on the pulmonary circulation in CTEPH at the level of the organising thrombus as well as in the small-vessel arteriopathy. Analysis of the distribution of the ET receptors in the specimens shows that the larger less occluded pulmonary arteries (> 14 mm diameter) had fewer recanalised channels present and a lower expression of ET receptors, in contrast to the smaller specimens. 4.1 PEA specimen histology The heterogeneous nature of the pulmonary endarterectomy specimens from our patient cohort is unsurprising. Macroscopically the surgical team could identify differences in the tissues removed at PEA surgery (using the classification from Jaimeson). To overcome the heterogeneity of the tissue, it would have been desirable to use a greater number of cross-sections from the same patient. This would have potentially allowed for a more systematic analysis of the surgical tissue based on anatomical location. This was not possible to perform as the bulk of the extracted tissue was required for histological analysis for the patient and could therefore not be sent away for autoradiography. The histopathological appearance of the cross-sections through our PEA specimens is consistent with previous studies [1], [4], [31] from pathological descriptions of CTEPH arising from post-mortem examinations, lung transplantation or from lung biopsies. 4.2 ET receptor distribution ETA vs ETB The ETA receptor activation results in vasoconstriction and smooth muscle cell proliferation. The ETB receptor is located in the endothelium and its activation prevents apoptosis of smooth muscle cells and causes vasodilatation via release of nitric oxide. The pattern of ETA and ETB receptor distribution in the lung has been previously demonstrated in animals [14] and humans [8]. In normal subject, congenital heart disease and idiopathic pulmonary hypertension subjects the larger calibre vessels showed predominant ETA expression with a relative increase in the ETB expression as the vessels narrow to 0.5-1 mm diameter (while remaining < 50% overall expression at this size). In the main pulmonary arteries > 90% of ET expression demonstrated in the medial layer is ETA receptor. ETB vascular expression is seen to a lesser degree in the small conduit arteries but at lower levels than seen for ETA. Within the rest of the lung ETA expression is found in the parenchyma, airway smooth muscle and epithelial cells. ETB is seen in high density in airway smooth muscle and lower levels in lung parenchyma and airway submucosal glands. The results of our experiments on PEA specimens have shown that both receptors are expressed with more expression of ETA receptors compared with ETB. This would fit with the size of our cross-sections indicating that they are conduit artery size where ETA expression has been shown to be greater. The level of ETB expression we have found is without question less than ETA but in some specimens seemed greater than one might predict given data from congenital heart disease and idiopathic pulmonary arterial hypertension patients. Bauer et al. [3] have shown, in addition to elevated circulating plasma big ET-1 levels, elevated levels of ETB mRNA with no change in ETA mRNA in CTEPH specimens suggesting ETB is upregulated. Some similarities are thought to exist in the vascular remodelling seen both in CTEPH to those observed in IPAH [21]. The implication of this on our findings is that ET receptors will also be present in smaller surgically inaccessible vessel obstructions hence ET receptor antagonists might have some effect on the SMCs in those obstructions. A randomised placebo controlled trial of ET receptor antagonist in patients with inoperable chronic thromboembolic pulmonary hypertension and patients with persistent pulmonary hypertension after pulmonary endarterectomy surgery [11] has shown statistically significant improvement in PVR and cardiac output but it is not possible to know whether this was because of effects on the distal vasculopathy or proximal obstructions described by the ‘two compartment model of CTEPH’ [20]. 5 Conclusion This study demonstrates the presence of functionally viable ET receptors in the surgically extracted tissue from patients with CTEPH. The ET receptor was associated with smooth muscle cells, mainly the contractile phenotype of SMC that surrounds the recanalised channels and can be seen within the more organised chronic thrombus. Both the ETA and ETB receptors were found with the ETA receptor showing more expression. This shows a potential role for ET receptors to influence both compartments in CTEPH and generates questions about how ET antagonists might influence the pathological development of the chronic thrombus in CTEPH. Author contributions RVMR, MS and MG carried out histology, data analysis, contributed to writing and manuscript review, REK carried out ligand binding and autoradiography, GH, KSS, DPJ identified and selected patient groups, APD and J P-K designed experiments, analysed data and contributed to writing and manuscript review. Conflicts of interest statement Funded in part by an unrestricted educational grant to JP-Z from Actelion Pharmaceuticals, Basle, Switzerland. KKS has received educational support from Actelion, Bayer and GlaxoSmithKline to attend conferences. MS, RVMR, REK, GH, KKS, DPJ, MG and APD have no conflicts of interest. Acknowledgements We acknowledge the support of the referring UK centres for PH; the Pulmonary Hypertension Association-UK, Wellcome Trust award WT107715/Z/15/Z, Programmes in Translational Medicines and Therapeutics (085686) and in Metabolic and Cardiovascular Disease (096822/Z/11/Z), the British Heart Foundation PG/09/050/27734, and the NIHR Cambridge Biomedical Research Centre. We also acknowledge the support of the Cambridge NIHR BRC Cell Phenotyping Hub and the Papworth Hospital Research Tissue Bank. This report presents independent research funded by the NIHR. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Fig. 1 (A) Typical PEA material Example of a PEA surgical specimen from the left lung of a patient with CTEPH. Cross-sections taken from the central proximal and distal tail portions are indicated with dashed lines. (B), Typical findings of H&E stained proximal PEA material. (C) Typical findings of H&E stained distal PEA material, being highly organised with frequent neovessels (scale bars = 100 μm). Fig. 2 We estimated the % of the PEA specimen area to be either total ET, ETA or ETB positive in organised (predominantly distal) and non-organised (predominantly proximal PEA material. We found significantly higher levels of total ET and ETA receptors in organised PEA material compared to non-organised PEA material (A). A highly organised PEA specimen is also included in this figure where total ET (B and C), ETA (D), ETB (E) are summarised. Serial staining of adjacent sections with H&E (F), SMA (G) and CD31 (H) suggested that ETA receptors were predominantly colocalised to areas also displaying SMA immunostaining (scale bar = 0.5 mm). Fig. 3 PEA histopathology and ET receptor expression. Representative images of the histopathology commonly observed in PEA material. Proximal PEA material are collagen rich (B) with little obvious pattern of (C) ETA or ETB (D) receptor expression. Distal PEA material tends to be more organised with the presence of frequent recanalised neovessels (E) surrounded by loose fibromyxoid tissue as demonstrated by H&E. An Elastic Van Gieson stain (F) demonstrates diffuse collagen (red) surrounded by elastin fibres (black). Immunostaining for ETA (G) and ETB (H) reveal vascular expression of both receptor types. Neovessels present in distal PEA material each recapitulating the histological architecture of an artery, having arranged contractile SMA-positive (fusiform) SMCs (I) and an endothelialised CD31 positive lumen (J). Arrows demonstrate an endothelial cell lined neovessel surrounded by organised SMCs. Scale bars in A–D = 100 μm. Scale bars in E–J = 50 μm. Fig. 4 ETA receptors are expressed by neovessels in PEA material. To confirm the vascular expression of ETA in distal PEA material we undertook confocal microscopy. (A) Cell nuclei were labelled using 4′,6-diamidino-2-phenylindole (DAPI; blue). (B) Cytoskeletal actin filaments were labelled using alexa488 (green) conjugated phalloidin and (C) immunostained with polyclonal rabbit anti-human ETA labelled with Texas red (red). Co-localisation studies confirmed strong ETA expression to be associated with Actin filaments in the muscularised portion of the recanalised vessel (D). Scale bars = 25 μm. Table 1 Patient demographics. Case Surgical classification Pre-PEA drug therapy Pre-PEA mPAP (mm Hg) Pre-PEA PVR (dyn·s·cm− 5) Post-PEA mPAP (mm Hg) Post-PEA PVR (dyn·s·cm− 5) Right Left 1 1 2 Sildenafil 55 794 26 218 2 1 1 None 50 816 17 146 3 1 1 None 47 908 25 156 4 2 3 Sildenafil 43 1162 37 549 5 1 2/3 None 29 315 25 202 6 2 3/4 Sildenafil 50 831 32 515 7 1 2 None 53 733 24 151 8 2 2 None 33 286 21 221 9 3 3 Sildenafil 74 1561 § § 10 2 2 None 33 297 27 204 11 1 2 Sildenafil 43 491 38 304 12 2 2 Sildenafil 44 1053 19 163 13 1 1 Sildenafil 43 880 29 382 14 2 2 None 28 222 20 166 15 1 1 Sildenafil 47 888 43 545 16 1 2 Sildenafil 60 1274 50 702 17 1 1 Sildenafil 45 475 22 126 18 2 2 None 31 400 # # 19 2 3 None 50 1504 42 1002 ==== Refs References 1 Arbustini E. Morbini P. D'Armini A.M. Repetto A. Minzioni G. Piovella F. Viganó M. Plaque composition in plexogenic and thromboembolic pulmonary hypertension: the critical role of thrombotic material in pultaceous core formation Heart 88 2002 177 182 12117850 2 Bacon C.R. Cary N.R. Davenport A.P. Endothelin peptide and receptors in human atherosclerotic coronary artery and aorta Circ Res 79 1996 794 801 8831503 3 Bauer M. Wilkens H. Langer F. Schneider S.O. Lausberg H. Schäfers H.J. Selective upregulation of endothelin B receptor gene expression in severe pulmonary hypertension Circulation 105 2002 1034 1036 11877350 4 Bloor C.M. Moser K.M. Pulmonary vascular lesions occurring in patients with chronic major vessel thromboembolic pulmonary hypertension Chest 103 1993 685 692 8449052 5 Quarck R. Wynants M. Ronisz A. Sepulveda M.R. Wuytack F. Van Raemdonck D. Meyns B. Delcroix M. Characterization of proximal pulmonary arterial cells from chronic thromboembolic pulmonary hypertension patients Respir. Res. 27 2012 13 27 6 Davenport A.P. Kuc R.E. Radioligand-binding and molecular-imaging techniques for the quantitative analysis of established and emerging orphan receptor systems Methods Mol. Biol. 306 2005 93 120 15867465 7 Davenport A.P. Hyndman K.A. Dhaun N. Southan C. Kohan D.E. Pollock J.S. Pollock D.M. Webb D.J. Maguire J.J. Endothelin Pharmacol. Rev. 68 2016 366 427 8 Davie N. Haleen S.J. Upton P.D. Polak J.M. Yacoub M.H. Morrell N.W. Wharton J. ET(A) and ET(B) receptors modulate the proliferation of human pulmonary artery smooth muscle cells Am. J. Respir. Crit. Care Med. 165 2002 398 405 11818328 9 Giaid A. Yanagisawa M. Langleben D. Michel R.P. Levy R. Shennib H. Kimura S. Masaki T. Duguid W.P. Stewart D.J. Expression of ET-1 in the lungs of patients with pulmonary hypertension N. Engl. J. Med. 328 1993 1732 1739 8497283 10 Hall S.M. Davie N. Klein N. Haworth S.G. Endothelin receptor expression in idiopathic pulmonary arterial hypertension: Effect of bosentan and epoprostenol treatment Eur Respir J. 38 2011 851 860 21406517 11 Jaïs X. D'Armini A.M. Jansa P. Torbicki A. Delcroix M. Ghofrani H.A. Hoeper Marius M. Lang I.M. Mayer E. Pepke-Zaba Joanna Perchenet L. Morganti A. Simonneau G. LJ Rubin Bosentan for treatment of inoperable chronic thromboembolic pulmonary hypertension J. Am. Coll. Cardiol. 52 2008 2127 2134 19095129 12 Jamieson S.W. Kapelanski D.P. Pulmonary endarterectomy Curr. Probl. Surg. 37 2000 165 252 10723452 13 Kuc R.E. Carlebur M. Maguire J.J. Yang P. Long L. Toshner M. Morrell N.W. Davenport A.P. Modulation of endothelin receptors in the failing right ventricle of the heart and vasculature of the lung in human pulmonary arterial hypertension Life Sci. 118 2014 391 396 24582810 14 Kuc R.E. Maguire J.J. Davenport A.P. Quantification of endothelin receptor subtypes in peripheral tissues reveals downregulation of ET(A) receptors in ET(B)-deficient mice Exp Biol Med (Maywood) 231 6 2006 741 745 Jun 16740991 15 Langer F. Bauer M. Tscholl D. Schramm R. Kunihara T. Lausberg H. Georg T. Wilkens H. Schäfers H. Circulating big ET-1: an active role in pulmonary thromboendarterectomy? J. Thorac. Cardiovasc. Surg. 130 2005 1342 1347 16256787 16 Lee J.H. Chun Y.G. Lee I.C. Tuder R.M. Hong S.B. Shim T.S. Lim C.M. Koh Y. Kim W.S. Kim D.S. Kim W.D. Lee S.D. Pathogenic role of endothelin 1 in hemodynamic dysfunction in experimental acute pulmonary thromboembolism Am. J. Respir. Crit. Care Med. 164 2001 1282 1287 11673223 17 Maguire J.J. Davenport A.P. Endothelin receptors and their antagonists Semin. Nephrol. 35 2015 125 136 25966344 18 Maguire J.J. Davenport A.P. Endothelin@25 — new agonists, antagonists, inhibitors and emerging research frontiers: IUPHAR review 12 Br. J. Pharmacol. 171 2014 5555 5572 25131455 19 Maguire J.J. Yu J.C. Davenport A.P. ETA receptor antagonists inhibit intimal smooth muscle cell proliferation in human vessels Clin Sci (Lond) 103 Suppl. 48 2002 184S 188S 12193082 20 Moser K.M. Braunwald N.S. Successful surgical intervention in severe chronic thromboembolic pulmonary hypertension Chest 64 1973 29 35 4717457 21 Peacock A. Simonneau G. Rubin L. Controversies, uncertainties and future research on the treatment of chronic thromboembolic pulmonary hypertension Proc. Am. Thorac. Soc. 3 2006 608 614 16963542 22 Pepke-Zaba J. Delcroix M. Lang I. Mayer E. Jansa P. Ambroz D. Treacy C. D'Armini A.M. Morsolini M. Snijder R. Bresser P. Torbicki A. Kristensen B. Lewczuk J. Simkova I. Barberà J.A. de Perrot M. Hoeper M.M. Gaine S. Speich R. Gomez-Sanchez M.A. Chronic thromboembolic pulmonary hypertension (CTEPH): results from an international prospective registry Circulation 124 2011 1973 1981 21969018 23 Pietra G.G. Edwards W.D. Kay J.M. Rich S. Kernis J. Schloo B. Ayres S.M. Bergofsky E.M. Brundage B.H. Detre K.M. Histopathology of primary pulmonary hypertension. A qualitative and quantitative study of pulmonary blood vessels from 58 patients in the National Heart, Lung, and Blood Institute, Primary Pulmonary Hypertension Registry Circulation 80 1989 1198 1206 2805258 24 Reesink HJ, Meijer RC, Lutter R, Boomsma F, Jansen HM, Kloek JJ, BresserP. Hemodynamic and clinical correlates of endothelin-1 in chronic thromboembolic pulmonary hypertension. Circ. J. 2006; 70:1058–63. 25 Schmeck J. Koch T. Patt B. Heller A. Neuhof H. van Ackern K. The role of endothelin-1 as a mediator of the pressure response after air embolism in blood perfused lungs Intensive Care Med. 24 1998 605 611 9681783 26 Simon M. Battistini B. Joo Kim Y. Tsang J. Plasma levels of endothelin-1, big endothelin-1 and thromboxane following acute pulmonary air embolism Respir Physiol Neurobiol. 138 2003 97 106 14519381 27 Skalli O. Pelte M.F. Peclet M.C. Gabbiani G. Gugliotta P. Bussolati G. Ravazzola M. Orci L. Alpha-smooth muscle actin, a differentiation marker of smooth muscle cells, is present in microfilamentous bundles of pericytes J Histochem Cytochem 37 1989 315 321 2918221 28 Sofia M. Faraone S. Alifano M. Micco A. Albisinni R. Maniscalco M. Di Minno G. Endothelin abnormalities in patients with pulmonary embolism Chest 111 1997 544 549 9118685 29 Stewart D.J. Levy R.D. Cernacek P. Langleben D. Increased plasma endothelin-1 in pulmonary hypertension: marker or mediator of disease? Ann. Intern. Med. 114 1991 464 469 1994793 30 Tsang J. Battistini B. Dussault P. Stewart K. Qayumi K.A. Biphasic release of immunoreactive endothelins following acute pulmonary thromboembolism in pigs J. Cardiovasc. Pharmacol. 36 5 Suppl 1 2000 S221 S224 11078382 31 Yi E.S. Kim H. Ahn H. Strother J. Morris T. Distribution of obstructive intimal lesions and their cellular phenotypes in chronic pulmonary hypertension. A morphometric and immunohistochemical study Am. J. Respir. Crit. Care Med. 162 2000 1577 1586 11029379

PMC005xxxxxx/PMC5000547.txt

==== Front BMC Pulm MedBMC Pulm MedBMC Pulmonary Medicine1471-2466BioMed Central London 29010.1186/s12890-016-0290-5Research ArticleDrop-out rate among patients treated with omalizumab for severe asthma: Literature review and real-life experience Caminati M. +39 0458123526ma.caminati@gmail.com 1Senna G. gianenrico.senna@ospedaleuniverona.it 1Stefanizzi G. giorgia.stefanizzi@ospedaleuniverona.it 1Bellamoli R. 1Longhi S. 1Chieco-Bianchi F. fulvia.chiecobianchi@gmail.com 2Guarnieri G. gabriella.guarnieri@gmail.com 3Tognella S. stognella@gmail.com 4Olivieri M. mario.olivieri@ospedaleuniverona.it 5Micheletto C. micheletto.claudio@libero.it 6Festi G. giuliana.festi@ospedaleuniverona.it 7Bertocco E. e.bertocco@libero.it 8Mazza M. francesco.mazza@aopn.fvg.it 9Rossi A. andrea.rossi@ospedaleuniverona.it 7Vianello A. andrea.vianello@sanita.padova.it 2on behalf of North East Omalizumab Network study groupBarp C. Bonazza L. Crivellaro M. A. Dama A. Donazzan G. Idotta G. Lombardi C. Nalin M. Pomari C. Schiappoli M. 1 Asthma Center and Allergy Unit, Verona General and University Hospital, Verona, Italy 2 Respiratory Pathophysiology Division, University-City Hospital of Padua, Padua, Italy 3 Department of Cardiologic, Thoracic and Vascular Sciences, University of Padua, Padua, Italy 4 Respiratory Unit, Orlandi General Hospital, Bussolengo, Verona, Italy 5 Unit of Occupational Medicine, Verona General and University Hospital, Verona, Italy 6 Respiratory Unit, Mater Salutis Hospital, Legnago, Verona, Italy 7 Pulmonary Unit, Verona University and General Hospital, Verona, Italy 8 Respiratory pathology Unit, Arzignano General Hospital, Vicenza, Italy 9 Pulmonary Unit, Pordenone General Hospital, Pordenone, Italy 25 8 2016 25 8 2016 2016 16 1 12823 11 2015 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background In patients with asthma, particularly severe asthma, poor adherence to inhaled drugs negatively affects the achievement of disease control. A better adherence rate is expected in the case of injected drugs, such as omalizumab, as they are administered only in a hospital setting. However, adherence to omalizumab has never been systematically investigated. The aim of this study was to review the omalizumab drop-out rate in randomized controlled trials (RCTs) and real-life studies. A comparative analysis was performed between published data and the Italian North East Omalizumab Network (NEONet) database. Results In RCTs the drop-out rate ranged from 7.1 to 19.4 %. Although the reasons for withdrawal were only occasionally reported, patient decision and adverse events were the most frequently reported causes. In real-life studies the drop-out rate ranged from 0 to 45.5 %. In most cases lack of efficacy was responsible for treatment discontinuation. According to NEONet data, 32 % of treated patients dropped out, with an increasing number of drop outs observed over time. Patient decision and lack of efficacy accounted for most treatment withdrawals. Conclusions Treatment adherence is particularly crucial in patients with severe asthma considering the clinical impact of the disease and the cost of non-adherence. The risk of treatment discontinuation has to be carefully considered both in the experimental and real-life settings. Increased knowledge regarding the main reasons for patient withdrawal is important to improve adherence in clinical practice. Keywords Drop-outAdherenceSevere asthmaOmalizumabissue-copyright-statement© The Author(s) 2016 ==== Body Background Adherence is usually defined as the extent to which the patient’s use of medication matches the prescribed regimen. Poor adherence has a critical relevance in the management of various chronic diseases as it may negatively affect treatment outcomes and result in increased hospitalizations, morbidity, and mortality [1]. In bronchial asthma the achievement of disease control is closely related to adherence. It has been extensively demonstrated that an irregular drug intake markedly affects patient’s quality of life, as it is responsible for an increased risk of nocturnal awakenings and impairment in routine daily activities, such as exercise and sports [2]. Lack of adherence is very common, particularly in chronic conditions [3–7]. In fact, the treatment discontinuation rate ranges from 20 to 40 % for acute illnesses and from 30 to 60 % for chronic diseases. Preventive treatments are associated with a non-adherence rate of up to 80 % [8]. As far as asthma is concerned, it is well known that about 50 % of patients are non-adherent. The issue becomes even more relevant in specific age groups such as children, adolescents and elderly [9]. A number of factors, including fear of treatment-related side effects, poor perception of symptoms, belief in alternative/complementary medicine but also complex treatment regimens, illness-related factors, inconvenience, and social background, may account for poor adherence, which has a very high social cost [1]. In the United States, irregular drug intake among patients with hypertension is responsible for 89 premature deaths every year [10]. It is estimated that annually $US100 billion which is spent on unnecessary or preventable hospitalizations related to poor adherence could be saved [11]. Many of the above mentioned variables have been described as determinants of poor adherence to asthma treatments. Also, poor awareness of the need for treatment even in the absence of symptoms and steroids fear are two main reasons for treatment withdrawal in asthmatic patients [12]. On the other side, caregivers themselves have to face some limitations such as difficulties in patients follow-up scheduling and time constraints, which may hamper patient’s adherence support [9]. A univocal and standardized tool for evaluation of adherence is lacking. Although many methods are currently available none of them can be considered as the gold standard [1]. Another controversial aspect concerns the definition of “acceptable adherence”. In some large studies, an adherence rate greater than 80 % has been considered satisfactory [1] but a general consensus about this issue has not been reached. In bronchial asthma evaluation of adherence is even more difficult as treatment is mainly based on inhaled drugs. In this case, an objective adherence evaluation may rely on different tools but due to many limitations with these tools their use in routine clinical practice is not suitable. Electronic devices are accurate but are also quite expensive [13]; therefore recording of pharmacy refills can be considered as a more affordable option but they are less accurate. Patients usually deny any lack of adherence, even in severe asthma [14]. Treatment discontinuation is one of the most relevant aspects of adherence, as it leads to major consequences. From this perspective, drop-out rate can be considered to be a surrogate marker of adherence. In randomized controlled trials (RCTs) a high drop-out rate can weaken the final results [15], and in the real-life setting it is related to preventable patient impairments and unnecessary costs. Furthermore, the detection and quantification of drop-out rate in a daily clinical setting is a complex issue, as regular follow-up for all patients is not always possible. Patients requiring treatment with injected drugs are more easily monitored, as treatment administration requires medical supervision. This is the case with omalizumab, an anti-immunoglobulin E (IgE) monoclonal antibody for the treatment of severe asthma. It must be administered in a hospital setting once or twice a month, according to the patient’s total IgE level [16]. Thus, treatment discontinuation can be easily detected and considered as a consistent marker of adherence. To our knowledge, the treatment discontinuation rate among patients undergoing omalizumab treatment has never been systematically investigated as a primary outcome. The present study aimed to review the drop-out rate and describe the most common reasons for patient withdrawal in RCTs and real-life studies published up to December 2014. A comparative analysis between published data and an Italian database, the North East Omalizumab Network (NEONet), was also conducted. Methods Search strategy A complete search of the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE and PubMed up to December 2014 was carried out. The search strategy retrieved citations containing the subject heading “omalizumab” and was restricted to randomized, double-blind, placebo-controlled trials and “real life studies” for severe allergic asthma in patients aged ≥18 years old. The keywords used were: omalizumab, asthma, controlled studies, randomized trial, real life studies, pragmatic studies. All retrieved studies were restricted to the English language. Italian North East Omalizumab Network (NEONet) database analysis A retrospective analysis of the NEONet database was carried out. Details about the Network and the data collecting methods are provided elsewhere [17]. In brief, NEONet is a non-profit project approved by the local ethics committee and involves 19 Allergy and Respiratory Referral Centres for Severe Asthma located in the North-East region of Italy. It aims to collect an extensive amount of clinical data on patients undergoing omalizumab treatment in a real-life setting and provide some new insights concerning current unmet needs (e.g. impact of omalizumab treatment on lung function and on asthma comorbidities, long-term follow-up of treated patients, adherence, non-responders profile, optimal treatment duration). The participating clinicians enter anonymous coded data into a shared limited-access web platform. Drop-out evaluation The drop-out rate and the most common reasons for treatment discontinuation were evaluated, if reported, in RCT, in “real life studies” and in the NEONet database. Reasons for withdrawal were categorized as follows: patient’s decision, lack of efficacy, adverse event, clinical efficacy, and other causes. With regard to the NEONet database, “lack of efficacy” and “clinical efficacy” were defined according to the GETE (global evaluation of treatment effectiveness) Questionnaire [18], which was completed by physicians for every patient. GETE is a five-point scale: 1 is excellent (complete control of asthma), 2 is good (marked improvement), 3 is moderate (discernible, but limited improvement), 4 is poor (no appreciable change), and 5 is worsening. Number 4 and 5 corresponded to “lack of efficacy” and number 1 and 2 corresponded to “clinical efficacy”. Statistical analysis Two-sample t-test was used to compare the variables in Table 4. Two-proportion z-test was used to analyze the differences between mean drop-out rates and reasons. All tests have been performed with a significance level of 5 %. A logistic regression analysis was provided in order to verify the association between drop-out rate and treatment duration. R software has been used. Results Randomized controlled studies (RCTs) As of December 2014, seven RCTs have been published (Table 1) [16, 19–24]. Overall, 1719 patients were included, with a slightly higher prevalence of females. Across the studies, the mean age ranged from 37.5 to 43.7 years. The drop-out rate, which was reported in all the analyzed studies, ranged from 7.1 to 19.4 %. However, reasons for withdrawal were not always reported. Patient’s decision accounted for the majority of drop outs in four of the selected studies [16, 20, 21, 24]; whereas in two studies adverse events were the main cause of treatment discontinuation [19, 22]. No data were available with regard to the timing of drop-outs after the initiation of treatment.Table 1 Overall dropout rate and main reasons for treatment discontinuation in RCT Author [ref] N duration (months) Mean ± SD age, years M/F Ratio Drop-out rate (%) Patient decision (%) Lack of efficacy (%) Adverse events (%) Other Causes (%) Busse et al. 2001 [16] 268 7 39.3 0.63 7.1 4.1 0.37 0.74 1.49 Soler et al. 2011 [23] 274 7 40.0 1.06 6.9 1.09 1.09 NR NR Holgate et al. 2004 [21] 126 8 41.1 0.55 8.7 8.7 NR NR NR Ayres et al. 2004 [19] 206 12 37.5 0.39 7.3 NR NR 7.3 NR Vignola et al. 2004 [24] 209 7 38.3 ± 14.7 0.92 8.1 8.1 NR NR NR Humbert et al 2005 [22] 209 7 43.4 ± 13.3 0.48 12.2 NR NR 4.5 NR Hanania et al. 2011 [20] 427 12 43.7 ± 14.3 0.63 19.4 11.00 NR 3.74 4.68 F female, M male, NR not reported, RCT randomized controlled trials, SD standard deviation Real-life studies As of December 2014, 19 real-life studies have been published on the use of omalizumab in severe asthma (Table 2) [25–42]. A total of 13,466 patients were included: compared with RCTs the age range was broader in real-life studies (29.5 to 49.9 years) with the inclusion of patients aged almost 10 years younger and 6 years older than RCT patients. The mean study duration was longer in real-life studies.Table 2 Overall dropout rate and main reasons for treatment discontinuation in real-life studies Author [ref] N duration (months) Mean ± SD age, years M/F Ratio Drop-out rate (%) Patient decision (%) Lack of efficacy (%) Adverse events (%) Other Causes (%) Molimard et al. 2008 [37] 146 12 46.5 ± 13.5 0.57 30.6 1.4 19 5.4 4.8 Brusselle et al. 2009 [29] 158 12 48.1 ± 17.1 0.85 45.5 10.1 13.3 12 10.1 Korn et al. 2009 [34] 280 5 43.9 ± 16.3 1.45 32.5 NR 14.28 NR NR Bavbek et al. 2010 [27] 18 6 41.8 ± 11.2 0.63 0 NR NR NR NR Cazzola et al. 2010 [30] 142 24 49.6 ± 4.1 1 8.5 2.11 1.4 1.4 3.5 Tzortzaki et al. 2012 [39] 60 26 54.0 ± 14.0 0.66 0 NR NR NR NR Wittchen et al. 2012 [42] 53 24 48.3 ± 13.7 1 NR NR NR NR NR Vennera M et al. 2012 [40] 266 15 51.0 ± 13.7 0.45 18.7 5.6 10.5 2.6 NR Lafeuille et al. 2012 [35] 644 24 49.9 ± 14.2 0.69 NR NR NR NR NR Eisner et al. 2012 [32] 4969 12 44.5 ± 16.6 0.56 NR NR NR NR NR Chen et al. 2013 [31] 4970 48 44.5 ± 16.6 0.56 NR NR NR NR NR Grimaldi-Bensouda et al. 2013 [33] 374 36 49.7 ± 14.6 0.58 NR NR NR NR NR Barnes et al. 2013 [26] 136 36 41.3 ± 14.5 0.46 NR NR NR NR NR Maselli et al. 2013 [36] 26 6 29.6 ± 18.7 1.6 0 NR NR NR NR Group 1a Maselli et al. 2013 [36] 26 24 34.0 ± 17.6 NR 0 NR NR NR NR Group 2b Braunstahl et al. 2013 [28] 943 12 45.0 ± 15.5 NR 16.6 8.4 NR NR 8.2 Özgür et al. 2013 [38] 26 6 47.6 ± 13.9 0.23 0 NR NR NR NR Vieira et al. 2014 [41] 15 6 45.6 ± 10.8 0.15 26.66 6.66 NR 20.00 NR Ancochea et al. 2014 [25] 214 12 48.2 ± 17.7 0.43 7.9 4.2 2.3 1.9 NR F female, M male, NR not reported, RCT randomized controlled trials, SD standard deviation aPatients with IgE levels above 700 IU/mL bPatients with IgE levels less or equal to 700 IU/mL In the 13 studies that reported the drop-out rate, it ranged from 0 to 45.5 %. No patients discontinued treatment in four of these studies [27, 36, 38, 39]. There was notable variability in the reasons given for discontinuing treatment across the different studies. Lack of efficacy was the most common reason for treatment discontinuation in most studies [29, 34, 37, 40]. Patient decision to discontinue treatment was the main reason for drop outs in two studies [25, 28] and adverse events were the most frequent reason for withdrawal in one study [37]. Comparison between RCTs and Real-life studies Table 3 provides a direct comparison of drop-out rates and reasons between RCTs and Real-life studies. Overall, drop-out rate in Real-life studies is significantly higher. The proportion of patients who discontinued omalizumab due to a lack of efficacy was significantly bigger in real-life studies than in RCTs. On the opposite patient’s decision and adverse events have more relevance in RCTs in comparison with Real-life studies.Table 3 Comparison of drop-out rate mean values and reasons between RCTs and Real-life studies RCT Real-life p-value Drop-out 11.65 % 17.50 % 0.0000 Patient decision 59.72 % 35.01 % 0.0000 Lack of efficacy 0.69 % 23.53 % 0.0000 Adverse events 22.92 % 12.04 % 0.0011 Other causes 116.67 % 29.41 % 0.0016 NEONet database The NEONet database included 221 patients. As shown in Table 4, among them 70 (32 %) dropped out; under treatment population and drop-outs did not significantly differ in terms of age, gender and mean treatment duration. Treatment discontinuation was more common amongst females (64 %). Patient decision accounted for most of the withdrawals (49 %), followed by a lack of efficacy (26 %). Within the group of patients dropping-out for “onset of contraindications”, pregnancy was the reason in all the cases. As far as adverse events is concerned, 3 cases of generalized urticarial have been described; arthralgia and myocarditis have been recorded in two other cases.Table 4 Overall drop-out rate and main reasons for treatment discontinuation in the NEONet database Patient population (n = 221) Drop-out patients (70, 32 %) Patients under treatment (151, 38 %) p-value Males, n (%) 25 (35.71) 68 (45.03) 0.0959 Females, n (%) 45 (64.29) 83 (54.97) Age-years, mean (SD) 46.79 (14.82) 47.44 (13.11) 0.4904 Treatment duration-months, mean (SD) 27.69 (20.94) 27.54 (22.96) 0.4992 Reason for drop-out, n (%) Lack of efficacy 18 (26) Patient’s decision discontinuation 34 (49) Efficacy 4 (6) Adverse events (local or systemic reactions) 5 (7) Onset of contraindications 6 (8) Patient moved to another referral center 3 (4) NEONet North East Omalizumab Network, SD standard deviation Table 5 provides a comparative overview of NEONet database and published Real-life studies in terms of drop-out rates and reasons. The overall drop-out rate was significantly higher in NEONet database. Patient’s decision as a cause of dropping out showed the same trend. On the opposite drop-out rates due to lack of efficacy and adverse events do not significantly differ between NEONet and published Real-life studies.Table 5 Comparison of drop-out rate mean values and reasons between NEONet database and published Real-life studies NEONet Real-life p-value Drop-out 31.67 % 17.50 % 0.0000 Patient decision 48.57 % 35.01 % 0.0160 Lack of efficacy 25.71 % 23.53 % 0.3475 Adverse events 7.14 % 12.04 % 0.1176 Other causes 18.57 % 29.41 % 0.0318 In our study population the proportion of drop-outs does not significantly change in different treatment duration time intervals, as described in Fig. 1, which also shows the 95 % Confidence Interval (CI) (blue lines). Furthermore, the logistic regression analysis confirms the lack of association between time and drop-out rate (p = 0.96).Fig. 1 Drop-out rates in different treatment duration time intervals (NEONet database; n = 221). The blue lines indicate the 95 % Confidence Interval (CI) Discussion This review of publications on omalizumab in severe asthma demonstrated that there is a wide variability in both the drop-out rate and the reasons for discontinuing treatment. Drop-out rates appeared to be the lowest in RCTs—possibly because these studies are conducted under rigorously controlled conditions. In contrast, real-life studies, which are more closely aligned with routine clinical practice, cited markedly higher drop-out rates of up to 46 %. The NEONet database was more in line with the data from real-life studies with reported dropout rates of 32 %. Lack of efficacy was cited as one of the most common reasons for treatment discontinuation in both real-life studies and the NEONet database, while patient decision and adverse events primarily contributed to the drop-out rates observed in RCTs. Poor treatment adherence is a well-known unmet need in patients with asthma. This is particularly the case with inhaled drugs [2, 13, 43]. Data regarding adherence patterns in patients treated with omalizumab are limited and the evidence is weakened by methodological differences across the studies [44]. However, despite the reported drop-out rates, adherence to omalizumab appears to be slightly higher than that observed with other anti-asthmatic drugs [45, 46]. Therefore, omalizumab therapy has been proposed as an alternative for patients with poorly controlled asthma for whom adherence does not improve with conventional interventions [46]. One possible explanation is that compared with oral or inhaled treatments, omalizumab is regularly administered in a hospital setting under direct medical supervision thereby improving treatment adherence. Conversely, subcutaneous allergen immunotherapy, which is also regularly administered in a hospital setting to patients with respiratory allergy [47], is characterized by a lower adherence rate in comparison to omalizumab [6, 48]. Of note, this immunotherapy is indicated in mild to moderate asthmatics with less severe symptoms [47]. On this basis, it could be argued that disease severity can positively affect adherence to treatment. A non-adherence rate of 44 % in asthmatics with steroid-dependent asthma has been reported [14]. Furthermore, a recent observational study on omalizumab adherence identified a lower pre-bronchodilator percentage of predicted forced expiratory volume in 1 s (FEV1) as an independent predictor of good adherence [44]. Treatment discontinuation unrelated to medical reasons represents the major drawback of non-adherence. It implies there are preventable direct and indirect costs affecting both patient quality of life and health systems resources [49]. To the best of the authors’ knowledge the drop-out rate among patients undergoing omalizumab treatment has never been systematically investigated as a primary outcome. Overall, a lower rate of treatment discontinuation with a narrow range was observed in RCTs. This finding is to be expected if the setting of experimental studies is taken into account. In fact, the RCT protocol typically mandates regular patient assessment and a strict follow-up schedule, often with a shorter duration of follow-up in comparison with real-life studies. All of these factors may account for a lower withdrawal rate, which is also a methodological requirement in order to strengthen the final results [15, 50]. Surprisingly, the reasons for patient drop outs were not reported in some RCTs [21, 24]. However, adverse effects and patient decision were responsible for most drop outs across the reviewed studies [25, 28, 29, 34, 37, 40]. RCT protocols are usually demanding for patients and withdrawal due to inconvenience is not unexpected [48]. As far as adverse effects are concerned, RCT protocols include strict and careful monitoring of potential treatment-related adverse events that more frequently results in patient exclusion from the study than in the real-life setting [50, 51]. In the real-life studies, drop-out prevalence was characterized by a marked variability, ranging from 0 % in four studies up to 45 % in the remaining studies. Although the reasons for drop-outs were sporadically reported, in most cases lack of efficacy was responsible for treatment discontinuation. The proportion of patients who discontinued omalizumab due to a lack of efficacy was significantly higher in real-life studies than in RCTs. The different patient selection process may provide a possible explanation. In fact, patients’ enrolment in RCTs relies on strict inclusion and exclusion criteria, which differs from the real-life setting. A recent review from our group [51] has highlighted that sensitization to a perennial allergen is missing in more than 20 % of patients undergoing omalizumab treatment, despite being included among the prescription criteria established by the European Medicines Agency (EMA) [52]. However, non-responders have also been described among patients matching all the EMA prescription criteria [17, 28], and the efficacy of omalizumab in non-atopic asthma is also supported by the literature [53]. Patient selection, particularly in the field of biological drugs for asthma, still represents a challenge [54, 55]. The relevance of a number of biomarkers has been recently investigated and still fosters current research. The poor specificity of many molecules and the complex relationship between symptoms, exacerbations, response to drugs and underlying inflammation hampers the identification of univocal and standardized biomarkers predictive of clinical response [56, 57]. Such biomarkers are still lacking for omalizumab and for current and upcoming biological treatments for severe asthma [55, 58]. Nevertheless, patient selection is one of the most important aspects in managing biological drugs as they target a very specific mechanism in the pathophysiologic picture of the disease [58, 59]. Omalizumab has a good safety profile, both in the experimental and real-life setting. Only three studies, two RCTs [19, 22] and one real-life study [37], reported adverse events as the main cause of treatment discontinuation, without any significant differences in terms of drop-out rate. Of note, a local reaction at the injection site was the commonest adverse event. This finding suggests that tolerability is an important issue and consequently it has to be carefully considered; as evidenced with other treatments, it can significantly affect adherence [60]. Therefore, clinicians should discuss tolerability issues with their patients as part of a strategy aimed at improving adherence. The results from the NEONet database were similar to those reported in published studies, although the overall drop-out rate seems to be higher in our study population. For project’s policy, Referral Centers included in the NEONet collaboration are requested to strictly and regularly follow-up the patients, thus under this perspective our clinical practice is more similar to a RCT setting than to a pure real-life one. It may provide an explanation for our finding. However drop-out rates due to lack of efficacy and adverse events do not significantly differ between NEONet and published Real-life studies. The population sample was smaller in comparison with other real-life studies, however it is quite homogeneous, as the patients live in the same geographical area, and the centers share the same diagnostic work-up and patient selection criteria [17]. In the NEONet population, patient decision was the most common reason for dropping out. Although several reasons can influence patient choice, inconvenience may play the most relevant role [6, 14]. In fact, the need for regular administration of omalizumab in hospital once or twice per month can strongly affect treatment adherence, as it has many implications such as work-absenteeism and economic burden. Under this perspective, patient’s perception of clinical efficacy as well as lack of efficacy, has a crucial relevance as it may weaken the motivation of the patient for continuing treatment. Interestingly, in our study population treatment length does not seem to affect drop-out rate. In fact, the proportion of drop-outs is similar in all the treatment duration time intervals (Fig. 1). Apparently the drop-out rate in the last interval is higher, but the small sample size in that range may account for this effect, as shown in the graph by the CI bars. Furthermore, the logistic regression analysis confirms the lack of association between time and drop-out rate (p = 0.96). Whether the length of treatment impacts on the adherence rate is not easy to evaluate in the published studies, due to the great variability in terms of study duration [25–42]. However the ideal treatment duration, as well as the identification of biomarkers that are accurate in predicting the clinical response are still lacking [58, 59]. In fact, lack of efficacy, similarly to the published Real life studies [25–42], accounted for 26 % of drop-outs among NEONet patients, despite all patients being fully matched with the current prescription criteria. In the real-life setting, many patient-related variables, such as smoking habits, comorbidities, and multi-drug treatments, may affect treatment efficacy and effectiveness [51, 61], even though prescription criteria are verified. In this scenario patient’s education, in terms of awareness of the treatment and its implications, has an even more relevant role in preventing drop-outs and generally supporting adherence [62, 63]. Some limitations of our work deserve to be highlighted. Two variables potentially affecting the drop-out rate, lung function at baseline and prescribed medications other than Omalizumab, have not been extensively analyzed. In the case of the first determinant, few data are available in literature, however a lower forced expiratory volume in 1 s (FEV1) has been described as an independent predictor of good adherence [44]. Concerning the published studies included in the present review [16, 19–42], a systematic analysis of the lung function and its impact on drop-out rate is not easy relying on the available information, affected by great variability, or not mentioned at all. In our dataset analysis, GETE questionnaire for the evaluation of clinical efficacy indirectly includes the impact of treatment on lung function. As lack of efficacy is one of the main drop-out reasons, it could be hypothesized that a poor lung function at baseline, maintained during the treatment, may act as a determinant of poor adherence. A great variability, or the lack of detailed information, also regards the prescribed medications other than Omalizumab [16, 19–42] and hampers an extensive analysis of this further drop-out determinant. The scenario is even more complex if we consider the amount of drugs prescribed for comorbidities. Such analysis is out of the aim of our paper and requires an adequately sized population sample. However, according to the literature adherence to omalizumab appears to be slightly higher than that observed with other anti-asthmatic drugs, independently of other medication prescribed at the same time [45, 46]. A second limitation of our work relates to the study design itself; in real-life observational studies it is difficult to avoid or properly assess bias, and conclusions are not easily applicable across a generalized population. Furthermore, often only a descriptive analysis has been provided. Nevertheless, to our knowledge treatment discontinuation rate has never been systematically investigated as a primary outcome in a real-life setting and awareness of the most common reasons for patient withdrawal may help in finalizing some practical suggestions to improve adherence in routine clinical practice. Conclusion In conclusion, the risk of treatment discontinuation is a significant drawback for omalizumab therapy and this warrants consideration when prescribing. The reasons for dropping out have to be carefully taken into consideration when planning specific long-term strategies in order to prevent treatment withdrawal. Abbreviations EMAEuropean Medicines Agency FEV1Forced expiratory volume in 1 s GETEGlobal evaluation of treatment effectiveness IgEImmunoglobulin E NEONetNorth East Omalizumab Network RCTRandomized clinical trial Acknowledgements The authors would like to thank Anna Battershill who provided English editing and styling of the manuscript on behalf of Springer Healthcare Communications. The authors would also like to thank the following members of the North East Omalizumab Network Study Group for their contribution to the manuscript: C. Barp (Belluno), L. Bonazza (Bolzano), MA Crivellaro (Padova), A Dama (Verona), G. Donazzan (Bolzano), G. Idotta (Cittadella, PD), C. Lombardi (Brescia), M. Nalin (Rovigo), C. Pomari (Negrar, VR), M. Schiappoli (Verona). Funding English editing and styling of the manuscript was provided by Springer Healthcare Communications and funded by Novartis (Italy). Availability of data and materials Data requests can be sent to Dr Marco Caminati. Authors’ contributions MC and GS conceived and designed the study, and drafted the manuscript. GS coordinated the data collection. FCB, GG, ST, MO, CM, GF, EB, FM, AR and AV participated in the data collection and contributed to data analysis and interpretation. All authors read and approved the final manuscript. Competing interests The authors declare no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. Consent for publication Not applicable. Ethics approval and consent to participate The Verona and Rovigo provinces Institutional Review Board and Ethics Committee approved this study (approval number: 223CESC). All participants gave written consent to take part in the study. ==== Refs References 1. Osterberg L Blaschke T Adherence to medication N Engl J Med 2005 353 5 487 97 10.1056/NEJMra050100 16079372 2. Lasmar L Camargos P Champs NS Fonseca MT Fontes MJ Ibiapina C Adherence rate to inhaled corticosteroids and their impact on asthma control Allergy 2009 64 5 784 9 10.1111/j.1398-9995.2008.01877.x 19183166 3. Christensen AJ Patient’s adherence to medical treatment regimens: bridging the gap between behavioural science and biomedicine. Current Perspectives in Psycology Series 2004 New Haven Yale University Press 4. Cutler DM Everett W Thinking outside the pillbox--medication adherence as a priority for health care reform N Engl J Med 2010 362 17 1553 5 10.1056/NEJMp1002305 20375400 5. Cutler DM Long G Berndt ER Royer J Fournier AA Sasser A The value of antihypertensive drugs: a perspective on medical innovation Health Aff (Millwood) 2007 26 1 97 110 10.1377/hlthaff.26.1.97 17211019 6. Reisacher WR Visaya JM Patient adherence to allergy immunotherapy Curr Opin Otolaryngol Head Neck Surg 2013 21 3 256 62 10.1097/MOO.0b013e32835f8048 23549440 7. Sabatè E Adherence to long term therapies: evidence for action 2003 Geneva World Health Organization 8. DiMatteo MR Variations in patients’ adherence to medical recommendations: a quantitative review of 50 years of research Med Care 2004 42 3 200 9 10.1097/01.mlr.0000114908.90348.f9 15076819 9. Braido F Baiardini I Blasi F Pawankar R Canonica GW Adherence to asthma treatments: ‘we know, we intend, we advocate’ Curr Opin Allergy Clin Immunol 2015 15 1 49 55 10.1097/ACI.0000000000000132 25479318 10. Chowdhury R Khan H Heydon E Shroufi A Fahimi S Moore C Adherence to cardiovascular therapy: a meta-analysis of prevalence and clinical consequences Eur Heart J 2013 34 38 2940 8 10.1093/eurheartj/eht295 23907142 11. Kronish IM Ye S Adherence to cardiovascular medications: lessons learned and future directions Prog Cardiovasc Dis 2013 55 6 590 600 10.1016/j.pcad.2013.02.001 23621969 12. Bender DG Overcoming barriers to nonadherence in asthma treatment J Allergy Clin Immunol 2002 109 6 Suppl. S554 S559 10.1067/mai.2002.124570 12063512 13. Sumino K Cabana MD Medication adherence in asthma patients Curr Opin Pulm Med 2013 19 1 49 53 10.1097/MCP.0b013e32835b117a 23143198 14. Gamble J Stevenson M McClean E Heaney LG The prevalence of nonadherence in difficult asthma Am J Respir Crit Care Med 2009 180 9 817 22 10.1164/rccm.200902-0166OC 19644048 15. Passalacqua G Baiardini I Senna G Canonica GW Adherence to pharmacological treatment and specific immunotherapy in allergic rhinitis Clin Exp Allergy 2013 43 1 22 8 10.1111/j.1365-2222.2012.04052.x 23278877 16. Busse W Corren J Lanier BQ McAlary M Fowler-Taylor A Cioppa GD Omalizumab, anti-IgE recombinant humanized monoclonal antibody, for the treatment of severe allergic asthma J Allergy Clin Immunol 2001 108 2 184 90 10.1067/mai.2001.117880 11496232 17. Caminati M Senna G Chieco Bianchi F Marchi MR Vianello A Micheletto C Omalizumab management beyond clinical trials: the added value of a network model Pulm Pharmacol Ther 2014 29 1 74 9 10.1016/j.pupt.2014.01.007 24508951 18. Lloyd A Turk F Leighton T Canonica GW Psychometric evaluation of global evaluation of treatment effectiveness: a tool to assess patients with moderate-to-severe allergic asthma J Med Econ 2007 10 285 96 10.3111/13696990701478856 19. Ayres JG Higgins B Chilvers ER Ayre G Blogg M Fox H Efficacy and tolerability of anti-immunoglobulin E therapy with omalizumab in patients with poorly controlled (moderate-to-severe) allergic asthma Allergy 2004 59 7 701 8 10.1111/j.1398-9995.2004.00533.x 15180756 20. Hanania NA Alpan O Hamilos DL Condemi JJ Reyes-Rivera I Zhu J Omalizumab in severe allergic asthma inadequately controlled with standard therapy: a randomized trial Ann Intern Med 2011 154 9 573 82 10.7326/0003-4819-154-9-201105030-00002 21536936 21. Holgate ST Chuchalin AG Hebert J Lötvall J Persson GB Chung KF Efficacy and safety of a recombinant anti-immunoglobulin E antibody (omalizumab) in severe allergic asthma Clin Exp Allergy 2004 34 4 632 8 10.1111/j.1365-2222.2004.1916.x 15080818 22. Humbert M Beasley R Ayres J Slavin R Hebert J Bousquet J Benefits of omalizumab as add-on therapy in patients with severe persistent asthma who are inadequately controlled despite best available therapy (GINA 2002 step 4 treatment): INNOVATE Allergy 2005 60 3 309 16 10.1111/j.1398-9995.2004.00772.x 15679715 23. Soler M Matz J Townley R Buhl R O’Brien J Fox H The anti-IgE antibody omalizumab reduces exacerbations and steroid requirement in allergic asthmatics Eur Respir J 2001 18 2 254 61 10.1183/09031936.01.00092101 11529281 24. Vignola AM Humbert M Bousquet J Boulet LP Hedgecock S Blogg M Efficacy and tolerability of anti-immunoglobulin E therapy with omalizumab in patients with concomitant allergic asthma and persistent allergic rhinitis: SOLAR Allergy 2004 59 7 709 17 10.1111/j.1398-9995.2004.00550.x 15180757 25. Ancochea J Chivato T Casan P Picado C Herraez L Casafont J Profile of patients treated with omalizumab in routine clinical practice in Spain Allergol Immunopathol (Madr) 2014 42 2 102 8 10.1016/j.aller.2012.10.010 23267505 26. Barnes N Menzies-Gow A Mansur AH Spencer D Percival F Radwan A Effectiveness of omalizumab in severe allergic asthma: a retrospective UK real-world study J Asthma 2013 50 5 529 36 10.3109/02770903.2013.790419 23574000 27. Bavbek S Aydin O Kepil Özdemir S Yilmaz I Celik GE Demirel YS Therapy with omalizumab in patients with severe persistent allergic asthma: a real life data in Turkey Tuberk Toraks 2010 58 4 425 34 21341120 28. Braunstahl GJ Chen CW Maykut R Georgiou P Peachey G Bruce J The eXpeRience registry: the ‘real-world’ effectiveness of omalizumab in allergic asthma Respir Med 2013 107 8 1141 51 10.1016/j.rmed.2013.04.017 23721684 29. Brusselle G Michils A Louis R Dupont L Van de Maele B Delobbe A “Real-life” effectiveness of omalizumab in patients with severe persistent allergic asthma: The PERSIST study Respir Med 2009 103 11 1633 42 10.1016/j.rmed.2009.06.014 19619998 30. Cazzola M Camiciottoli G Bonavia M Gulotta C Ravazzi A Alessandrini A Italian real-life experience of omalizumab Respir Med 2010 104 10 1410 6 10.1016/j.rmed.2010.04.013 20483574 31. Chen H Eisner MD Haselkorn T Trzaskoma B Concomitant asthma medications in moderate-to-severe allergic asthma treated with omalizumab Respir Med 2013 107 1 60 7 10.1016/j.rmed.2012.09.008 23083840 32. Eisner MD Zazzali JL Miller MK Bradley MS Schatz M Longitudinal changes in asthma control with omalizumab: 2-year interim data from the EXCELS Study J Asthma 2012 49 6 642 8 10.3109/02770903.2012.690477 22793527 33. Grimaldi-Bensouda L Zureik M Aubier M Humbert M Levy J Benichou J Does omalizumab make a difference to the real-life treatment of asthma exacerbations?: Results from a large cohort of patients with severe uncontrolled asthma Chest 2013 143 2 398 405 10.1378/chest.12-1372 23505637 34. Korn S Thielen A Seyfried S Taube C Kornmann O Buhl R Omalizumab in patients with severe persistent allergic asthma in a real-life setting in Germany Respir Med 2009 103 11 1725 31 10.1016/j.rmed.2009.05.002 19515548 35. Lafeuille MH Dean J Zhang J Duh MS Gorsh B Lefebvre P Impact of omalizumab on emergency-department visits, hospitalizations, and corticosteroid use among patients with uncontrolled asthma Ann Allergy Asthma Immunol 2012 109 1 59 64 10.1016/j.anai.2012.04.015 22727159 36. Maselli DJ Singh H Diaz J Peters JI Efficacy of omalizumab in asthmatic patients with IgE levels above 700 IU/mL: a retrospective study Ann Allergy Asthma Immunol 2013 110 6 457 61 10.1016/j.anai.2013.04.011 23706716 37. Molimard M de Blay F Didier A Le Gros V Effectiveness of omalizumab (Xolair) in the first patients treated in real-life practice in France Respir Med 2008 102 1 71 6 10.1016/j.rmed.2007.08.006 17920257 38. Özgür ES Ozge C Ilvan A Nayci SA Assessment of long-term omalizumab treatment in patients with severe allergic asthma long-term omalizumab treatment in severe asthma J Asthma 2013 50 6 687 94 10.3109/02770903.2013.792348 23557459 39. Tzortzaki EG Georgiou A Kampas D Lemessios M Markatos M Adamidi T Long-term omalizumab treatment in severe allergic asthma: the South-Eastern Mediterranean “real-life” experience Pulm Pharmacol Ther 2012 25 1 77 82 10.1016/j.pupt.2011.11.004 22155001 40. Vennera Mdel C Perez De Llano L Bardagi S Ausin P Sanjuas C Gonzalez H Omalizumab therapy in severe asthma: experience from the Spanish registry--some new approaches J Asthma 2012 49 4 416 22 10.3109/02770903.2012.668255 22443408 41. Vieira T de Oliveira JF da Graca Castel-Branco M Short and long-term quality of life and asthma control with omalizumab therapy in a real life setting in Portugal Allergol Immunopathol (Madr) 2014 42 1 3 10 10.1016/j.aller.2012.07.006 23253691 42. Wittchen HU Muhlig S Klotsche J Buhl R Kardos P Ritz T Omalizumab versus ‘usual care’: results from a naturalistic longitudinal study in routine care Int Arch Allergy Immunol 2012 159 1 83 93 10.1159/000335382 22573022 43. Wu AC Butler MG Li L Fung V Kharbanda EO Larkin EK Primary adherence to controller medications for asthma is poor Ann Am Thorac Soc 2015 12 2 161 6 10.1513/AnnalsATS.201410-459OC 25569765 44. Janson SL Solari PG Trzaskoma B Chen H Haselkorn T Zazzali JL Omalizumab adherence in an observational study of patients with moderate to severe allergic asthma Ann Allergy Asthma Immunol 2015 114 6 516 21 10.1016/j.anai.2015.04.010 26021894 45. Broder MS Chang EY Ory C Kamath T Sapra S Adherence and persistence with omalizumab and fluticasone/salmeterol within a managed care population Allergy Asthma Proc 2009 30 2 148 57 10.2500/aap.2009.30.3190 19152727 46. Hendeles L Khan YR Shuster JJ Chesrown SE Abu-Hasan M Omalizumab therapy for asthma patients with poor adherence to inhaled corticosteroid therapy Ann Allergy Asthma Immunol 2015 114 1 58 62 10.1016/j.anai.2014.10.012 25528738 47. Zuberbier T Bachert C Bousquet PJ Passalacqua G Walter Canonica G Merk H GA(2) LEN/EAACI pocket guide for allergen-specific immunotherapy for allergic rhinitis and asthma Allergy 2010 65 12 1525 30 10.1111/j.1398-9995.2010.02474.x 21039596 48. Senna G Caminati M Lockey RF Allergen immunotherapy adherence in the real world: How bad is it and how can it be improved? Curr Treat Options Allergy 2015 2 39 53 10.1007/s40521-014-0037-6 49. Schlender A Alperin PE Grossman HL Sutherland ER Modeling the impact of increased adherence to asthma therapy PLoS One 2012 7 12 e51139 10.1371/journal.pone.0051139 23236442 50. Saturni S Bellini F Braido F Paggiaro P Sanduzzi A Scichilone N Randomized Controlled Trials and real life studies. Approaches and methodologies: a clinical point of view Pulm Pharmacol Ther 2014 27 2 129 38 10.1016/j.pupt.2014.01.005 24468677 51. Caminati M Senna G Guerriero M Dama AR Chieco-Bianchi F Stefanizzi G Omalizumab for severe allergic asthma in clinical trials and real-life studies: what we know and what we should address Pulm Pharmacol Ther 2015 31 28 35 10.1016/j.pupt.2015.01.006 25640019 52. European Medicines Agency; Xolair: EPAR - Product Information. http://www.ema.europa.eu/ema/index.jsp?curl=pages/medicines/human/medicines/000606/human_med_001162.jsp&mid=WC0b01ac058001d124. Accessed 20 June 2015. 53. Domingo C Pomares X Angril N Rudi N Amengual MJ Mirapeix RM Effectiveness of omalizumab in non-allergic severe asthma J Biol Regul Homeost Agents 2013 27 1 45 53 23489686 54. Arron JR Choy DF Scheerens H Matthews JG Noninvasive biomarkers that predict treatment benefit from biologic therapies in asthma Ann Am Thorac Soc 2013 10 Suppl S206 13 10.1513/AnnalsATS.201303-047AW 24313774 55. Bartminski G Crossley M Turcanu V Novel biomarkers for asthma stratification and personalized therapy Expert Rev Mol Diagn 2015 15 3 415 30 10.1586/14737159.2015.988613 25479456 56. Caffarelli C Calcinai E Rinaldi L Povesi Dascola C Terracciano L Corradi M Hydrogen peroxide in exhaled breath condensate in asthmatic children during acute exacerbation and after treatment Respiration 2012 84 4 291 8 10.1159/000341969 23018317 57. Caffarelli C Dascola CP Peroni D Ricò S Stringari G Varini M Folesani G Corradi M Airway acidification in childhood asthma exacerbations Allergy Asthma Proc 2014 35 3 51 6 10.2500/aap.2014.35.3740 24801459 58. Hilvering B Pavord ID What goes up must come down: biomarkers and novel biologicals in severe asthma Clin Exp Allergy 2015 45 7 1162 9 10.1111/cea.12500 25640208 59. Fajt ML Wenzel SE Asthma phenotypes and the use of biologic medications in asthma and allergic disease: the next steps toward personalized care J Allergy Clin Immunol 2015 135 2 299 310 10.1016/j.jaci.2014.12.1871 25662302 60. Senna G Caminati M Canonica GW Safety and tolerability of sublingual immunotherapy in clinical trials and real life Curr Opin Allergy Clin Immunol 2013 13 6 656 62 10.1097/ACI.0000000000000007 24126613 61. Battaglia S Basile M Spatafora M Scichilone N Are asthmatics enrolled in randomized trials representative of real-life outpatients? Respiration 2015 89 5 383 9 10.1159/000375314 25791779 62. Eakin MN Rand CS Improving patient adherence with asthma self-management practices: what works? Ann Allergy Asthma Immunol 2012 109 2 90 2 10.1016/j.anai.2012.06.009 22840247 63. Shams MR Fineman SM Asthma adherence: how can we help our patients do it better? Ann Allergy Asthma Immunol 2014 112 1 9 12 10.1016/j.anai.2013.10.013 24331386

PMC005xxxxxx/PMC5000548.txt

==== Front BMC Infect DisBMC Infect. DisBMC Infectious Diseases1471-2334BioMed Central London 178610.1186/s12879-016-1786-6Research ArticleCost of hospital management of Clostridium difficile infection in United States—a meta-analysis and modelling study Zhang Shanshan Shanshan.zhang@ed.ac.uk 12Palazuelos-Munoz Sarah Sarah.Palazuelos2@sanofipasteur.com 3Balsells Evelyn M. e.balsells@ed.ac.uk 1Nair Harish Harish.Nair@ed.ac.uk 1Chit Ayman Ayman.Chit@sanofipasteur.com 45Kyaw Moe H. Moe.Kyaw@sanofipasteur.com 41 Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Medical School, Teviot Place, Edinburgh, EH8 9AG UK 2 Department of Preventive Dentistry, Peking University School and Hospital of Stomatology, 22 Zhongguancun South Avenue, Beijing, 100081 China 3 Sanofi Pasteur, Lyon, France 4 Sanofi Pasteur, Swiftwater, PA USA 5 Lesli Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario Canada 25 8 2016 25 8 2016 2016 16 1 44725 4 2016 18 8 2016 © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Clostridium difficile infection (CDI) is the leading cause of infectious nosocomial diarrhoea but the economic costs of CDI on healthcare systems in the US remain uncertain. Methods We conducted a systematic search for published studies investigating the direct medical cost associated with CDI hospital management in the past 10 years (2005–2015) and included 42 studies to the final data analysis to estimate the financial impact of CDI in the US. We also conducted a meta-analysis of all costs using Monte Carlo simulation. Results The average cost for CDI case management and average CDI-attributable costs per case were $42,316 (90 % CI: $39,886, $44,765) and $21,448 (90 % CI: $21,152, $21,744) in 2015 US dollars. Hospital-onset CDI-attributable cost per case was $34,157 (90 % CI: $33,134, $35,180), which was 1.5 times the cost of community-onset CDI ($20,095 [90 % CI: $4991, $35,204]). The average and incremental length of stay (LOS) for CDI inpatient treatment were 11.1 (90 % CI: 8.7–13.6) and 9.7 (90 % CI: 9.6–9.8) days respectively. Total annual CDI-attributable cost in the US is estimated US$6.3 (Range: $1.9–$7.0) billion. Total annual CDI hospital management required nearly 2.4 million days of inpatient stay. Conclusions This review indicates that CDI places a significant financial burden on the US healthcare system. This review adds strong evidence to aid policy-making on adequate resource allocation to CDI prevention and treatment in the US. Future studies should focus on recurrent CDI, CDI in long-term care facilities and persons with comorbidities and indirect cost from a societal perspective. Health-economic studies for CDI preventive intervention are needed. Electronic supplementary material The online version of this article (doi:10.1186/s12879-016-1786-6) contains supplementary material, which is available to authorized users. Keywords Clostridium DifficileEconomic analysisSystematic reviewMeta-analysisSanofi Pasteur funded this studyissue-copyright-statement© The Author(s) 2016 ==== Body Background Clostridium difficile is the leading cause of infectious nosocomial diarrhoea in the United States (US) [1] and the incidence and severity of C. difficile infection (CDI) are increasing [2]. CDI is associated with significant morbidity and mortality; it represents a large clinical burden due to the resultant diarrhoea and potentially life-threatening complications, including pseudomembranous colitis, toxic megacolon, perforations of the colon and sepsis [3–5]. Up to 25 % of patients suffer from a recurrence of CDI within 30 days of the initial infection. Patients at increased risk of CDI are those who are immuno-compromised, such as those with human immunodeficiency virus (HIV) or who are receiving chemotherapy [6–8], patients receiving broad-spectrum antibiotic therapy [9, 10] or gastric acid suppression therapy [9, 11], patients aged over 65 years [10], patients with serious underlying disease [12], patients in intensive care units (ICUs) [10], or patients who have recently undergone non-surgical gastrointestinal procedures or those being tube-fed [10]. CDI represents a significant economic burden on US healthcare systems. Infected patients have an increased length of hospital stay compared to uninfected patients, besides there are significant costs associated with treating recurrent infections. A few systematic reviews of cost-of-illness studies on CDI cost are available [13–21]. These reviews mainly listed the range of reported cost of their respective observation period or were limited by the small number of included studies or inadequate control for confounding factors. No meta-analysis of large number of cost data in the US has been conducted to date. The cost for patients discharged to long-term care facility (LTCF) and recurrent CDI management are understudied. The cost of case management and total financial burden of CDI treatment in the US is therefore underestimated and remains controversial. The aim of the current study is to conduct a systematic review and meta-analysis of currently available data to identify and quantify the financial burden attributable to CDI, and to further estimate the total economic burden of CDI hospital management in the US. Methods Search strategy English-language databases with online search tools were searched for to offer maximum coverage of the relevant literature: Medline (via the Ovid interface 1946 to July 2015); EMBASE (via the Ovid interface 1980 to July 2015); The Centre for Review and Dissemination Library (incorporating the DARE, NHS EED, and NHS HTA databases); The Cochrane Library (via the Wiley Online Library) and Health Technology Assessment Database (1989 to July 2015). We supplemented our data by searching relevant published reports from: National epidemiological agencies, Google search for grey literature and hand searched the reference lists of the included studies. The general search headings identified were: Clostridium difficile, economic, costs, cost analysis, health care costs, length of stay, hospitalization. Examples of the strategy for Medline and EMBASE are listed in Additional file 1. Study selection All studies that reported novel direct medical cost and/or indirect costs related to CDI management were included. Review articles, comments, editorials, letters, studies of outbreaks, case reports, posters and articles reporting results from economic modelling of a single treatment measure (i.e. cost effectiveness of faecal transplantation) were excluded in the final analysis. All relevant publications from January 2005 to July 2015 were included in the search. We included the following healthcare settings: hospitals, long-term care facilities and community. Geographical scope covered the US. We did not apply any language restriction. Our predefined inclusion and exclusion criteria are shown in Additional file 1. Data extraction Two reviewers (SP, SZ) independently selected the included articles and extracted data. After combining their results, any discrepancies were solved by discussion with HN and MK. The primary outcomes were CDI-related costs (total costs of those with CDI and other comorbidities) and CDI-attributable costs (total costs of CDI management only, after controlling for the confounders). For studies with control groups (e.g. matched patients without CDI), the CDI-attributable cost extracted was either the cost provided by the articles or calculated by reviewers using the CDI-related cost minus the treatment cost of control groups. The secondary outcome was resource utilization associated with CDI, i.e. CDI-related length of stay (LOS) in hospital and CDI-attributable LOS. The study characteristics of each article were extracted. These included basic publication information, study design, statistical methods, economic data reporting characteristics and population information. When multiple cost data were presented in a study, we included only one cost estimate for each population subgroup as per the priority below:Matched data > Unmatched data. Adjusted model results > Unadjusted model results. Regression model results > Calculated difference. Total cost/charges > Subgroup cost/charge (i.e. survivors, died). Median (Interquantile Range: IQR) > Mean (Standard Deviation, SD). All costs/charges data were inflated to 2015 US$ equivalent prices adjusted for the Consumer Price Index. If the price year was not reported, it was assumed to be the last year of the data collection period. In cases where charges were reported without cost-to-charge given, costs were estimated using a cost-to-charge ratio of 0.60, which is commonly used value in US health economic studies [22]. Meta-analysis and estimation of national impact We carried out meta-analysis for cost studies following a Monte Carlo simulation approach, as reported by Jha et al [23] and Zimlichman et al [17], bearing in mind the heterogeneity of the included studies. For each subgroup of CDI, we synthesized the data and reported a point estimate and 90 % confidence intervals (CIs) for the CDI-related cost, CDI-attributable cost and their respective LOS. For each included study, we simulated distribution with pooled results weighted by sample size. We fitted a triangular distribution for each of the included studies based on their reported measures of central tendency and dispersion, i.e. mean and 95 % CI, median and IQR, or median and range. Then we simulated 100,000 sample draws from the modeled distribution of each study. At each iteration, we calculated the weighted average of all included studies. Finally, we reported the mean and 90 % CI from the resulting distribution of the 100,000 weighted average of CDI. This approach facilitated the combination of cost data and eliminated the limitation of combining non-normally distributed data. Monte Carlo simulations were conducted using the Monte Carlo simulation software @RISK, version 7.0 (Palisade Corp). We estimated the national financial impact of CDI on the US healthcare system, by determining the potential boundaries. The higher boundary was the total number of CDI cases in the US in 2011 extracted from Lessa et al [24], while the lower boundary was the result from a meta-analysis to estimate the total burden of CDI cases in the US [25] (For detailed results see Additional file 1). The total annual cost of CDI management was calculated multiplying the average cost of management per case of CDI, with the total number of CDI cases per year in the US (Fig. 1). We assumed that all CDI cases received treatment in hospital. A point estimate of the final cost (with range) was reported based on a Monte Carlo simulation of 100,000 sample draws.Fig. 1 Formula for total annual cost calculation Sensitivity analysis We extracted the total number of CDI patients and CDI-attributable costs from previous studies [25] and reviews [17, 26] to carry out a sensitivity analysis of our total cost estimates. Quality assessment The quality of the studies included was assessed mainly based on the complexity of the statistical method (Fig. 2). All studies were included in the final analyses.Fig. 2 Quality Assessment Method Results Search results The search strategy identified 2671 references from databases. Seven additional references were identified through other sources. After screening the titles, abstracts and relevant full texts (Fig. 3), a total of 42 studies were included in this review.Fig. 3 PRISMA diagram of economic burden search of C. difficile Study characteristics The characteristics of the 42 included studies [27–68] are summarized in Table 1. Cost data collection periods ranged from 1997 to 2012. Most studies (n = 27) used national level databases, with 17 used National Independent Sample (NIS) database and the remaining 10 studies extracted data from various national databases. Fifteen studies were conducted at state level, of which 6 studies only collected data in single hospital. All studies reported cost in hospital level of care, no articles identified in LTCF and community. Nearly all identified references were retrospective hospital database studies (n = 40) and only 1 study was a prospective observational study [29] and another study was a decision tree model [48].Table 1 Overview of selected references that assessed economic burden attributable to CDI by type of CDI considered in the US ID Reference State, city Data collection period Type of CDI Population Sample size (Total) Sample size (CDI cases) Age of CDI patients Mean ± SD or (Range), years CDI definition (short) Quality assessment Statistical methodology Data source 1 Ali 2012 [27] National 2004–2008 Comp. Liver transplant 193,714 5159 >18 ICD-9; 008.45 (Primary Diagnosis-PD, Secondary Diagnosis-SD) Low No matching; no regression Nationwide Inpatient Sample (NIS) 2 Ananthakrishnan 2008 [28] National 2003 Comp. IBD 124,570 2804 >18 CDI: 73a; CDI-IBD: 54a ICD-9; 008.45 (PD) Medium No matching; regression NIS 3 Arora 2011 [29] Houston 2007–2008 Req. General 85 85 Horn’s Index Score 1&2: 64 ± 19; Horn’s Index Score 3&4: 65 ± 15 Toxin assay Low No matching; no regression St Luke’s Episcopal Hospital 4 Bajaj 2010 [30] National National: 2005 Tertiary: 2002–2006 Both Cirrhosis 83,230 1165 CDI: 69 ± 20; Cirrhosis-CDI: 61 ± 15 ICD-9; 008.45 (PD, SD) Medium No matching; regression NIS 5 Campbell 2013 [31] National 2005–2011 Comp. General NR 4521 Renal impairment 72.9 ± 13.4; Advanced Age: 78.7 ± 7.4; Cancer/BMT 69.2 ± 14.0; IBD 61.2 ± 18.3; Cabx exposure 61.2 ± 14.8 Toxin assay High Matching; regression Health Facts electronic health record (HER) database 6 Damle 2014 [14] National 2008–2012 Comp. Colorectal surgery 84,648 1266 >18 63 ± 17 ICD-9; 008.45 (PD, SD) Medium No matching; regression University Health System Consortium database 7 Dubberke 2008 [33] Missouri 2003–2003 Both Non- Surgical 24,691 439 67(18–101) a Toxin assay High Matching; regression Barnes-Jewish Hospital Electronic record 8 Dubberke 2014 [2, 34, 71] Missouri 2003–2009 Both Recurrent CDI 3958 421 >18 Toxin assay or clinical diagnosis for recurrent CDI High Matching; regression Barnes-Jewish Hospital Electronic record 9 Egorova 2015 [35] National 2000–2011 Comp. Vascular surgery NR 2808 68.4 ICD-9; 008.45 (PD, SD) High Matching: regression NIS 10 Flagg 2014 [36] National 2004–2008 Comp. Cardiac surgery 349,112 2581 All age band ICD-9; 008.45 (SD) High Matching: regression NIS 11 Fuller 2009 [37] Maryland and California 2007–2008 for Maryland 2005–2006 for California Comp. General 3760 3760 – Clinical diagnosis Medium No matching; regression Health Services and Cost Review Commission, Maryland; The Office of State-wide Planning and Development, California 12 Glance 2011 [38] National 2005–2006 Comp. Trauma 149,648 768 69(45–82) a Clinical diagnosis Medium No matching; regression NIS 13 Jiang 2013 [39] Rhode Islands 2010–2011 Comp. General 225,999 6053 >18 71.4 ± 15.8 ICD-9; 008.45 (SD) Medium Matching; no regression Rhode Island’s 11 acute-care hospitals 14 Kim 2012 [40] National 2001–2008 Comp. Cystectomy 10,856 153 >18 68.49 ± 10.52 ICD-9 ; 008.45 (SD) Medium No matching; regression NIS 15 Kuntz 2012 [41] Colorado 2005–2008 Comp. General 3067 3067 All age band, Outpatient 62.8 ± 19.4; Inpatient 69.9 ± 16.3 ICD-9 + toxin assay Medium No matching; regression Kaiser Permanente Colorado and Kaiser Permanente Northwest members 16 Lagu 2014 [42] Massachusetts, Boston one hospital 2004–2010 Comp. Sepsis 218,915 2348 70.9 ± 15.1 ICD-9; 008.45 (PD, SD) + toxin assay Medium Matching; no regression Baystate Medical Center (Premier Healthcare Informatics database, a voluntary, fee-supported database) 17 Lameire 2015 National 2002–2009 Comp. Cardiac surgery 512,217 421,294 >40 CABG 65.4 ± 10.5 VS 66.1 ± 12.3 ICD-9; 008.45 (PD, SD) Medium No matching; regression NIS 18 Lawrence 2007 [44] Missouri 1997–1999 Both ICU 1872 76 Primary 68.9 (34–93) Secondary 58.7 (16–91) Toxin assay Medium No matching; regression A 19-bed medical ICU in a Midwestern tertiary care referral center. 19 Lesperance 2011 [45] National 2004–2006 Comp. Elective colonic resections 695,010 10,077 >18 All 69.8; Surgery-CDI 68.7 ICD-9; 008.45 (SD) Medium No matching; regression NIS 20 Lipp 2012 [46] New York 2007–2008 Comp. General 4,853,800 3883 >17 ICD-9; 008.45 (SD) Medium No matching; regression - The SPARCS database- acute care non-federal hospitals in New York State 21 Maltenfort 2013 [47] National 2002–2010 Both Arthroplasty NR NR All age band ICD-9; 008.45 (PD, SD) Low No matching; no regression NIS 22 McGlone 2012 [48] National 2008 Comp. General NR NR >65 ICD-9; 008.45 (SD) Low No matching; no regression Decision tree model 23 Nguyen 2008 [49] National 1998–2004 Comp. IBD 527,187 2372 47.4 ± 0.2 ICD-9; 008.45 (secondary diagnosis) Medium No matching; regression NIS 24 Nylund 2011 [50] National 1997,2000, 2003,2006 Both Children 10,495,728 21,274 CDI 9.5 ± 0.07(SEM) ICD-9; 008.45 (PD, SD) High Matching: regression Healthcare Cost and Utilization Project Kids’Inpatient Database 25 O’Brien 2007 [51] Massachusetts 1999–2003 Req. General 3692 1036 Primary 70 ± 17.6; Secondary 70 ± 17.2 ICD-9; 008.45 (PD, SD) Low No matching; no regression Massachusetts hospital discharge data 26 Pakyz 2011 [52] National 2002–2007 Comp. General 30,071 10,857 CDI 61 ± 17 ICD-9; 008.45 (SD) High Matching; regression University Health System Consorsoum (UHC) 27 Pant 2012 [53] National 2009 Both Organ transplant (OT) 244,955 6451 >18, OT-CDI 58 ± 16 a; CDI-only 73 ± 22 a ICD-9; 008.45 (PD, SD) Medium No matching; regression NIS 28 Pant 2012 (2) [54] National 2009 Both Renal disease 184,139 5151 >18, ESRD + CDI 66 ± 14 CDI ONLY 70 ± 17 ICD-9; 008.45 (PD, SD) Medium No matching; regression NIS 29 Pant 2013 [55] National 2009 Both Children with IBD 12,610 447 <20, 15.1 ± 4.1 ICD-9; 008.45 (PD, SD) Medium No matching; regression The Healthcare Cost and Utilization Project Kids’ Inpatient Database (HCUP-KID) 30 Peery 2012 [56] National From 2009 Req. General 110,533 110,533 All age band ICD-9; 008.45 (PD) Low No matching; no regression National Ambulatory Medical Care Survey (NAMCS) and NIS 31 Quimbo 2013 [57] National 2005–2010 Comp. High Risk subgroups 21,177 26,620 >18 67.5 ± 17.6 ICD-9; 008.45 (PD, SD) High Matching: regression HealthCare Integrated Research Database 32 Reed 2008 Pennsylvania 2002–2006 Comp. High Risk subgroups 9164 524 >17 Hospital acquired CDAD Low No matching; no regression A large academic community hospital 33 Sammons 2013 [59] National 2006–2011 Both Children 13,295 4447 1–18 6 (2–13) a ICD-9; 008.45 (PD, SD) + toxin assay High Matching; regression Free-standing children’s hospitals via the Paediatric Health Information System (PHIS) 34 Singal 2014 [60] National 2007 Comp. Cirrhosis 89,673 1444 All age band ICD-9; 008.45 (PD, SD) Medium No matching; regression NIS 35 Song 2008 [61] Maryland 2000–2005 Both General 9025 630 >18 unmatched 57.6 matched 60.3 Toxin assay High Matching; regression The Johns Hopkins hospital 36 Stewart 2011 [62] National 2007 Both General 82,214 41,207 All age band, 70 ICD-9; 008.45 (PD, SD) Medium Matching; no regression NIS 37 Tabak 2013 [63] Pennsylvania 2007–2008 Comp. General 77,257 255 All 64.8 ± 17.6 CDI 71.1 ± 14.8 Toxin assay High Matching; regression Six Pennsylvania hospitals via a clinical research database 38 VerLee 2012 Michigan 2002–2008 Req. General 517,413 517,413 All age band ICD-9; 008.45 (PD) Low No matching; no regression All Michigan acute care hospitals 39 Wang 2011 [65] Pennsylvania 2005–2008 Both General 7,227,788 78,273 All age band ICD-9; 008.45 (PD, SD) High Matching; regression The Pennsylvania Health Care Cost Containment Council (PHC4) database 40 Wilson 2013 [66] National 2004–2008 Comp. Ileostomy 13,245 217 All age band ICD-9; 008.45 (SD) High Matching; regression NIS 41 Zerey 2007 [67] National 1999–2003 Both Surgical 1,553,597 8113 All age band 70 am ICD-9; 008.45 (PD, SD) Medium No matching; regression NIS 42 Zilberberg 2009 [68] National 2005 Both Prolonged acute mechanical ventilation 64,910 3468 >18 66.7 ± 15.9 ICD-9; 008.45 (PD, SD) Medium Matching; no regression NIS Abbreviations: NR not reported, IBD inflammatory bowel disease, LOS length of stay, ICU intensive care unit, retrosp. retrospective, Comp. complicating, Req. requiring, both requiring and complicating, PD primary diagnosis, SD secondary diagnosis a Median (Range) Most studies (n = 15) investigated economic outcomes in all age inpatients. Three studies reported cost data in children less than 20 years old. The mean/median age of the CDI patient groups ranged from 47.4 to 73.0 years. Other studies investigated complicated CDI in high-risk patient groups, such as those with major surgery (n = 16), inflammatory bowel diseases (n = 2), liver or renal disease (n = 4), elderly (n = 2) and ICU patients (n = 1). There was 1 study each in non-surgical inpatients, sepsis inpatients and patients with prolonged acute mechanical ventilation. There was 1 study focusing only on recurrent CDI in the general population. The sample sizes of included studies ranged from 85 to 7,227,788, with a median sample size of 83,939. A total of 28.8 million inpatient hospital-days were analysed, of which 1.31 million inpatient hospital-days were CDI patients. The median sample size of CDI population was 2938. The methods to identify CDI varied according to the type of CDI that was assessed in the study. CDI cases were identified either with laboratory test, i.e. positive C. diffcile toxin assay, or hospital discharge diagnosis of C. difficile (primary and/secondary) from administrative datasets using the International Classifications of diseases, Ninth, Clinical Modification, ICD-9-CM 008.45. Clinical diagnosis was also used in two studies. CDI was classified in three types: Community-onset CDI (CO-CDI) requiring hospitalization, Hospital-onset CDI (HO-CDI) complicating other diseases, or both CDI (Table 2). Most of included studies considered HO-CDI (n = 23) or both CDI types (n = 17). Only four studies investigated CO-CDI only. However, subgroup data of CO-CDI is also available in studies that reported both CDI types.Table 2 Classification of CDI Cases by Setting of Acquisition Case definition Criteria for classification CO-CDI - Discharge code ICD-9-CM 008.45 as Primary diagnosis HO-CDI - Discharge code ICD-9-CM 008.45 as secondary diagnosis, without a primary diagnosis of a CDI-related symptom (e.g. diarrhea) - Study population ≥ 48 h of hospitalization - Symptom onset and/or positive laboratory assay at least ≥ 48 h hospitalization Both CDI - No distinction of settings of acquisition - Discharge code ICD-9-CM 008.45 in any position Abbreviations: CO-CDI community-onset CDI, HO-CDI hospital-onset CDI, ICD-9-CM The International Classification of Diseases, Ninth Revision, Clinical Modification CDI costs and LOS The mean CDI-attributable costs per case of CO-CDI were $20,085 (Range: $7513–$29,662), lower than HO-CDI $34,149 (Range:$1522–$122,318). HO-CDI showed a wider range within which the additional cost for CDI in the general population ranged from $6893 to $90,202 and in high risk groups ranged from $7332 in congestive heart failure patients to $122,318 in renal impairment patients. The mean CDI-attributable LOS was 5.7 days (Range: 2.1–33.4) for CO-CDI, 7.8 (Range:2.3–21.6) days for HO-CDI, and 13.6 (Range: 2.2–16) days for both groups. Cost data and LOS for individual studies are presented in Tables 3 and 4.Table 3 CDI-attributable costs/charges and CDI-related management costs/charges Author, Year Population Outcome Statistic Incremental CDI-attributable cost/charges CDI-related cost/charges Note Sample size Attributable cost 2015$ SD or 95 % CI Sample size CDI only cost 2015$ SD, 95 % CI or IQR CO-CDI Inpatient Cost Arora 2011 [29] General Cost Median 85 25,436 85 25,436 O’Brien 2007 [51] General Cost Mean 4015 14,736 4015 14,736 Peery 2012 [56] General Cost Median 110,553 7513 110,553 7513 VeerLee 2012 [64] General Charges Mean 68,686 74,211 120,156 68,686 74,211 120,156 Kuntz 2012 [41] General Cost Mean 1650 929 4800 1650 929 4800 Outpatient Kuntz 2012 [41] General Cost Mean 1316 11,877 35,923 1316 11,877 35,923 Inpatient O’Brien 2007 [51] General Cost Median 1036 7263 1036 7263 PD VeerLee 2012 [64] General Charges Mean 17,413 27,463 40,484 17,413 27,463 40,484 PD O’Brien 2007 [51] General Cost Mean 3327 16,946 34,655 3327 16,946 Rehospitalisation Sammons 2013 [59] Children Cost Mean 2060 19,993 15,973 24,013 2060 19,993 15,973 24,013 Community onset Ananthakrishnan 2008 [28] IBD Charges Median 44,400 16,864 CDI only Pant 2013 [55] IBD Charges Mean 12,610 12,761 6868 18,655 447 50,050 CDI only Bajaj 2010 [30] Cirrhosis Charges Mean 58,220 70,309 CDI only Quimbo 2013 [57] CDI History Cost Mean 1866 29,662 20,798 42,300 933 51,863 36,641 73,411 CDI only Total numbers/Weighted Mean 224,617 20,085 314,141 23,322 HO-CDI Inpatient Cost Fuller 2009 [37] General Cost Coefficient 1282 18,466 288 1282 18,466 288 Maryland, SD Fuller 2009 [37] General Cost Coefficient 2478 29,980 271 2478 29,980 271 California, SD Lipp 2012 [46] General Cost Mean 3826 32,050 3826 32,050 SD McGlone 2012 [48] General Cost Median 54,046 10,016 8547 12,055 54,046 10,016 8547 12,055 SD Cost-hospital perspective-6 days LOS McGlone 2012 [48] General Cost Median 54,046 11,116 9476 13,366 54,046 11,116 9476 13,366 10 days LOS McGlone 2012 [48] General Cost Median 54,046 12,194 10,146 14,896 54,046 12,194 10,146 14,896 14 days LOS O’Brien 2007 [51] General Cost Median 2656 6630 2656 6630 SD VeerLee 2012 [64] General Charges Mean 51,273 90,202 146,767 51,273 90,202 146,767 SD Jiang 2013 [39] General Cost Median 7264 11,689 1211 21,751 Pakyz 2011 [52] General Cost Mean 30,071 31,180 10,857 64,732 Unadjusted Pakyz 2011 [52] General Cost Median 30,071 24,456 10,857 39,598 22,400 88,537 Unadjusted Pakyz 2011 [52] General Cost Mean 30,071 31,169 10,857 64,000 63,541 64,458 Adjusted Tabak 2013 [63] General Cost Mean 1020 6893 1365 13,617 255 22,992 12,222 42,470 Campbell 2013 [31] Age > = 65 Cost Mean 3064 7536 4302 10,771 3064 48,932 67,727 Quimbo 2013 [57] Elderly Cost Mean 34,732 45,749 43,279 48,359 10,933 83,004 78,548 87,713 Sammons 2013 [59] Children Cost Mean 2414 99,012 84,626 113,398 2414 99,012 84,626 113,398 Ananthakrishnan 2008 [28] IBD Charges Median 80,170 7655 2804 24,623 Ananthakrishnan 2008 [28] IBD Charges Mean 80,170 14,368 9467 19,270 – Campbell 2013 [31] IBD Cost Mean 84 1522 −14,932 11,888 84 40,194 44,845 Quimbo 2013 [57] IBD cost Mean 3618 11,825 9851 14,181 1206 42,035 35,918 49,191 Ananthakrishnan 2008 [28] Ulcerative colitis (UC) Charges Median 1843 26,750 Nguyen 2008 [49] UC Charges Mean 43,645 14,749 196 43,381 Regression Ananthakrishnan 2008 [28] Crohn's disease (CD) Charges Median 961 22,738 Nguyen 2008 [49] CD Charges Mean 73,197 14,316 329 41,453 Regression Reed 2008 Digestive disorders Charges Mean 2394 3670 320 9076 8068 Damle 2014 [14] Colorectal surgery Cost Median 84,648 14,644 13,700 15,589 1266 21,309 38,218 – Kim 2012 [40] Cystectomy Cost Mean 10,856 25,014 153 57,379 50,204 64,554 Lesperance 2011 [45] Elective colonic resection Charges Mean 695,010 84,899 10,077 158,401 Reed 2008 Major bowel procedures Charges Mean 1035 25,476 45 47,064 31,302 Wilson 2013 [66] Ileostomy Cost Mean 13,462 20,272 217 35,076 Wilson 2013 [66] Ileostomy Cost Coefficient 13,462 17,513 14,106 20,921 Egorova 2015 [35] Vascular surgery Cost Median 450,251 14,250 4708 36,847 22,912 62,903 Flagg 2014 [36] Cardiac surgery Cost Median 5160 19,524 2580 213,661 Adjusted Flagg 2014 [36] Cardiac surgery Cost Median 349,122 38,320 2580 72,730 Unadjusted Lemaire 2015 [43] Cardiac surgery Cost Median 421,294 35,968 – 72,685 CABG Lemaire 2015 [43] Cardiac surgery Cost Median 90,923 59,696 – 106,141 VS Reed 2008 OR procedure for infectious /parasitic diseases Charges Mean 449 7462 32 35,524 25,498 Glance 2011 [38] Trauma Cost Median 149,656 24,131 768 39,296 Campbell 2013 [31] Cabx Cost Mean 1641 18,567 10,448 26,687 1641 78,948 99,739 Quimbo 2013 [57] Cabx Cost Mean 17,716 38,413 35,195 41,922 4429 64,242 59,145 69,780 Lagu 2014 [42] Sepsis Cost Median 4736 5792 4933 6665 2368 28,576 16,496 50,494 Reed 2008 Septicaemia Charges Mean 1211 9141 92 22,378 20,591 Campbell 2013 [31] Renal impairment Cost Mean 3236 5024 1118 8928 3236 50,586 72,180 Quimbo 2013 [57] RI Cost Mean 22,132 122,318 111,315 134,405 5533 201,212 183,706 220,386 Ali 2012 [27] Liver transplant Charges Mean 193,714 77,361 5159 158,038 Singal 2014 [60] Cirrhosis Charges Mean 89,673 23,310 1444 47,401 Reed 2008 Congestive Heart Failure Charges Mean 2542 7332 35 14,738 13,841 Quimbo 2013 [57] Immunocompromised Cost Mean 14,344 33,632 30,151 37,516 3586 73,612 66,048 82,041 Campbell 2013 [31] Cancer/BMT Cost Mean 782 687 −6480 7855 782 48,280 72,605 Total numbers/Weighted mean 3,020,827 34,149 207,801 49,712 Dubberke 2014 [2, 34, 71] Recurrent CDI Cost Mean 3958 12,163 3958 11,523 4728 26,167 Total cost difference Dubberke 2014 [2, 34, 71] Recurrent CDI Cost Mean 3958 12,692 9752 15,919 Adjusted Song 2008 [61] General Cost Median 1260 373 630 30,305 Stewart 2011 [62] General Cost Mean 82,414 9670 41,207 26,790 Wang 2011 [65] General Cost Median 7,227,788 4914 78,273 12,081 Nylund 2011 [50] Children Charges Median 3565 15,937 3565 25,549 1997 Nylund 2011 [50] Children Charges Median 4356 20,750 4356 31,858 2000 Nylund 2011 [50] Children Charges Median 5574 23,627 5574 33,625 11,348 97,822 2003 Nylund 2011 [50] Children Charges Median 7779 23,362 7779 35,444 13,601 110,343 2006 Sammons 2013 [59] Children Cost Mean 698,616 51,304 44,746 57,969 698,616 51,304 44,746 57,969 Dubberke 2008 [33] Non-surgical Cost Median 24,691 11,749 439 20,569 Raw data Dubberke 2008 [33] Non-surgical Charges Median 24,691 23,961 439 42,154 Raw data Dubberke 2008 [33] Non-surgical Cost Mean 24,691 3173 3078 3815 Linear regression Dubberke 2008 [33] Non-surgical Cost Median 24,691 4190 342 18,842 Matched cases Dubberke 2008 [33] Non-surgical Cost Mean 24,691 6520 4910 8381 Linear regression, 180 days Dubberke 2008 [33] Non-surgical Cost Median 24,691 9284 342 35,414 Matched cases, 180 days Zerey 2007 [67] Surgical Charges Median 1,553,597 59,424 8113 81,708 Zerey 2007 [67] Surgical Charges Coefficient 1,553,597 94,402 91,589 97,216 Multivariate regression analysis Zilberberg 2009 [68] Prolonged acute mechanical ventilation (PAMV) Cost Median 64,910 48,065 3468 190,188 107,689 333,290 Unadjusted Zilberberg 2009 [68] PAMV Cost Mean 3370 12,616 9186 16,046 3468 91,039 71,306 Adjusted Lawrence 2007 [44] ICU Cost Median 1872 7043 76 15,016 ICU stay Lawrence 2007 [44] ICU Cost Median 1872 36,095 76 60,723 Entire hospital stay Bajaj 2010 [30] Cirrhosis Charges Mean 83,230 49,460 1165 96,678 Maltenfort 2013 [47] Arthroplasty Charges Median – 43,648 – 84,877 52,498 142,827 Pant 2012 [53] Organ transplant Charges Mean 49,198 77,246 73,412 81,080 63,651 42,054 69,033 Pant 2012 (2) [54] Renal disease Charges Coefficient 184,139 69,679 68,338 71,020 59,793 87,982 Pant 2013 [55] IBD Charges Mean 12,610 39,453 32,470 46,436 Total numbers/Weighted Mean 10,012,927 14,403 981,005 45,421 Abbreviations: CO-CDI community-onset CDI, HO-CDI hospital-onset, PAMV prolonged acute mechanical ventilation, Cabx concomitant antibiotic use, UC ulcerative colitis, CD Crohn’s disease, IBD inflammatory bowel disease, ICU intensive care unit, CABG coronary artery bypass grafting, VS valvular surgery, BMT, PD primary diagnosis, SD secondary diagnosis, Calculated numbers were marked in Italic, attributable cost = cost of CDI group- cost of control non-CDI group Table 4 CDI-attributable LOS and CDI-related LOS Reference Population Statistic CDI VS NO CDI LOS (Days) CDI LOS (Days) Sample size Value SD or 95 % CI Sample size Value SD or 95 % CI CO-CDI Inpatient days Arora 2011 [29] Horn’s index 1&2 Mean 33 15.1 16.2 33 15.1 16.2 Arora 2011 [29] Horn’s index 3&4 Mean 52 33.4 33.3 52 33.4 33.3 Kuntz 2012 [41] General outpatient Mean 1650 10.0 17.0 1650 10.0 17.0 Kuntz 2012 [41] General inpatient Mean 1316 14.9 20.9 1316 14.9 20.9 O’Brien 2007 [51] General Mean 4015 6.4 4015 6.4 Pant 2013 [55] IBD Coefficient 12,610 2.1 1.4 2.8 2.1 1.4 2.8 Peery 2012 [56] General Median 110,553 5.0 110,553 5.0 Quimbo 2013 [57] CDAD History Mean 1866 2.9 2.4 3.6 933 8.9 7.2 11.0 Sammons 2013 [59] Children Median 2060 5.6 4.5 6.6 2060 6.0 4.0a 13.0a VeerLee 2012 [64] General Mean 68,686 7.1 7.0 68,686 7.1 7.0 Weighted Mean 202,841 5.7 189,298 5.9 HO-CDI inpatient days Jiang 2013 [39] General Median 7264 8.0 1211 13.0 Lipp 2012 [46] General Mean 3826 12.0 3826 12.0 Pakyz 2011 [52] General Mean 30,071 11.1 10,857 21.1 21.0 21.2 Tabak 2013 [63] General Median 1020 2.3 0.9 3.8 255 12.0 9.0a 21.0a Wang 2013 General Median 7,227,788 7.0 78,273 6.0 4.0a 11.0a Campbell 2013 [31] Age > = 65 Mean 3064 3.0 1.4 4.6 3064 21.3 25.3 Quimbo 2013 [57] Elderly Mean 34,732 7.8 7.5 8.1 10,933 18.8 18.2 19.5 Sammons 2013 [59] Children Median 2414 21.6 19.3 23.9 2414 23.0 12.0a 44.0a Ananthakrishnan 2008 [28] IBD Median 80,170 3.0 2804 7.0 Campbell 2013 [31] IBD Mean 84 3.0 −2.3 8.3 84 21.0 19.1 Quimbo 2013 [57] IBD Mean 3618 3.3 2.9 3.7 1206 12.8 11.6 14.2 Nguyen 2008 [49] Crohn’s disease Mean 73,197 3.8 329 9.5 Nguyen 2008 [49] Ulcerative colitis Mean 43,645 3.2 196 9.9 Reed 2008 Digestive disorders Mean 2394 3.0 320 6.9 5.2 Damle 2014 [14] Colorectal surgery Median 84,648 8.4 8.0 8.9 1266 13.0 18.0 Lesperance 2011 [45] Elective colonic resection Mean 695,010 11.7 10,077 22.6 Reed 2008 Major bowel procedures Mean 1035 10.0 45 20.9 11.3 Wilson 2013 [66] Ileostomy Mean 13,462 11.6 217 18.7 Campbell 2013 [31] Cabx exposure Mean 1641 7.8 5.7 9.9 1641 29.3 34.7 Quimbo 2013 [57] Concomitant Antibiotic Use Mean 17,716 7.8 7.4 8.3 4429 17.9 17.0 18.9 Lagu 2014 [42] Sepsis Mean 4736 5.1 4.4 5.7 2368 19.2 Reed 2008 Septicemia Mean 1211 5.0 92 10.7 7.6 Egorova 2015 [35] Vascular surgery Median 450,251 6.7 4708 15.0 9.0a 25.0a Flagg 2014 [36] Cardiac surgery Median 349,122 10.0 2580 21.0 Glance 2011 [38] Trauma Median 149,656 10.0 768 16.0 Lemaire 2015 [43] Cardiac surgery (CABG) Median 421,294 12.0 19.0 Lemaire 2015 [43] Cardiac surgery (VS) Median 90,923 16.0 24.0 Reed 2008 Congestive Heart Failure Mean 2542 5.0 35 9.7 7.0 Reed 2008 OR procedure for infectious /parasitic diseases Mean 449 2.0 32 14.7 8.6 Lawrence 2007 [44] ICU Median 76 14.9 1.0b 86.0b Lawrence 2007 [44] ICU Median 76 38.3 4.0b 184.0b Ali 2012 [27] Liver transplant Mean 193,714 10.1 5159 17.8 Singal 2014 [60] Cirrhosis Mean 89,673 7.5 1444 13.9 Quimbo 2013 [57] Immunocompromised Mean 14,344 8.4 7.9 9.0 3586 22.1 20.6 23.7 Campbell 2013 [31] Renal impairment Mean 3236 4.0 2.9 5.1 3236 22.7 28.2 Quimbo 2013 [57] Renal impairment Mean 22,132 17.3 16.4 18.3 5533 37.5 35.5 39.6 Campbell 2013 [31] Cancer/BMT Mean 782 4.0 2.3 5.7 782 21.3 18.5 Weighted Mean 10,120,864 7.8 168,892 13.5 Both CO-CDI and HO-CDI inpatient cost Song 2008 [61] General Median 1260 4.0 630 22.0 Stewart 2011 [62] General Mean 82,414 5.1 41,207 13.0 14.0 Nylund 2011 [50] Children, 1997 Median 3565 3.0 3565 5.0 3.0a 14.0a Nylund 2011 [50] Children, 2000 Median 4356 4.0 4356 6.0 3.0a 15.0a Nylund 2011 [50] Children, 2003 Median 5574 4.0 5574 6.0 3.0a 14.0a Nylund 2011 [50] Children, 2006 Median 7779 4.0 7779 6.0 3.0a 15.0a Sammons 2013 [59] Children Median 698,616 12.2 10.6 13.8 698,616 10.0 5.0a 23.0a Bajaj 2010 [30] Cirrhosis Mean 83,230 7.1 1165 14.4 Bajaj 2010 [30] CDI only Mean 58,220 12.7 Pant 2013 [55] IBD Mean 12,610 2.2 1.5 2.8 447 8.2 Dubberke 2008 [33] Non-surgical Median 24,691 6.0 439 10.0 2. 0b 87.0b Lawrence 2007 [44] ICU stay Median 1872 3.1 76 6.1 1.0b 86.0b Lawrence 2007 [44] Hospital stay Median 1872 14.4 76 24.5 2.0b 184.0b Maltenfort 2013 [47] Arthroplasty Median – 7.0 – 10.0 7.0a 17.0a Zerey 2007 [67] Surgical Median 1,553,597 16.0 15.6 16.4 8113 18.0 Pant 2012 [53] Organ transplant Median 49,198 9.6 9.3 9.9 63,651 Pant 2012 (2) [54] Renal disease Coefficient 184,139 9.4 9.2 9.5 59,793 Zilberberg 2009 [68] Prolonged acute mechanical ventilation Median 3370 6.1 4.9 7.4 3468 25.0 15.0a 40.0a Weighted Mean 2,718,143 13.6 957,175 9.0 Abbreviations: CO-CDI community-onset CDI, HO-CDI Hospital-onset CDI, PAMV prolonged acute mechanical ventilation, Cabx concomitant antibiotic use, UC ulcerative colitis, CD Crohn’s disease, IBD inflammatory bowel disease, ICU intensive care unit, CABG coronary artery bypass grafting, VS valvular surgery, BMT, PD primary diagnosis, SD secondary diagnosis, Calculated numbers were marked in Italic, attributable cost = cost of CDI group- cost of control non-CDI group aQ1-Q3 bMin-Max Using a Monte Carlo simulation, we generated point estimates and 90 % CI for both cost and LOS; the meta-analysis results are shown in Table 5. The total cost of inpatient management of CDI-related disease was $42,316 (90 % CI: $39,886–$44,765) per case, of which the total CDI-attributable cost was $21,448 (90 % CI: 21,152–21,744) per case. For the inpatient management, the attributable cost for those HO-CDI was $34,157 (90 % CI: $33,134–$35,180), which was 1.5 times as much as CO-CDI management $20,095 (90 % CI: $4991–$35,204).Table 5 Meta analysis results of cost and LOS of CDI management CDI category CDI-attributable cost per case (2015 US$) CDI-related cost per case (2015 US$) CDI-attributable LOS per case (Days) CDI-related LOS per case (Days) Weighted mean 90 % CI Weighted mean 90 %CI Weighted mean 90 % CI Weighted mean 90 % CI CO-CDI 20,095 4991 35,204 23,329 12,520 34,141 5.7 4.1 7.3 5.7 4.1 7.3 HO-CDI 34,157 33,134 35,180 53,487 42,054 66,326 9.7 9.7 9.7 14.1 13.0 15.4 Both CO-CDI and HO-CDI 17,650 17,292 18,009 46,000 42,502 49,533 10.4 9.7 11.0 11.8 7.1 17.6 Overall inpatient 21,448 21,152 21,744 42,316 39,886 44,765 9.7 9.6 9.8 11.1 8.7 13.6 Abbreviations: CO-CDI community-onset CDI, HO-CDI Hospital-onset CDI Similar patterns were observed in LOS data. The total CDI-related LOS was 11.1 days (90 % CI: 8.7–13.6) and CDI-attributable LOS was 9.7 (90 % CI: 9.6–9.8). The HO-CDI patients had longer CDI-attributable LOS 9.7 days (90 % CI: 9.7–9.7) than CO-CDI patients 5.7 days (90 % CI: 4.1–7.3). CDI annual national impact estimate The total burden of healthcare facility CDI in US was estimated 293,300 (Range: 264,200–453,000) cases per year [25]. The total financial burden of CDI inpatient management was estimated to be US$6.3 (Range: $1.9–$7.0) billion in 2015, which required 2.4 million days of hospital stay. The total CDI related disease management cost was nearly doubled at US$12.4 (Range: $3.7–$14.4) billion in 2015 (Table 6). A sensitivity analysis showed that the total CDI-attributable cost ranged from $1.31 to $13.61, which covers our estimates (Additional file 1).Table 6 Total cost of CDI management in US Total number of HCF CDI cases per year (2011) [25] Mean 95 % CI All population ≥2 years Median 293,300 264,200 322,500  Adults ≥18 Upper boundary 288,900 261,100 316,700  Adults ≥18 Lower boundary 133,887 91,780 195,402 Cost per CDI case management (2015 US$) Weighted Mean 90 % CI  Overall CDI-attributable cost 21,448 21,152 21,744  Overall CDI-related cost 42,316 39,886 44,765 Total cost per year (in Billions, 2015 US$) Weighted Mean Range Total CDI-attributable cost per year 6.29 1.94 7.01 Mean 6.29 5.59 7.01  Upper boundary 6.19 5.52 6.88  Lower boundary 2.87 1.94 4.25 Total CDI-related cost per year 12.41 3.66 14.44 Mean 12.41 5.59 14.44  Upper boundary 12.25 10.41 14.18  Lower boundary 5.67 3.66 8.75 Abbreviations: HCF healthcare facility, CDI clostridium difficile infection, CI confidence intervals Quality assessment A summary of the quality assessment for statistical methods in included studies is shown in Additional file 1. There were 13 studies of high quality, 21 studies with medium quality and 8 low quality studies. Discussion We systematically reviewed 42 published cost studies of CDI case management in the past 10 years (2005–2015) and found a significant financial burden associated with CDI in the US. The total CDI-attributable cost was US$6.3 billion, which is higher than previously reported (range US$1.1–4.8 billion) [14, 16, 17]. The mean cost for CDI-attributable hospitalized patients per case was US$21,448, nearly half of the mean CDI-related inpatient cost. This review facilitated a meta-analysis of a large number of cost studies for costs related to CDI management and provided an uncertainty range. Zimlichman et al [17] applied this method to calculate CDI cost based on cost data from two cost-of-illness studies (O’Brian 2007 [51] & Kyne 2002 [69]) and obtained a lower cost [2012US $11,285 ($9118–$13,574)] than ours. Our review combined 100-point estimates and ranges from 42 individual studies, which provided more accurate and comprehensive data of the cost result. Despite the methodological heterogeneity in perspectives, treatment procedure and statistical analysis, each included study met our inclusion criteria, which were defined to identify studies that provided real world estimates of costs, therefore the combination of these data with uncertainty range represented a valuable and reliable summary of CDI-related cost. Furthermore, we evaluated hospital onset CDI and community onset CDI separately. We found that CDI complicating hospitalization cost more than CDI requiring hospitalization and the former had longer attributable hospital stay. Therefore, other factors, such as comorbidity, may contribute to infections and increase the difficulty of CDI treatment. We estimated that the total cost attributable to CDI management in the US was nearly US$6.3 (Range: $1.9–$7.0) billion, which is similar to Dubberke and Olsen’s estimates at $4.8 billion [14], but significantly higher than other studies (US$ 1.5 billion in Zimlichman et al [17] and $1.1 billion in Ghantoji et al [16]). The later studies reported lower attributable cost per case based on a limited number of studies before 2005, which arguably is out-of-date. To compare with the latest review on global CDI cost (Nanwa et al [26]), this review identified 8 additional studies with recent data. Nanwa et al [26] found that the mean attributable CDI costs ranged from US$8911 to US$30,049, which is similar to our results. In this study, we only assessed the quality of study emphasizing statistical methods and did not use the modified economic evaluation guideline as other COI systematic reviews. Cost and LOS estimation of healthcare-associated infections has the potential to be misleading if the confounders such as patients’ comorbidities or daily severity of illness were not properly controlled for. Using either the matching design or multivariable regression analysis allows to control known confounders and may, in part, address selection bias [70]. We found that whether advanced statistical methods were used and described was crucial for the assessment of data quality, which has not be fully captured by the existing quality assessment tool. Therefore in this study we assessed quality of included studies using this new method. Moreover, Nanwa et al [26] has evaluated the methodological completeness of most included studies (34 out of 42); we agree with their recommendations regarding possible improvement of future cost-of-illness study. However, we need to bear in mind that cost effects or excess LOS are still likely to be overestimated if the interval to onset of HAI is not properly accounted for in the study design or analysis [70]. Our systematic review has some limitations. First, all included studies reported direct medical costs from hospital perspective, therefore indirect cost to patients and society and costs of additional care after hospital discharge, have not been captured. No studies reported indirect cost (productivity loss due to work day losses) of patients or care-givers, and we failed to identify studies assessing cost of CDI in long-term care facilities, where about 9 % of CDI patients were discharged to for an average of 24 days of after-care. This would result in an additional US$141 million burden on the healthcare system and society due to LTCF transfers [14]. Second, we did not separate primary CDI from recurrent CDI cost in our review because only two studies reported cost specifically to recurrent CDI $12,592 (Range: $9752, $15,919) [2]. Moreover, we found it difficult to exactly match the CDI case definition in cost study (e.g. ICD10 Code primary diagnosis and secondary diagnosis) with the case definition in epidemiology studies (e.g. community onset, hospital onset), therefore we did not estimate CDI patients managed at outpatient and community settings due to lack of both epidemiology and economic data. The total costs of CDI management may be higher than our current estimate. Fourth, unlike other published reviews, we did not include cost studies from countries other than the US nor facilitate any international comparison. This study initially aimed to identify cost-of-illness studies in North America, but we did not find any studies reporting cost data from Canada. This is likely because we restricted our search to English language databases. Therefore the cost of CDI management in Canada remains unknown. However, we did not apply any language restrictions to the current review. Effective prevention can reduce the burden of diseases. Strategies have been promoted such as appropriate use of antimicrobials, use of contact precautions and protective personal equipment to care for infected patients, effective cleaning and disinfection of equipment and the environment, and early recognition of disease as primary prophylaxis [71]. As CDI is an infectious disease, the population at risk would benefit from an effective vaccine, which is currently under development [72, 73]. More cost of illness studies for recurrent CDI, or in LTCF, and indirect cost from a societal perspective are needed in the future. We would also recommend that published studies report their methods and include point estimates with uncertainty range. Further economic studies for CDI preventive interventions are needed. Conclusion This review indicates that CDI places a significant financial burden on the US healthcare system. In addition, our findings suggest that the economic burden of CDI is greater than previously reported in the US. This review provides strong evidence to aid policy-making on adequate resource allocation to CDI prevention and treatment in US. Additional files Additional file 1: Appendices-cdiff cost review.docx; Addpendix 1–5; Appendix 1. Embase and Medline searches for each topic of interest (13th July 2015) , Appendix 2. Inclusion and exclusion criteria, Appendix 3. Statistical methods used in selected studies and quality assessment Appendix, 4. Total number of CDI cases in United States 2011, Appendix 5. Sensitivity analysis results (DOCX 101 kb) Additional file 2: CDI Cost Review.xlsx; CDI cost review; CDI cost review data extraction primary results (XLSX 529 kb) Abbreviations CDIclostridium difficile infection CIsconfidence intervals CO CDIcommunity-onset CDI HCFhealthcare facility HIVhuman immunodeficiency virus HO-CDIhospital-onset cdi ICD-9-CMthe international classification of diseases, ninth revision, clinical modification ICUsintensive care units IQRinterquantile range LTCFlong-term care facility NISnational independent sample SDstandard deviation USUnited States Acknowledgements We gratefully acknowledge the comments and suggestions from Guy De Bruyn, Clarisse Demont, Kinga Borsos (Sanofi Pasteur) during manuscript preparation. We thank Sanofi Pasteur for financial support for this work. The findings and conclusions in this report are those of the authors and do not necessarily represent the official views or policies of Sanofi Pasteur. Funding Sanofi Pasteur funded this study. Availability of data and materials The datasets supporting the conclusions of this article are included within the article and its Additional file 2. Authors’ contributions Study design (MK, HN, AC); data collection (SZ, SP, EB); data analysis (SZ, EB); data interpretation (SZ, EB, HN, AC, MK); development of initial draft manuscript (SZ, EB, HN), critical revisions for intellectual content of manuscript (SZ, SP, EB, HN, AC, MK); study supervision (HN, MK). All authors reviewed and approved the final draft of manuscript. Competing interests SP, AC, MK are employees of Sanofi Pasteur. Consent for publication Not applicable. Ethics approval and consent to participate Not applicable. ==== Refs References 1. Crobach M Dekkers O Wilcox M Kuijper E European Society of Clinical Microbiology and Infectious Diseases (ESCMID): data review and recommendations for diagnosing Clostridium difficile-infection (CDI) Clin Microbiol Infect 2009 15 12 1053 1066 10.1111/j.1469-0691.2009.03098.x 19929972 2. Dubberke ER Carling P Carrico R Strategies to prevent clostridium difficile infections in acute care hospitals: 2014 update Infect Control Hosp Epidemiol 2014 35 SUPPL2 628 645 10.1086/522262 24799639 3. Mylonakis E Ryan E Calderwood S Clostridium difficile—Associated diarrhea: A review Arch Intern Med 2001 161 4 525 533 10.1001/archinte.161.4.525 11252111 4. Rubin M Bodenstein L Kent K Severe Clostridium difficile colitis Dis Colon Rectum 1995 38 4 350 354 10.1007/BF02054220 7720439 5. Triadafilopoulos G Hallstone AE Acute abdomen as the first presentation of pseudomembranous colitis Gastroenterology 1991 101 3 685 691 10.1016/0016-5085(91)90526-Q 1860633 6. Sanchez T Brooks J Sullivan P Bacterial diarrhea in persons with HIV infection, United States, 1992–2002 Clin Infect Dis 2005 41 11 1621 1627 10.1086/498027 16267735 7. Bilgrami S Feingold J Dorsky D Incidence and outcome of Clostridium difficile infection following autologous peripheral blood stem cell transplantation Bone Marrow Transplant 1999 23 10 1039 1042 10.1038/sj.bmt.1701773 10373070 8. Barbut F Corthier G Charpak Y Prevalence and pathogenicity of Clostridium difficile in hospitalized patients. A French multicenter study Arch Intern Med 1996 156 13 1449 1454 10.1001/archinte.1996.00440120107012 8678714 9. Cohen S Gerding D Johnson S Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by the society for healthcare epidemiology of America (SHEA) and the infectious diseases society of America (IDSA) Infect Control Hosp Epidemiol 2010 31 5 431 455 10.1086/651706 20307191 10. Bignardi G Risk factors for Clostridium difficile infection J Hosp Infect 1998 40 1 1 15 10.1016/S0195-6701(98)90019-6 9777516 11. Aseeri M Schroeder T Kramer J Zackula R Gastric acid suppression by proton pump inhibitors as a risk factor for clostridium difficile-associated diarrhea in hospitalized patients Am J Gastroenterol 2008 103 9 2308 2313 10.1111/j.1572-0241.2008.01975.x 18702653 12. Bauer M Notermans D van Benthem B Clostridium difficile infection in Europe: a hospital-based survey Lancet 2011 377 9759 63 73 10.1016/S0140-6736(10)61266-4 21084111 13. Dubberke ER Wertheimer AI Review of current literature on the economic burden of Clostridium difficile infection Infect Control Hosp Epidemiol 2009 30 1 57 66 10.1086/592981 19049438 14. Dubberke ER Olsen MA Burden of Clostridium difficile on the healthcare system Clin Infect Dis 2012 55 Suppl 2 S88 S92 10.1093/cid/cis335 22752870 15. Gabriel L Beriot-Mathiot A Hospitalization stay and costs attributable to Clostridium difficile infection: a critical review J Hosp Infect 2014 88 1 12 21 10.1016/j.jhin.2014.04.011 24996516 16. Ghantoji SS Sail K Lairson DR Dupont HL Garey KW Economic healthcare costs of Clostridium difficile infection: a systematic review J Hosp Infect 2010 74 4 309 318 10.1016/j.jhin.2009.10.016 20153547 17. Zimlichman E Henderson D Tamir O Health care-associated infections: a meta-analysis of costs and financial impact on the US health care system JAMA Intern Med 2013 173 22 2039 2046 10.1001/jamainternmed.2013.9763 23999949 18. Johnson S Recurrent Clostridium difficile infection: A review of risk factors, treatments, and outcomes J Infect 2009 58 6 403 410 10.1016/j.jinf.2009.03.010 19394704 19. Mergenhagen KA Wojciechowski AL Paladino JA A review of the economics of treating Clostridium difficile infection Pharmacoeconomics 2014 32 7 639 650 10.1007/s40273-014-0161-y 24807468 20. Wiegand PN Nathwani D Wilcox MH Stephens J Shelbaya A Haider S Clinical and economic burden of Clostridium difficile infection in Europe: a systematic review of healthcare-facility-acquired infection J Hosp Infect 2012 81 1 1 14 10.1016/j.jhin.2012.02.004 22498638 21. Bouza E Consequences of Clostridium difficile infection: understanding the healthcare burden Clin Microbiol Infect 2012 18 Suppl 6 5 12 10.1111/1469-0691.12064 23121549 22. [Accessed November 9, 2015] Cost-to-charge ratio files. Healthcare Cost and Utilization Project Web site. http://www.hcup-us.ahrq.gov/db/state/costtocharge.jsp. 23. Jha A Chan D Ridgway A Franz C Bates DW Improving Safety And Eliminating Redundant Tests: Cutting Costs In U.S. Hospitals Health Aff 2009 28 5 1475 1484 10.1377/hlthaff.28.5.1475 24. Lessa FC Winston LG McDonald LC Emerging Infections Program C. difficile Surveillance Team Burden of Clostridium difficile infection in the United States N Engl J Med 2015 372 24 2369 2370 26061850 25. Hernández EB, Nair H, Campbell H, Kyaw M. Global burden of healthcare- and community- C. difficile-associated disease-systematic review and meta-analysis (unpublisehd report). University of Edinburgh; 2015. 26. Nanwa N Kendzerska T Krahn M The economic impact of Clostridium difficile infection: a systematic review Am J Gastroenterol 2015 110 4 511 519 10.1038/ajg.2015.48 25848925 27. Ali M Ananthakrishnan AN Ahmad S Kumar N Kumar G Saeian K Clostridium difficile infection in hospitalized liver transplant patients: a nationwide analysis Liver Transpl 2012 18 8 972 978 10.1002/lt.23449 22505356 28. Ananthakrishnan AN Mcginley EL Binion DG Excess hospitalisation burden associated with Clostridium difficile in patients with inflammatory bowel disease Gut 2008 57 2 205 210 10.1136/gut.2007.128231 17905821 29. Arora V Kachroo S Ghantoji SS Dupont HL Garey KW High Horn’s index score predicts poor outcomes in patients with Clostridium difficile infection J Hosp Infect 2011 79 1 23 26 10.1016/j.jhin.2011.04.027 21700363 30. Bajaj JS Ananthakrishnan AN Hafeezullah M Clostridium difficile is associated with poor outcomes in patients with cirrhosis: A national and tertiary center perspective Am J Gastroenterol 2010 105 1 106 113 10.1038/ajg.2009.615 19844204 31. Campbell R Dean B Nathanson B Haidar T Strauss M Thomas S Length of stay and hospital costs among high-risk patients with hospital-origin Clostridium difficile-associated diarrhea J Med Econ 2013 16 3 440 448 10.3111/13696998.2013.770749 23356421 32. Damle RN Cherng NB Flahive JM Clostridium difficile infection after colorectal surgery: a rare but costly complication J Gastrointest Surg 2014 18 10 1804 1811 10.1007/s11605-014-2600-7 25091840 33. Dubberke ER Reske KA Olsen MA McDonald LC Fraser VJ Short- and long-term attributable costs of Clostridium difficile-associated disease in nonsurgical inpatients Clin Infect Dis 2008 46 4 497 504 10.1086/526530 18197759 34. Dubberke ER Schaefer E Reske KA Zilberberg M Hollenbeak CS Olsen MA Attributable inpatient costs of recurrent Clostridium difficile infections Infect Control Hosp Epidemiol 2014 35 11 1400 1407 10.1086/678428 25333435 35. Egorova NN Siracuse JJ Mckinsey JF Nowygrod R Trend, risk factors, and costs of clostridium difficile infections in vascular surgery Ann Vasc Surg 2015 29 4 792 800 10.1016/j.avsg.2014.10.031 25595110 36. Flagg A Koch CG Schiltz N Analysis of Clostridium difficile infections after cardiac surgery: epidemiologic and economic implications from national data J Thorac Cardiovasc Surg 2014 148 5 2404 2409 10.1016/j.jtcvs.2014.04.017 24823282 37. Fuller RL McCullough EC Bao MZ Averill RF Estimating the Costs of Potentially Preventable Hospital Acquired Complications Health Care Financ Rev 2009 30 4 17 32 19719030 38. Glance LG Stone PW Mukamel DB Dick AW Increases in mortality, length of stay, and cost associated with hospital-acquired infections in trauma patients Arch Surg 2011 146 7 794 801 10.1001/archsurg.2011.41 21422331 39. Jiang Y Viner-Brown S Baier R Burden of hospital-onset Clostridium difficile infection in patients discharged from Rhode Island hospitals, 2010–2011: application of present on admission indicators Infect Control Hosp Epidemiol 2013 34 7 700 708 10.1086/670993 23739074 40. Kim SP Shah ND Karnes RJ The implications of hospital acquired adverse events on mortality, length of stay and costs for patients undergoing radical cystectomy for bladder cancer J Urol 2012 187 6 2011 2017 10.1016/j.juro.2012.01.077 22498229 41. Kuntz JL Johnson ES Raebel MA Epidemiology and healthcare costs of incident Clostridium difficile infections identified in the outpatient healthcare setting Infect Control Hosp Epidemiol 2012 33 10 1031 1038 10.1086/667733 22961023 42. Lagu T Stefan MS Haessler S The impact of hospital-onset Clostridium difficile infection on outcomes of hospitalized patients with sepsis J Hosp Med (Online) 2014 9 7 411 417 10.1002/jhm.2199 43. Lemaire A Dombrovskiy V Batsides G The Effect of Clostridium difficile Infection on Cardiac Surgery Outcomes Surg Infect (Larchmt) 2015 16 1 24 28 10.1089/sur.2013.097 25402213 44. Lawrence SJ Puzniak LA Shadel BN Gillespie KN Kollef MH Mundy LM Clostridium difficile in the intensive care unit: epidemiology, costs, and colonization pressure Infect Control Hosp Epidemiol 2007 28 2 123 130 10.1086/511793 17265392 45. Lesperance K Causey MW Spencer M Steele SR The morbidity of Clostridium difficile infection after elective colonic resection-results from a national population database Am J Surg 2011 201 2 141 148 10.1016/j.amjsurg.2010.09.017 21266214 46. Lipp MJ Nero DC Callahan MA Impact of hospital-acquired Clostridium difficile J Gastroenterol Hepatol 2012 27 11 1733 1737 10.1111/j.1440-1746.2012.07242.x 22849881 47. Maltenfort MG Rasouli MR Morrison TA Parvizi J Clostridium difficile colitis in patients undergoing lower-extremity arthroplasty: rare infection with major impact Clin Orthop Relat Res 2013 471 10 3178 3185 10.1007/s11999-013-2906-x 23479237 48. Mcglone SM Bailey RR Zimmer SM The economic burden of Clostridium difficile Clin Microbiol Infect 2012 18 3 282 289 10.1111/j.1469-0691.2011.03571.x 21668576 49. Nguyen GC Kaplan GG Harris ML Brant SR A national survey of the prevalence and impact of Clostridium difficile infection among hospitalized inflammatory bowel disease patients Am J Gastroenterol 2008 103 6 1443 1450 10.1111/j.1572-0241.2007.01780.x 18513271 50. Nylund CM Goudie A Garza JM Fairbrother G Cohen MB Clostridium difficile infection in hospitalized children in the United States Arch Pediatr Adolesc Med 2011 165 5 451 457 10.1001/archpediatrics.2010.282 21199971 51. O’Brien JA Lahue BJ Caro JJ Davidson DM The emerging infectious challenge of clostridium difficile-associated disease in Massachusetts hospitals: clinical and economic consequences Infect Control Hosp Epidemiol 2007 28 11 1219 1227 10.1086/522676 17926270 52. Pakyz A Carroll NV Harpe SE Oinonen M Polk RE Economic impact of Clostridium difficile infection in a multihospital cohort of academic health centers Pharmacotherapy: J Hum Pharmacol Drug Ther 2011 31 6 546 551 10.1592/phco.31.6.546 53. Pant C Anderson MP O’Connor JA Marshall CM Deshpande A Sferra TJ Association of Clostridium difficile infection with outcomes of hospitalized solid organ transplant recipients: results from the 2009 Nationwide Inpatient Sample database Transpl Infect Dis 2012 14 5 540 547 10.1111/j.1399-3062.2012.00761.x 22726461 54. Pant C Deshpande A Anderson MP Sferra TJ Clostridium difficile infection is associated with poor outcomes in end-stage renal disease J Investig Med 2012 60 2 529 532 10.2310/JIM.0b013e318242b313 22222233 55. Pant C Anderson MP Deshpande A Health care burden of Clostridium difficile infection in hospitalized children with inflammatory bowel disease Inflamm Bowel Dis 2013 19 5 1080 1085 10.1097/MIB.0b013e3182807563 23478808 56. Peery AF Dellon ES Lund J Burden of gastrointestinal disease in the United States: 2012 update Gastroenterol 2012 143 5 1179 1187 10.1053/j.gastro.2012.08.002 57. Quimbo RA Palli SR Singer J Strauss ME Thomas SM Burden of Clostridium difficile-associated diarrhea among hospitalized patients at high risk of recurrent infection J Clin Outcomes Manag 2013 20 12 544 554 58. Reed IJF Edris BA Eid S Molitoris A Clostridium difficile: the new epidemic Int J Infect Dis 2009 7 1 1 5 59. Sammons JS Localio R Xiao R Coffin SE Zaoutis T Clostridium difficile infection is associated with increased risk of death and prolonged hospitalization in children Clin Infect Dis 2013 57 1 1 8 10.1093/cid/cit155 23532470 60. Singal AK Salameh H Kamath PS Prevalence and in-hospital mortality trends of infections among patients with cirrhosis: a nationwide study of hospitalised patients in the United States Aliment Pharmacol Ther 2014 40 1 105 112 10.1111/apt.12797 24832591 61. Song X Bartlett JG Speck K Naegeli A Carroll K Perl TM Rising economic impact of clostridium difficile-associated disease in adult hospitalized patient population Infect Control Hosp Epidemiol 2008 29 9 823 828 10.1086/588756 18643746 62. Stewart DB Hollenbeak CS Clostridium difficile colitis: factors associated with outcome and assessment of mortality at a national level J Gastrointest Surg 2011 15 9 1548 1555 10.1007/s11605-011-1615-6 21720924 63. Tabak YP Zilberberg MD Johannes RS Sun X McDonald LC Attributable burden of hospital-onset Clostridium difficile infection: a propensity score matching study Infect Control Hosp Epidemiol 2013 34 6 588 596 10.1086/670621 23651889 64. Verlee KE Finks JL Wilkins MJ Wells EV Michigan Clostridium difficile hospital discharges: frequency, mortality, and charges, 2002–2008 Public Health Rep 2012 127 1 62 71 22298923 65. Wang L Stewart DB Increasing hospital costs for Clostridium difficile colitis: type of hospital matters Surgery 2011 150 4 727 735 10.1016/j.surg.2011.08.019 22000185 66. Wilson MZ Hollenbeak CS Stewart DB Impact of Clostridium difficile colitis following closure of a diverting loop ileostomy: results of a matched cohort study Colorectal Dis 2013 15 8 974 981 10.1111/codi.12128 23336347 67. Zerey M Paton BL Lincourt AE Gersin KS Kercher KW Heniford BT The burden of Clostridium difficile in surgical patients in the United States Surg Infect (Larchmt) 2007 8 6 557 566 10.1089/sur.2006.062 18171114 68. Zilberberg MD Nathanson BH Sadigov S Higgins TL Kollef MH Shorr AF Epidemiology and outcomes of clostridium difficile-associated disease among patients on prolonged acute mechanical ventilation Chest 2009 136 3 752 758 10.1378/chest.09-0596 19465510 69. Kyne L Hamel M Polavaram R Kelly C Health care costs and mortality associated with nosocomial diarrhea due to Clostridium difficile Clin Infect Dis 2002 34 3 346 353 10.1086/338260 11774082 70. de Angelis G Murthy AR Beyersmann J Harbarth S Estimating the impact of healthcare-associated infections on length of stay and costs Clin Microbiol Infect 2010 16 12 1729 1735 10.1111/j.1469-0691.2010.03332.x 20673257 71. Dubberke E Carling P Carrico R Strategies to Prevent Clostridium difficile Infections in Acute Care Hospitals: 2014 Update Infect Control Hosp Epidemiol 2014 35 6 628 645 10.1086/522262 24799639 72. Bruyn Gd, Foglia G, Saleh J, Workman D, Pollak R, Gesser R. A phase II study of the safety and immunogenicity of different vaccination schedules of a candidate clostridium difficile toxoid vaccine: vaccination schedule selection for phase III 24th Annual Meeting of the European Congress of Clinical Microbiology and Infectious Diseases (ECCMID); 2014; Barcelona, Spain; 2014. 73. Foglia G Shah S Luxemburger C Pietrobon PJF Clostridium difficile: Development of a novel candidate vaccine Vaccine 2012 30 29 4307 4309 10.1016/j.vaccine.2012.01.056 22682287

PMC005xxxxxx/PMC5000554.txt

==== Front Front PsycholFront PsycholFront. Psychol.Frontiers in Psychology1664-1078Frontiers Media S.A. 10.3389/fpsyg.2016.01279PsychologyOriginal ResearchHow Online Basic Psychological Need Satisfaction Influences Self-Disclosure Online among Chinese Adolescents: Moderated Mediation Effect of Exhibitionism and Narcissism Liu Ying 1Liu Ru-De 1*Ding Yi 2Wang Jia 1Zhen Rui 1Xu Le 11Beijing Key Laboratory of Applied Experimental Psychology, School of Psychology, Beijing Normal University, BeijingChina2Graduate School of Education, Fordham University, New York, NYUSAEdited by: Andrej Košir, University of Ljubljana, Slovenia Reviewed by: Marco Fyfe Pietro Gillies, Goldsmiths, University of London, UK; Theodoros Kostoulas, University of Geneva, Switzerland *Correspondence: Ru-De Liu, rdliu@bnu.edu.cnThis article was submitted to Human-Media Interaction, a section of the journal Frontiers in Psychology 26 8 2016 2016 7 127927 1 2016 11 8 2016 Copyright © 2016 Liu, Liu, Ding, Wang, Zhen and Xu.2016Liu, Liu, Ding, Wang, Zhen and XuThis is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Under the basic framework of self-determination theory, the present study examined a moderated mediation model in which exhibitionism mediated the relationship between online basic psychological need satisfaction and self-disclosure on the mobile Internet, and this mediation effect was moderated by narcissism. A total of 296 Chinese middle school students participated in this research. The results revealed that exhibitionism fully mediated the association between online competence need satisfaction and self-disclosure on the mobile net, and partly mediated the association between online relatedness need satisfaction and self-disclosure on the mobile net. The mediating path from online basic psychological need satisfaction (competence and relatedness) to exhibitionism was moderated by narcissism. Compared to the low level of narcissism, online competence need satisfaction had a stronger predictive power on exhibitionism under the high level of narcissism condition. In contrast, online relatedness need satisfaction had a weaker predictive power on exhibitionism. online basic psychological need satisfactionexhibitionismnarcissismself-disclosureChinese adolescents ==== Body Introduction With the rapid development and popularity of smart phone technology, people increasingly enjoy accessing to the Internet through mobile phones (Ishii, 2004; Wu et al., 2013; Wells et al., 2014), especially for adolescents (Hollenbaugh, 2011; Wang J.L. et al., 2011). The smart phone provides optimal conditions for people to access social networking sites (SNS) anytime and anywhere with its characteristics of portability and convenience. The existing research has indicated that using SNS through mobile device can increase self-disclosure behavior (Kwak et al., 2014). Online self-disclosure represents the amount of information that an Internet user intends to reveal to others (Joinson and Paine, 2007). It includes two dimensions, namely, breadth and depth (Levinger and Snoek, 1972; Wheeless, 1978; Hollenbaugh and Ferris, 2014). Breadth refers to the diversity of topics involved in the process of disclosing online. Depth is characterized by more personal or intimate disclosures. Through SNS such as Facebook (Kisekka et al., 2013; Kim, 2016), blogs (Hollenbaugh, 2010; Chen, 2012), WeChat (Wen, 2014), and Twitter (Choi and Toma, 2014; Klausen, 2015) on the mobile net, users can disclose particular information as they talk about various topics, communicate deeply, post photos or videos, and update their status. The previous research on online self-disclosure can be divided into three categories: comparison between online self-disclosure and offline self-disclosure (Nguyen et al., 2012; Emanuel et al., 2014); the influence factors of online self-disclosure (Valkenburg and Peter, 2007; Rosen et al., 2010; Kisilevich and Last, 2011; Forest and Wood, 2012; Hollenbaugh and Ferris, 2014); and the effect of online self-disclosure (Joinson et al., 2007; Bryce and Klang, 2009; Ko and Kuo, 2009; Zimmer et al., 2010; Kisilevich and Last, 2011; Park et al., 2011). Self-disclosure online has both positive and negative consequences. Basic psychological need satisfaction is one of the important positive effects of self-disclosure online (Smock et al., 2011; Ang et al., 2015). In specific, self-disclosure online can produce psychological benefits such as a sense of autonomy, recognition, and belongingness. Previous studies have concentrated on the gratifications of various Internet usages, but few studies focused on the impact of gratifications from Internet usage on human network behavior. In particularly, compared to adults, teenagers prefer to disclose more private information through the Internet (McKenna et al., 2002; Gibbs et al., 2006; Joinson and Paine, 2007; Mazer et al., 2007; Walther, 2011), especially at the age of 15 years (Ma and Leung, 2006; Valkenburg and Peter, 2007). Thus, the assumption comes, is the satisfied psychological need in the network the reason why teenagers are more likely to disclose on the Internet? Therefore, the present study intended to investigate the effect of online basic psychological need satisfaction on self-disclosure on the mobile net among adolescents. Furthermore, it is of great value to futher explore the underlying mechanism such as the mediator or moderator of the association between online basic psychological need satisfaction and self-disclosure to reveal valuable information about the underlying processes through which this relationship occurs. Psychological needs are the fundamental driving force of an individual’s behavior. Self-determination theory (SDT) provides a unique perspective to understand the relationship between psychological needs and network behavior (Zhu et al., 2011; Shen et al., 2013). According to SDT, there are three basic psychological needs: competence refers to the need to perform successful social interactions with skills and ability; relatedness considers one’s need to feel connected with others; and autonomy refers to the need to decide one’s own behavior and act freely (Deci and Ryan, 1985). The purpose of various human behaviors is to satisfy the basic psychological needs throughout the lifetime (Deci and Ryan, 2000). Self-disclosure online such as publishing opinions, posting photos or videos, and communicating with other users through social media affords disclosers the opportunities to satisfy basic psychological needs (Ang et al., 2015). Besides, people become more or less interested in those activities as a function of the degree to which they experience satisfaction of competence, relatedness, and autonomy while engaging in the activities (Deci and Ryan, 2000). That is, the fulfilled basic psychological needs provide positive feedback on network behavior. The higher the need being satisfied in the activity, the stronger the internal motivation of the activity and the more behavior involved (Moller et al., 2010). Based on the above theories, the current study concluded that the more satisfaction experienced online, the more engagement in online disclosure behavior. A series of empirical research studies on network activities, such as behavior in the network learning environment (Chen and Jang, 2010), Internet usage (Zhao et al., 2011), network games (Ryan et al., 2006; Przybylski et al., 2009; Wang C.K.J. et al., 2011), and Facebook usage (Sheldon and Gunz, 2009; Sheldon et al., 2011) showed that the higher the degree of satisfaction of psychological needs, the more the online behavioral involvement. For example, a research on online games indicated that children who perceived higher level of satisfaction of competence, relatedness and autonomy need online tended to use the Internet more often (Shen et al., 2013). Thereby, the existing studies indirectly demonstrated that the inherent properties of the experiences provided by the Internet motivated children’s sustained Internet engagement. It was inferred that the rewarding experience of obtaining these gratifications online, in turn, might become compulsive and cause increasingly more Internet usages to satisfy the same needs repeatedly. However, the previous studies mainly focused on children or other network behaviors, few empirical studies have directly investigated the relationship between online basic psychological need satisfaction and self-disclosure on the mobile net among adolescents. Adolescence is a critical period of rapid physical and mental growth and development, during which adolescents are not only eager to be free from parents and teachers’ control, but are also eager to obtain understanding and admiration from others (Fuligni, 1998). To extend the literature, this research aimed to examine the influence of online basic psychological need satisfaction on self-disclosure on the mobile net among adolescents. Moreover, motivation is derived from the need to act directly on the behavior. Accordingly, motivation acts as a mediator between need and behavior. In the virtual context, psychological and social variables affect motives for media use, which in turn predict the frequency and type of media use (Katz et al., 1974; Rubin, 2002). Exhibitionism is a critical motivation for users to create content online (Koskela, 2004; Hollenbaugh, 2011; Hollenbaugh and Ferris, 2014), which deserves further explanation (Hollenbaugh and Ferris, 2015). Exhibitionism is considered as the desire of individuals to frequently present their private lives in public to attract other’s attention (Koskela, 2004). It includes a combination of self-display, vanity, and superiority. People who score higher in exhibitionism tend to demand more social attention and reveal self-promoting information online to attract attention and appreciation from others. The prevalence of mobile phones and social media like Facebook and blogs has further promoted exhibitionism (Koskela, 2004; Qian and Scott, 2007; Schmidt, 2007). It has been demonstrated that exhibitionism positively predicted self-disclosure (Hollenbaugh, 2011; Ryan and Xenos, 2011; Hollenbaugh and Ferris, 2014, 2015). Theoretical and empirical studies indicated that adolescents’ online basic psychological need satisfaction can promote exhibitionism, which in turn predicts self-disclosure online. According to SDT, basic psychological need satisfaction is the internal dynamics of behavior, which enhances internal motivation and facilitates the internalization of external motivation (Deci and Ryan, 2000). With the development of independent consciousness and self-consciousness, adolescents increasingly show a strong desire for self-presentation in adolescence (Mazur, 2010). They are eager to exhibit their abilities and skills to maintain their self-image and obtain the recognition and appreciation from others. According to Bandura, feelings of personal competence are related to self-perceptions of efficacy regarding one’s ability in dealing with distinct social domains, and are seen as the proximal and direct predictors of psychological motivation (Bandura et al., 1999). Internet provides an excellent opportunity for adolescents to experience the feeling to be unique and good at certain skills. In the virtual context, individuals are more willing to engage in exhibition when obtaining higher satisfied competence need. Similarly, exhibitionism motivation usually exists in interpersonal interaction. To satisfy relatedness need, people always spend a lot of efforts to get the appreciation and affection from others. In order to obtain close relationships, people are concerned more about their performance and self-image (McClelland, 1976). The background behind exhibiting is to leave a good impression on others. The mobile phone network plays an active role in social development, such as its role in promoting the exchange of information and expanding the scope of students’ interpersonal communication. In the virtual context, relatedness need motivates people to maintain positive self-image through self-expression and online display (Gibbs et al., 2006). When individuals experience the caring, understanding and support from the surrounding environment or other people online, people usually tend to have more positive self-expression. In addition, when individuals feel they can decide their own behavior online, they experience a kind of internal attribution, then the internal motivation of participating in the activities is high. In short, satisfied psychological needs can facilitate the internalization of external motivation and promote the individual to insist on a certain activity over a period of time. The relation between basic psychological need satisfaction and exhibitionism is also supported by some empirical research. Hollenbaugh (2011) posited that recognition (competence) and social (relatedness) needs underlie the motivations for producers of Internet content. Relatedness and competence needs can be satisfied by being overly exhibitionistic (Lee and Robbins, 1995). Strong feelings of satisfaction should be positively reinforced and act as a motivational force for more behavioral involvement (Moller et al., 2010). In conclusion, this study proposed a mediation model, demonstrating that exhibitionism mediated the relationship between online basic psychological need satisfaction and self-disclosure on the mobile net. Notably, much empirical work posited that competence, relatedness, and autonomy need satisfaction each made unique predictive contributions to human behavior (Sheldon and Gunz, 2009). Therefor, we formulated the following hypotheses to, respectively, investigate the impact of three kinds of basic psychological need satisfaction on self-disclosure on the mobile net (H1–H3) and the mediating role of exhibitionism among the associations (H4): (i) H1 Competence need satisfaction positively predicts self-disclosure on the mobile net. (ii) H2 Relatedness need satisfaction positively predicts self-disclosure on the mobile net. (iii) H3 Autonomy need satisfaction positively predicts self-disclosure on the mobile net. (iv) H4 Exhibitionism mediates the associations between online psychological need satisfaction (competence, relatedness, autonomy) and self-disclosure on the mobile net. The mediation effect model focuses on the influence mechanism of the independent variable on the dependent variable. Nevertheless, this approach cannot answer the question of when the influence power will be more effective. In fact, the degree of basic psychological need satisfaction varies with each individual, and this difference would be reflected in the motivation of online behavior. Research has showed that personality was an important internal cause of the individual differences for need satisfaction and motivation (Caspi et al., 2005). Personality moderated the impact of individuals’ need on motivation, which would lead to the individual differences in motivation (Leary, 1999). Therefore, this study proposed that exhibitionism was not only influenced by online basic psychological need satisfaction, but was also influenced by individuals’ personality traits. Narcissism is one of the personality factors that influences the exhibitionism (Wang and Stefanone, 2013). The social-personality perspective conceptualizes narcissism as a long-term, diversified, and comprehensive personality trait that is not necessarily pathological (Morf and Rhodewalt, 2001; Campbell et al., 2006). It is commonly found in individuals (Miller and Campbell, 2010). Indeed, narcissism may be adaptive in some ways (Sedikides et al., 2004). Narcissists usually have positive self-concept, and they will view themselves in a positive way. The main characteristics of narcissism include grandiosity, positive self-evaluation, self-importance, lack of empathy, and a need for admiration (Wink, 1991; Campbell, 1999; Morf and Rhodewalt, 2001; Campbell and Foster, 2002; Ames et al., 2006). Stemming from the underlying need to exhibit superiority, narcissism positively predicts exhibitionism (Wink, 1991; Morf and Rhodewalt, 2001). A narcissist who has a strong desire to be admired by others is associated with higher exhibitionism motivation to disclose private information that emphasizes attractiveness. Actually, it is even claimed that social media such as Facebook, blogs, and Twitter specifically provides a platform for narcissistic individual to fulfill the basic psychological need by exhibiting superiority. Previous studies have indicated that the degree of need satisfaction from using Facebook differs as a function of personality (Park et al., 2009; Ross et al., 2009; Urista et al., 2009). Narcissistic individuals themselves have a very strong exhibitionism motivation, which drives them to exhibit their talents to others to get attention and admiration. Thus, the easy accessibility of the smart phone gratifies the narcissistic individuals’ need to engage in self-promotion that ultimately reveals his or her exhibitionist tendencies. Narcissists are gratified largely by the exhibitionistic nature of SNS (Bibby, 2008; Wang and Stefanone, 2013). This implies that people with high level of narcissism have a stronger exhibitionism motivation when their psychological needs are gratified online. In addition, narcissism increases significantly between the ages of 14 and 18 years (Carlson and Gjerde, 2009). Teenagers of about 15 years old are in the center stage of puberty, and they particularly desire capability, support and autonomy. Therefore, considering personality characteristics is helpful to understand the effect of basic psychological need satisfaction of Internet users with different personality types on self-disclosure on the mobile net. In summary, we proposed the following hypothesis: (i) H5 Narcissism moderates the relationship between online basic psychological need satisfaction (competence, relatedness, autonomy) and exhibitionism. Materials and Methods Participants The random sampling method was used to select 296 middle school students (females: 175, males: 121; average age = 16.90 years, standard deviation = 1.36) from an ordinary middle school in Beijing city to participate in the survey. All participants were assured that their responses would be kept confidential and irrelevant to their course grade. After completing the questionnaires, participants received course credit. All the participants in the survey were smart phone users, and all had experience with accessing to the Internet through smart phones. Ethical Statement The local ethical committee of Beijing Normal University approved this study. Written informed consent was obtained from school principal, teachers and parents of all of these students. All participants were informed of their right to withdraw from the survey at any time. Measures Online Basic Psychological Need Satisfaction Participants’ online basic psychological need satisfaction was measured by an online need satisfaction questionnaire (Shen et al., 2013). In order to ensure the domain specific measure, each item was associated with a mobile Internet situation. The scale included three subscales: autonomy (four items, e.g., I felt a certain freedom of action when I used the Internet by mobile phone), competence (four items, e.g., I am satisfied with my performance on mobile Internet) and relatedness (four items, e.g., When I was on mobile Internet, I feel I was supported by others online). A 7-point scale was provided, ranging from 1 (strongly disagree) to 7 (strongly agree). Higher scores indicated higher basic psychological need satisfaction perceived online. A reliability test based on the data of this study revealed a satisfactory internal consistency (α = 0.824, 0.798, 0.888 for autonomy, competence, and relatedness, respectively). Exhibitionism For assessing participants’ tendency toward exhibitionism when using the mobile Internet, five items from the subscale of a Facebook motives questionnaire were chosen for this study (Hollenbaugh and Ferris, 2014). In order to ensure the domain specific measure, each item was associated with a mobile net situation. An additional item was created to measure participants’ desire to use the mobile Internet to get somebody’s attention. The final measure consisted of six items (The new item: If no one can see, I’m not going to publish content on the mobile net). Each item was answered using a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). The confirmatory factor analysis was carried out, and the overall fitting index of the scale was as follows: χ2/df = 2.325, CFI = 0.988, TLI = 0.973, RMSEA = 0.067. A reliability test based on the data of this study revealed a satisfactory internal consistency (α = 0.838). The analysis results showed that the exhibitionism scale had good reliability and construct validity. Narcissism Narcissism was assessed using the revised 16-item Narcissism Personality Inventory (NPI-16; Ames et al., 2006; Jones and Paulhus, 2014). According to previous studies (Penney and Spector, 2002; Aviram and Amichai-Hamburger, 2005; Leung, 2013), participants responded on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree) in the current study. The internal reliability coefficient for narcissism was 0.70. Self-Disclosure on the Mobile Net For assessing self-disclosure on the mobile net, a slightly revised version of the self-disclosure online scale was adapted from previous studies (Valkenburg and Peter, 2007; Wang J.L. et al., 2011). These scales consisted of two dimensions. Each dimension contained four items to assess both breadth and depth of self-disclosure on the mobile net (We deleted an item from the depth dimension that was related to sex and was not suitable for young people.). In order to ensure the domain specific measure, each item was associated with a mobile net situation. Participants responded on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). In this study, the internal reliability coefficients for breadth and depth were 0.851 and 0.852. Finally, basic demographic information was requested, including gender and age. Procedure and Data Analysis The investigation was conducted in the students’ classroom. Trained research assistants were present during the entire process. Research assistants instructed the participants to express their personal opinions and judgments before answering the questionnaires. The participants did not need to write their names on the questionnaires, and the confidentiality of their responses was assured. The basic psychological need satisfaction online questionnaire was administered first, followed by the exhibitionism scale, the narcissism scale and the self-disclosure on the mobile net scale. All the questionnaires administrated in this study were in the Chinese language. It took approximately 40 min for the students to complete all the instruments. Data were collected through a series of questionnaires. First, descriptive statistics were calculated to characterize the sample, including information about students’ gender and age. Second, correlations among the seven main variables (independent variables: competence, relatedness, autonomy; mediator variable: exhibitionism; moderator variable: narcissism; dependent variables: breadth, depth) were also analyzed. Furthermore, a structural equation modeling (SEM; Joreskog and Sorbom, 1979) analysis was conducted in order to explore the hypothesized model by AMOS 17.0 in two interlinked steps. In the first step, we tested the mediation models (Hypotheses 1–4). A bootstrap estimation procedure with 1000 bootstrap samples was used to test the significance of mediation effects. In the second step, we integrated the proposed moderator variable into the model and empirically examined the overall moderated mediation (Hypothesis 5). Results Preliminary Analyses In this study, data were collected by means of self-report questionnaires (Supplementary Data Sheets 1 and 2). Harman’s single factor test method was adopted to examine the common method bias (Podsakoff et al., 2003). Results showed that the first un-rotated factor explained the variance of 27.739%, far less than the critical value. Therefore, the influence of common method bias in this study was not serious. Descriptive statistics for all variables are showed in Table 1. In addition, difference in disclosure online by gender was analyzed. Independent-samples t-test demonstrated that there was no significant difference between girls and boys in breadth and depth of self-disclosure on the mobile net (t = 0.042, p > 0.05; t = 0.041, p > 0.05). Results of correlations analysis indicated that self-disclosure on the mobile net was in various degrees significantly associated with all six variables. Satisfaction of all three online needs satisfaction was significantly correlated with breadth (r ranged from 0.37 to 0.45; p < 0.01) and depth of self-disclosure on the mobile net (r ranged from 0.38 to 0.55; p < 0.01). Exhibitionism was significantly positively correlated with satisfaction of three needs (r = 0.27, 0.43, 0.46, p < 0.01) and self-disclosure (r = 0.31, 0.41, p < 0.01). Autonomy, competence, and relatedness needs satisfaction and narcissism had significant but weak positive correlation (r = 0.19, 0.27, 0.27, p < 0.01), indicating that the independent variable and moderate variable had relative independence with each other, suitable for a subsequent moderating effect analysis. The hypothesis model of this research can be further analyzed. Table 1 Descriptive statistics and correlations among the variables. (N = 296). Variables M SD 1 2 3 4 5 6 1. Autonomy 4.73 1.26 – 2. Competence 3.90 1.27 0.64** – 3. Relatedness 3.75 1.36 0.56** 0.79** – 4. Narcissism 3.00 0.45 0.19** 0.27** 0.27** – 5. Exhibitionism 2.97 0.85 0.27** 0.43** 0.46** 0.20** – 6. Breadth 3.15 0.92 0.39** 0.37** 0.45** 0.26** 0.31** – 7. Depth 2.89 1.02 0.38** 0.43** 0.55** 0.23** 0.41** 0.70** *p < 0.05; **p < 0.01.The Effect of Online Basic Psychological Need Satisfaction on Self-Disclosure on the Mobile Net: The Mediating Effect of Exhibitionism According to the process of the moderated mediation model test procedure, this study first examined the mediating effect of exhibitionism, and then examined the moderating effect of narcissism. Structural equation modeling (Joreskog and Sorbom, 1979) by AMOS 17.0 was performed to test our hypothesized mediation model. The results of the final model (Figure 1) indicated a good fit with the data: χ2/df = 2.605, p < 0.001; IFI = 0.964; TLI = 0.945; CFI = 0.964; and RMSEA = 0.074. As we hypothesized, online autonomy and relatedness needs satisfaction positively predicted self-disclosure on the mobile net (β = 0.18, p < 0.01, β = 0.47, p < 0.01), partially providing support for H1–H3. Specifically, online competence and relatedness needs satisfaction positively predicted exhibitionism (β = 0.18, p = 0.07, β = 0.39, p < 0.05). In turn, exhibitionism positively predicted self-disclosure on the mobile net (β = 0.21, p < 0.01). Further analysis found that exhibitionism showed a full mediation effect on the path from online competence need satisfaction to self-disclosure on the mobile net, and a partial mediation effect on the path from online relatedness need satisfaction to self-disclosure on the mobile net. There was no mediating effect of exhibitionism between online autonomy satisfaction and self-disclosure on the mobile net. In the present study, a bootstrapping method with 1000 bootstrap samples was used to test the significance of mediation effects. If the CIs did not include zero (p < 0.05), we concluded that the mediated effects were statistically significant (Preacher and Hayes, 2008). Bootstrap analysis testified that the indirect effect of online competence need satisfaction on self-disclosure on the mobile net via exhibitionism was significantly different from zero (90% CI = 0.002–0.056). The indirect effect of online relatedness need satisfaction on self-disclosure on the mobile net via exhibitionism was significantly different from zero (90% CI = 0.015–0.098). Therefore, H4 was partially supported. FIGURE 1 Finalized structural model. aRepresents: marginally significant. *p < 0.05, **p < 0.01. The Moderate Effect of Narcissism In this part of the present study, the independent variables were online competence and relatedness needs satisfaction, the moderator variable was narcissism, and the dependent variable was exhibitionism. Because there was no mediating effect of exhibitionism between online autonomy satisfaction and self-disclosure on the mobile net, the independent variable did not include online autonomy satisfaction in this part of the analysis. Centralizing the independent variables and moderator variable, we investigated the interaction effect of both online competence and relatedness needs satisfaction and narcissism on exhibitionism using structural equation model. The results of the final model (Figure 2) indicated a good fit with the data: χ2/df = 3.307, p < 0.001; IFI = 0.938; TLI = 0.918; CFI = 0.938; and RMSEA = 0.088. As we hypothesized, online competence and relatedness needs satisfaction significantly positive predicted exhibitionism (β = 0.17, p = 0.06; β = 0.38 p < 0.001), the predictive effect of narcissism was not significant. The interaction effect of online competence need satisfaction and narcissism significantly and positively predicted exhibitionism (β = 0.24, p < 0.05), while the interaction effect of relatedness need satisfaction and narcissism significantly and negatively predicted exhibitionism (β =–0.23, p < 0.05). Research results showed that narcissism played a significant positive moderating role in the influence of competence need satisfaction on exhibitionism. On the contrary, narcissism played a significant negative moderating role in the influence of relatedness need satisfaction on exhibitionism. FIGURE 2 Finalized structural model. aRepresents: marginally significant. *p < 0.05, ***p < 0.001. Based on the above considerations, this study validated the integration model. The result of the final model (Figure 3) indicated a good fit with the data: χ2/df = 2.810, p < 0.001; IFI = 0.943; TLI = 0.925; CFI = 0.942; and RMSEA = 0.078. FIGURE 3 Finalized structural model. aRepresents: marginally significant. *p < 0.05, ***p < 0.001. In order to reveal the essence of the interaction effect, this study used a simple slope analysis to analyze the specific moderating effect of narcissism. First, subjects were divided into two groups according their narcissism scores. One group represented high level of narcissism with scores that were higher than one standard deviation; the other group represented the low level of narcissism with scores that were lower than one standard deviation. Second, the linear regression was used, the independent variables were online competence or relatedness needs satisfaction, and the dependent variable was exhibitionism. Regression coefficients of the predictive effect of online competence need satisfaction on exhibitionism in the high level of narcissism group and in the low level of narcissism group were 0.47 (t = 6.73, p < 0.01) and 0.31 (t = 3.84, p < 0.01), respectively. Third, the same method was used to divide the participants into two groups, with one group scored higher than one standard deviation and the other group scored lower than one standard deviation on online competence need satisfaction. We calculated the average scores of the two groups on online competence need satisfaction and entered them into the two regression equations mentioned above. Then the exhibitionism scores under different conditions of narcissism and online competence need satisfaction were calculated, as shown in Figure 4. Under the higher level of narcissism condition, the promoting effect of online competence need satisfaction on exhibitionism was stronger than under the lower level of narcissism condition. In addition, regression coefficients of the predictive effect of relatedness need satisfaction on exhibitionism in the high level of narcissism and in the low level of narcissism group were 0.47 (t = 6.69, p < 0.01) and 0.39 (t = 4.84, p < 0.01). Next, participants were divided into two groups, with one group scored higher than one standard deviation and the other group scored lower than one standard deviation on online relatedness need satisfaction. We calculated the average scores of the two groups on online competence need satisfaction and entered them into the two regression equations. The exhibitionism scores under different conditions of narcissism and online relatedness need satisfaction were calculated, as shown in Figure 5. On the contray, under the lower level of narcissism condition, the promoting effect of online relatedness need satisfaction on exhibitionism was stronger. These findings validated the H5. FIGURE 4 The interactive effect of online competence need satisfaction and narcissism on exhibitionism. FIGURE 5 The interactive effect of online relatedness need satisfaction and narcissism on exhibitionism. In summary, exhibitionism was proved to fully mediate the association between online competence need satisfaction and self-disclosure on the mobile net, but only partly mediated the association between online relatedness need satisfaction and self-disclosure on the mobile net. Moreover, narcissism moderated the mediation paths. Specifically, when the online competence need satisfaction was higher, adolescents with a high level of narcissism showed a stronger exhibitionism motivation than those with a low level of narcissism, while when the online relatedness need satisfaction was higher, the result was exactly opposite. Discussion Based on the SDT, this study constructed a moderated mediation model to examine the mediation effect of exhibitionism in the relationship between online basic psychological need satisfaction and self-disclosure on the mobile net, and the moderating role of narcissism in the association between online basic psychological need satisfaction and exhibitionism. The results partially validated our research hypotheses. Exhibitionism was proved to fully mediate the association between online competence need satisfaction and self-disclosure on the mobile net, but only partly mediated the association between online relatedness need satisfaction and self-disclosure on the mobile net. Moreover, narcissism moderated the mediation paths from both competence and relatedness need satisfaction and exhibitionism. This research contributed to providing some theoretical and practical implications for practice and future research on self-disclosure online. Inconsistent with previous research results (Winter et al., 2014), gender had no significant effect on self-disclosure on the mobile net in this study. Adolescents about 15 years old particularly enjoy accessing the Internet to disclose private information about themselves (Valkenburg and Peter, 2007). Regardless of gender, both boys and girls have a strong desire to satisfy their psychological need, so this study speculated that this may be one of the reasons why there was no gender difference. The Mediating Role of Exhibitionism in the Association between Online Basic Psychological Need Satisfaction (Competence and Relatedness) and Self-disclosure on the Mobile Net Following the need-motivation-behavior model, this study introduced the important mediator variable of exhibitionism into the relationship between online basic psychological need satisfaction and self-disclosure on the mobile net. In line with our assumptions, the results of structural equation model showed that exhibitionism fully mediated the relationship between online competence need satisfaction and self-disclosure on the mobile net, and partially mediated that between online relatedness need satisfaction and self-disclosure on the mobile net. In addition, there was no significant mediation effect of exhibitionism in the relationship between online autonomy need satisfaction and self-disclosure on the mobile net. Online competence need satisfaction did not directly promote the self-disclosure behavior of the young people in this study, and it completely depended on the mediating role of the exhibitionism motivation. This was most likely due to the physical and mental characteristics of the adolescents. Adolescence is a developmental stage at which individuals may experience a number of stressors including completing academic requirements, developing appropriate social roles with peers, and achieving expectations of increasing independence from family (Compas et al., 2001). At the core of this type of adolescent rebellion is the expression of the ego and the need for societal recognition. Most adolescents desire to be attractive and desirable. They have a strong need to express themselves and attract attention, and receive the recognition and approval of others through their own efforts around them. The advent of the Internet created a diversified open platform for students to exhibit their appearance, performance, and ability online. Correspondingly, the feeling of competence would further enhance their senses of recognition and affirmation, which encourage them to actively exhibit themselves which is in line with the exhibitionist desire of young boys and girls. According to the SDT, this shows a cyclical process in which teenagers with more online satisfaction actively seek opportunities for self-expression in order to get more attention and appreciation from others. Therefore, competence need satisfaction online leads to self-disclosure on the mobile net through exhibitionism. Our findings indicated that the link between online relatedness need satisfaction and self-disclosure on the mobile net was significantly and partially mediated by exhibitionism. Adolescence is characterized by a struggle for individual independence. With the rapidly change of physiology and the psychological, adolescents are more likely to feel lonely specially and desire to be understood (Maes et al., 2015). Feelings of loneliness arise a signal to people that there is something missing in their social relationships and to motivate them to reconnect again. Although they have an urgent need to be related to and supported by peers other than their parents, it is difficult for them to show their real face in front of teachers and parents. The Internet has created virtual spaces and communities for young people to find a sense of belonging and to relieve their loneliness. Self-disclosure online is the act of making the self known to others, and it can serve to strengthen relationships. Through self-disclosure online, adolescents obtain more relatedness satisfaction. The online relatedness psychological need satisfaction reinforces subsequent network behavior to pursue more satisfaction. In addition, the link between online relatedness need satisfaction and self-disclosure on the mobile net was partially mediated by exhibitionism in this study. Actually, the motivation of self-disclosure online also includes seeking companionship, relationship maintenance, entertainment, and so on (Hollenbaugh and Ferris, 2014). Besides, with the stability and deepening of the relationship, maybe other motivations like relationship maintenance should be included in the future study. In addition, our findings indicated that the link between online autonomy need satisfaction and self-disclosure on the mobile net was not mediated by exhibitionism. Teenagers try to become independent individuals on a psychological level and become free of dependence on their parents. But in real life, opportunities to act independently may be limited. With the rapid development of the Internet, a relatively freedom atmosphere allows people to express their thoughts and emotions without the threat of repercussion. According to the theory of self-determination, when young people’s autonomy needs are satisfied through the network, they will continue to pursue this activity. This study showed that there was a direct prediction effect between satisfaction of online autonomy need and self-disclosure. Interestingly, the impact of online autonomy need satisfaction and self-disclosure on the mobile net was not mediated by exhibitionism. One plausible explanation was that the motivation of self-disclosure online also included other motivations such as entertainment and passing time (Hollenbaugh and Ferris, 2014), which should be the focus of future studies. The Moderation Effect of Narcissism for the Relationship between Online Competence and Relatedness Psychological Needs Satisfaction and Exhibitionism In this study, we explored whether narcissistic personality trait had a moderating effect on the front path from online competence and relatedness needs satisfaction on exhibitionism. The results of the study proved that the main effect of narcissistic personality trait on exhibitionism was not significant, inconsistent with previous research (Wang and Stefanone, 2013). However, further analysis showed that the interaction effect of narcissism and both competence and relatedness needs satisfaction could significantly and positively predict exhibitionism, and further explained that all the factors and conditions would not work alone, but work interactively. The impact mechanism of online basic psychological need satisfaction on self-disclosure on the mobile net is a complex integrated process. As motivations are driving forces and psychological dispositions reinforce certain behavior to gratifying desires, different people with varying psychological and emotional states are motivated by different needs, which could be gratified in numerous ways via engagement with social media (Nabi et al., 2006). It is likely that different users access to mobile net for different underlying needs and that these needs may be associated with different types of motivations. People with a high level of narcissism have a strong desire to gain attention and approval of others. Higher degrees of competence need satisfaction from the network make narcissistic individuals feel more confident about their superiority, thus exhibiting more effort to get more people’s recognition and appreciation. In other words, our findings suggest that increased competence need satisfaction for people with a high level of narcissism did not necessarily increase the same extent of online exhibitionism to the same degree as it did for people with a low level of narcissism. The moderating effect of narcissism on the relationship between online relatedness need satisfaction and exhibitionism was opposite to the above research results. When narcissistic individuals obtain a sense of belonging, they also tend to disclose more information online. Actually, narcissists required an audience to meet their constant need for admiration in order to enhance their feelings of self-importance instead of caring about other people’s feelings (Morf and Rhodewalt, 2001; Campbell and Foster, 2007; Carlson et al., 2011). It is possible that their feeling of belongingness is different from other people’s. They are usually not interested in forming strong interpersonal relationships but rather in establishing superficial weak connections (and they are also skilled at initiating them; Campbell and Foster, 2002). If a narcissistic individual feels very connected to others but not very competent, then he or she should experience a more pressing desire to become more competent than to become more connected. In contrast, for average people, one’s perceived online relationship formation was a stronger predictor of exhibitionism than for narcissistic individuals. One possible explanation was that adolescents adopt online exhibition as strategies to enhance online friendships resulting from their positive attitude toward online relationship formation. Implications and Suggestions for Future Research Extending previous research, our findings provide empirical support for SDT in the context of the mobile net. The present study validated the influence mechanism of online basic psychological need satisfaction on self-discloser on the mobile net. It is helpful to improve our understanding of the self-disclosure behavior of adolescents. First, these research results have some practical implications. On the one hand, Internet usage such as self-disclosure online affords opportunities to satisfy the basic psychological needs of young people; on the other hand, teenagers are eager to achieve personal perfection and independence, establish intimacy outside of their families, and develop social-emotional relationships. When they obtain a sense of competence, belongingness, and autonomy through disclosing private information on the Internet, they can become obsessed with network behavior. Due to a deficiency of self-control, young people might be caught in a vicious cycle. At present, how to help adolescents take advantage of self-disclosure behavior instead of becoming addicted to it has already become a research topic worthy of urgent attention. Second, self-disclosure online preference in adolescents reflects a thought-provoking social phenomenon that is currently quite common in China. Young people may not have the chance to express their opinions freely and to be recognized and appreciated by the external world. In the real world, parents should affirm their teenagers’ strong points and good qualities through approaches such as praising and encouraging them. Teachers in the learning process should also pay attention to encouraging and inspiring students’ interest in study, and in the process of teaching, give classmates encouragement and praise, avoid fatigue, and help more teenagers to build confidence. There are some limitations to this research that need to be improved in a future study. First, this study did not take the basic psychological need satisfaction in daily life into account. The basic psychological need satisfaction in daily life is one of the potential impact factors of self-disclosure on the mobile net. To a certain extent, it is worthwhile to explore the relationship among online and offline psychological need satisfaction and self-disclosure online. This research will focus on this relationship in the following study. Second, the method adopted in this study mainly includes questionnaire survey method. In view of the popularity of Social media like Facebook, Twitter, and blogs among young people, future study should be more concerned about the objective behavior of the self-disclosure online such as amount, breadth and depth through the big data analytics. In addition, it is helpful to systematically and thoroughly understand the continuous process and the rule of quantitative change and qualitative change among students by tracking studies. It would be helpful to explore the dynamic relationship between psychological need satisfaction and network behavior over a longer time period. Author Contributions Conception and design of the study: YL, RL. Collection, analysis and interpretation of data: YL, RL, JW. Drafting the article: YL, RL. Revising the article critically: YL, RL, YD, RZ, and LX. Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Supplementary Material The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpsyg.2016.01279 DATA SHEET 1 Online basic psychological need satisfaction+exhibitionism+narcissism+self-disclosure questionnaire. Click here for additional data file. Click here for additional data file. Click here for additional data file. ==== Refs References Ames D. R. Rose P. Anderson C. P. (2006 ). The NPI-16 as a short measure of narcissism. J. Res. Pers. 40 440 –450 . 10.1037/a0033192 Ang C. S. Talib M. A. Tan K. A. Tan J. P. Yaacob S. N. (2015 ). Understanding computer-mediated communication attributes and life satisfaction from the perspectives of uses and gratifications and self-determination. Comput. Hum. Behav. 49 20 –29 . 10.1016/j.chb.2015.02.037 Aviram I. Amichai-Hamburger Y. (2005 ). Online infidelity: aspects of dyadic satisfaction, self-disclosure, and narcissism. J. Comput. Mediat. Commun. 10 229 –232 . Bandura A. Freeman W. H. Lightsey R. (1999 ). Self-efficacy: the exercise of control. J. Cogn. Psychother. 604 158 –166 . Bibby P. (2008 ). Dispositional factors in the use of social networking sites: findings and implications for social computing research. Intell. Secur. Inform. 5075 392 –400 . 10.1007/978-3-540-69304-8_40 Bryce J. Klang M. (2009 ). Young people, disclosure of personal information and online privacy: control, choice and consequences. Inform. Secur. Tech. Rep. 14 160 –166 . 10.1016/j.istr.2009.10.007 Campbell W. K. (1999 ). Narcissism and romantic attraction. J. Pers. Soc. Psychol. 77 1254 –1270 . 10.1037/0022-3514.77.6.1254 Campbell W. K. Brunell A. B. Finkel E. J. (2006 ). “Narcissism, interpersonal self-regulation, and romantic relationships: an agency model approach ,” in Self and Relationships: Connecting Intrapersonal and Interpersonal Processes eds Vohs K. D. Finkel E. J. (New York, NY : Guilford Press ) 57 –83 . Campbell W. K. Foster C. A. (2002 ). Narcissism and commitment in romantic relationships: an investment model analysis. Pers. Soc. Psychol. Bull. 28 484 –495 . 10.1177/0146167202287006 Campbell W. K. Foster J. D. (2007 ). “The narcissistic self: background, an extended agency model, and ongoing controversies ,” in Frontiers in Social Psychology: The Self eds Sedikides C. Spencer S. (Philadelphia, PA : Psychology Press ) 115 –138 . Carlson E. N. Vazire S. Oltmanns T. F. (2011 ). You probably think this paper’s about you: narcissists’ perceptions of their personality and reputation. J. Pers. Soc. Psychol. 101 185 –201 . 10.1037/a0023781 21604895 Carlson K. S. Gjerde P. F. (2009 ). Preschool personality antecedents of narcissism in adolescence and young adulthood: a 20-year longitudinal study. J. Res. Pers. 43 570 –578 . 10.1016/j.jrp.2009.03.003 20161614 Caspi A. Roberts B. W. Shiner R. L. (2005 ). Personality development: stability and change. Annu. Rev. Psychol. 56 453 –484 . 10.1146/annurev.psych.55.090902.141913 15709943 Chen G. M. (2012 ). Why do women write personal blogs? Satisfying needs for self-disclosure and affiliation tell part of the story. Comput. Hum. Behav. 28 171 –180 . Chen K. C. Jang S. J. (2010 ). Motivation in online learning: testing a model of self-determination theory. Comput. Hum. Behav. 26 741 –752 . 10.1016/j.chb.2010.01.011 Choi M. Toma C. L. (2014 ). Social sharing through interpersonal media: patterns and effects on emotional well-being. Comput. Hum. Behav. 36 530 –541. 10.1016/j.chb.2014.04.026 Compas B. E. Connorsmith J. K. Saltzman H. Thomsen A. H. Wadsworth M. E. (2001 ). Coping with stress during childhood and adolescence: problems, progress, and potential in theory and research. Psychol. Bull. 127 87 –127 . 10.1037/0033-2909.127.1.87 11271757 Deci E. L. Ryan R. M. (1985 ). Intrinsic Motivation and Self-Determination in Human Behavior. New York, NY : Plenum . Deci E. L. Ryan R. M. (2000 ). The “what” and “why” of goal pursuits: human need and the self-determination of behavior. Psychol. Inq. 11 227 –268 . 10.1080/08870440902783628 Emanuel L. Neil G. J. Bevan C. Fraser D. S. Stevenage S. V. Whitty M. T. (2014 ). Who am I? Representing the self offline and in different online contexts. Comput. Hum. Behav. 41 146 –152 . 10.1016/j.chb.2014.09.018 Forest A. L. Wood J. V. (2012 ). When social networking is not working: individuals with low self-esteem recognize but do not reap the benefits of self-disclosure on facebook. Psychol. Sci. 23 295 –302 . 10.1177/0956797611429709 22318997 Fuligni A. J. (1998 ). Authority, autonomy, and parent-adolescent conflict and cohesion: a study of adolescents from Mexican, Chinese, Filipino, and European backgrounds. Dev. Psychol. 34 782 –792 .9681270 Gibbs J. L. Ellison N. B. Heino R. D. (2006 ). Self-presentation in online personals: the role of anticipated future interaction, self-disclosure, and perceived success in Internet dating. Commun. Res. 33 152 –177 . 10.1177/0093650205285368 Hollenbaugh E. E. (2010 ). Personal journal bloggers: profiles of disclosiveness. Comput. Hum. Behav. 26 1657 –1666 . 10.1016/j.chb.2010.06.014 Hollenbaugh E. E. (2011 ). Motives for maintaining personal journal blogs. Cyberpsychol. Behav. Soc. Netw. 14 13 –20 . 10.1089/cyber.2009.0403 21329438 Hollenbaugh E. E. Ferris A. L. (2014 ). Facebook self-disclosure: examining the role of traits, social cohesion, and motives. Comput. Hum. Behav. 30 50 –58 . 10.1016/j.chb.2013.07.055 Hollenbaugh E. E. Ferris A. L. (2015 ). Predictors of honesty, intent, and valence of facebook self-disclosure. Comput. Hum. Behav. 50 456 –464 . 10.1016/j.chb.2015.04.030 Ishii K. (2004 ). Internet use via mobile phone in Japan. Telecomm. Policy 28 43 –58 . 10.1016/j.telpol.2003.07.001 Joinson A. N. Paine C. B. (2007 ). “Self-disclosure, privacy and the Internet ,” in Oxford Handbook of Internet Psychology eds Joinson A. N. McKenna K. Y. A. Postmes T. Reips U.-D. (Oxford : Oxford University Press ) 237 –252 . Joinson A. N. Woodley A. Reips U. D. (2007 ). Personalization, authentication and self-disclosure in self-administered Internet surveys. Comput. Hum. Behav. 23 275 –285 . 10.1016/j.chb.2004.10.012 Jones D. N. Paulhus D. L. (2014 ). Introducing the short dark triad (sd3) a brief measure of dark personality traits. Assessment 21 28 –41 . 10.1177/1073191113514105 24322012 Joreskog K. G. Sorbom D. (1979 ). Advances in Factor Analysis and Structural Equation Models. Cambridge, MA : ABT books . Katz E. Blumler J. G. Gurevitch M. (1974 ). “Utilization of mass communication by the individual ,” in The Use of Mass Communications: Current Perspectives on Gratifications Research eds Blumler J. G. Katz E. (Beverly Hills, CA : Sage ). Kim H. S. (2016 ). What drives you to check in on Facebook? Motivations, privacy concerns, and mobile phone involvement for location-based information sharing. Comput. Hum. Behav. 54 397 –406 . 10.1016/j.chb.2015.08.016 Kisekka V. Bagchi-Sen S. Rao H. R. (2013 ). Extent of private information disclosure on online social networks: an exploration of facebook mobile phone users. Comput. Hum. Behav. 29 2722 –2729 . 10.1016/j.chb.2013.07.023 Kisilevich S. Last M. (2011 ). “Exploring gender differences in member profiles of an online dating site across 35 countries ,” in Proceedings of the International Conference on Analysis of Social Media and Ubiquitous Data (Berlin : Springer ) 57 –78 . Klausen J. (2015 ). Tweeting the jihad: social media networks of western foreign fighters in Syria and Iraq. Stud. Confl. Terror. 38 1 –22 . 10.1080/1057610X.2014.974948 Ko H. C. Kuo F. Y. (2009 ). Can blogging enhance subjective well-being through self-disclosure? Cyberpsychol. Behav. 12 75 –79 . 10.1089/cpb.2008.0163 19132911 Koskela H. (2004 ). Webcams, TV shows and mobile phones: empowering exhibitionism. Surveill. Soc. 2 199 –215 . Kwak K. T. Choi S. K. Lee B. G. (2014 ). Sns flow, sns self-disclosure and post hoc interpersonal relations change: focused on Korean facebook user. Comput. Hum. Behav. 31 294 –304 . 10.1016/j.chb.2013.10.046 Leary M. R. (1999 ). “The scientific study of personality ,” in Personality: Contemporary Theory and Research eds Derlega V. J. Winstead B. A. Jones W. H. (Belmont, CA : Wadsworth Group ) 4 –24 . Lee R. M. Robbins S. B. (1995 ). Measuring belongingness: the social connectedness and social assurance scales. J. Couns. Psychol. 42 232 –241 . 10.1037/0022-0167.42.2.232 Leung L. (2013 ). Generational differences in content generation in social media: the roles of the gratifications sought and of narcissism. Comput. Hum. Behav. 29 997 –1006 . 10.1016/j.chb.2012.12.028 Levinger G. K. Snoek J. D. (1972 ). Attraction in Relationship: A New Look at Interpersonal Attraction. New York, NY : General Learning Press . Ma M. Leung L. (2006 ). Unwillingness-to-communicate, perceptions of the Internet and self-disclosure in ICQ. Telemat. Inform. 23 22 –37 . 10.1016/j.tele.2005.01.001 Maes M. Vanhalst J. Spithoven A. W. M. Noortgate W. V. D. Goossens L. (2015 ). Loneliness and attitudes toward aloneness in adolescence: a person-centered approach. J. Youth Adolesc. 45 1 –21 . 10.1007/s10964-015-0354-5 Mazer J. P. Murphy R. E. Simonds C. J. (2007 ). I’ll see you on “Facebook”: the effects of computer-mediated teacher self-disclosure on student motivation, affective learning, and classroom climate. Commun. Educ. 56 1 –17 . 10.1080/03634520601009710 Mazur E. (2010 ). Self-presentation and interaction in blogs of adolescents and young emerging adults. J. Adolesc. Res. 25 124 –144 . 10.1177/0743558409350498 McClelland D. C. (1976 ). “Sources of stress in the drive for power ,” in Psychopathology of Human Adaptation ed. Serban G. (New York, NY : Springer ) 247 –270 . 10.1007/978-1-4684-2238-2_16 McKenna K. Y. A. Green A. S. Gleason M. E. J. (2002 ). Relationship formation on the Internet: what’s the big attraction? J. Soc. Issues 58 9 –31 . 10.1111/1540-4560.00246 Miller J. D. Campbell W. K. (2010 ). The case for using research on trait narcissism as a building block for understanding narcissistic personality disorder. Pers. Disord. 1 180 –191 . 10.1037/a0018229 Moller A. C. Deci E. L. Elliot A. J. (2010 ). Person-level relatedness and the incremental value of relating. Pers. Soc. Psychol. Bull. 36 754 –767 . 10.1177/0146167210371622 20460651 Morf C. C. Rhodewalt F. (2001 ). Unraveling the paradoxes of narcissism: a dynamic self-regulatory processing model. Psychol. Inq. 12 177 –196 . 10.1207/S15327965PLI1204_1 Nabi R. L. Keli F. Tricia D. Shawnika H. (2006 ). Does misery love company? exploring the therapeutic effects of tv viewing on regretted experiences. J. Commun. 56 689 –706 . 10.1111/j.1460-2466.2006.00315.x Nguyen M. Bin Y. S. Campbell A. (2012 ). Comparing online and offline self-disclosure: a systematic review. Cyberpsychol. Behav. Social Netw. 15 103 –111 . 10.1089/cyber.2011.0277 Park N. Jin B. Jin S. A. A. (2011 ). Effects of self-disclosure on relational intimacy in facebook. Comput. Hum. Behav. 27 1974 –1983 . Park N. Kee K. F. Valenzuela S. (2009 ). Being immersed in social networking environment: facebook groups, uses and gratifications, and social outcomes. Cyberpsychol. Behav. 12 729 –733 . 10.1089/cpb.2009.0003 19619037 Penney L. M. Spector P. E. (2002 ). Narcissism and counterproductive work behavior: do bigger egos mean bigger problems? Int. J. Sel. Assess. 10 126 –134 . 10.1111/1468-2389.00199 Podsakoff P. M. Mackenzie S. B. Lee J. Y. Podsakoff N. P. (2003 ). Common method biases in behavioral research: a critical review of the literature and recommended remedies. J. Appl. Psychol. 88 879 –903 . 10.1037/0021-9010.88.5.879 14516251 Preacher K. J. Hayes A. F. (2008 ). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav. Res. Methods 40 879 –891 . 10.3758/BRM.40.3.879 18697684 Przybylski A. K. Weinstein N. Ryan R. M. Rigby C. S. (2009 ). Having to versus wanting to play: background and consequences of harmonious versus obsessive engagement in video games. Cyberpsychol. Behav. 12 485 –492 . 10.1089/cpb.2009.0083 19772442 Qian H. Scott C. R. (2007 ). Anonymity and self-disclosure on weblogs. J. Comput. Mediat. Commun. 12 1428 –1451 . 10.1111/j.1083-6101.2007.00380.x Rosen D. Stefanone M. A. Lackaff D. (2010 ). “Online and offline social networks: investigating culturallyspecific behavior and satisfaction,” in Proceedings of the 43rd Hawaii International Conference on System Sciences (Washington, DC : IEEE ). Ross C. Orr E. S. Sisic M. Arseneault J. M. Simmering M. G. Orr R. R. (2009 ). Personality and motivations associated with Facebook use. Comput. Hum. Behav. 25 578 –586 . 10.1016/j.chb.2008.12.024 Rubin A. M. (2002 ). “The uses-and-gratifications perspective of media effects ,” in Media effects: Advances in Theory and Research eds Bryant J. Zillmann D. (Mahwah, NJ : Lawrence Erlbaum Associates ) 525 –548 . Ryan R. M. Rigby C. S. Przybylski A. (2006 ). The motivational pull of video games: a self-determination theory approach. Motiv. Emot. 30 344 –360 . 10.1007/s11031-006-9051-8 Ryan T. Xenos S. (2011 ). Who uses facebook? An investigation into the relationship between the big five, shyness, narcissism, loneliness, and facebook usage. Comput. Hum. Behav. 27 1658 –1664 . 10.1016/j.chb.2011.02.004 Schmidt J. (2007 ). Blogging practices: an analytical framework. J. Comput. Mediat. Commun. 12 1409 –1427 . 10.1111/j.1083-6101.2007.00379.x Sedikides C. Rudich E. A. Gregg A. P. Kumashiro M. Rusbult C. (2004 ). Are normal narcissists psychologically healthy: self-esteem matters. J. Pers. Soc. Psychol. 87 400 –416 . 10.1037/0022-3514.87.3.400 15382988 Sheldon K. M. Abad N. Hinsch C. (2011 ). A two-process view of facebook use and relatedness need-satisfaction: disconnection drives use, and connection rewards it. J. Pers. Soc. Psychol. 100 766 –775 . 10.1037/a0022407 21280967 Sheldon K. M. Gunz A. (2009 ). Psychological needs as basic motives, not just experiential requirements. J. Pers. 77 1467 –1492 . 10.1111/j.1467-6494.2009.00589.x 19678877 Shen C.-X. Liu R.-D. Wang D. (2013 ). Why are children attracted to the Internet? The role of need satisfaction perceived online and perceived in daily real life. Comput. Hum. Behav. 29 185 –192 . 10.1016/j.chb.2012.08.004 Smock A. D. Ellison N. B. Lampe C. Wohn D. Y. (2011 ). Facebook as a toolkit: a uses and gratification approach to unbundling feature use. Comput. Hum. Behav. 27 2322 –2329 . 10.1016/j.chb.2011.07.011 Urista M. A. Dong Q. Day K. D. (2009 ). Explaining why young adults use MySpace and Facebook through uses and gratifications theory. Hum. Commun. 12 215 –229 . Valkenburg P. M. Peter J. (2007 ). Preadolescents’ and adolescents’ online communication and their closeness to friends. Dev. Psychol. 43 267 –277 . 10.1037/0012-1649.43.2.267 17352538 Walther J. B. (2011 ). “Theories of computer-mediated communication and interpersonal relations ,” in The Handbook of Interpersonal Communication 4th Edn eds Knapp M. L. Daly J. A. (Thousand Oaks, CA : Sage ) 443 –479 . Wang C. K. J. Liu W. C. Chye S. Chatzisarantis N. L. D. (2011 ). Understanding motivation in Internet gaming among Singaporean youth: the role of passion. Comput. Hum. Behav. 27 1179 –1184 . 10.1016/j.chb.2010.12.012 Wang J. L. Jackson L. A. Zhang D. J. (2011 ). The mediator role of self-disclosure and moderator roles of gender and social anxiety in the relationship between Chinese adolescents’ online communication and their real-world social relationships. Comput. Hum. Behav. 27 2161 –2168 . 10.1016/j.chb.2011.06.010 Wang S. S. Stefanone M. A. (2013 ). Showing off? human mobility and the interplay of traits, self-disclosure, and facebook check-ins. Soc. Sci. Comput. Rev. 31 437 –457 . 10.1177/0894439313481424 Wells T. Bailey J. T. Link M. W. (2014 ). Comparison of smartphone and online computer survey administration. Soc. Sci. Comput. Rev. 32 238 –255 . 10.1177/0894439313505829 Wen X. (2014 ). A study of wechat’s effects on college students’ interpersonal communication and the educational countermeasures. Psychol. Res. 14 35 –38 . Wheeless L. R. (1978 ). A follow-up study of the relationships among trust, disclosure, and interpersonal solidarity. Hum. Commun. Res. 4 143 –157 . 10.1111/j.1468-2958.1978.tb00604.x Wink P. (1991 ). Two faces of narcissism. J. Pers. Soc. Psychol. 61 590 –597 . 10.1111/j.1467-6494.2012.00767.x 1960651 Winter S. Neubaum G. Eimler S. C. Gordon V. Theil J. Herrmann J. (2014 ). Another brick in the facebook wall——how personality traits relate to the content of status updates. Comput. Hum. Behav. 34 194 –202 . 10.1016/j.chb.2014.01.048 Wu A. M. Cheung V. I. Ku L. Hung E. P. (2013 ). Psychological risk factors of addiction to social networking sites among Chinese smartphone users. J. Behav. Addict. 2 160 –166 . 10.1556/JBA.2.2013.006 25215198 Zhao L. Lu Y. B. Wang B. Huang W. (2011 ). What makes them happy and curious online? An empirical study on high school students’ Internet use from a self-determination theory perspective. Comput. Educ. 56 346 –356 . 10.1016/j.compedu.2010.08.006 Zhu Y. Chen L. Chen H. Chern C. (2011 ). How does Internet information seeking help academic performance? The moderating and mediating roles of academic self-efficacy. Comput. Educ. 57 2476 –2484 . 10.1016/j.compedu.2011.07.006 Zimmer J. C. Arsal R. E. Al-Marzouq M. Grover V. (2010 ). Investigating online information disclosure: effects of information relevance, trust and risk. Inform. Manag. 47 115 –123 . 10.1016/j.im.2009.12.003

PMC005xxxxxx/PMC5000556.txt

==== Front Front PhysiolFront PhysiolFront. Physiol.Frontiers in Physiology1664-042XFrontiers Media S.A. 10.3389/fphys.2016.00365PhysiologyOriginal ResearchReduced Sodium Current in the Lateral Ventricular Wall Induces Inferolateral J-Waves Meijborg Veronique M. F. 12*†Potse Mark 345†Conrath Chantal E. 1Belterman Charly N. W. 13De Bakker Jacques M. T. 126Coronel Ruben 131Department of Clinical and Experimental Cardiology, Academic Medical CenterAmsterdam, Netherlands2Interuniversity Cardiology Institute of the NetherlandsUtrecht, Netherlands3Electrophysiology and Heart Modeling Institute LIRYC, Université de BordeauxBordeaux, France4Modélisation et calculs pour l'électrophysiologie cardiaque (Carmen) team, Inria Bordeaux Sud-OuestBordeaux, France5Center for Computational Medicine in Cardiology, Institute of Computational Science, Università della Svizzera italianaLugano, Switzerland6Department of Medical Physiology, University of UtrechtUtrecht, NetherlandsEdited by: T. Alexander Quinn, Dalhousie University, Canada Reviewed by: Steve Poelzing, Virginia Tech, USA; Alfonso Bueno-Orovio, University of Oxford, UK *Correspondence: Veronique M. F. Meijborg veromeijborg@gmail.comThis article was submitted to Cardiac Electrophysiology, a section of the journal Frontiers in Physiology †These authors have contributed equally to this work. 26 8 2016 2016 7 36511 5 2016 09 8 2016 Copyright © 2016 Meijborg, Potse, Conrath, Belterman, De Bakker and Coronel.2016Meijborg, Potse, Conrath, Belterman, De Bakker and CoronelThis is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Background: J-waves in inferolateral leads are associated with a higher risk for idiopathic ventricular fibrillation. We aimed to test potential mechanisms (depolarization or repolarization dependent) responsible for inferolateral J-waves. We hypothesized that inferolateral J-waves can be caused by regional delayed activation of myocardium that is activated late during normal conditions. Methods: Computer simulations were performed to evaluate how J-point elevation is influenced by reducing sodium current conductivity (GNa), increasing transient outward current conductivity (Gto), or cellular uncoupling in three predefined ventricular regions (lateral, anterior, or septal). Two pig hearts were Langendorff-perfused with selective perfusion with a sodium channel blocker of lateral or anterior/septal regions. Volume-conducted pseudo-electrocardiograms (ECG) were recorded to detect the presence of J-waves. Epicardial unipolar electrograms were simultaneously recorded to obtain activation times (AT). Results: Simulation data showed that conduction slowing, caused by reduced sodium current, in lateral, but not in other regions induced inferolateral J-waves. An increase in transient outward potassium current or cellular uncoupling in the lateral zone elicited slight J-point elevations which did not meet J-wave criteria. Additional conduction slowing in the entire heart attenuated J-waves and J-point elevations on the ECG, because of masking by the QRS. Experimental data confirmed that conduction slowing attributed to sodium channel blockade in the left lateral but not in the anterior/septal ventricular region induced inferolateral J-waves. J-waves coincided with the delayed activation. Conclusion: Reduced sodium current in the left lateral ventricular myocardium can cause inferolateral J-waves on the ECG. J-waveearly repolarizationdepolarizationconductioncellular uncouplingsodium currentFundació la Marató de TV310.13039/100008666080632Fondation Leducq10.13039/501100001674ShapeHeart Network, 10801 ==== Body Introduction J-waves in inferolateral leads of the surface electrocardiogram (ECG)—or early repolarization (ER) pattern—are characterized as an elevation of the QRS-ST junction manifested as a notch or slur (Sacher et al., 2013; Mizusawa and Bezzina, 2014; Macfarlane et al., 2015). The J-wave was considered a benign phenomenon (Shipley and Hallaran, 1935) until Haïssaguerre et al. demonstrated an increased prevalence of J-waves in patients with idiopathic ventricular fibrillation (Haïssaguerre et al., 2008). This association was confirmed by a meta-analysis of nine studies (Wu et al., 2013). The mechanism underlying the inferolateral J-waves—or ER pattern—is subject of an ongoing debate (Wellens, 2008; Hoogendijk et al., 2013). Yan and colleagues proposed a cellular mechanism for J-waves based on experiments performed in canine arterially perfused ventricular wedge preparations (Yan and Antzelevitch, 1996). They postulated that J-waves are generated by a transmural voltage gradient resulting from a more prominent transient outward potassium current (Ito) in the sub-epicardium, leading to a more prominent action potential (AP) notch than in the sub-endocardium. An alternative mechanism is based on regional conduction slowing. Late potentials at the terminal QRS complex in the ECG have been related to delayed activation (Simson et al., 1983). Because of the analogy between inferolateral J-waves and the ST segment elevations in the Brugada Syndrome some investigators posit a common mechanism for the two syndromes (Antzelevitch and Yan, 2010). However, sodium channel blockers cause a differential effect, as these are used to provoke ST segment elevations in the right precordial leads in Brugada Syndrome, but attenuate inferolateral J-waves (Roten et al., 2012). Also, the different location of the J-wave or ST segment elevations—right precordial (Antzelevitch et al., 2005) or inferolateral leads (Haïssaguerre et al., 2008)—indicates involvement of different regions. The inferolateral location of J-waves suggests a substrate in the inferolateral area of the heart, which is normally a late activated region (Durrer et al., 1970). We surmise that when this area undergoes additional conduction slowing the delayed AP will generate a voltage gradient just strong enough to cause a J-wave in the inferolateral leads. The aim of this study was (1) to test whether delayed depolarization and/or early repolarization can cause J-waves, (2) to test whether left lateral involvement is essential for J-wave appearance in inferolateral leads, and (3) to evaluate a mechanism by which sodium channel blockers can reduce J-waves. For these purposes we used a computational approach. We also employed a pig model to replicate the computational findings on regional sodium channel blockade. We selected a pig model to test the conduction hypothesis because pig hearts lack Ito (Li et al., 2003), which could therefore not have interfered with the changes in activation. Materials and methods Computer simulations A detailed description of the computer model is provided in the Data Supplement. Computer simulations were performed to test the possible contribution of three different electrical properties in the genesis of inferolateral J-waves (or ER-pattern). Within the modeled heart three areas were defined: lateral zone, anterior zone, and septal zone (Figure 1A). Within each area we simulated the following interventions and evaluated their effects on the ECG. By reducing the sodium current conductivity (GNa) to 12.5% of baseline condition we tested the depolarization hypothesis, whereas by increasing the transient outward potassium current conductivity (Gto) 10-fold we tested the repolarization hypothesis. As an alternative test for the depolarization hypothesis we simulated diffuse fibrosis with consequent conduction slowing by reducing the intracellular and extracellular conductivity to 12.5% of baseline condition (cellular uncoupling). The factor of reducing the GNa to 12.5% was chosen by a stepwise reduction of GNa to ½, ¼, ⅛, and 1/16 and selecting the largest value at which the effects of J-point elevations were present. Similarly, the increase of Gto was selected by a stepwise increase of Gto to 5, 10, and 15 ×, whereby the smallest increase to produce J-wave elevation was chosen. We also exaggerated the simulation to a 20-fold reduction of GNa (= 5% of baseline) and a 20-fold increase of Gto in order to evaluate the increment of pathophysiology, which may occur preceding an arrhythmic event (Haïssaguerre et al., 2008). On top of the simulations that induced the most and largest J-waves or J-point elevations, we tested the effects of “systemic” sodium channels blockers by reducing GNa outside the affected zone to 40% of baseline. The 40% was chosen as the value in which J-waves or J-points disappeared. Figure 1 Computational and experimental setup. (A) Heart and thorax model with indication of the three areas in which electrical properties were varied: lateral, anterior, and septal zone. Dots in thorax model indicate electrode positions for which surface ECGs were calculated (B) Schematic of experimental setup. The bucket wall contained 61 electrodes (gray dots). QRSbegin and QRSend mark the maximum QRS duration determined using all leads and may deviate from the QRS duration in a single lead. The 11 × 11 electrode grid (green) overlies the cannulated left obtuse marginal coronary artery (OM, red shaded area: selectively perfused tissue). See Supplementary Figure S1 for electrode configuration of the 9 × 12 grid. AT, activation time; RT, repolarization time. In the calculated 12-lead ECGs we determined the total QRS duration (first QRS onset in any lead to last QRS end in any lead), J-point amplitude, and presence of J-point elevations and J-waves. The J-point (Jp) was defined as the top of the end QRS notch or as the point where end QRS slurring started according to the consensus report (Macfarlane et al., 2015). A J-point elevation was defined as a Jp amplitude of 0.05 mV or more in an inferolateral lead (I, II, III, aVF, aVL, and V4-V6). A J-wave was a J-point elevation (notch or slur) of 0.1 mV or more. Difference ECGs were obtained by subtracting baseline ECGs from intervention ECGs. Experimental setup The experimental protocol was approved by the local Animal Experiments Committee (Academic Medical Center, University of Amsterdam) and carried out in accordance with national and institutional guidelines. Pigs (n = 2, male, 50–60 kg) were premedicated, intubated, and ventilated. The heart was excised and perfused according to Langendorff with a (circa 1:1) blood-Tyrode's mixture (pH = 7.35–7.45). The left obtuse marginal coronary artery (OM) or left anterior descending coronary artery (LAD) was separately cannulated. See Data Supplement for more details. The cannula was connected to a separate temperature-controlled perfusion system with the same blood-Tyrode's mixture and with a side branch for the infusion of flecainide (Tambocor, 3M Nederland, Zoeterwoude, The Netherlands, 6 or 60 μM). After baseline electrophysiological recordings, we administered flecainide to the OM/LAD cannula. For the OM perfusion the concentration was 60 μM and for LAD perfusion this was 6 μM. These are calculated concentrations based on the circulating volumes in the two perfusion systems. Initially we used a high concentration. This was chosen because the recirculating system limits the time during which a drug can be infused regionally without entering the main circulating system and causing conduction slowing in the entire heart (this is a characteristic of the cardiac circulation). During the wash-in of the drug temporary intermediate concentrations are present. During this wash-in phase the observations were made at a similar degree of conduction slowing. With the infusion of a high flecainide concentration spontaneous arrhythmias occurred after a couple of minutes following the measurements. Therefore, we used a lower concentration in the following experiment and we waited until a similar activation delay occurred in the myocardial regions. Data analysis was restricted to the conditions in which a similar degree of conduction slowing was present, and therefore a similar degree of sodium blockade (independent of the final concentration of flecainide). Electrophysiological recordings The left atrium was paced at a cycle length of 450 ms. An 11 × 11 electrode grid (OM perfusion) or a 9 × 12 electrode grid (LAD perfusion) was fixed to the epicardial surface overlapping the entire LV (and with the 9 × 12 grid also the anterior RV) to obtain local unipolar epicardial electrograms. Supplementary Methods and Supplementary Figure S1 provide details on the electrode configurations. The Langendorff-perfused heart was submerged in a bucket filled with perfusion fluid, containing 61 electrodes to obtain pseudo-electrocardiograms (pseudo-ECGs, Figure 1B). The reference signal was the average of all electrodes. In the pseudo-ECGs we determined the maximum QT interval and maximum QRS duration including the J-wave. Definition for Jp was similar as described above. Because the pseudo-ECG amplitudes were about twice those of real ECGs we adjusted the J-wave criteria accordingly. J-point elevations ≥0.2 mV were denoted as J-waves. J-wave onset (Jo) was defined as time of first deviation at the end of QRS complex initiating a J-wave—notch or slur—relative to QRS onset (Macfarlane et al., 2015). The inferolateral leads constituted the six columns of electrodes opposite the LV area (n = 18) and one bottom electrode (gray boxes in Figure 5). J-wave interval was defined as Jo to end of QRS. In the difference ECG—flecainide ECG minus baseline ECG—we determined the moment and amplitude of maximum peak difference (positive/negative). In each local unipolar electrogram we determined activation times (ATs) and repolarization times as before (Figure 1B; Coronel et al., 2006). Difference AT maps were calculated as flecainide AT map minus baselines AT map. Recordings with ST segment elevation or a flat T-wave were excluded from analysis of repolarization times. Signal analysis was performed offline using software (Potse et al., 2002) based on Matlab (The MathWorks, Inc., Natick, MA, USA). Statistics Continuous variables were presented as mean ± SD if normally distributed and as median (25th–75th percentile) if not normally distributed. Results Simulations Table 1 summarizes the simulation data on QRS durations, J-wave occurrence, maximum activation time, and activation delay for each zone of the various simulations. The ultimate AT in the anterior and lateral zones were later than in the septal zone. Table 1 Simulation data. QRS (ms) AT max (ms) AT delay (ms) J-wave Difference ECG Amax (mV) #leads (Jp ≥ 0.1 mV (Jp ≥ 0.05 mV)) Apeak (mV) Tpeak (ms) Baseline 81 – – 0 0 (0) – –    Lateral 61    Anterior 64    Septal 49 GNa Reduction    Lateral 94 93 14 0.14 4 (5) 0.40 54    Anterior 88 88 13 0.10 1 (1) 0.35 58    Septal 81 65 11 0 0 (0) 0.33 38 Gto Increase    Lateral 99 61 0 0.07 0 (4) 0.13 57    Anterior 113 64 0 0.09 0 (3) −0.15 61    Septal 99 51 1 0 0 (0) 0.21 47 Uncoupling    Lateral 96 103 15 0.06 0 (2) −0.27 54    Anterior 94 98 14 0.09 0 (2) 0.20 51    Septal 82 83 0 0 0 (0) 0.23 45 QRS, QRS duration; AT max, maximum activation time in affected zone; AT delay, activation time delay in affected zone; A max, maximum J-point amplitude; # leads, number of leads with J-waves; Apeak, amplitude of maximum peak in difference ECG; Tpeak, timing of maximum peak in difference ECG. Simulations of regional GNa reduction GNa reduction to 12.5% in the affected region caused a delay of the AP without affecting the AP morphology (Supplementary Figure S2A). Figure 2 shows 6 ECG leads at baseline and after GNa reduction in each zone. Figure 2 GNa reduction simulations. ECG at baseline (blue) and resulting from GNa reduction to 12.5% of baseline (red) in 3 zones; (A), lateral; (B), anterior; (C), septum. Gray, Difference ECG (GNa reduction minus baseline). Asterisks, J-waves. Boxed panel (D), additional GNa reduction in the rest of the heart (blue) causes disappearance of J-waves. GNa reduction in the lateral zone led to J-waves in the inferolateral leads (II, III, aVF, and V6) with a maximum amplitude of 0.14 mV in lead II (Table 1). The extremity leads showed J-wave notches and lead V6 a J-wave slur. GNa reduction in the anterior zone led to a notching J-wave in lead I only, and to J-point depressions in the inferior leads (II, III, aVF). GNa reduction in the septal zone did not induce J-waves. To exclude a secondary role of Ito for J-wave induction in these simulations, we performed a GNa intervention in the lateral zone in a model lacking Ito (Gto = 0 and GNa = 12.5% of baseline). In this model, the reduction of GNa in the lateral zone caused similar results in J-point elevations albeit with circa 0.02 mV lower amplitudes, which can be explained by the small differences in QRS morphology between the reference ECGs of the models with and without Ito (Supplementary Figure S3). When GNa was amply reduced to 5% of baseline in this Ito lacking model, J-wave amplitudes were increased about 2-fold compared to the model with GNa reduction to 12.5% (Supplementary Figure S4A). Simulations of regional Gto increase A 10-fold Gto increase caused a deeper AP notch at the epicardium of the affected region, without influencing the endocardial AP notch (Supplementary Figure S2B). Figure 3 shows the ECG results of a 10-fold Gto increase in each zone. In all simulations of Gto increase J-waves were absent. There were J-point elevations, although in fewer leads, and with lower amplitudes compared to GNa reduction (Table 1). Overall, Gto increase did prolong the QRS duration, but did not delay activation anywhere. When Gto was amply increased to 20-fold of baseline (until loss of AP dome occurred), J-point amplitudes increased about four times followed by ST-segment elevation in the inferolateral leads (Supplementary Figure S4B) compared to a 10-fold Gto increase. The ECG changes during a Gto increase did not resemble the typical inferolateral J-wave pattern that has been associated with idiopathic ventricular fibrillation (notch or slur in leads I, II, III, aVF, aVL, and V4-V6, see methods). Figure 3 Gto reduction simulations. ECG at baseline (blue) and resulting from a 10-fold Gto increase (red). No J-waves emerge after Gto increase. Organization as in Figure 2. Simulations of regional cellular uncoupling Cellular uncoupling (i.e., reduction of intracellular and extracellular conductivity to 12.5% of baseline) in the affected region caused a delay of the AP without affecting the AP morphology (Supplementary Figure S2C). Figure 4 shows the ECG results of cellular uncoupling in each zone. By reducing intercellular coupling in the lateral or anterior region, small J-point notching was induced but no J-waves appeared. The difference ECGs were of intermediate amplitude compared to GNa reduction and Gto increase. Timing of the difference ECG peak was similar as with GNa reduction and Gto increase. Cellular uncoupling in the lateral and anterior region induced activation delays of about 15 ms and caused maximum activation in the affected zone that determined the end of QRS (Table 1). Figure 4 Cellular uncoupling simulations. ECG at baseline (blue) and resulting from cellular uncoupling to 12.5% of baseline (red). No J-waves emerge after uncoupling. Organization as in Figure 2. GNa reduction in the rest of the heart on top of J-waves and J-point elevations Sodium channel blockers can attenuate inferolateral J-waves (Roten et al., 2012). Therefore, we simulated a GNa reduction in the rest of the heart on top of each intervention in the lateral zone (last column in Figures 2–4). In the 3 simulations with GNa reduction in the rest of the heart, pre-existing J-waves or J-point elevations shrunk or disappeared, masked by the QRS complex that widened with 27, 22, and 17 ms (GNa reduction, Gto increase, and cellular uncoupling, respectively). GNa reduction in the rest of the heart delayed activation in all zones with latest activation occurring outside the 3 zones (i.e., 116 ms in the GNa reduction and Gto increase interventions) or in the lateral zone (i.e., 123 ms in the cellular uncoupling intervention). Experiments Figure 5 shows the unfolded bucket with electrodes and some examples of pseudo-ECGs at baseline and during OM flecainide infusion (60 μM). In this heart, J-waves appeared on the inferolateral pseudo-ECG leads. One J-wave was observed just outside this area, with reciprocal J-point depressions in the other leads (Figure 5: pseudo-ECG at C). At baseline J-waves were present in 4 leads. After flecainide infusion the number of J-waves in inferolateral leads increased, while in the other leads 2 of 3 J-waves disappeared (Table 2: OM perfusion). The amplitude of the difference ECG was larger and positive in inferolateral leads compared to the other leads. After flecainide infusion the QRS duration was increased by 26 ms due to arising J-waves. In the heart with LAD perfusion (Figure 5, Table 2), some J-waves were present at baseline, albeit mainly in the most superior leads. After flecainide infusion (6 μM) all J-waves disappeared in inferolateral leads and arose in 2 leads near the RV posterior wall. The amplitude of the difference ECG was negative and larger in inferolateral leads than in the other leads (Table 2: LAD perfusion). The peak of the difference ECG also occurred earlier during LAD perfusion [15 (12–27) ms] compared to OM perfusion [35 (28–41) ms]. Figure 5 ECG before and after flecainide. Unfolded bucket (middle boxes) with electrodes (black dots) and heart position. Shaded boxes indicate the inferolateral area. (A), OM perfusion. (B), LAD perfusion. Stars indicate leads showing J-waves. Surrounding are examples of pseudo-ECGs (blue, baseline; red, during flecainide). Green, difference ECG. A and E correspond with the pseudo-ECGs shown in Figures 6, 7. Flecainide infusion induced or exacerbated inferolateral J-waves in the OM perfusion but not in the LAD perfusion. Table 2 ECG characteristics at baseline and during flecainide. OM perfusion LAD perfusion Baseline Flecainide (60 μM) Baseline Flecainide (6 μM) Total QRS, ms 87 113 77 76 INFEROLATERAL LEADS, n = 19    J-wave # leads, N/n 1/19 10/19 4/19 0/19    Jo, ms 62 42 45 -    A_dECG, mV 0.22 (0.14–0.36) −0.25 (−0.35—0.20) OTHER LEADS, n = 42    J-wave # leads, N/n 3/42 1/42 1/42 2/42    Jo, ms 55 55 48 34    A_dECG, mV −0.11 (−0.17—0.05) 0.17 (−0.16—0.23) QT interval, ms 294 300 273 269 QRS, QRS duration; J-wave # leads, number of leads with J-wave (N) out of number of selected leads (n); Jo, first onset of J-wave; A_dECG, maximum or minimum amplitude of difference ECG [median (25th–75th percentile)]. Activation maps Figure 6 demonstrates the activation maps at baseline and during flecainide infusion (60 μM) in the OM. At baseline, the OM region was activated latest (right side of the AT map), and showed the largest conduction delay after flecainide infusion. The J-wave interval overlaps this region of delayed activation (dotted surface in flecainide AT map) and even outreaches the AT map. We quantified the activation delay by selecting a column of electrodes inside and outside the OM region (white striped boxes) and summarized the data (Table 3). After flecainide infusion the delay in AT was larger in the OM region than in the rest of the LV. In the non-perfused regions no relevant changes occurred, as expected. Figure 6 Activation during. OM perfusion. Two pseudo-ECGs (left column); activation (AT) maps (isochrone lines at 10 ms intervals) with two epicardial electrograms (EG, right column) at baseline (top panel) and after 60 μM flecainide infusion (middle panel). AT map: thick black lines indicate isochrones of J-waves (*a and *b). Dotted area represents overlap with J-wave interval, which outreaches the AT map. Numbers 1 (“perfused” region) and 2 (“not perfused” region) recording sites of the corresponding EGs. Pseudo-ECG: arrows indicate the moment of last activation in the AT map. A and E correspond with pseudo-ECGs in Figure 5. Bottom panel: shows the difference pseudo-ECGs and difference AT map. Dashed white ellipses indicate a region within and outside the area perfused with flecainide used to determine mean ATs. Note that the effect of flecainide extended beyond the QRS duration before application and that the region subjected to conduction slowing (right side of AT map) was late activated before application of flecainide. Table 3 Data of local electrograms. Perfused Not perfused Baseline mean ± SD Flecainide mean ± SD Baseline mean ± SD Flecainide mean ± SD OM PERFUSION No. electrodes 10 10 10 10 AT, ms 39 ± 3 67 ± 9 31 ± 10 34 ± 11 AT delay, ms – 28 ± 7 – 3 ± 3 RT, ms 236 ± 7 239 ± 5 248 ± 5 247 ± 4 LAD PERFUSION No. electrodes 8 7 8 8 AT, ms 26 ± 10 42 ± 16 31 ± 5 28 ± 5 AT delay, ms – 16 ± 6 – −3 ± 1 RT, ms 214 ± 4 234 ± 15 220 ± 7 209 ± 9 “Perfused” and “not perfused” refers to region that is or is not selectively perfused. AT, activation time; RT, repolarization time. Figure 7 shows the activation maps at baseline and during flecainide infusion (6 μM) in the LAD region. This is an extended map with two thirds of the map overlying the LV and one third on the left overlying the RV anterior wall. At baseline, the J-wave interval overlaps that of late activation in the RV (dotted surface) and even outreaches the AT map. After 5 min of flecainide infusion, conduction was delayed in the LAD region and inferolateral J-waves were no longer present. Table 3 demonstrates that within the perfused region (lower left white striped box in Figure 7) activation at baseline was earlier in the activation sequence compared to the region outside the selectively perfused area (right upper box in Figure 7). After flecainide infusion activation was latest in the perfused region. Figure 7 Activation during. LAD perfusion. Description is similar to Figure 6. Note that the effect of flecainide (6 μM) was limited to the QRS duration before application and that the region subjected to conduction slowing was relatively early activated before application of flecainide. Discussion Our results show that J-waves can be induced as a result of regional conduction slowing due to reduced sodium current only in the lateral region, but not in the anterior or septal region of the heart. Either a regional increase in transient outward potassium current or cellular uncoupling was less effective in inducing J-waves, irrespective of the region. Additionally, a sodium blockade in the rest of the heart attenuated J-waves on the ECG by masking the J-waves in the prolonged QRS. The experimental data support the simulation data by showing that regional conduction slowing resulting from sodium channel blockade in the lateral but not in the anterior/septal region induces J-waves. The regional conduction slowing in the lateral zone causes local activation to occur beyond the duration of the baseline QRS complex. As a consequence, the J-wave interval coincides largely with the region of conduction delay (Figure 6). J-wave mechanism The mechanism of the inferolateral J-waves is a debated issue (Wellens, 2008; Hoogendijk et al., 2013). The two prevailing hypotheses for inferolateral J-waves are focused either on depolarization (Abe et al., 2010) or repolarization, similar to Brugada Syndrome (Yan and Antzelevitch, 1996). We have shown that the amplitude of the J-point elevation is largest with GNa reduction compared to Gto increase and cellular uncoupling. Only GNa reduction in the lateral and anterior region caused J-point elevations that met the criteria of J-waves. This observation supports the depolarization hypothesis. Cellular uncoupling induces smaller J-point elevations (no J-waves). Since activation delays due to GNa reduction and cellular uncoupling were similar (about 15 ms), we argue that their difference in J-point elevations may be explained by the reduced tissue conductivity following cellular uncoupling. In an area of reduced tissue conductivity the current generated by the activation wave front is smaller, resulting in a smaller potential field on the torso. Alternatively, J-waves may be caused by early repolarization of the AP since the increase in Gto resulted in minor J-point elevations, which fits with an expected current flow from endocardium toward epicardium during phase one repolarization. However, although the simulated 10-fold increase of Gto in this study is very large (see also Supplementary Figure S2) it induces J-point elevations that are only half the size of those induced by GNa reduction, and do not reach the critical J-wave level of 0.1 mV. Also, difference ECGs had smaller amplitudes. The latter hypothesis is therefore the less likely but cannot be excluded based on our data. Furthermore, it may be argued that Ito might play a role in the J-wave induction during a reduction of GNa. Indeed, in a model lacking Ito, the same reduction of GNa led to smaller J-point elevations, although the influence was minor, and might be explained by deeper S-waves already present during baseline (i.e., reference ECG). Moreover, the peak amplitudes of the difference ECGs (GNa minus reference) were 0.06 mV larger in the Ito lacking model compared to the model with Ito (Supplementary Figure S3B), whereas the timing of the peaks was similar. We therefore conclude that in the simulation of GNa reduction, the role of Ito in the J-wave genesis is minor and may even have an opposing effect, i.e., in presence of Ito the effects of GNa reduction on the ECG are smaller. Further amplification of the interventions showed that both GNa reduction to 5% and 20-fold Gto increase lead to larger J-wave amplitudes and QRS broadening. However, increasing the Gto 20 times does also induce ST-segment elevations in inferolateral leads, which do not resemble the inferolateral J-waves under consideration in this study. Moreover, reduction of GNa to 5% of baseline lead to typical enhancement of the J-wave notching/slurring as seen in patients during the interval preceding an event of ventricular fibrillation (Haïssaguerre et al., 2008). The amplitude of the difference ECG is largest with GNa reduction followed by cellular uncoupling and then Gto increase. Also, the difference ECG was larger with intervention in the anterior region than with intervention in the lateral region, and was smallest with intervention in the septal region. However, the amplitude of the difference ECG is not directly reflected in the amplitude of a J-point elevation. This implies that the timing and spread of the difference ECG contributes importantly to the change in QRS morphology. In the pig experiments, the peak of the difference ECG occurred earlier during LAD perfusion compared to OM perfusion, whereas in the computational results the peak of the difference ECG occurred earlier in the septal compared to the lateral or anterior zone. The separate perfusions in the ex vivo hearts, however, did cover slightly different regions within the heart, i.e., with LAD perfusion we influenced the anterior as well as the septal regions. Therefore, combining the computational results from the septal and anterior zones likely represents the ex vivo observations more closely. Enhanced Gto caused more QRS widening compared to a decreased GNa or cellular uncoupling (Table 1), whereas no activation delay occurred. This indicates that early repolarization does contribute to QRS duration. Our experimental and simulation data suggest that conduction delay resulting from reduced sodium current in the region that is activated intrinsically late in the activation sequence at baseline, i.e., the lateral region, predominantly contributes to the genesis of inferolateral J-waves, whereas conduction delay in earlier activating regions, i.e., the anterior and/or septal region, shows minor, or no J-point elevations and even J-point depression. We observed that although the AT delay in LAD perfusion was smaller than in OM perfusion it led to J-point depression rather than J-point elevations. We suggest that this difference in J-point deviation is related to the position of the region with delayed activation with respect to the anterolateral recording leads. The septal involvement causes the voltage vector during the J wave to point rightward, away from the anterolateral leads. It is similar to the explanation of how a right bundle branch block results in broad S-wave in V6. The timing of the activation within the QRS complex (normally late activation in the OM region, and normally early activation in the anterior/septal region) causes the LAD region to have a relatively small influence on the J-wave. Recently, it has been shown in a case report that J-waves in the inferior ECG leads can result from delayed activation in the basal inferior LV region, without shortening of the AP duration (Park et al., 2014). This confirms that the region of abnormality is important. Remarkably, all different interventions—GNa reduction, Gto increase, and cellular uncoupling—within the lateral region show similar results in polarity of J-point elevations and difference ECGs, although only GNa reduction led to J-waves. All interventions in the anterior region led to negative difference ECGs in the inferior leads and J-point elevation (no J-waves) were only present in lateral ECG leads. The reason that the effects of interventions are smaller in the anterior and septal zones—despite similar amplitudes of difference ECGs among zones per intervention—is therefore related to the extent of masking by the QRS complex. Modulation of J-waves J-wave amplitude is modulated by heart rate (Aizawa et al., 2012), autonomic tone (Abe et al., 2010), and drugs (Haïssaguerre et al., 2009; Roten et al., 2012). It has been demonstrated in patients that sodium channel blockers like ajmaline, pilsicainide, and flecainide attenuate J-waves in the inferolateral leads (Kawata et al., 2012; Roten et al., 2012; Nakagawa et al., 2014) and broaden the QRS (Roten et al., 2012). Our simulation data explain these findings by demonstrating that GNa reduction in the rest of the heart widens the QRS complex and consequently masks the pre-existing J-waves. In patients with idiopathic ventricular fibrillation it has been shown that inferolateral J-waves augment after a pause and diminish at higher heart rates (Haïssaguerre et al., 2008; Nakagawa et al., 2014). It has been supposed that the attenuation of J-waves at increasing heart rate results from reduced transient outward potassium current due to the relatively slow recovery from inactivation (Koncz et al., 2014). We did not study the effect of heart rate increase, but we surmise that conduction may also play a role in this phenomenon. Shorter coupling intervals result in lower upstroke velocities of the action potentials, especially in diseased hearts (Kodama et al., 1984). It may therefore have a similar effect as administration of ajmaline and we would expect a concomitant QRS prolongation. Study limitations Nowadays, computational techniques increase in maturity and reliability and are therefore more and more powerful to enlarge our insight in physiology and pathophysiology. As a consequence, it may reduce the number of required animal experiments. However, results from computational models are co-determined by the choice of parameter settings in the model which, due to uncertainty in the experimental data underlying the model, are partly based on assumptions. Due to the assumptions, results from the computational model could not directly be translated to the clinical situation. The results of our additional experiments, however, invigorate the computational findings. The model did account for interaction between different currents. However, we did not study combinations of factors (GNa reduction, Gto increase, and cellular uncoupling), although these together may lead to more exacerbated J-waves, as long as they occur in the same region. Also, it has been shown that different balances of ionic current densities generate viable action potentials (Britton et al., 2013), and therefore it would be of interest to study how the effect of each factor used in this study may change within the setting of different balances of other ion current densities. Yet, our model provides valuable insight into the potential mechanism underlying inferolateral J-waves. Another study limitation is that the pig model lacks Ito and therefore it was not suitable to test the role of Ito. With this model we were, nevertheless, able to induce J-waves, indicating that Ito is not required to induce J-waves. Conclusion Conduction slowing caused by reduced sodium current in the lateral region of the heart causes inferolateral J-waves on the ECG. The interval of J-waves coincides with the activation time of the region of delayed activation. The cardiac tissue in which J-waves are induced is characterized by a relatively late activation in the normal heart. Global conduction slowing attenuates J-waves due to masking by the prolonged QRS complex. Enhanced transient outward potassium current and cellular uncoupling have minor potency to elicit inferolateral J-waves. Although our study cannot exclude the role of repolarization abnormality, it predominantly affirms the depolarization hypothesis especially when tissue conductivity is preserved. Our study also provides an explanation for J-wave attenuation by sodium channel inhibition. Author contributions VM: design, data acquisition, data analyses, data interpretation, writing MP: design, data acquisition, data analyses, data interpretation, writing CC: data interpretation, revising CB: data acquisition, revising JDB: data interpretation, revising RC: design, data acquisition, data interpretation, revising. All authors meet the following criteria: (i) Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work, (2) Drafting the work or revising it critically for important intellectual content, (3) Final approval of the version to be published, (4) Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Funding Support from Fundació Marató de TV3 grant (project 080632), Barcelona, Spain and from Fondation LeDucq grant (ShapeHeart, project 10801). This work was granted access to the HPC resources of IDRIS under the allocation x2015037379 made by GENCI. Conflict of interest statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Supplementary material The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fphys.2016.00365 Click here for additional data file. Abbreviations ATactivation time EREarly Repolarization LADleft anterior descending coronary artery OMleft obtuse marginal coronary artery pseudo-ECGpseudo-electrocardiogram ==== Refs References Abe A. Ikeda T. Tsukada T. Ishiguro H. Miwa Y. Miyakoshi M. . (2010 ). Circadian variation of late potentials in idiopathic ventricular fibrillation associated with J waves: insights into alternative pathophysiology and risk stratification . Heart Rhythm 7 , 675 –682 . 10.1016/j.hrthm.2010.01.023 20189495 Aizawa Y. Sato A. Watanabe H. Chinushi M. Furushima H. Horie M. . (2012 ). Dynamicity of the J-wave in idiopathic ventricular fibrillation with a special reference to pause-dependent augmentation of the J-wave . J. Am. Coll. Cardiol. 59 , 1948 –1953 . 10.1016/j.jacc.2012.02.028 22624834 Antzelevitch C. Brugada P. Borggrefe M. Brugada J. Brugada R. Corrado D. . (2005 ). Brugada syndrome: report of the second consensus conference . Hear. Rhythm 2 , 429 –440 . 10.1016/jhrthm.2005.01.005 15898165 Antzelevitch C. Yan G. X. (2010 ). J wave syndromes . Hear. Rhythm 7 , 549 –558 . 10.1016/j.hrthm.2009.12.006 20817017 Britton O. J. Bueno-Orovio A. Van Ammel K. Lu H. R. Towart R. Gallacher D. J. . (2013 ). Experimentally calibrated population of models predicts and explains intersubject variability in cardiac cellular electrophysiology . Proc. Natl. Acad. Sci. U.S.A. 110 , E2098 –E2105 . 10.1073/pnas.1304382110 23690584 Coronel R. de Bakker J. M. T. Wilms-Schopman F. J. G. Opthof T. Linnenbank A. C. Belterman C. N. W. . (2006 ). Monophasic action potentials and activation recovery intervals as measures of ventricular action potential duration: experimental evidence to resolve some controversies . Heart Rhythm 3 , 1043 –1050 . 10.1016/j.hrthm.2006.05.027 16945799 Durrer D. van Dam R. T. Freud G. E. Janse M. J. Meijler F. L. Arzbaecher R. C. (1970 ). Total excitation of the isolated human heart . Circulation 41 , 899 –912 . 10.1161/01.CIR.41.6.899 5482907 Haïssaguerre M. Derval N. Sacher F. Jesel L. Deisenhofer I. de Roy L. . (2008 ). Sudden cardiac arrest associated with early repolarization . N. Engl. J. Med. 358 , 2016 –2023 . 10.1056/NEJMoa071968 18463377 Haïssaguerre M. Sacher F. Nogami A. Komiya N. Bernard A. Probst V. . (2009 ). Characteristics of recurrent ventricular fibrillation associated with inferolateral early repolarization. Role of Drug Therapy . J. Am. Coll. Cardiol. 53 , 612 –619 . 10.1016/j.jacc.2008.10.044 19215837 Hoogendijk M. G. Potse M. Coronel R. (2013 ). Critical appraisal of the mechanism underlying J waves . J. Electrocardiol. 46 , 390 –394 . 10.1016/j.jelectrocard.2013.06.017 23866294 Kawata H. Noda T. Yamada Y. Okamura H. Satomi K. Aiba T. . (2012 ). Effect of sodium-channel blockade on early repolarization in inferior/lateral leads in patients with idiopathic ventricular fibrillation and Brugada syndrome . Heart Rhythm 9 , 77 –83 . 10.1016/j.hrthm.2011.08.017 21855521 Kodama I. Wilde A. Janse M. J. Durrer D. Yamada K. (1984 ). Combined effects of hypoxia, hyperkalemia and acidosis on membrane action potential and excitability of guinea-pig ventricular muscle . J. Mol. Cell. Cardiol. 16 , 247 –259 . 10.1016/S0022-2828(84)80591-X 6716491 Koncz I. Gurabi Z. Patocskai B. Panama B. K. Szél T. Hu D. . (2014 ). Mechanisms underlying the development of the electrocardiographic and arrhythmic manifestations of early repolarization syndrome . J. Mol. Cell. Cardiol. 68 , 20 –28 . 10.1016/j.yjmcc.2013.12.012 24378566 Li G. R. Du X. L. Siow Y. L. Karmin O. Tse H. F. Lau C. P. (2003 ). Calcium-activated transient outward chloride current and phase 1 repolarization of swine ventricular action potential . Cardiovasc. Res. 58 , 89 –98 . 10.1016/S0008-6363(02)00859-3 12667949 Macfarlane P. W. Antzelevitch C. Haïssaguerre M. Huikuri H. V. Potse M. Rosso R. . (2015 ). The early repolarization pattern - a consensus paper . J. Am. Coll. Cardiol. 66 , 470 –477 . 10.1016/j.jacc.2015.05.033 26205599 Mizusawa Y. Bezzina C. R. (2014 ). Early repolarization pattern: its ECG characteristics, arrhythmogeneity and heritability . J. Interv. Card. Electrophysiol. 39 , 185 –192 . 10.1007/s10840-013-9870-y 24532112 Nakagawa K. Nagase S. Morita H. Ito H. (2014 ). Left ventricular epicardial electrogram recordings in idiopathic ventricular fibrillation with inferior and lateral early repolarization . Heart Rhythm 11 , 314 –317 . 10.1016/j.hrthm.2013.10.057 24184784 Park C. Lehrmann H. Jadidi A. S. Schiebeling-Römer J. Allgeier J. Arentz T. (2014 ). Abstract PO04-209: is this really a J-wave syndrome? Hear. Rhythm 11 , S411 10.1016/j.hrthm.2014.03.033 Potse M. Linnenbank A. C. Grimbergen C. A. (2002 ). Software design for analysis of multichannel intracardial and body surface electrocardiograms . Comput. Methods Programs Biomed. 69 , 225 –236 . 10.1016/S0169-2607(02)00014-7 12204450 Roten L. Derval N. Sacher F. Pascale P. Wilton S. B. Scherr D. . (2012 ). Ajmaline attenuates electrocardiogram characteristics of inferolateral early repolarization . Heart Rhythm 9 , 232 –239 . 10.1016/j.hrthm.2011.09.013 21914496 Sacher F. Lim H. S. Haïssaguerre M. (2013 ). Sudden cardiac death associated with J wave elevation in the inferolateral leads: insights from a multicenter registry . J. Electrocardiol. 46 , 456 –460 . 10.1016/j.jelectrocard.2013.06.028 23981312 Shipley R. A. Hallaran W. R. (1935 ). The four-lead electrocardiogram in two hundred normal men and women . Am. Heart J. 11 , 325 –345 . 10.1016/S0002-8703(36)90417-9 Simson M. B. Untereker W. J. Spielman S. R. Horowitz L. N. Marcus N. H. Falcone R. A. . (1983 ). Relation between late potentials on the body surface and directly recorded fragmented electrograms in patients with ventricular tachycardia . Am. J. Cardiol. 51 , 105 –112 . 10.1016/S0002-9149(83)80020-4 6849248 Wellens H. J. (2008 ). Early repolarization revisited . N. Engl. J. Med. 358 , 2063 –2065 . 10.1056/NEJMe0801060 18463384 Wu S. H. Lin X. X. Cheng Y. J. Qiang C. C. Zhang J. (2013 ). Early repolarization pattern and risk for arrhythmia death: a meta-analysis . J. Am. Coll. Cardiol. 61 , 645 –650 . 10.1016/j.jacc.2012.11.023 23290543 Yan G. X. Antzelevitch C. (1996 ). Cellular Basis for the Electrocardiographic J Wave . Circulation 93 , 372 –379 . 10.1161/01.CIR.93.2.372 8548912

PMC005xxxxxx/PMC5000576.txt

==== Front Front Hum NeurosciFront Hum NeurosciFront. Hum. Neurosci.Frontiers in Human Neuroscience1662-5161Frontiers Media S.A. 10.3389/fnhum.2016.00429NeuroscienceOriginal ResearchAttention Diversion Improves Response Inhibition of Immediate Reward, But Only When it Is Beneficial: An fMRI Study Scalzo Franco 1O’Connor David A. 12Orr Catherine 13Murphy Kevin 4Hester Robert 1*1Melbourne School of Psychological Sciences, University of MelbourneMelbourne, VIC, Australia2Cognitive Neuroscience Centre, Reward and Decision-Making Group, Centre National pour la Recherche ScientifiqueLyon, France3Departments of Psychiatry and Psychology, University of VermontBurlington, VT, USA4Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff UniversityCardiff, UKEdited by: Tetsuo Kida, National Institute for Physiological Sciences, Japan Reviewed by: Annette Horstmann, Max Planck Institute for Human Cognitive and Brain Sciences, Germany; Jennifer Silvers, University of California, Los Angeles, USA *Correspondence: Robert Hester, hesterr@unimelb.edu.au26 8 2016 2016 10 42917 5 2016 10 8 2016 Copyright © 2016 Scalzo, O’Connor, Orr, Murphy and Hester.2016Scalzo, O’Connor, Orr, Murphy and HesterThis is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Deficits of self-control are associated with a number of mental state disorders. The ability to direct attention away from an alluring stimulus appears to aid inhibition of an impulsive response. However, further functional imaging research is required to assess the impact of shifts in attention on self-regulating processes. We varied the level of attentional disengagement in an functional magnetic resonance imaging (fMRI)-based Go/No-go task to probe whether diversion of attention away from alluring stimuli facilitates response inhibition. We used the attention-grabbing characteristic of faces to exogenously direct attention away from stimuli and investigated the relative importance of attention and response inhibition mechanisms under different delayed reward scenarios [i.e., where forgoing an immediate reward ($1) led to a higher ($10) or no payoff in the future]. We found that diverting attention improved response inhibition performance, but only when resistance to an alluring stimulus led to delayed reward. Region of interest analyses indicated significant increased activity in posterior right inferior frontal gyrus during successful No-go trials for delayed reward trials compared to no delayed reward trials, and significant reduction in activity in the superior temporal gyri and left caudate in contexts of high attentional diversion. Our findings imply that strategies that increase the perceived benefits of response inhibition might assist individuals in abstaining from problematic impulsive behaviors. attentionresponse inhibitionrewardGo/No-go taskinferior frontal gyrussuperior temporal gyrusfMRIAustralian Research Council10.13039/501100000923DP1092852 ==== Body Introduction An important facet of human cognition is an individual’s capacity to exercise self-control. The ability to refrain from inappropriate behaviors facilitates effective interaction with society, care for one’s self, and pursuit of longer-term goals at the expense of immediate gratification (Mischel et al., 1988; Baumeister and Heatherton, 1996). Deficits in self-control are associated with a number of health issues including substance abuse (Fillmore and Rush, 2002; Monterosso et al., 2005; Goudriaan et al., 2006) and mental state disorders (Penadés et al., 2007; Boonstra et al., 2010). Self-control has been characterized as a balance between long-term goals and immediate temptations (Ochsner and Gross, 2005; Li and Sinha, 2008; Heatherton and Wagner, 2011). There is also evidence that visual attention is important for controlling impulsive responses to immediately available rewards (Mischel and Ebbesen, 1970; Mischel et al., 1972; Casey et al., 2011). For instance, resistance to a tempting stimulus can be prolonged by focussing on less tempting features of the target (Mischel and Baker, 1975), or deploying attention away from the target (Mischel and Ebbesen, 1970; Mischel et al., 1972). Conversely, by controlling visual fixations toward appetitive items, attention has been shown to bias choices for fixated items (Armel et al., 2008; Lim et al., 2011). However, despite the wealth of research in this field, the question of whether inhibition of motor responses over immediately available rewards can be improved by diverting attention away from them has not yet been explored. Moreover the neural correlates of such a phenomenon remain unexamined. Response inhibition has been functionally well-defined in the prefrontal cortex (PFC), particularly the right inferior frontal gyrus (rIFG; Aron, 2011; Tabibnia et al., 2011), although others suggest a more general role for the rIFG (Hampshire and Sharp, 2015). On the other hand, the dorsal striatum is implicated in reward-related motivational and learning processes for goal-directed behavior (Balleine et al., 2007; Padmala and Pessoa, 2010; O’Connor et al., 2012). It is theorized that self-regulatory failure is more likely when a striatal response prevails over a PFC response (Heatherton and Wagner, 2011). For instance, exposure to highly alluring cues (e.g., offered your favorite chocolate) may overwhelm PFC response, or PFC function may be impaired (e.g., due to negative mood; Peters and Büchel, 2011). Is it also possible that, by reducing the saliency of stimuli and related striatal response, the probability of self-regulatory failure can be decreased? Hypoactivity in reward-related neural areas has been accompanied by hypoactivity in neural regions associated with attention during successful response inhibition or craving resistance (Volkow et al., 2010; O’Connor et al., 2012). These regions include the right superior temporal gyrus (rSTG), which has been associated with shifting attention in tasks that involve relative value coding (Hampton et al., 2008; Hare et al., 2010; Lim et al., 2013). We have previously argued that the ability to direct attention away from an alluring stimulus may be an endogenous mechanism that assists inhibitive control over that stimulus when there is a reason to do so (O’Connor et al., 2012). If an individual can direct attention away from a cue, then the prepotency of an alluring stimulus is reduced and inhibition may be easier, requiring less involvement of rIFG than might otherwise be the case (O’Connor et al., 2012). During employment of cognitive control strategies designed to resist cue-induced craving, hypoactivation of visual processing areas was accompanied by either no significant change to rIFG activation (Brody et al., 2007) or rIFG hyperactivity (Volkow et al., 2010). The results may be further evidence that for improved understanding of PFC-related resistance to reward, attentional mechanisms should be taken into account. In this functional magnetic resonance imaging (fMRI) study, we modified a Go/No-go task to investigate whether response inhibition can be enhanced by exogenously diverting attention away from immediately rewarding target stimuli. In addition to standard Go trials requiring a button press response, we also introduced Go-Money trials which, when responded to with sufficient speed, provided immediate feedback for a small monetary reward. A subset of Go-Money trials was visually modified to indicate that participants had to inhibit their standard rapid rewarding responses (No-go trials). A response to No-go trials was considered a failure of response inhibition. Crucially, No-go trials could be accompanied by either a high or low means of diverting attention. This manipulation allowed us to investigate whether diverting attention from an immediately rewarding stimulus improves response inhibition. Processing faces appears to be automatic and mandatory (Farah, 1996; Vuilleumier and Schwartz, 2001; Lavie et al., 2003) and were therefore chosen to exogenously divert attention away from No-go trials. To contrast these high-level attention diversion No-go trials, scrambled faces accompanied the remaining No-go trials. Because scrambled faces do not possess the same attention-capturing characteristics, these served as low-level attention diversion No-go trials. Finally, No-go trials were further manipulated to address another important question. Specifically, if diverting attention away from immediately rewarding stimuli is actually effective in improving response inhibition, is this enhancement only effective if there is a larger potential reward available in the future? To explore this possibility, we compared performance for No-go trials where successful response inhibition would contribute to a larger reward but where no immediate feedback is given, against performance on No-go trials where no such delayed reward contingencies were available. In this way, the paradigm was designed to include a model of real-life circumstances in which abstinence is required over an immediate and tangible reward, in order to obtain a larger, less tangible, future benefit. In parallel with a hypothesized behavioral improvement in response inhibition over immediately rewarding stimuli as a result of attention diversion, we hypothesized modulation of brain regions relevant to cognitive control (PFC), reward (striatum), and attention (STG). Materials and Methods Participants Twenty-six volunteers participated in this study, recruited from the community through advertising. Five participants were excluded from data analyses due to either non-completion of scan (one), excessive head movement during structural scans (three), or identification of anomalous anatomical features (one). Twenty-one healthy volunteers (13 females and eight males; Mage = 24.7 years, SD = 4.9, range = 17.7–33.5) were included in the data analyses. All were right-handed, as determined by the Edinburgh Handedness Inventory (Oldfield, 1971), and reported no current or past history of neurological or psychiatric disorders or psychotropic medication use. All participants, and a parent or guardian for those aged less than 18 years, provided written informed consent and were screened for physical or medical conditions affecting eligibility for magnetic resonance imaging (MRI) scanning. The University of Melbourne Human Ethics Committee approved the study protocol. Participants were compensated $20/h for their participation, plus 5% of the amount earned during the Go/No-go task. The average performance bonus was $34. Go/No-go Task Key Condition Manipulations The modified Go/No-go task consisted of two key condition manipulations (Figure 1). First, we examined the notion that diversion of attention away from an alluring stimulus might facilitate response inhibition by utilizing the assumed attention-grabbing attributes of faces. Second, we utilized a manipulation of delayed reward to test whether the proposed shift in attention away from immediately rewarding targets to aid response inhibition is exclusive to situations in which successful control of impulses yields a future benefit. The task manipulated future reward insofar as for half of the No-go events, successful response inhibition produced no delayed reward. In addition to these key manipulations, we also developed alluring reward-response associations for targets by providing small immediate monetary rewards and feedback for successful Go-Money and unsuccessful No-go trials. FIGURE 1 Examples of the visual stimuli used for the Go/No-go task and experimental manipulations. (A) Examples of target stimuli. No reward was associated with successful response to house (Go) trials, and an immediate one dollar reward was provided for successful response to church or castle (Go-Money) trials. (B) Example of use of lights for target stimuli. No-go trials were defined by whether a church or castle had lights on/off in their windows. (C) Examples illustrate manipulation of attention diversion by using a face and scrambled face in the background as high and low attention diversion, respectively. Successful response inhibition of a castle resulted in a ten-dollar reward, whereas successful response inhibition of a church yielded no reward. For each trial, participants were presented with an image of a building. Two characteristics of the building stimulus determined whether participants should respond (Go trials), respond rapidly for a reward (Go-Money trials) or withhold their response (No-go trials). These characteristics were the building type (house, church, or castle) and whether lights were on or off in the windows of the building. Go trials, represented by houses, always required a response from participants. Neither reward nor performance feedback was provided for Go trials, so the target was not alluring. The second most frequent trials to appear, Go-Money trials, were represented by churches and castles. Upon presentation of Go-Money trials, participants were required to respond rapidly. A rapid response ensured immediate monetary reward feedback of $1 and meant that Go-Money trials were alluring. Finally, the least frequent type of trial, No-go trials, were also represented by churches and castles. This conflation with Go-Money trials was intentional as it meant that associations with immediate reward feedback were held constant and, therefore, No-go trials remained alluring. Indeed, failure to inhibit No-go trials still led to an immediate reward outcome of $1. The only characteristic that differentiated Go-Money trials from No-go trials was whether the windows of the building showed lights to be “on” or “off.” Therefore, depending on instructions at the beginning of the experimental block, participants could respond rapidly to presentation of a church with lights “on” in one trial and then withhold response to presentation of a church with lights “off” in another trial. This conflation and nuanced difference also ensured that participants had to attend fully to each stimulus in order to attain the appropriate behavior. As previously outlined, experimental conditions varied on two factors: (a) high and low attention diversion; and (b) large delayed reward and no delayed reward for successful response inhibition. For (a) high and low attention diversion, stimuli were presented with a background face or scrambled face, respectively. Although we were only interested in the effect of attention diversion on No-go performance, face/scrambled face backgrounds were applied to all trials to ensure that participants could not identify No-go trials simply by the presence of a face or scrambled face. To minimize emotional engagement and possible related interference in amygdalae, a passive face with eyes closed was used. Faces were fitted to an oval frame and placed behind relevant stimuli. For (b) large delayed reward and no delayed reward for successful response inhibition, the concept of a “delayed” or future reward was simulated through the absence of any immediate feedback for successful response inhibition. In this way, the requirement to inhibit a response was not tangibly alluring, as it provided no concrete feedback about reward outcomes. Moreover, both delayed and no delayed reward conditions had the same potent immediate reward association, so that failure to withhold an impulse yielded the previously learned immediate and tangible reward. Instead, participants were simply instructed that for each successful response inhibition of a No-go trial represented by a castle, they would earn a $10 reward, whereas each successful response inhibition of a No-go trial represented by a church would earn no such reward. Therefore, the condition of delayed reward for successful inhibition was modeled to be closest to a real-life situation, including the contingency that failure to abstain yielded some immediate, small reward. That is, abstinence was required over an immediate and tangible reward to obtain a larger, but less tangible, future benefit. Task Design Prior to entering the MRI scanner, participants were given detailed instructions and were fully practiced on the task and its contingencies until they had a good understanding of it. The Go/No-go task consisted of eight blocks of trials with 180 trials per block, and used a ratio of 6:2:1 Go:Go-Money:No-go responses (i.e., 120 Go, 40 Go-Money, and 20 No-go trials per block). In four of the eight blocks, Go-Money trials were defined as churches and castles with their lights “on,” and No-go trials were churches and castles with lights “off.” In the other four blocks, Go-Money trials were churches/castles with lights “off,” and No-go trials were churches/castles with lights “on.” An event-related design permitted presentation of different trials in arbitrary sequences, thus reducing potential for habituation or anticipation (Rosen et al., 1998), and facilitated averaging across specific events. Background attention diversion and target stimuli were counterbalanced across the present experiment such that there were four sequences in total. No-go trials were pseudo-randomly interspersed throughout the Go and Go-Money trials. The stimulus was presented for 750 ms, followed by a 1000 ms interstimulus interval, and then a 500 ms fixation cross. For Go-Money and No-go trials, the fixation cross was preceded by a feedback screen for 750 ms. In terms of feedback, a tick (√) or cross (X) was used to signify whether a response was correct or incorrect, respectively. Successful Go-Money trials, necessitated that response be within a time window of 100–400 ms. A response faster than 100 ms indicated high likelihood that the response preceded visual processing of the target (Macknik and Livingstone, 1998), and the 400 ms threshold was set to facilitate a spontaneous response. For Go-Money trials, participants received immediate feedback comprising a tick and one dollar reward for successful trials (√ $1.00) or that their response either took longer than 400 ms (Slow X $0.00), or was faster than 100 ms (Fast X $0.00). Successful withholding of a response to the castle yielded a tick and a 10-dollar reward although no feedback on amount earned for delayed reward was provided until the end of session. Failed inhibition of No-go trials resulted in immediate reward of one dollar (“X $1.00”). There was neither feedback nor reward for House trials. An example of a typical sequence is shown in Figure 2. This portion of the task was approximately 60 min in duration. FIGURE 2 Example of a typical sequence of the Go/No-go task. In this example, participants were instructed to withhold their response when a “castle” and “church” had lights “off” in their windows. The first target was a house, which required a “Go” response at all times. No reward or performance feedback was provided for the house and so the target was not alluring. The following two figures were a church and castle with lights “on,” and both required a “Go” response. Each stimulus was presented for 750 ms, followed by a 1000 ms interstimulus interval, and then a 500 ms fixation cross. For Go-Money and No-go trials, the fixation cross was preceded by a feedback screen for 750 ms. A successful response provided immediate one dollar reward and feedback, and a response that was either too slow (>400 ms) or too fast (<100 ms) earned no reward although feedback was provided. The images were alluring because of the immediate one dollar reward. The fourth image was a castle with lights off, and therefore, response was to be withheld. Successful inhibition to the castle yielded a tick and a 10-dollar reward (or no reward for a church). No feedback was provided on monetary amount for delayed reward until the end of the session. Failed inhibition of castle or church resulted in a cross to signify the response was incorrect and immediate reward of one dollar. To mitigate possible “reversal learning” effects from the light on/off manipulation between blocks of Go/No-go trials, each block was preceded by a “Go task” which required participants to respond to all (Go-Money and Go) targets, within 100–400 ms. Each inter-block Go task was approximately 1 min in duration, and contained all stimuli in random order, with each target presented for 750 ms, followed by a feedback screen for 750 ms for Go-Money trials, and then a fixation cross for 500 ms. For Go-Money trials, participants received immediate feedback comprising a tick and one dollar reward for successful trials (√ $1.00) or that their response either took longer than 400 ms (Slow X $0.00), or was faster than 100 ms (Fast X $0.00). There was neither feedback nor reward for House trials. Apparatus Visual stimuli were presented using E-Prime software (version 2.0, Psychology Software Tools, Pittsburgh, PA, USA) on a laptop PC (Intel 2 Ghz, 256 mb Nvidia Video Card) that was interfaced with the magnetic resonance scanner during fMRI data acquisition. Stimuli were projected onto a screen located near the feet of the participant, who viewed the screen via a mirror attached to a 32 channel head coil. Behavioral responses were recorded using a scanner-compatible two-button box (Fiber-Optic response pad, Current Designs, Philadelphia, PA, USA). fMRI data were acquired at Swinburne University (Hawthorn, Australia) using a Siemens Tim Trio 3T MRI scanner (Erlangan, Germany). Functional Magnetic Resonance Imaging Data Acquisition Functional magnetic resonance imaging data for the Go/No-go tasks were acquired using 180 (gradient) echo-planar imaging (EPI) sequences which provided T2∗ (time constant for loss of signal in sequence). Weighted BOLD activity measurements were obtained for each functional run with the following parameters: repetition time (TR) = 2 s; echo time (TE) = 36 ms; flip angle (FA) = 90°; 192 mm field of view; and 38 contiguous slices of 4 mm slice thickness. An oblique 30° orientation to the anterior–posterior commissure line was employed in data acquisition. The first two volumes of each run were discarded prior to data analysis to account for transients in the magnetic field of scanner. Eight functional runs were collected for each participant. At the completion of functional neuroimaging, high-resolution structural images were acquired using an MPRAGE T1-weighted sequence [TR = 1900 ms; TE = 2.3 ms, FA = 90, slice thickness = 0.90 mm; in-plane resolution = 1 mm × 1 mm]. During data processing, functional data were overlaid on the structural image for each participant, so that activations could be accurately localized with anatomy. Data Processing and Analysis Go/No-go Data Behavioral data was assessed using E-Prime 2.0 software (Psychology Software Tools, Pittsburgh, PA, USA), IBM® SPSS® Statistics Version 18 (Chicago, IL, USA), and Microsoft Excel (2007). To assess whether attention diversion improved response inhibition, and whether the outcome of the inhibition influenced performance, a two-way repeated measures analysis of variance (with pair-wise comparisons for significant effects) was conducted. The F-statistic was used to determine whether there was a significant difference between means. Confidence intervals were calculated using SPSS and provided additional information regarding the statistical power of each comparison. The dependent variable, mean response inhibition accuracy, was varied by two factors (a) level of attention diversion (High/Low), and (b) future reward (Delayed reward/No delayed reward). Additional secondary analyses were conducted to check for use of cognitive appraisal strategies during response inhibition (e.g., differences in response times between conditions and ensure a minimum level of responding). Functional Magnetic Resonance Imaging Data Functional magnetic resonance imaging data were processed using Analysis of Functional NeuroImages (AFNI) software (Cox, 1996). Following image reconstruction and concatenation of runs, functional data were time-shifted using Fourier interpolation to adjust for difference in slice acquisition times, aligned to corresponding anatomical data, and warped to standard Talairach space. Motion was corrected using three-dimensional volume registration with the third volume from the first run as a base. Volumes were blurred using a 4.1 mm full-width half max filter, each voxel was then scaled to a mean of 100 and values over 200 were clipped. To examine the influence of reward and attention diversion on inhibition performance, an event-related analysis was performed that estimated BOLD activity during correct No-go trials. Hemodynamic response functions were calculated using deconvolution of each successful No-go trial response. Activity related to errors, Go-Money trials, feedback screens and motion, were modeled as additional regressors to avoid contamination of baseline and event-related data. TR pairs were censored when the Euclidian Norm of the motion derivative exceeded 1.0. The baseline estimate was the mean activation recorded during the ongoing trial period (Go trials). Thus, the activation observed during successful No-go trial and Go-Money responses represented activation that differed from that required for the ongoing trial period (or Go) responses. The absence of collinearity between regressors within AFNI X-matrices was confirmed during deconvolution using xmat_tool.py. Event-related map voxels for each regressor of interest were extracted, resampled to anatomical data resolution (1 mm3), and masked using a group-averaged EPI mask dataset. Group activation maps for successful response inhibition were determined with one-sample t-tests against the null hypothesis of zero event-related activation changes (i.e., no change related to baseline). Significant voxels passed (a) a voxelwise statistical threshold (t = 4.84, p ≤ 0.0001), and (b) a continuity threshold – part of a larger 112 μl cluster of contiguous significant voxels. The combination of probability and cluster thresholding maximized the power of the statistical test and minimized the likelihood of false positives. Simulation using the 3D ClustSim function (run within the whole brain) in AFNI and an uncorrected voxelwise threshold p = 0.0001, indicated a minimum cluster size of 112 μl. Activation clusters derived from this whole brain analysis of response inhibition were used to construct activation maps. Whole brain analysis revealed regions of event-related activation during successful No-Go trials. The mean activation for clusters in this map was calculated for the purposes of a functionally derived region of interest (ROI) analysis. ROIs were functionally defined by the No-go > Go contrast. Activation estimates between conditions were compared using two-way repeated-measures ANOVA, post hoc pairwise comparisons tested the effects of our experimental manipulations, and corrected using a modified Bonferroni procedure for multiple comparisons (Keppel, 1991). Results Behavioral Data The effect of attention diversion on mean response inhibition accuracy in delayed reward and no delayed reward trials of the Go/No-go is shown in Figure 3. There was a significant interaction effect between reward and attention diversion condition on inhibition accuracy, F(1,20) = 6.14, p = 0.022, ηp2 = 0.24. For delayed reward trials, mean inhibition accuracy was significantly higher in the high attention diversion condition, M = 050, SD = 0.19, 95% CI [0.41, 0.58], than in the low attention diversion condition, M = 0.46, SD = 0.20, 95% CI [0.37, 0.55], but not significantly different for no delayed reward trials, high attention diversion condition, M = 0.40, SD = 0.21, 95% CI [0.30, 0.50], and low attention diversion condition, M = 0.41, SD = 0.22, 95% CI [0.31, 0.51]. Main effects of delayed reward, F(1,20) = 7.44, p = 0.013, ηp2 = 0.27, and strength of attention diversion, F(1,20) = 0.72, p = 0.406, ηp2 = 0.04, were qualified by the significant interaction effect. In summary, attention diversion assisted response inhibition performance, but only when response inhibition led to future reward. FIGURE 3 Mean response inhibition accuracy by strength of attention diversion and delayed reward conditions. Error bars represent standard error of the mean. n = 21. Attention diversion assisted response inhibition performance, but only when inhibition led to delayed gratification. We also examined whether response inhibition improvements were in part due to trade-offs in Go and Go-Money trial response times (RTs). For alluring Go-Money and non-alluring Go trials (houses), overall mean RTs were faster for high attention diversion (face) and non-alluring stimuli (house) conditions (Table 1). There was no significant interaction effect between reward and attention diversion condition on RTs, F(1,20) = 2.22, p = 0.152, ηp2 = 0.10, and no main effect of strength of attention diversion, F(1,20) = 0.96, p = 0.338, ηp2 = 0.05. The main effect of reward condition was significant, F(1,20) = 10.15, p = 0.005, ηp2 = 0.34. For low attention diversion trials, RTs were significantly faster for Go trials than for Go-Money trials, mean difference = 6.79 ms, p = 0.013, 95% CI [1.60, 11.99], and for high attention diversion trials, RTs were also significantly faster for Go trials than for Go-Money trials, mean difference = 11.55 ms, p = 0.008, 95% CI [3.35, 19.76]. In summary, mean RTs were faster for Go trials than Go-Money trials. In addition, this difference did not vary as a function of attention diversion strength suggesting accuracy data was representative of response inhibition performance. Table 1 Mean response times in milliseconds by stimuli and attention diversion. Condition Mean SD 95% CI Go-Money (Churches and Castles)/Face 381.7 55.1 [356.7, 406.8] Go-Money (Churches and Castles)/Scrambled Face 388.5 54.5 [363.7, 413.3] Go (Houses)/Face 373.7 41.2 [354.9, 392.5] Go (Houses)/Scrambled Face 385.2 42.3 [366.0, 404.5] n = 21. SD, standard deviation; CI, confidence interval.Functional Magnetic Resonance Imaging BOLD Activity Whole brain analysis revealed 20 regions of event-related activation during successful No-go trials (as shown in Table 2). Event-related ROI analysis was, however, restricted to a priori neural areas (STG, rIFG, and striatum) to avoid reverse inferences (as recommended by Kriegeskorte et al., 2009). Previous literature, including our recent work, has shown these nodes to be implicated in shifts of attention during response inhibition (STG; O’Connor et al., 2012; Lim et al., 2013), goal-directed stopping (rIFG; Aron, 2011), and dorsal striatum in reward-related processes for goal-directed behavior (O’Connor et al., 2012). Therefore, subsequent ROI analyses focussed on the activity of these selected clusters, which were identified as functionally relevant. Also, minimizing the number of ROIs reduced the probability of a type I error (Poldrack, 2007). Table 2 Regions of event-related activation during successful No-go trials. Center of Massc Structure HSa Volume (μl)b x y z Insula Rd 1888 32 17 12 Insula Le 2052 -29 16 14 Superior Frontal Gyrus R 1652 13 48 44 Medial Frontal Gyrus∗ R 999 2 4 54 Medial Frontal Gyrus L 906 -2 46 46 Postcentral Gyrus∗ L 864 -49 -19 23 Middle Frontal Gyrus R 133 36 5 58 Middle Frontal Gyrus L 600 -36 4 59 Inferior Frontal Gyrus∗∗ R 352 41 -5 38 Inferior Frontal Gyrus∗ L 550 -41 0 39 Caudate∗ L 524 -14 5 5 Fusiform Gyrus R 615 25 -59 -8 Fusiform Gyrus L 279 -25 -70 -6 Inferior Parietal Lobule R 284 44 -70 44 Posterior Cingulate R 261 1 -56 28 Culmen R 188 12 -69 -2 Cingulate Gyrus∗ L 182 0 -44 42 Superior Temporal Gyrus∗ R 149 59 -37 10 Superior Temporal Gyrus∗∗ L 160 -61 -25 2 Parahippocampal Gyrus R 113 18 -42 8 n = 21. aHS, hemisphere; bμL, microliters. cMontreal Neurological Institute Brain Atlas Anatomical Coordinates. dR, right; eL, left. ∗p < 0.05; ∗∗p < 0.01. Sidak corrected. The following structures had significant main effects for distractor conditions: left inferior frontal gyrus, caudate, and right and left superior temporal gyri. The following structures had significant main effects for delayed-reward conditions: right inferior frontal gyrus, right medial frontal gyrus, left postcentral gyrus, and left cingulate gyrus.Activation maps and percentage BOLD signal change for the STG, left caudate, and rIFG are shown in Figures 4 and 5, and statistical analysis is summarized in Table 3. There was no significant interaction effect between reward and attention diversion condition on any of rSTG, p = 0.135, left STG (lSTG), p = 0.121, left caudate, p = 0.451, or rIFG activation p = 0.428. Although the interaction effects were non-significant, the behavioral data revealed a context specific effect of our attentional manipulation such that high attention diversion only facilitated inhibitory control when paired with the possibility of delayed reward. In order to assess the neural bases of this effect, pairwise comparisons were conducted. The main effect of delayed reward condition was not significant for rSTG activation, p = 0.134, lSTG, p = 0.121, nor left caudate, p = 0.383, but was significant for rIFG activation, p = 0.001. The main effect of attention diversion strength on rIFG activation was not significant, p = 0.377, but was significant for rSTG activation, p = 0.029, lSTG, p < 0.001, and left caudate, p = 0.030. For the rSTG, for delayed reward trials activation was not significantly different between the high and low attention diversion conditions, p = 0.453, but activation was significantly lower in the high attention diversion condition than the low attention diversion condition for no delayed reward trials, p = 0.022. For the lSTG, for no-delayed-reward trials, activation was significantly lower in the high than low attention diversion condition, p = 0.004, and for delayed reward trials, activation was also significantly lower in the high attention diversion condition than the low attention diversion condition, p = 0.012. For the left caudate, activation was not significantly different between attention diversion conditions for delayed reward trials, p = 0.229. For no delayed reward trials, left caudate activation was significantly lower in the high attention diversion condition than the low attention diversion condition, p = 0.029. Table 3 Region of interest analysis statistical summary. Region Test stastic F(1,20) p-valuea Partial eta squared Mean difference [95% CI] Left Superior Temporal Gyrus, coordinatesbxyz, -61 -25 2, volume 160 μl Interaction effect 0.58 0.121 0.12 Main effect for delayed reward 2.63 0.121 0.12 Main effect for strength of attention diversion (AD) 27.14 <0.001 0.58      No delayed reward condition (High less Low AD strength) 0.004 -0.18 [-0.29, -0.06]      Delayed reward condition (High less Low AD strength) 0.012 -0.12 [-0.21, -0.03] Right Superior Temporal Gyrus, coordinatesbx y z, 59-37 10, volume 149 μl Interaction effect 2.42 0.135 0.11 Main effect for delayed reward 2.44 0.134 0.11 Main effect for AD strength 5.55 0.029 0.22      No delayed reward condition (High less Low AD strength) 0.022 -0.95 [-0.17, -0.02]      Delayed reward condition (High less Low AD strength) 0.453 -0.02 [-0.08, 0.04] Left Caudate, coordinatesbx y z,-14 5 5, volume 524 μl Interaction effect 0.59 0.451 0.03 Main effect for delayed reward 0.80 0.383 0.04 Main effect for AD strength 5.43 0.030 0.21      No delayed reward condition (High less Low AD strength) 0.029 -0.07 [-0.14, -0.01]      Delayed reward condition (High less Low AD strength) 0.229 -0.04 [-0.11, 0.03] Right Inferior Frontal Gyrus, coordinatesbx y z, 59-37 10, volume 352 μl Interaction effect 0.66 0.428 0.03 Main effect for delayed reward 0.82 0.377 0.04 Main effect for AD strength 14.21 0.001 0.42      No delayed reward condition (High less Low AD strength) 0.080 0.06 [-0.01, 0.13]      Delayed reward condition (High less Low AD strength) 0.003 0.09 [0.04, 0.15] n = 21. CI, confidence interval. aSidak corrected; bPeak Montreal Neurological Institute Brain Atlas Anatomical Coordinates.FIGURE 4 BOLD signal change in superior temporal gyri during successful response inhibition. (A) Activation maps for left and right superior temporal gyri showing significant activity for successful response inhibition, overlaid on coronal brain sections (Talairach template; using AFNI software), p ≤ 0.0001. (B) Change in BOLD activity plotted by attention diversion and delayed reward conditions. Error bars represent the standard error of the mean. n = 21. FIGURE 5 BOLD signal change in left caudate and right inferior frontal gyrus during successful response inhibition. (A) Activation maps for left caudate and right inferior frontal gyrus showing significant activity for successful response inhibition, overlaid on coronal brain sections (Talairach template; using AFNI software), p ≤ 0.0001. (B) Change in BOLD activity plotted by attention diversion and delayed reward conditions. Error bars represent the standard error of the mean. n = 21. In summary, deactivation of the rSTG was significantly greater for high than low attention diversion condition, but only for no delayed reward trials, and deactivation of the lSTG was significantly greater for the high than low attention diversion condition, for all successful No-go trials. Activation of the left caudate was significantly lower for high than low attention diversion condition, but only for no delayed reward trials, and activation of the rIFG was significantly greater for delayed reward trials than no delayed reward trials, but only for the high attention diversion condition. Discussion In this study, we used exogenous diversions of attention to vary the degree to which participants directed their attention away from alluring stimuli. We found that attention diversion improved response inhibition performance. This finding adds to previous research by providing evidence that response inhibition can be improved by exogenously modulating attention. We also manipulated future benefit in that successful withholding either led to a larger, delayed reward or no delayed reward. Interestingly, we found that attention diversion was only helpful to response inhibition performance, when successful control of impulses ultimately led to a larger, delayed reward. Lack of perceived benefit may, therefore, compromise the application of implicit self-control behaviors. Regions previously implicated in response inhibition and attention showed sensitivity to context-specific manipulations of attention. Specifically, we observed increased recruitment of the posterior rIFG and enhanced response inhibition performance for delayed reward trials compared to no delayed reward trials. Engagement of posterior rIFG has been associated with selective, goal-directed stopping (Chikazoe et al., 2009; Verbruggen et al., 2010; Aron, 2011). rIFG activation did not vary across the attention diversion conditions. However, STG were more de-activated for high attention diversion trials than low. Increased deactivation of STG is interpreted to be indicative of a degree of disengagement from salient (immediately rewarding) stimuli, facilitating successful response inhibition (O’Connor et al., 2012). Shifts of attention away from target stimuli might also be reflected in reduced activity in reward-related neural processes. Our finding of increased deactivation of the left caudate for higher attention diversion trials was consistent with this concept. Dorsal striatal activity has been associated with elevated target saliency (Pizzagalli et al., 2009; Onoda et al., 2011), and computation of relative value between outcomes or in comparison to expected reward (O’Doherty et al., 2004; Balleine and O’Doherty, 2010; Wunderlich et al., 2012). The inference is that the encoding of value potentially informs prefrontal executive processes, consistent with a system that computes value and best action-outcome (Frydman et al., 2011). However, our left caudate results were only significant for the no delayed reward condition and not the delayed reward condition. Other regions, such as the ventral striatum and orbitofrontal cortex, have been consistently linked to reward-related processes (Fitzgerald et al., 2009; Plassmann et al., 2010). Comparison of BOLD activity between reward and attention diversion conditions did not detect any significant change in these regions during successful response inhibition. However, the context for reward in our study is different, which may explain why the conditions do not vary. Our findings may have relevance in a number of health issues where impaired self-control is thought to be factor. Some clinical populations are known to exhibit compromised response inhibition and high reward sensitivity (e.g., addiction, Goldstein and Volkow, 2002; Dackis and O’Brien, 2005). Deficits in using shifts of attention to diffuse target saliency may be critical for the initiation and continuation of self-regulatory lapses (e.g., rumination in residual depression and relapse associated with exposure to conditioned drug-cues in addiction). It would be instructive to understand whether differences in these self-regulatory processes between individuals vary over time (Kane and Engle, 2002; Unsworth and Engle, 2007; Friedman et al., 2008; Casey et al., 2011), are reflected in neural circuitry or functioning of the dopaminergic network (Buckholtz et al., 2010), and amenable to training (Klingberg, 2010). Our findings indicate that perceived lack of future benefit may undermine the application of such implicit self-control behaviors. In public health policy, measures to diffuse target saliency and emphasize future benefit may aid resistance to immediate reward. For instance, plain paper packaging of cigarettes may help reduce cigarette saliency, and extolling the future health benefits of stopping smoking may provide a more tangible delayed reward for smokers. Also, a perception that successful resistance to an immediate reward brings uncertain future benefit may somewhat deplete response inhibition capacity, resulting in more impulsive behavior (Milkman, 2012). The experimental design was a practical way to mimic real-world situations as the MRI scanner environment is highly constrained. However, a caveat is that our laboratory findings may not translate to everyday circumstances. Delay to reward was constrained by the duration of the laboratory session and might not be analogous to real-life delayed reward. The facilitating effect of faces on response inhibition may not generalize to other situations. While it is difficult to determine the authenticity of participants’ efforts to adhere to inhibition instructions or their willingness to engage properly in the exercise, analysis of performance markers (e.g., response times, accuracy, non-response to Go trials) indicated a high level of engagement and diligence. These results indicate that improved response inhibition accuracy on high attention diversion/delayed reward No-go trials cannot be attributed to slower response speed. In addition, people responded more quickly to Go-trials (houses) than Go-Money trials (churches and castles), which was expected given that identification of a single feature (building type for house) was sufficient to respond to the house, compared to two features for churches and castles (building type and lights). Also, high levels of non-response to Go-Money trials would have implied a strategy to maximize No-go gain, and similarly, relatively low accuracy (less than 10%) for No-go trials may have indicated difficulty with the task or a strategy of maximizing immediate rewards. There was, however, no evidence of strategies to maximize immediate or delayed reward. Moreover, block order was counterbalanced throughout the experiment to mitigate possible learning effects, and we used inter-block “Go task” runs to mitigate effects of reversal learning on subsequent blocks and reinforce immediate reward association irrespective of previous contingencies. Future research could extend the present study by utilizing gradational changes to attention diversion (face) stimuli in order to expand understanding of the functional relationship between attention diversion, reward, and response inhibition. The methodology has been used successful in recent research (e.g., Preuschoff et al., 2008), but the high number of events necessary for sufficient power precluded integration of the methodology within the current study. In addition, a modified task comprising of explicitly stated temporal delays with real waiting periods before rewarding successful inhibition performance would lend greater credibility to the suggestion that this type of task represents a fusion of response inhibition (impulsive action) and delay discounting (impulsive choice). This study adds to previous literature of the importance of an attentional mechanism for successful response inhibition of alluring stimuli. In the present experimental paradigm, inhibition appears to be a set of distinct neural processes related to stopping and the ability to implicitly control attention, which might be a target for intervention (training). This study also highlighted the importance of perceived future benefit for these implicit self-regulatory behaviors. Author Contributions DO and FS designed the study, and collected, analyzed, and interpreted the data. FS drafted the manuscript, and DO and RH revised the manuscript. RH, CO, and KM contributed to study design. All authors discussed the results and commented on the manuscript. Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding. The research was supported by the Australian Research Council DP1092852. The authors gratefully acknowledge contributions to data collection by Sarah Rossiter and Kathleen Charles-Walsh, and neuroimage data acquisition by Richard Nibbs. ==== Refs References Armel K. C. Beaumel A. Rangel A. (2008 ). Biasing simple choices by manipulating relative visual attention. Judgm. Decis. Mak. 3 396 –403 . Aron A. R. (2011 ). From reactive to proactive and selective control: developing a richer model for stopping inappropriate responses. Biol. Psychiat. 69 e55 –e68 . 10.1016/j.biopsych.2010.07.024 20932513 Balleine B. W. Delgado M. R. Hikosaka O. (2007 ). The role of the dorsal striatum in reward and decision-making. J. Neurosci. 27 8161 –8165 . 10.1523/JNEUROSCI.1554-07.2007 17670959 Balleine B. W. O’Doherty J. P. (2010 ). Human and rodent homologies in action control: corticostriatal determinants of goal-directed and habitual action. Neuropsychopharmacology 35 48 –69 . 10.1038/npp.2009.131 19776734 Baumeister R. F. Heatherton T. F. (1996 ). Self-regulation failure: an overview. Psychol. Inq. 7 1 –15 . 10.1207/s15327965pli0701_1 Boonstra A. M. Kooij J. J. S. Oosterlaan J. Sergeant J. A. Buitelaar J. K. (2010 ). To act or not to act, that’s the problem: primarily inhibition difficulties in adult ADHD. Neuropsychology 24 209 –221 . 10.1037/a0017670 20230115 Brody A. L. Mandelkern M. A. Olmstead R. E. Jou J. Tiongson E. Allen V. (2007 ). Neural substrates of resisting craving during cigarette cue exposure. Biol. Psychiatry 62 642 –651 . 10.1016/j.biopsych.2006.10.026 17217932 Buckholtz J. W. Treadway M. T. Cowan R. L. Woodward N. D. Li R. Ansari M. S. (2010 ). Dopaminergic network differences in human impulsivity. Science 329 :532 10.1126/science.1185778 Casey B. J. Somerville L. H. Gotlib I. H. Ayduk O. Franklin N. T. Askren M. K. (2011 ). Behavioral and neural correlates of delay of gratification 40 years later. Proc. Natl. Acad. Sci. U.S.A. 108 14998 –15003 . 10.1073/pnas.1108561108 21876169 Chikazoe J. Jimura K. Asari T. Yamashita K. Morimoto H. Hirose S. (2009 ). Functional dissociation in right inferior frontal cortex during performance of Go/No-Go task. Cereb. Cortex 19 146 –152 . 10.1093/cercor/bhn065 18445602 Cox R. W. (1996 ). AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29 162 –173 . 10.1006/cbmr.1996.0014 8812068 Dackis C. O’Brien C. (2005 ). Neurobiology of addiction: treatment and public policy ramifications. Nat. Neurosci. 8 1431 –1436 . 10.1038/nn1105-1431 16251982 Farah M. J. (1996 ). Is face recognition ‘special’? Evidence from neuropsychology. Behav. Brain Res. 76 181 –189 . 10.1016/0166-4328(95)00198-0 8734052 Fillmore M. T. Rush C. R. (2002 ). Impaired inhibitory control of behavior in chronic cocaine users. Drug Alcohol Depend. 66 265 –273 . 10.1016/s0376-8716(01)00206-x 12062461 Fitzgerald T. H. Seymour B. Dolan R. J. (2009 ). The role of human orbitofrontal cortex in value comparison for incommensurable objects. J. Neurosci. 29 8388 –8395 . 10.1523/jneurosci.0717-09.2009 19571129 Friedman N. P. Miyake A. Young S. E. De Fries J. C. Corley R. P. Hewitt J. K. (2008 ). Individual differences in executive functions are almost entirely genetic in origin. J. Exp. Psychol. 137 201 –225 . 10.1037/0096-3445.137.2.201 Frydman C. Barberis N. Camerer C. Bossaerts P. Rangel A. (2011 ). Testing Theories of Investor Behavior Using Neural Data. Working Paper: Caltech. Available at: http://ssrn.com/abstract = 1892338. 10.2139/ssrn.1892338 Goldstein R. Z. Volkow N. D. (2002 ). Drug addiction and its underlying neurobiological basis: neuroimaging evidence for the involvement of the frontal cortex. Am. J. Psychiat. 159 1642 –1652 . 10.1176/appi.ajp.159.10.1642 12359667 Goudriaan A. E. Oosterlaan J. De Beurs E. van den Brink W. (2006 ). Neurocognitive functions in pathological gambling: a comparison with alcohol dependence. Tourette syndrome and normal controls. Addiction 101 534 –547 . 10.1111/j.1360-0443.2006.01380.x 16548933 Hampshire A. Sharp D. J. (2015 ). Contrasting network and modular perspectives on inhibitory control. Trends Cogn. Sci. 19 445 –452 . 10.1016/j.tics.2015.06.006 26160027 Hampton A. N. Bossaerts P. O’Doherty J. P. (2008 ). Neural correlates of mentalizing-related computations during strategic interactions in humans. Proc. Natl. Acad. Sci. U.S.A. 105 6741 –6746 . 10.1073/pnas.0711099105 18427116 Hare T. A. Camerer C. F. Knoepfle D. T. O’Doherty J. P. Rangel A. (2010 ). Value computations in ventral medial prefrontal cortex during charitable decision making incorporate input from regions involved in social cognition. J. Neurosci. 30 583 –590 . 10.1523/jneurosci.4089-09.2010 20071521 Heatherton T. F. Wagner D. D. (2011 ). Cognitive neuroscience of self-regulation failure. Trends Cogn. Sci. 15 132 –139 . 10.1016/j.tics.2010.12.005 21273114 Kane M. J. Engle R. W. (2002 ). The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: an individual-differences perspective. Psychon. B. Rev. 9 637 –671 . 10.3758/bf03196323 Keppel G. (1991 ). Design and Analysis: A Researcher’s Handbook. Upper Saddle River, NJ : Prentice Hall . Klingberg T. (2010 ). Training and plasticity of working memory. Trends Cogn. Sci. 14 317 –324 . 10.1016/j.tics.2010.05.002 20630350 Kriegeskorte N. Simmons W. K. Bellgowan P. S. F. Baker C. I. (2009 ). Circular analysis in systems neuroscience: the dangers of double dipping. Nat. Neurosci. 12 535 –540 . 10.1038/nn.2303 19396166 Lavie N. Ro T. Russell C. (2003 ). The role of perceptual load in processing distractor faces. Psychol. Sci. 14 510 –515 . 10.1111/1467-9280.03453 12930485 Li C. R. Sinha R. (2008 ). Inhibitory control and emotional stress regulation: neuroimaging evidence for frontal-limbic dysfunction in psycho-stimulant addiction. Neurosci. Biobehav. R. 32 581 –597 . 10.1016/j.neubiorev.2007.10.003 Lim S. L. O’Doherty J. P. Rangel A. (2011 ). The decision value computations in the vmPFC and striatum use a relative value code that is guided by visual attention. J. Neurosci. 31 13214 –13223 . 10.1523/JNEUROSCI.1246-11.2011 21917804 Lim S. L. O’Doherty J. P. Rangel A. (2013 ). Stimulus value signals in ventromedial PFC reflect the integration of attribute value signals computed in fusiform gyrus and posterior superior temporal gyrus. J. Neurosci. 33 8729 –8741 . 10.1523/jneurosci.4809-12.2013 23678116 Macknik S. L. Livingstone M. S. (1998 ). Neuronal correlates of visibility and invisibility in the primate visual system. Nat. Neurosci. 1 144 –149 . 10.1038/393 10195130 Milkman K. L. (2012 ). Unsure what the future will bring? You may overindulge: uncertainty increases the appeal of wants over shoulds. Organ. Behav. Hum. Dec. 119 163 –176 . 10.1016/j.obhdp.2012.07.003 Mischel W. Baker N. (1975 ). Cognitive appraisals and transformations in delay behavior. J. Pers. Soc. Psychol. 31 254 –261 . 10.1037/h0076272 Mischel W. Ebbesen E. B. (1970 ). Attention in delay of gratification. J. Pers. Soc. Psychol. 16 329 –337 . 10.1037/h0029815 Mischel W. Ebbesen E. B. Raskoff Zeiss A. (1972 ). Cognitive and attentional mechanisms in delay of gratification. J. Pers. Soc. Psychol. 21 204 –218 . 10.1037/h0032198 5010404 Mischel W. Shoda Y. Peake P. K. (1988 ). The nature of adolescent competencies predicted by preschool delay of gratification. J. Pers. Soc. Psychol. 54 687 –696 . 10.1037/0022-3514.54.4.687 3367285 Monterosso J. R. Aron A. R. Cordova X. Xu J. London E. D. (2005 ). Deficits in response inhibition associated with chronic methamphetamine abuse. Drug Alcohol Depend. 79 273 –277 . 10.1016/j.drugalcdep.2005.02.002 15967595 Ochsner K. N. Gross J. J. (2005 ). The cognitive control of emotion. Trends Cogn. Sci. 9 242 –249 . 10.1016/j.tics.2005.03.010 15866151 O’Connor D. A. Rossiter S. Yücel M. Lubman D. I. Hester R. (2012 ). Successful inhibitory control over an immediate reward is associated with attentional disengagement in visual processing areas. NeuroImage 62 1841 –1847 . 10.1016/j.neuroimage.2012.05.040 22641143 O’Doherty J. P. Dayan P. Schultz J. Deichmann R. Friston K. Dolan R. J. (2004 ). Dissociable roles of ventral and dorsal striatum in instrumental conditioning. Science 304 452 –454 . 10.1126/science.1094285 15087550 Oldfield R. C. (1971 ). The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9 97 –113 . 10.1016/0028-3932(71)90067-4 5146491 Onoda K. Okamoto Y. Kunisato Y. Aoyama S. Shishida K. Okada G. (2011 ). Inter-individual discount factor differences in reward prediction are topographically associated with caudate activation. Exp. Brain Res. 212 593 –601 . 10.1007/s00221-011-2771-3 21695536 Padmala S. Pessoa L. (2010 ). Interactions between cognition and motivation during response inhibition. Neuropsychologia 48 558 –565 . 10.1016/j.neuropsychologia.2009.10.017 19879281 Penadés R. Catalán R. Rubia K. Andrés S. Salamero M. Gastó C. (2007 ). Impaired response inhibition in obsessive compulsive disorder. Eur. Psychiat. 22 404 –410 . 10.1016/j.eurpsy.2006.05.001 Peters J. Büchel C. (2011 ). The neural mechanisms of inter-temporal decision-making: understanding variability. Trends Cogn. Sci. 15 227 –239 . 10.1016/j.tics.2011.03.002 21497544 Pizzagalli D. A. Holmes A. J. Dillon D. G. Goetz E. L. Birk J. L. Ryan Bogdan A. M. (2009 ). Reduced caudate and nucleus accumbens response to rewards in unmedicated individuals with major depressive disorder. Am. J. Psychiat. 166 702 –710 . 10.1176/appi.ajp.2008.08081201 19411368 Plassmann H. O’Doherty J. Rangel A. (2010 ). Appetitive and aversive goal values are encoded in the medial orbitofrontal cortex at the time of decision making. J. Neurosci. 30 10799 –10808 . 10.1523/jneurosci.0788-10.2010 20702709 Poldrack R. A. (2007 ). Region of interest analysis for fMRI. Soc. Cogn. Affect. Neur. 2 67 –70 . 10.1093/scan/nsm006 Preuschoff K. Quartz S. R. Bossaerts P. (2008 ). Human insula activation reflects risk prediction errors as well as risk. J. Neurosci. 28 2745 –2752 . 10.1523/JNEUROSCI.4286-07.2008 18337404 Rosen B. R. Buckner R. L. Dale A. M. (1998 ). Event-related functional MRI: past, present, and future. Proc. Natl. Acad. Sci. U.S.A. 95 773 –780 . 10.1073/pnas.95.3.773 9448240 Tabibnia G. Monterosso J. R. Baicy K. Aron A. R. Poldrack R. A. Chakrapani S. (2011 ). Different forms of self-control share a neurocognitive substrate. J. Neurosci. 31 4805 –4810 . 10.1523/jneurosci.2859-10.2011 21451018 Unsworth N. Engle R. W. (2007 ). The nature of individual differences in working memory capacity: active maintenance in primary memory and controlled search from secondary memory. Psychol. Rev. 114 104 –132 . 10.1037/0033-295x.114.1.104 17227183 Verbruggen F. Aron A. R. Stevens M. A. Chambers C. D. (2010 ). Theta burst stimulation dissociates attention and action updating in human inferior frontal cortex. Proc. Natl. Acad. Sci. U.S.A. 107 13966 –13971 . 10.1073/pnas.1001957107 20631303 Volkow N. D. Fowler J. S. Wang G. J. Telang F. Logan J. Jayne M. (2010 ). Cognitive control of drug craving inhibits brain reward regions in cocaine abusers. NeuroImage 49 2536 –2543 . 10.1016/j.neuroimage.2009.10.068 19913102 Vuilleumier P. Schwartz S. (2001 ). Emotional facial expressions capture attention. Neurology 56 153 –158 . 10.1212/wnl.56.2.153 11160948 Wunderlich K. Dayan P. Dolan R. J. (2012 ). Mapping value based planning and extensively trained choice in the human brain. Nat. Neurosci. 15 786 –791 . 10.1038/nn.3068 22406551

PMC005xxxxxx/PMC5000577.txt

==== Front ParasiteParasiteparasiteParasite1252-607X1776-1042EDP Sciences 10.1051/parasite/2016034parasite16001710.1051/parasite/2016034Research ArticleDistribution of Plasmodium species on the island of Grande Comore on the basis of DNA extracted from rapid diagnostic tests La distribution des espèces de Plasmodium dans l’île de Grande Comore, à partir de l’ADN extrait des tests de diagnostic rapide Papa Mze Nasserdine 1*Ahouidi Ambroise D. 1Diedhiou Cyrille K. 1Silai Rahamatou 2Diallo Mouhamadou 1Ndiaye Daouda 3Sembene Mbacké 4Mboup Souleymane 11 Laboratory of Bacteriology-Virology, Hospital Aristide le Dantec Dakar BP 7325 Senegal 2 Laboratory of National Malaria Control Program Moroni Comoros 3 Laboratory of Parasitology and Mycology, Faculty of Medicine and Pharmacy, Cheikh Anta Diop University BP 5005 Dakar Senegal 4 Faculty of Science and Technology, Department of Animal Biology, Cheikh Anta Diop University Dakar Senegal * Corresponding author: npapamze@gmail.com2016 26 8 2016 23 parasite/2016/013401 3 2016 23 7 2016 © N. Papa Mze et al., published by EDP Sciences, 20162016N. Papa Mze et al.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In the Union of Comoros, interventions for combating malaria have contributed to a spectacular decrease in the prevalence of the disease. We studied the current distribution of Plasmodium species on the island of Grande Comore using nested PCR. The rapid diagnostic tests (RDTs) currently used in the Comoros are able to identify Plasmodium falciparum but no other Plasmodium species. In this study, we tested 211 RDTs (158 positive and 53 negative). Among the 158 positive RDTs, 22 were positive for HRP2, 3 were positive only for pLDH, and 133 were positive for HRP2 and pLDH. DNA was extracted from a proximal part of the nitrocellulose membrane of RDTs. A total of 159 samples were positive by nested PCR. Of those, 156 (98.11%) were positive for P. falciparum, 2 (1.25%) were positive for P. vivaxI, and 1 (0.62%) was positive for P. malariae. None of the samples were positive for P. ovale. Our results show that P. falciparum is still the most dominant species on the island of Grande Comore, but P. vivax and P. malariae are present at a low prevalence. Dans l’Union des Comores, des interventions pour la lutte contre le paludisme ont contribué à une diminution spectaculaire de la prévalence de la maladie. Nous avons étudié la répartition actuelle des espèces de Plasmodium sur l’île de Grande Comore par PCR imbriquée. Les tests de diagnostic rapide (TDRs) actuellement utilisés aux Comores sont en mesure d’identifier Plasmodium falciparum, mais pas d’autres espèces de Plasmodium. Dans cette étude, nous avons testé 211 TDRs (158 positifs et 53 négatifs). Parmi les 158 TDRs positifs, 22 étaient positifs pour HRP2, 3 étaient positifs seulement pour pLDH et 133 étaient positifs pour à HRP2 et pLDH. L’ADN a été extrait d’une partie proximale de la membrane de nitrocellulose des TDRs. Au total, 159 échantillons étaient positifs par PCR nichée. Parmi eux, 156 (98,11 %) étaient positifs pour P. falciparum, 2 (1,25 %) étaient positifs pour P. vivax et 1 (0,62 %) était positif pour P. malariae. Aucun des échantillons n’était positif pour P. ovale. Nos résultats montrent que P. falciparum est toujours l’espèce dominante dans l’île de Grande Comore, mais P. vivax et P. malariae sont présents à une faible prévalence. Plasmodium speciesRDTNested PCRMalariaComoros ==== Body Introduction Malaria is a disease caused by a parasite that belongs to the genus Plasmodium. It is responsible for about 627,000 deaths worldwide annually with about 90% occurring in sub-Saharan Africa [19]. In the Union of Comoros (consisting of three islands: Grande Comore, Moheli and Anjouan), located in the Indian Ocean between Madagascar and the African coast, malaria is one of the major public health concerns, with Plasmodium falciparum being the most prevalent species in this region [17]. Therefore, three major strategies were implemented in 2004, comprising the use of insecticide-treated bed nets, introduction of Intermittent Preventive Treatment (IPT) in pregnant women, and the treatment of patients with artemisinin-based combination therapy. These strategies have resulted in a significant decrease in malaria transmission. The prevalence of malaria among pregnant women decreased from 30.4% to 8% between 2004 and 2008, and the hospital case fatality rate among children under 5 years dropped from 0.36% to 0.12% between 2005 and 2008 (PNLP 2004–2009, unpublished data). This decline allowed the National Malaria Control Program to bring into focus strategies for malaria eradication in the Union of Comoros, which was introduced for the first time in 2007 on Moheli Island. The population of the island was given mass drug administration using Artequick® (artemisinin-piperaquine) and primaquine. The program was later introduced in 2012 on the island of Anjouan and in late 2013 on Grande Comore. The results are encouraging: no deaths were recorded in the first quarter of 2014 (PNLP 2014, unpublished data). The significant decrease of malaria may also induce a change in the distribution of Plasmodium species in the Union of Comoros. For better treatment and intervention for malaria elimination, it is necessary to know the current distribution of Plasmodium species. This will also enable us to assess the existing approach against malaria in the Union of Comoros. A study on the distribution of Plasmodium species by microscopy conducted in the Union of Comoros showed that P. falciparum is the most prevalent species [17]. Microscopy analysis remains the standard method for the diagnosis of malaria. However, it requires expertise particularly when the parasitemia is low but also in case of mixed infections [20]. In developing countries, microscopists are not sufficiently trained and this can lead to misidentification of the Plasmodium species [9]. The use of PCR methods can help to fill this gap. The study’s goal was to reassess the distribution of the Plasmodium species using rapid diagnostic tests (RDTs) DNA by PCR, in areas where malaria is hypoendemic (Moroni), mesoendemic (Mitsamiouli), and meso to hyperendemic (Mbeni) [16] (PNLP 2004–2009, unpublished data). Materials and methods Study population Positive and negative rapid diagnostic tests (RDTs) performed in febrile patients (Malaria pLDH/HRP2 Combo: Access Bio, PBX-KM30003 and SD Bioline Malaria Ag Pf/Pan: SD Bioline, 05FK60) for malaria diagnosis were collected in Grande Comore, at the National Malaria Control Program in the capital city Moroni and at two hospitals of two regions of Grande Comore: Mitsamiouli and Mbeni from 2012 to 2013. These RDTs detect the presence of both the HRP2 protein, specific to P. falciparum, and the pLDH protein, common to P. falciparum and the other three species: Plasmodium malariae, Plasmodium vivax, and Plasmodium ovale. Only the RDTs with a valid control band were included in this study. Two hundred eleven RDTs were used, including 158 positive RDTs (14 for the kit SD Bioline Malaria Ag Pf/Pan Malaria and 144 pLDH/HRP2 Combo kit), and 53 negative RDTs (all done with the Combo Kit). Among the 158 positive samples, 22 were positive only for HRP2, 133 were positive for HRP2 and pLDH, and 3 were positive only for pLDH. Among the positive ones, 29 came from Moroni, 52 from Mitsamiouli, and 77 from Mbeni. DNA extraction Parasite DNA was extracted from RDTs using a proximal part of the nitrocellulose membrane (1/3 NC) as previously described by Cnops et al. [6]. DNA was extracted with the QIAamp DNA Mini kit (Qiagen) according to the manufacturer’s recommendations for filter paper. DNA amplification Species-specific Plasmodium identification nested PCR was performed using the following primers [18]: 5′-CCT GTT GTT GCC TTA AAC TTC-3′, and 5′-TTA AAA TTG TTG CAG TTA AAA-3′. PCR was carried out using the following conditions: Initial 4-min denaturation at 94 °C followed by 35 cycles with 30-s at 94 °C, 1-min at 55 °C, and 4-min final extension at 72 °C. 1 μL of the nest-1 amplification products was used as DNA template for the nest-2 amplification. The following primers specific to each species were used for the nest-2 PCR: 5′-TTA AAC TGG TTT GGG AAA ACC AAA TAT ATT-3′, 5′-ACA CAA TGA ACT CAA TCA TGA CTA CCC GTC-3′ for P. falciparum, 5′-CGC TTC TAG CTT AAT CCA CAT AAC TGA TAG-3′, 5′-ACT TCC AAG CCG AAG CAA AGA AAG TCC TTA-3′ for P. vivax, 5′-ATA ACA TAG TTG TAC GTT AAG AAT AAC CGC-3′, 5′-AAA ATT CCC ATG CAT AAA AAA TTA TAC AAA-3′ for P. malariae, and 5′-GGA AAA GGA CAC ATT AAT TGT ATC CTA GTG-3′, 5′-ATC TCT TTT GCT ATT TTT TAG TAT TGG AGA-3′ for P. ovale. PCR was carried out using the following conditions: Initial 4-min denaturation at 94 °C followed by 35 cycles with 30-s at 94 °C, 1-min at 58 °C, and 4-min final extension at 72 °C. PCR products were analyzed on 2% agarose gel. The size of DNA bands obtained was analyzed by GeneRuler 100 bp DNA ladder marker (Quick Load®, 100pb Ladder DNA). Statistical analysis The data were analyzed by EpiTools software (Z-test to compare sample proportion). The p-value was determined and the threshold of significance was estimated at 0.05 for all statistical tests. Results In this study, 211 RDTs (158 positive and 53 negative) were successfully tested by nested PCR. Among the 158 positive RDTs, 2 (1.3%) were found negative by PCR; and among the 53 negative RDTs, 3 (5.7%) showed positive results for P. falciparum by PCR. Among the 159 positive RDTs by nested PCR, 156 were positive for P. falciparum (98.11%), 2 for P. vivax (1.25%), and 1 for P. malariae (0.62%). All samples were negative for P. ovale. No mixed infections were identified. Among 22 RDTs that presented a positive result for HRP2, 20 were positive for P. falciparum by PCR and 2 were negative for all species. On the other hand, 133 RDTs that had a positive band for P. falciparum (HRP2 positive) or both P. falciparum and non-P. falciparum (HRP2 and pLDH positive) were P. falciparum positive by PCR. Among the 3 positive RDTs for the detection of pLDH, two were positive by PCR for P. vivax and one for P. malariae. In the capital Moroni, 25 samples were positive for P. falciparum, 1 sample was positive for P. vivax, and 1 sample was positive for P. malariae. In Mbeni, 76 samples were positive for P. falciparum and 1 sample was positive for P. vivax. In Mitsamiouli, all species were positive for P. falciparum (Table 1). Table 1. The distribution of Plasmodium species in the three regions of the island of Grande Comore Sites Moroni Mitsamiouli Mbeni Endemicity Hypoendemic Mesoendemic Meso to hyperendemic Total n = 27 n = 55 n = 77 P. falciparum 25 (92.6%) 55 (100%) 76 (98.7%) 156 P. vivax 1 (3.7%) 0 1 (1.3%) 2 P. malariae 1 (3.7%) 0 0 1 P. ovale 0 0 0 0 We investigated whether there was an association between the distribution of species and the endemicity using the Z-test. A significant difference was found for the prevalence of P. falciparum between Moroni and Mitsamiouli (p = 0.041) and between Moroni and Mbeni (p = 0.0345), whereas no difference was observed between Mitsamiouli and Mbeni (p = 0.84). Concerning the prevalence of P. vivax, a significant difference was found between Moroni and Mbeni (p < 0.0001). Discussion To contribute to malaria elimination in the Comoros, we evaluated the current distribution of Plasmodium species using DNA extracted from RDTs. In this study, nested PCR was used to determine the Plasmodium species, because current RDTs used in the Comoros can specify only P. falciparum; microscopy requires more expertise and can be less sensitive [7]. Two RDTs that were found to be positive for P. falciparum were negative by PCR. These false positive results could be due mostly to the persistence of HRP2 in recently cured P. falciparum infected patients [1, 14], but also to the presence of auto-antibodies [10] or anti-rheumatic factors [3, 12]. Three samples were negative by RDTs, but were positive for P. falciparum by PCR. These false negative results could be due to low parasitemia [13] or HRP2 deletion in some isolates of P. falciparum [11]. Another explanation could be the presence of anti-antibodies in serum to HRP2 [5], or the presence of an inhibitor in the blood, preventing the occurrence of the P. falciparum control band [8]. Therefore, in these three cases only the HRP2 band should be present. The false negative results for P. falciparum found in this study were also found in previous studies using the Malaria pLDH/HRP2 Combo test [4, 21]. However, we did not obtain false negatives for species other than P. falciparum, unlike previous studies [4, 21], perhaps because the negative RDTs used in our study were moderate in number. It is therefore important to better monitor false positives and false negatives for better calculation of the prevalence of malaria. Misidentification of the Plasmodium agent can delay malaria treatment and may also lead to complications or increase the risk of antimalarial resistance [2]. A total of 133 RDTs had a positive band for P. falciparum and a positive band for Plasmodium spp. This result suggests that these samples could be positive for only P. falciparum, or they could be mixed Plasmodium species infections (P. falciparum plus other species). However after PCR, we found that all RDTs were positive only for P. falciparum. This result confirms that the presence of mixed species is not common in the Comoros [15, 17]. We also determined the Plasmodium species distribution by PCR and have shown a prevalence of 98.11%, 1.3%, and 0.6%, respectively, for P. falciparum, P. vivax, and P. malariae. However, Ouledi in 1995 found prevalence rates of 90% for P. falciparum, 8% for P. malariae, and 1.5% for P. vivax [15]. A significant decrease of the prevalence of P. malariae (p = 0.010) and a significant increase of the prevalence of P. falciparum (p = 0.0172) have been found between our results and the results reported by Ouledi. A study conducted in 2011 [17] found a prevalence of 96% for P. falciparum, 2% for P. malaria, and 1.5% for P. vivax. For this study, no significant difference was observed for the prevalence of P. falciparum (p = 0.3802), P. vivax (p = 0.879), and P. malariae (p = 0.309). We found that the prevalence of P. falciparum in Mitsamiouli and Mbeni was higher than in Moroni. This difference can be explained by the fact that Mitsamiouli and Mbeni are areas where malaria is mesoendemic and meso to hyperendemic, respectively, while in Moroni malaria is hypoendemic. P. ovale was not found in this study, whereas in the previous results it was observed at a prevalence of 0.5% [15, 17]. The absence of P. ovale species may be explained by the fact that in this study, we collected samples only from Grande Comore, whereas the two previous studies were carried out on the three islands of the Union of Comoros. The presence of non-P. falciparum species in our study and previous studies is important information to use for malaria diagnosis on the island. These results show that it is important to regularly monitor the prevalence of the different Plasmodium species using more sensitive tools such as PCR in the Comoros Islands. Conclusion This study, which determined the prevalence of Plasmodium species using PCR performed from DNA extracted from RDTs, confirms the strong predominance of P. falciparum in the Comoros. The use of more sensitive tools such as PCR, with a large number of samples for the detection of Plasmodium species on the Comoros Islands, will provide more information for malaria elimination on the islands. Conflict of interest The authors declare no conflict of interest in relation with this paper. We thank the sample collection team in Comoros (Fazul A, M.A. Maamoune, Mohamed A). We also thank Guillaume A.B, Iguosadolo Nosamiefan, Baba Dieye, Dior Diop, Abdoulay AH, Gora Diop, Kevin Ma, and Benedicta Mensah for critical reading of the manuscript. Cite this article as: Papa Mze N, Ahouidi AD, Diedhiou CK, Silai R, Diallo M, Ndiaye D, Sembene M & Mboup S: Distribution of Plasmodium species on the island of Grande Comore on the basis of DNA extracted from rapid diagnostic tests. Parasite, 2016, 23, 34. ==== Refs 1 Abba K , Deeks JJ , Olliaro P , Naing CM , Jackson SM , Takwoingi Y , Donegan S , Garner P . 2011 Rapid diagnostic tests for diagnosing uncomplicated P. falciparum malaria in endemic countries . Cochrane Database of Systematic Reviews , CD008122 . 2 Ayalew F , Tilahun B , Taye B . 2014 Performance evaluation of laboratory professionals on malaria microscopy in Hawassa Town, Southern Ethiopia . BioMed Central Research Notes , 7 , 839 .25422030 3 Bartoloni A , Sabatinelli G , Benucci M . 1998 Performance of two rapid tests for Plasmodium falciparum malaria in patients with rheumatoid factors . New England Journal of Medicine , 338 , 1075 .9537883 4 Bharti PK , Silawat N , Singh PP , Singh MP , Shukla M , Chand G , Dash AP , Singh N . 2008 The usefulness of a new rapid diagnostic test, the First Response Malaria Combo (pLDH/HRP2) card test, for malaria diagnosis in the forested belt of central . Malaria Journal , 7 , 126 .18620560 5 Biswas S , Tomar D , Rao DN . 2005 Investigation of the kinetics of histidine-rich protein 2 and of the antibody responses to this antigen, in a group of malaria patients from India . Annals of Tropical Medicine and Parasitology , 99 , 553 –562 .16156968 6 Cnops L , Boderie M , Gillet P , Van Esbroeck M , Jacobs J . 2011 Rapid diagnostic tests as a source of DNA for Plasmodium species-specific real-time PCR . Malaria Journal , 10 , 67 .21435256 7 Doctor SM , Liu Y , Whitesell A , Thwai KL , Taylor SM , Janko M , Emch M , Kashamuka M , Muwonga J , Tshefu A , Meshnick SR . 2016 Malaria surveillance in the Democratic Republic of the Congo: comparison of microscopy, PCR, and rapid diagnostic test . Diagnostic Microbiology and Infectious Disease , 85 (1 ), 16 –18 .26915637 8 Durand F , Faure O , Brion JP , Pelloux H . 2005 Invalid result of Plasmodium falciparum malaria detection with the Binax-NOW Malaria rapid diagnostic test . Journal of Medical Microbiology , 54 , 1115 .16192446 9 Gomes LT , Tada MS , Katsuragawa TH , Povoa MM , Viana GM , Alecrim M , De Santana-Filho FS , Arcanjo AR , Couto AA , Calvosa VS , Nery AF , Fontes CJ . 2013 Low sensitivity of malaria rapid diagnostic tests stored at room temperature in the Brazilian Amazon Region . Journal of Infection in Developing Countries , 7 , 243 –252 .23493003 10 Iqbal J , Sher A , Rab A . 2000 A Plasmodium falciparum histidine-rich protein 2-based immunocapture diagnostic assay for malaria: cross-reactivity with rheumatoid factors . Journal of Clinical Microbiology , 38 , 1184 –1186 .10699018 11 Koita OA , Doumbo OK , Ouattara A , Tall LK , Konare A , Diakite M , Diallo M , Sagara I , Masinde GL , Doumbo SN , Dolo A , Tounkara A , Traoré I , Krogstad DJ . 2012 False-negative rapid diagnostic tests for malaria and deletion of the histidine-rich repeat region of the hrp2 gene . American Journal of Tropical Medicine and Hygiene , 86 , 194 –198 .22302847 12 Laferl H , Kandel K , Pichler H . 1997 False positive dipstick test for malaria . New England Journal of Medicine , 337 , 1635 –1636 . 13 Murray CK , Bell D , Gasser RA , Wongsrichanalai C . 2003 Rapid diagnostic testing for malaria . Tropical Medicine & International Health , 8 , 876 –883 .14516298 14 Murray CK , Gasser RA , Magill AJ , Miller RS . 2008 Update on rapid diagnostic testing for malaria . Clinical Microbiology Reviews , 21 , 97 –110 .18202438 15 Ouledi A . 1995 Épidémiologie et prévention du paludisme dans les îles du sud-ouest de l’Océan Indien . Santé , 5 , 368 –371 .8784541 16 Rebaudet S , Bogreau H , Silaï R , Lepere JF , Bertaux L , Pradines B , Delmont J , Gautret P , Parola P , Rogier C . 2010 Genetic structure of Plasmodium falciparum and elimination of Malaria, Comoros Archipelago . Emerging Infectious Diseases Journal , 16 , 1686 –1694 . 17 Revue de la Performance du Paludisme (RPP) dans l’Union des Comores, rapport 2011 Available from: https://extranet.who.int/evaluationregistry/EvaluationView.aspx?id=37 18 Singh B , Bobogare A , Cox-Singh J , Snounou G , Abdullah MS , Rahman HA . 1999 A genus- and species-specific nested polymerase chain reaction malaria detection assay for epidemiologic studies . American Journal of Tropical Medicine and Hygiene , 60 , 687 –692 .10348249 19 WHO . 2013 World Malaria Report . Geneva : World Health Organization Retrieved from http://www.who.int/malaria/publications/world_malaria_report_2013/ 20 World Health Organization . 2009 WHO Malaria Rapid Diagnostic Test Performance – Results of WHO Product Testing of Malaria RDTs: Round 2 . Retrieved from www.who.int/malaria/publications/atoz/9789241599467/en/index.html 21 Xiaodong S , Tambo E , Chun W , Zhibin C , Yan D , Jian W , Jiazhi W , Xiaonong Z . 2013 Diagnostic performance of CareStart malaria HRP2/pLDH (Pf/pan) combo test versus standard microscopy on falciparum and vivax malaria between China-Myanmar endemic borders . Malaria Journal , 12 , 6 .23294729

PMC005xxxxxx/PMC5000580.txt

==== Front Front PsycholFront PsycholFront. Psychol.Frontiers in Psychology1664-1078Frontiers Media S.A. 10.3389/fpsyg.2016.01197PsychologyOriginal ResearchExecutive Functions in Children Who Experience Bullying Situations Medeiros Wandersonia 1Torro-Alves Nelson 2*Malloy-Diniz Leandro F. 3Minervino Carla M. 41Laboratory of Cognitive Sciences and Perception-Laboratory of Mental Health, Education and Psychometric, Universidade Federal da ParaíbaParaíba, Brazil2Postgraduate Program in Cognitive Neuroscience and Behaviour, Laboratory of Cognitive Sciences and Perception, Universidade Federal da ParaíbaParaíba, Brazil3ILUMINA Neurosciences, LINC-INCT, Universidade Federal de Minas GeraisBelo Horizonte, Brazil4Postgraduate Program in Cognitive Neuroscience and Behaviour, Laboratory of Mental Health, Education and Psychometric, Universidade Federal da ParaíbaParaíba, BrazilEdited by: Amitai Abramovitch, Texas State University, USA Reviewed by: Eyal Kalanthroff, Ben-Gurion University of the Negev, Israel; Joseph Mcguire, Semel Institute for Neuroscience and Human Behavior, UCLA, USA *Correspondence: Nelson Torro-Alves, nelsontorro@yahoo.com.brThis article was submitted to Psychopathology, a section of the journal Frontiers in Psychology 26 8 2016 2016 7 119721 4 2016 28 7 2016 Copyright © 2016 Medeiros, Torro-Alves, Malloy-Diniz and Minervino.2016Medeiros, Torro-Alves, Malloy-Diniz and MinervinoThis is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Bullying is characterized by intentional, repetitive, and persistent aggressive behavior that causes damage to the victim. Many studies investigate the social and emotional aspects related to bullying, but few assess the cognitive aspects it involves. Studies with aggressive individuals indicate impairment in executive functioning and decision-making. The objective of this study was to assess hot and cold executive functions in children who experience bullying. A total of 60 children between 10 and 11 years of age were included in the study. They were divided into four groups: aggressors (bullies), victims, bully-victims, and control. Tests for decision-making, inhibitory control, working memory, and cognitive flexibility were used. The bully group made more unfavorable choices on the Iowa Gambling Task, which may indicate difficulties in the decision-making process. The victim group took longer to complete the Trail Making Test (Part B) than aggressors, suggesting lower cognitive flexibility in victims. The hypothesis that aggressors would have lower performance in other executive functions such as inhibitory control, working memory, and cognitive flexibility has not been confirmed. This study indicates that bullies have an impairment of hot executive functions whereas victims have a comparatively lower performance in cold executive functions. In addition to social and cultural variables, neurocognitive and emotional factors seem to influence the behavior of children in bullying situations. bullyingdecision-makingexecutive functionaggressive behaviorcognitive flexibility ==== Body Introduction The word bullying is used to characterize intentional repetitive and persistent aggressive behavior toward a victim (Olweus, 1994). There is an uneven power relationship between the aggressor and the victim in bullying due to differences in age, physique, or strength. This difference sustains the behavior of the bully even despite clear signs of discomfort and displeasure on the part of those suffering from it (Smith, 2002). Bullying aggression can occur by direct physical contact (kicking, punching, pushing, theft, or damage to the victim’s objects), psychological aggression (verbal abuse involving nicknames, insults, or mean comments about race, sexuality, religion, and physical features) or indirectly (excluding the victim from playing or group conversations) (Bullock, 2002). In a bullying situation, children can take on different roles. Aggressing children (bullies) have the intention of causing harm or excluding others (Berger, 2007). Children that are victims suffer from the constant aggression and often fail to react or get others to stop. Children considered victims-aggressors are those that bully/offend but also suffer aggression, and they differ from aggressors because they are not as popular and usually replicate the aggression with a more fragile child (Bandeira and Hutz, 2012). Bystanders are those children who are not directly involved in the aggression but those who witness bullying. Bystander often do not know how to behave in the face of aggression and become silent for fear of becoming victims, or for not trusting the actions taken by school professionals (Lopes Neto, 2005; Miranda, 2011). The prevalence of bullying seems to vary depending on the sociocultural context. For example, Berger (2007) reviewed the prevalence of bullying in different countries and found a range between 3 and 27% of bullies and between 9 and 32% of victims. However, methodological differences and the definition of bullying itself make it difficult to establish epidemiological comparisons. Understanding the psychological processes involved in the onset and maintenance of a bullying relationship involves clarifying the cognitive and personality factors of bullies and victims. Koh and Wong (2015) argue that the psychological traits of the aggressors reflect potential adaptive advantages related to sexual selection. However, there is evidence that cognitive deficits and certain personality traits are most frequently found in children and adolescents who bully (Medeiros et al., 2014). Children who are bullies and bully-victims show more frequent antisocial behavior and lower levels of empathy compared to victims and children who do not experience bullying (Camodeca and Goossens, 2005; Gery et al., 2009; Viding et al., 2011). They also have lower academic performance, an increased school drop-out rate, and higher involvement with the justice system (Gini, 2006). Coolidge et al. (2004) observe that bullying behavior is associated with deficits in executive functioning, conduct disorders, oppositional-defiant disorder, attention deficit hyperactivity disorders (ADHDs), and increased use of substances such as alcohol and marijuana. Regarding executive functions, Diamond (2013) believes that these functions involve three main centers: inhibitory control, working memory, and cognitive flexibility. According to the author, the other functions such as reasoning, planning and organization are built from these three functions. Currently, some authors have distinguished executive functions into cold and hot. Cool executive functions are related to cognitive/rational high-order process and are used to general cognitive control. Hot executive functions, in turn, are cognitive/emotional processes related to affective decision making, motivation, and social cognition. According to Damásio (1996), decision-making processes are related to the interpretation of body states and emotional bias defined as somatic markers. The process of somatic markers interpretation is important both to risk perception and decision considering immediate and future outcomes. Antisocial behavior has been associated to impairment in somatic marker processing (Damásio et al., 1996; Séguin, 2004; Sinclair and Gansler, 2006; Tung and Chhabra, 2011). Despites the knowledge of social rules, antisocial subjects present rule-breaking behaviors due to the lack of interpretation of these emotional-somatic signals. Verlinden et al. (2014) found that children who are not involved in bullying situations as bullies or victims have better scores on intelligence tests. Bullies, victims, and bully-victims have greater difficulty with inhibitory control according to the reports of their parents in the BRIEF Scale. This result suggests a probable deficit in executive functioning related to involvement in bullying situations. Such results, however, have certain limitations. Verlinden et al. (2014) use indirect measures of executive functioning in questionnaires that assess parents’ perceptions of such cognitive processes. Cognitive-emotional aspects of executive functions are poorly investigated in studies on bullying, however, they are particularly important in regulating behavior in social situations (Smith and Jones, 2012). Affective decision-making seems to be related to the presence of various psychopathological conditions such as ADHD; autism spectrum disorders, substance abuse such as alcohol and/or cigarettes; conduct disorders; schizophrenia, as well as behavioral problems such as high disinhibition, self-harm, and aggressive behavior (Best et al., 2002; Ernst et al., 2003, 2010; Verdejo-García et al., 2006; Suhr and Tsanadis, 2007; DeVito et al., 2008; Fairchild et al., 2009; Herrera, 2011; Mata et al., 2011; Sallum et al., 2013). Bullies often have alterations in behavior, therefore, the possibility that decision-making may also be impaired in these individuals cannot be ruled out. In view of the likely involvement of executive functioning in different behavioral patterns related to bullying, the objective of this study was to evaluate the different components of these functions in groups of bullies, victims, bully-victims, and a control group. As a hypothesis, we consider that bullies, victims and bully-victims child groups would achieve lower scores on the evaluation of executive functions than the group that has no direct involvement with bullying. Another hypothesis was that the group of aggressors and victims-aggressors would demonstrate lower performance on inhibitory control and decision-making in comparison to victims and controls. Materials and Methods Sample Initially, the Peer Aggression and Victimization Scale (PAVS) was applied to 225 students of the 6th grade of two public schools and a private school. After the exclusion of children who did not fit in the pre-established age group, the scales and the free informed consent form were delivered to parents. Children were recruited according to the results of the PAVS scale. Children were excluded if they were 12 years or older (as they would be at a different phase of development, in this case in adolescence), with complaints of uncorrected visual or hearing difficulties and/or those with compromising cognitive impairment. Thirty-nine children completed the individual steps, however, they were not included in data analysis because their parents did not deliver the Strengths and Difficulties Questionnaire. The sample comprised 60 children (32 females and 28 males), with age between 10 to 11 years and attending sixth grade in middle school. A total of 34 children attended private schools and 26 attended public schools in João Pessoa. Instruments Strengths and Difficulties Questionnaire – SDQ (Goodman, 1997) The instrument used to characterize the sample was the Strengths and Difficulties Questionnaire- SDQ, developed by Goodman (1997) and validated for the Brazilian context by Fleitlich et al. (2000). It is a screening questionnaire that aims to assess mental health of children and adolescents (4–16 years). It has 25 items, divided into five subscales: emotional symptoms, conduct problems, hyperactivity, relationship problems with peers and prosocial behavior. A total index of difficulty which is the sum of the subscales (except sociability) is also generated. The instrument can be used in three versions (self-reporting, a version for parents and a version for teachers). In the present study, we used the version for parents. Each item has three alternatives, false (zero), more or less true (one point) and true (two points). Bullying Evaluation: Peer Aggression and Victimization Scale (PAVS; Cunha et al., 2009) The PAVS is a self-reported, 18-item scale, applicable to students attending the second half of elementary school (in general, children from 10 to 15 years of age), that investigates behaviors of bullying and victimization among peers. The child selects the frequency (never, rarely, sometimes, very often, or always) with which they performed or suffered a certain behavior at school during the previous 6 months. The answers were added separately according to the following classification: direct aggression, relational aggression, indirect physical aggression, and victimization. This study did not investigate “indirect physical aggression.” From the sum of the scores in each class, participants were divided into subgroups according to the cutoff points (Cunha et al., 2009). The scale was used to classify participants into groups of bullies, victims, and bully-victims, in addition to a control group, by using the following criteria: (a) Bully group – This group comprises children with a high frequency of behavior in the direct aggression items (score ≥ 9) and low (score ≤ 12) or moderate (score ≤ 16) behavior in the victimization items. Children with high scores only in the relational aggression items were not included. (b) Victim group – This group comprises children with a high frequency of victimization behavior (score ≥ 16) and a low level of direct physical aggression (score ≤ 7) and relational aggression (score ≤ 6). (c) Bully-victim group – This group comprises children with a high frequency of direct aggressive behavior (score ≥ 9) and victimization (score ≥ 16). Children with a high score in victimization and high scores only in relational aggression were not included. (d) Control group – This group comprises children with a low frequency of direct aggressive behavior (score ≤ 7) and victimization with a low (score ≤ 12) or moderate (score < 16) frequency. Evaluation of Executive Functioning The protocol for the analysis of cold executive functions used the model proposed by Diamond (2013). In this model, three main cores are part of executive functioning: inhibitory control, working memory, and cognitive flexibility. These three functions give rise to the other functions, such as reasoning, planning, and organization. The following instruments were used. Digit Span Backward (DSB) Subtest (Wechsler, 2013) A subtest of the Wechsler Intelligence Scale for Children (WISC-IV), the DSB evaluates working memory. For this task, the professional applying the test reads some numbers aloud, and the child must repeat them in descending order. The tables for 10 and 11 years of age were used to transform the raw scores into weighted scores. Trail Making Test Part B (TMT-B) The TMT has two parts: A and B. This study used only part B, which evaluates alternating attention and mental flexibility. The child was instructed to connect the numbers in ascending order and in alphabetical order. The execution time of the activity was considered to determine the score. When there was an error, the evaluator showed it to the participant and requested correction, which increased the execution time. Victoria Stroop Color-Word Test The Stroop Test was used to assess attention and inhibitory control. The Victoria version includes three cards, 1 (color), 2 (word), and 3 (color-word). The first card (color) contains colored rectangles with the colors pink, green, blue, and brown, which must be named by the child as quickly as possible. The second card (word) lists the words EACH, TODAY, NEVER, and EVERYTHING, printed in the same colors, and the child is asked to simply read the words as quickly as possible. The third card (color-word) lists the names of the four colors, printed in colors that are incompatible with the written word (e.g., the word “Blue” is printed in pink). The child is asked not to read the names but instead to name the printed colors as quickly as possible. For the assessment, the execution time for each card and the number of mistakes (errors not spontaneously corrected by the child) were taken into account (Kulaif, 2005). For the assessment of the “hot” executive functions, the test of affective decision-making described below was used. Iowa Gambling Task (IGT; Bechara et al., 1994) The Brazilian version of the IGT, adapted by Malloy-Diniz et al. (2008), was used to evaluate hot executive functions as a test of emotional decision-making. In this task, participants aim to achieve the maximum gain from an initial cash loan. Individuals make 100 selections of cards, not knowing in advance how many are allowed, and they must make decisions that lead to a final positive result according to the feedback that they receive. Card decks A and B initially offer an advantage, but in the long term, they become unfavorable. Decks C and D offer an overall advantage because, although they have a lower value of rewards, the punishments are also smaller, ultimately resulting in a higher overall gain. In this study, to increase the chances that the test evaluated hot executive functions, a reward (candy) was included, according to the following criteria: • Gains of 25, 50, and 75 (frequent in advantageous decks): receives one piece of candy; • Losses of 25, 50, and 75 (frequent in advantageous decks): loses one piece of candy; • Gains ≥ 100 (frequent in disadvantageous decks): receives two pieces of candy; • Losses ≥ 100 (frequent in disadvantageous decks): loses two pieces of candy; and • Losses = 1500 (only in disadvantageous decks): loses all candy. Procedures After approval by the school and parents by means of agreement documents and free and informed consent forms, the groups were determined by applying the PAVS. For the individual step, tests for the assessment of executive functioning were applied in an isolated room arranged by the school. The professional applying the test was with the child throughout task execution to answer questions and prevent mistakes due to confusion. The study was approved by the Research Ethics Committee of the University Hospital Lauro Wanderley (Hospital Universitário Lauro Wanderley), UFPB (CAAE process: 17883413.5.0000.5183). All procedures were performed according to Regulation 466/96 of the National Health Council (Conselho Nacional de Saúde – CNS). Participation was voluntary, and the participants were informed in advance that they could withdraw their consent at any time during the study. Statistical Analysis The softwares SPSS 21.0 and Microsoft Office Excel 2007 were used for the tabulation of data and statistical analysis. The Shapiro–Wilk test and Levene’s test showed that data did not present normal distribution and equality of variances (homoscedasticity), respectively. For this reason, non-parametric testing was selected. The Kruskal–Wallis test was used for comparisons between groups using a significance level of 0.05. When Kruskal–Wallis test was inferior to 0.05, we performed Mann–Whitney pairwise comparisons. In order to control the probability of Type I error, we corrected the critical value of alfa by dividing the familywise error rate (0.05) by the number of comparisons (6). Therefore, we considered as statistically significant only the probabilities values inferior to 0.0083. In addition, we determined effect sizes estimates (Fritz et al., 2012; Field, 2013). As proposed by Cohen (1988), effect sizes were calculated using the formula: r=zN⁢                               (1) where r is the effect size estimate, z is the standard score of the distribution, and N is the total of the sample size. According to Cohen’s guidelines used to interpret r, a large effect is superior to 0.5, a medium effect is 0.3 and a small effect is 0.1. Large effect sizes associated to non-significant results may suggest to carry out a research with a greater power, whereas small effect sizes associated to significant results may indicate that the observed effects are not so robust (Fritz et al., 2012). Results With regard to socio demographic characteristics, a total of 32 out of the 60 children who participated in the sample were female, and 28 were male, with 34 attending private schools and 26 attending public schools in João Pessoa, Paraíba, Brazil. The participants were divided into four groups according to their result on the PAVS scale: bullies (n = 15; seven male), victims (n = 15; six male), bully-victims (n = 15; nine male), and control (n = 15; six male). A preliminary statistical analysis showed no differences between genders with regard to the variables investigated in the study (p > 0.05). Table 1 shows the average score of the four groups in the dimensions of the PAVS scale. In Table 2, we present data of the four groups of participants and results of the statistical analysis. Table 1 Means and standard deviations of age and scores in the PAVS scale dimensions in the four groups of participants. Variable Bully Victim Bully-Victim Control Age 10.73 (0.45) 10.87 (0.35) 10.80 (0.41) 10,73 (0.45) Relacional aggression 8.20 (4.29) 5.93 (1.62) 8.53 (3.29) 4.87 (1.12) Direct aggression 11.73 (2.01) 6.47 (0.91) 12.67 (1.71) 6.40 (1.18) Victimization 13.33 (2.19) 20.73 (4.90) 23.73 (5.78) 11.07 (2.05) Table 2 Statistical analysis and scores obtained by the four groups of participants in the Strengths and Difficulties Questionnaire (SDQ), Digit Span Backward Subtest (DSB), Trail Making Test part B (TMT-B), Victoria Stroop Color-Word Test (STROOP), Iowa Gambling Task (IGT). Instrument Bully Victim Bully-Victim Control Kruskal–Wallis SDQ Emotional symptoms 3.53 (2.26) 5.80 (3.07) 3.27 (2.86) 4.00 (2.77) p = 0.086 Conduct problems 3.07 (2.65) 1.87 (1.80) 2.73 (1.43) 2.27 (1.62) p = 0.472 Hyperactivity 4.60 (3.26) 3.53 (2.10) 4.33 (1.91) 3.93 (2.89) p = 0.780 Peer relationship Problems 1.53 (1.72) 2.67 (1.63) 2.47 (2.56) 1.20 (1.01) p = 0.074 Prosocial behavior 7.07 (2.40) 9.27 (0.96) 7.87 (1.59) 8.33 (1.54) p = 0.010ˆ* Total difficulties 12.80 (8.24) 14.07 (7.16) 12.80 (6.71) 11.40 (5.27) p = 0.780 DSB 9.33 (2.52) 9.53 (2.35) 9.93 (1.94) 8.73 (2.12) p = 0.460 TMT-B 40.27 (10.27) 61.40 (17.31) 48.60 (12.43) 48.20 (11.91) p = 0.003ˆ* STROOP Color (Time) 16.00 (0.92) 19.13 (0.89) 18.58 (1.21) 17.80 (1.03) p = 0.126 Color (Errors) 0.00 (0.00) 0.07 (0.26) 0.00 (0.00) 0.13 (0.352) p = 0.284 Word (Time) 11.27 (3.41) 12.40 (2.41) 12.26 (2.68) 12.67 (2.58) p = 0.205 Word (Errors) 0.07 (0.26) 0.00 (0.00) 0.13 (0.51) 0.07 (0.26) p = 0.792 Color-word (Time) 27.47 (1.68) 34.20 (3.25) 35.21 (2.76) 30.40 (1.84) p = 0.018ˆ* Color-word (Errors) 0.40 (0.63) 0.27 (0.59) 0.47 (1.12) 0.60 (1.24) p = 0.869 IGT Deck A choices 25.15 (0.74) 22.60 (1.29) 20.79 (0.96) 21.07 (1.26) p = 0.039ˆ* Deck B choices 27.33 (1.55) 27.53 (1.29) 30.13 (1.60) 29.47 (1.57) p = 0.286 Deck C choices 25.00 (1.17) 25.00 (0.99) 26.47 (1.04) 24.53 (0.66) p = 0.325 Deck D choices 24.00 (1.82) 24.87 (1.94) 21.73 (1.37) 24.93 (1.57) p = 0.566 General Trend Block 1 (1–20) -0.93 (0.64) -1.47 (0.74) -1.47 (0.90) -1.07 (0.54) p = 0.971 General trend block 2 (21–40) -1.20 (0.95) -0.40 (1.58) -3.07 (1.53) -1.47 (0.71) p = 0.859 General trend block 3 (41–60) -0.27 (0.67) 1.47 (1.75) -2.00 (1.08) 1.07 (1.40) p = 0.697 General trend block 4 (61–80) -0.13 (1.50) -0.93 (1.24) 0.80 (1.59) -0.67 (1.11) p = 0.640 General trend block 5 (81–100) 0.53 (0.95) 1.07 (0.93) 2.13 (1.38) 1.07 (1.18) p = 0.995 General trend -2.00 (3.20) -0.27 (3.95) -3.60 (3.48) -1.07 (3.03) p = 0.881 Values correspond to means and standard deviations.Strengths and Difficulties Questionnaire – SDQ We found no differences between groups with regard to the total score of difficulties (χ2 = 1.088, p = 0.780), emotional problems (χ2 = 6.585, p = 0.086), hyperactivity (χ2 = 1.087, p = 0.780), conduct problems (χ2 = 2.517, p = 0.472) and peer relationship problems (χ2 = 6.920, p = 0.740). In the prosocial behavior subscale, we found differences between groups (χ2 = 11.347, p = 0.01). Mann–Whitney tests showed that victims presented higher scores than bullies (U = 33.00, z = -3.217, p = 0.001, r = -0.59), but not in comparison to the control group (U = 73.5, z = -1.703; p = 0.089, r = -0.31) and bully-victims (U = 54.5, z = -2.495; p = 0.013, r = -0.46). Bullies, bully-victims and controls had similar scores in prosocial behavior compared one another. Digit Span Backward (DSB) Subtest There was no significant difference between the groups with regard to DSB (χ2 = 2.587, p = 0.46), indicating that they had similar patterns of performance in working memory. Trail Making Test Part B (TMT-B) Statistical analysis showed significant differences between groups in TMT-B (χ2 = 13.839, p = 0.003). Mann–Whitney tests showed that the victim group had a longer execution time in TMT-B compared to bullies (U = 32.5, z = -3.322; p = 0.001, r = -0.61), but not differed from bully-victims (U = 65, z = -1.972, p = 0.049, r = -0.36), and controls (U = 62.5, z = -2.075, p = 0.038, r = -0.38). This result indicates a lower cognitive flexibility in the victim group. The other groups did not differ one another: aggressors compared to bully-victims (U = 66, z = -1.932, p = 0.053, r = -0.35); bullies compared to controls (U = 66, z = -1.93, p = 0.054, r = -0.35); bully-victims compared to controls (U = 109.5, z = -0.125, p = 0.901, r = -0.02; Figure 1). FIGURE 1 Time, in seconds, on the Trail Making Test Part B (TMT-B). ∗Significant difference for the victim group compared to the bully group (p = 0.001). Stroop Color-Word Test The Kruskal–Wallis test showed significant differences between groups only for the third card (color-word; χ2 = 10,039, p = 0.018). Mann–Whitney tests showed that the bully group had a shorter execution time compared to the victim (U = 35, z = -2.736, p = 0.006, r = -0.50) and bully-victim groups (U = 31, z = -2.754, p = 0.006, r = -0.50), but not differed from control group (U = 52, z = -2.109, p = 0.035, r = -0.39; Figure 2). In the third card, we found no differences between victims compared to bully-victims (U = 87, z = -0.195, p = 0.846, r = 0.04); victims compared to controls (U = 93, z = -0.525, p = 0.600, r = 0.10); bully-victims compared to controls (U = 83, z = -0.669, p = 0.503, r = 0.12). For the first card (color), we found no statistically significant differences between groups (χ2 = 5.718; p = 0.126), but victims presented longer execution time than other groups. We find no differences between groups with regard to Stroop word (time; χ2 = 4.587, p = 0.205), Stroop color (errors; χ2 = 3.795, p = 0.284), Stroop word (errors; χ2 = 1.037, p = 0.792), and Stroop color-word (errors; χ2 = 0.718, p = 0.869) (Figure 2). FIGURE 2 Time, in seconds, on the Stroop Color-Word Test. ∗Significant difference for the bully group compared to victim (p = 0.006) and bully-victim (p = 0.006). Iowa Gambling Task – IGT The Kruskal–Wallis test showed significant differences between groups only for choices from Deck A (χ2 = 8,393, p = 0.039). Mann–Whitney tests showed that the bully group had the highest score considering all choices from Deck A compared to the bully-victim group (U = 34.5 z = -2.755, p = 0.006, r = 0.50), but not differed from victims (U = 61.5 z = -1.666, p = 0.96, r = 0.30) and the control group (U = 49, z = -2.246, p = 0.025, r = 0.41). Other groups had a similar number of choices of cards in Deck A: victims compared to bully-victims (U = 82, z = -1.006, p = 0.314, r = 0.18); victims compared to controls (U = 94, z = -0.771, p = 0.440, r = 0.14); bully-victims compared to controls (U = 99.50, z = -0.241, p = 0.810, r = 0.04). There was no significant differences between the groups with regard to the general score trends in blocks (χ2 = 0.241, p = 0.971 in Block 1; χ2 = 0.758, p = 0.859 in Block 2; χ2 = 1.435, p = 0.697 in Block 3; χ2 = 1.685, p = 0.640 in Block 4, and χ2 = 0.096, p = 0.995 in Block 5) and the overall general trend (χ2 = 0.668, p = 0.881). There was also no difference between the total number of choices from Decks B (χ2 = 3.780, p = 0.286), C (χ2 = 3.466, p = 0.325), and D (χ2 = 2.031, p = 0.566) (Figure 3). FIGURE 3 Average of choices from decks A, B, C, and D on the Iowa Gambling Task (IGT). ∗Significant difference for the bully group compared to the bully-victim group in Deck A (p = 0.006). Discussion In this study, executive functioning (inhibitory control, working memory, and cognitive flexibility) and emotional decision-making were assessed in children who experience bullying. This study is innovative because it investigates multiple components of executive functioning and their relationship to bullying. We used the Strengths and Difficulties Questionnaire – SDQ (parent version) to characterize chid behavior. In the SDQ, offending children (bullies) did not differ from other groups with regard to the symptoms of hyperactivity and behavior problems, contradicting the results of Coolidge et al. (2004), which found a higher prevalence of challenging behavior, conduct problems and ADHD in offending children compared to the control group. Therefore, it is clear that aggressors of this sample did not differ from controls with respect to behavior problems, probably due to this group presenting many children who also had average levels of victimization. Viding et al. (2011) claim that not all behavior problems are due to the same cause, so it is important to investigate the profile of each group. The group of victims obtained the highest score of prosocial behavior, related to behaviors of empathy (helping others, being nice, and caring for younger children) than the group of bullies. However, there were no differences between victims compared to controls and bully-victims. Deficits in executive functioning have been reported in several developmental and behavioral disorders (Lezak, 1982; Hamdan and Pereira, 2009). In this study, there was no significant difference between groups with regard to working memory, assessed by DSB Subtest. With regard to working memory, Best et al. (2002) found no differences between patients with aggressive and impulsive behavior compared to controls. Nevertheless, they observed that the clinical group showed impairment in the decision-making process. Contrary to expectations, there was no deficit in inhibitory control functions and cognitive flexibility in bullies, as assessed by the Stroop test and TMT-B, respectively. The bully group had a shorter execution time on the TMT-B compared to the victims group and the third Stroop card (color-word) compared to the victims and bully-victims groups and not presented more errors. Brennan (2002) found no association between high levels of juvenile delinquency and poor performance in the executive function assessment tasks. However, our results are different from those reported by other authors who observed inhibitory control difficulties in aggressive individuals (Best et al., 2002; Ellis et al., 2009). Verlinden et al. (2014) found a relationship between low inhibitory control and involvement in bullying, whether in the bully, victim or bully-victim roles. Nevertheless, the authors used an indirect assessment with questionnaires directed to parents, which may explain the difference between the results. Compared to bullies, the victim group had a longer TMT-B execution time, indicating less efficient performance in the context of cognitive flexibility. Although not statistically significant, we found medium effect sizes to the comparisons between victims and bully-victims (r = 0.36) and between victims and controls (r = 0.38), what indicates a reduction in cognitive flexibility in victims compared to those groups. This result is consistent with those found by Dertelmann (2011), who found lower performance in cognitive flexibility tests and working memory in child victims of abuse (Dertelmann, 2011). Brennan (2002) found that children who had suffered abuse and higher delinquency levels had lower scores on the assessment of executive functioning. This result shows that the presence of victimization is a factor that may be associated with deficits in the development of cognitive impairment. Other studies also show worse performance in tasks that assess executive functioning in individuals who have suffered physical or sexual assaults (Stein et al., 2002; Coolidge et al., 2004). The association between deficits in executive functioning and vulnerability to aggression can be explained as a consequence of exposure to violence, but it can also be understood as a factor of vulnerability to such acts. The different types of victimization investigated and the lack of longitudinal studies do not allow us to safely determine whether impairment in executive functioning is a result of aggression, whether it is associated with psychiatric disorders developed due to aggression (anxiety disorders, post-traumatic stress disorder), or whether it is part of the cognitive and personality features of these individuals, which may predispose them to suffer aggression (Stein et al., 2002). According to Teicher et al. (2003), exposure to violence or severe stress in childhood, depending on its severity and intensity, can cause neurobiological changes and affect brain development. For example, Johnson (2012) suggests that the presence of deficits in executive functioning since childhood can make individuals less efficient in problem solving and, therefore, less resilient in adverse situations. In this study, compared with the bully-victim group, children in the bully group choose more cards from one of the disadvantageous decks (Deck A). Decks A and B are considered disadvantageous because they cause losses over the long term of task execution compared to decks C and D. Although deck B is also unfavorable, Deck A has the highest frequency of punishments but is lower in intensity (Singh, 2013). We found no statistically significant differences between bullies and controls in IGT, however, the effect size obtained in the comparison (0.41) indicates that groups might differ each other in studies involving a greater sample, with bullies choosing more disadvantageous cards. This finding suggests that bullies are more sensitive to the intensity of punishment than they are to the frequency of punishment. The choice for one of the unfavorable decks by bullies indicates a preference for immediate gains (two pieces of candy), ignoring punishment and the future consequences of the choice. Such behavior has been designated “myopia for the future” (Bechara et al., 1994, 2002; Gomes et al., 2011). With regard to “myopia for the future,” the following analogy can be made for a situation experienced at school: a child can choose between advantageous attitudes (not attacking), which generate long-term gains (e.g., being aware of doing the right thing, building lasting and true friendships), and unfavorable behavior (aggression), which brings immediate gains (a sense of power, entertaining peers, being popular) but generate losses in the long run (complaints, punishment by parents, poor school performance, and shallow friendships). In this sense, it is possible to consider that the practice of bullying in the school context may be associated with a decrease in the decision-making process of bullies. Decision-making deficits are clearly found in children and adolescents with behavioral disorders, conduct disorders and in patients who suffered injuries to the orbitofrontal cortex (Best et al., 2002; Ernst et al., 2003; Fairchild et al., 2009). Bully-victims present similarities and differences with regard to both groups of victims and bullies. In the IGT, bully-victims were similar to controls and victims, but choose more advantage cards as compared to bullies. In SQD, bully-victims presented scores of prosocial behavior more similar to bullies than victims. A possible explanation is that the decreasing of prosocial behavior in bully-victims may be related to the dissemination of the aggression suffered. For Bandeira and Hutz (2010), bully-victims children are more likely to present depressive symptoms, anxiety, and externalizing behaviors, and unlike children in the bullies group, they are not popular but rather rejected by their peers. The results of this study can be analyzed by considering the dichotomy proposed by Kerr and Zelazo (2004). These authors suggest the existence of hot (more closely related to motivation and emotional control) and cold (more closely related to logical-rational aspects of cognition) executive functions. If, on one hand, victims have experienced greater difficulties in tasks that require cold executive functions, then bullies have impaired “hot” executive functions. This study includes certain limitations, such as the sample size and the fact that some children in the bully group have shown moderate levels of victimization. Another limitation of the study is the use of a self-reported scale, which can generate interference in the division of the groups, although this problem was minimized by the application of the ICU scale in children and parents. It should also be considered that the methodology used was transversal and causal inferences about the investigated aspects cannot be made. We suggest that future studies be conducted with larger samples, longitudinal studies and different cultures. In addition to sociocultural variables, this study shows that executive functioning, including decision-making, can also play a relevant role in bullying behavior. This type of study may lead to the development of customized intervention strategies according to the profile of students in each school because not all behavioral issues are due to the same cause and not every victim responds to aggression in the same manner (Viding et al., 2011). Author Contributions Conceived and designed the experiments: WM, NT-A, and CM. Performed the experiments: WM. Analyzed the data: WM, NT-A, and CM. Contributed with materials and analysis tools: WM, NT-A, CM, and LM-D. Wrote the paper: WM, NT-A, CM, and LM-D. Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. ==== Refs References Bandeira C. M. Hutz C. S. (2010 ). As implicações do bullying na auto-estima de adolescentes. Psicol. Esc. Educ. 14 131 –138 . 10.1590/S1413-85572010000100014 Bandeira C. D. M. Hutz C. S. (2012 ). Bullying: prevalence, implications and gender differences. Psicol. Esc. Educ. 16 35 –44 . 10.1590/S1413-85572012000100004 Bechara A. Damásio A. R. Damásio H. Anderson S. W. (1994 ). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition 50 7 –15 . 10.1016/0010-0277(94)90018-3 8039375 Bechara A. Dolan S. Hindes A. (2002 ). Decision-making and addiction (part II): myopia for the future or hypersensitivity to reward? Neuropsychologia 40 1690 –1705 . 10.1016/S0028-3932(02)00016-7 11992657 Berger K. S. (2007 ). Update on bullying at school: science forgotten? Dev. Rev. 27 90 –126 . 10.1016/j.dr.2006.08.002 Best M. Williams J. M. Coccaro E. F. (2002 ). Evidence for a dysfunctional prefrontal circuit in patients with an impulsive aggressive disorder. Proc. Natl. Acad. Sci. U.S.A. 99 8448 –8453 . 10.1073/pnas.112604099 12034876 Brennan S. G. C. (2002 ). The Relationship between Maltreatment in Childhood and Delinquency: An Examination of IQ and Executive Functions. Palo Alto, CA : Pacific Graduate School of Psychology . Bullock J. (2002 ). Bullying Among Children. Child. Educ. 78 130 –133 . 10.1080/00094056.2002.10522721 Camodeca M. Goossens F. A. (2005 ). Aggression, social cognitions, anger and sadness in bullies and victims. J. Child Psychol. Psychiatry 46 186 –197 . 10.1111/j.1469-7610.2004.00347.x 15679527 Cohen J. (1988 ). Statistical Power Analysis for the Behavioral Sciences, 2nd Edn. Hillsdale, NJ : Lawrence Earlbaum Associates . Coolidge F. L. DenBoer J. W. Segal D. L. (2004 ). Personality and neuropsychological correlates of bullying behavior. Pers. Individ. Dif. 36 1559 –1569 . 10.1016/j.paid.2003.06.005 Cunha J. M. Weber L. N. D. Steiner Neto P. (2009 ). “Escala de vitimização e agressão entre pares (EVAP) ,” in Pesquisando em Família - Instrumentos Para Coleta e Análise de Dados , eds Weber L. Dessen M. A. (Curitiba : Juá Editora ), 108 –120 . Damásio A. (1996 ). O erro de Descartes: Emoção, Razão e o Cérebro Humano. São Paulo : Companhia das Letras . Damásio A. R. Everitt B. J. Bishop D. (1996 ). The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philos. Trans. R. Soc. Lond. B Biol. Sci. 351 1413 –1420 . 10.1098/rstb.1996.0125 8941953 Dertelmann C. D. F. V. (2011 ). Avaliação Neuropsicológica em Crianças Vítimas de Maus-Tratos , Dissertação de mestrado, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre . DeVito E. E. Blackwell A. D. Kent L. Ersche K. D. Clark L. Salmond C. H. (2008 ). The effects of methylphenidate on decision making in attention-deficit/hyperactivity disorder. Biol. Psychiatry 64 636 –639 . 10.1016/j.biopsych.2008.04.017 18504036 Diamond A. (2013 ). Executive functions. Annu. Rev. Psychol. 64 135 –168 . 10.1146/annurev-psych-113011-143750 23020641 Ellis M. L. Weiss B. Lochman J. E. (2009 ). Executive functions in children: associations with aggressive behavior and appraisal processing. J. Abnorm. Child Psychol. 37 945 –956 . 10.1007/s10802-009-9321-5 19408113 Ernst M. Grant S. J. London E. D. Contoreggi C. S. Kimes A. S. Spurgeon L. (2003 ). Decision making in adolescents with behavior disorders and adults with substance abuse. Am. J. Psychiatry 160 33 –40 . 10.1176/appi.ajp.160.1.33 12505799 Ernst M. Luckenbaugh D. A. Moolchan E. T. Temple V. A. Jenness J. Korelitz K. E. (2010 ). Decision-making and facial emotion recognition as predictors of substance-use initiation among adolescents. Addict. Behav. 35 286 –289 . 10.1016/j.addbeh.2009.10.014 19914005 Fairchild G. van Goozen S. H. M. Stollery S. J. Aitken M. R. F. Savage J. Moore S. C. (2009 ). Decision making and executive function in male adolescents with early-onset or adolescence-onset conduct disorder and control subjects. Biol. Psychiatry 66 162 –168 . 10.1016/j.biopsych.2009.02.024 19362293 Field A. (2013 ). Discovering Statistics Using IBM SPSS Statistics. Thousand Oaks, CA : Sage Publications . Fleitlich B. Cortázar P. G. Goodman R. (2000 ). Questionário de capacidades e dificuldades (SDQ). Infanto Rev. Neuropsiquiatria Infânc. Adolescênc. 8 44 –50 . Fritz C. O. Morris P. E. Richler J. J. (2012 ). Effect size estimates: current use, calculations, and interpretation. J. Exp. Psychol. Gen. 141 2 –18 . 10.1037/a0024338 21823805 Gery I. Miljkovitch R. Berthoz S. Soussignan R. (2009 ). Empathy and recognition of facial expressions of emotion in sex offenders, non-sex offenders and normal controls. Psychiatry Res. 165 252 –262 . 10.1016/j.psychres.2007.11.006 19167095 Gini G. (2006 ). Social cognition and moral cognition in bullying: what’s wrong? Aggress. Behav. 32 528 –539 . 10.1002/ab.20153 Gomes F. Mata F. S. N. Lage G. M. Paiva de Moraes P. H. Moraes P. Fuentes D. (2011 ). Avaliação neuropsicológica do processo de tomada de decisões em crianças e adolescentes: uma revisão integrativa da literatura. Rev. Psiquiatr. Clín. 38 106 –115 . Goodman R. (1997 ). The strengths and difficulties questionnaire: a research note. J. Child Psychol. Psychiatry 38 581 –586 . 10.1111/j.1469-7610.1997.tb01545.x 9255702 Hamdan A. C. Pereira A. P. D. A. (2009 ). Neuropsychological assessment of executive functions: Methodological questions. Psicol. Reflexão E Crít. 22 386 –393 . 10.1590/S0102-79722009000300009 Herrera G. M. (2011 ). Bulimia nervosa: emotions and making decisions. Rev. Psiquiatr. Salud Ment. 4 88 –95 . 10.1016/j.rpsm.2011.03.002 23446144 Johnson M. H. (2012 ). Executive function and developmental disorders: the flip side of the coin. Trends cogn. sci. 16 454 –457 . 10.1016/j.tics.2012.07.001 22835639 Kerr A. Zelazo P. D. (2004 ). Development of “hot” executive function: the children’s gambling task. Brain Cogn. 55 148 –157 . 10.1016/S0278-2626(03)00275-6 15134849 Koh J. B. Wong J. S. (2015 ). Survival of the fittest and the sexiest: evolutionary origins of adolescent bullying. J. Interpers. Violence 10.1177/0886260515593546 [Epub ahead of print] . Kulaif T. (2005 ). O Teste de Cores e Palavras de Stroop Modificado Para Analfabetos, Dissertação de mestrado, Universidade de São Paulo, São Paulo . Lezak M. D. (1982 ). The problem of assessing executive functions. Int. J. Psychol. 17 281 –297 . 10.1080/00207598208247445 Lopes Neto A. A. (2005 ). Bullying: comportamento agressivo entre estudantes. J. Pediatr. 81 164 –172 . 10.1590/S0021-75572005000700006 Malloy-Diniz L. F. Leite W. B. Moraes P. H. P. de Correa H. Bechara A. Fuentes D. (2008 ). Brazilian portuguese version of the iowa gambling task: transcultural adaptation and discriminant validity. Rev. Bras. Psiquiatr. 30 144 –148 . 10.1590/S1516-44462008005000009 18470405 Mata F. G. D. Neves F. S. Lage G. M. Moraes P. H. P. D. Mattos P. Fuentes D. (2011 ). Neuropsychological assessment of the decision making process in children and adolescents: an integrative review of the literature. Arch. Clin. Psychiatry 38 106 –115 . 10.1590/S0101-60832011000300005 Medeiros W. M. B. Moita Minervino C. A. S. Duarte J. S. Cavalcanti J. D. T. Alves N. T. (2014 ). Competência emocional e bullying: uma visão da neurociência. Pediatr. Mod. 50 100 –110 . Miranda R. D. S. (2011 ). Bullying a Partir de Representações Sociais De Estudantes, Dissertação de Mestrado, Universidade Federal da Paraíba, João Pessoa . Olweus D. (1994 ). Bullying at School. NewYork, NY : Springer . Sallum I. Mata F. Miranda D. M. Malloy-Diniz L. F. (2013 ). Staying and shifting patterns across IGT trials distinguish children with externalizing disorders from controls. Front. Psychol. 4 :899 10.3389/fpsyg.2013.00899 Séguin J. R. (2004 ). Neurocognitive elements of antisocial behavior: relevance of an órbito-frontal cortex account. Brain Cogn. 55 185 –197 . 10.1016/S0278-2626(03)00273-2 15134852 Sinclair S. Gansler D. (2006 ). Integrating the somatic marker, and social cognition theories to explain different manifestations of antisocial personality. New School Psychol. Bull. 4 25 –47 . Singh V. (2013 ). A potential role of reward and punishment in the facilitation of the emotion-cognition dichotomy in the iowa gambling task. Front. Psychol. 4 :944 10.3389/fpsyg.2013.00944 Smith P. K. (2002 ). “Intimidação por colegas e maneiras de evitá-la ,” in Violência nas Escolas e Políticas Públicas, eds Debarbieux E. Blaya C. (Brasilia : Unesco ), 187 –205 . Smith P. K. Jones A. P. (2012 ). The importance of developmental science for studies in bullying and victimization. Int. J. Dev. Sci. 6 71 –74 . 10.3233/DEV-2012-11093 Stein M. B. Kennedy C. M. Twamley E. W. (2002 ). Neuropsychological function in female victims of intimate partner violence with and without posttraumatic stress disorder. Biol. Psychiatry 52 1079 –1088 . 10.1016/S0006-3223(02)01414-2 12460691 Suhr J. A. Tsanadis J. (2007 ). Affect and personality correlates of the iowa gambling task. Pers. Individ. Dif. 43 27 –36 . 10.1016/j.paid.2006.11.004 Teicher M. H. Andersen S. L. Polcari A. Anderson C. M. Navalta C. P. Kim D. M. (2003 ). The neurobiological consequences of early stress and childhood maltreatment. Neurosci. Biobehav. Rev. 27 33 –44 . 10.1016/S0149-7634(03)00007-1 12732221 Tung S. Chhabra N. (2011 ). A comparative study on the neuropsychological status of delinquent and non-delinquent boys. Int. J. Cul. Ment. Health 4 121 –127 . 10.1080/17542863.2010.530772 Verdejo-García A. Pérez-García M. Bechara A. (2006 ). Emotion, decision-making and substance dependence: a somatic-marker model of addiction. Curr. Neuropharmacol. 4 17 –31 . 10.2174/157015906775203057 18615136 Verlinden M. Veenstra R. Ghassabian A. Jansen P. W. Hofman A. Jaddoe V. W. V. (2014 ). Executive function in gand non-verbal intelligence as predictors of bullying in early elementary school. J. Abnorm. Child Psychol. 42 953 –966 . 10.1007/s10802-013-9832-y 24337736 Viding E. McCrory E. J. Blakemore S.-J. Frederickson N. (2011 ). Behavioural problems and bullying at school: can cognitive neuroscience shed new light on an old problem? Trends Cogn. Sci. 15 289 –291 . 10.1016/j.tics.2011.05.001 21664171 Wechsler D. (2013 ). Escala de Inteligência Wechsler para Crianças- WISC-IV: Manual de instruções para aplicação e avaliação (1a edição). São Paulo : Casa do Psicólogo .

PMC005xxxxxx/PMC5000583.txt

==== Front Oral OncolOral OncolOral Oncology1368-83751879-0593Elsevier S1368-8375(16)30114-210.1016/j.oraloncology.2016.07.011CorrigendumCorrigendum to “DNA methylation markers for oral pre-cancer progression: A critical review” [Oral Oncology 53 (2015) 1–9] Shridhar Krithiga g.krithiga@phfi.orga⁎1Walia Gagandeep Kaur a1Aggarwal Aastha aGulati Smriti aGeetha A.V. aPrabhakaran Dorairaj abcDhillon Preet K. aRajaraman Preetha da Centre for Chronic Conditions and Injuries, Public Health Foundation of India, Gurgaon, Haryana, Indiab Centre for Chronic Disease Control, Gurgaon, Haryana, Indiac London School of Hygiene and Tropical Medicine, London, United Kingdomd Center for Global Health, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA⁎ Corresponding author at: Centre of Chronic Conditions and Injuries, Public Health Foundation of India, 4th Floor, Plot No. 47, Sector 44, Gurgaon 122002, Haryana, India. Tel.: +91 124 4781400x4482.Centre of Chronic Conditions and InjuriesPublic Health Foundation of India4th FloorPlot No. 47Sector 44Gurgaon 122002HaryanaIndia g.krithiga@phfi.org1 Joint first authors. 1 9 2016 9 2016 60 e1 © 2016 Elsevier Ltd. All rights reserved.2016Elsevier LtdThis is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). ==== Body The authors regret the error published in Introduction Section on Page 1, Line 7: “Over a million new cases are reported every year from more developed regions of the World [1], more so among young adults [4,5]”. Please note the corrected statement with respect to the above mentioned line: “Over a hundred thousand new cases are reported every year from more developed regions of the World [1], more so among young adults [4,5]”. The authors would like to apologise for any inconvenience caused.

PMC005xxxxxx/PMC5000584.txt

==== Front BiosystemsBioSystemsBio Systems0303-26471872-8324Elsevier Science Ireland S0303-2647(16)30077-610.1016/j.biosystems.2016.06.002ArticleReducing complexity in an agent based reaction model—Benefits and limitations of simplifications in relation to run time and system level output Rhodes David M. abHolcombe Mike m.holcombe@epigenesys.co.ukbQwarnstrom Eva E a⁎a Department of Cardiovascular Science, Medical School, University of Sheffield, Sheffield, S10 2RX, United Kingdomb Department of Computer Science, University of Sheffield, Sheffield, S1 4DP, United Kingdom⁎ Corresponding author at: Department of Computer Science, Regent Court, 211 Portobello, Sheffield, S1 4DP, UK.1 9 2016 9 2016 147 21 27 25 2 2015 26 5 2016 9 6 2016 © 2016 The Authors2016This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Agent based modelling is a methodology for simulating a variety of systems across a broad spectrum of fields. However, due to the complexity of the systems it is often impossible or impractical to model them at a one to one scale. In this paper we use a simple reaction rate model implemented using the FLAME framework to test the impact of common methods for reducing model complexity such as reducing scale, increasing iteration duration and reducing message overheads. We demonstrate that such approaches can have significant impact on simulation runtime albeit with increasing risk of aberrant system behaviour and errors, as the complexity of the model is reduced. Keywords Agent-based computational modelComplexityLimitationsScaleIterationsRuntimeModel reduction ==== Body 1 Introduction Agent based modelling (ABM) is a methodology (Niazi and Hussain, 2011) for modelling complex systems used in a large variety of scientific fields from engineering and manufacturing to biology, ecology and social sciences (Coakley et al., 2006, Deissenberg et al., 2008, Holcombe et al., 2012, Grimm and Railsback, 2005, Shen et al., 2006, Macy and Willer, 2002). ABM uses a bottom up approach where agents are autonomous entities representing individual components of the system being modelled and system level behaviour is an emergent property of the actions and interactions of the various agents. However in many cases the systems being modelled may be comprised of millions or potentially billions of components and a model faithfully incorporating each individual as an agent may be either impossible to run on current hardware or have a runtime or volume of output data that make simulations impractical to perform. In these cases using ABM requires greater levels of abstraction to be employed within the model in order for it to be practical. Marked abstractions can be justified in cases where system behaviour is the focus of the analysis and the status of individual agents is not central to the output of the simulation. Hence as long as the abstraction is limited, so that the model is unaltered at the level of overall functionality, reduced complexity simulations still provide useful outputs. Here we use a simple ABM based on a chemical reaction as described previously (Andrews and Bray, 2004, Pogson et al., 2006), and which has recently been expanded upon to explore specific aspects of biological regulatory systems (Pogson et al., 2008, Rhodes and Smith et al., 2015), to assess the impact of reducing model complexity on performance and system level output. The aims were to determine the degree to which simulations could be simplified without losing system level output while maintaining the core system design. 2 Material and methods 2.1 Agent based model To test the impact of varying settings within a simulation we used a simple model of a reaction between two different types of agents which combine to form a third in a one to one ratio (A + B −> C). The agents move within a bounded volume of space by a random walk implementation of Brownian motion and will interact with each other within a given range based on their affinity and the simulation settings (Pogson et al., 2006, Pogson et al., 2008). Fig. 1 demonstrates the output of a typical simulation using a starting concentration of A which is 2 times that of B. This simple reaction model was used in favour of a more complex system for the tests for several reasons. Firstly the reaction is a single step process involving only one interaction between agents which allows evaluation by simply measuring agent population levels. While in a more complex system in which there are more reactions or multiple reactions per agent, changes/errors in system behaviour could be masked through feedback mechanisms. In addition, agent based models are based on the idea of system level behaviour emerging from many low level interactions such as this reaction. If complexity changes do not impact the behaviour of the low level interactions then the emergent behavior should remain the same independent of the number of low level interactions within the system. The ABM was developed in FLAME (Greenough et al., 2008) a platform designed for high performance and parallel processing of agents. In FLAME agents are modelled as state machines with memory, using transition functions between states which can read and write to the agent’s memory. Communication in FLAME is achieved entirely by messages which can by input and output by transition functions and are available to all agents simultaneously. In order to maintain synchronicity a function that needs to read a message must wait until all message outputs from all agents have been completed before it can begin. This synchronous messaging system allows agents to be processed in parallel across multiple processors and eliminates the impact of the order in which agents are processed on the behaviour of the model. 2.2 Model complexity reduction 2.2.1 Scale The scale of the simulation (the number of agents) was adjusted over a range of 2000 fold to a level at which the system no longer accurately represented the behaviour of the complete population. The reduction in the number of agents is compensated by a proportional increase in their interaction volumes. As interactions take place within a 3-D environment, a fixed distance interaction range produces a sphere volume of space around the agent in within which interactions can occur. Hence as the volume of a sphere is proportional to the cube of its radius, the interaction range is modified by the cube-root of the scale change according to the formula: range = baseRange × (∛(1/modelScale)) Therefore if the population is halved, the volume of the sphere of interaction range is doubled. The sphere of interaction determines the rate at which agents can interact and so in this simulation is acting as a rate constant modifier. The rate of this particular reaction is dependent on the rate constant and concentrations of both reagent agents and hence halving both concentrations (by reducing the scale by half) would result in a reduction in reaction rate to one quarter without modifying the rate constant. By changing the interaction range to double the rate constant while halving both agent concentrations the overall reaction rate is halved with the aim of having the percentage of agents reacting over a given time remaining the same. 2.2.2 Time step To assess the impact of less frequent updating and consequent loss of detail on system behaviour, the length of each iteration was increased. Agent behaviour was maintained by proportionally changing the movement and interaction volume of each agent, with a doubling of the time step resulting in a doubling of the interaction volume according to the formula: range = baseRange × (∛(timeStep)) In this case an increase in interaction range adjusts the rate constant to increase the effective reaction rate per iteration to compensate for a reduced number of iterations per simulation. The reaction rate measured per second should however remain the same as each iteration represents a longer period of time. Agent movement uses a random walk implementation of Brownian motion with the length of each random step governed by a diffusion coefficient. Hence the change in size of each random step is proportional to the root of the change in time step according to the formula: distance = (√(diffusion × timestep)) Table 1 shows the parameters used in the reaction model. The simulation environment was modelled as a simple sphere with agents bound within its volume (derived from the environment radius parameter) and remaining the same size throughout the tests. The numbers of agents in the starting iteration was adjusted over a range of 2000 fold to adjust the scale of the simulation with the interaction range adjusted as previously described. The time step was increased up to 600 fold with interaction volume increased proportionately. The diffusion coefficient remained constant throughout all tests while the distance of each random walk step varied with time step, as described above. Simulation starting states used agents generated in random positions throughout the simulation environment so that each run tested a unique set of interactions between agents. To determine if complexity reductions increased the variance of the system level output produced by these random starting states, each test was repeated 5 times. 2.3 Agent messaging Agent based models rely on the ability of agents to communicate with each other in order for complex behaviour to emerge. Agent interactions can produce conflicts that need to be resolved for example when multiple agents attempt to interact with a single other agent. Depending on the complexity of the conflict resolution system implemented in the model errors in interactions can occur. Next simulations were designed to investigate the overheads and impact of conflict resolution within the broadcast messaging system of the FLAME framework. In this framework agents communicate entirely through messages, which can be sent and received into their local vicinity. Messages can contain general information such as a location broadcast or be designated for a specific agent such as a request for interaction. This broadcast message system is one of many types used in ABM however all systems need the ability for agents to communicate and that communication makes up part of each iteration’s computational overhead. Illustration of results of interaction checks performed using varying systems. No messaging (A) can result in loss or duplication of agents. Interaction confirmation (B) can solve the loss or duplication errors but can miss potential interactions that can occur (C). Looping interaction confirmations (D), show how the second loop of checks picks up the interactions missed in the initial interaction confirmation check. 2.3.1 No messaging If an agent is within interaction range with another it assumes interaction occurs with no communication between the agents. If more than one agent is within interaction range with another they will both assume reaction has occurred and alter state, generating errors within the simulation. In the example in Fig. 2A two agents of type A assume binding with one agent of type B, depending on the implementation of the interaction this will lead to either an overall loss of one type A agent and the formation of one type AB or the overall creation of a duplicate type B agent due to the formation of two type AB agents. 2.3.2 Interaction confirmation One agent type sends requests for interaction to the nearest interacting agent within range and the responding agent sends out a single message to confirm the reaction can occur to the closest agent it received a request from. This process will eliminate the loss/duplication errors that occur with no messaging, therefore if two agents both request interaction with the same agent, that agent will respond to only one with a confirmation, illustrated in Fig. 2B. However as in Fig. 2C if an agent (A2) requests an interaction and is denied due to a closer agent being confirmed a potential interaction with a more distant agent (A2 and B2) can be missed leading to errors from lost interactions. 2.3.3 Looping interaction confirmation Messaging occurs in the same way as with Interaction confirmation (Fig. 2C) but repeats the cycle of messages until all possible interactions have occurred (Fig. 2D). This eliminates both error from loss/duplication and error from lost interactions but at the cost of increased computing overhead. We tested the impact of having no messaging versus a full looping confirmation system in terms or both runtime and duplication error rate under varying density settings. For each density we adjusted the volume of the simulation environment while maintaining total agent numbers hence forcing the agents into higher or lower concentrations and therefore increasing the likelihood of creating an interaction conflict. 3 Results and discussion 3.1 Scale and time step From the results shown in Fig. 3A, the simulations in which the scale of the model was reduced, the adjustments to interaction range adjusting the rate constant of the reaction appear to compensate for the variation in agent concentrations. The results demonstrate that the overall system behaviour remained largely unchanged across several fold reduction in model scale. However, as the reductions became more extreme (2000 fold, less than 100 total agents) the system behaviour began to deviate noticeably and eventually break down. Reducing the scale and the total number of agents in the simulation lowers the number of agent interactions to be processed per iteration, reducing runtime. Similarly as the data produced per iteration includes all agents, the size of the simulation output files was proportionally reduced. We see a similar impact on system level output when increasing iteration time steps, leaving the output consistent across alteration of several fold but diverging at extreme changes (600 fold) (Fig. 3B). Increasing the length of each time step reduces the total number of iterations required and results in a decrease in the overall runtime, which is roughly proportional for the majority of increments. However a minimum simulation runtime overhead appears to remain at the extreme time steps, preventing any further reduction in runtime. As the number of iterations processed is reduced proportionally to the time step, so is the amount of simulation data output. As agent movement in this simulation uses a random walk implementation, each agent moves in random jumps in each iteration, as the length of iterations increase so does the length of the jump. At very large time-steps agents may traverse a large proportion on the simulation environment in a single iteration. As the reaction model in this case was designed with an empty environment, large distance steps had little consequence on the simulation with the agent distribution remaining spread throughout the simulation volume throughout the tests (Fig. 3D). However in a simulation with physical obstacles, large distance time-steps may impact agent movement leading to noticeable divergence in system behaviour. Combining both time step increases and scale reductions showed similar overall behaviour, but with divergence presenting earlier (20 fold time step and 30 fold scale) when combined than by changing either parameter alone (Fig. 3C). In addition, runtime reductions were slightly greater when combining changes in time step and scale, demonstrating that effects on runtime improvements and simulation divergence were additive. Despite the system level output varying due to changes of scale and time-step, the variance between individual runs at any setting remained highly consistent despite the random starting locations of each agent. At the highest scale the standard deviation (SD) over 5 runs was 0.0004 at the end time point, while reducing the scale by 100 fold only increased the SD to 0.0041. Further halving in scale to the point where the simulation broke down did increase the variance to 0.0296. Similarly an increase in time-step by 600 fold changed the SD from 0.0041 to 0.0082. This demonstrates that up to the point where simulation behaviour breaks down these complexity changes do not make the variance between runs significantly higher and accurate readings can be obtained by few simulation run repeats. (A) Scale of simulation was adjusted by varying agent numbers by indicated proportion and interaction volumes by the inverse amount. Time step was fixed to 1 in each case. (B) Time step for each iteration was varied, increasing movement and interaction volumes by indicated amount and reducing total number of iterations by the same proportion. Scale was fixed to 200 in each case. (C) Scale and time step were varied simultaneously by indicated amounts. Graphs display percentage of total number of agent type A reacted (left) and total simulation time (right). (D) Agent distribution throughout simulation volume at different equivalent time points with time step adjusted 100 fold. Colours represent different agent types, Red − A, Green − B, Blue − C. Pictures are from a single simulation run for each time step setting, using the same initial agent distribution. 3.2 Agent messaging and density Forcing agents into higher concentrations by increasing density, increases the number of potential interactions in each iteration and thus increases the number of potential conflicts to be resolved. As can be seen in Fig. 4A, without a robust messaging system controlling potential interaction conflicts, a large number of erroneous interactions can occur, which may have a significant impact on system level behaviour. It can also be seen that conversely when interactions are much rarer, the likelihood of conflict is reduced and very few errors occur even without robust interaction checks. However from the runtime results in Fig. 4B we can see that the overhead of implementing the interaction confirmation loops is reasonably small when there are few conflicts to be resolved. At higher densities with larger number of conflicts, the message overhead becomes much higher resulting at the highest density with roughly 75% of the runtime being taken up by interaction resolution. Therefore we conclude that interaction confirmation is most costly on simulation runtime and although reducing the robustness of messaging would have a large impact on runtime it would also significantly increase error rate. In order to reduce both runtime by limiting messaging and error rate by minimizing interactions, the simulation density needs to be reduced to levels where interaction conflict is minimal and either the error rate is tolerable or the overhead of interaction confirmation is negligible. However, determining a tolerable error rate also depends on the nature of the interactions within the simulation. In some simulations interactions may feedback on themselves or from one another in a positive or negative manner. Negative feedback may reduce the impact of errors by self-regulating the system to compensate, whereas errors in positive feedback systems will compound leading to greater and greater error rates. An example of positive feedback can be seen in Fig. 4C in which the simple reaction model has had the addition of a disassociation mechanic which reverts agent C back to agents A and B after a fixed delay. In this system which does not include messaging, interaction errors cause duplication of agents as illustrated in Fig. 2, after dissociation these additional agents can rebind causing further errors. The repeated binding errors generate increasing numbers of erroneous agents leading to creation of far more of agent C than should have been possible from the starting agent concentrations. With messaging enabled (Fig. 4D) the system does not produce these errors and stabilizes at equilibrium between binding and dissociation. The difference between messaging systems in this model demonstrates the low tolerance for errors and the large changes in system output resulting from such positive feedback systems. In the investigation of scale and time step we explored two methods of reducing simulation density which may help reduce this messaging overhead. Decreasing the simulation scale reduces the total number of agents and therefore the number or interactions occurring in each iteration, lowering the message system overhead in addition to the previously described runtime reductions. However the likelihood of conflict per agent will remain unchanged leading to errors without interaction confirmation. Reducing the time step of each iteration spreads interactions over multiple time points decreasing the effective density of the simulation and the likelihood of conflict. Reducing time step sufficiently will reduce error rates to a low enough level that message confirmation can be removed in favour of performance. However, reducing time steps increases the total number of iterations and hence runtime as previously shown, and may not result in an overall performance increase. Hence with some testing of tradeoffs between scale, time step, message overhead and error rate, runtimes and data output can be optimized while maintaining acceptable accuracy of system level output. Error rate as percentage of total number of interactions resulting in agent duplications at varying simulation density (A) Runtime for simulations of varying density with no messaging or full confirmation loop messaging (B), results show messaging overhead correlates with number of interaction conflicts to resolve. Agent concentration in the simple reaction model with addition of dissociation of reacted agents, using no messaging (C) or full confirmation loop messaging (D). Duplication errors occurring without messaging can feedback resulting in increasing error over time whereas with messaging the system reaches equilibrium between binding and dissociation. 3.3 NFκB signaling pathway model To determine if these modifications could be applied to more complex models we tested scale and timestep changes on the ABM model developed as part of our previous work (Rhodes and Smith et al., 2015). This model is a cellular biological simulation of activation of the NFκB signaling pathway which contains multiple types of protein and receptor agents. The model features several types of interactions including binding, dissociation, transport, changes of state, agent destruction and creation and hence should be a more rigorous test of the complexity changes. Simulations were run in this model at three complexity levels, with the higher complexity model simulating approximately a 1:1 ratio of agent:protein and 1 s time steps. The medium complexity model was implemented with 10 fold-reduced scale, 10 fold increased time step and message confirmation present but limited to only the densest of agent interactions and the lowest complexity test was performed by reducing scale and increasing timestep by a further 10 fold. The results shown in Fig. 5A demonstrate the activation of several proteins within the signal pathway that activate each other in a cascade starting with MyD88 activation by a cell surface receptor. The high and medium complexity simulations show signal amplification through the cascade with similar peaks of activity in terms of both time and intensity. However the low intensity model simulations resulted in progressive dampening of activation through the pathway, demonstrating a significant reduction in the number of agent interactions occurring in a manner similar to that of the reaction rate tests. In Fig. 5B and C can be seen two typical system level outputs of the simulation, in which both the medium and the high complexity simulations agree well with in vitro data (Yang et al., 2003, Carlotti et al., 1999). The low complexity model however shows only a small change in these outputs, showing that the signal dampening effects of the complexity changes lead to almost no change at the bottom of the signal pathway. The reduction in complexity from high to medium resulted in a reduction in running time to less than 1/100th of the time required for the more complex model. The results demonstrate the ability to significantly improve simulation performance without losing system level behaviour. We believe that through complexity changes such as these, improvements to runtimes can be achieved in a variety of ABMs, especially those with large numbers of relatively simple agents such as signalling pathways, cellular models (Kaul et al., 2013) and population models (Mathevet et al., 2003). Because of inherent differences in agent behaviour, interactions and environment between different ABM models, it is difficult to derive general rules regarding the effect of complexity on ABM output. However our data show that reduction in complexity may be a valuable consideration in design or optimisation specifically of large scale ABMs. Protein activation cascade shows consistent amplification through the signal pathway at high and medium complexity but a dampening of signal at low complexity (A). Simulated degradation of IκB (B) and ratio of nuclear to cytoplasmic NFκB (C) over 60 min of stimulation with the cytokine interleukin1- (IL-1), are consistent between high complexity (blue) and medium complexity (red) models, but greatly reduced in low complexity simulations (green). Total simulation runtime (D) reduced over 100 fold from high to medium complexity and over a further 100 fold from medium to low complexity. 4 Conclusions We have used a simple chemical reaction ABM to study the impact of reducing simulation complexity on the system level output and simulation runtime. We have shown the number of agents and the length of time step can be varied by several orders of magnitude and still produce very similar system level behaviour while having a large impact on runtime and data output. We also show that a lack of robust interaction messaging can lead to large error rates and yet the overhead of those robust checks can be significant. Therefore engineering the simulation in a way that generates less interaction conflict can provide large benefits in accuracy and/or runtime. ABMs are rarely expected to produce perfect predictions, but are accepted as abstractions and used to identify trends in behaviour of the simulated system under specific conditions. Therefore the benefits of these complexity reductions in terms of runtime and data output may well outweigh any small inaccuracies in the simulation output. Acknowledgements Studies were supported by grant BB/J009687/1 from the Biotechnology and Biological Sciences Research Council to EEQ and MH. Fig. 1 Agent concentrations in a typical simulation. Concentration of Agents A,B and C over time in a typical simulation run for the reaction A + B −> C. Fig. 1Fig. 2 Agent interaction conflict resolution systems. Fig. 2Fig. 3 Impact of adjusting scale and time step on simulation. Fig. 3Fig. 4 Impact of Messaging on Interaction Error and Runtime. Fig. 4Fig. 5 Impact of complexity on NFκB model. Fig. 5Table 1 Simulation parameters. Table 1Variable Formulae Symbol Value at Model Scale 1 and Timestep 0.1 Environment radius 17.5 μm Model Scale modelScale 1 Diffusion Coefficient diffusion 5  × 10−5 cm2/s Timestep length timestep 0.1 s Interaction range (radius) baseRange 0.3 μm Starting Agent population − Agent A 300 × modelScale Starting Agent population − Agent B 600 × modelScale ==== Refs References Andrews S.S. Bray D. Stochastic simulation of chemical reactions with spatial resolution and single molecule detail Phys. Biol. 1 3 2004 137 151 16204833 Carlotti F. Activation of nuclear factor kappaB in single living cells: dependence of nuclear translocation and anti-apoptotic function on EGFPRELA concentration J. Biol. Chem. 274 53 1999 37941 37949 10608861 Coakley S. From Molecules to Insect Communities − How Formal Agent Based Computational Modelling Is Uncovering New Biological Facts 2006 In scientiae mathematicae japonicae online 765 778 Deissenberg C. FURACE: A massively parallel agent-based model of the European economy Appl. Math. Comput. 204 2 2008 541 552 Greenough C. The Exploitation of Parallel High Performance Systems in the FLAME Agent-based Simulation Framework 2008 RAL Technical Reports RAL-TR-2008–2022 Grimm V. Railsback S.F. Individual-based Modeling and Ecology: (Princeton Series in Theoretical and Computational Biology) 2005 Princeton University Press Holcombe M. Modelling complex biological systems using an agent-based approach Integr. Biol. 4 1 2012 53 64 Kaul H. A multi-paradigm modeling framework to simulate dynamic reciprocity in a bioreactor PLoS One 8 3 2013 e59671 23555740 Macy M.W. Willer R. FROM FACTORS TO ACTORS: computational sociology and agent-Based modeling Annual Rev. Sociol. 28 1 2002 143 166 Mathevet R. Agent-based simulations of interactions between duck population: farming decisions and leasing of hunting rights in the Camargue (Southern France) Ecol. Modell. 165 2–3 2003 107 126 Niazi M. Hussain A. Agent-based computing from multi-agent systems to agent-based models: a visual survey Scientometrics 89 2 2011 479 499 Pogson M. Formal agent-based modelling of intracellular chemical interactions Biosystems 85 1 2006 37 45 16581178 Pogson M. Introducing spatial information into predictive NF-κB modelling—An agent-based approach PLoS One 3 6 2008 e2367 18523553 Rhodes D.M. Smith S.A. Computational modelling of NF-κB activation by IL-1RI and its Co-Receptor TILRR, predicts a role for cytoskeletal sequestration of I(Bα in inflammatory signalling PLoS One 10 6 2015 e0129888 26110282 Shen W. Applications of agent-based systems in intelligent manufacturing: an updated review Adv. Eng. Inf. 20 4 2006 415 431 Yang L. RelA control of IκBα phosphorylation J. Biol. Chem. 278 33 2003 30881 30888 12663663

PMC005xxxxxx/PMC5000585.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081107ijms-17-01107ReviewAntioxidant Activity of γ-Oryzanol: A Complex Network of Interactions Minatel Igor Otavio 1Francisqueti Fabiane Valentini 2Corrêa Camila Renata 2Lima Giuseppina Pace Pereira 1*Battino Maurizio Academic EditorCapanoglu Esra Academic Editor1 Department of Chemistry and Biochemistry, Institute of Bioscience, Sao Paulo State University, Botucatu 18618-689, Brazil; igorminatel@hotmail.com2 Department of Pathology, Botucatu Medical School, Sao Paulo State University, Botucatu 18618-970, Brazil; fabiane_vf@yahoo.com.br (F.V.F.); ccorrea@fmb.unesp.br (C.R.C.)* Correspondence: gpplima@ibb.unesp.br; Tel.: +55-14-3880-057309 8 2016 8 2016 17 8 110720 5 2016 07 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).γ-oryzanol (Orz), a steryl ferulate extracted from rice bran layer, exerts a wide spectrum of biological activities. In addition to its antioxidant activity, Orz is often associated with cholesterol-lowering, anti-inflammatory, anti-cancer and anti-diabetic effects. In recent years, the usefulness of Orz has been studied for the treatment of metabolic diseases, as it acts to ameliorate insulin activity, cholesterol metabolism, and associated chronic inflammation. Previous studies have shown the direct action of Orz when downregulating the expression of genes that encode proteins related to adiposity (CCAAT/enhancer binding proteins (C/EBPs)), inflammatory responses (nuclear factor kappa-B (NF-κB)), and metabolic syndrome (peroxisome proliferator-activated receptors (PPARs)). It is likely that this wide range of beneficial activities results from a complex network of interactions and signals triggered, and/or inhibited by its antioxidant properties. This review focuses on the significance of Orz in metabolic disorders, which feature remarkable oxidative imbalance, such as impaired glucose metabolism, obesity, and inflammation. γ-oryzanolferulic acidantioxidant capacitydyslipidemiaobesityinflammation ==== Body 1. Introduction Grains are the most common staple food consumed worldwide. Taking into account that rice (Oryza sativa L.) constitutes the principal grain in the human diet, and since it feeds over half of the world’s population, is very important to consider its constituents, such as γ-oryzanol (Orz), fiber, γ-amino butyric acid, and vitamins. Therefore, the beneficial effects attributed to brown rice (BR) consumption must consider the synergic interaction of all these bioactive constituents. The consumption of BR (unpolished) in regular meals is strongly recommended, since the polishing step to obtain white rice reduces approximately 94% of the grain’s Orz content [1]. In addition, the polishing process removes other compounds that exert antioxidant activities, such as phenolics, tocopherols, and tocotrienols [1]. Furthermore, Orz composition and its amounts are variable among rice cultivars [2]; it is unequally distributed in the grain, with higher levels present in the bran layer and lower concentrations in the kernel. Strategies to improve BR’s bioactive components include affecting the germination process. By inducing germination of the whole rice grain, its compounds are remarkably increased [3], whereas the Orz content is slightly higher in germinated rice than in BR, and this is cultivar-dependent [4]. Orz comprises a mixture of ferulic acid (FA) esters and phytosterols (sterols and triterpenic alcohols) [5,6]. At least 10 steryl ferulates were identified in Orz, such as cycloartenyl ferulate, 24-methylenecycloartanyl ferulate, campestenyl ferulate, campesteryl ferulate, stigmastenyl ferulate, sitosteryl ferulate, ∆7-stigmastenyl ferulate, stigmasteryl ferulate, campestanyl ferulate, and sitostanyl ferulate [5]. Among these, cycloartenyl, 24-methylenecycloartanyl, campesteryl and sitosteryl ferulates predominate (Figure 1). The Orz constituents are commonly purified by high performance liquid chromatography (HPLC), whereas to identify isomers or the molecular variability of these constituents, methods as crystallization, nuclear magnetic resonance, and mass spectrometry (MS), have been employed [5,7,8,9]. However, the most suitable method to identify and quantify Orz with more sensibility is the liquid chromatography coupled to MS/MS [8,10]. The higher number of components identified by this method suggest that it is more recommended to identify and quantify Orz in biological tissues and fluids. To better understand the mechanisms underlying the health benefits of Orz, and its interaction with different molecules, is necessary to consider the molecular structure of its metabolites. The consumption of Orz has been proved to be safe, with no relevant side effects reported. However, the most of the data available comes from studies in vitro or from animal models. In a recent study, Szcześniak et al. revised several of these studies and concluded that beneficial effects of Orz are due to its antioxidant activity and modifications in lipids metabolism [11]. A remarkable lack of specific dosages have used in animal models (doses range to 1–2000 mg/kg of body weight), or in vitro (doses range to 0.1–1000 µmol) [11]. Nevertheless, is still necessary to clarify the exact mechanisms of action and confirm the results obtained in human studies. For example, in mildly hypercholesterolemic men a daily dose of 50 mg of Orz, for 4 weeks, lowered total cholesterol, low-density lipoprotein (LDL) cholesterol, and LDL/high-density lipoprotein (HDL) cholesterol ratio by 6.3%, 10.5%, and 18.9%, respectively; whereas, increasing this dose to 800 mg/day did not enhance the pattern of lowering lipids [12]. Steryl ferulates arising from Orz share certain similarities with cholesterol (Figure 1). As an essential component of all mammalian cells, cholesterol is also an important structural component of myelin and a precursor of oxysterols, steroid hormones, and bile acids [13]. Orz has been shown to reduce plasma cholesterol levels and hepatic intake [14,15]; hence, it can affect different cell functions in the human organism. A great variety of biological effects has been attributed to Orz, such as antidiabetic [16], antioxidant [1,17], and anti-inflammatory activities [18]. However, until recently, the most studied Orz-related activities include its hypolipidemic and anti-obesity effects [15,16,19,20]. These potential health benefits are mainly verified through the introduction of a diet high in BR or germinated BR (GBR). Moreover, not only is Orz responsible for these effects, FA (the major metabolite of Orz) has been shown to improve lipid metabolism, hypertension, and glucose tolerance [15,21]. Here, we describe the wide range of beneficial activities arising from Orz’s antioxidant activity, and we then discuss how this compound is coupled to a number of health benefits. 2. Antioxidant Activity of γ-Oryzanol In order to establish the beneficial effects of Orz in the antioxidant defense of cellular systems, it is important to consider that dietary antioxidants are essential for maintaining normal cellular functions and to ensure body homeostasis. Nevertheless, the regulation of a redox mechanism through dietary means is currently gaining considerable traction in the field of human and food sciences. Oxidative stress results in a deleterious process that culminates in the damage of cell structures, including membranes and lipids, as well as proteins and DNA [22]. Reactive oxygen species (ROS) are constantly produced by enzymatic and non-enzymatic reactions. The major reactions catalyzed by enzymes that generate ROS include those involving NADPH oxidase, nitric oxide synthase (NOS), xanthine oxidase, arachidonic acid, and metabolic enzymes such as the cytochrome P450 enzymes, cyclooxygenase, and lipoxygenase. Non-enzymatic production of ROS comes from the mitochondrial respiratory chain. The major ROS produced in the human organism include singlet oxygen (1O2), superoxide anion (O2•−), hydroxyl radical (OH•), hydrogen peroxide (H2O2) and organic peroxides [23]. In addition, other molecules that affect oxidative balance are the reactive nitrogen species (RNS), such as nitric oxide (NO), nitrite (NO2−); carbon monoxide (CO); hydrogen sulfide (H2S) and its anion HS− [23]. Oxidative imbalance is responsible for producing several reactive molecules, which are scavenged by Orz or its metabolites. The consumption of high-fat diets (HFD) has been shown to induce the formation of free radicals and ROS, resulting in lipid peroxidation and oxidative stress [24]. Orz and FA suppressed lipid peroxidation in mice fed a HFD [14] consumption based on a diet that included 15 mg/day of both compounds lowered plasma and erythrocyte thiobarbituric acid reactive substances (TBARS), when compared to control mice fed the HFD alone [14]. This finding illustrates that Orz and FA can act as ROS scavengers and prevent lipid peroxidation. Furthermore, the prevention of lipid peroxidation avoids lipotoxicity, which is associated with mitochondrial dysfunction, and formation of cellular ROS. In addition, these compounds have the capacity to reduce glucose-6-phosphate dehydrogenase (G6PD) [25], which promotes the expression of pro-oxidative enzymes NAPDH oxidase and NOS. Metabolites of Orz can induce different antioxidant responses in the organism, as observed in the serum levels of total antioxidant capacity (TAOC) and malondialdehyde (MDA) in rats [15]. In serum, reduced TAOC and increased MDA content was induced by HFD. However, FA treatment better improved TAOC and MDA levels when compared to Orz [15]. Regardless of the material (BR, bran, or isolated compounds) used to assess the antioxidant capacity of rice, it is controversial to strictly assign this potential to a given compound in isolate. Phenolic acids, tocopherols, tocotrienols, carotenoids and Orz are typical constituents of rice. Different rice cultivars may contain 8–10 times more Orz than vitamin E [2,17], which is considered one of the most effective antioxidants due to its biodisponibility. Nevertheless, the three major Orz metabolites (cycloartenyl, 24-methylenecycloartanyl and campesteryl ferulates) had higher antioxidant activities against cholesterol oxidation when compared to α- and γ-vitamin E isomers [17]. Among these, the highest antioxidant activity was imputed for 24-methylenecycloartanyl ferulate, which demonstrated variable antioxidant activity of the metabolites [17]. In another report, cycloartenyl, 24-methylenecycloartanyl, and β-sitosteryl ferulates, and FA showed a strong free radical scavenging and antioxidative protection of lipid peroxidation, which were comparable to α-tocopherol [26]. The hydroxyl group on the phenolic ring and an electron delocalization induced by ROS are important characteristics evolved in antioxidant activity of phytosterols [17,27]. In addition to the high amounts of Orz, its major metabolite ferulic acid presents the CH=CH–COOH group (cinnamic acid) that ensures an efficient antioxidant activity [27]. However, the major effect of Orz as an antioxidant is probably due to its capacity to prevent lipid peroxidation and the resulting oxidative stress. Thus, all the potential health benefits associated with Orz intake should be interpreted by considering its antioxidant capacity and other metabolic interactions. Another important situation to consider when examining oxidative stress associated with redox imbalance is the resultant mitochondrial dysfunction. Different antioxidant systems are activated in cells, which fight the ROS produced and includes antioxidant molecules like superoxide dismutase (SOD), catalase [28], and glutathione [29,30]. SOD is responsible for catalyzing the dismutation of O2− into H2O2, which is converted into H2O and O2 by catalase. Glutathione transferases comprise a super family of proteins that carries several redox regulations and occurs in all cellular life forms [31]. The fine regulation of these antioxidant systems is essential to prevent mitochondrial dysfunction, and its deregulation has long been implicated in the pathogenesis of Parkinson’s disease (PD) [32]. The production of free radicals and oxidative stress are among the deleterious factors associated with neuronal mitochondrial dysfunction. In a Drosophila melanogaster model of PD induced by rotenone, Orz improved antioxidant defenses, prevented oxidative stress, and attenuated mitochondrial dysfunction [33]. A significant increase in antioxidant enzymes (such as catalase, superoxide dismutase, and glutathione-S-transferase) was also observed and linked to abrogation of deleterious MDA and ROS produced by rotatone [33]. These activities are likely associated to the inhibition of free radical generation and the consequent prevention of inflammation progress. 3. Relation between γ-Oryzanol and Glucose Metabolism At the cellular and molecular levels, oxidative stress is considered a key factor in the development of insulin resistance, impaired glucose, and diabetes. Many studies have indicated that BR ameliorates glucose metabolism [20,34,35,36]. Nevertheless, this statement is more accurate when one considers all the bioactive compounds present in rice. Mice fed a HFD plus BR showed ameliorated glucose tolerance and insulin resistance [35]; however, in the same study, a daily oral dose of Orz exerted the same effects as BR, suggesting that Orz or its metabolites are primarily responsible for the modulation of glucose metabolism [35]. A close relationship exists between obesity and insulin regulation. Adiponectin produced by adipocytes has been shown to modulate glucose and lipid metabolism in insulin-sensitive tissues, such as liver and skeletal muscle [37]. Furthermore, obesity promotes adipocytes dysfunction and results in a consequently decreased level of adiponectin secretion [38]. In an stress-induced model of hypoadiponectinemia, Orz restored the globular and full-length adiponectin levels [39]. Full-length adiponectin is related to phosphorylation and activation of 5′-AMP-activated protein kinase (AMPK). AMPK phosphorylation positively regulates glucose metabolism and insulin sensitivity by reducing the expression levels of molecules involved in gluconeogenesis [40], such as phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase (G6Pase) in hepatocytes [37]. In addition, the activation of AMPK results in the phosphorylation of the β-isoform of coenzyme A carboxylase (ACC-β), which inhibits acetyl coenzyme A carboxylase (ACC) [37], and consequently results in increased fatty acid oxidation (Figure 2). Rodents fed a diet supplemented with Orz and FA were shown to exhibit regulated type 2 diabetes parameters, as their fasting glucose levels improved and their levels of glucose reduced during an oral tolerance test [15]. These effects may be explained by the results reported by Son et al., who showed that mice fed a HFD supplemented with either 0.5% Orz or 0.5% FA exhibited significantly lower blood glucose levels, and G6Pase and PEPCK activities, as well as higher glycogen and insulin concentrations, and glucokinase activity [25]. Insulin suppresses the expression of many hepatic genes associated with diabetes [41], including G6Pase and PEPCK. Both genes are essential for the regulation of hepatic gluconeogenesis, and its suppression represents an important step in type 2 diabetes control [42]. Another organ involved in the type 2 diabetes pathogenesis is the pancreas. Endoplasmic reticulum (ER) stress in pancreatic islet cells is linked to progressive β-cells dysfunction, apoptosis, and insulin resistance [43]. The ER is the cellular organelle in which protein synthesis, folding, and sorting take place. However, the development of stress in this organelle is accomplished by several metabolic disorders, resulting from misfolded protein accumulation and ROS formation. Although the organ-specific action of Orz in the pancreas is still unclear, following oral administration, Orz reaches its maximum plasma concentration in about 1 h. The distribution of Orz occurs mainly in the brain, whereas considerable amounts are found in the pancreas [44]. In the pancreas, Orz has been shown to decrease the expression of ER stress-responsive genes such as Ddit3 (CCAAT/enhancer-binding protein-homologous protein), Dnajb9 (ER resident DNAJ 4), and the spliced form of X box binding protein 1 (Xbp1s) [44]. These results suggest that Orz prevents ER stress-induce apoptosis, and it consequently enhances β-cell insulin production. Although Orz absorption by adipose tissues is lower than in the pancreas [44], it might improve adiponectin levels as discussed earlier. As Orz exerts its effects in the pancreas (it decreases ER stress and improves insulin secretion) and in adipose tissue (it improves adiponectin levels), it is feasible that Orz may display synergic effects in different organs, particularity as they relate to glucose metabolism (Figure 2). Improved levels of adiponectin and insulin culminates in liver AMPK activation. Adiponectin receptors 1 (AdipoR1) and 2 (AdipoR2) in the liver are stimulated by full-length adiponectin and they activate the phosphorylation of AMPK and PPAR-α, respectively [45]. Both pathways can increase fatty acid oxidation and lead to decreased triglyceride content [45,46]. AMPK stimulates fatty acid oxidation and ketogenesis, leading to reductions in cholesterol synthesis and lipogenesis. This kinase protects against lipid-induced hepatic disorders and consequently reduces ER stress [43]. 4. Anti-Obesity Effects of γ-Oryzanol The rising prevalence of overweight and obesity (body mass index ≥ 30 kg/m2) has become a global pandemic [47,48]. Improvements in quality of life and increases in income have created nutritional transitions and changes in dietary habits, such as the increased consumption of foods rich in fat and sugar, and of low nutritive quality. These changes are directly associated with obesity and the development of chronic diseases, such as type 2 diabetes mellitus (T2DM), cardiovascular diseases, dyslipidemia, and some cancers [49]. The consumption of whole grains, such as BR, is a promising approach to manage or prevent obesity and associated diseases. Most of these preventive effects are attributed to dietary fibers, since individuals with high intakes of dietary fiber face lower risk for developing obesity, moreover, the high consumption of fiber significantly contributes to weight loss [50]. The potential health benefits associated with the consumption of BR was evident in a study conducted in individuals with metabolic syndrome [16]. BR consumption resulted in decreased body weight, total cholesterol, and LDL-cholesterol levels, as well as lower postprandial concentrations of insulin and glucose, when compared to individuals consuming white rice [16]. However, dietary fibers from rice have either a slight (or no) effect on total cholesterol, triglycerides, and free fatty acids (FFA) blood levels [34,51]. Thus, these effects may be promoted by Orz and FA, as they showed a significant decrease in the body weight of rodents that were fed diets rich in fat and sugar [15,25,35]. The consumption of HFD is related to increased body weight gain and the development of local and systemic oxidative stress. This scenario constitutes an important triggering of metabolic syndrome and associated symptoms, such as hyperlipidemia, hyperglycemia, hypertension, insulin resistance, and hyperinsulinemia [52,53]. The steryl ferulates of Orz demonstrate antioxidant activity, as they donate hydrogen from their ferulic acid constituent [54]; beneficial effects may be reached by the antioxidant capacity of these bioactive compounds or by improving the metabolism of dietary components, such as cholesterol. Given the fact that FA is one of the major metabolites of Orz, it is possible assume that its effects in ameliorating obesity-related symptoms may be reached by Orz consumption. Wang et al. found that Orz and FA have similar effects in alleviating obesity and dyslipidemia in rats fed with HFD and high fructose diets. Both compounds were efficient in serum normalization of total cholesterol, triglycerides and LDL-cholesterol, and they induced FFA level reductions and high density lipoprotein (HDL) cholesterol increases [15]. Rong et al. showed that the addition of 1% of Orz to hypercholesterolemic diet for 7 weeks was able to decrease in 34% the plasma non-HDL-cholesterol of F1B Golden hamsters. In the same study, when Orz at 0.5% was added to hypercholesterolemic diet and animals fed for 10 weeks, a 57% reduction in plasma non-HDL-cholesterol was observed [55]. The capacity of Orz and FA to reduce triglyceride and cholesterol levels is directly induced by the suppression of hepatic lipogenesis, which occurs via regulation of the activities of NADPH-generating enzymes [14]. In addition, Orz and FA are able to improve the plasma and hepatic lipid profile by increasing faecal lipid excretion [14]. The available evidence suggests that intakes of 1.5–2.0 g of plant sterols may lower blood LDL-cholesterol by an average of 8.5%–10% [56,57]. In addition, the consumption of foods with low amounts of saturated fat and cholesterol, in association with the intake of sterols, can exacerbate LDL reduction by 20% [58]. It is noteworthy that Orz shares certain molecular similarities with cholesterol (Figure 1). Thus, it is pertinent to consider that phytosterols exert their cholesterol-lowering effects by decreasing cholesterol micellarization. Inside the intestinal lumen, dietary phytosterols are solubilized in micelles by bile acids, prior diffuse to enterocytes. Phytosterols have a higher solubility and affinity to the bile salt micelles than cholesterol and they may be effective for displacing cholesterol in micellarization [59]. In addition, phytosterol esters interact with digestive enzymes—particularly pancreatic cholesterol esterase (PCE). This enzyme is responsible for hydrolyzing lipids before micelle formation. In contrast to esters, free phytosterols show no effect on cholesterol ester hydrolysis [60]. The serum availability of FFA in the body is essential to induce hepatic lipogenesis, and Orz may control this mechanism by lowering FFA and reducing hepatic triglyceride synthesis [15]. This result is likely obtained by the decreased expression of liver X receptor α (LXRα), fatty acid synthase (FAS), and stearoyl coenzyme-A desaturase-1 (SCD-1) [15]. Unregulated appetite in humans is mainly derived from a leptin deficiency [61]; leptin is an adipocyte-derived hormone that acts on a subset of hypothalamic neurons to regulate food intake, thermogenesis, and the blood glucose levels [62]. Leptin inhibits food intake, stimulates cell energy expenditure, and results in a reduction of the body’s fat stores [62]. However, the contrasting effects of Orz, and their ability to decrease serum leptin levels or to attenuate one’s preference for HFD have been reported [15,35]. In addition to its critical role in appetite regulation, leptin resistance is associated with overnutrition and hypothalamus ER stress. Increased levels of FFA and overnutrition are conditions that lead to ER stress, and trigger a dysfunctional protein folding [61]. The intracellular accumulation of misfolded proteins results in ER stress and leads to the consequent activation of a complex network known as the unfolded protein response [63]. These mechanisms are directly involved in obesity, insulin resistance, and type 2 diabetes [63]. However, the reversing of ER stress and its associated improvement in the protein folding process resulted in increased insulin sensitivity and reverted type 2 diabetes in obese mice [64]. Kozuka et al. (2012), found that Orz attenuated the ER stress, improved glucose metabolism, and decreased plasma leptin. In addition, the authors observed an attenuated preference for dietary fat and the decreased expression of the following ER stress–responsive genes: CCAAT/enhancer-binding protein-homologous protein (Chop), endoplasmic reticulum resident DNAJ 4 (ERdj4), and the spliced form of X-box binding protein 1 (Xbp1s) [35]. Adipogenesis is regulated by various transcription factors that coordinate innumerous protein responses and culminates into preadipocytes to adipocytes differentiation [65]. Among the transcription factors expressed in adipocytes, CCAAT-enhancer-binding proteins (C/EBPs) and PPARγ are key factors in this process, and their regulation may stop the complex transcriptional cascade and protein activation necessary for adipogenesis [66]. PPARγ is more essential for adipocyte differentiation than any other transcription factor [67]. Two isoforms of PPARγ (PPARγ1 and PPARγ2) are generated by the same gene; however, PPARγ1 is expressed in several tissues, whereas PPARγ2 expression is almost restricted to adipose tissue. Even in PPARγ2 knockout mice, an compensatory effect of PPARγ1 is observed [68]. In addition, the inhibition of PPARγ1 blocks adipocyte maturation (hypertrophy) and the expression of C/EBPα [69], suggesting that PPARγ is essential for adipocyte lipid accumulation (Figure 3). In addition to their direct effect on differentiation, PPARγ and C/EBPα can be stimulated by C/EBP-β and C/EBP-δ, factors that are expressed within the earlier phases of differentiation [65]. Additional factors that are present in parallel pathways are involved in PPAR-γ and C/EBPs regulation, such as sterol regulatory element-binding protein-1c (SREBP-1c). Furthermore, SREBP-1c is an important regulator of lipogenic enzymes such as ACC and FAS, and it controls the expression of PPARγ through the induction of endogenous ligand [70]. The insulin stimulation of 3T3-L1 preadipocytes significantly enhances SREBP-1c expression [70], whereas, ectopic expression of dominant-negative SREBP-1c has been shown to suppress differentiation through the regulation of genes involved in cholesterol homeostasis, fatty acid synthesis, and key enzymes involved in glycerolipid synthesis [71]. Ho et al. showed that extracts of GBR or BR down-regulated the expression of C/EBP-β, C/EBP-α, PPARγ, and SREBP-1c [19]. These data suggest that the bioactive compounds present in BR can control adipocytes differentiation. However, which compounds were present in the extract, and which accounted for anti-adipogenic effects, have not been defined. In contrast, Jung et al. showed that Orz induced 3T3-L1 cell differentiation into adipocytes by stimulating PPAR-γ and C/EBPα protein expression [72]. The results presented in the same study suggests that the differentiation of preadipocyte to adipocyte is induced by Orz and dependent of mammalian target of rapamycin complex 1 (mTORC1), which in turn can activate PPAR-γ [72]. The exactly participation of Orz in adipocyte differentiation has not been fully explained; however, this process seems to be strictly associated with ROS production [53], and an effective mechanism of action can be induced by the direct repression of transcription factors and/or ROS scavenging. Important molecules involved in adipocytes maturation (hypertrophy) are glycerol-3-phosphate dehydrogenase (GPDH) [73] and fatty acid binding protein 4 (FABP4/aP2) [74]. Elevated GPDH in the adipose tissues is related to the increased synthesis of triacylglycerol [75]. However, the fatty acids used for glycerol 3-phosphate esterification must be derived from circulating lipoproteins and/or from food [75]. Extracts of GBR were associated with decreased GPDH activity in 3T3-L1 cells [19]. By blocking PPARγ and C/EBPs expression, or by decreasing GPDH activity, Orz is able to directly influence in lipid accumulation and fat mass expansion, which are characteristics of adipocyte hypertrophy (Figure 3). FABP4 is constantly released from the adipocytes and plays a crucial role in fatty acid uptake. Insulin secretion inhibits FABP4 release; it then coordinates lipid accumulation during adipocytes maturation [74]. FAS is a homodimeric enzyme responsible for the endogenous synthesis of fatty acids, which play a central role in the regulation of body weight and obesity [76]. In normal conditions, FAS converts excess carbohydrates into fatty acids, and they are then esterified to storage triacylglycerols. However, in situations of metabolic disorders as cancer [77] and obesity [76], FAS can be found in deregulated levels. Increased FAS expression in adipose tissue is linked with increased energy intake [76]. In 3T3-L1 cells being differentiated into adipocytes, both GBR and possibly Orz have shown interesting anti-adipogenic activities by decreasing the mRNA expression of FAS [19]. In the literature there are few articles that have investigated, in isolation, the anti-obesity effects of Orz or its metabolites. Nevertheless, the application of GBR and/or BR extract to assess this effect allows one to extrapolate some effects to Orz, particularly since this compound is certainly what differentiates between those health benefits that are attributed to rice and those not found in others grains. 5. γ-Oryzanol and Inflammation The Orz components may be useful to prevent the installation of inflammatory process in allergic reaction, since the non-polar structure of cycloartenyl ferulate proved to be capable of sequestering the immunoglobulin E and inhibit the allergic reaction mediated by mast cell degranulation [78]. There are several health benefits attributed to Orz due to its anti-inflammatory and antioxidant activities. The presence of inflammation increases ROS production inside the cell, either through NADPH oxidase or the mitochondrial electron transport chain [79]. These reactive molecules are directly related to the progression of inflammatory processes, as they induce cell injury and/or lead to the activation of redox-sensitive transcription factors (Figure 4). Some ROS arising from the plasma or organelles membrane can influence transcription by regulating the phosphorylation of transcription factors, whereas ROS arising from the perinuclear mitochondria or from a nuclear flavoenzyme can participate in transcriptional control by directly targeting DNA [23]. In addition, inflammation can be exacerbated by an ER folding process (which produces ROS), or by a disruption in this process, leading to unfold protein release and cell damage [80]. Among the transcription factors, nuclear factor-kappa B (NF-κB) is involved in the regulation of proinflammatory genes, which represents a key step in the production of proinflammatory cytokines such as tumor necrosis factor-α (TNF-α), IL-1β, IL-6, and IL-8 [81]. The role of Orz in regulating these cytokines was verified in an experimental model of colitis. Significant reductions in the mRNA expression of TNF-α, IL-1β, IL-6, and cyclooxigenase-2 were observed in mice treated with Orz. The same author described a reduction in the tissue infiltration of inflammatory cells [18]. NF-κB is a member of the Rel family of proteins that can form homodimers or heterodimers. The activity of NF-κB is regulated by inhibitory IκB proteins [81]. Inflammatory or redox cell stimulation induces the IκB kinase (IKK) pathway and results in a cascade of activations, such as MAP kinase, c-Jun amino-terminal kinases (JNK), and TNF receptor associated factor 1 (TRAF1) and 2 (TRAF2) [82]. NF-κB is trapped in the cytoplasm in stimulated cells and it is translocated into the nucleus following the presence of stimuli that include oxidative stress [82]. Interestingly, Islam et al. (2009) reported that phytosteryl ferulates of Orz were able to inhibit the nuclear translocation of NF-κB in LPS-stimulated RAW 264.7 macrophages. The exact mechanism that allows Orz or its metabolites to inhibit NF-κB activity remains unclear; however, this inhibition appears to be induced by scavenging ROS or blocking molecules that active transcription factors such as TNF-α, IL-1β, IL-6, and cyclooxigenase-2 (Figure 4). 6. Conclusions Orz plays an important role, at least in part, in preventing some lifestyle diseases related to oxidative stress and high fat intake. Before attributing some organ-specific effects to Orz, it is necessary to consider its variable uptake by cells, as well as its interactions with the transcription factors, ROS, and proteins/enzymes involved in specific health disorders. Orz’s radical scavenging capacity triggers a complex network of interactions and culminates in organ-cell specific responses. These interactions are related to reducing the processes involved in ER stress, lipid intake, and peroxidation, as well as those related to improved glucose metabolism. Orz has attracted attention as a functional food with several beneficial interactions in organism, particularly given its antioxidant, anti-obesity, and anti-inflammatory properties, as well as its ability to improve insulin resistance and hepatic metabolism. All of these disorders exhibit a characteristic redox imbalance. However, it is certainly clear that much more research is required to recognize how Orz and its metabolites are required (and used) by organs or cells when they occur in association. Acknowledgments English-language editing of this manuscript was provided by Journal Prep. The authors gratefully acknowledge the financial support from the “Conselho Nacional de Desenvolvimento Científico e Tecnológico” (CNPq) (Project No. 478372/2013-2; 305177/2015-0). Author Contributions Igor Otavio Minatel and Giuseppina Pace Pereira Lima decided the topics, analyzed literature, designed and wrote the manuscript. Igor Otavio Minatel created the figures. Fabiane Valentini Francisqueti and Camila Renata Corrêa, helped to wrote and revised the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Molecular structures of the four main γ-oryzanol (Orz)’s components (1–4). Chemical structures are composed by ferulic acid and steryl ferulates (gray background). (1) cycloartenyl ferulate; (2) 24-methylenecycloartanyl ferulate; (3) campesteryl ferulate; and (4) sitosteryl ferulate. In the human body, Orz can be metabolized to (5) ferulic acid, and steryl ferulates closely similar to (6) cholesterol. Figure 2 Synergic interaction of Orz with organs-organelles. Endoplasmic reticulum (ER) stress results in misfolded protein accumulation and leads to pancreatic β-cell death by apoptosis. Orz decreases the expression of ER stress-responsive genes Ddit3, Dnajb9 and Xbp1s, and it consequently enhances β-cell insulin production. In addition, Orz improves the adipocyte production of adiponectin. Increased levels of insulin and adiponectin can activate 5′-AMP-activated protein kinase (AMPK) (via AdipoR1), which reduces the expression of phosphoenolpyruvate carboxykinase (PEPCK) and G6Pase, and inhibits gluconeogenesis. Furthermore, AMPK induces β-isoform of coenzyme A carboxylase (ACC-β) phosphorylation, which inhibits acetyl coenzyme A carboxylase (ACC) and results in increased fatty-acid oxidation. Full-length adiponectin activates peroxisome proliferator-activated receptors (PPAR-α) (via AdipoR2) and, thereby stimulating fatty-acid oxidation and decreasing triglyceride content in the tissues. Figure 3 Steps of adipocytes differentiation and the possible effects of Orz. Adipose tissue stem cells (ASCs) are induced to differentiate into mature adipocytes through a complex network of signals. PPARγ and C/EBPα are the major regulators of this differentiation. By blocking PPARγ and C/EBPs expression, Orz exerts a direct influence on adipocytes differentiation. Immature adipocytes require lipid uptake, and Orz reduces the activities of glycerol-3-phosphate dehydrogenase (GPDH), fatty acid synthase (FAS), fatty acid binding protein 4 (Fabp4) and sterol regulatory element-binding protein-1c (SREBP-1c). This complex network is likely associated with systemic reduced insulin resistance, as well as to ameliorated ER stress and improved adiponectin secretion, as induced by Orz and its metabolites. Figure 4 Signaling mechanisms of ROS-mediated nuclear factor kappa-B (NF-κB) activation. Inflammatory stimuli (proinflammatory cytokines, oxidative stress, etc.), and ROS produced by mitochondria, NADPH oxidase, and the endoplasmic reticulum triggers those kinase pathways that results in NF-κB activation. NF-κB can then translocate to the nucleus and induces target gene transcription, such as TNF-α, IL-1β, IL-6, and IL-8. Orz can reduce inflammation by scavenging ROS and consequently inhibiting the NF-κB pathways. ==== Refs References 1. Tuncel N.B. Yılmaz N. γ-oryzanol content, phenolic acid profiles and antioxidant activity of rice milling fractions Eur. Food Res. Technol. 2011 233 577 585 10.1007/s00217-011-1551-4 2. Minatel I.O. Han S.-I. Aldini G. Colzani M. Matthan N.R. Correa C.R. Fecchio D. Yeum K.-J. Fat-soluble bioactive components in colored rice varieties J. Med. Food 2014 17 1134 1141 10.1089/jmf.2014.3146 25162990 3. Wu F. Yang N. Touré A. Jin Z. Xu X. Germinated brown rice and its role in human health Crit. Rev. Food Sci. Nutr. 2013 53 451 463 10.1080/10408398.2010.542259 23391013 4. Kiing S.C. Yiu P.H. Rajan A. Wong S.C. Effect of germination on γ-oryzanol content of selected sarawak rice cultivars Am. J. Appl. Sci. 2009 6 1658 1661 10.3844/ajassp.2009.1658.1661 5. Xu Z. Godber J.S. Purification and identification of components of γ-oryzanol in rice bran oil J. Agric. Food Chem. 1999 47 2724 2728 10.1021/jf981175j 10552553 6. Lerma-García M.J. Herrero-Martínez J.M. Simó-Alfonso E.F. Mendonça C.R.B. Ramis-Ramos G. Composition, industrial processing and applications of rice bran γ-oryzanol Food Chem. 2009 115 389 404 10.1016/j.foodchem.2009.01.063 7. Norton R.A. Quantitation of steryl ferulate and p -coumarate esters from corn and rice Lipids 1995 30 269 274 10.1007/BF02537832 7791537 8. Fang N. Yu S. Badger T.M. Characterization of triterpene alcohol and sterol ferulates in rice bran using LC-MS/MS J. Agric. Food Chem. 2003 51 3260 3267 10.1021/jf021162c 12744652 9. Bao Y. Yanase E. Nakatsuka S. Isolation of campesteryl ferulate and epi-campesteryl ferulate, two components of γ-oryzanol from rice bran Biosci. Biotechnol. Biochem. 2013 77 877 879 10.1271/bbb.120938 23563552 10. Kim H.W. Kim J.B. Shanmugavelan P. Kim S.N. Cho Y.S. Kim H.R. Lee J.-T. Jeon W.-T. Lee D.J. Evaluation of γ-oryzanol content and composition from the grains of pigmented rice-germplasms by LC-DAD-ESI/MS BMC Res. Notes 2013 6 149 10.1186/1756-0500-6-149 23587158 11. Szcześniak K.A. Ostaszewski P. Ciecierska A. Sadkowski T. Investigation of nutriactive phytochemical—γ-oryzanol in experimental animal models J. Anim. Physiol. Anim. Nutr. (Berl.) 2015 10.1111/jpn.12428 12. Berger A. Rein D. Schäfer A. Monnard I. Gremaud G. Lambelet P. Bertoli C. Similar cholesterol-lowering properties of rice bran oil, with varied γ-oryzanol, in mildly hypercholesterolemic men Eur. J. Nutr. 2005 44 163 173 10.1007/s00394-004-0508-9 15309429 13. Ikonen E. Cellular cholesterol trafficking and compartmentalization Nat. Rev. Mol. Cell Biol. 2008 9 125 138 10.1038/nrm2336 18216769 14. Jin Son M. Rico C.W. Hyun Nam S. Young Kang M. Influence of oryzanol and ferulic acid on the lipid metabolism and antioxidative status in high fat-fed mice J. Clin. Biochem. Nutr. 2010 46 150 156 10.3164/jcbn.09-98 20216948 15. Wang O. Liu J. Cheng Q. Guo X. Wang Y. Zhao L. Zhou F. Ji B. Effects of ferulic acid and γ-oryzanol on high-fat and high-fructose diet-induced metabolic syndrome in rats PLoS ONE 2015 10 1 14 10.1371/journal.pone.0118135 25646799 16. Shimabukuro M. Higa M. Kinjo R. Yamakawa K. Tanaka H. Kozuka C. Yabiku K. Taira S.-I. Sata M. Masuzaki H. Effects of the brown rice diet on visceral obesity and endothelial function: The BRAVO study Br. J. Nutr. 2014 111 310 320 10.1017/S0007114513002432 23930929 17. Xu Z. Hua N. Godber J.S. Antioxidant activity of tocopherols, tocotrienols, and γ-oryzanol components from rice bran against cholesterol oxidation accelerated by 2,2′-azobis(2-methylpropionamidine) dihydrochloride J. Agric. Food Chem. 2001 49 2077 2081 10.1021/jf0012852 11308370 18. Islam M.S. Murata T. Fujisawa M. Nagasaka R. Ushio H. Bari A.M. Hori M. Ozaki H. Anti-inflammatory effects of phytosteryl ferulates in colitis induced by dextran sulphate sodium in mice Br. J. Pharmacol. 2008 154 812 824 10.1038/bjp.2008.137 18536734 19. Ho J.-N. Son M.-E. Lim W.-C. Lim S.-T. Cho H.-Y. Germinated brown rice extract inhibits adipogenesis through the down-regulation of adipogenic genes in 3T3-L1 adipocytes Plant Foods Hum. Nutr. 2013 68 274 278 10.1007/s11130-013-0366-9 23907589 20. Kozuka C. Yabiku K. Takayama C. Matsushita M. Shimabukuro M. Natural food science based novel approach toward prevention and treatment of obesity and type 2 diabetes: Recent studies on brown rice and γ-oryzanol Obes. Res. Clin. Pract. 2013 7 e165 e172 10.1016/j.orcp.2013.02.003 23697584 21. Ardiansyah Shirakawa H. Koseki T. Ohinata K. Hashizume K. Komai M. Rice bran fractions improve blood pressure, lipid profile, and glucose metabolism in stroke-prone spontaneously hypertensive rats J. Agric. Food Chem. 2006 54 1914 1920 10.1021/jf052561l 16506853 22. Gorrini C. Harris I.S. Mak T.W. Modulation of oxidative stress as an anticancer strategy Nat. Rev. Drug Discov. 2013 12 931 947 10.1038/nrd4002 24287781 23. Nathan C. Cunningham-Bussel A. Beyond oxidative stress: An immunologist’s guide to reactive oxygen species Nat. Rev. Immunol. 2013 13 349 361 10.1038/nri3423 23618831 24. Miller E.R. Appel L.J. Risby T.H. Effect of dietary patterns on measures of lipid peroxidation: Results from a randomized clinical trial Circulation 1998 98 2390 2395 10.1161/01.CIR.98.22.2390 9832483 25. Son M.J. Rico C.W. Nam S.H. Kang M.Y. Effect of oryzanol and ferulic acid on the glucose metabolism of mice fed with a high-fat diet J. Food Sci. 2011 76 4 7 10.1111/j.1750-3841.2010.01907.x 21535685 26. Islam M.S. Yoshida H. Matsuki N. Ono K. Nagasaka R. Ushio H. Guo Y. Hiramatsu T. Hosoya T. Murata T. Antioxidant, free radical–scavenging, and NF-κB–inhibitory activities of phytosteryl ferulates: Structure–activity studies J. Pharmacol. Sci. 2009 111 328 337 10.1254/jphs.09146FP 19942803 27. Cuvelier M.-E. Richard H. Berset C. Comparison of the antioxidative activity of some acid-phenols: Structure-activity relationship Biosci. Biotechnol. Biochem. 1992 56 324 325 10.1271/bbb.56.324 28. Kaynar H. Meral M. Turhan H. Keles M. Celik G. Akcay F. Glutathione peroxidase, glutathione-S -transferase, catalase, xanthine oxidase, Cu–Zn superoxide dismutase activities, total glutathione, nitric oxide, and malondialdehyde levels in erythrocytes of patients with small cell and non-small cell lung cancer Cancer Lett. 2005 227 133 139 10.1016/j.canlet.2004.12.005 16112416 29. Aoyama K. Nakaki T. Impaired glutathione synthesis in neurodegeneration Int. J. Mol. Sci. 2013 14 21021 21044 10.3390/ijms141021021 24145751 30. Berndt C. Lillig C.H. Flohé L. Redox regulation by glutathione needs enzymes Front. Pharmacol. 2014 5 168 10.3389/fphar.2014.00168 25100998 31. Board P.G. Menon D. Glutathione transferases, regulators of cellular metabolism and physiology Biochim. Biophys. Acta 2013 1830 3267 3288 10.1016/j.bbagen.2012.11.019 23201197 32. Abou-Sleiman P.M. Muqit M.M.K. Wood N.W. Expanding insights of mitochondrial dysfunction in Parkinson’s disease Nat. Rev. Neurosci. 2006 7 207 219 10.1038/nrn1868 16495942 33. Araujo S.M. de Paula M.T. Poetini M.R. Meichtry L. Bortolotto V.C. Zarzecki M.S. Jesse C.R. Prigol M. Effectiveness of γ-oryzanol in reducing neuromotor deficits, dopamine depletion and oxidative stress in a Drosophila melanogaster model of Parkinson’s disease induced by rotenone Neurotoxicology 2015 51 96 105 10.1016/j.neuro.2015.09.003 26366809 34. Madar Z. Effect of brown rice and soybean dietary fiber on the control of glucose and lipid metabolism in diabetic rats Am. J. Clin. Nutr. 1983 38 388 393 6310982 35. Kozuka C. Yabiku K. Sunagawa S. Ueda R. Taira S.I. Ohshiro H. Ikema T. Yamakawa K. Higa M. Tanaka H. Brown rice and its component, γ-oryzanol, attenuate the preference for high-fat diet by decreasing hypothalamic endoplasmic reticulum stress in mice Diabetes 2012 61 3084 3093 10.2337/db11-1767 22826028 36. Sun Q. Spiegelman D. van Dam R.M. Holmes M.D. Malik V.S. Willett W.C. Hu F.B. White rice, brown rice, and risk of type 2 diabetes in US men and women Arch. Intern. Med. 2010 170 961 969 10.1001/archinternmed.2010.109 20548009 37. Yamauchi T. Kamon J. Minokoshi Y. Ito Y. Waki H. Uchida S. Yamashita S. Noda M. Kita S. Ueki K. Adiponectin stimulates glucose utilization and fatty-acid oxidation by activating AMP-activated protein kinase Nat. Med. 2002 8 1288 1295 10.1038/nm788 12368907 38. Combs T.P. Berg A.H. Obici S. Scherer P.E. Rossetti L. Endogenous glucose production is inhibited by the adipose-derived protein Acrp30 J. Clin. Investig. 2001 108 1875 1881 10.1172/JCI14120 11748271 39. Ohara K. Kiyotani Y. Uchida A. Nagasaka R. Maehara H. Kanemoto S. Hori M. Ushio H. Oral administration of γ-aminobutyric acid and γ-oryzanol prevents stress-induced hypoadiponectinemia Phytomedicine 2011 18 655 660 10.1016/j.phymed.2011.01.003 21316207 40. Barthel A. Schmoll D. Novel concepts in insulin regulation of hepatic gluconeogenesis Am. J. Physiol. Endocrinol. Metab. 2003 285 E685 E692 10.1152/ajpendo.00253.2003 12959935 41. O’Brien R.M. Granner D.K. Regulation of gene expression by insulin Physiol. Rev. 1996 76 1109 1161 10.1042/bj2780609 8874496 42. Lochhead P.A. Salt I.P. Walker K.S. Hardie D.G. Sutherland C. 5-aminoimidazole-4-carboxamide riboside mimics the effects of insulin on the expression of the 2 key gluconeogenic genes PEPCK and glucose-6-phosphatase Diabetes 2000 49 896 903 10.2337/diabetes.49.6.896 10866040 43. Salvadó L. Palomer X. Barroso E. Vázquez-Carrera M. Targeting endoplasmic reticulum stress in insulin resistance Trends Endocrinol. Metab. 2015 26 438 448 10.1016/j.tem.2015.05.007 26078196 44. Kozuka C. Sunagawa S. Ueda R. Higa M. Tanaka H. Shimizu-Okabe C. Ishiuchi S. Takayama C. Matsushita M. Tsutsui M. γ-Oryzanol protects pancreatic β-cells against endoplasmic reticulum stress in male mice Endocrinology 2015 156 1242 1250 10.1210/en.2014-1748 25594697 45. Yamauchi T. Nio Y. Maki T. Kobayashi M. Takazawa T. Iwabu M. Okada-Iwabu M. Kawamoto S. Kubota N. Kubota T. Targeted disruption of AdipoR1 and AdipoR2 causes abrogation of adiponectin binding and metabolic actions Nat. Med. 2007 13 332 339 10.1038/nm1557 17268472 46. Kadowaki T. Yamauchi T. Adiponectin and adiponectin receptors Endocr. Rev. 2005 26 439 451 10.1210/er.2005-0005 15897298 47. Ng M. Fleming T. Robinson M. Thomson B. Graetz N. Margono C. Mullany E.C. Biryukov S. Abbafati C. Abera S.F. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: A systematic analysis for the Global Burden of Disease Study 2013 Lancet (London, England) 2014 384 766 781 10.1016/S0140-6736(14)60460-8 48. Malik V.S. Willett W.C. Hu F.B. Global obesity: Trends, risk factors and policy implications Nat. Rev. Endocrinol. 2013 9 13 27 10.1038/nrendo.2012.199 23165161 49. WHO/FAO Diet, nutrition and the prevention of chronic diseases Public Health Nutr. 2004 7 99 250 Available online: http://www.who.int/nutrition/publications/obesity/PHNvol7no1afeb2004/en/ (accessed on 26 June 2016) 50. Anderson J.W. Baird P. Davis R.H. Ferreri S. Knudtson M. Koraym A. Waters V. Williams C.L. Health benefits of dietary fiber Nutr. Rev. 2009 67 188 205 10.1111/j.1753-4887.2009.00189.x 19335713 51. Li J. Kaneko T. Qin L.-Q. Wang J. Wang Y. Sato A. Long-term effects of high dietary fiber intake on glucose tolerance and lipid metabolism in GK rats: Comparison among barley, rice, and cornstarch Metabolism 2003 52 1206 1210 10.1016/S0026-0495(03)00159-8 14506628 52. Gregório B.M. de Souza D.B. Nascimento F.A.M. Matta L. Fernandes-Santos C.F. The potential role of antioxidants in metabolic syndrome Curr. Pharm. Des. 2016 22 859 869 10.2174/1381612822666151209152352 26648468 53. Rani V. Deep G. Singh R.K. Palle K. Yadav U.C.S. Oxidative stress and metabolic disorders: Pathogenesis and therapeutic strategies Life Sci. 2016 148 183 193 10.1016/j.lfs.2016.02.002 26851532 54. Mandak E. Nyström L. The effect of in vitro digestion on steryl ferulates from rice (Oryza sativa L.) and other grains J. Agric. Food Chem. 2012 60 6123 6130 10.1021/jf300781a 22607464 55. Rong N. Ausman L.M. Nicolosi R.J. Oryzanol decreases cholesterol absorption and aortic fatty streaks in hamsters Lipids 1997 32 303 309 10.1007/s11745-997-0037-9 9076667 56. Lagiou P. Løvik M. Marchelli R. Martin A. Moseley B. Plant stanols and plant sterols and blood LDL-cholesterol EFSA J. 2009 1 9 10.2903/j.efsa.2009.1175 57. Demonty I. Ras R.T. van der Knaap H.C.M. Duchateau G.S.M.J.E. Meijer L. Zock P.L. Geleijnse J.M. Trautwein E.A. Continuous dose-response relationship of the LDL-cholesterol-lowering effect of phytosterol intake J. Nutr. 2008 139 271 284 10.3945/jn.108.095125 19091798 58. Katan M.B. Grundy S.M. Jones P. Law M. Miettinen T. Paoletti R. Efficacy and safety of plant stanols and sterols in the management of blood cholesterol levels Mayo Clin. Proc. 2003 78 965 978 10.1016/S0025-6196(11)63144-3 12911045 59. Hamada T. Goto H. Yamahira T. Sugawara T. Imaizumi K. Ikeda I. Solubility in and affinity for the bile salt micelle of plant sterols are important determinants of their intestinal absorption in rats Lipids 2006 41 551 556 10.1007/s11745-006-5004-y 16981433 60. Brown A.W. Hang J. Dussault P.H. Carr T.P. Plant sterol and stanol substrate specificity of pancreatic cholesterol esterase J. Nutr. Biochem. 2010 21 736 740 10.1016/j.jnutbio.2009.04.008 19615880 61. Ozcan L. Ergin A.S. Lu A. Chung J. Sarkar S. Nie D. Myers M.G. Ozcan U. Endoplasmic reticulum stress plays a central role in development of leptin resistance Cell Metab. 2009 9 35 51 10.1016/j.cmet.2008.12.004 19117545 62. Kwon O. Kim K.W. Kim M.-S. Leptin signalling pathways in hypothalamic neurons Cell. Mol. Life Sci. 2016 73 1457 1477 10.1007/s00018-016-2133-1 26786898 63. Ozcan U. Cao Q. Yilmaz E. Lee A.-H. Iwakoshi N.N. Ozdelen E. Tuncman G. Görgün C. Glimcher L.H. Hotamisligil G.S. Endoplasmic reticulum stress links obesity, insulin action, and type 2 diabetes Science 2004 306 457 461 10.1126/science.1103160 15486293 64. Ozcan U. Yilmaz E. Ozcan L. Furuhashi M. Vaillancourt E. Smith R.O. Görgün C.Z. Hotamisligil G.S. Chemical chaperones reduce ER stress and restore glucose homeostasis in a mouse model of type 2 diabetes Science 2006 313 1137 1140 10.1126/science.1128294 16931765 65. Farmer S.R. Transcriptional control of adipocyte formation Cell Metab. 2006 4 263 273 10.1016/j.cmet.2006.07.001 17011499 66. Rosen E.D. MacDougald O.A. Adipocyte differentiation from the inside out Nat. Rev. Mol. Cell Biol. 2006 7 885 896 10.1038/nrm2066 17139329 67. Kim S.W. Her S.J. Kim S.Y. Shin C.S. Ectopic overexpression of adipogenic transcription factors induces transdifferentiation of MC3T3-E1 osteoblasts Biochem. Biophys. Res. Commun. 2005 327 811 819 10.1016/j.bbrc.2004.12.076 15649418 68. Zhang J. Fu M. Cui T. Xiong C. Xu K. Zhong W. Xiao Y. Floyd D. Liang J. Li E. Selective disruption of PPARγ 2 impairs the development of adipose tissue and insulin sensitivity Proc. Natl. Acad. Sci. USA 2004 101 10703 10708 10.1073/pnas.0403652101 15249658 69. Zuo Y. Qiang L. Farmer S.R. Activation of CCAAT/enhancer-binding protein (C/EBP) α expression by C/EBP β during adipogenesis requires a peroxisome proliferator-activated receptor-γ-associated repression of HDAC1 at the C/EBP α gene promoter J. Biol. Chem. 2006 281 7960 7967 10.1074/jbc.M510682200 16431920 70. Kim J.B. Wright H.M. Wright M. Spiegelman B.M. ADD1/SREBP1 activates PPARγ through the production of endogenous ligand Proc. Natl. Acad. Sci. USA 1998 95 4333 4337 10.1073/pnas.95.8.4333 9539737 71. Ericsson J. Jackson S.M. Kim J.B. Spiegelman B.M. Edwards P.A. Identification of glycerol-3-phosphate acyltransferase as an adipocyte determination and differentiation factor 1- and sterol regulatory element-binding protein-responsive gene J. Biol. Chem. 1997 272 7298 7305 10.1074/jbc.272.11.7298 9054427 72. Jung C. Lee D.-H. Ahn J. Lee H. Choi W. Jang Y. Ha T.-Y. γ-Oryzanol enhances adipocyte differentiation and glucose uptake Nutrients 2015 7 4851 4861 10.3390/nu7064851 26083118 73. Pairault J. Green H. A study of the adipose conversion of suspended 3T3 cells by using glycerophosphate dehydrogenase as differentiation marker Proc. Natl. Acad. Sci. USA 1979 76 5138 5142 10.1073/pnas.76.10.5138 291926 74. Wu L.E. Samocha-Bonet D. Whitworth P.T. Fazakerley D.J. Turner N. Biden T.J. James D.E. Cantley J. Identification of fatty acid binding protein 4 as an adipokine that regulates insulin secretion during obesity Mol. Metab. 2014 3 465 473 10.1016/j.molmet.2014.02.005 24944906 75. Swierczynski J. Zabrocka L. Enhanced glycerol 3-phosphate dehydrogenase activity in adipose tissue of obese humans Mol. Cell. Biochem. 2003 254 55 59 10.1023/A:1027332523114 14674682 76. Berndt J. Kovacs P. Ruschke K. Klöting N. Fasshauer M. Schön M.R. Körner A. Stumvoll M. Blüher M. Fatty acid synthase gene expression in human adipose tissue: Association with obesity and type 2 diabetes Diabetologia 2007 50 1472 1480 10.1007/s00125-007-0689-x 17492427 77. Menendez J.A. Lupu R. Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis Nat. Rev. Cancer 2007 7 763 777 10.1038/nrc2222 17882277 78. Oka T. Fujimoto M. Nagasaka R. Ushio H. Hori M. Ozaki H. Cycloartenyl ferulate, a component of rice bran oil-derived γ-oryzanol, attenuates mast cell degranulation Phytomedicine 2010 17 152 156 10.1016/j.phymed.2009.05.013 19577449 79. Mittal M. Siddiqui M.R. Tran K. Reddy S.P. Malik A.B. Reactive oxygen species in inflammation and tissue injury Antioxid. Redox Signal. 2014 20 1126 1167 10.1089/ars.2012.5149 23991888 80. Zhang K. Kaufman R.J. From endoplasmic-reticulum stress to the inflammatory response Nature 2008 454 455 462 10.1038/nature07203 18650916 81. Gilmore T.D. Introduction to NF-κB: Players, pathways, perspectives Oncogene 2006 25 6680 6684 10.1038/sj.onc.1209954 17072321 82. Kabe Y. Ando K. Hirao S. Yoshida M. Handa H. Redox regulation of NF-κB activation: Distinct redox regulation between the cytoplasm and the nucleus Antioxid. Redox Signal. 2005 7 395 403 10.1089/ars.2005.7.395 15706086

PMC005xxxxxx/PMC5000586.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081130ijms-17-01130ArticleInfluences of Electromagnetic Energy on Bio-Energy Transport through Protein Molecules in Living Systems and Its Experimental Evidence Pang Xiaofeng 1*Chen Shude 2Wang Xianghui 2Zhong Lisheng 3Bacchus Marie-Christine Academic Editor1 Institute of Physical Electrons, University of Electronic Science and Technology of China, Chengdu 610054, China2 Department of Physics, East China Normal University, Shanghai 200062, China; sdchen@phy.ecnu.edu.cn (S.C.); xhwang@phy.ecnu.edu.cn (X.W.)3 State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, China; lszhong@mail.xjtu.edu.cn* Correspondence: pangxf2006@aliyun.com; Tel.: +86-28-8527-329325 7 2016 8 2016 17 8 113016 1 2016 27 6 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).The influences of electromagnetic fields (EMFs) on bio-energy transport and its mechanism of changes are investigated through analytic and numerical simulation and experimentation. Bio-energy transport along protein molecules is performed by soliton movement caused by the dipole–dipole electric interactions between neighboring amino acid residues. As such, EMFs can affect the structure of protein molecules and change the properties of the bio-energy transported in living systems. This mechanism of biological effect from EMFs involves the amino acid residues in protein molecules. To study and reveal this mechanism, we simulated numerically the features of the movement of solitons along protein molecules with both a single chain and with three channels by using the Runge–Kutta method and Pang’s soliton model under the action of EMFs with the strengths of 25,500, 51,000, 76,500, and 102,000 V/m in the single-chain protein, as well as 17,000, 25,500, and 34,000 V/m in the three-chain protein, respectively. Results indicate that electric fields (EFs) depress the binding energy of the soliton, decrease its amplitude, and change its wave form. Also, the soliton disperses at 102,000 V/m in a single-chain protein and at 25,500 and 34,000 V/m in three-chain proteins. These findings signify that the influence of EMFs on the bio-energy transport cannot be neglected; however, these variations depend on both the strength and the direction of the EF in the EMF. This direction influences the biological effects of EMF, which decrease with increases in the angle between the direction of the EF and that of the dipole moment of amino acid residues; however, randomness at the macroscopic level remains. Lastly, we experimentally confirm the existence of a soliton and the validity of our conclusion by using the infrared spectra of absorption of the collagens, which is activated by another type of EF. Thus, we can affirm that both the described mechanism and the corresponding theory are correct and that EMFs or EFs can influence the features of energy transport in living systems and thus have certain biological effects. electromagnetic energydipole–dipole interactionprotein moleculesolitoncollagenbio-energy transport mechanism ==== Body 1. Introduction Prevalent in our environment, electromagnetic fields (EMFs) or waves (EMWs) of varying frequencies and strengths are generated by such sources as the irradiations of high-voltage transmission lines, electrical appliances, microwave stations, and radio equipment. As such, it is necessary to understand whether these externally applied EMFs, EMWs, or electric fields (EFs) have any biological effects on animals and humans [1,2]. Much research has focused on determining any relationship between EMFs and biological processes [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]. Li et al. [10,11,12,13,14,15] studied the biologic effects of environmental EMFs, observing the variations of the dielectric constant and conductivity and absorbed strength of infrared light of bio-tissues as well as of the rheology features of the blood in animals under the influences of different electromagnetic fields relative to those without electromagnetic fields. Zhang et al. [16,17] measured the expression of matrix metalloproteinase and tight-junction proteins in rats by following a pulse EMF at high frequencies, which induced blood–brain barrier permeability changes, and also studied the effects of a pulse EMF with high frequencies on the fluorescence spectrum of serum in the rats. Beebe et al. [18] studied the nanosecond pulsed electric field effect on cell growth and the development of bio-tissues, as well as apoptosis induction and tumor growth inhibition. Lazzaro et al. [19] and Apollonio et al. [20] discussed the feasibility of microwave energy affecting biological systems via nonthermal mechanisms and offered systematic approaches, respectively. Hofmann et al. [21] investigated the possibility of electroporation therapy for head and neck cancer. Kekez et al. [22] researched contributions to the biophysics of lethal effects of EFs on microorganisms. Pang et al. [23] investigated and discussed the mechanism and properties of biological thermal effects of microwaves and noted that microwaves can influence the proliferations of cells and tissues. These results indicated that EMFs and EFs have certain biological effects. Although animals or humans are not measurably affected by EMFs unless they come in close contact with high-voltage transmission lines, research should focus more on the proliferation of microwaves and radio waves and their influences on health. Hence, the biological effects of these influences on the health of human beings merit examination. Only a few conclusions supporting the theory that EMFs and EFs containing microwave radio waves have biological effects have been accepted. Because of varying types of research and instrumentation, experimental results for the same questions range considerably. Thus, a widely accepted and unified conclusion is difficult to acquire, and the mechanism of influence of EMFs on life activity has not been revealed or elucidated [1,2,3]. However, epidemiological investigations have shown that EMFs, including microwaves, radio waves, and those from high-voltage transmission lines, have always had adverse effects on health [3,4,5,6,7,8,9,10,11,12,13,14,15,16]. Therefore, the influence of EMFs on the health of human beings and animals cannot be dismissed. The rapidly increasing usage of electrical appliances, microwave instruments, cell phones, and other electromagnetic devices has led to expansive distribution of EMFs in our environment. In this case, it is necessary to study and release the biological effects of EMFs and their influences on the health of human beings and animals. This need suggests that investigations should focus on the biological effects of EMFs—in particular, the mechanisms in depth through the latest ideas and methods in theoretical analyses and experimental measurements. One key issue would be to analyze and investigate the electromagnetic properties of biotissues and biomacromolecules and the distributions and properties of charged groups, or atoms and molecules, as well as any variations under the influence of externally applied EMFs. Examination of these charged particles, molecules, or species, as well as their properties of movement, could lead to a better understanding of biological mechanisms under the effect of EMFs. In practice, these charged particles, molecules, or species exist widely in cells and biomacromolecules, such as protein and DNA [9,24], upon which the externally applied EMF can influence their biological processes and properties, and any biological effects can also be exhibited clearly. In this paper, we first seek any mechanism of biological effect from EMFs and EFs. Energy transport, released from the hydrolysis reaction of adenosine triphosphate (ATP) molecules along the protein molecules, is a typical target that exemplifies this described mechanism; i.e., EMFs can disturb and influence energy transport considerably through its interaction with the amino acid residues with certain electric dipole moments. Here we reveal the mechanism of influence of EMFs on energy transport in protein molecules and further study the properties of this mechanism. 2. Theories of Energy Transport in Protein Molecules and the Mechanism of Influence of EFs on Transport 2.1. Davydov’s Theory of Energy Transport and Its Features Energy in living systems comes mainly from the hydrolysis reaction of ATP molecules, which is denoted [9,24] by ATP4−+H2O→ADP3−+HPO42−+H++0.43eV where ADP is adenosine diphosphate. The energy of 0.43 eV released from this chemical reaction is used in many life activities and processes, such as muscle contraction, neuroelectric pulse transfer along the neurolemma, DNA reduplication, and calcium and sodium pumping in cell membranes, which are some basic life processes and activities in life systems. This function suggests clearly that the energy released in this reaction and its transport is related closely to the growth and development of human beings and animals. Thus, most life processes require the release of energy by ATP hydrolysis, with protein molecules playing a key role in energy transport. As it is known, the amino acid molecule consists of an amino group (NH2), a carboxyl group (COOH), and a side group or chain functional group attached to an α-carbon atom, they polymerize to form long chains of residues of …H–N–C=O…H–N–C=O…H–N–C=O…H–N–C=O…, where the dotted lines indicate the hydrogen bond, that constitute the chain structure of protein molecules. When the polypeptide chains have been formed, they can further fold into an α-helix, a β-sheet, and a globular conformation. In an α-helix structure, three chains of hydrogen-bonded peptide groups can be represented approximately along the horizontal direction of the sequence. In this process, the distributions of the positive and negative charges in each amino acid residue change, and most of the amino acid residues are polarized and have certain electric dipole moments. Figure 1 shows a typical structure of an α-helix protein molecule [24,25,26,27,28,29,30,31,32,33], in which the forms of the three polypeptide chains built by hydrogen bonds and amide-I bonds are clearly exhibited. However, questions remain as to how bio-energy is transported into life systems. Although several decades of research have been amassed, in 1971 Davydov proposed the soliton theory. According to this theory, bio-energy transports along the α-helical protein molecules, for which the structure is denoted in Figure 1 [24,25,26,27,28,29,30,31,32,33]. The mechanism of the bio-energy transport can be described as follows. The stretching vibration of C=O bonds(Amide Is) in the amino acid residues in the proteins is affected by energy released from ATP hydrolysis, in which the vibrational quanta, called excitons, and the deformation of amino acid residues also occur simultaneously and influence each other in this case. Thus, the nonlinear coupling interaction between the excitons and the deformation of amino acid residues, that occur in this process, make the excitons self-trap as a soliton, which transports further along the protein molecules in virtue of the dipole–dipole interaction between neighboring amino acid residues. This is a well-known soliton mechanism of energy transport in life systems. Davydov’s theory works in α-helix protein molecules with three channels in Figure 1 [24,25,26,27,28,29,30,31,32,33]. In this case, a biological process of energy transport always occurs from the produced place to the absorbed place in the living system, which is carried out by means of protein molecules such as collagen, myosin, myoglobin, and actin. According to the mechanism of bio-energy transport, Davydov established the theory of bio-energy transport in protein molecules [24,25,26,27,28,29,30,31,32,33], in which Davydov gave the Hamiltonian of the protein molecules, which was represented by (1) HD=∑n[ε0Bn+Bn−J(Bn+Bn+BnBn+)]+∑n[Pn22M+12w(un−un−1)2]+∑n[χ1(un+1−un−1)Bn+Bn]=Hex+Hph+Hint where Bn+(Bn) is the creation (annihilation) operator for an Amide I quantum (exciton) in the site n, un is the displacement operator of amino acid residue at site n, Pn is its conjugate momentum operator, M is the mass of an amino acid residue and M = 1.17 × 10−25 kg in single-protein molecules or 5.73 × 10−25 kg in α-helix proteins with three channels, w is the elastic constant of the protein molecular chains and w = (13–19.5) N/m for single-protein molecules or (39–58.5) N/m for α-helix proteins, χ1 = 6.2 × 10−11 N is a nonlinear coupling parameter and represents the size of the exciton-phonon interaction in this process, ε0 = 0.205 eV is the energy of the Amide I quantum (exciton), J is the dipole–dipole interaction energy between neighboring amino acid residues, J = 1.55 × 10−22 or J = 9.68 × 10−4 eV, and r0 = 4.5 × 10−10 m is the average distance between the neighboring amino acid residues [24,25,26,27,28,29,30,31,32,33]. The wave function of the systems proposed by Davydov [24,25,26,27,28,29] is the form of (2) D2(t)=|φD〉|β(t)〉=∑nφn(t)Bn+exp{−iℏ∑n[βn(t)Pn−πn(t)un]}|0〉 where |0〉=|0〉ex|0〉ph, |0〉ex and |0〉ph are the ground states of the exciton and phonon, respectively, Davydov’s soliton, obtained from Equations (1) and (2) in the semiclassical limit and using the continuum approximation [24,25,26,27,28,29], has the form of (3) φD(x,t)=(uD2)1/2 seach[μDr0(x−x0−vt)]exp{i[ℏv2Jr02(x−x0)−Evt/ℏ]} If, |φD(t)〉=∑nφn(t)Bn+|0〉ex in Equation (2) is an eigenstate of the number operator, N∧=∑nBn+Bn, then the soliton contains only one exciton because N=〈φD(t)|N∧|φD(t)〉=1, i.e., N∧|φD(t)〉=1|φD(t)〉. This finding indicates that the Davydov soliton contains only one excitation, which corresponds to the excited state of a single particle and is localized over a scale of r0/μD; where μD=χ22/(1−s2)wJ,s2=v2/v02, and v0=r0(w/M)1/2; where v0 is the sound speed in the protein molecular chains; v is the velocity of the soliton; and GD=4JμD is its nonlinear interaction energy accepted in this process. This finding shows that Davydov’s soliton is formed through the self-trapping of one exciton and that it has a binding energy EBD=−χ14/3Jw2. These results clearly exhibit that the energy released from the hydrolysis reaction of the ATP molecule promoted the form of a soliton and its transported along the protein molecules in a bell-type solitary wave or a soliton with an invariable amplitude and velocity, as given in Equation (3) [9,27,34]. This finding indicates that the energy cannot be damped and dissipated in the transport process and is significant for biological processes because energy is retained in the transport process due to the feature and essence of the soliton. Thus, these life activities clearly require the soliton. Davydov’s idea yields a compelling picture of the mechanism of energy transport in living systems and has led to extensive research in biophysics [34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73]. However, the issues related to Davydov’s model, including its foundation, accuracy quantum and classical properties, thermal stability, and lifetimes, have been the focus of much research [34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71]. These investigations and discussions focus mainly on the validity of the Davydov theory and the thermal stability of the Davydov soliton at the biological temperature 300 K. Some numerical simulations have indicated that the Davydov soliton is not stable at this temperature [36,37,38,39,40,41,42,43,44,45,46,47]. At the same time, Monte Carlo numerical calculations indicate that the correlation characteristic of soliton-like quasiparticles occurs only at low temperatures [42,43,44], approximately T < 10 K, for widely accepted parameter values. This finding is consistent at a qualitative level with the results of Cottingham et al. [46] and Schweitzer [47]. The latter is a straightforward quantum-mechanical perturbation calculation, in which the lifetime of the Davydov’s soliton is approximately 10−12–10−13 s at 300 K, in which the soliton can transport only over approximately 10 amino acid residues. Therefore, Davydov’s theory is not suitable for protein molecules. In addition, Förner’s investigations showed that Davydov’s soliton is stable only at 40 K and that it disperses completely at higher temperatures [39,40,41,42,43]. These results indicate clearly that Davydov’s soliton is not a real carrier of the energy transport in protein molecules; thus, Davydov’s theory is not appropriate to the systems. This finding demonstrates the necessity of developing new theories of energy transport in living systems. 2.2. Pang’s Theory of Energy Transport and Its Properties On the basis of the difficulties described concerning Davydov’s theory and the results researched by Cruzeiro-Hansson [37,38] and Förner et al. [39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74], we improve Davydov’s model by changing simultaneously the Hamiltonian and the wave function of the systems, in which we added a new coupling interaction of the excitons with the displacement of amino acid residues into the Hamiltonian in Equation (1) and replaced further the Davydov’s wave function of the one-quantum (exciton)excited state in Equation (2) by a quasi-coherent two-quantum state [75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102]. In this case, the representations in Equations (1) and (2) for the single-channel protein molecules are replaced by (4) |Φ(t)〉=|α(t)〉|β(t)〉=1λ[1+∑nαn(t)Bn++12!(∑nαn(t)Bb2)2]|0〉ex×exp{−iℏ∑n[βn(t)Pn−πnun|0〉ph and (5) H=Hex+Hph+Hint=∑n[ε0Bn+Bn−J(Bn+Bn+BnBn+)]+∑n[Pn22M+12w(un−un−1)2]+∑n[χ1(un+1−un−1)Bn+Bn+χ2(un+1−un)(Bn+1+Bn+Bn+Bn+1)] respectively; where the created and annihilated operators of the exciton are represented by Bn+ and Bn, respectively; |0〉ex and |0〉ph are the ground states of the exciton and phonon, respectively; and un and Pn are the displacement and momentum operators of amino acid residue at the site n, respectively. The βn(t)=〈Φ(t)|un|Φ(t)〉, and πn(t)=〈Φ(t)|Pn|Φ(t)〉 are two sets of unknown functions; and λ is a normalization constant. Present nonlinear coupling constants are χ1 and χ2 = (10−15) × 10−11 N, which represent the modulations of the on-site energy and dipole–dipole interaction energy of excitons due to the variations of displacements of amino acid residue in the protein molecules, respectively. Other parameters are same as those in the Davydov‘s model mentioned previously. Using Equations (4) and (5) and working from the Schrödinger equation and the Heisenberg equation, we obtained (6) iℏα.n(t)=ε0αn(t)−J[αn+1(t)+αn−1(t)]+χ1[qn+1(t)−qn−1(t)]αn(t)+χ2[qn+1(t)−qn(t)][αn+1(t)+αn−1(t)]+52{w(t)−12∑mqm(t)πm(t)−π.m(t)q.m(t)]}αn(t) (7) Mq..n(t)=W[qn+1(t)−2qn(t)+qn−1(t)]+2χ1[|αn+1|2−|αn−1(t)|]+2χ2{αn*(t)[αn+1(t)−αn−1(t)]+αn(t)[αn+1*(t)−αn−1*(t)]} In the continuum approximation, we get from Equations (6) and (7) [73,74,75,76,77,78,79,80,81,82,83,84] (8) iℏ∂∂tα(x,t)=R(t)α(x,t)−Jr02∂2∂x2α(x,t)−Gp|α(x,t)|2α(x,t) and (9) M∂2β(x,t)∂t2−wro2∂2β(x,t)∂x2=−4(χ1+χ1)r0∂∂x|α(x,t)|2 where R(t)==ε0−2J+52{W(t)−12∑m[β.n(t)πm(t)−π.n(t)β(t)]}. The soliton solution of Equation (8) is denoted by (10) α(x,t)=(μp2)1/2sech[(μp/r0)(x−x0−vt)]×exp{i[ℏv2Jr02(x−x0)−Evtℏ]} With μP=2(χ1+χ2)2w(1−s2)J and the nonlinear interaction en GP=8(χ1+χ2)2w(1−s2) and s=v/v0. In this case, the energy of the soliton in Equation (10), or the energy transported by the soliton, is obtained by (11) E=<Φ(t)|H|Φ(t)>=1r0∫−∞∞2[Jr02(∂α∂x)2+R|α(x,t)|2−Gp|α(x,t)|4dx+1r0∫−∞∞12[M(∂β(x,t)∂t)2+wr0(∂β(x,t)∂x)2]dx=E0+12Msolv2. The static (rest) energy of the soliton is (12) E0=2(ε0−2J)−8(χ1+χ2)43w3J=Es0+W where W=[2(χ1+χ2)4]/3w2J is the energy of deformation of the amino acid residues. The effective mass of the soliton is (13) Msol=2mex+8(χ1+χ2)4(9s2+2−3s4)3w2J(1−s2)3v02 In such a case, the binding or forming energy of the soliton in Pang’s theory is denoted by (14) EBP=−8(χ1+χ2)43Jw2 These mathematical models clearly indicate that the properties of Pang’s soliton [75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101] differ from those of Davydov’s. Through concrete calculations, we found that Pang’s soliton is thermally stable and has a sufficient lifetime of 10−9–10−10 s at the physiological temperature of 300 K, which is approximately 800× that of Davydov’s soliton (10−12−10−13 s), in which Pang’s soliton can transport more than several hundreds of amino acid residues. Thus, Pang’s soliton plays an important role in the biological processes. The comparison of Pang’s soliton with Davydov’s soliton is given in Table 1, which clearly indicates that Pang’s soliton (or theory) differs considerably from that of Davydov’s soliton (or theory). Since then, the results of Pang’s theory were also confirmed by other studies [75,76,77,78,79,80,81,82,83,84,85,86]. Therefore, Pang’s soliton is a carrier of energy transport, and the Pang’s model can be applied to energy transport in protein molecules [97,101,102,103,104,105,106]. Thus, we here applied the Pang’s model to study the influences of EFs and EMFs on properties of energy transport in α-helical protein molecules (Figure 1). 2.3. Mechanism of Influence of Electric Field on Energy Transport in Protein Molecules Equations (11)–(14) indicate that the properties of the energy transported by the soliton involving its velocity (v), effective mass (Msol), energy (E), and rest energy (E0), which are determined by the features of the exciton, the amino acid residues, and the structure of the protein molecule, including the effective mass of the exciton (mex), the mass of the amino acid residue (M), the elastic constant of the protein molecular chains (w), the nonlinear exciton–phonon interaction coefficients (χ1 and χ2), the Amide I vibrational energy (ε0), the dipole–dipole interaction energy between the neighboring amino acid residues (J), and the distance between the neighboring amino acid residues (r0). This clearly indicates that the properties of the energy transport or the soliton will change once these characteristic parameters of the exciton, amino acid residues, and protein molecule structures are altered under the influences of externally applied electromagnetic or light fields, as well as temperatures. On the basis of these characters and features, we seek the mechanism that influences the EMFs or the EFs on energy transport in protein molecules. As described, energy released from the hydrolysis reaction of the ATP molecules is transported along protein molecules in the solitons by virtue of the dipole–dipole interaction between neighboring amino acid residues with certain electric dipole moments. The externally applied EFs or EMFs can interact with these amino acid residues according to the EMF theory; thus, the properties of the energy transport or movement of soliton will vary, along with the externally applied EFs or EMFs, because the latter can vary the sizes and directions of the dipole–dipole interaction between the neighboring amino acid residues in such a case. Thus, some biological effects arising from the variations of the biological energy in protein molecule will occur correspondingly, which is the influencing mechanism of EMF or EF on the energy transport. In other words, this is a mechanism of biological effect through EMFs or EFs. If we assume that the strength of the EF in the EMF is denoted by E→ and that the electric dipole moments of the amino acid residue in the protein molecules is denoted by p→, then the energy of interaction of the EF or the EMF with the amino acid residues can be denoted by E→.p→, according to the EMF theory [82,87,99]. In such a case, the dipole–dipole interaction energy between neighboring amino acid residues in the protein molecules will be changed from J to J+E→.p→. Then we can affirm that the properties of the energy transported by the soliton will be altered notably because the soliton in Equations (10)–(14) is very sensitive to variations of the dipole–dipole interaction between neighboring amino acid residues. This conclusion will be confirmed by the following results. 3. Variation of Properties of Energy Transport Arising from the EF in Protein Molecules 3.1. Analytic Results for Changes of Properties of the Soliton Transporting the Energy under the Influence of EFs As mentioned previously, when protein molecules are exposed in an EMF or an EF, the dipole–dipole interaction between the neighboring amino acid residues in the protein molecules is changed into J+E→.p→. Then the variation of features of the solitons in Equations (10)–(14) in Pang’s model will appear in this case [75,76,77,78,79,80,81,82,83,84,85,86]. These variations in the soliton from Equations (10)–(14) can be obtained, which are described as follows: (1) The amplitude (μP) effective mass (Msol), energy (E), rest energy (E0), and binding energy EBP of the soliton are decreased and depressed after EF is applied because the physical parameters in Equations (11)–(14) are inversely proportional to the dipole–dipole interactional energy J. This means that the capability and value of the energy transported by the soliton is decreased because of the increases of dipole–dipole interaction between neighboring amino acid residues. If the strength of an EF in an EMF is very high, then the capability and value of the energy transport will depress considerably. In such a case, we could infer and suppose that some new biological effects will occur and that these new biological effects have just arisen from the EF (2) The EF varies the form and outline of the soliton in Equation (10) because the form and outline of the solitary wave, Sech[(μP/r0)(x−x0−vt)]×exp{i[ℏv2Jr02(χ1+χ2)−Evtℏ]}, in Equation (10) and its amplitude of envelope, μP/r0, as well as its phase of the carrier wave, [ℏv2Jr02(x−x0)−Evtℏ], are all changed with the variation of dipole–dipole interaction J under the influenceof EF. These changes arising from EFs will also affect the proliferation of cells and life bodies because of variations in the bio-energy they obtain. (3) The biological effects of EFs closely depend on both strength and direction with respect to the dipole moment of amino acid residues because the externally applied electric-field, E→ and dipole moments of the amino acid residue, p→, all possess a certain strength and direction. In this case, we should consider the direction and strength of the EF, E→, and the dipole moments of the amino acid residue as well as their relationships. Thus, the electromagnetic energy of interaction between them should be represented by E→.p→=|E→||p→|cosθ, where θ is the angle between the two vectors, E→ and p→. This implies that the variations of the dipole–dipole interaction between neighboring amino acid residues caused by the EF should be expressed by (J+E→.p→)−J=|E→||p→|cosθ, which decreases when the angle (θ) increases. If θ = 0, then E→.p→=|E→||p→|. If θ=900, then E→.p→=0. Therefore, the EF has a stronger biological effect on the former and no biological effect on the latter. This result indicates clearly that the biological effect depends on the direction of externally applied EF with respect to that of electric dipole moments of the amino acid residues. If the directions of EF are different, although their strengths are the same, then their biological effects are also different. This finding implies that the biological effects of EFs depend on both the strength and the direction with respect of the dipole moment of amino acid residues [81,86,97]. However, it is worth noting the direction from which the biological effects arise from the EF at the macroscopic level. The orientations of many proteins and amino acid residues within the proteins over any macroscopic region tend to be random. However, this condition depends on the biotissue structure because some biotissues are well organized. Clearly, the orientation of the EF to the structure will be important in this case. In other cases, the overall effect being calculated will not depend on the direction of the field. 3.2. Results of Numerical Simulation for Changes of Property of the Energy Transport Resulting from EF 3.2.1. Results in Single-Protein Chains We now investigate the influences of EFs in EMFs on the energy transported by the soliton in protein molecules with single channels and three channels by using the numerical simulation method [107,108], respectively. In this case, the variation of the dipole–dipole interaction is represented by (J+E→.p→)−J=|E→||p→|cosθ, which is related to the strengths of the EF in the EMF. Therefore, our purpose is to determinate the changed features of the movement of the soliton transporting the energy with varying EFs, which can be obtained by the fourth-order Runge–Kutta method [107,108]. In such a case, we must establish the dynamic equations of the soliton in this numerical simulation. Obviously, the dynamic equations of the soliton can be obtained from Equations (6) and (7) in Pang’s model. Their derivations are depicted as follows. First, we use first the transformation an(t)→an(t)exp[iε0t/ℏ] to eliminate the term ε0an(t) in Equation (6). Then, we make the transformation according to the Runge–Kutta method [107,108]: an(t)=an(t)rn+ia(t)in. Thus, Equations (6) and (7) become (15) ℏα.rn=−J(αin+1+αin−1)+χ1(qn+1−qn−1)αin+χ2(qn+1−qn)(ain+1+αin−1) (16) −ℏα.in=−J(αrn+1+αrn−1)+χ1(qn+1−qn−1)αirn+χ2(qn+1−qn)(arn+1+αrn−1) (17) q.n=y/M (18) y.=W(qn+1−2qn+qn−1)+2χ1(αrn+12+αin+12−αrn−12−αin−12)+4χ2[αrn(αrn+1−αrn−1)+αin(αin+1−αin−1)] (19) |αn|2=|αrn|2+|αin|2 where arn and ain are real and imaginary parts of an, respectively. Equations (15)–(19) are discretely coupled and can be used to determine the dynamic features and states of the soliton by using the fourth-order Runge–Kutta method in the numerical simulation. Obviously, in this case there are four equations for one amino acid residue from Equations (15)–(18). Thus, we should find solutions of 4 N associated equations for the protein molecules constructed by N amino acid residues. However, when the fourth-order Runge–Kutta method [107,108] is used to find the solutions of Equations (15)–(18), we should discretize these equations further. Thus, the n is replaced by j, the time is denoted by n, and the step length of the space variable is denoted by h in the previous equations in this simulation. Then we can get the representations of the solutions from the given equations. The concrete equations for finding the solutions are described in Appendix A. In concrete calculations, we must determine the values of the parameters in Equations (15)–(18). The values for the parameters M, J, W, ε0, x1, and x2 are known in Pang’s theory of the energy transport in protein molecules. The widely accepted values of these parameters are J = 9.68 × 10−4 eV, ε0 = 0.205 eV, χ1=6.2×10−11N,w=13 N/m, χ2=(10−18)×10−12 N and M = 1.17 × 10−25 kg in single-protein molecules or 5.73 × 10−25 kg in α-helix proteins [24,25,26,27,28,29,30,31,32,33,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90]. However, we need to confirm the value of the electric dipole moment |p→| of the amino acid residues, which is a key parameter for finding the relationship to varying solitons transporting the bio-energy with changing EFs applied externally to protein molecules. Many researchers have calculated and measured the values of |p→| of the amino acid residues in protein molecules [24,109,110,111]. Results have shown the electric dipole moments in the region of a few −10 debyes (1 debye = 3.33 × 10−30 cm). Therefore, it is reasonable to choose |p→|=10 debyes in the calculation [24,109,110,111]. From Equations (15)–(19) using the given values of parameters, we can determine the changes of the solution of Equations (15)–(19) numerically, a(t)rn and a(t)in, and of the corresponding |an(t)|2, which denotes the probability of appearance of the soliton related to its amplitude, with varying time and space by the fourth-order Runge–Kutta method [107,108]. In this calculation, we choose the time step Δt to be between 0.2 and 0.5(M¯/w¯)1/2 and the initial excitation of an(0)=Asech[(n−n0)×(χ¯1+χ¯2)/4J¯w¯] (where A is normalization constant) and the initial states of amino acid residues, qn(0) = πn(0) = 0 at the site n; where the molecular chain is fixed, the number of amino acid residues, N, is chosen to be 400 and a time step of 0.0195 is used. This means that 800 coupled differential equations with first-order-of-time derivation had to be solved in such a case. At the same time, the system of units eV for energy, A0 for length, and ps for time have been used to be suitable for the numerical solutions of Equations (15)–(19). Otherwise, by using numerical simulations obtained by the fourth-order Runge–Kutta method [107,108], we could also satisfy the total energy of the soliton, E ≤ Φ(t)|H|Φ(t) ≥ constant, in which a possible imaginary part of the energy, which could occur because of numerical inaccuracies, is zero. Its accuracy is 0.001 feV; when the soliton is in motion, its probability of appearance must be normalized at all times, i.e., the number of particles for the system must be conservative, ∑n|an(t)|2=∑n|an(0)|2=1 up to 0.3 ppm. Meanwhile, the initial excitation conditions described previously are also required in this calculation. Total numerical simulation is performed through data-paralleling algorithms and MATLAB language. On the basis of the methods and conditions given, we obtain the representation for the change of |an|2=|aj|2, which is the probability of the soliton occurred at the nth (or jth) amino acid molecule, with varying positions and times under the actions of different EFs. We first calculate the solutions of Equations (15)–(19) numerically in the uniform and periodic proteins with a single chain using the above-average values for these parameters, i.e., M¯ = 1.17 × 10−25 kg; J¯ = 1.55 × 10−22 J; or = 9.68 × 10−4 eV; ε0¯ = 0.20 5 eV; χ1¯ = 6.2 × 10−11 N; w¯ = (13 − 19.5) N/m; and χ2¯=(11−18)×10−12 N, which are widely accepted in investigations of energy transport in α-helical protein molecules [24,25,26,27,28,29,30,31,32,33,65,66,67,68,69,70,71,72,73,74]. If the fourth-order Runge–Kutta method is used, then the results for the state of transport of the soliton in the time–place are shown in Figure 2 and Figure 3, respectively, in which we show the movements or progress of the soliton transporting the energy (in other words, its probability |an)t)|2) with varying time and space, where the symbols of three axes and their physical significances are marked clearly; where n is the number of amino acid residues the soliton has transported; and t is time of movement of the soliton. If the probabilities or amplitudes of the soliton, obtained from this calculation, are always constant in the movement process, then we can affirm that the solution of the dynamic equations is a soliton. Otherwise, these equations do not provide the soliton solution, which indicates that the soliton was dispersed or damped and that the energy transport was also dispersed or dissipated due to the influence of an externally applied field, according to the soliton theory [9,27,36]. Therefore, we can study and confirm the influences of EFs or EMFs on the soliton or energy transport in the protein molecules through the results obtained from the numerical simulations. Figure 2 and Figure 3 indicate that this solution is a soliton because its probabilities or amplitudes are invariable in the propagation processes of the long-time period of 250 ps and the long distances of 400 amino acid residues, which are shown in Figure 2. Figure 3 exhibits the collision property of two solitons and also shows that the probabilities or amplitudes of the two solitons are invariable after the collision, resembling a feature of classical particles. Therefore, Figure 2 and Figure 3 clearly show that the numerical solutions of Equations (15)–(19) are reliable and indicate the presence of a soliton according to the soliton theory [9,27,34].Thus, we can affirm that Equations (15)–(19) have the soliton solution, which is exactly the carrier of the energy transport in uniform and periodic protein molecules. When protein molecules are exposed to EFs, the states of the soliton will change because of variations in the dipole–dipole interaction J, which would be replaced by J+E→.p→=J+|E→||p→| at θ=00, as shown previously. As such, studies should explore further the properties of various states of the soliton. We studied these variations by using Equations (15)–(19) and the fourth-order Runge–Kutta method [107,108] under the influences of different strengths of EFs with |E→| = 25,500, 51,000, 76,500, and 102,000 V/m, which correspond to the variations of the dipole–dipole interaction energy of ΔJ=J−J¯ = 5%, 10%, 15%, and 20%, respectively, between the neighboring amino acid residues arising from the EF, in which the electric dipole moment |p→| = 10 debyes is used, in which other parameters used by their average values , that are M¯,w¯,ε0¯,χ1¯, and χ2¯. Figure 4 shows the states of movement of the soliton under these conditions. For instance, the range of variations increases with the increase of strength of the EFs, such that the soliton is stable at |E→| = 25,500 and 51,000 V/m because its amplitudes have not been altered during the transport processes. However, the soliton disperses at |E→| = 76,500 V/m, as shown in Figure 4c, and disperses significantly at |E→| = 102,000 V/m, as shown in Figure 4d. Also, Figure 4 shows that their amplitudes are changed or reduced in these cases and that small ripples occur around the solitons in Figure 4c,d. This occurrence indicates that the states of the soliton, that transport the bio-energy, are changed because of influences by the EFs. This finding suggests that the features of bio-energy are highly sensitive to changes in the dipole–dipole interaction or the states and properties of externally applied EFs. 3.2.2. Results in α-Helix Protein Molecules with Three Channels We also numerically simulated the dynamic states of the soliton that occurred in the α-helix protein molecules with three channels under the influence of EFs. The Hamiltonian and the wave function of the α-helix protein molecules in Pang’s model [86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101] are, respectively, represented by (20) H=∑nα[ε0Bnα+Bnα−J(Bnα+Bn+1α+BnαBn+1α+)]+∑nα[Pnα22M+12w(qnα−qn−1α)2]+∑[χ1(qn+1α−qn−1α)×Bnα+Bnα+χ2(qn+1α−qn−1α)(Bn+1α+Bnα+Bnα+Bn+1α)+L(Bnα+Bn+1α+Bnα+Bn−1α)],α=1,2,3. and (21) |Φ(t)〉=|α(t)〉|β(t)〉=1λ[1+∑nααnα(t)Bnα++12!(∑nααnα(t)Bnα+)2]|0〉ex×exp{−iℏ∑n[qnα(t)Pnα−πnα(t)unα|0〉ph where L is the coefficient of the chain–chain interactions among the three channels, and α = 1, 2, 3 denote the three chains. According to this above method, from Equations (20) and (21) we can get the dynamic equations of the soliton in the discrete case, which are (22) iℏαnα(t).=ε0αnα(t)−J[(αn+1α(t)++αn−1α(t))]+χ1[(qn+1α(t)−qn−1α(t)]αnα(t)+χ2[qn+1α(t)−qn−1α(t)]×[(αn+1α(t)+αn−1α(t)]+52{W(t)−12∑m[qnα(t)πmα(t)−π.nα(t)q.mα(t)}αnα(t)+L[αnα+1(t)+αnα−1(t)] (23) Mq..nα(t).=w[qn+1α(t)−2qnα(t)+qn−1α(t)]+2χ1[|αn+1α(t)|2−|αn−1α(t)|2]+2χ2{αnα*(t)[αn+1α(t)−αn−1α(t)]+αnα(t)[αn+1α*−αn−1α*(t)]} By means of Equations (22) and (23) and the fourth-order Runge–Kutta method [107,108] mentioned previously, we can also numerically simulate the features of the solutions of Equations (22) and (23), which are denoted in Appendix B. In this numerical simulation, we use the fourth-order Runge–Kutta method [107,108] with the initial condition of anα(0)=A'sech[(nα−n0α)×(χ¯1+χ¯2)/4J¯w¯], where A’ is the normalization factor. Meanwhile, we use M¯ = 5.73 × 10−25 kg, w¯ = 39 N/m, ε0¯ = 0.2055 eV, J¯ = 9.68 × 10−4 eV, χ1¯ = 6.2 × 10−11 N, χ2¯ = (10 − 18) × 10−12 N, and L¯= 1.5 meV for the α-helix protein molecules in the simulation, which are widely accepted in energy-transport investigations [24,25,26,27,28,29,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101]. The numerical solutions of Equations (22) and (23) and their variations for the protein molecules with three channels are shown in Figure 5a, which shows the motion behaviors of the solution, in which the previously given initial conditions are motivated simultaneously on the first ends of the three chains. From this figure, we see that their solution can always retain a bell shape while moving over a long distance of the spacing of 400 amino acid residues in the period of 40 ps along the molecular chains without the dispersion. This feature is similar to the numerical results in Figure 2 for the single-chain proteins. On the basis of the soliton theory [9,27,36], we can also affirm from this result that this solution of Equations (22) and (23) also indicate the existence of a soliton in this case. Therefore, Equations (22) and (23) can be used to simulate the dynamic properties of the soliton excited in the protein molecules with three channels under the action of EF. We studied the collision property of two solitons, setting up from opposite ends of the three channels in the protein molecules by using the fourth-order Runge–Kutta method. The result is shown in Figure 5b, in which the initial conditions given simultaneously motivate the opposite ends of the three channels, where the initial two solitons separating the 100 amino acid spaces in each channel collide with each other after approximately 17 ps. After this collision, the two solitons in each channel go through each other without scattering to propagate toward and separately along the three chains, which is also similar to the rules of collision for two solitons in the numerical results shown in Figure 3 for single-chain proteins. In accordance with the soliton theory [9,27,34], we can also confirm from the two results in Figure 5 that this solution to Equations (22) and (23) is still a soliton. Thus, by using this method, we can study the changes to the properties of energy transported by the solitons in Equations (22) and (23) under the influences of EFs. When the protein molecules with the three channels are acted on by an EF, the states of the soliton will also change because of variations in the dipole–dipole interaction J, as noted previously. We studied the changing states of movement of the soliton under the effects of EFs of different strengths by using Equations (22) and (23) and the fourth-order Runge–Kutta method [107,108], in which the dipole–dipole interaction J is replaced by J+E→.p→=J+|E→||p→| at θ=900; where J = 9.68 × 10−4 eV and |p→|=10 debyes; other parameters are used as their average values, M¯, w¯, ε0¯, ε0¯, χ1¯, and χ2¯, as described. Figure 6 shows the states of movement of the solitons in the cases of |E→| = 17,000, 25,500, and 34,000 V/m, which correspond to variations of the dipole–dipole interaction energy of ΔJ=J−J¯ = 3%, 5%, and 7% between the neighboring amino acid residues, respectively. From these figures, we see clearly that the states of the soliton vary with increasing EF strength. The results show that the soliton is stable at |E→|= 17,000 V/m but that it disperses at |E→| = 25,500 V/m and damps at 34,000 V/m. The stability of solitons in three-channel α-helix protein molecules is reduced with respect to the solitons in single-chain protein molecules under the influence of an EF through the existence of the disperse effect, which is caused by the chain–chain interactions among the three channels. Thus, we can surmise that the state of a soliton transporting energy is highly sensitive to the EFs in EMFs. Marracino et al. [112] showed the effects of EFs in EMFs on chemical reactions and determined that a 100,000 V/m electric field can have a significant effect on chemical reaction in micelles. In such a case, we think that this result might serve somewhat as a basis of comparison. These comparisons indicate the relevance of our investigations of the biological effects of EFs or EMFs because the strengths of electric field, as described previously, can generate corresponding electrically interactional energies to the amino acid residues within a few nanometers, which is approximately one order of magnitude smaller than that of the dipole–dipole interactional energy J between them. Therefore, these estimated values are basically the same as those in the calculations previously described, which, we believe, are basically correct. 4. Experimental Evidences for this Theory The theoretical results and mechanisms of the biological effects of EMFs mentioned previously require further experimental confirmation. Experimental evidence should relate mainly to the affirmation of the nonlinear excitation or the soliton, which provides the bio-energy transport in an α-helix protein molecule, and its changes with varying EF in EMF. Investigations indicate that the nonlinear interaction, or the soliton, can be confirmed from the infrared spectrum of absorption from the α-helix protein molecule [113]. The essence of the experimental evidence is to confirm the real existence of the soliton in transporting the bio-energy within the α-helix protein molecules. Therefore, the first step of the investigation is to determine the existence of soliton excitation in the protein molecules with α-helix structures. Subsequently, investigation should focus on the exact influence of the EF on the soliton. By confirming the existence of a soliton and indicating that EMFs can influence or change the properties of the soliton, we can confirm the correctness of the previously given mechanics for the biological effects of EFs, that is, EMFs can influence the bio-energy transport in protein molecules. Careri et al. [113,114,115,116,117], Scott [30,31,118,119,120,121], and Alexander et al. [122,123] measured the infrared spectrum of absorption for acetanilide (ACN) [113], a molecular structure of like-protein molecules. From these investigations, they confirmed that the 1666- and 1650-cm−1 bands that occurred in the infrared spectra represent the excited states of amide-I mode in ACN, which corresponds to the excitations of the exciton and the soliton, respectively. Their infrared absorption strengths change linearly and exponentially by increasing the temperatures in ACN, respectively. Thus, the existence of the soliton in ACN was affirmed [115,116,117,118,119]. We chose a collagen protein with α-helix conformation to confirm the existence of the soliton and study the influence of EFs, and to affirm further the validity of the mechanism and theory previously described. These investigations are summarized as follows. 4.1. Experimental Evidence of the Existence of Solitons in Protein Molecules Because collagen is a common biomacromolecule that widely exists in a solid-like or soft condensed state from 0 to 95 °C in living systems, it is a basic component of surface-tissue musculature, e.g., smooth muscle [113,114,115,116,117,118,119,120,121,122,123,124,125]. Tropocollagen, a kind of collagen, is an α-superhelical biopolymer with three channels (Figure 7), in which each α-peptide chain contains 1050 amino acid residues and a sugary side chain. The structure consists of approximately 35% glycine, 10% proline, and 9% hydroproline, as well as some alumine and hydrolysin. Its molecular structure might be described as follows. Its primary conformation is a chain of (Gly-X-Y)n, where X and Y are the proline and the hydroproline, respectively. Its secondary structure consists of main chains that are regularly folded into an α-helical chain with a left-hand spin, in which the glycine is at the center of the helix and the proline and hydroxylproline are at its exterior. If the three chains are again folded into a multi-helix structure, a tertiary conformation is constructed in which each chain contains several helices. When the three chains are assembled and wind further into a right-hand spin to construct a long fiber, in virtue of the hydrogen bonds and the C=O…NH groups, its quaternary conformation is obtained. Thus, the linkage between the two lysine residue side groups in the peptide chains occurs through covalent bonding, which is formed and produced by the oxidoreductase reaction of lysine, as represented by –CO–CH(NH)–CH2–CH2–CH2–CH=N–CH2–CH2–CH2–CH2–CH(NH)–CO–. Collagen is, therefore, a kind of α-helical protein molecule with an α-helix conformation (Figure 7), in which the hydrogen bonds and the covalent bonds are arranged alternately, which plays an important role in stabilizing the molecular structure of the collagen and completing its biological functions (such as the transport of energy and information) and enhancing its tensile strength. We used the features of the infrared spectrum to confirm the existence of the soliton and the influences of EMF and could thus verify further the validity of the previously given mechanism and theory. We measured the infrared spectrum of absorption of the collagen, which was supplied by Sigma-Aldrich (St. Louis, MO, USA), using the spectrum GXFFIR spectrometer with a DTGS detector and a variable-temperature bath with a reported accuracy of ±1 °C, in which infrared silicon–carbon bars served as a light source, was provided by Perkin Elmer (Waltham, MA, USA), and a 670 Nicolet FT-IR spectrometer with a 4-cm−1 resolution and ATR full-reflective device with 16 successive scans were supplied by Nicolet Nexus (Ramsey, MN, USA), respectively. In this experiment we measured and collected mainly the infrared absorption spectrum of the collagen in the region of 1000–2000 cm−1 by using, first, the Perkin Elmer spectrum GXFFIR spectrometer [108,109,110,111,112,113,114,115,116,117,118,119,120,121,124,125,126] and, again, the 670 Nicolet FT-IR and the GXFFIR spectrometers with resolutions of 4 cm−1 to check the results. The measured samples of collagen were sandwiched between KBr windows at temperatures controlled by a variable-temperature bath. Throughout the experiment, we inspected the infrared absorption spectrum of the collagen in the range of 1000–4000 cm−1. To obtain an acceptable signal-to-noise ratio, we took 16 scans of these infrared spectra. When the temperatures of the samples changed from 15 to 95 °C, variations of the infrared spectra of the collagen were also measured and inspected by a spectrometer. In this experiment, the water and the water vapor in these samples were completely drained from the tested samples so as not to influence results. The infrared spectrum of collagen at 25 °C in the range of 1540–1710 cm−1 is shown in Figure 8. Its spectrum at high frequencies is dominated by the amide spectrum, in which three clear Amide I vibrational modes are present: 1666.11, 1680.38, and 1695.32 cm−1, where an important feature in the spectrum is the appearance of a new band at 1650.01 cm−1. Other amide bands, such as the Amide II at 1624.9 cm−1, the Amide III at 1553.1, and so on are also observed and obtained from the previously designated. The infrared spectrum of collagen denoted in Figure 8 has the following properties: (1) Amide II, III bands, in addition to an Amide I band, exist in the infrared absorption spectrum of the collagen; (2) a new band of 1650 cm−1 appears besides the conventional 1666 cm−1 band. These results are very interesting and important because from this experiment we confirm the appearances of 1650 cm−1 and 1666 cm−1,which correspond the excitations of soliton and exciton in the collagen in this case, respectively, in accordance with Careri et al. [113,114,115,116,117] and Scott [30,31,118,119,120,121] researched conclusions. Thus we may use the method and material to investigate further the influences of EF in EMF on the soliton, or energy transport in collagen, which is described in detail as follows. At the same time, the infrared spectra of absorption of collagen at different temperatures are carefully recorded, where the temperatures of the samples varied from 15 to 95 °C, with the intervals of 10 °C and a reported accuracy of ±1 °C, which is controlled by variable-temperature equipment. The temperature-dependent intensity of infrared absorption at temperatures ranging from 15 to 95 °C is shown in Figure 9. Figure 9 clearly indicates that the intensity of the 1650-cm−1 band increases with the decrease of temperature, without any apparent change in frequency and shape, but is weakened at 95 °C. However, the strength of the Amide I infrared absorption of the 1666-cm−1 band decreases with a decrease in temperature. The peak strengths of the 1650- and 1666-cm−1 bands versus temperature are clearly shown in Figure 9. Although the temperature dependences of strengths for the 1650- and 1666-cm−1 bands differ, the absorption strength of the 1666-cm−1 band increases linearly with increasing temperature; however, the strength of the 1650-cm−1 band decreases exponentially with an increase in temperature This relationship can be approximately simulated in the exponential form of I = I0 exp {−[0.437 + 8.987 × 10−6 (T/°C)2]}(24) where T is represented in Celsius temperature (°C); and I0 is a constant related to the initial strength. Figure 10 shows the experimental data of the relationship between the logarithm of relative strength, Ln (I/I0), and the temperature, (T/°C)2, for the 1650-cm−1 peak in the collagen, and this relationship can be simulated by Ln (I/I0) = −(0.437 + 8.987 × 10−6 (T/°C)2). It denotes that the strengths of the 1650-cm−1 peak in the infrared spectrum of absorption in the collagen decreased exponentially with increasing temperatures. Figure 10b gives the linear changed relation of relative strength, I/I0, for the 1666-cm−1 peak changing with increasing temperatures in the infrared spectrum of the absorption of the collagen molecule, a novel and interesting finding. On the basis of the experimental results in Figure 8, Figure 9 and Figure 10, we can affirm again the existence of solitons in collagen according to the theory and conclusions of Careri et al. [113,114,115,116,117], Scott [30,31,108,109,110,111,112,113,114,115,116,117,118,119,120,121], and Alexander et al. [122,123]. Taking into account these results, we studied further the influences of EMFs on solitons, because the outline and features of solitons depend closely on the dipole–dipole interaction between the neighboring amino acid residues with certain electric dipole moments in the collagen, as mentioned previously. 4.2. Experimental Evidence of the Influence of EFs on Solitons in Protein Molecules We investigated and measured further the influence of EMFs on the properties of the 1650-cm−1 peak in collagen, which is related to the soliton excited, by using the 670 Nicolet FT-IR spectrometer based on the above results. If we obtain the changes of features of the peak of 1650 cm−1 by varying the externally applied electric voltage, we can affirm that the EF varies the states and features of the soliton, or the bio-energy transport, in the collagen because of variations of the electric dipole moments of amino acids in the protein. In this experiment the electric voltage, which is applied on the collagen, changed from 15,000 to 20,000 V, and our results are shown in Figure 11, Figure 12, Figure 13 and Figure 14. Figure 11 shows the results of the infrared spectrum of absorption of collagen in 480–2000 cm−1, and it is apparent that the 1650 cm−1 peak occurs in this case. Hence, the soliton exists within the collagen in this case. In this experiment, the externally applied voltages are linked on the two sides of the thin plates, where the measured collagen samples are first made into powders, which are again inserted into the center of the thin plates and were kept in tight contact with each other through extrusion and pressurization. Subsequently, they were placed in the sample bath in the FT-IR spectrometer. When the electric circuit built was connected, the collagen samples were exposed to the externally applied EF. We could then measure and record the infrared spectra of the collagen samples and their variations (Figure 12, Figure 13 and Figure 14). Figure 12 shows the decreases in the peak height with increases in EF strength up to 30,000 V/m, and the inverse beyond 30,000 V/m. Figure 13 and Figure 14 indicate changes in the position of the 1650-cm−1 peak and its half-peak width with increases to the externally applied EF strength. Figure 13 clearly shows that the position of this peak lifts with increases to the EF strength below 30,000 V/m but lowers sluggishly after 30,000 V/m. For its half-peak width, we find that the half-peak width decreases with increases to the EF strength up to 30,000 V/m, but it increases sluggishly after 30,000 V/m (Figure 14). Therefore, Figure 12, Figure 13 and Figure 14 exhibit clearly that the features of the 1650-cm−1 peak vary under the influences of externally applied electric voltages, which are basically consistent with those in Figure 6. Thus, we can affirm and judge from these experiments that the externally applied EFs influence and change the states and features of the soliton and the bio-energy transport in the collagen (Figure 12, Figure 13 and Figure 14). Hence, we verified the validity of these results and the mechanism of influence of EMFs and EFs on life bodies through changes of the bio-energy transport or in the features of the soliton caused by changes to the electric properties of amino acids in protein molecules. 5. Conclusions The mechanism of influence of an externally applied EF or EMF on bio-energy transport along a protein molecule and their properties are investigated by using analytic methods and numerical simulation as well as experimental measurements. Energy, released by the hydrolysis reaction of an ATP molecule, and its transport are the basic biological activities in the life system, including muscle contraction, DNA duplication, neuroelectric pulse transfer along the neurolemma, and calcium and sodium pumping. This transport is conducted through movement of the soliton along the protein molecules and the dipole–dipole interaction between neighbor amino acid residues. Thus, we affirmed that externally applied EFs or EMFs can directly change the strength and direction of electric dipole moments of amino acid residues in protein molecules, which results directly in variations of property of the bio-energy transported by the soliton, thus a series of new biological effects can occur in living systems. In this investigation we obtained the following results. The first result confirms one mechanism of the biological effect of EMFs and EFs, that is, the EFs and EMFs changed the features of bio energy transport through variations of electric dipole moments of the amino acid residue or the dipole–dipole interactional energy between the neighboring amino acid residues. Thus, we determined first that the targets of the biological effects of EMFs and EFs are the amino acid residues in protein molecules. The second result establishes a theory of the biological effects of EMFs and EFs through the study of soliton mechanisms and bio-energy transport in protein molecules. In this theory, the dipole–dipole interactional energy J between neighboring amino acid residues is replaced by J+E→.p→=J+|E→||p→|cosθ. We found changes to the features of bio-energy transport in the Pang’s soliton under different EFs using analytical, numerical, and experimental methods. Our analytical investigations indicated that EMFs and EFs influenced both the amplitude of the soliton as well as its form and outline. Its degree of effect depended on the strength of the EF, as well as its direction with respect to the electric dipole moments of amino acid residues. Thus, the biological effects of EFs and EMFs decrease with increases to the angle θ between them. If θ=00, then E→.p→=|E→||p→|, but E→.p→=0 at θ=900, therefore, EMFs and EFs have no biological effect in this case, even at high strengths. Hence, different EMFs and EFs have different biological effects as well, whereas the same EMFs and EFs also have different biological effects because their effects are determined by both the strength and the direction of the EMF or the EF. However, this effect has obvious randomness at the macroscopic level. In the numerical simulation, we found that EMFs and EFs change the states and features of the movement of the soliton by using the fourth-order Runge–Kutta numerical simulation method in Pang’s model [89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105]. By applying this simulation, we found that the solitons are stable at EF strengths of 25,500 and 51,000 V/m, but the solitons disperse at 76,500 V/m and significantly so at 102,000 V/m for protein molecules with single chains. However, the soliton is stable only at the EF strength of 17,000 V/m. It disperses at 25,500 V/m and damps at 34,000 V/m in protein molecules with three channels. This finding implies that the stability of a soliton in a three-channel α-helix protein molecule is reduced compared with that in a single-chain protein molecule because of the influence of the dispersed effect of chain–chain interactions among the three channels under the actions of EFs and EMFs. At the same time, we found that the capability of the bio-energy transported by the soliton is depressed considerably if the strength of the EMF or the EF is very high. These results verified that EMFs and EFs can vary the properties of the energy transport and the states of the soliton and that other biological effects could occur in living systems. Finally we inspected and confirmed experimentally the real existence of the soliton, which corresponds to the excitation of a 1650-cm−1 peak, by using the infrared spectra of absorption of collagen with an α-helical structure and its change of features with varying external EFs, in which the height, position, and half-peak width of the soliton vary with different external EFs. However, we should note the following problems associated with these investigations. (1) We have not studied concretely the macroscopic biological effects arising from changes to energy transport under the influences of EMFs and EFs. Thus, further research into the molecular and cellular biology must be pursued. Thus, we cannot confirm that the concrete biological effects arising from variations in the bio-energy transport in protein molecules in the presence of EMFs or EFs are advantageous or harmful to the health of humans and animals. (2) The mechanism of the biological effects of EFs and EMFs that we propose require additional experimental confirmation, i.e., through instrumentation and novel methods, taking direct measurements of any changed features in the electric dipole moments of α-helix proteins or of the amino acid residues in them arising from EMFs and EFs, which entails many challenges. (3) Because the strength of EMF frequency is altered in a real EMF, we studied the biological effects of static EFs or DC fields only. Therefore, further investigations would focus on the biological effects of AC fields or altered EFs. Acknowledgments The authors would like to acknowledge the National Basic Research Program of China under Grant No. 2011CB503701 for its financial support. Author Contributions Xiaofeng Pang, Shude Chen, Xianghui Wang and Lisheng Zhong finished together this researched work. This paper is mainly written by Xiaofeng Pang. Conflicts of Interest The authors declare no conflict of interest. Appendix A. Solutions to Equations (17)–(20) Note that these are base equations derived from numerical computer simulations and the Runge–Kutta method. (A1) αrj,n+1=αrjn+h6K1j+2K2j)+3K3j+K4j),αij,n+1=αijn+h6(L1j+2L2j+2L3j+L4j),qj,n+1=qjn+h6(M1+2M2j+2M3j+M4j),qn+1−qn−1)αin+χ2(qn+1−qn)(ain+1+αin−1),yj,n+1=yjn+h6(N1j+2N3j+N4j), where (A2) K1=−Jℏ(αij+1+αij−1n+χ1ℏ(qj+1n−qj−1n)αi+χ2ℏ(qj+1n−qjn)(αij+1n−αij−1n),K2j=K1j−Jh2ℏ(L1j+2L2j+2L3j+L4j)+χ1h2ℏ(M1j+1−M1j−1)(aijn+h2L1j)+χ2h2ℏ(qj+1,n−qjn)(L1j+1+L1j−1),M1j=yjn/M;M2j=M1j+h2MN1j;M3j=M1j+h2MN2j;M4j=M1j+hMN3j;N1j=W(qj+1,n−2qjn+qj−1,n)+2χ1(arj+1,n2+aij+1,n2−arj−1,n2−aij−1,n2)+4χ2[arjn(arj+1,n−arj−1,n)+aijn(aij+1,n−aij−1,n)];N2j=W[qj+1,n−2qjn+qj−1,n+h2(M1j+1−2M1j+M1j−1)]+2χ1[(arj+1,n+h2K1j+1)2+(aij+1,n+h2L1j+1)2−(arj−1,n+h2K1j−1)2−(aij−1,n+h2L1j−1)2]+4χ2{(arjn+h2K1j)[arj+1,n−arj−1,n+h2(K1j+1−K1j−1)]+(aijn+h2L1j)[aij+1,n−aij−1,n+h2(L1j+1−L1j−1)]};N3j=W[qj+1,n−2qjn+qj−1,n+h2(M2j+1−2M2j+M2j−1)]+2χ1[(arj+1,n+h2K2j+1)2+(aij+1,n+h2L2j+1)2−(arj−1,n+h2K2j−1)2−(aij−1,n+h2L2j−1)2]+4χ2{(arjn+h2K2j)[arj+1,n−ar−1,n+h2(K2j+1−K2j−1)]+(aijn+h2L2j)[aij+1,n−aij−1,n+h2(L2j+1−L2j−1)]};N4j=W[qj+1,n−2qjn+qj−1,n+h(M3j+1−2M3j+M3j−1)]+2χ1[(arj+1,n+hK3j+1)2+(aij+1,n+hL3j+1)2−(arj−1,n+hK3j−1)2−(aij−1,n−hL3j−1)2]+4χ2{(arjn+hK3j)[arj+1,n−arj−1,n+h(K3j+1−K3j−1)]+(aijn+hL3j)[aij+1,n−aij−1,n+h(L3j+1−L3j−1)]} Appendix B. Solutions to Equations (17)–(20) From the time-dependent Schrödinger equation (B1) H|Φ>=iℏ∂∂t|Φ> with the Hamiltonian Equation (3) and the time-dependent wave function Equation (4) and (B2) iℏ ∂∂t<| Φ(t)|un|Φ(t)>=<Φ(t)|[un,H] |Φ(t)> (B3) iℏ ∂∂t<Φ(t)|Pn|Φ(t)=<Φ(t)| [Pn,H] | Φ(t)> and considering further the neighboring interactions among the three channels we can determine (B4) iℏa˙nα(t)=ε0anα(t)−J[an+1α(t)+an−1α(t)]+χ1[qn+1α(t)−qn−1α(t)]anα(t) +χ2[qn+1α(t)−qn−1α(t)][an+1α(t)+an−1α(t)] +52{w(t)−12∑m[qmα(t)πmα(t)−π˙mα(t)q˙mα(t)]}anα(t)+L[anα+1(t)+anα−1(t)] (B5) Mq¨nα=W[qn+1α(t)−2qnα(t)+qn−1α(t)]+2χ1[|an+1α(t)|2−|an−1α(t)|2] +2χ2{anα*(t)[an+1α(t)−an−1α(t)]+anα(t)[a*n+1α(t)−a*n−1α(t)]}. Also, we can eliminate the term containing ε0 in Equation (B4) through the following transformation: (B6) φnα(t)=anα(t)exp[−iε0t/ℏ] Because an(t) in Equations (B4) and (B5) is a complex function, we can make the following transformation (B7) anα(t)=arnα(t)+iainα(t) with |an|2=|arn|2+|ain|2 Thus Equations (B4) and (B5) change as (B8) ℏa˙rnα=−J(ain+1α+ain−1α)+χ1(qn+1α−qn−1α)ainα+χ2(qn+1−qn−1α)(ain+1α+ain−1α) +L[ainα+1(t)+ainα−1(t)] (B9) −ℏa˙inα=−J(arn+1α+arn−1α)+χ1(qn+1α−qn−1α)arnα+χ2(qn+1α−qn−1α)(arn+1α+arn−1α)+L[ainα+1(t)+ainα−1(t)] (B10) q˙nα=ynαM (B11) y˙nα=W[qn+1α−2qnα+qn−1α]+2χ1[arn+1α2+ain+1α2−ain−1α2−ain−1α2] +4χ2[arnα(arn+1α−arn−1α)+ainα(ain+1α−ain−1α)], where arn and ain are real and imaginary parts of an(t), respectively. Therefore, Equations (B8)–(B11) are dynamic in Equations (17)–(20), which can be used to simulate and calculate the dynamic properties of particles. Therefore, the dynamic properties of the peptide groups or amino acid molecules mentioned previously can be calculated and studied through Equations (B8)–(B11), as detailed in Appendix A for single-chain protein molecules. Figure 1 The molecular structure of an α-helical protein molecule. Figure 2 State of the new soliton in the case of a longtime period of 250 ps and long spacing of 400 amino acid residues. Figure 3 The collision behavior of two solitons for Equations (18)–(21). Figure 4 States of Pang’s soliton in the case of (a) |E→| = 25,500; (b) 51,000; (c) 76,500; and (d) 102,000 V/m, respectively, where “site k” denoted the number of amino acid residue, ”n”. Figure 5 States of (a) movement and collision features of (b) Pang’s solitons in uniform α-helix proteins. Figure 6 States of solitons in α-helix protein molecules of which |E→| = (a) 17,000; (b) 25,500; and (c) 34,000 V/m, respectively. Figure 7 Molecular structure of collagen: (a) fundamental structure of right α-helix with three channels; (b) atomic distribution on top section of three channel–axes, where G is carbon atom, is hydrogen bond; (c) one-dimensional structure of gly-pro-hydropro. Figure 8 The infrared spectrum of collagen in 1540–1740 cm−1. Figure 9 Changes of intensity for infrared absorption of collagen in the region at (1) 95 °C; (2) 85 °C; (3) 75; (4) 65 °C; (5) 55 °C; (6) 45 °C; (7) 35 °C; (8) 25 °C; and (9) 15 °C. Figure 10 Temperature dependences of intensity of peaks in the infrared spectrum of collagen: (a) Relation of logarithm of relative intensity, Ln (I/I0), versus (T/°C)2 for a 1650-cm−1 peak, where “●” denotes experimental data; and (b) linear temperature dependence of relative intensity, I/I0, for a 1666-cm−1 peak. Figure 11 Infrared spectrum of absorption of collagen in 480–2000 cm−1. Figure 12 Changes in the relative height of a 1650-cm−1 peak with increases to externally applied voltage. Figure 13 Changes in the position of a 1650-cm−1 peak with increases to the externally applied voltage. Figure 14 Changes to the width of a half-peak for a 1650-cm−1 peak with increases to the externally applied voltage. ijms-17-01130-t001_Table 1Table 1 Comparison of soliton features in Pang’s model and the Davydov model. Lifetime at 300 K (S) Critical Temperature (K) Number of Amino Acids Traveled by Soliton In Lifetime Nonlinear Interaction G (×10−21 J) Amplitude of Soliton Width of the Soliton (×10−10 m) Binding Energy of Soliton (×10−21 J) Pang’s model 10−9–10−10 320 Several hundreds 1.18 0.974 14.88 −0.188 Davydov model 10−12–10−13 <200 <10 3.8 1.72 4.95 −7.8 ==== Refs References 1. Pang X.F. Bio-Electromagnetism 1st ed. The Defense Industry Press of China Beijing, China 2009 14 52 2. Fröhlich H. Biological Coherence and Response to External Stimuli 1st ed. Springer-Verlag New York, NY, USA 1988 5 64 3. Ahlbom A. Day N. Feychting M. Skinner R.E. Dockerty J. Linet J. McBride M. Michaelis M. Olsen J. Tynes T. A pooled analysis of magnetic fields and childhood leukaemia Br. J. Cancer 2000 83 692 698 10.1054/bjoc.2000.1376 10944614 4. Dowson D.I. Lewith G. Campbell M. Mullee M.A. Brewster L.A. Overhead high-voltage cables and recurrent headache and depressions Practitioner 1988 232 435 436 3249722 5. Greenland S. Sheppard A.R. Kaune W.T. Poole C. Kelsh M.A. A Pooled analysis of magnetic fields, wire codes, and childhood leukemia Epidemiology 2000 11 624 634 10.1097/00001648-200011000-00003 11055621 6. Perry S. Pearl L. Binns R. Power frequency magnetic field: Depressive Illness and myocardial infarction Public Health 1989 103 177 180 10.1016/S0033-3506(89)80072-1 2740472 7. Perry F.S. Reichmanis M. Marino A.A. Becker R.O. Environmental power-frequency magnetic fields and suicide Health Phys. 1981 41 267 277 10.1097/00004032-198108000-00003 7275611 8. Bromberg J. Darnell J.E. The role of STATs in transcriptional control and their impact on cellular function Oncogene 2000 19 2468 2473 10.1038/sj.onc.1203476 10851045 9. Pang X.F. Biophysics Press of University of Electronic Science and Technology of China Chengdu, China 2008 67 173 10. Li G. Pang X.F. Biological effects of environmental electromagnetic fields Adv. Mater. Res. 2011 183–185 532 536 10.4028/www.scientific.net/AMR.183-185.532 11. Li G. Pang X.F. The influence of electromagnetic field on the electromagnetic properties of biological tissue Prog. Biochem. Biophys. (Chin.) 2011 38 604 610 10.3724/SP.J.1206.2010.00537 12. Li G. Li B. Yang S.F. Pang X.F. The influences of static magnetic field on the electric features of testicular tissue of rats Aerosp. Med. Med. Eng. 2012 25 172 175 13. Li G. Yan Y.Y. Han S.G. Pang X.F. The influences of static magnetic field on the brain tissue of the rats using infrared spectrum metho Laser Infrared 2012 42 894 896 14. Li G. Yan Y.J. Huan Y. Zhou Y. Pang X.F. The influences of electromagnetic field with extremely low frequency on the characteristics of infrared spectrum of the sensitive tissue in rat Spectrosc. Spectr. Anal. 2012 32 1194 1197 15. Li G. Li B. Yan Y.J. Yang S.F. Pang X.F. Calculation of equivalent electrical parameters in human tissue and its applications Mater. Rev. 2011 25 142 145 16. Zhang Y.M. Zhou Y. Pang X.F. The Investigation of effects of pulse electromagnetic field on the fluorescence spectrum of serum in rat Spectrosc. Spectr. Anal. 2012 32 2162 2165 17. Zhang Y.M. Li G. Yan Y.J. Pang X.F. Altered expression of matrix metalloproteinases and tight junction proteins with PEMF-induced BBB permeability change in rats Biomed. Environ. Sci. 2011 24 408 414 22108330 18. Beebe S.J. Fox P.M. Rec L.J. Somers K. Stark R.H. Schoenbach K.H. Nanosecond pulsed electric field (nsPEF) effects on cells and tissues: Apoptosis induction and tumor growth inhibition IEEE Trans. Plasma Sci. 2002 30 286 292 10.1109/TPS.2002.1003872 19. Lazzaro V.D. Capone F. Apollonio F. Borea P.A. Cadossi R. Fassina L. Grassi C. Liberti M. Paffi A. Parazzini M. A consensus panel review of central nervous system effects of the exposure to low-intensity extremely low-frequency magnetic fields Brain Stimul. 2013 6 469 476 10.1016/j.brs.2013.01.004 23428499 20. Apollonio F. Liberti M. Paffi A. Merla C. Marracino P. Denzi A. Marino C. d’Inzeo G. Feasibility for microwaves energy to affect biological systems via nonthermal mechanisms: A systematic approach IEEE Trans. Microw. Theory Tech. 2013 61 2031 2045 10.1109/TMTT.2013.2250298 21. Hofmann G.A. Dev S.B. Dimer S. Nanda G.S. Electroporation therapy: A new approach for treatment of head and neck cancer IEEE Trans. Biomed. Eng. 1999 46 752 759 10.1109/10.764952 10356882 22. Kekez M.M. Savic P. Johnson B.F. Contribution to the biophysics of the lethal effects of electric field on microorganisms Biochim. Biophys. Acta 1996 1278 79 88 10.1016/0005-2736(95)00194-8 8611611 23. Pang X.F. Zhang A.Y. Investigations of mechanism and properties of biological thermal effects of the microwave China J. Atom. Mol. Phys. 2001 18 278 281 24. Davydov A.S. Biology and Quantum Mechanics Pergaman New York, NY, USA 1982 161 211 25. Davydov A.S. Solitons in Molecular Systems 2nd ed. Reidel Publishing Company Dordrecht, The Netherlands 1991 23 79 26. Davydov A.S. Ermakov V.N. Soliton generation at the boundary of molecular chain Phys. D 1988 32 318 329 10.1016/0167-2789(88)90059-0 27. Davydov A.S. Solitons in molecular systems Phys. Scr. 1979 20 387 394 10.1088/0031-8949/20/3-4/013 28. Davydov A.S. The lifetime of molecular solitons J. Biol. Phys. 1991 18 111 125 10.1007/BF00395058 29. Davydov A.S. Solitons and energy transfer along protein molecules J. Theor. Biol. 1977 66 379 387 10.1016/0022-5193(77)90178-3 886872 30. Scott A.C. Davydov’s soliton Phys. Rep. 1992 217 1 67 10.1016/0370-1573(92)90093-F 31. Scott A.C. Dynamics of Davydov’s soliton Phys. Rev. A 1982 26 578 595 10.1103/PhysRevA.26.578 32. Brown D.W. Ivic Z. Unification of polaron and soliton theories of exciton transport Phys. Rev. E 1989 40 9876 9887 10.1103/PhysRevB.40.9876 33. Brown D.W. Lindenberg K. West B.J. Nonlinear density-matrix equation for the study of finite-temperature soliton dynamics Phys. Rev. B 1987 35 6169 6180 10.1103/PhysRevB.35.6169 34. Guo B.L. Pang X.F. Solitons Chinese Science Press Beijing, China 1987 4 140 35. Pang X.F. The transport of bio-energy in protein molecules Chin. J. Biochem. Biophys. 1986 18 1 8 36. Christiansen P.L. Scott A.C. Davydov’s Soliton Revisited Plenum Press New York, NY, USA 1990 34 103 37. Cruzeiro L. Halding J. Christiansen P.L. Skovgard O. Scott A.C. Temperature effects on Davydov soliton Phys. Rev. A 1985 37 880 887 10.1103/PhysRevA.37.880 38. Cruzeio-Hansson L. Mechanism of thermal destabilization of the Davydov soliton Phys. Rev. A 1992 45 4111 4115 10.1103/PhysRevA.45.4111 9907463 39. Forner W. Quantum and disorder effects in Davydov soliton theory Phys. Rev. A 1991 44 2694 2708 10.1103/PhysRevA.44.2694 9906252 40. Forner W. Quantum and temperature effects on Davydov soliton dynamics: Averaged Hamiltonian method J. Phys. Condens. Matter 1992 4 1915 1923 10.1088/0953-8984/4/8/007 41. Forner W. Davydov soliton dynamics: Two-quantum states and diagonal disorder J. Phys. Condens. Matter 1991 3 3235 3254 10.1088/0953-8984/3/19/003 42. Lomdahl P.S. Kerr W.C. Do Davydov solitons exist at 300 K? Phys. Rev. Lett. 1985 55 1235 1239 10.1103/PhysRevLett.55.1235 10031763 43. Kerr W.C. Lomdahl P.S. Quantum-mechanical derivation of the equations of motion for Davydov solitons Phys. Rev. B 1987 35 3629 3632 10.1103/PhysRevB.35.3629 44. Wang X. Brown D.W. Lindenberg K. West B. Alternative formulation of Davydov theory of energy transport in biomolecules systems Phys. Rev. A 1988 37 3557 3566 10.1103/PhysRevA.37.3557 45. Wang X. Brown D.W. Lindenberg K. Quantum Monte Carlo simulation of Davydov model Phys. Rev. Lett. 1989 62 1796 1799 10.1103/PhysRevLett.62.1796 10039770 46. Cottingham J.P. Schweitzer J.W. Calculation of the lifetime of a Davydov soliton at finite temperature Phys. Rev. Lett. 1989 62 1792 1795 10.1103/PhysRevLett.62.1792 10039769 47. Schweitzer J.W. Lifetime of the Davydov soliton Phys. Rev. A 1992 45 8914 8922 10.1103/PhysRevA.45.8914 9906994 48. Mettle B. Shaw P.B. Evolution of a molecular exciton on a Davydov lattice at T = 0 Phys. Rev. B 1988 38 3075 3086 49. Ivic Z. Przulj Z. Kosti D. Decay and slowing down of the multiquanta Davydov-like solitons in molecular chains Phys. Rev. E 2000 61 6963 6967 10.1103/PhysRevE.61.6963 50. Teki J. Ivic Z. Zekovi S. Przulj Z. Kinetic properties of multiquanta Davydov-like solitons inmolecular chains Phys. Rev. E 1999 60 821 825 10.1103/PhysRevE.60.821 51. Zekovi S. Ivic Z. Damping and modification of the multiquanta Davydov-like solitons in molecular chains Bioelectrochem. Bioenerg. 1999 48 297 300 10.1016/S0302-4598(99)00014-8 10379542 52. Pouthier V. Two-vibron bound states in alpha-helix proteins: The interplay between the intramolecular anharmonicity and the strong vibron-phonon coupling Phys. Rev. E 2003 68 10.1103/PhysRevE.68.021909 14525008 53. Pouthier V. Falvo C. Relaxation channels of two-vibron bound states in α-helix proteins Phys. Rev. E 2004 69 10.1103/PhysRevE.69.041906 15169042 54. Falvo C. Pouthier V. Vibron–polaron in α-helices. I. Single-vibron states J. Chem. Phys. 2005 123 184709 184716 10.1063/1.2101569 16292923 55. Falvo C. Pouthier V. Vibron–polaron in α-helices. II. Two-vibron states J. Chem. Phys. 2005 123 10.1063/1.2101570 16292924 56. Cruzeiro L. The Davydov/Scott model for energy storage and transport in proteins J. Biol. Phys. 2009 35 43 55 10.1007/s10867-009-9129-0 19669568 57. Silva P.A.S. Cruzeiro L. Dynamics of a nonconserving Davydov monomer Phys. Rev. E 2006 74 10.1103/PhysRevE.74.021920 17025485 58. Silva P.A.S. Cruzeiro-Hansson L. A reduced set of exact equations of motion for a non-number-conserving Hamiltonian Phys. Lett. A 2003 315 447 451 10.1016/S0375-9601(03)01112-5 59. Pouthier V. Energy relaxation of the amide-I mode in hydrogen-bonded peptide units: A route to conformational change J. Chem. Phys. 2008 128 10.1063/1.2831508 18282072 60. Pouthier V. Tsybin Y.O. Amide-I relaxation-induced hydrogen bond distortion: Anintermediate in electron capture dissociation mass pectrometry of α-helical peptides? J. Chem. Phys. 2008 129 10.1063/1.2965525 19044894 61. Moritsugu K. Miyashita O. Kidera K. Vibrational energy transfer in a protein molecule Phys. Rev. Lett. 2000 85 3970 3973 10.1103/PhysRevLett.85.3970 11041973 62. Fujisaki H. Zhang Y. Straub J.E. Time-dependent perturbation theory for vibrational energy relaxation and dephasing in peptides and proteins J. Chem. Phys. 2006 124 10.1063/1.2191038 16626248 63. Pang X.F. The properties of collective excitation in organic protein molecular system J. Phys. Condens. Matter 1990 2 9541 9553 64. Pang X.F. Comment the thermodynamic properties of α-helix protein: A soliton approach Phys. Rev. 1994 49 4747 4751 65. Pang X.F. Nonlinear Quantum Mechanical Theory Chongqing Press Chongqing, China 1994 356 465 66. Pang X.F. Properties of soliton in protein molecules with nonlinear nearest neighbour interaction Chin. Sci. Bull. 1993 38 1572 1581 67. Pang X.F. The thermodynamic properties of the solitons excited in the protein molecules Chin. Sci. Bull. 1993 38 1665 1677 68. Pang X.F. Quantum-mechamical method for the soliton transported bio-energy in protein Chin. Phys. Lett. 1993 10 437 440 10.1088/0256-307X/10/7/014 69. Pang X.F. Stability of the soliton excited in protein in the biological temperature range Chin. Phys. Lett. 1993 10 573 576 10.1088/0256-307X/10/9/017 70. Pang X.F. Influence of the soliton in anharmonic molecular crystals with temperature on Mossbauer effect Eur. Phys. J. B 1999 10 415 423 10.1007/s100510050871 71. Pang X.F. Chen X.R. Distribution of vibrational energy- levels of protein molecular chains Commun. Theor. Phys. 2001 35 323 326 72. Pang X.F. The effect of Raman scattering accompanied by the soliton excitation occurred in the molecular crystals Phys. D 2001 154 138 158 10.1016/S0167-2789(01)00220-2 73. Pang X.F. An improvement of the Davydov theory of bio-energy etransport in the protein molecular systems Phys. Rev. E 2000 62 6989 6998 74. Pang X.F. The lifetime of the soliton in the improved Davydov model at the biological temperature 300 K for protein molecules Eur. Phys. J. B 2001 19 297 316 75. Pang X.F. Zhang H.W. Yu J.F. Feng Y.P. States and properties of the soliton transported bio-energy in nonuniform protein molecules at physiological temperature Phys. Lett. A 2005 335 408 416 10.1016/j.physleta.2004.12.079 76. Pang X.F. Luo Y.H. Stabilization of the soliton transported bio-energy in protein molecules in the improved model Commun. Theor. Phys. 2004 41 470 476 77. Pang X.F. Feng Y.P. Quantum Mechanics in Nonlinear Systems World Science Publisher Co. Singapore 2005 487 556 78. Pang X.F. Liu M.J. Features of Motion of Soliton Transported Bio-energy in aperiodic alpha-helix protein molecules with three channels Commun. Theor. Phys. 2009 51 170 180 79. Pang X.F. The effects of damping and temperature of medium on the soliton excited in α-helix protein molecules with three channels Mod. Phys. Lett. B 2009 23 71 88 10.1142/S0217984909017728 80. Pang X.F. Lui M.J. The influences of temperature and chain-chain interaction on features of solitons excited in α-Helix protein molecules with three channels Int. J. Mod. Phys. B 2009 23 2303 2322 10.1142/S0217979209052546 81. Pang X.F. Influence of structure disorders and temperatures of systems on the bio-energy transport in protein molecules Front. Phys. China 2008 3 457 488 10.1007/s11467-008-0039-6 82. Pang X.F. Yu J.F. Lao Y.H. Combination effects of structure nonuniformity of proteins on the soliton transported bio-energy Int. J. Mod. Phys. B 2007 21 13 42 10.1142/S021797920703659X 83. Pang X.F. Liu M.J. Properties of soliton-transported bio-energy in α-helix protein molecules with three channels Commun. Theor. Phys. 2007 48 369 376 84. Pang X.F. Theory of bio-energy transport in protein molecules and its experimental evidences as well as applications (I) Front. Phys. China 2007 2 469 493 10.1007/s11467-007-0060-1 85. Pang X.F. Zhang H.W. Theoretical investigation of properties of infrared absorption of α-helix protein molecules Int. J. Infrared Millim. Waves 2006 27 735 812 10.1007/s10762-006-9118-3 86. Pang X.F. Zhang H.W. Liu M.J. Influences of heat bath and structure disorder in protein molecules on the soliton transported bio-energy in the improved model J. Phys. Condens. Matter 2006 18 613 627 10.1088/0953-8984/18/2/018 87. Pang X.F. Zhang H.W. Yu J.F. Luo Y.H. Influences of variations of characteristic parameters arising from the structure nonuniformity of the protein molecules on states of the soliton transported bio-energy in the improved model Int. J. Mod. Phys. B 2006 20 3027 3041 10.1142/S0217979206034960 88. Pang X.F. Chen X.R. The properties of nonlinear energy-spectra of acetanilide Int. J. Mod. Phys. 2006 20 2505 2518 10.1142/S0217979206034820 89. Pang X.F. Yu J.F. Luo Y.H. Influences of quantum and disorder effects on solitons exited in protein molecules in improved model Commun. Theor. Phys. 2005 43 367 376 90. Pang X.F. Zhang H.W. Changes of the Mössbauer effect caused by the excitation of the solitons in the organic molecular crystals at finite temperature J. Phys. Chem. Solids 2005 66 963 972 91. Pang X.F. Zhang H.W. Yu J.F. Luo Y.H. Thermal stability of the new soliton transported bio-energy under influence of fluctuations of characteristic Parameters at biological temperature in the protein molecules Int. J. Mod. Phys. B 2005 19 4677 4699 10.1142/S0217979205032991 92. Pang X.F. Yu J.F. Liu M.J. Changes of properties of the soliton with temperature under influences of structure disorder in the α-helix protein molecules with three channels Mol. Phys. 2010 108 1297 1315 10.1080/00268971003674214 93. Pang X.F. Chen X.R. Calculation of vibrational energy-spectra of α-helical protein molecules and its properties Commun. Theor. Phys. 2002 37 715 722 94. Pang X.F. Chen X.R. Vibrational energy-spectra and infrared absorption of α-helical protein molecules Chin. Phys. Lett. 2002 19 1096 1099 95. Pang X.F. Nonlinear Quantum Mechanics Chinese Electronic Industry Press Beijing, China 2009 356 412 96. Pang X.F. Xiao H.L. Cue G.P. Zhang H.W. Dong B. Experiment studies of properties of infrared absorption of biological tissues Int. J. Infrared Millim. Waves 2010 31 521 532 97. Pang X.F. The properties of bio-energy transport and influence of structure nonuniformity and temperature of systems on energy transport along polypeptide chains Prog. Biophys. Mol. Biol. 2012 108 1 46 21951575 98. Pang X.F. The mechanism and properties of bio-photon emission and absorption in protein molecules in living systems J. Appl. Phys. 2012 111 10.1063/1.4709420 99. Pang X.F. The theory of bio-energy transport in the protein molecules and its properties Phys. Life Rev. 2011 8 264 286 10.1016/j.plrev.2011.06.001 21782532 100. Pang X.F. Correctness and completeness of the theory of bio-energy transport Phys. Life Rev. 2011 8 302 306 10.1016/j.plrev.2011.08.009 101. Pang X.F. The checkout and verification of theory of bio-energy transport in the protein molecules Biophys. Rev. Lett. 2014 9 1 79 10.1142/S179304801330003X 102. Pang X.F. The features of infrared spectrum of bio-polymer and its theoretical investigation Int. J. Mod. Phys. B 2014 29 10.1142/S0217979215500411 103. Su X.D. Jin F.J. Davydov-Pang model: An improved Davydov protein soliton theory Phys. Life Rev. 2011 8 300 301 10.1016/j.plrev.2011.08.004 21900056 104. Liang S.D. Physical insights to the bio-energy transport in the protein molecules Phys. Life Rev. 2011 8 287 288 10.1016/j.plrev.2011.07.013 21820981 105. Tao S. The function of soliton on bio-energy transport in the protein molecules Phys. Life Rev. 2011 8 291 292 21852208 106. He N.Y. An important biological theory—Solving the transport of bio-energy in living systems Phys. Life Rev. 2011 8 296 297 10.1016/j.plrev.2011.07.009 21831729 107. Stiefel J. Einfuhrung in die Numerische Mathematic Teubner Verlag Stuttgart, Germany 1965 78 156 108. Atkinson K.E. An Introdution to Numerical Analysis Wiley New York Inc. New York, NY, USA 1987 34 104 109. Kumar A. Singh G. Measurement of dielectric constant and loss factor of the dielectric material at microwave frequencies Prog. Electromagn. Res. 2007 69 47 54 10.2528/PIER06111204 110. Clifford E.F. Prilusky J. Silman I. Sussman J.L. A server and database for dipole moments of proteins Nucleic Acids Res. Adv. 2007 35 W512 W521 111. Antosiewicz J. Computation of the dipole moments of proteins Biophys. J. 1995 69 1344 1354 10.1016/S0006-3495(95)80001-9 8534804 112. Marracino P. Amadei A. Apollonio F. d’Inzeo G. Liberti M. diCrescenzo A. Fontana A. Zappacosta R. Aschi M. Modeling of chemical reactions in micelle: Water-mediated, Keto-Enol Interconversion as a case study J. Phys. Chem. 2011 115 8102 8111 10.1021/jp2018567 21648425 113. Careri G. Buontempo U. Galluzzi F. Scott A.C. Gratton E. Shyamsunder E. Spectroscopic evidence for Davydov-like solitons in acetanilide Phys. Rev. B 1984 30 4689 4698 10.1103/PhysRevB.30.4689 114. Careri G.A. Gransanti A. Rupley J.A. Critical exponents of protonic percolation in hydrated lysozyme powders Phys. Rev. A 1988 37 2703 2705 10.1103/PhysRevA.37.2703 115. Careri G.A. Gratton E.A. Shyamsunder E. Fine structure of the amide-I bond in acetanilide Phys. Rev. A 1988 37 4048 4051 10.1103/PhysRevA.37.4048 116. Careri G.A. Buonttempo U. Caeta F. Scott A.C. Infrared absorption in acetanilide by solitons Phys. Rev. Lett. 1983 51 304 307 10.1103/PhysRevLett.51.304 117. Careri G.A. Eilbeck J.C. Stability of solutions of the discrete self-trapping equation Phys. Lett. A 1985 109 201 204 118. Scott A.C. Davydov’s soliton revisited Phys. D 1990 51 333 342 10.1016/0167-2789(91)90243-3 119. Scott A.C. Gratton E. Shyamsunder E. Careri G. IR overtone spectrum of the vibrational soliton crystalline acetanilide Phys. Rev. B 1985 32 5551 5553 10.1103/PhysRevB.32.5551 120. Scott A.C. Bigio I.J. Johnston C.T. Polarons in acetanide Phys. Rev. B 1989 39 12883 12887 10.1103/PhysRevB.39.12883 121. Alexander D.M. Krumbansl J.A. Localized excitation in hydeogen-bonded molecular crystals Phys. Rev. B 1986 33 7172 7185 10.1103/PhysRevB.33.7172 122. Alexander D.M. Analog of small Holstein polaron in hydrogen-bonded amide systems Phys. Rev. Lett. 1985 60 138 141 10.1103/PhysRevLett.54.138 10031264 123. Weaver R.F. Molecular Biology McGraw Hill Boston, MA, USA 2002 41 125 124. Chen H.L. Structure and Function of Biomacromolecules Press of Shanghu Medicine University Shanghu, China 1998 113 122 125. Pang X.F. Molecular Bio-Physics Printer of University of Electronic Science and Technology of China Chengdu, China 2003 68 71 126. Susi H. Ard T.S. Carroll J. The infrared spectrum and water binding of collagen as a function of relative humidity Biopolymers 1971 10 1597 1604 10.1002/bip.360100913 5166550

PMC005xxxxxx/PMC5000587.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081153ijms-17-01153ArticleThe Exon Junction Complex Controls the Efficient and Faithful Splicing of a Subset of Transcripts Involved in Mitotic Cell-Cycle Progression Fukumura Kazuhiro 12*Wakabayashi Shunichi 34Kataoka Naoyuki 56Sakamoto Hiroshi 1Suzuki Yutaka 4Nakai Kenta 34Mayeda Akila 2Inoue Kunio 1da Silva Mateus Webba Academic Editor1 Department of Biology, Graduate School of Science, Kobe University, 1-1 Rokkodaicho, Nadaku, Kobe 657-8501, Japan; hsaka@kobe-u.ac.jp (H.S.); kunio@kobe-u.ac.jp (K.I.)2 Division of Gene Expression Mechanism, Institute for Comprehensive Medical Science (ICMS), Fujita Health University, Toyoake, Aichi 470-1192, Japan; mayeda@fujita-hu.ac.jp3 Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan; s-wakaba@hgc.jp (S.W.); knakai@ims.u-tokyo.ac.jp (K.N.)4 Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba 277-8561, Japan; ysuzuki@k.u-tokyo.ac.jp5 Laboratory for Malignancy Control Research, Medical Innovation Center, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan6 Laboratory of Cell Regulation, Departments of Applied Animal Sciences and Applied Biological Chemistry, Graduate School of Agriculture and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan; kataoka.naoyuki.6m@kyoto-u.ac.jp* Correspondence: fukumura@fujita-hu.ac.jp; Tel.: +81-562-93-937802 8 2016 8 2016 17 8 115316 5 2016 22 6 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).The exon junction complex (EJC) that is deposited onto spliced mRNAs upstream of exon–exon junctions plays important roles in multiple post-splicing gene expression events, such as mRNA export, surveillance, localization, and translation. However, a direct role for the human EJC in pre-mRNA splicing has not been fully understood. Using HeLa cells, we depleted one of the EJC core components, Y14, and the resulting transcriptome was analyzed by deep sequencing (RNA-Seq) and confirmed by RT–PCR. We found that Y14 is required for efficient and faithful splicing of a group of transcripts that is enriched in short intron-containing genes involved in mitotic cell-cycle progression. Tethering of EJC core components (Y14, eIF4AIII or MAGOH) to a model reporter pre-mRNA harboring a short intron showed that these core components are prerequisites for the splicing activation. Taken together, we conclude that the EJC core assembled on pre-mRNA is critical for efficient and faithful splicing of a specific subset of short introns in mitotic cell cycle-related genes. exon junction complex (EJC)Y14pre-mRNA splicingmitotic cell-cycle ==== Body 1. Introduction Pre-mRNA splicing, the correct and precise removal of introns is an essential part of gene expression in eukaryotes. The spliceosome, which catalyzes pre-mRNA splicing, deposits a multi-protein complex, called the exon junction complex (EJC), onto spliced mRNAs ~24 nucleotides (nt) upstream of exon–exon junctions in a sequence-independent manner (reviewed in [1]). The EJC is composed of four core components, eIF4AIII, Y14, MAGOH and MLN51, and many proteins that are weakly associated with the EJC core, termed EJC peripheral factors. In metazoans, the EJC core functions as a binding platform for more than a dozen peripheral protein factors that allow it to regulate multiple subsequent post-splicing gene expression events including mRNA export, mRNA localization, translation, and mRNA surveillance via nonsense-mediated mRNA decay (NMD). The well-characterized representatives of EJC peripheral factors are Aly/REF, UAP56, NXF1/TAP and NXT1/p15 that are involved in mRNA export, and UPF1, UPF2, UPF3 and SMG6 that are essential factors for NMD. Notably, the EJC peripheral factors also include several splicing regulatory proteins such as RNPS1, ACINUS, SAP18 and PININ (reviewed in [1]). RNPS1 was originally identified as a general splicing activator in vitro and as a regulator of alternative splicing in vivo [2,3,4]. RNPS1 also has roles in the 3′-end processing, translation and NMD [5,6,7]. It is known that ACINUS is involved in apoptosis, RNA processing and transcriptional regulation [8,9]. SAP18 was identified as a component of the Sin3 histone deacetylase complex that enhances transcriptional repression [10], but SAP18 is also capable of modulating alternative splicing via its ubiquitin-like fold [11]. PININ was originally identified as a desmosome-associated protein [12], but it also functions as a splicing co-activator [13]. RNPS1, SAP18, and ACINUS were identified as a ternary complex termed the apoptosis and splicing-associated protein (ASAP) complex [8]. Moreover, a recent structural analysis showed that RNPS1 and SAP18 interact with PININ, forming another ternary complex, PSAP [14]. However, it still remains unclear whether these ternary complexes are associated with the EJC core. Interestingly, it was shown that core and peripheral EJC components regulate alternative splicing of BCL-X pre-mRNA through its binding to a cis-acting element, whose activity is distinct from the established EJC function [15]. All this evidence suggested that the EJC core is capable of recruiting various splicing regulators and that these interactions may indeed regulate pre-mRNA splicing. In this study, we performed an siRNA-mediated depletion of an EJC core factor, Y14, followed by whole transcriptome analysis to identify the introns affected by Y14. Intriguingly, we found that Y14 plays a critical role in the efficient and faithful splicing of a particular group of transcripts including short introns, many of which are involved in mitotic cell-cycle progression. Accordingly, knockdown of Y14 induced G2/M arrest and apoptosis in HeLa cells. Furthermore, a tethering assay of the EJC core components (eIF4AIII, Y14 or MAGOH) demonstrated that the formation of the EJC core onto pre-mRNA (not onto mRNA) enhances splicing. These results provide a considerable insight into the EJC-mediated splicing fine-tuning mechanism for short introns in functionally related genes. 2. Results 2.1. The EJC Core Component Y14 Is Required for Efficient and Faithful Splicing of a Subset of Transcripts To investigate whether the EJC is implicated in pre-mRNA splicing, we performed a deep-sequencing analysis of transcriptome in Y14-knockdown HeLa cells, i.e., RNA-Seq analysis. DNA libraries were prepared with poly(A)+ mRNA isolated from total RNA (DNase-digested), which is derived from HeLa cells treated with Y14 siRNA or control siRNA. The resulting reads were aligned to the human genome reference sequence using the TopHat mapping tool. To examine the splicing efficiency, we calculated the intron retention rate (IRR) from the RNA-Seq data sets from control siRNA- and Y14 siRNA-treated HeLa cells as described in Supplementary Experimental Procedures. As a result, we found that 626 introns in 483 genes were retained at higher levels (IRR high score group) in Y14-knockdown HeLa cells (Supplementary Table S1A,B). In contrast, 335 introns in 250 genes were retained at lower levels (IRR low score group) in Y14-knockdown HeLa cells (Supplementary Table S1C,D). We selected 15 introns, and the RNA-Seq data were validated by RT–PCR (Figure 1A; 11 introns from the IRR high score group, two introns from the IRR low score group, and two introns as controls). We also identified five introns of which splicing was moderately inhibited in Y14-knockdown HeLa cells according to our RNA-Seq data sets (Figure 1B). These results indicated that the splicing efficiency of some specific introns is enhanced by Y14, but splicing of other specific introns is repressed. Moreover, we found that knockdown of another EJC core component, eIF4AIII, has similar splicing repressive effect on Y14-knockdown responsive introns (Supplementary Figure S1). Taken together, we conclude that the EJC core selectively affects the splicing efficiency of some particular, but not all, introns. To examine the role of the EJC in efficient pre-mRNA splicing, we focused on a set of retained introns in Y14-knockdown HeLa cells. At first, we investigated the transcripts from the AURKB (Aurora B kinase), MDM2 (murine double minute2) and ACTG1 (actin γ1) genes in Y14-knockdown cells. We tested whether the intron retention would be accompanied by the aberrant splicing, generating the abnormal mRNAs. Interestingly, Y14 knockdown resulted in the reduction of intact mRNAs accompanied by the production of several abnormal mRNAs from the MDM2 and AURKB genes (Figure 2A,B), while only the full-length transcript from the ACTG1 gene was detected in Y14-knockdown HeLa cells (Figure 2C). Sequencing of truncated transcripts for the MDM2 and AURKB genes confirmed that aberrant splicing and exon skipping occurred in Y14-knockdown HeLa cells (Figure 2A,B). These abnormal transcripts might be translated into the proteins that could be deleterious for cells, although we found the amounts of MDM2 and AURKB proteins were largely unaffected (Figure 2D). These results suggested that the EJC contributes to the efficient and proper pre-mRNA splicing of a subset of transcripts. 2.2. The Targets of Y14-Mediated Splicing Activation Are Short Introns in Genes Involved in Cell Cycle Progression It has been reported that the EJC components play an important role in proper splicing of transcripts containing long introns (>1000 nt) in Drosophila [16,17]. To examine if this is the case in mammalian cells, we investigated the size distribution of the Y14-knockdown responsive introns. Remarkably, 52.4% (328/626) of the introns in the IRR high score group, in which splicing was strongly inhibited in Y14-knockdown cells, were shorter than 500 nt (Figure 3A and Supplementary Table S2). The ratios of the shorter introns (<500 nt) in the IRR low score group and a control Ref-seq group were 37.0% (124/335) and 25.1% (34422/137116), respectively, which are significantly lower than the ratio in the IRR high score group. These results suggest that the EJC has a critical role in efficient splicing of pre-mRNAs with short introns in mammals, in stark contrast to the EJC-sensitive splicing defect of long introns in Drosophila. Next, we investigated the biological function of the 483 genes, containing 626 introns in the IRR high score group. We found that the enriched functional categories are related to mitotic cell cycle progression, including mitotic cell cycle (33/483), cell cycle check point (17/483), negative regulation of ubiquitin-protein ligase activity in mitotic cell cycle (11/483), anaphase-promoting complex-dependent proteasomal ubiquitin-dependent protein catabolic process (12/483), and regulation of ubiquitin-protein ligase activity involved in mitotic cell cycle (11/483) (Figure 3B and Supplementary Table S3). Therefore, we assumed that intron retention might disrupt proper cell cycle progression in Y14-knockdown HeLa cells. Indeed, previous studies had shown that depletion of several EJC components induces the abnormal mitotic spindle formation, genome instability, and apoptosis [15,18]. Consistent with these observations, we found that Y14-knockdown caused abnormal nuclear structures and multinuclear phenotypes, which reflected a disruption of normal cell cycle progression (Supplementary Figure S2A). To examine cell cycle progression, we employed a FACS (fluorescence-activated cell sorting) analysis and found an increase in the population of cells at the G2/M and sub G0/G1 phases in Y14-knockdown HeLa cells (Supplementary Figure S2B). Furthermore, we investigated genome stability by staining Y14-knockdown cells with an antibody against Ser139-phosphorylated histone H2A.X (γH2A.X), the marker for double-strand DNA breaks, and we found that Y14-knockdown induced an increase in H2A.X foci (Supplementary Figure S2C). Taken together, we conclude that the EJC plays a crucial role for efficient and faithful pre-mRNA splicing of the genes that are involved in mitosis and genome stability. 2.3. The Binding of the EJC Core Is Required for Splicing Activation of a Model Pre-mRNA The EJC is usually forms onto spliced mRNA, however, our implication of the EJC in splicing postulates its association with pre-mRNA. To examine whether the assembly of the EJC core onto pre-mRNA is required for the efficient splicing of Y14-knockdown responsive introns, we used the PSMB4 (proteasome subunit, β type 4) gene as a model [19]. The PSMB4 intron 5 is a typical short intron (186 nt), which is retained in Y14- and eIF4AIII-knockdown HeLa cells (Figure 1A and Supplementary Figure S1). We first confirmed the Y14 association with PSMB4 pre-mRNA containing intron 5 by immunoprecipitation using the Y14 antibody. As expected, Y14 strongly associated with the intron 5-harboring pre-mRNA as well as the intron 5-excised mRNA. On the other hand, the translation initiation factor eIF4E only associated with the spliced mRNA (Figure 4A). These results suggested that the EJC is indeed formed on PSMB4 pre-mRNA. We next investigated whether the EJC could increase the splicing efficiency of PSMB4 pre-mRNA with intron 5. We employed a tethering assay using the λN-BoxB system, which uses the λN peptide to tether the protein of interest to RNAs [20]. We constructed the PSMB4 exon 5–exon 6 mini-gene fused with five copies of BoxB sequences at the 3′ terminus of exon 6 and the effecter plasmids encoding HA-λN tagged EJC core components (eIF4AIII, Y14 or MAGOH) (Figure 4B). To prevent the NMD-degradation of RNA products from the PSMB4 mini-gene during this tethering assay, we performed the experiment in the context of siRNA-mediated UPF1 knockdown that represses NMD [20]. Western blotting was performed to check the protein expression levels of HA-λN tagged EJC components as well as the depletion efficiency of endogenous UPF1. The experiments showed that protein expression level of HA-λN-eIF4AIII was higher than those of HA-λN-Y14 and HA-λN-MAGOH under the efficient depletion of endogenous UPF1 (Figure 4C). We then performed RT–PCR to examine the splicing efficiency of the PSMB4 reporter transcript. Splicing efficiency was increased when the pre-mRNA was tethered with the EJC core components (Figure 4D). We observed that splicing activation by eIF4AIII (approximately five-fold increase compared to HA-λN control) was higher than that caused by Y14 or MAGOH (approximately two-fold increase compared to HA-λN control). It is thus likely that this difference of splicing activation was due to the expression levels of the tethered proteins. In these tethering experiments, we assume that one of the tethered EJC core factors (eIF4AIII, Y14, or MAGOH) would be able to associate with the rest of the endogenous EJC core factors. Next, we performed the tethering of eIF4AIII or MAGOH to PSMB4 reporter transcripts in Y14-knockdown HeLa cells, where it was expected that neither tethered eIF4AIII nor MAGOH could form the EJC core. Western blot analysis confirmed the protein expression levels of HA-λN-eIF4AIII and HA-λN-MAGOH, and the depletion of endogenous Y14 (Figure 4E). RT–PCR analysis revealed that splicing efficiencies of PSMB4 reporter transcripts tethered with eIF4AIII or MAGOH were no longer enhanced in the absence of Y14 (Figure 4F). These results suggest that the EJC core formation on pre-mRNA is a prerequisite for observed splicing activation. 2.4. RNPS1 Is a Key Factor in EJC Core-Mediated Splicing Activation Our results indicated that the EJC core recruits a trans-acting factor to activate splicing. The EJC core has been reported to associate with accessory factors involved in pre-mRNA splicing, mRNA export, NMD, and translation (reviewed in [1]). To identify the EJC-recruited accessory proteins that promote the efficient splicing, we performed siRNA-mediated knockdown of RNPS1 (splicing activator/regulator) and UPF1 (essential NMD factor). Western blot analysis confirmed that Y14, RNPS1 and UPF1 were efficiently depleted (Figure 5A). Interestingly, RT–PCR analysis showed that RNPS1 knockdown induced the retention of several (Figure 5B), but not all (Figure 5C), Y14-knockdown responsive introns (Figure 5B). In contrast, UPF1 knockdown did not induce intron retention, indicating that intron retentions by Y14 or RNPS1 knockdown are not due to the survival of transcript generated by the loss of NMD function. In addition, we checked the transcripts of MDM2, AURKB and ACTG1 by RT–PCR in RNPS1- or UPF1-knockdown HeLa cells. Here, we observed abnormal transcripts of MDM2 and AURKB (both contain Y14-knockdown responsive introns) and concomitant reduction of AURKB protein level in RNPS1-knockdown cells (Supplementary Figure S3A,B,D). In contrast, we detected only the full-length transcript of ACTG1 (contains control Y14-knockdown nonresponsive intron) (Supplementary Figure S3C). These results strongly suggest that RNPS1 interacts with the EJC core and promotes the efficient and faithful pre-mRNA splicing of the target Y14-knockdown responsive introns. 3. Discussion It has been recently shown that knockdown of the EJC core factor causes global alternative splicing changes in mammalian cells [21]. Our Y14-knockdown experiments followed by RNA-Seq analysis uncover an important new aspect of the EJC core function. We found that the EJC core contributes, not only to the efficiency, but also to the fidelity of constitutive splicing in a set of functionally related genes. 3.1. The EJC as a Master Splicing Controller of Genes Involved in Cell Cycle Progression The EJC was documented to have multiple roles in the post-splicing events of mammalian gene expression (reviewed in [1]). Here, we demonstrate that the EJC core component Y14 is required for the efficient splicing of target introns in many genes involved in mitotic cell cycle progression. The Y14-knockdown derived intron-retention events were also accompanied by a variety of aberrant splicing, such as alternative splice site usage and exon skipping. The generation of these abnormal transcripts naturally leads to a reduction of the full-length transcripts. The abnormal transcripts may often be dead-end mRNAs that are destined to be degraded or they may even produce antagonistic or dominant negative proteins, which disturb correct mitotic cell cycle progression. Consistently, it was previously shown that depletion of Y14 results in G2/M cell cycle arrest followed by apoptosis [22]. Here, we observed that Y14 knockdown in HeLa cells induces abnormal nuclear structure, multinucleated cells, G2/M cell cycle arrest, and genome instability. We identified various abnormal transcripts of AURKB (Aurora B kinase) and MDM2 (murine double minute 2) genes in Y14-knockdown HeLa cells. AURKB, a serine/threonine kinase, functions in chromosome segregation, cleavage of polar spindle microtubules and cytokinesis [23]. Inhibition of the AURKB function in mitotic cells causes misaligned chromosomes and defective cytokinesis, which results in polyploidy (≥4N cells) [23,24]. MDM2 possesses E3 ubiquitin ligase activity that targets P53, and MDM2 knockout in mouse germ line causes embryonic lethality at the blastocyst stage due to inappropriate apoptosis [25,26,27]. Thus, the known functions of MDM2 and AURKB would be able to explain a part of the phenotype caused by Y14 knockdown. The changes in transcript level, alternative splicing, and protein level in the core EJC-deficient cells were reported to cause the disruption of proper cell cycle progression and the apoptosis process, which is indeed consistent with our results. Mouse Magoh mutant haplo-insufficiency causes the defect of mitosis of neural stem cells and apoptosis, which are rescued by restoring the expression of Lis1, a microtubule-associated protein essential for mitotic spindle integrity [18]. Moreover, a recent study demonstrated that the EJC components regulate the alternative splicing of several apoptotic genes; i.e., knockdown of the EJC core (Y14 and eIF4AIII) or splicing-related EJC peripheral (RNPS1, ACINUS and SAP18) proteins increases the production of the pro-apoptotic splice variant of Bcl-xS pre-mRNA [15]. Taking our findings and these studies together, we conclude that the EJC plays an important role in the expression of genes involved in proper cell cycle progression and apoptosis. 3.2. Molecular Mechanisms of EJC-Mediated Splicing Regulation We found that the EJC core factor, Y14, controls splicing of a specific group of short-intron. Using the model PSMB4 pre-mRNA harboring intron 5 (186 nt), we showed that the EJC deposition near the intron is critical to stimulating splicing activity. Recent studies in Drosophila also indicated that efficient splicing of the piwi pre-mRNA containing intron 4 is promoted by RnpS1 and Acinus, which are recruited by the pre-deposited EJC at adjacent spliced exon junctions [28,29]. It was proposed that pre-mRNA splicing of short introns occurs by the formation of a splicing complex across the introns (termed “intron definition”), whereas that of long intron, a cross-exon splicing complex is formed (termed “exon definition”) prior to the splicing of adjacent introns [30,31]. Therefore, the deposit of the EJC may underpin precise short intron recognition and formation of a stable intron definition complex. Previously, it was shown that the EJC associates with several splicing regulators such as RNPS1, PININ, ACINUS, and SAP18, which contain specific domains that are capable of interacting with general splicing factors (reviewed in [1]). Here, we demonstrate that the EJC-peripheral factor, RNPS1 at least, is the trans-acting factor for the efficient splicing of pre-mRNAs containing Y14-knockdown responsive short introns. On the other hand, RNPS1 was reported to be associated with SAP18 and ACINUS, to form the apoptosis and splicing-associated protein (ASAP) complex [8]. Moreover, a recent structural analysis revealed that RNPS1 and SAP18 are able to interact with PININ, forming another ternary complex, PSAP [14]. Therefore, it remained to be elucidated whether RNPS1 solely or RNPS1 complex, such as ASAP (PSAP), is responsible for the EJC core mediated splicing activation. Taken together, we propose the model that the initial deposition of the EJC core at adjacent (upstream and/or downstream) spliced junctions recruits EJC-peripheral splicing regulator(s), either RNPS1 alone or in the ASAP (PSAP) complex, to promote the efficient or stable formation of intron definition complexes on the proximate short intron (Figure 6). This finding provides a mechanistic link between the originally identified RNPS1 as a general splicing activator/regulator [2,3] and the detection of RNPS1 as a peripheral component of the EJC (reviewed in [1]). Interestingly, we observed pre-mRNA splicing activation, not inhibition, by the Y14-knockdown experiment in another specific subset of pre-mRNAs, suggesting EJC-mediated repression rather than activation of splicing. In this opposite case, it will be interesting to ascertain what is the trans-acting factor recruited by EJC core to promote splicing repression. We wish to propose that the EJC core as potential master splicing controller with potential to recruit splicing regulators, either positive or negative, to define distinct splicing activity modes. 4. Experimental Procedures 4.1. Plasmid Constructions and Antibodies To construct pCS2-HA-λN-eIF4AIII, pCS2-HA-λN-Y14, and pCS2 -HA-λN-MAGOH, cDNAs were amplified by PCR and subcloned into pCS2-HA-λN vector as previously described [32]. Five contiguous copies of the BoxB sequence were amplified by PCR from pCS2+Rluc-BoxB [32], and cloned into pcDNA3 (Thermo Fisher Scientific, Waltham, MA, USA). The pcDNA3-PSMB4-5BoxB mini-gene was obtained by subcloning PCR-amplified HeLa genomic DNA containing the exon 5, intron 5 and exon 6 region into the pcDNA3-5BoxB vector. The following antibodies were commercially available: anti-Y14 (Sigma, St. Louis, MO, USA), anti-UPF1 and anti α-tubulin (Cell Signaling Technology, Danvers, MA, USA), and anti-MDM2 and anti-AURKB (Abcam, Cambridge, UK). The anti-RNPS1 antibody was previously described [2]. 4.2. Cell Culture and siRNA Knockdown HeLa cells were maintained in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum. ON-TARGET plus SMART pool siRNA reagents and negative control siRNA (GE Healthcare, Chicago, IL, USA) were used to knockdown the expression of Y14, RNPS1 and UPF1. Transfection of the siRNA was performed with Lipofectamine RNAiMax (Thermo Fisher Scientific) according to the manufacture’s protocol. HeLa cells were grown in 35 mm dishes and transfected with each siRNA (100 pmol). At 48 h post-transfection, total proteins and RNAs were isolated from the siRNA-treated HeLa cells using ISOGEN (Wako, Kyoto, Japan). 4.3. RNA-Seq Analysis For RNA-Seq, mRNA isolation and DNA library preparation were performed according to the manufacturer’s protocol (Illumina, San Diego, CA, USA). The DNA libraries were prepared from four independent RNA sources; HeLa cells treated with two control siRNAs and two Y14 siRNAs. These samples were sequenced on a high-throughput platform (HiSeq2000, Illumina) using a 76 bp single-end strategy. The reads were mapped onto the hg19 human genome sequences using the TopHat 1.12.0 (https://ccb.jhu.edu/software/tophat/index.shtml). All positions of junctions contained in the mapping results were annotated as an intron in the ENSEMBL annotation database (http://asia.ensembl.org/index.html). Our RNA-Seq analysis is shown in Supplementary Experimental Procedures. RNA-Seq raw data have been deposited in DDBJ database (http://www.ddbj.nig.ac.jp/index-e.html) under accession No. DRA004068. 4.4. Tethering Experiments For the tethering assays, 0.1 µg of pcDNA3-PSMB4-5BoxB with 0.5 µg of pCS2-HA-λN-eIF4AIII, pCS2-HA-λN-Y14 or pCS2-HA-λN-MAGOH were co-transfected into UPF1 siRNA- or Y14 siRNA-treated HeLa cells in 35 mm dishes, using PolyFect transfection reagent (QIAGEN, Venlo, The Netherlands). Transfected HeLa cells were cultured for 24 h before extraction of proteins and RNAs. Expression level of HA-λN fusion proteins and endogenous UPF1 or Y14 protein were examined by Western blotting. To analyze splicing products from the PSMB4 mini-gene, total RNA from transfected cells were analyzed by RT–PCR using T7 and PSMB4-E6AS-XhoI primers (Supplementary Table S4). PCR products were analyzed by 1.5% or 2% agarose gel electrophoresis. Splicing products were quantified using NIH Image J software (https://imagej.nih.gov/ij/) [33,34]. 4.5. Immunoprecipitation Experiments For immunoprecipitation of Y14 and eIF4E-associated mRNA, whole HeLa cell extracts were prepared and mixed with antibodies conjugated with Dynal beads protein G (Invitrogen, Carlsbad, CA, USA) in NET2 buffer [35]. After a 3 h incubation at 4 °C, the beads were washed six times with NET2 buffer and bound RNA was recovered by phenol extraction and ethanol precipitation. The precipitated RNAs were analyzed by RT–PCR. Acknowledgments We would like to thank Samuel I. Gunderson for U1-70K anti-bodies. We are especially grateful to Yuichiro Mishima and Teruaki Takasaki for exciting discussion and valuable comments. Computational resources were provided by the supercomputer system at Human Genome Center, Institute of Medical Science, the University of Tokyo. This work was supported by Grants-in-Aid for Scientific Research (Grant Numbers 23510234 and 26290062) from Japan Society for the Promotion of Science (JSPS). Supplementary Materials Supplementary materials can be found at http://www.mdpi.com/1422-0067/17/8/1153/s1. Click here for additional data file. Author Contributions Kazuhiro Fukumura, Shunichi Wakabayashi, Kenta Nakai and Kunio Inoue designed experiments, and Kazuhiro Fukumura, Shunichi Wakabayashi, and Yutaka Suzuki performed experiments. Kazuhiro Fukumura, Shunichi Wakabayashi, Naoyuki Kataoka, Hiroshi Sakamoto, Kenta Nakai, Akila Mayeda and Kunio Inoue analyzed the data, and Kazuhiro Fukumura, Shunichi Wakabayashi, Kenta Nakai, Akila Mayeda and Kunio Inoue wrote and edited the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 A subset of introns are retained upon Y14 knockdown. RNA-Seq-based selection was performed with total RNAs that were prepared from control siRNA- or Y14 siRNA-treated HeLa cells. The selected representative introns were analyzed by RT–PCR (see Supplementary Table S4 for primer sequences). All PCR products were subcloned and the sequences were verified. The schematic representation on the right of each panel indicates the corresponding unspliced- and spliced-products. (A) The upper and lower left panels represent the IRR high score group (log 2 [Y14 IRR/Ctl IRR] ≥ 1.0, p < 0.05) and low score group (log 2 [Y14 IRR/Ctl IRR] ≤ −1.0, p < 0.05), respectively. The lower right panel shows the control group with CDK1 (E5–E6) and ACTG1 (E3–E4) pre-mRNAs; their splicing efficiencies were not changed either in Y14 siRNA- or in control siRNA-treated cells; and (B) these five selected introns were categorized in the following IRR score group (0 < log 2 [Y14 IRR/Ctl IRR] < 1, p < 0.05 or log 2 [Y14 IRR/Ctl IRR] ≥ 1.0, p > 0.05), in which RT–PCR analyses showed apparent intron retention in sY14 siRNA-treated cells. Figure 2 Y14 is required for faithful splicing of MDM2 and AURKB pre-mRNAs. (A–C) HeLa cells were transfected with control siRNA or Y14 siRNA and obtained total RNAs at 48 h post-transfection were analyzed by RT–PCR using primer sets for MDM2 (A), AURKB (B), and ACTG1 (C) transcripts. The RT–PCR products were subcloned and the sequences were verified. The schematic representation on the right indicates the corresponding mRNA products. Black boxes represent full-length exons and grey boxes represent truncated exons generated by alternative splice site usage; and (D) Western blot analysis of whole cell extracts of control siRNAs- or Y14 siRNA-treated HeLa cell using anti-Y14, anti-MDM2, anti-AURKB, and anti-TUBULIN antibodies. Figure 3 A majority of retained introns in Y14 knockdown cells are short (<500 nt) and exist in a subset of genes involved in cell cycle and apoptosis. (A) Retained introns in control siRNA-, Y14 siRNA-treated HeLa cells and RefSeq were grouped by length and plotted as a ratio to the total introns; and (B) gene ontology (GO) analysis indicated the functions of 483 genes that showed intron retention inY14 siRNA-treated HeLa cells. Figure 4 Core EJC assembly is required for increased splicing efficiency of the mini-PSMB4 model pre-mRNA. (A) Whole HeLa cell extracts were subjected to immunoprecipitation (IP) using anti-Y14 or anti-eIF4E antibody in the absence of RNase A. Total RNAs (5% of input) and co-precipitated RNAs were analyzed by RT–PCR using primer sets for PSMB4 (E5–E6) and ACTG1 (E3–E4). The schematic representation on the right indicates the corresponding unspliced- and spliced-products. Asterisk (*) indicates non-specific PCR products; (B) The schematic representation of a model PSMB4 exon 5–exon 6 pre-mRNA fused with five BoxB sites in the downstream of exon 6. The HA-λN tagged EJC core components (eIF4AIII, Y14 and MAGOH) are represented by the oval; (C) Western blot analysis of expressed HA-λN fusion proteins and endogenous UPF1 protein. UPF1 siRNA-treated HeLa cells were transfected with the PSMB4 E5–E6-5×BoxB mini-gene plasmids and the indicated HA-λN-tagged EJC component plasmids; (D) RT–PCR analysis was performed to detect the unspliced- and spliced- products from the PSMB4 E5–E6 mini-gene. All experiments were independently repeated three times. Averages and standard deviations of the relative amount of spliced mRNA are shown in the right panel; and (E,F) the same tethering experiments as (C,D) using Y14 siRNA-treated HeLa cells. Figure 5 RNPS1 is required for efficient removal of some, but not all, EJC core-responsive introns. (A) HeLa cells were transfected with specific siRNAs against Y14, RNPS1, UPF1, or control (Ctl). At 48 h post-transfection, whole cell extracts were subjected to Western blot analysis. The asterisk (*) indicates a non-specific signal; and (B,C) total RNAs were isolated and analyzed by RT–PCR using primer sets for MDM2, AURKB and ACTG1 (shown in Supplementary Table S4). The schematic representation on the right of each panel indicates the corresponding unspliced- and spliced-products. Figure 6 A model of EJC mediated splicing activation. RNPS1 and other EJC associated splicing regulators interact with the core EJC and recruit general splicing factors to essential splicing elements of specific short introns, leading to the efficient or stable formation of an intron definition complex. ==== Refs References 1. Le Hir H. Sauliere J. Wang Z. The exon junction complex as a node of post-transcriptional networks Nat. Rev. Mol. Cell Biol. 2016 17 41 54 10.1038/nrm.2015.7 26670016 2. Mayeda A. Badolato J. Kobayashi R. Zhang M.Q. Gardiner E.M. Krainer A.R. Purification and characterization of human RNPS1: A general activator of pre-mRNA splicing EMBO J. 1999 18 4560 4570 10.1093/emboj/18.16.4560 10449421 3. Sakashita E. Tatsumi S. Werner D. Endo H. Mayeda A. Human RNPS1 and its associated factors: A versatile alternative pre-mRNA splicing regulator in vivo Mol. Cell. Biol. 2004 24 1174 1187 10.1128/MCB.24.3.1174-1187.2004 14729963 4. Trembley J.H. Tatsumi S. Sakashita E. Loyer P. Slaughter C.A. Suzuki H. Endo H. Kidd V.J. Mayeda A. Activation of pre-mRNA splicing by human RNPS1 is regulated by CK2 phosphorylation Mol. Cell. Biol. 2005 25 1446 1457 10.1128/MCB.25.4.1446-1457.2005 15684395 5. Lykke-Andersen J. Shu M.D. Steitz J.A. Communication of the position of exon–exon junctions to the mRNA surveillance machinery by the protein RNPS1 Science 2001 293 1836 1839 10.1126/science.1062786 11546874 6. Viegas M.H. Gehring N.H. Breit S. Hentze M.W. Kulozik A.E. The abundance of RNPS1, a protein component of the exon junction complex, can determine the variability in efficiency of the Nonsense Mediated Decay pathway Nucleic Acids Res. 2007 35 4542 4551 10.1093/nar/gkm461 17586820 7. McCracken S. Longman D. Johnstone I.L. Caceres J.F. Blencowe B.J. An evolutionarily conserved role for SRm160 in 3’-end processing that functions independently of exon junction complex formation J. Biol. Chem. 2003 278 44153 44160 10.1074/jbc.M306856200 12944400 8. Schwerk C. Prasad J. Degenhardt K. Erdjument-Bromage H. White E. Tempst P. Kidd V.J. Manley J.L. Lahti J.M. Reinberg D. ASAP, a novel protein complex involved in RNA processing and apoptosis Mol. Cell. Biol. 2003 23 2981 2990 10.1128/MCB.23.8.2981-2990.2003 12665594 9. Joselin A.P. Schulze-Osthoff K. Schwerk C. Loss of Acinus inhibits oligonucleosomal DNA fragmentation but not chromatin condensation during apoptosis J. Biol. Chem. 2006 281 12475 12484 10.1074/jbc.M509859200 16537548 10. Zhang Y. Iratni R. Erdjument-Bromage H. Tempst P. Reinberg D. Histone deacetylases and SAP18, a novel polypeptide, are components of a human Sin3 complex Cell 1997 89 357 364 10.1016/S0092-8674(00)80216-0 9150135 11. Singh K.K. Erkelenz S. Rattay S. Dehof A.K. Hildebrandt A. Schulze-Osthoff K. Schaal H. Schwerk C. Human SAP18 mediates assembly of a splicing regulatory multiprotein complex via its ubiquitin-like fold RNA 2010 16 2442 2454 10.1261/rna.2304410 20966198 12. Ouyang P. Sugrue S.P. Characterization of pinin, a novel protein associated with the desmosome-intermediate filament complex J. Cell Biol. 1996 135 1027 1042 10.1083/jcb.135.4.1027 8922384 13. Wang P. Lou P.J. Leu S. Ouyang P. Modulation of alternative pre-mRNA splicing in vivo by pinin Biochem. Biophys. Res. Commun. 2002 294 448 455 10.1016/S0006-291X(02)00495-3 12051732 14. Murachelli A.G. Ebert J. Basquin C. Le Hir H. Conti E. The structure of the ASAP core complex reveals the existence of a Pinin-containing PSAP complex Nat. Struct. Mol. Biol. 2012 19 378 386 10.1038/nsmb.2242 22388736 15. Michelle L. Cloutier A. Toutant J. Shkreta L. Thibault P. Durand M. Garneau D. Gendron D. Lapointe E. Couture S. Proteins associated with the exon junction complex also control the alternative splicing of apoptotic regulators Mol. Cell. Biol. 2012 32 954 967 10.1128/MCB.06130-11 22203037 16. Sauliere J. Haque N. Harms S. Barbosa I. Blanchette M. Le Hir H. The exon junction complex differentially marks spliced junctions Nat. Struct. Mol. Biol. 2010 17 1269 1271 10.1038/nsmb.1890 20818392 17. Roignant J.Y. Treisman J.E. Exon junction complex subunits are required to splice Drosophila MAP kinase, a large heterochromatic gene Cell 2010 143 238 250 10.1016/j.cell.2010.09.036 20946982 18. Silver D.L. Watkins-Chow D.E. Schreck K.C. Pierfelice T.J. Larson D.M. Burnetti A.J. Liaw H.J. Myung K. Walsh C.A. Gaiano N. The exon junction complex component Magoh controls brain size by regulating neural stem cell division Nat. Neurosci. 2010 13 551 558 10.1038/nn.2527 20364144 19. Nothwang H.G. Tamura T. Tanaka K. Ichihara A. Sequence analyses and inter-species comparisons of three novel human proteasomal subunits, HsN3, HsC7-I and HsC10-II, confine potential proteolytic active-site residues Biochim. Biophys. Acta 1994 1219 361 368 10.1016/0167-4781(94)90060-4 7918633 20. Gehring N.H. Kunz J.B. Neu-Yilik G. Breit S. Viegas M.H. Hentze M.W. Kulozik A.E. Exon-junction complex components specify distinct routes of nonsense-mediated mRNA decay with differential cofactor requirements Mol. Cell 2005 20 65 75 10.1016/j.molcel.2005.08.012 16209946 21. Wang Z. Murigneux V. Le Hir H. Transcriptome-wide modulation of splicing by the exon junction complex Genome Biol. 2014 15 551 10.1186/s13059-014-0551-7 25476502 22. Ishigaki Y. Nakamura Y. Tatsuno T. Hashimoto M. Shimasaki T. Iwabuchi K. Tomosugi N. Depletion of RNA-binding protein RBM8A (Y14) causes cell cycle deficiency and apoptosis in human cells Exp. Biol. Med. (Maywood) 2013 238 889 897 10.1177/1535370213494646 23970407 23. Nair J.S. Ho A.L. Tse A.N. Coward J. Cheema H. Ambrosini G. Keen N. Schwartz G.K. Aurora B kinase regulates the postmitotic endoreduplication checkpoint via phosphorylation of the retinoblastoma protein at serine 780 Mol. Biol. Cell 2009 20 2218 2228 10.1091/mbc.E08-08-0885 19225156 24. Nigg E.A. Mitotic kinases as regulators of cell division and its checkpoints Nat. Rev. Mol. Cell Biol. 2001 2 21 32 10.1038/35048096 11413462 25. Manfredi J.J. The Mdm2-p53 relationship evolves: Mdm2 swings both ways as an oncogene and a tumor suppressor Genes Dev. 2010 24 1580 1589 10.1101/gad.1941710 20679392 26. Jones S.N. Roe A.E. Donehower L.A. Bradley A. Rescue of embryonic lethality in Mdm2-deficient mice by absence of p53 Nature 1995 378 206 208 10.1038/378206a0 7477327 27. Montes de Oca Luna R. Wagner D.S. Lozano G. Rescue of early embryonic lethality in mdm2 -deficient mice by deletion of p53 Nature 1995 378 203 206 10.1038/378203a0 7477326 28. Hayashi R. Handler D. Ish-Horowicz D. Brennecke J. The exon junction complex is required for definition and excision of neighboring introns in Drosophila Genes Dev. 2014 28 1772 1785 10.1101/gad.245738.114 25081352 29. Malone C.D. Mestdagh C. Akhtar J. Kreim N. Deinhard P. Sachidanandam R. Treisman J. Roignant J.Y. The exon junction complex controls transposable element activity by ensuring faithful splicing of the piwi transcript Genes Dev. 2014 28 1786 1799 10.1101/gad.245829.114 25104425 30. Berget S.M. Exon recognition in vertebrate splicing J. Biol. Chem. 1995 270 2411 2414 10.1074/jbc.270.6.2411 7852296 31. Wahl M.C. Will C.L. Luhrmann R. The spliceosome: Design principles of a dynamic RNP machine Cell 2009 136 701 718 10.1016/j.cell.2009.02.009 19239890 32. Mishima Y. Fukao A. Kishimoto T. Sakamoto H. Fujiwara T. Inoue K. Translational inhibition by deadenylation-independent mechanisms is central to microRNA-mediated silencing in zebrafish Proc. Natl. Acad. Sci. USA 2012 109 1104 1109 10.1073/pnas.1113350109 22232654 33. Fukumura K. Taniguchi I. Sakamoto H. Ohno M. Inoue K. U1-independent pre-mRNA splicing contributes to the regulation of alternative splicing Nucleic Acids Res. 2009 37 1907 1914 10.1093/nar/gkp050 19190090 34. Fukumura K. Kato A. Jin Y. Ideue T. Hirose T. Kataoka N. Fujiwara T. Sakamoto H. Inoue K. Tissue-specific splicing regulator Fox-1 induces exon skipping by interfering E complex formation on the downstream intron of human F1γ gene Nucleic Acids Res. 2007 35 5303 5311 10.1093/nar/gkm569 17686786 35. Ideue T. Sasaki Y.T. Hagiwara M. Hirose T. Introns play an essential role in splicing-dependent formation of the exon junction complex Genes Dev. 2007 21 1993 1998 10.1101/gad.1557907 17675447 36. Shibuya T. Tange T.O. Sonenberg N. Moore M.J. eIF4AIII binds spliced mRNA in the exon junction complex and is essential for nonsense—Mediated decay Nat. Struct. Mol. Biol. 2004 11 346 351 10.1038/nsmb750 15034551 37. Trapnell C. Williams B.A. Pertea G. Mortazavi A. Kwan G. van Baren M.J. Salzberg S.L. Wold B.J. Pachter L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation Nat. Biotechnol. 2010 28 511 515 10.1038/nbt.1621 20436464 38. Roberts A. Trapnell C. Donaghey J. Rinn J.L. Pachter L. Improving RNA-Seq expression estimates by correcting for fragment bias Genome Biol. 2011 12 R22 10.1186/gb-2011-12-3-r22 21410973 39. Roberts A. Pimentel H. Trapnell C. Pachter L. Identification of novel transcripts in annotated genomes using RNA-Seq Bioinformatics 2011 27 2325 2329 10.1093/bioinformatics/btr355 21697122

PMC005xxxxxx/PMC5000588.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081165ijms-17-01165ArticleA Female-Biased Odorant Receptor from Apolygus lucorum (Meyer-Dür) Tuned to Some Plant Odors Zhang Zhixiang 12Zhang Meiping 1*Yan Shuwei 2Wang Guirong 2Liu Yang 2*Schuster Bernhard Academic Editor1 School of Life Science, Shanxi Normal University, Linfen 041000, China; zhang3121414@126.com2 State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China; ysw_0220@163.com (S.Y.); grwang@ippcaas.cn (G.W.)* Correspondence: zhangmp2006@163.com (M.Z.); yangliu@ippcaas.cn (Y.L.); Tel.: +86-357-205-1197 (M.Z.); +86-10-6281-6947 (Y.L.)28 7 2016 8 2016 17 8 116511 5 2016 08 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).Apolygus lucorum (Meyer-Dür) (Hemiptera: Miridae) is a serious pest of cotton, jujube, grape and many other crops around the world. Understanding how olfactory information directs this insect to its host plants may provide environment-friendly approaches to the control of its population in agriculture. In our study, we cloned an odorant receptor gene, AlucOR46, that was specifically expressed in antennae and female-biased. Functional expression of AlucOR46 in Xenopus oocytes showed that it is tuned to six plant volatiles (S)-(−)-Limonene, (R)-(+)-Limonene, (E)-2-Hexenal, (E)-3-Hexenol, 1-Heptanol and (1R)-(−)-Myrtenol. Electroantennogram (EAG) recordings revealed that all six compounds could elicit electrophysiological responses from the antennae of A. lucorum, higher in females. Our results are in agreement with previous reports showing that (E)-2-Hexenal could attract female A. lucorum in behavior experiments. These results suggest that AlucOR46 might play an important role in locating the host plants of A. lucorum and therefore represents a suitable target for green pest control. Apolygus lucorumodorant receptorplant volatileXenopus oocyteselectroantennogram ==== Body 1. Introduction The green mirid bug, Apolygus lucorum (Meyer-Dür) (Hemiptera: Miridae) is an important worldwide pest. Before commercial cultivation of transgenic Bacillus thuringiensis (Bt) cotton in China, Helicoverpa armigera was the major cotton pest while populations of A. lucorum were kept at a low level. However, since the widespread planting of trans-Bt cotton and reduction of insecticide spraying, the population of A. lucorum increased dramatically so that it has become the key insect pest for cotton and several other agricultural crops [1]. Due to its serious damage in agriculture, A. lucorum became the object of many studies on its life cycle, habits and host plants preference [2,3,4]. A. lucorum is a highly polyphagous insect and feeds on over one hundred plant species. Furthermore, it can easily and frequently switch between habitats and host plants [1,3,5]. As shown in previous studies, host preference and other behaviors in insects are modulated by host plant volatiles [6,7]. Therefore, accurate perception of plant volatiles is highly important for the adaptability of this phytophagous insect to different environmental conditions. Behavior experiments using a Y-shaped olfactometer in the laboratory and field observations were performed to study the preferences of A. lucorum adults to six different host plant species and their volatiles [8]. Electroantennogram (EAG) responses of adult A. lucorum to different plant volatiles have also been recorded [9]. Six electrophysiologically active compounds were identified, four of which also proved to be strong attractants for adults of A. lucorum [10]. However, the physiological and biochemical mechanisms underlying the detection of these compounds still need to be investigated. A sophisticated olfactory system is essential for survival and reproduction, allowing insects to locate food sources, identify mates and avoid predators [11]. Odorants entering olfactory sensilla interact with soluble odorant-binding proteins (OBPs), present in the sensillar lymph, and with membrane-bound odorant receptors (ORs) [12]. ORs, which represent the key elements of odor detection, present seven transmembrane domains (TMDs) with inverted membrane topology, where the N-terminus is intracellular and the C-terminus extracellular [13,14,15]. They are believed to act as ligand-gated ion channels formed by the interaction of individual specific receptors with a conserved co-receptor, named Orco [15,16,17,18]. RNA interference (RNAi) experiments have shown that Orco is required for olfaction in A. lucorum [19]. In our previous study, we have cloned four OR genes from this species, one of which was tuned to (Z)-3-Hexenyl acetate and several other floral compounds [20]. In the present study we report the functional characterization of another OR (AlucOR46), selected among the 80 OR genes identified in the antennae by a transcriptome project (Yang Liu, unpublished), selected on the basis of its female-biased expression. When expressed in Xenopus oocytes, AlucOR46 specifically responds to six plant volatiles that also elicit electrophysiological responses from the antennae of A. lucorum in a female-biased fashion. This receptor might be involved in locating the host plant and could represent a candidate target for pest control. 2. Results 2.1. Gene Cloning and Sequence Analysis Based on the analysis of A. lucorum antennal transcriptome (Yang Liu, unpublished), we cloned a full-length OR gene, AlucOR46 (GenBank accession number: KU188516), with an open reading frame (ORF) of 1185 bp, encoding a protein of 394 amino acids. AlucOR46 is predicted to present 7 TMDs with an intracellular N-terminus and an extracellular C-terminus. Its identity with other ORs of the same species is very poor, 12.7% with AlucOrco and between 10% and 16% with other individual ORs (Figure 1). 2.2. Tissue Expression Pattern of AlucOR46 The expression pattern of AlucOR46 in different tissues of male and female A. lucorum was monitored by quantitative real-time PCR (qRT-PCR). The results show that AlucOR46 was mainly expressed in antennae with female levels nearly four times those of males, making AlucOR46 a typical female-biased gene (Figure 2). 2.3. Functional Characterization of AlucOR46 To identify ligands for this receptor, AlucOR46 was coexpressed with AlucOrco in Xenopus oocytes and responses to odorants were recorded using two-electrode voltage clamp. We used 65 compounds including terpenoids, alcohols, aldehydes and benzoates. Only six compounds: (S)-(−)-Limonene, (R)-(+)-Limonene, (E)-2-Hexenal, (E)-3-Hexenol, 1-Heptanol and (1R)-(−)-Myrtenol were found to elicit responses from AlucOR46/Orco, the last four being stronger than the other two (Figure 3). We then determined dose-response curves for the best four compounds and calculated half maximal effective concentration (EC50) values to be 3.71 × 10−5, 2.53 × 10−5, 1.38 × 10−5 and 7.44 × 10−5 M for (E)-2-Hexenal, (E)-3-Hexenol, 1-Heptanol and (1R)-(−)-Myrtenol, respectively (Figure 4 and Table 1). 2.4. Electrophysiological Responses of A. lucorum Antennae Next we recorded the electrophysiological responses of female and male antennae of A. lucorum to the six compounds selected in the Xenopus assay. The mean EAG response value to the blank stimulus (10 μL hexane) was 84.44 ± 3.74 (mean ± SEM) μV for A. lucorum females and 80.28 ± 4.84 μV for males. The mean response values to the reference stimulus (10 μL of 0.1 M 1-Hexanol), was 219.14 ± 14.46 μV for females and 222.22 ± 15.86 μV for males, which were significantly higher than to the blank stimulus (both p < 0.001). The difference between females and males in their responses to the blank or reference stimulus was not significant (p = 0.274 and 0.448). (E)-2-Hexenal and (E)-3-Hexenol proved to be the strongest stimuli, followed by 1-Heptanol. The other three stimuli produced much weaker signals. Responses were generally similar between sexes, in some cases significantly higher in female antennae (Figure 5). 3. Discussion The selective response of AlucOR46 to plant volatiles and its female-biased expression suggest that this receptor could be involved by A. lucorum in locating host plant for feeding and oviposition [21,22,23]. In several studies, functional characterization of insects’ OR has been successfully conducted using heterologous systems [24,25,26,27]. When expressed in Xenopus oocytes, AlucOR46 was tuned to six plant volatiles, with stronger responses and higher sensitivity to (E)-2-Hexenal, (E)-3-Hexenol, 1-Heptanol and (1R)-(−)-Myrtenol. Except for (1R)-(−)-Myrtenol, the other three chemicals are all straight chain compounds and are similar in structure (Table 1). Different chemicals with similar structures could activate the same OR, a fact proven by many in vitro experiments. For example, in Spodoptera exigua, SexiOR3 was narrowly tuned to E-β-farnesene and several compounds of related structure [28]. However, although the four chemicals could stimulate similar responses in heterologous expression, the EAG responses to them in both female and male showed significant differences. This may be caused by the fact that olfactory selectivity does not only depend on ORs but also on other olfactory genes such as OBPs, sensory neuron membrane proteins (SNMPs) and odorant-degrading enzymes (ODEs), as well as from the expression level of these genes [12]. There is also a possibility that other ORs tuned to the same compounds may exist in the olfactory system of this species. Previous studies in other mirids showed differences in the EAG responses between sexes. Males were more sensitive to insect-produced pheromones, while females were more sensitive to plant volatiles, cues to oviposition sites [29,30]. The EAG results of (E)-2-Hexenal and 1-Heptanol in our study are consistent with this report; however, the other four compounds were not mentioned in previous studies. Specifically, in both Lygus lineolaris and Lygocoris pabulinus, female antennae produced larger EAG responses than male’s to both the above compounds, with (E)-2-Hexenal eliciting stronger responses than 1-Heptanol in both sexes [29,30]. (E)-2-Hexenal is one of the green leaf volatiles (GLVs) released by plants after mechanical damage or herbivores attack. Herbivores use GLVs to locate host plants and plants also use GLVs to attract predators of pests to protect themselves [31,32,33]. Previous studies in Y-tube olfactometer and field trapping showed that A. lucorum females, but not males, could be significantly attracted by (E)-2-Hexenal, (Z)-3-Hexenol, phenylacetaldehyde and acetophenone, which are among the volatiles of cotton, alfalfa and cowpea [34]. Our results suggest that (E)-2-Hexenal might play an important role in locating host plants for females of A. lucorum. Besides, insects could also generate this compound. For example, L. lineolaris releases high doses of (E)-2-Hexenal when it is disturbed. This chemical is absent in the volatiles collected from calm males [35]. In conclusion, AlucOR46 is a receptor tuned to host plant volatiles and could represent an attractive target to control this important agricultural pest. 4. Materials and Methods 4.1. Insect Rearing and Tissue Collection The A. lucorum (Meyer-Dür) used in all experiments were obtained from a laboratory colony established and maintained at the Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China. Insects were reared with fresh corns and green beans and maintained at 28 ± 1 °C, with 60% ± 5% relative humidity and a 14 h:10 h light:dark photoperiod. Antennae, heads (without antennae), thoraxes, abdomens and legs were collected from male and female adults on the third day after eclosion, immediately frozen in liquid nitrogen and stored at −70 °C. 4.2. Plant Volatile Compounds The 65 odorants tested in this study are listed in Table S1. All the chemicals were purchased from Sigma-Aldrich (Saint Louis, MO, USA). In two-electrode voltage-clamp electrophysiological recordings, odorants were dissolved in dimethyl sulphoxide (DMSO) as 1 M stock solutions. Before experiments, these were diluted to the appropriate concentrations in 1× Ringer’s buffer (96 mM NaCl, 2 mM KCl, 5 mM MgCl2, 0.8 mM CaCl2, and 5 mM HEPES, pH 7.6). In EAG experiments, the six selected compounds, (S)-(−)-Limonene, (R)-(+)-Limonene, (E)-2-Hexenal, (E)-3-Hexenol, 1-Heptanol and (1R)-(−)-Myrtenol, were dissolved in hexane at the concentration of 0.1 M. 4.3. RNA Isolation and cDNA Synthesis Total RNA was isolated using Trizol reagent (Invitrogen, Carlsbad, CA, USA), quantified on a NanoDrop-2000 spectrophotometer (NanoDrop Technologies, Inc., Wilmington, DE, USA) and digested with DNaseI (Fermentas, Glen Burnie, MD, USA) to remove trace amounts of genomic DNA, before synthesis of single-strand cDNA using Revert Aid First Strand cDNA Synthesis Kit (Fermentas). The cDNA of antennae was used as the template for gene cloning and, together with cDNAs from heads (without antennae), thoraxes, abdomens and legs as templates for qRT-PCR. 4.4. Gene Cloning and Sequence Analysis To clone the full-length ORF of AlucOR46 specific primers were designed using Primer Premier 5.0 software (PREMIER Biosoft International, Palo Alto, CA, USA); their sequences are reported in Table S2. PCR reaction mixtures of 25 μL contained 1 μL cDNA, 0.25 μL primeSTAR HS DNA polymerase, 5 μL 5× PrimerSTAR Buffer, 2 μL dNTP mixture (2.5 mM each) and 0.5 μL of each primer (10 μM). PCR conditions were: initial denaturation at 95 °C for 3 min; 35 cycles of 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 2 min; final extension at 72 °C for 10 min. The amplification product was purified from 1.0% agarose gels and ligated into the pEasy-T3 vector (TransGenBiotech, Beijing, China) following the manufacturer’s instructions. Plasmids were extracted and sequenced at BGI (Beijing, China). The amino acid sequences of AlucOR12, AlucOR18, AlucOR28, AlucOR30 and AlucOrco were obtained from GenBank (accession numbers: KP010358, KP010359, KP010360, KP010361 and KC881255, respectively). Amino acid sequences were aligned using ClustalW2 [36]. TMDs were predicted using TMHMM Server Version 2.0 [37]. 4.5. Quantitative Real-Time PCR To evaluate the expression of AlucOR46 in different tissues of male and female A. lucorum, qRT-PCR was performed using cDNA from antennae (A), heads without antennae (H), thoraxes (T), abdomens (Ab) and legs (L) on the ABI Prism 7500 Fast Detection System (Applied Biosystems, Carlsbad, CA, USA). To correct for samples variation and normalize AlucOR46 expression level, AlucActin gene (KU188517) was used as a reference. Primers were designed using the Beacon Designer 7.90 software (PREMIER Biosoft International) (Table S2). qRT-PCR reactions were conducted in 20 μL reaction mixtures containing 0.5 μL of each primer (10 μM), 1 μL of sample cDNA, 8 μL of sterilized H2O and 10 μL 2× Go Taq qPCR Master Mix (Promega, Madison, WI, USA). The qRT-PCR cycling program was: 95 °C for 2 min, 40 cycles of 95 °C for 30 s, 60 °C for 1 min. Relative quantification was performed by using the comparative 2−∆∆Ct method, where ∆Ct = (Ct, OR gene − Ct, reference gene), ∆∆Ct = (∆Ct, different samples − ∆Ct maximum). Each experiment was repeated three times using three independently isolated RNA samples. 4.6. Vector Construction and cRNAs Synthesis The full ORF of AlucOR46 was amplified by primers with restriction enzyme sites (ApaI and NotI) (Table S2) and cloned into pT7Ts vector. The vector was linearized by the restriction enzyme SmaI and complimentary ribonucleic acid (cRNA) was synthesized from the linearized plasmid using mMESSAGE mMACHINE T7 kit (Ambion, Austin, TX, USA). 4.7. Two-Electrode Voltage Clamp Electrophysiological Recordings Oocytes expression and electrophysiological recording were performed as described in previous reports [24,38]. Mature healthy Xenopus oocytes were treated with 2 mg/mL collagenase in washing buffer (96 mM NaCl, 2 mM KCl, 5 mM MgCl2, and 5 mM HEPES, pH 7.6) for 1–2 h at room temperature. Then, the Xenopus oocytes were microinjected with a mixture of 27.6 ng AlucOR46 cRNA and 27.6 ng AlucOrco cRNA. After injection, oocytes were cultured at 18 °C for 3–7 days in 1X Ringer’s solution supplemented with 5% dialyzed horse serum, 50 μg/mL, tetracycline 100 μg/mL streptomycin and 550 μg/mL sodium pyruvate. Whole-cell currents were recorded from injected oocytes in response to different odors using two-electrode voltage clamp and dose-response curves were obtained at a holding potential of −80 mV. Micropipettes filled with 3 M KCl were used as electrodes. During the recording, oocytes were challenged with a panel of 65 compounds in a random order at a flow rate of 8 mL/min for 15 s. Before next stimulus, 1× Ringer’s solution was used to wash oocyte at a flow rate of 10 mL/min to allow the current to return to baseline. Data acquisition and analysis were performed with Digidata 1440A and pClamp 10.0 software (Axon Instruments Inc., Union City, CA, USA). Dose-response data were analyzed using GraphPad Prism 5. 4.8. Electroantennogram Experiment EAG recordings were used to measure the responses of females and males A. lucorum to six plant volatiles, (S)-(−)-Limonene, (R)-(+)-Limonene, (E)-2-Hexenal, (E)-3-Hexenol, 1-Heptanol and (1R)-(−)-Myrtenol. EAG signals were recorded and analyzed using Syntech IDAC 4 and GC-EAD softwares (Syntech, Hilversum, The Netherlands). Chemicals were dissolved in hexane to the final concentration of 0.1 M and 20 μL of the solutions were applied to a piece of folded filter paper (0.5 cm × 2 cm), which was inserted into a glass Pasteur pipette. The antennae of A. lucorum were excised at the base, and few segments were removed at the distal end. The antennae were connected between two glass electrodes filled with 0.1 M KCl using electrode gel. To deliver stimuli, a constant airstream of 30 mL/s produced by a stimulus controller (CS-55, Syntech) was sent through the glass Pasteur pipette for 0.2 s at 10 mL/s airflow. EAG signals recorded from the antenna were amplified by 10× AC/DC headstage preamplifier (Syntech), then acquired by Intelligent Data Acquisition Controller (IDAC-4, Syntech), sent to the computer and finally recorded by Syntech software. Blank and reference stimuli were 10 μL of pure hexane and 10 μL of 0.1 M 1-Hexanol, respectively [29]. Antennae were stimulated with the six compounds in random order. EAG responses for each compound were recorded from six females and six males. Relative EAG responses for each compound were calculated by the formula: Relative EAG response = (EAG response to the test compound − mean EAG response to the blank stimulus)/(mean EAG response to the reference stimulus − mean EAG response to the blank stimulus) [39]. The differences of mean relative EAG response between female and male to the same test compound were compared using Student’s t-tests. Statistical analyses of the above data were processed in SPSS 23.0. Acknowledgments We thank Paolo Pelosi for comments and editorial assistance on the manuscript. This work was supported by National Natural Science Foundation of China (31471833 and 31321004) and the National Transgenic Crop Initiative (2012ZX08009001). Supplementary Materials Supplementary materials can be found at http://www.mdpi.com/1422-0067/17/8/1165/s1. Click here for additional data file. Author Contributions Zhixiang Zhang, Meiping Zhang, Guirong Wang and Yang Liu conceived and designed the experiments; Zhixiang Zhang, Meiping Zhang, Shuwei Yan and Yang Liu performed the experiments; Zhixiang Zhang and Yang Liu analyzed the data; Zhixiang Zhang contributed reagents/materials/analysis tools; Zhixiang Zhang, Meiping Zhang and Yang Liu wrote the paper. Conflicts of Interest The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results. Figure 1 Alignment of amino acid sequences of AlucOR46, AlucOR12, AlucOR18, AlucOR30, AlucOR28 and AlucOrco. The seven transmembrane domains (TM1–TM7) are marked by solid lines. The conserved amino acid sites among the 6 ORs are marked with black shading. Amino acid similarities are very poor between these members. In particular, AlucOR46 is 12.7% identical to AlucOrco and shares 15.7%, 13.7%, 14.2% and 10.4% amino acids with AlucOR12, AlucOR18, AlucOR28 and AlucOR30, respectively. Figure 2 Tissue expression patterns of AlucOR46 in adults of A. lucorum. A: antenna; H: heads without antenna; T: thoraxes; Ab: abdomens; L: legs. Asterisk indicates significant difference between female and male. Figure 3 Functional characterization of AlucOR46/Orco in Xenopus oocytes. (A) Inward current responses of AlucOR46/Orco Xenopus oocytes to 10−4 M solution of (S)-(−)-Limonene, (R)-(+)-Limonene, (E)-2-Hexenal, (E)-3-Hexenol, 1-Heptanol and (1R)-(−)-Myrtenol; (B) Response profile of AlucOR46/Orco Xenopus oocytes. Error bars indicate standard error of the mean (SEM) (n = 6); (C) Tuning curve of AlucOR46. Tuning curve for the AlucOR46 to an odor panel comprising 65 odorants arranged along the x-axis. The odors which elicited the strongest responses are in the middle of the distribution, the weakest near the edges. Figure 4 Dose-response of AlucOR46/Orco expressed in Xenopus. (A) AlucOR46/Orco Xenopus oocytes were stimulated with a concentrations range of (E)-2-Hexenal, (E)-3-Hexenol, 1-Heptanol and (1R)-(−)-Myrtenol; (B) Dose-response curves of AlucOR46/Orco Xenopus oocytes to (E)-2-Hexenal, (E)-3-Hexenol, 1-Heptanol and (1R)-(−)-Myrtenol. Responses are normalized by defining the maximal response as 100 in each group. The Error bar indicates SEM (n = 6). Figure 5 Relative electroantennogram (EAG) responses of female and male A. lucorum to six plant volatiles. NS indicates that there are no significant differences. Asterisks indicate significant differences in EAG response between female and male antennae, p < 0.05. Error bars indicate SEM (n = 6). ijms-17-01165-t001_Table 1Table 1 The structure of six active compounds and the half maximal effective concentration (EC50). values of four compounds. Odorants Structure EC50 (M) (R)-(+)-Limonene - (S)-(−)-Limonene - (E)-2-Hexenal 3.71 × 10−5 (E)-3-Hexenol 2.53 × 10−5 1-Heptanol 1.38 × 10−5 (1R)-(−)-Myrtenol 7.44 × 10−5 ==== Refs References 1. Lu Y.H. Wu K.M. Biology and Control of Cotton Mirids Golden Shield Press Beijing, China 2008 2. Lu Y.H. Wu K.M. Wyckhuys K.A. Guo Y.Y. Temperature-dependent life history of the green plant bug, Apolygus lucorum (Meyer-Dür)(Hemiptera: Miridae) Appl. Entomol. Zool. 2010 45 387 393 10.1303/aez.2010.387 3. Lu Y.H. Wu K.M. Wyckhuys K.A. Guo Y.Y. Overwintering hosts of Apolygus lucorum (Hemiptera: Miridae) in northern China Crop Prot. 2010 29 1026 1033 10.1016/j.cropro.2010.03.017 4. Pan H.S. Liu B. Lu Y.H. Wyckhuys K.A. Seasonal alterations in host range and fidelity in the polyphagous mirid bug, Apolygus lucorum (Heteroptera: Miridae) PLoS ONE 2015 10 1165 10.1371/journal.pone.0117153 25692969 5. Lu Y.H. Jiao Z.B. Wu K.M. Early season host plants of Apolygus lucorum (Heteroptera: Miridae) in northern China J. Econ. Entomol. 2012 105 1603 1611 10.1603/EC12003 23156156 6. Schoonhoven L.M. van Loon J.J. Dicke M. Insect-Plant Biology Oxford University Press Oxford, UK 2005 7. Bruce T.J. Wadhams L.J. Woodcock C.M. Insect host location: A volatile situation Trends Plant Sci. 2005 10 269 274 10.1016/j.tplants.2005.04.003 15949760 8. Wu G.Q. Xiao L.B. Tang Y.A. Sun Y. Bai L.X. Relative preferences of Apolygus lucorum adults for six host species and their volatiles Chin. J. Appl. Entomol. 2012 49 641 647 9. Chen Z.C. Su L. Ge F. Su J.W. Electroantennogram responses of the green leaf bug, Lygus lucorum Meyer-Dür (Hemiptera: Miridae), to sex pheromone analogs and plant volatiles Acta Entomol. Sin. 2010 53 47 54 10. Pan H.S. Lu Y.H. Wyckhuys K.A. Wu K.M. Preference of a polyphagous mirid bug, Apolygus lucorum (Meyer-Dür) for flowering host plants PLoS ONE 2013 8 1165 10.1371/journal.pone.0068980 23874835 11. Su C.Y. Menuz K. Carlson J.R. Olfactory perception: Receptors, cells, and circuits Cell 2009 139 45 59 10.1016/j.cell.2009.09.015 19804753 12. Leal W.S. Odorant reception in insects: Roles of receptors, binding proteins, and degrading enzymes Annu. Rev. Entomol. 2013 58 373 391 10.1146/annurev-ento-120811-153635 23020622 13. Clyne P.J. Warr C.G. Freeman M.R. Lessing D. Kim J. Carlson J.R. A novel family of divergent seven-transmembrane proteins: Candidate odorant receptors in Drosophila Neuron 1999 22 327 338 10.1016/S0896-6273(00)81093-4 10069338 14. Vosshall L.B. Amrein H. Morozov P.S. Rzhetsky A. Axel R. A spatial map of olfactory receptor expression in the Drosophila antenna Cell 1999 96 725 736 10.1016/S0092-8674(00)80582-6 10089887 15. Benton R. Sachse S. Michnick S.W. Vosshall L.B. Atypical membrane topology and heteromeric function of Drosophila odorant receptors in vivo PLoS Biol. 2006 4 1165 10.1371/journal.pbio.0040020 16402857 16. Neuhaus E.M. Gisselmann G. Zhang W. Dooley R. Stortkuhl K. Hatt H. Odorant receptor heterodimerization in the olfactory system of Drosophila melanogaster Nat. Neurosci. 2005 8 15 17 10.1038/nn1371 15592462 17. Hallem E.A. Ho M.G. Carlson J.R. The molecular basis of odor coding in the Drosophila antenna Cell 2004 117 965 979 10.1016/j.cell.2004.05.012 15210116 18. Vosshall L.B. Hansson B.S. A unified nomenclature system for the insect olfactory coreceptor Chem. Senses 2011 36 497 498 10.1093/chemse/bjr022 21441366 19. Zhou Y.L. Zhu X.Q. Gu S.H. Cui H.H. Guo Y.Y. Zhou J.J. Zhang Y.J. Silencing in Apolygus lucorum of the olfactory coreceptor Orco gene by RNA interference induces EAG response declining to two putative semiochemicals J. Insect Physiol. 2014 60 31 39 10.1016/j.jinsphys.2013.10.006 24216470 20. Yan S.W. Zhang J. Liu Y. Li G.Q. Wang G.R. An olfactory receptor from Apolygus lucorum (Meyer-Dür) mainly tuned to volatiles from flowering host plants J. Insect Physiol. 2015 79 36 41 10.1016/j.jinsphys.2015.06.002 26050917 21. Anderson A.R. Wanner K.W. Trowell S.C. Warr C.G. Jaquin-Joly E. Zagatti P. Robertson H. Newcomb R.D. Molecular basis of female-specific odorant responses in Bombyx mori Insect Biochem. Mol. Biol. 2009 39 189 197 10.1016/j.ibmb.2008.11.002 19100833 22. Wanner K.W. Anderson A.R. Trowell S.C. Theilmann D.A. Robertson H.M. Newcomb R.D. Female-biased expression of odorant receptor genes in the adult antennae of the silkworm, Bombyx mori Insect Mol. Biol. 2007 16 107 119 10.1111/j.1365-2583.2007.00708.x 17257213 23. Zhang J. Liu C.C. Yan S.W. Liu Y. Guo M.B. Dong S.L. Wang G.R. An odorant receptor from the common cutworm (Spodoptera litura ) exclusively tuned to the important plant volatile cis-3-hexenyl acetate Insect Mol. Biol. 2013 22 424 432 10.1111/imb.12033 23679893 24. Wang G.R. Carey A.F. Carlson J.R. Zwiebel L.J. Molecular basis of odor coding in the malaria vector mosquito Anopheles gambiae Proc. Natl. Acad. Sci. USA 2010 107 4418 4423 10.1073/pnas.0913392107 20160092 25. Sun M.J. Liu Y. Walker W.B. Liu C.C. Lin K.J. Gu S.H. Zhang Y.J. Zhou J.J. Wang G.R. Identification and characterization of pheromone receptors and interplay between receptors and pheromone binding proteins in the diamondback moth, Plutella xyllostella PLoS ONE 2013 8 1165 10.1371/journal.pone.0062098 23626773 26. Carey A.F. Wang G. Su C.Y. Zwiebel L.J. Carlson J.R. Odorant reception in the malaria mosquito Anopheles gambiae Nature 2010 464 66 71 10.1038/nature08834 20130575 27. Zhang Y.N. Zhang J. Yan S.W. Chang H.T. Liu Y. Wang G.R. Dong S.L. Functional characterization of sex pheromone receptors in the purple stem borer, Sesamia inferens (Walker) Insect Mol. Biol. 2014 23 611 620 10.1111/imb.12109 25039606 28. Liu C.C. Liu Y. Guo M.B. Cao D.P. Dong S.L. Wang G.R. Narrow tuning of an odorant receptor to plant volatiles in Spodoptera exigua (Hübner) Insect Mol. Biol. 2014 23 487 496 10.1111/imb.12096 24779920 29. Chinta S. Dickens J.C. Aldrich J.R. Olfactory reception of potential pheromones and plant odors by tarnished plant bug, Lygus lineolaris (Hemiptera: Miridae) J. Chem. Ecol. 1994 20 3251 3267 10.1007/BF02033724 24241990 30. Groot A.T. Timmer R. Gort G. Lelyveld G.P. Drijfhout F.P. van Beek T.A. Visser J.H. Sex-related perception of insect and plant volatiles in Lygocoris pabulinus J. Chem. Ecol. 1999 25 2357 2371 10.1023/A:1020834226520 31. Loughrin J.H. Manukian A. Heath R.R. Turlings T.C. Tumlinson J.H. Diurnal cycle of emission of induced volatile terpenoids by herbivore-injured cotton plant Proc. Natl. Acad. Sci. USA 1994 91 11836 11840 10.1073/pnas.91.25.11836 11607499 32. Matsui K. Green leaf volatiles: Hydroperoxide lyase pathway of oxylipin metabolism Curr. Opin. Plant Biol. 2006 9 274 280 10.1016/j.pbi.2006.03.002 16595187 33. Scala A. Allmann S. Mirabella R. Haring M.A. Schuurink R.C. Green leaf volatiles: A plant’s multifunctional weapon against herbivores and pathogens Int. J. Mol. Sci. 2013 14 17781 17811 10.3390/ijms140917781 23999587 34. Zhang S.Q. Identification of Host Palnt Semiochemicals and the Attraction for Apolygus lucorum (Meyer-Dür) Ph.D. Thesis Agricultural University of Hebei Province Baoding, China 2011 35. Wardle A.R. Borden J.H. Pierce H.D. Jr. Gries R. Volatile compounds released by disturbed and calm adults of the tarnished plant bug, Lygus lineolaris J. Chem. Ecol. 2003 29 931 944 10.1023/A:1022987901330 12775153 36. ClustalW2 Available online: http://www.ebi.ac.uk/Tools/msa/clustalw2 (accessed on 14 October 2015) 37. TMHMM Server v. 2.0 Available online: http://www.cbs.dtu.dk/services/TMHMM (accessed on 14 October 2015) 38. Lu T. Qiu Y.T. Wang G.R. Kwon J.Y. Rutzler M. Kwon H.W. Pitts R.J. Van Loon J.J.A. Takken W. Carlson J.R. Odor coding in the maxillary palp of the malaria vector mosquito Anopheles gambiae Curr. Biol. 2007 17 1533 1544 10.1016/j.cub.2007.07.062 17764944 39. Sun Y.F. Yu H. Zhou J.J. Pickett J.A. Wu K.M. Plant volatile analogues strengthen attractiveness to insect PLoS ONE 2014 9 1165 10.1371/journal.pone.0099142 24911460

PMC005xxxxxx/PMC5000589.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081179ijms-17-01179ArticleCytoprotection against Hypoxic and/or MPP+ Injury: Effect of δ–Opioid Receptor Activation on Caspase 3 Xu Yuan 1†Zhi Feng 1†Shao Naiyuan 1Wang Rong 1Yang Yilin 1*Xia Ying 2*Prokai-Tatrai Katalin Academic Editor1 Modern Medical Research Center, The Third Affiliated Hospital of Soochow University, Changzhou 213000, Jiangsu, China; 13685262339@163.com (Y.X.); danielzhif@163.com (F.Z.); naiyuanshao@126.com (N.S.); wangrong1949@163.com (R.W.)2 Department of Neurosurgery, The University of Texas McGovern Medical School, Houston, TX 77030, USA* Correspondence: bigyang@vip.sina.com (Y.Y.); Y55738088@gmail.com or Ying.Xia@uth.tmc.edu (Y.X.); Tel.: +86-519-6887-0000 (Y.Y.); +1-713-500-6288 (Y.X.)† These authors contributed equally to this work. 09 8 2016 8 2016 17 8 117905 6 2016 13 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).The pathological changes of Parkinson’s disease (PD) are, at least partially, associated with the dysregulation of PTEN-induced putative kinase 1 (PINK1) and caspase 3. Since hypoxic and neurotoxic insults are underlying causes of PD, and since δ-opioid receptor (DOR) is neuroprotective against hypoxic/ischemic insults, we sought to determine whether DOR activation could protect the cells from damage induced by hypoxia and/or MPP+ by regulating PINK1 and caspase 3 expressions. We exposed PC12 cells to either severe hypoxia (0.5%–1% O2) for 24–48 h or to MPP+ at different concentrations (0.5, 1, 2 mM) and then detected the levels of PINK1 and cleaved caspase 3. Both hypoxia and MPP+ reduced cell viability, progressively suppressed the expression of PINK1 and increased the cleaved caspase 3. DOR activation using UFP-512, effectively protected the cells from hypoxia and/or MPP+ induced injury, reversed the reduction in PINK1 protein and significantly attenuated the increase in the cleaved caspase 3. On the other hand, the application of DOR antagonist, naltrindole, greatly decreased cell viability and increased cleaved caspase 3. These findings suggest that DOR is cytoprotective against both hypoxia and MPP+ through the regulation of PINK1 and caspase 3 pathways. Parkinson’s diseaseδ-opioid receptorcytoprotectionhypoxiaMPP+PINK1caspase 3 ==== Body 1. Introduction Parkinson’s disease (PD) is characterized by the accumulation of cytoplasmic protein inclusions called Lewy bodies in neurons, and the insufficient production of dopamine, which is produced in the substantia nigra of the midbrain [1]. Over the past few decades, many scientists and clinicians around the world have devoted themselves to understanding its pathophysiology, clinical courses and therapies, but until now, there are still limited therapeutic options for PD treatment. Chronic pharmacological therapies that use dopaminergic drugs, are associated with a series of side effects such as L-dopa-induced dyskinesias [2,3] and the risk of tumor formation. Therefore, it is of utmost importance to find novel strategies for PD treatment. Although the etiopathogenesis of PD is complex, the vulnerability of midbrain dopaminergic neurons to oxidative stress, and environmental neurotoxins affecting the dopamine biosynthetic pathways [4] has long been implicated as potential causes of PD. Furthermore, as the morbidity of PD is greater among older people, it might be associated with age-related conditions such as prolonged ischemia or hypoxia in the brain. There is ample evidence to show that an insufficient blood or oxygen supply to the brain, could attenuate neurons’ resistance to environmental damage, and it can even trigger cell death [5,6,7]. Therefore, hypoxia/ischemia and neurotoxins should also be recognized as critical pathogenic factors that contribute to the development of PD. One of major breakthroughs in PD research was the discovery of the close association between PINK1 and autosomal recessive familial Parkinson’s disease [8,9]. In healthy mitochondria, PINK1 protects cells from damage-induced mitochondrial dysfunction, oxidative stress and cell apoptosis [10]. However, pathogenic PINK1 mutations in PD lead to a loss-of-function of the PINK1 molecule [11,12,13], leading to depolarization of the mitochondrial membrane potential. Consequently, this induces the mitophagic destruction of mitochondria [14] and then the release of apoptotic signals [15,16]. Like most cells which undergo pathologically mediated cell apoptosis, the midbrain dopaminergic neurons’ death in PD is caspases-dependent [17]. Once the initiator caspases are activated by apoptotic signals, they produce a chain reaction, activating several other executioner caspases, leading to cell death [18,19,20,21,22]. Considering the complexity of the causes, the neuronal signaling involved, and the mechanisms in PD, it is of utmost importance to find new strategies for halting dopaminergic neuron degeneration by protecting neuronal cells against various insults such as hypoxia and neurotoxins. According to our previous work, δ-opioid receptor (DOR) is neuroprotective and actively participates in the control of neuronal survival [23,24,25]. Since hypoxic and neurotoxic insults are underlying causes of PD, and DOR is neuroprotective against hypoxic/ischemic insults, we sought to determine whether DOR activation could protect the cells from damage induced by hypoxia and/or MPP+ by regulating PINK1 and caspase 3 expression. In this work, we used in vitro PD models either in the condition of hypoxia or using MPP+ (1-methyl-4-phenyl-pyridinium ion), which is a neurotoxin agent which has been wildly used in animal and cell models by destroying dopaminergic neurons in the substantia nigra in vivo and in vitro [26,27] to mimic PD conditions. Our study was aimed at addressing the following two fundamental questions: Are there any changes in PINK1 and caspase 3 expressions under hypoxic/MPP+ stress? Can DOR activation regulate PINK1 and caspase 3 expression and improve cell survival in hypoxia and MPP+ models? 2. Results 2.1. Prolonged Hypoxia and MPP+ Stress Caused Severe PC12 Cell Injury Firstly, we used MTT assay to examine the effects of hypoxia and MPP+ on PC12 cell viability. The data showed that after hypoxic exposure at 1% O2 for 24 h, the cell viability had a significant reduction (79.20% vs. 100% of the control group, p < 0.01, n = 3; Figure 1a-left panel) and it was further decreased after prolonging the exposure time to 48 h (63.91% vs. 100% of the control level, p < 0.01, n = 3; Figure 1a-right panel). We also applied MPP+ to the PC12 cells to induce parkinsonian injury and chose 1 mM as the working concentration in this work based on our preliminary experiment. MTT assay showed that MPP+ induced a similar injury to that of hypoxic stress (Figure 2a). Compared to the control group, MPP+ exposure reduced the cell viability by 20.81% (p < 0.05, n = 3; Figure 2a-left panel) at 24 h and 33.77% at 48 h (p < 0.05, n = 3; Figure 2a-right panel) after the exposure. Moreover, we measured LDH (lactate dehydrogenase) leakage in the medium to further validate the effects of hypoxia and MPP+ on the PC12 cells. As shown in Figure 1b, LDH leakage progressively increased with the duration of hypoxic exposure, with an increase by 22.42% after 24 h-hypoxia and by 34.92% after 48 h-hypoxia (p < 0.01, n = 3; Figure 1b). LDH leakage also showed a 45.53% increase (p < 0.01 vs. the control, n = 3, respectively; Figure 2b-left panel) after MPP+ exposure for 24 h and a 62.68% increase (p < 0.05 vs. the control, n = 3, respectively; Figure 2b-right panel) after MPP+ exposure for 48 h. We also examined cellular morphology using microscope. In the first 24 h of exposure to 1% O2 or 1.0 mM MPP+, these highly differentiated PC12 cells did not show any appreciable changes in cellular morphology. However, they grew slower in both hypoxic and MPP+ conditions as compare the control. After prolonging the exposure duration to 48 h, the numbers of cells sharply decreased, and their shape had major changes, including blebbing and cell shrinkage. All these information demonstrated that both hypoxic and MPP+ stress cause severe injury in PC12 cells. 2.2. Both Prolonged Hypoxia and MPP+ Insults Increased the Level of Cleaved Caspase 3 with a Reduction of PINK1 Protein Since caspase 3 activation plays a central role in the execution-phase of cell injury [28], we investigated whether hypoxia and MPP+ insults increase the activation of caspase 3 by measuring the changes in the cleaved caspase 3 with apoptotic activity and the full-length caspase 3 protein with no apoptotic activity [18]. As depicted in Figure 3 and Figure 4, the level of full-length pro-caspase 3 (35 kDa) significantly decreased, while the level of cleaved caspase 3 (17 kDa) largely increased after 48 h of hypoxic exposure or 24 h of MPP+ exposure. Since PINK1 is thought to play an important role in protecting nerve cells from parkinsonism by inhibiting caspase 3 action [29], we further investigated if the increase in the activated caspase 3 is associated with a reduction of PINK1 expression in hypoxic and MPP+ conditions. As shown in Figure 5, hypoxia at 0.5% of O2 for 24 h caused a 44.35% reduction in PINK1 protein (p < 0.01, n = 3; Figure 5-left panel) and hypoxia at 1% of O2 for 48 h led to a more marked decrease (67.53% reduction vs. the control level, p < 0.01, n = 3; Figure 5-right panel). MPP+ stress also significantly reduced PINK1 expression (Figure 6). This reduction was dose-dependent in response to MPP+ exposure within the concentration range of 0.5 to 2.0 mM. After 24 h-exposure to 0.5 mM of MPP+, the relative density of PINK1 protein decreased by 15.10% (p < 0.01 vs. the control, n = 3; Figure 6). As the MPP+ concentration was increased, PINK1 protein density declined more significantly. For example, 24 h-exposure to 2.0 mM MPP+ led to a 49.82% reduction in PINK1 signal density (p < 0.01 vs. the control, n = 3; Figure 6). This data suggests that hypoxia and MPP+ insults may negatively regulate PINK1 expression, and thus affect caspase 3 signaling. 2.3. DOR Activation Attenuated PC12 Cell Injury Induced by Hypoxic and MPP+ Stress Furthermore, we determined whether DOR activation is protective against hypoxic and MPP+ insults. For the cells under the condition of 24 h-hypoxia with relatively mild injury, the application of DOR agonist UFP-512 (5 μM) or antagonist naltrindole (1 μM) did not cause any significant change in the cell viability. However, after prolonging the hypoxic exposure to 48 h and inducing more severe cell injury, DOR activation largely reversed the reduction of cell viability (from 63.91% in hypoxia alone to 84.30% in hypoxia plus DOR activation, p < 0.01, n = 3; Figure 2a-right panel), while DOR inhibition further aggravated the hypoxic-induced reduction of cell viability (from 63.91% in hypoxia alone to 54.63% in hypoxia plus DOR inhibition, p < 0.01, n = 3; Figure 2a-right panel). DOR activation increased the cell viability by 13.97% (p < 0.05, n = 3; Figure 2a-left panel) following 24 h-exposure to 1.0 mM MPP+. In contrast, DOR inhibition with naltrindole led to a 7.7% reduction in cell viability (p < 0.01, n = 3; Figure 2a-left panel). On the other hand, the MTT assay did not detect any significant change in MPP+-induced injury at 48 h after the administration of UFP-512 or naltrindole though the latter tended to deteriorate the MPP+ injury. With LDH leakage assay, although no significant change was detected at 24 h after the administration of the DOR agonist in hypoxic cells, a significant reduction in LDH leakage (−11.36%, p < 0.05 vs. H, n = 3; Figure 1b-right panel) was seen at 48 h after the administration of the DOR agonist in hypoxic exposure. Probably because of the sensitive issue in the LDH assessment, DOR activation with UFP-512 or inhibition with naltrindole did not induce any statistically significant changes in LDH leakage after MPP+ exposure, although the trends of the changes were consistent with the results of the MTT assay (Figure 2b). Taken together, DOR activation generally is cytoprotective against hypoxic and MPP+ insults, while its inhibition induced an opposite effect. 2.4. DOR Activation Upregulated PINK1 Expression in Hypoxia or MPP+ Stress Furthermore, we found that DOR activation increased PINK1 expression in hypoxia or MPP+ stress. As shown in Figure 7a, the hypoxia-induced reduction in PINK1 expression was greatly reversed by the application of DOR agonist UFP-512. DOR activation also effectively reversed the MPP+ induced reduction in PINK1 protein (Figure 7b). Hypoxia at 1% O2 for 48 h did not induce any major change in DOR protein expression. UFP-512 had no appreciable effect on the level of DOR protein (Figure 7a). However, 1.0mM MPP+ markedly reduced DOR expression, which was slightly attenuated by DOR activation with UFP-512 (Figure 7b). 2.5. DOR Activation Inhibited Hypoxia/MPP+-Induced Production of Cleaved Caspase 3 Since caspase 3 is a critical factor in hypoxia and MPP+ injury, we further investigated whether DOR activation and inhibition affects caspase 3 signaling. Our data showed that the hypoxia or MPP+ induced increase in cleaved caspase 3 was significantly attenuated by DOR activation with more caspase 3 remaining in an inactivated status (full-length protein) (Figure 3 and Figure 4). In contrast, DOR inhibition with naltrindole resulted in a marked increase in cleaved caspase 3, along with a decrease of inactivated caspase 3 under both hypoxic and MPP+ conditions. Our results suggest that DOR signaling may have an inhibitory effect on the transition from inactivated caspase 3 to activated caspase 3. 3. Discussion In this study, we have made several interesting findings regarding the effects of DOR activation on cell survival and PINK1 and caspase 3 expression. Prolonged hypoxia, or a high concentration of MPP+ reduced cell viability with a reduction in PINK1 protein and an increase in cleaved caspase 3. DOR activation protected the cells from hypoxia and MPP+ injury with an upregulation of PINK1 and downregulation of cleaved caspase 3, while its inhibition induced an opposite effect. Hypoxia and MPP+ stress have been recognized as potential pathogenic factors that contribute to the development of PD [6,7]. Although the specific mechanism underlying neuron death in PD is not yet clearly understood, a large body of evidence strongly supports that mitochondrial dysfunction is evident in the brains of PD patients [30,31]. According to past studies, they induced cell apoptosis through destroying mitochondrial stabilizations [29,30,31]. Moreover, apoptosis has been found to be caspase-dependent [32]. Two classes of caspase-dependent pathways have been identified [33,34]. One of them is dependent on the release of apoptotic factors from mitochondria. In this class, different inducing agents result in a collapse of the mitochondrial transmembrane potential, which brings about the irreversible change in the cell death process [33,34,35]. According to the results of our study, both hypoxia and MPP+ insults led to an increase in the expression level of activated caspase 3, along with a decrease in the expression level of precursor forms of caspase 3, suggesting that both hypoxic or MPP+-induced cell apoptosis is associated with an increase in caspase 3 activity. Furthermore, we have demonstrated a reduction in PINK1 expression in hypoxic and MPP+ conditions. Past studies support the significant role played by PINK1 in neuroprotection, as it protects cells by stabilizing mitochondrial networks through maintaining membrane potential and suppressing mitophagy [36]. It has been proven that in cultured mammalian cells, overexpression of wild-type PINK1 protects cells against apoptosis, whereas small interfering RNA (siRNA)-mediated PINK1 deprivation accelerates apoptotic cell death [29,37]. Since both prolonged hypoxia and MPP+ insults reduced the PINK1 protein concentration, we hypothesized that these two cell injury models may share a common mechanism, which is associated with the dysregulation of PINK1 and caspase 3 signaling. As our conjecture, such dysregulation led to a swelling or enlargement of mitochondria due to a loss of membrane maintenance, while mitochondrial dysfunction may be associated with the release of apoptogenic factors, which triggers the conversion of inactive caspases to the active forms, therefore resulting in a reduction in cell viability. It is interesting to note that DOR activation effectively attenuated cell injury induced by hypoxia and MPP+ insults and reversed the reduction in PINK1 and the increase in cleaved caspase 3. Our results strongly suggest that DOR-mediated neuroprotection is closely associated with the rebalance of survival signals via the regulation of PINK1 and caspase 3. In summary, our findings showed that prolonged hypoxia, and MPP+ stress can cause severe cellular injury by decreasing PINK1 expression and thus lead to mitochondrial dysfunction, which is associated with the caspase signaling pathway. DOR activation positively regulated PINK1 expression and negatively affected the transition from inactivated caspase 3 to activated caspase 3, thus attenuating hypoxia or MPP+ injury. Our findings sheds a light on DOR’s potential as a promising target that can be applied for clinical neurotherapeutics, especially for Parkinsonism conditions. 4. Materials and Methods 4.1. Chemicals and Reagents UFP-512, a specific and potent DOR agonist was produced by our research group. Naltrindole hydrochloride was purchased from Tocris Bioscience (Cat: 0740, Bristol, UK). MPP+ (1-methyl-4-phenylpyridinium), MTT powder for cell viability, and fetal bovine serum (FBS) were all purchased form Sigma Chemical Co. (Cat: D048, 15H467, M2128, respectively, St. Louis, MO, USA). LDH cytotoxicity assay kit was purchased from Beyotime Biotechnology (Cat: C0016, Shanghai, China). Dulbecco’s Modified Eagle Medium (DMEM) for cell culture was purchased from Gibco®, Thermo Fisher Scientific (Cat: 11995-065, Waltham, MA, USA). Anti-PINK1 antibody was purchased from Novus Biologicals (Cat: BC100-494, Littleton, CO, USA). Anti-β-actin antibody, anti-caspase 3-antibody were all purchased from Cell Signaling Technology (Cat: 4970, 4691, 4060, 9662S, respectively, Danvers, CO, USA). 4.2. Cell Cultures and Experimental Groups Highly differentiated PC-12 cell line was obtained from American Type Culture Collection (Manassas, VA, USA) and maintained in Dulbecco’s Modified Eagle Medium (DMEM), supplemented with 10% FBS. Under normoxic control conditions, the cells were incubated at 37 °C in a humidified atmosphere with 5% CO2. Before induction of hypoxia or MPP+ Parkinsonism, the cells were cultured in 6-well plates, and were then randomly allocated to normoxia, hypoxia and MPP+ groups. For hypoxia, the cells were placed in a hypoxic chamber (Galaxy 48R, New Brun-swick, Edison, NJ, USA) at 37 °C, and its O2 levels were kept strictly at 0.5% or 1% by constantly flushing with nitrogen. For mimicking PD conditions, the cells were exposed to 0.5–2.0 mM of MPP+. UFP-512 (5 μM) and naltrindole (1 μM) were separately added to the culture mediums before the onset of hypoxia and MPP+ exposure. In the normoxic control group, they were added to the culture medium at a similar time point. There were the following experimental groups: C: normoxic control. H: hypoxia. H + U: DOR activation with UFP-512 (5 μM) in hypoxic condition. H + N: DOR inhibition with naltrindole (1 μM) in hypoxic condition. M: MPP+. M + U: DOR activation with UFP-512 (5 μM) under MPP+ insult. M + N: DOR inhibition with naltrindole (1 μM) under MPP+ insult. 4.3. Cell Viability Assay Cell viability was measured by a MTT assay. Exponentially growing cells were plated at 6000 cells/well in a 96-well flat-bottom plate, and were allowed to incubate overnight at 37 °C in a humidified incubator with 5% CO2. Wells without cells but containing a 200 μL culture medium served as a control for the minimum absorbance. After drug treatment for 24 h, MTT reagent (20 μL/200 μL per well of the 96 well plate) was added, and the cells were incubated another 4 h before measurement. The absorbance was assessed at the wavelength of 490 nm using a microplate reader (BioTek, Winooski, VT, USA). Lactate Dehydrogenase Assessment Cytotoxicity was quantitatively evaluated by measuring the activity of lactate dehydrogenase (LDH) in the culture medium using a LDH cytotoxicity assay kit. The cells were treated with indicated compounds and incubated for the desired period. Plates containing 10% lactate release reagent and a 200 μL of culture medium without cells were set as maximum control and blank control respectively. After 5 min of centrifugation at 400 g, 120 μL supernatant was transferred to a new 96 well plate and mixed with the provided working solution. These mixtures were incubated at room temperature, protected from light, and for 30 min, the absorbance of each solution was recorded by a microplate reader (BioTek, Winooski, VT, USA) at the wavelength of 490 nm. % cytotoxicity was calculated as follows: % Cytotoxicity=[experimental (OD490)−blank (OD490)]×100[maximum LDH release (OD490)−blank  (OD490)] 4.4. Western Blotting Cells were lyzed at 4 °C using lysis buffer containing 0.1% protease inhibitor, 1% phosphatase inhibitor and 0.5% 100 mM PMSF (KeyGEN Biotec, Cat: KGP2100, Nanjing, China). The protein concentration was determined using the BCA protein assay kit, and equal amounts of proteins or equal proportions of cell lysates were analyzed using a Western blot. Protein samples were diluted in a 6× sample buffer containing no reducing agent and run in 10% SDS-PAGE. After electrophoresis, proteins were transferred to hydrophobic polyvinylidenedifluorid (PVDF) membranes, and then probed with various mAbs. The binding of mAbs was detected using HRP conjugated secondary antibodies, and visualized using Western Lightening® Chemiluminescence Reagent Plus (Perkin-Elmer, Boston, MA, USA). Quantitation was performed by densitometry using the NIH Image program (Image J). 4.5. Statistical Analysis All data are presented as means ± SEM of at least three independent experiments. Statistical analysis was performed using one-way ANOVA followed by Bonferroni’s multiple comparison test (Prism 5, GraphPad Software, La Jolla, CA, USA). Acknowledgments Yilin Yang was supported by Jiangsu SPMS (BL2014035) of China. Ying Xia was supported by Memorial Hermann’s Foundation and Vivian L Smith Neurologic Foundation. Author Contributions Ying Xia, Yilin Yang, Yuan Xu and Feng Zhi conceived and designed the experiments; Yuan Xu and Rong Wang performed the experiments; Yuan Xu, Feng Zhi and Naiyuan Shao analyzed the data; Yilin Yang, Naiyuan Shao and Feng Zhi contributed reagents/materials/analysis tools; Yuan Xu and Ying Xia wrote the paper. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Responses of PC12 cells to DOR activation/inhibition under hypoxia. (a) Effects of hypoxia on cell viability. PC12 cells were exposed to hypoxia at 1% O2 for 24–48 h, and then the cell viability was measured by an MTT assay; (b) Effects of hypoxia on LDH leakage. PC12 cells were exposed to hypoxia at 1% O2 for 24–48 h, and then LDH leakage was measured. C: normoxic control. H: hypoxia. H + U: DOR activation with UFP-512 in hypoxic condition. H + N: DOR inhibition with naltrindole in hypoxic conditions. N = 3 in each group. * p < 0.05, ** p < 0.01 vs. control. # p < 0.05, ## p < 0.01 vs. H. Note that the cell viability was progressively reduced by the increase in hypoxic duration. DOR activation increased cell viability and decreased LDH leakage in hypoxic stress, while DOR inhibition further increased hypoxia induced injury. Figure 2 DOR activation protected PC12 cells against MPP+ insults. (a) Effects of MPP+ on cell viability. PC12 cells were exposed to 1.0 mM MPP+ for 24–48 h, and then cell viability was measured by an MTT assay; (b) Effects of MPP+ on LDH leakage. PC12 cells were exposed to 1.0 mM MPP+ for 24–48 h, and then LDH leakage was measured. C: normoxic control. M: MPP+. M + U: DOR activation with UFP-512 exposed to 1.0 mM MPP+. M + N: DOR inhibition with naltrindole exposed to 1.0 mM MPP+. N = 3 in each group. * p < 0.05, ** p < 0.01 vs. control. Note that cell viability was progressively reduced by the increase in MPP+ exposure duration, DOR activation increased cell viability in the first 24 h and largely prevented LDH leakage after 48 h, while naltrindole further increased the injury induced by MPP+. Figure 3 DOR induced attenuation of activated caspase 3 overexpression under hypoxia. Effects of hypoxia on pro-caspase 3 and cleaved caspase 3 expression in PC12 cells. The experiments were conducted under the same conditions described in Figure 1. C: normoxic control. H: hypoxia. H + U: DOR activation with UFP-512 in hypoxic conditions. H + N: DOR inhibition with naltrindole in hypoxic conditions. N = 3 for each group. ** p < 0.01 vs. control. # p < 0.05, ## p < 0.01 vs. H. Note that the level of cleaved caspase 3 increased and the level of pro-caspase 3 decreased after 48 h exposure to hypoxia. DOR activation with UFP-512 significantly attenuated the expression level of cleaved caspase 3, whereas naltrindole led to an increase in the level of cleaved caspase 3, and a decrease in that of inactivated caspase 3. Figure 4 DOR activation attenuated the increase in activated caspase 3 induced by MPP+ insults. The experiments were conducted under the same conditions as described in Figure 2. C: normoxic control. M: MPP+. M + U: DOR activation with UFP-512 exposed to 1.0 mM MPP+. M + N: DOR inhibition with naltrindole exposed to 1.0 mM MPP+. N = 3 for each group. ** p < 0.01 vs. control. # p < 0.05, ## p < 0.01 vs. M. Note that the level of cleaved caspase 3 increased while the level of pro-caspase 3 decreased after 24-h exposure to MPP+. DOR activation with UFP-512 decreased MPP+-induced increase in cleaved caspase 3, whereas naltrindole led to an increase in cleaved caspase 3 with a reduction in inactivated caspase 3. Figure 5 Hypoxia reduced PINK1 protein density in PC12 cells. The effects of hypoxia on PINK1 protein density at different oxygen levels for different durations was analyzed by Western blot. C: normoxic control. H: hypoxia. N = 3 for each group. ** p < 0.01 vs. control. Note that both hypoxic conditions significantly reduced the level of PINK1 protein, while there was a more significant reduction, when under hypoxia at 1% O2 for 48 h. Figure 6 MPP+-induced reduction in PINK1 protein of PC12 cells. PINK1 protein was detected using Western blot. C: normoxic control. M: MPP+. ** p < 0.01 vs. control. Note that MPP+ exposure significantly reduced the level of PINK1 protein and this reduction was more marked as the concentration of MPP+ increased. Figure 7 Effect of DOR activation on PINK1 and DOR expression in PC12 cells exposed to hypoxic or MPP+ insults. (a) PC12 cells were exposed to hypoxia at 1% O2 for 48 h. C: normoxic control. H: hypoxia. H + U: DOR activation with UFP-512 in hypoxia. H + N: DOR inhibition with naltrindole in hypoxia. Note that hypoxia at 1% O2 for 48 h greatly decreased PINK1 expression, while DOR activation increased the level of PINK1 in the same hypoxic condition. In contrast, DOR expression did not change significantly in hypoxia with/without DOR activation; (b) PC12 cells were exposed to 1.0 mM MPP+ for 24 h. C: normal control. M: MPP+. M + U: DOR activation with UFP-512 in MPP+ stress. M + N: DOR inhibition with naltrindole in MPP+ stress. Note that DOR activation reversed the reduction of PINK1 expression induced by MPP+ insult, and partially attenuated MPP+ induced reduction of DOR expression. ==== Refs References 1. Valente E.M. Abou-Sleiman P.M. Caputo V. Muqit M.M. Harvey K. Gispert S. Ali Z. del Turco D. Bentivoglio A.R. Healy D.G. Hereditary early-onset Parkinson’s disease caused by mutations in PINK1 Science 2004 304 1158 1160 10.1126/science.1096284 15087508 2. Mazzucchi S. Frosini D. Ripoli A. Nicoletti V. Linsalata G. Bonuccelli U. Ceravolo R. Serotonergic antidepressant drugs and L-dopa-induced dyskinesias in Parkinson’s disease Acta Neurol. Scand. 2015 131 191 195 10.1111/ane.12314 25274076 3. Politis M. Lindvall O. Clinical application of stem cell therapy in Parkinson’s disease BMC Med. 2012 10 1 10.1186/1741-7015-10-1 22216957 4. Feng L.R. Maguire-Zeiss K.A. Gene therapy in Parkinson’s disease: Rationale and current status CNS Drugs 2010 24 177 192 10.2165/11533740-000000000-00000 20155994 5. Gao C. Zhu W. Tian L. Zhang J. Li Z. MCT4-mediated expression of EAAT1 is involved in the resistance to hypoxia injury in astrocyte-neuron co-cultures Neurochem. Res. 2015 40 818 828 10.1007/s11064-015-1532-2 25645447 6. Karunasinghe R.N. Lipski J. Oxygen and glucose deprivation (OGD)-induced spreading depression in the Substantia Nigra Brain Res. 2013 1527 209 221 10.1016/j.brainres.2013.06.016 23796781 7. Rodriguez-Grande B. Blackabey V. Gittens B. Pinteaux E. Denes A. Loss of substance P and inflammation precede delayed neurodegeneration in the substantia nigra after cerebral ischemia Brain Behav. Immun. 2013 29 51 61 10.1016/j.bbi.2012.11.017 23232501 8. Siuda J. Jasinska-Myga B. Boczarska-Jedynak M. Opala G. Fiesel F.C. Moussaud-Lamodiere E.L. Scarffe L.A. Dawson V.L. Ross O.A. Springer W. Early-onset Parkinson’s disease due to PINK1 p.Q456X mutation—Clinical and functional study Parkinsonism Relat. Disord. 2014 20 1274 1278 10.1016/j.parkreldis.2014.08.019 25226871 9. Yunfu W. Guangjian L. Ping Z. Yanpeng S. Xiaoxia F. Wei H. Jiang Y. Jingquan H. Songlin W. Hongyan Z. PINK1 and its familial Parkinson’s disease-associated mutation regulate brain vascular endothelial inflammation J. Mol. Neurosci. 2014 53 109 116 10.1007/s12031-013-0207-1 24385196 10. Minami A. Nakanishi A. Matsuda S. Kitagishi Y. Ogura Y. Function of alpha-synuclein and PINK1 in Lewy body dementia (Review) Int. J. Mol. Med. 2015 35 3 9 25355138 11. Kazlauskaite A. Muqit M.M. PINK1 and Parkin—Mitochondrial interplay between phosphorylation and ubiquitylation in Parkinson’s disease FEBS J. 2015 282 215 223 10.1111/febs.13127 25345844 12. Pickrell A.M. Youle R.J. The roles of PINK1, parkin, and mitochondrial fidelity in Parkinson’s disease Neuron 2015 85 257 273 10.1016/j.neuron.2014.12.007 25611507 13. Van der Merwe C. van Dyk H.C. Engelbrecht L. van der Westhuizen F.H. Kinnear C. Loos B. Bardien S. Curcumin Rescues a PINK1 Knock Down SH-SY5Y Cellular Model of Parkinson’s Disease from Mitochondrial Dysfunction and Cell Death Mol. Neurobiol. 2016 10.1007/s12035-016-9843-0 27003823 14. Burbulla L.F. Fitzgerald J.C. Stegen K. Westermeier J. Thost A.K. Kato H. Mokranjac D. Sauerwald J. Martins L.M. Woitalla D. Mitochondrial proteolytic stress induced by loss of mortalin function is rescued by Parkin and PINK1 Cell Death Dis. 2014 5 e1180 10.1038/cddis.2014.103 24743735 15. Gogvadze V. Orrenius S. Zhivotovsky B. Analysis of mitochondrial dysfunction during cell death Methods Mol. Biol. 2015 1264 385 393 25631030 16. Orrenius S. Gogvadze V. Zhivotovsky B. Calcium and mitochondria in the regulation of cell death Biochem. Biophys. Res. Commun. 2015 460 72 81 10.1016/j.bbrc.2015.01.137 25998735 17. Cohen G.M. Caspases: The executioners of apoptosis Biochem. J. 1997 326 1 16 10.1042/bj3260001 9337844 18. Choudhary G.S. Al-Harbi S. Almasan A. Caspase-3 activation is a critical determinant of genotoxic stress-induced apoptosis Methods Mol. Biol. 2015 1219 1 9 25308257 19. Sakahira H. Enari M. Nagata S. Cleavage of CAD inhibitor in CAD activation and DNA degradation during apoptosis Nature 1998 391 96 99 10.1038/nature15532 9422513 20. Liu X. Zou H. Slaughter C. Wang X. DFF, a heterodimeric protein that functions downstream of caspase-3 to trigger DNA fragmentation during apoptosis Cell 1997 89 175 184 10.1016/S0092-8674(00)80197-X 9108473 21. Liu X. Li P. Widlak P. Zou H. Luo X. Garrard W.T. Wang X. The 40-kDa subunit of DNA fragmentation factor induces DNA fragmentation and chromatin condensation during apoptosis Proc. Natl. Acad. Sci. USA 1998 95 8461 8466 10.1073/pnas.95.15.8461 9671700 22. Rathnasamy G. Sivakumar V. Rangarajan P. Foulds W.S. Ling E.A. Kaur C. NF-kappaB-mediated nitric oxide production and activation of caspase-3 cause retinal ganglion cell death in the hypoxic neonatal retina Investig. Ophthalmol. Vis. Sci. 2014 55 5878 5889 10.1167/iovs.13-13718 25139733 23. Zhang J. Gibney G.T. Zhao P. Xia Y. Neuroprotective role of delta-opioid receptors in cortical neurons Am. J. Physiol. Cell Physiol. 2002 282 C1225 C1234 10.1152/ajpcell.00226.2001 11997236 24. Zhang J. Qian H. Zhao P. Hong S.S. Xia Y. Rapid hypoxia preconditioning protects cortical neurons from glutamate toxicity through delta-opioid receptor Stroke J. Cereb. Circ. 2006 37 1094 1099 10.1161/01.STR.0000206444.29930.18 16514101 25. Ma M.C. Qian H. Ghassemi F. Zhao P. Xia Y. Oxygen-sensitive-opioid receptor-regulated survival and death signals: Novel insights into neuronal preconditioning and protection J. Biol. Chem. 2005 280 16208 16218 10.1074/jbc.M408055200 15687501 26. Monti C. Bondi H. Urbani A. Fasano M. Alberio T. Systems biology analysis of the proteomic alterations induced by MPP(+ ), a Parkinson’s disease-related mitochondrial toxin Front. Cell. Neurosci. 2015 9 14 10.3389/fncel.2015.00014 25698928 27. Chen T. Hou R. Li C. Wu C. Xu S. MPTP/MPP+ suppresses activation of protein C in Parkinson’s disease J. Alzheimer Dis. JAD 2015 43 133 142 28. Ding A.X. Sun G. Argaw Y.G. Wong J.O. Easwaran S. Montell D.J. CasExpress reveals widespread and diverse patterns of cell survival of caspase-3 activation during development eLife 2016 5 e10936 10.7554/eLife.10936 27058168 29. Arena G. Gelmetti V. Torosantucci L. Vignone D. Lamorte G. De Rosa P. Cilia E. Jonas E.A. Valente E.M. PINK1 protects against cell death induced by mitochondrial depolarization, by phosphorylating Bcl-xL and impairing its pro-apoptotic cleavage Cell Death Differ. 2013 20 920 930 10.1038/cdd.2013.19 23519076 30. Gautier C.A. Corti O. Brice A. Mitochondrial dysfunctions in Parkinson’s disease Rev. Neurol. 2014 170 339 343 10.1016/j.neurol.2013.06.003 24119854 31. Subramaniam S.R. Chesselet M.F. Mitochondrial dysfunction and oxidative stress in Parkinson’s disease Prog. Neurobiol. 2013 106–107 17 32 10.1016/j.pneurobio.2013.04.004 23643800 32. Liu X.R. Li Y.Q. Hua C. Li S.J. Zhao G. Song H.M. Yu M.X. Huang Q. Oxidative stress inhibits growth and induces apoptotic cell death in human U251 glioma cells via the caspase-3-dependent pathway Eur. Rev. Med. Pharmacol. Sci. 2015 19 4068 4075 26592828 33. Meng X.W. Fraser M.J. Feller J.M. Ziegler J.B. Caspase-3-dependent and caspase-3-independent pathways leading to chromatin DNA fragmentation in HL-60 cells Apoptosis Int. J. Program. Cell Death 2000 5 61 67 10.1023/A:1009689710184 34. Liu X. Kim C.N. Yang J. Jemmerson R. Wang X. Induction of apoptotic program in cell-free extracts: Requirement for dATP and cytochrome c Cell 1996 86 147 157 10.1016/S0092-8674(00)80085-9 8689682 35. Lax A. Soler F. Fernandez-Belda F. Mitochondrial damage as death inducer in heart-derived H9c2 cells: More than one way for an early demise J. Bioenerg. Biomembr. 2009 41 369 377 10.1007/s10863-009-9236-4 19777329 36. Rakovic A. Shurkewitsch K. Seibler P. Grunewald A. Zanon A. Hagenah J. Krainc D. Klein C. Phosphatase and tensin homolog (PTEN)-induced putative kinase 1 (PINK1)-dependent ubiquitination of endogenous Parkin attenuates mitophagy: Study in human primary fibroblasts and induced pluripotent stem cell-derived neurons J. Biol. Chem. 2013 288 2223 2237 10.1074/jbc.M112.391680 23212910 37. Li L. Hu G.K. PINK1 protects cortical neurons from thapsigargin-induced oxidative stress and neuronal apoptosis Biosci. Rep. 2015 35 e00174 10.1042/BSR20140104 25608948

PMC005xxxxxx/PMC5000590.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081182ijms-17-01182ArticleSerum Concentrations of Endothelin-1 and Matrix Metalloproteinases-2, -9 in Pre-Hypertensive and Hypertensive Patients with Type 2 Diabetes Kostov Krasimir 1*Blazhev Alexander 2Atanasova Milena 2Dimitrova Anelia 1Cho William Chi-shing Academic Editor1 Department of Physiology and Pathophysiology, Medical University-Pleven, 1 Kliment Ohridski Str., 5800 Pleven, Bulgaria; anelija.dimitrova@gmail.com2 Division of Biology, Medical University-Pleven, 1 Kliment Ohridski Str., 5800 Pleven, Bulgaria; yalishanda9@gmail.com (A.B.); milenaar2001@yahoo.com (M.A.)* Correspondence: dr.krasi_kostov@abv.bg; Tel.: +359-889-257-45901 8 2016 8 2016 17 8 118201 6 2016 13 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).Endothelin-1 (ET-1) is one of the most potent vasoconstrictors known to date. While its plasma or serum concentrations are elevated in some forms of experimental and human hypertension, this is not a consistent finding in all forms of hypertension. Matrix metalloproteinases -2 and -9 (MMP-2 and MMP-9), which degrade collagen type IV of the vascular basement membrane, are responsible for vascular remodeling, inflammation, and atherosclerotic complications, including in type 2 diabetes (T2D). In our study, we compared concentrations of ET-1, MMP-2, and MMP-9 in pre-hypertensive (PHTN) and hypertensive (HTN) T2D patients with those of healthy normotensive controls (N). ET-1, MMP-2, and MMP-9 were measured by ELISA. Concentrations of ET-1 in PHTN and N were very similar, while those in HTN were significantly higher. Concentrations of MMP-2 and MMP-9 in PHTN and HTN were also significantly higher compared to N. An interesting result in our study is that concentrations of MMP-2 and MMP-9 in HTN were lower compared to PHTN. In conclusion, we showed that increased production of ET-1 in patients with T2D can lead to long-lasting increases in blood pressure (BP) and clinical manifestation of hypertension. We also demonstrated that increased levels of MMP-2 and MMP-9 in pre-hypertensive and hypertensive patients with T2D mainly reflect the early vascular changes in extracellular matrix (ECM) turnover. pre-hypertensiontype 2 diabetesendothelin-1matrix metalloproteinases-2matrix metalloproteinases-9vascular remodeling ==== Body 1. Introduction Endothelin-1 is one of the most potent vasoconstrictors known in humans to date [1]. Although, different types of cells, including cardiac myocytes, vascular smooth muscle cells (VSMCs), fibroblasts, or epithelial cells are able to synthesize and release ET-1, the most important biological source is the vascular endothelium [2]. ЕТ-1 is secreted primarily from the endothelial cells and influenced of the underlying VSMCs. Considering that approximately 80% of the total amount of ET-1 synthesized by endothelial cells is released toward the basolateral side of cells, tissue levels are higher than plasma levels. Thus, ET-1 acts primarily as a paracrine/autocrine peptide, and not as a circulating hormone [3]. Except through impact on vascular tone, ET-1 is involved in the complex regulation of BP through effects on renal hemodynamics and water-salt balance, influence on adrenal aldosterone, and catecholamine production, it also participates in the central and baroreceptor regulation and has positive inotropic effects on the heart [4]. In addition, ET-1 potentiates the action of other vasoconstrictors, such as angiotensin II (Ang II), phenylephrine, and serotonin [5]. The role of ET-1 and its receptors in the regulation of BP and in the pathogenesis of hypertension is not clearly established. For instance, while the plasma or vascular levels are elevated in some forms of experimental and human hypertension, this is not a consistent finding in all forms of hypertension [6,7]. Several reports suggested that patients with hypertension have elevated levels of ET-1. However, many other studies reported no difference of ET-1 levels between normotensive and hypertensive subjects [4]. An increased level of ET-1 has been demonstrated in some animal models of diabetes. Similarly, elevated levels of ET-1 have been reported in patients with diabetes, a finding not confirmed by all reports [8]. The role of MMPs in the process of vascular remodeling is extensively discussed [9,10,11,12]. Vascular remodeling is permanent process of structural changes in the vessel wall in response to hemodynamic stimulus [13]. In various forms of hypertension, including in human essential hypertension, resistance arteries undergoing inward remodeling, while larger vessels show hypertrophy [14,15,16]. MMP-2 and MMP-9, which degrade type IV collagen of the vascular basal membrane [17] are between most investigated MMPs and they play an essential role in the remodeling process [12,18,19]. MMP-2 and MMP-9 are secreted by a variety vascular and non-vascular cell types, such as endothelial cells, podocytes, fibroblasts, and myofibroblasts, macrophages formed by monocytes, as well as by resident tissue macrophages [20]. They are responsible for vascular remodeling, angiogenesis, inflammation, and atherosclerotic complications [21]. MMP-2 may participate in the pathogenesis of hypertension and through direct interaction with vasoactive peptides. For example, it could cleave big ET-1 to active ET-1, which have higher vasoconstrictor activity [22]. In patients with hypertension, it has been found that the plasma levels and activity of MMP-2 and MMP-9 can be increased [23,24,25], decreased [26,27,28], or unchanged [13,29,30]. The difficulty in finding precise correlations between activity/levels of ММРs in hypertension may depend largely on the impact of antihypertensive medications [31], as well on the clinical stage of patients who are assessed. Additionally, high blood glucose levels in diabetics induces disregulation of the MMPs/TIMPs system, which significantly upsets the balance between synthesis and degradation of vascular extracellular matrix (ECM) [32,33]. Based on the above, we tested serum concentrations of ET-1, MMP-2, and MMP-9 in pre-hypertensive and hypertensive patients with T2D, to clarify if there link between their levels and BP values. 2. Results 2.1. Serum Concentrations of Endothelin-1 (ET-1) in the Groups Concentrations of ET-1 were significantly higher in HTN 6.64 ± 5.36 pg/mL compared to PHTN 3.52 ± 2.29 pg/mL (F = 4.41, p < 0.05) and N 3.55 ± 1.78 pg/mL (F = 4.56, p < 0.05), but this difference was not observed between PHTN and N (F = 0.00, p > 0.05). Concentrations of ET-1 in PHTN and N are very similar, while those in HTN are significantly higher (Figure 1). These results show a possible connection between increased circulating ET-1 levels and clinical manifestation of arterial hypertension in patients with T2D. This is probably a consequence by dysmetabolic vascular changes leading to increased production of ET-1 and intensification of its pro-oxidant/pro-inflammatory effects and vasoconstrictor activity. 2.2. Serum Concentrations of Matrix Metalloproteinase-2 (MMP-2) in the Groups Concentrations of MMP-2 in PHTN 38.31 ± 9.12 ng/mL and HTN 36.22 ± 9.56 ng/mL were significantly higher compared to N 27.62 ± 6.94 ng/mL (F = 12.71, p < 0.002 and F = 8.41, p < 0.007) (Figure 2). Despite the fact that there were no statistical differences between PHTN and HTN (F = 0.39, p > 0.05), it is noteworthy that, in HTN, concentrations of MMP-2 are lower. This indicates that the balance between synthesis and degradation of ECM proteins in the vascular wall is developing dynamically over time. Probably, the expression of MMP-2 is induced at the beginning of the hypertensive process and its increased levels are mainly reflecting the early changes in ECM vascular turnover, provided that no significant vascular complications exist. 2.3. Serum Concentrations of MMP-9 in the Groups Concentrations of MMP-9 in PHTN 49.60 ± 12.37 ng/mL and HTN 35.55 ± 10.25 ng/mL were significantly higher compared to N 21.86 ± 7.47 ng/mL (F = 59.35, p < 0.0001 and F = 19.78, p < 0.0002). There were also statistical differences between PHTN and HTN, as it should be noted that, in HTN, concentrations of MMP-9 were significantly lower (F = 11.95, p < 0.002) (Figure 3). MMP-9, similar to MMP-2 is induced at the early stages of hypertension, and this is probably favorable to alleviate the initial vascular tensile stress. Later, the effects of MMP-2 and MMP-9 are counterbalanced by expression of tissue inhibitors of MMPs (TIMPs) and their concentrations began to decline. 3. Discussion The results of our study demonstrate that concentrations of ET-1 in PHTN are very similar with those in N. This is not surprising, because elimination of ET-1 from the blood occurs rapidly. Additionally, the secretion of ET-1 from endothelial cells is polarized mainly toward the underlying VSMCs, which leads to a minimal increase of its circulating levels [6] in PHTN. On the contrary, it can be supposed that concentrations of ET-1 in HTN are significantly higher, which is supported by our experimental data. To exclude the influence of age and sex as factors in the analysis of the data is correct to clarify that concentrations of ET-1 do not show significant gender [34] and age differences. A number of studies of Donato et al., show that in healthy adults, plasma ET-1 concentrations either increase modestly or do not change with aging [35]. According to other authors, plasma ET-1 concentrations increase with age in some adults [36], as this process may be reversible after chronic exercise training [37]. Experimental data in rodent models do not show significant age-specific effects of ET-1 in relation to BP, because increased levels correlated with contractions in aortas from young rats, but not from old rats [38]. An age-associated increase in arterial pressure is a clinical hallmark of aging and results from joint effects of multiple factors, including, intimal-medial thickening, arterial pro-inflammatory responses, and vasoconstriction from Ang II and ET-1 effects [39]. Similar to our results, according to which plasma concentrations of ET-1 have been significantly higher in hypertensive patients with T1D and T2D compared to controls, are reported by Schneider et al. [40]. In keeping with this, it can be supposed that there is a possible connection between increased circulating levels of ET-1 and the development of hypertension in patients with T2D. This is probably the result of its enhanced vasoconstrictor, pro-oxidative, and pro-inflammatory action as a consequence of diabetes-related vascular changes. ET-1 is linked to the pathogenesis of hypertension by means of low-grade vascular inflammation [41,42] and oxidative stress at the vascular wall [43,44,45]. Low-grade inflammation localized in the vascular tissue is an important factor in the pathophysiology of hypertension [46]. ET-1 can activate the macrophages, which result in the release of pro-inflammatory and chemotactic mediators, such as TNF-α, IL-1, IL-6, and IL-8 [47,48,49]. Overexpression of ET-1 is associated with an inflammatory response, increased activation of NF-κB and the expression of several proinflammatory cytokines, such as TNF-α, IL-1, and IL-6 [50]. In turn, this transcription factor, and pro-inflammatory cytokines, can stimulate the production of ET-1 [51], and this could lead to increased BP [52,53,54]. The relationship between oxidative stress in the vessel wall and the development of hypertension is shown in many experimental models, including in human hypertension [55,56,57,58]. Various research supports the role of ET-1 in the formation of reactive oxygen species (ROS) and its relationship with oxidative stress and endothelial dysfunction in humans. ET-1 stimulates the production of ROS in human endothelial and vascular smooth muscle cell cultures [59,60], as well as in isolated vessels [61,62,63]. It is assumed that the main mechanism for the increased production of ROS in hypertension is increased expression of vascular NADPH oxidase [44,64,65,66]. Increased production of ROS in the vascular wall leads to activation of NF-κB. This, in turn, stimulates the synthesis of pro-inflammatory cytokines, chemokines, and adhesion molecules, which are associated with the development of vascular inflammatory response [67]. Thus, inflammation and oxidative stress form a vicious cycle in the development of endothelial dysfunction, which is implemented with active participation of ET-1. Elevated ET-1 levels may suppress NO synthesis in the endothelium [68]. One general observation, made in almost all studies, investigating endothelin receptor blockade and vascular function in animal models of hypertension, hypercholesterolemia, or atherosclerosis, is that long-term treatment with ETA receptor antagonists, improves endothelium-dependent NO-mediated vasodilation [69]. ET-1 causes insulin resistance and may participate in the pathogenesis of the metabolic syndrome [68]. Blockade of ET-1 signaling, improves vasodilation in diabetes and reduces insulin resistance [70]. Given the all vascular and extravascular effects of ET-1 taken together, we hypothesize that increased production of ET-1 in patients with T2D can lead to a long-lasting increase in blood pressure and clinical manifestation of hypertension. In our study, we observed that, in PHTN, concentrations of MMP-2 and MMP-9 were significantly higher compared to N. Similar results are reported by Derosa et al., who found that the levels of MMP-2, MMP-9, and TIMP-1 are increased in patients with hypertension [23], as well as in patients with T2D [71]. Increased concentrations of MMP-9 in hypertensive patients with T2D have been reported earlier, also from other researchers [72,73,74]. An interesting result in our study is that concentrations of both metalloproteinases in HTN were also significantly higher compared to N, but lower compared to PHTN. In keeping with this, we hypothesize that MMP-2 and MMP-9 are induced at the early stages of the hypertension, and this is probably favorable for alleviation of the initial vascular tensile stress. Long-term effects of MMP-2 and MMP-9 in the vessel wall are counterbalanced by expression of TIMPs and their concentrations begin to decline [75,76,77], and may even be reduced in comparison to those of the control group. Reasons for this conclusion, given our data from a previous study which showed that the concentrations of MMP-9 in patients with mild, and especially with severe, hypertension are reduced significantly, compared to those of controls [78]. Similar results are reported by Zervoudaki et al., who observed a significant decrease of plasma levels of MMP-2 and MMP-9 in patients with essential hypertension in comparison with normotensive persons [28]. Li-Saw-Hee and coauthors also reported that the proteolytic activity of MMP-9 is suppressed in hypertensive patients [27]. The reduced concentration of MMP-9 in hypertension is associated with a decrease in the total activity of MMP-9, resulting in the accumulation of collagen in vascular wall of resistive arteries, reduction in their elasticity, and progression of hypertension [11]. Discrepancies between the data about MMP-2 and MMP-9 in different studies could be explained, considering that the balance between synthesis and degradation of ECM in hypertension is changing dynamically over time, and that production of ММРs are induced only for a certain period after the start of hypertension [76]. Elevated levels or activity of ММРs may indicate early changes in vascular ECM turnover, which later leads to the increase in arterial stiffness [58]. In the debut of hypertension, increased ММР expression is related to increasing arterial elasticity ex vivo [79] and in vivo [75]. Thus, the vascular wall normalizes the tensile stress and, in the short term, counteracts the increased BP. At this stage, MMPs are key players in ECM degradation. However, in the long-term, ECM proteins are synthesized again and they form new connections each other. This violates the beneficial effects of the initial remodeling process and ultimately leads to increased arterial stiffness [12]. It should be noted that, in comparison with the general population, atherosclerosis in patients with T2D is manifested earlier, and it may be more generalized and severe. Significantly higher serum concentrations of MMP-2 and MMP-9 are found in patients with T2D and atherosclerosis [74]. Overexpression of MMP-2 and MMP-9 in diabetic atherosclerotic plaques may increase their vulnerability which, in turn, increases the risk of ischemic cardiovascular events [80]. Furthermore, a chronic increase in MMP activation is central to age-associated arterial structural remodeling [81]. Throughout aging, the balance between MMPs and their inhibitors is changing [82] and MMP-2/-9 expression and activity are increased in vascular walls [83,84]. Typical vascular diseases such as hypertension and atherosclerosis also could be viewed as accelerated arterial aging and they are also linked to increased MMP activation [81]. Violation of the physiological balance between ММРs/TIMPs has been confirmed in early stages of diabetic retinopathy [73] and nephropathy [72,85]. Therefore, increased levels of MMP-2 and MMP-9 in pre-hypertensive and hypertensive patients with T2D, reflect mainly the early changes in ECM vascular turnover, provided that there are no significant vascular complications. 4. Materials and Methods 4.1. Study Population and Design The study was approved by the University Ethics Committee and conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all subjects. The study population was consisted of 60 persons: 40 prehypertensive and hypertensive T2D patients treated at the University Hospital Georgi Stranski, Pleven, and 20 healthy normotensive individuals. Three groups were formed: Group I (n = 20): normotensive controls (N); Group II (n = 20): pre-hypertension group (PHTN); and Group III (n = 20): hypertension group (HTN). Clinical characteristics of each group are shown in Table 1. 4.2. Immunological and Laboratory Testing All laboratory determinations were obtained after a 12 h fast. To measure ET–1, MMP-2, MMP-9, and other laboratory parameters, blood was drawn into serum tubes. Serum was obtained after centrifugation at 1500 rpm for 15 min, and then stored at −80 °C until assayed. 4.2.1. Immunological Testing Indirect ELISA for Determination of ET-1 To measure ET-1, an ELISA kit from Biomedica Medizinprodukte GmbH and Co. KG, Divischgasse 4, A-1210 Wien, Austria (cat. No. BI-20052) was used. According to the manufacturer’s instructions, to each well-plate 50 µL tested sera or standard was added at various concentrations to construct a calibration curve. Then 200 µL of detection antibody was added to each well and incubated for 16–24 h at room temperature. After this period, plates were washed five times with 300 µL diluted wash buffer per well. After the last wash, 200 µL of conjugate was added to each well and incubated for 1 h at room temperature. The plate was washed again five times with 300 µL washing buffer, in each well 200 µL substrate was added and incubated for 30 min in the dark. The reaction was stopped with 50 µL of stop solution. The serum samples were assayed at 450 nm on an automatic micro-ELISA plate reader (Ceres UV 900 C, BioTek Instruments Inc., Winooski, VT, USA) at the Immunological Laboratory of Biology Department of Medical University, Pleven. Indirect ELISA for Determination of MMP-2 To measure MMP-2, an ELISA kit from R and D Systems (cat. No. DMP2F0) (Minneapolis, MN, USA) was used. According to the manufacturer’s instructions, 100 μL of assay diluent RD1-74 was added to each well-plate , then 50 μL tested sera, diluted 1:10 with calibrator diluent RD5-32 (20 μL serum + 180 μL calibrator diluent) or standards was added at various concentrations to construct a calibration curve. After 2 h downtime at room temperature on a shaker, plates were washed three times with 400 μL wash buffer per well. After the last wash 200 μL of conjugate was added to each well and incubated for 2 h at room temperature on a shaker. The plate was washed again three times and in each well 200 μL substrate solution was added. This was incubated for 30 min at room temperature in the dark. The reaction was stopped with 50 μL of stop solution, and the color in the wells changed from blue to yellow. Within 30 min the serum samples were assayed at 450 nm on an automatic micro-ELISA plate reader (Ceres UV 900 C, BioTek Instruments Inc., Winooski, VT, USA) at the Immunological Laboratory of Biology Department of Medical University, Pleven. Indirect ELISA for Determination of MMP-9 To measure MMP-9 an ELISA kit from R and D Systems (cat. No. DMP900) (Minneapolis, MN, USA) was used. According to the manufacturer’s instructions, to each well-plate 100 μL of assay diluent RD1-34 was added, then 100 μL tested sera, diluted 1:100 with calibrator diluent RD5-10 (10 μL serum + 990 μL calibrator diluent), or standards, was added at various concentrations to construct a calibration curve. After 2 h downtime at room temperature on a shaker, plates were washed three times with 400 μL wash buffer per well. After the last wash 200 μL anti-MMP-9 antibody conjugated with peroxidase and was incubated for 1 h at room temperature on a shaker. The plate was washed again three times was added and in each well 200 μL substrate solution was added. This was incubated for 30 min at room temperature in the dark. The reaction was stopped with 50 μL of stop solution, and the color in the wells changed from blue to yellow. Within 30 min the serum samples were assayed at 450 nm on an automatic micro-ELISA plate reader (Ceres UV 900 C, BioTek Instruments Inc., Winooski, VT, USA) at the Immunological Laboratory of Biology Department of Medical University, Pleven. 4.2.2. Biochemical Assays Enzymatic methods were used to measure of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG). C-reactive protein (CRP) and glycated haemoglobin (HbA1c) were measured by a turbidimetric immunoassay. 4.3. Blood Pressure Classification and Measurements 4.3.1. Blood Pressure Classification The definitions of pre-hypertension (PHTN) and hypertension (HTN) were adopted according 2013 European Society of Cardiology (ESC)/ European Society of Hypertension (ESH) Hypertension Guidelines. PHTN, also known as high-normal BP was defined as systolic blood pressure (SBP) between 130 and 139 mmHg and/or diastolic blood pressure (DBP) between 85 and 89 mmHg. HTN was defined as SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg, or if the patients have been diagnosed or had taken antihypertensive drugs at any time during the preceding six months. Normal BP was defined as SBP between 120 and 129 mmHg and/or DBP between 80 and 84 mmHg. 4.3.2. Blood Pressure Measurements BP was measured using a standard cuff mercury sphygmomanometer on the left arm in a sitting position, after 5–10 min rest. All patients and control persons were subjected of three BP measurements. The average of the last two of three consecutive measurements was considered as the baseline BP. 4.4. Physical Measurements Body mass index (BMI) was calculated, using the standard metric BMI formula (kg/m2). BMI between 18.5 and 24.9 was considered normal, 25 to 29.9 was considered overweight, and equal to or higher than 30 was considered obese. 4.5. Statistical Methods Statgraphics Centurion XVI software (Statpoint Technologies, Inc., Warrenton, VA, USA) was used for statistical analyses. The significance of the differences between groups was assessed by Fisher’s F-test (ANOVA). The data are represented as means ± SD and p < 0.05 was considered statistically significant. 5. Conclusions Hypertension is present in a high proportion of patients with T2D and enhances the risk of cardiovascular disease. Our results support a possible pathogenetic role of ET-1 in hypertension associated with T2D. We showed that increased serum concentrations of ET-1 in patients with T2D may assist clinical manifestation of hypertension. Endothelin receptor antagonists (ERAs) are a promising new and innovative drug class, which may have a particular role in the treatment of hypertension as part of the metabolic syndrome or T2D. We also demonstrated that increased concentrations of MMP-2 and MMP-9 in pre-hypertensive and hypertensive patients with T2D may indicate early changes in vascular ECM turnover which, over time, leads to the increase in arterial stiffness. Although, our findings should be confirmed in a larger prospective study, they have an important clinical implication, since it allows making an early assessment of patients with increased cardiovascular risk and allowing the earliest possible start of antihypertensive treatment, when the vascular remodeling process is still reversible. Further research is needed to investigate how glycemic control and antihypertensive drug therapy can affect concentrations of ET-1, MMP-2, MMP-9, and TIMPs, and what the relationship is of these molecules with the pathogenesis of hypertension in T2D. Acknowledgments This work was supported by Medical University of Pleven, Grant No. 7/2013. Author Contributions Krasimir Kostov conceived and designed of the study, data analysis and interpretation, wrote the paper; Alexander Blazhev, Milena Atanasova and Anelia Dimitrova contributed reagents/materials/analysis tools. Conflicts of Interest The authors declare no conflict of interest. Abbreviations BP Blood pressure SBP Systolic blood pressure DBP Diastolic blood pressure T2D Type 2 diabetes ET-1 Endothelin-1 Ang II Angiotensin II MMP-2 Matrix metalloproteinase-2 MMP-9 Matrix metalloproteinase-9 MMPs Matrix metalloproteinases TIMPs Tissue inhibitors of MMPs VSMCs Vascular smooth muscle cells ECM Extracellular matrix PHTN Pre-hypertension group HTN Hypertension group N Normotensive controls ROS Reactive oxygen species NF-kB Nuclear factor-kappa B TNF-α Tumor necrosis factor-alpha IL-1 Interleukin-1 IL-6 Interleukin-6 IL-8 Interleukin-8 Figure 1 Serum concentrations of Endothelin-1 (ET-1) in pre-hypertensive (PHTN)/hypertensive (HTN) patients with T2D and healthy normotensive controls (N). Figure 2 Serum concentrations of MMP-2 in PHTN, HTN, and N. Figure 3 Serum concentrations of MMP-9 in PHTN, HTN, and N. ijms-17-01182-t001_Table 1Table 1 Clinical characteristics of the groups in whole study population. Variables All Groups (n = 60) N PHTN HTN (n = 20) (n = 20) (n = 20) Men, n (%) 9 (45.0) 7 (35.0) 8 (40.0) Women, n (%) 11 (55.0) 13 (65.0) 12 (60.0) Mean age, years 1 35.4 (19.0–56.0) 60.2 (46.0–79.0) 66.9 (45.0–89.0) Duration of T2D 1 N/A 2 9.8 (1.0–34.0) 12.1 (2.0–22.0) HbA1c (%) 1 N/A 7.0 (5.4–13.3) 8.0 (5.3–11.4) BMI, kg/m2 1 25.0 (22.0–28.0) 28.7 (24.0–35.0) 28.0 (24.0–34.0) SBP, mmHg 1 119.0 (95.0–125.0) 136.6 (130.0–140.0) 156.7 (150.0–185.0) DBP, mmHg 1 80.5 (70.0–85.0) 79.5 (70.0–90.0) 87.0 (75.0–100.0) TC, mmol/L 1 3.9 (3.5–4.2) 5.3 (4.0–8.1) 5.2 (3.1–9.5) LDL–C, mmol/L 1 2.5 (1.8–3.0) 3.3 (1.6–6.5) 3.0 (1.3–4.8) HDL–C, mmol/L 1 1.2 (1.0–1.5) 0.9 (0.5–1.5) 0.9 (0.4–1.6) TG, mmol/L 1 1.3 (1.2–1.5) 2.5 (1.3–4.8) 2.0 (1.0–4.0) CRP, mg/L 1 1.1 (0.3–3.5) 8.0 (0.7–23.3) 8.3 (1.0–23.9) 1 Mean (range); 2 N/A, not available. ==== Refs References 1. Meyers K.E. Sethna C. Endothelin antagonists in hypertension and kidney disease Pediat. Nephrol. 2013 28 711 720 10.1007/s00467-012-2316-4 23070275 2. Rodríguez-Pascual F. Busnadiego O. Lagares D. Lamas S. Role of endothelin in the cardiovascular system Pharmacol. Res. 2011 63 463 472 10.1016/j.phrs.2011.01.014 21296157 3. Del Villar C.P. Alonso C.J.G. Feldstein C.A. Juncos L.A. Romero J.C. Role of endothelin in the pathogenesis of hypertension Mayo Clin. Proc. 2005 80 84 96 10.1016/S0025-6196(11)62963-7 15667034 4. Kohan D.E. Rossi N.F. Inscho E.W. Pollock D.M. Regulation of blood pressure and salt homeostasis by endothelin Physiol. Rev. 2011 91 1 77 10.1152/physrev.00060.2009 21248162 5. Tostes R.C. Fortes Z.B. Callera G.E. Montezano A.C. Touyz R.M. Webb R.C. Carvalho M.H.C. Endothelin, sex and hypertension Clin. Sci. 2008 114 85 97 10.1042/CS20070169 18062774 6. Hynynen M.M. Khalil R.A. The vascular endothelin system in hypertension–recent patents and discoveries Recent Pat. Cardiovasc. Drug Discov. 2006 1 95 10.2174/157489006775244263 17200683 7. Vorobiof G. Blaxall B.C. Bisognano J.D. The future of endothelin–receptor antagonism as treatment for systemic hypertension Curr. Hypertens. Rep. 2006 8 35 44 10.1007/s11906-006-0039-2 16600158 8. Cardillo C. Campia U. Bryant M.B. Panza J.A. Increased activity of endogenous endothelin in patients with type II diabetes mellitus Circulation 2002 106 1783 1787 10.1161/01.CIR.0000032260.01569.64 12356630 9. Dollery C.M. McEwan J.R. Henney A.M. Matrix metalloproteinases and cardiovascular disease Circ. Res. 1995 77 863 868 10.1161/01.RES.77.5.863 7554139 10. Galis Z.S. Khatri J.J. Matrix metalloproteinases in vascular remodeling and atherogenesis the good, the bad, and the ugly Circ. Res. 2002 90 251 262 11861412 11. Dhingra R. Pencina M.J. Schrader P. Wang T.J. Levy D. Pencina K. Vasan R.S. Relations of matrix remodeling biomarkers to blood pressure progression and incidence of hypertension in the community Circulation 2009 119 1101 1107 10.1161/CIRCULATIONAHA.108.821769 19221217 12. Lemarié C.A. Tharaux P.L. Lehoux S. Extracellular matrix alterations in hypertensive vascular remodeling J. Mol. Cell. Cardiol. 2010 48 433 439 10.1016/j.yjmcc.2009.09.018 19837080 13. Friese R.S. Rao F. Khandrika S. Thomas B. Ziegler M.G. Schmid-Schönbein G.W. O’Connor D.T. Matrix metalloproteinases: Discrete elevations in essential hypertension and hypertensive end–stage renal disease Clin. Exp. Hypertens. 2009 31 521 533 10.3109/10641960802668730 19886850 14. Heagerty A.M. Aalkjaer C. Bund S.J. Korsgaard N. Mulvany M.J. Small artery structure in hypertension. Dual processes of remodeling and growth Hypertension 1993 21 391 397 10.1161/01.HYP.21.4.391 8458640 15. Mulvany M.J. Baumbach G.L. Aalkjaer C. Heagerty A.M. Korsgaard N. Schiffrin E.L. Heistad D.D. Vascular remodeling Hypertension 1996 28 505 506 8794840 16. Mulvany M.J. Small artery remodeling and significance in the development of hypertension Physiology 2002 17 105 109 17. Intengan H.D. Schiffrin E.L. Vascular remodeling in hypertension roles of apoptosis, inflammation, and fibrosis Hypertension 2001 38 581 587 10.1161/hy09t1.096249 11566935 18. Raffetto J.D. Khalil R.A. Matrix metalloproteinases and their inhibitors in vascular remodeling and vascular disease Biochem. Pharmacol. 2008 75 346 359 10.1016/j.bcp.2007.07.004 17678629 19. Humphrey J.D. Mechanisms of arterial remodeling in hypertension coupled roles of wall shear and intramural stress Hypertension 2008 52 195 200 10.1161/HYPERTENSIONAHA.107.103440 18541735 20. Bourboulia D. Stetler-Stevenson W.G. Matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs): Positive and negative regulators in tumor cell adhesion Semin. Cancer Biol. 2010 20 161 168 10.1016/j.semcancer.2010.05.002 20470890 21. Jaiswal A. Chhabra A. Malhotra U. Kohli S. Rani V. Comparative analysis of human matrix metalloproteinases: Emerging therapeutic targets in diseases Bioinformation 2011 6 23 30 10.6026/97320630006023 21464841 22. Fernandez-Patron C. Radomski M.W. Davidge S.T. Vascular matrix metalloproteinase-2 cleaves big endothelin-1 yielding a novel vasoconstrictor Circ. Res. 1999 85 906 911 10.1161/01.RES.85.10.906 10559137 23. Derosa G. D’Angelo A. Ciccarelli L. Piccinni M.N. Pricolo F. Salvadeo S. Cicero A.F. Matrix metalloproteinase-2, -9, and tissue inhibitor of metalloproteinase-1 in patients with hypertension Endothelium 2006 13 227 231 10.1080/10623320600780942 16840178 24. Tayebjee M.H. Nadar S.K. MacFadyen R.J. Lip G.Y. Tissue inhibitor of metalloproteinase-1 and matrix metalloproteinase-9 levels in patients with hypertension: Relationship to tissue doppler indices of diastolic relaxation Am. J. Hypertens. 2004 17 770 774 10.1016/S0895-7061(04)00902-1 15363818 25. Wallace S. McEniery C.M. Dakham Z. Pusalkar P. Maki-Petaja K. Ashby M.J. Wilkinson I.B. Matrix metalloproteinase-9 (MMP-9), MMP-2, and serum elastase activity are associated with systolic hypertension and arterial stiffness Arterioscler. Thromb. Vasc. Biol. 2005 25 372 378 15556929 26. Intengan H.D. Schiffrin E.L. Collagen degradation is diminished in mesenteric arteries of spontaneously hypertensive rats after hypertension is established Hypertension 1999 34 329 27. Li–Saw–Hee F.L. Edmunds E. Blann A.D. Beevers D.G. Lip G.Y. Matrix metalloproteinase-9 and tissue inhibitor metalloproteinase-1 levels in essential hypertension: Relationship to left ventricular mass and anti-hypertensive therapy Int. J. Cardiol. 2000 75 43 47 10.1016/S0167-5273(00)00274-6 11054505 28. Zervoudaki A. Economou E. Stefanadis C. Pitsavos C. Tsioufis K. Aggeli C. Toutouzas P. Plasma levels of active extracellular matrix metalloproteinases 2 and 9 in patients with essential hypertension before and after antihypertensive treatment J. Hum. Hypertens. 2003 17 119 124 10.1038/sj.jhh.1001518 12574790 29. Ahmed S.H. Clark L.L. Pennington W.R. Webb C.S. Bonnema D.D. Leonardi A.H. Zile M.R. Matrix metalloproteinases/tissue inhibitors of metalloproteinases: Relationship between changes in proteolytic determinants of matrix composition and structural, functional, and clinical manifestations of hypertensive heart disease Circulation 2006 113 2089 2096 10.1161/CIRCULATIONAHA.105.573865 16636176 30. Martinez M.L. Lopes L.F. Coelho E.B. Nobre F. Rocha J.B. Gerlach R.F. Tanus-Santos J.E. Lercanidipine reduces matrix metalloproteinase-9 activity in patients with hypertension J. Cardiovasc. Pharmacol. 2006 47 117 122 10.1097/01.fjc.0000196241.96759.71 16424795 31. Schieffer B. Bünte C. Witte J. Hoeper K. Böger R.H. Schwedhelm E. Drexler H. Comparative effects of AT1-antagonism and angiotensin-converting enzyme inhibition on markers of inflammation and platelet aggregation in patients with coronary artery disease J. Am. Coll. Cardiol. 2004 44 362 368 10.1016/j.jacc.2004.03.065 15261932 32. Pugliese G. Pricci F. Pugliese F. Mene P. Lenti L. Andreani D. Di U.M. Mechanisms of glucose-enhanced extracellular matrix accumulation in rat glomerular mesangial cells Diabetes 1994 43 478 490 10.2337/diab.43.3.478 8314022 33. Death A.K. Fisher E.J. McGrath K.C. Yue D.K. High glucose alters matrix metalloproteinase expression in two key vascular cells: Potential impact on atherosclerosis in diabetes Atherosclerosis 2003 168 263 269 10.1016/S0021-9150(03)00140-0 12801609 34. Suzuki N. Matsumoto H. Kitada C. Yanagisawa M. Miyauchi T. Masaki T. Fujino M. Immunoreactive endothelin-1 in plasma detected by a sandwich-type enzyme immunoassay J. Cardiovasc. Pharmacol. 1989 13 S151 S152 10.1097/00005344-198900135-00039 2473292 35. Donato A.J. Gano L.B. Eskurza I. Silver A.E. Gates P.E. Jablonski K. Seals D.R. Vascular endothelial dysfunction with aging: Endothelin-1 and endothelial nitric oxide synthase Am. J. Physiol. Heart Circ. Physiol. 2009 297 H425 H432 10.1152/ajpheart.00689.2008 19465546 36. Seals D.R. Jablonski K.L. Donato A.J. Aging and vascular endothelial function in humans Clin. Sci. 2011 120 357 375 10.1042/CS20100476 21244363 37. Maeda S. Tanabe T. Miyauchi T. Otsuki T. Sugawara J. Iemitsu M. Matsuda M. Aerobic exercise training reduces plasma endothelin-1 concentration in older women J. Appl. Physiol. 2003 95 336 341 10.1152/japplphysiol.01016.2002 12611765 38. Barton M. Cosentino F. Brandes R.P. Moreau P. Shaw S. Lüscher T.F. Anatomic heterogeneity of vascular aging role of nitric oxide and endothelin Hypertension 1997 30 817 824 10.1161/01.HYP.30.4.817 9336378 39. Wang M. Zhang J. Telljohann R. Jiang L. Wu J. Monticone R.E. Lakatta E.G. Chronic matrix metalloproteinase inhibition retards age-associated arterial proinflammation and increase in blood pressure Hypertension 2012 60 459 466 10.1161/HYPERTENSIONAHA.112.191270 22689745 40. Schneider J.G. Tilly N. Hierl T. Sommer U. Hamann A. Dugi K. Kasperk C. Elevated plasma endothelin-1 levels in diabetes mellitus Am. J. Hypertens. 2002 15 967 972 10.1016/S0895-7061(02)03060-1 12441216 41. Böhm F. Pernow J. The importance of endothelin-1 for vascular dysfunction in cardiovascular disease Cardiovasc. Res. 2007 76 8 18 10.1016/j.cardiores.2007.06.004 17617392 42. Pernow J. Shemyakin A. Böhm F. New perspectives on endothelin-1 in atherosclerosis and diabetes mellitus Life Sci. 2012 91 507 516 10.1016/j.lfs.2012.03.029 22483688 43. Skalska A.B. Pietrzycka A. Stępniewski M. Correlation of endothelin-1 plasma levels with plasma antioxidant capacity in elderly patients treated for hypertension Clin. Biochem. 2009 42 358 364 10.1016/j.clinbiochem.2008.11.002 19046960 44. Romero M. Jiménez R. Sánchez M. López–Sepúlveda R. Zarzuelo A. Tamargo J. Duarte J. Vascular superoxide production by endothelin-1 requires Src non-receptor protein tyrosine kinase and MAPK activation Atherosclerosis 2010 212 78 85 10.1016/j.atherosclerosis.2010.04.031 20553682 45. Piechota A. Polańczyk A. Gorąca A. Role of endothelin-1 receptor blockers on hemodynamic parameters and oxidative stress Pharmacol. Rep. 2010 62 28 34 10.1016/S1734-1140(10)70240-1 20360613 46. Savoia C. Sada L. Zezza L. Pucci L. Lauri F.M. Befani A. Volpe M. Vascular inflammation and endothelial dysfunction in experimental hypertension Int. J. Hypertens. 2011 281240 10.4061/2011/281240 21915370 47. Ruetten H. Thiemermann C. Endothelin-1 stimulates the biosynthesis of tumour necrosis factor in macrophages: ET-receptors, signal transduction and inhibition by dexamethasone J. Physiol. Pharmacol. 1997 48 675 688 9444616 48. Hofman F.M. Chen P. Jeyaseelan R. Incardona F. Fisher M. Zidovetzki R. Endothelin-1 induces production of the neutrophil chemotactic factor interleukin-8 by human brain-derived endothelial cells Blood 1998 92 3064 3072 9787140 49. Browatzki M. Schmidt J. Kübler W. Kranzhöfer R. Endothelin–1 induces interleukin-6 release via acctivation of the transcription factor NF-κB in human vascular smooth muscle cells Basic Res. Cardiol. 2000 95 98 105 10.1007/s003950050170 10826501 50. Yang L.L. Gros R. Kabir M.G. Sadi A. Gotlieb A.I. Husain M. Stewart D.J. Conditional cardiac overexpression of endothelin-1 induces inflammation and dilated cardiomyopathy in mice Circulation 2004 109 255 261 10.1161/01.CIR.0000105701.98663.D4 14718401 51. Virdis A. Schiffrin E.L. Vascular inflammation: A role in vascular disease in hypertension Curr. Opin. Nephrol. Hypertens. 2003 12 181 187 10.1097/00041552-200303000-00009 12589179 52. Vierhapper H. Wagner O. Nowotny P. Waldhäusl W. Effect of endothelin-1 in man Circulation 1990 81 1415 1418 10.1161/01.CIR.81.4.1415 2180594 53. Schneider M.P. Hilgers K.F. Klingbeil A.U. John S. Veelken R. Schmieder R.E. Plasma endothelin is increased in early essential hypertension Am. J. Hypertens. 2000 13 579 585 10.1016/S0895-7061(99)00260-5 10912738 54. Letizia C. Celi M. Cerci S. Scuro L. Delfini E. Subioli S. D’Erasmo E. High circulating levels of adrenomedullin and endothelin-1 in obesity associated with arterial hypertension Ital. Heart J. Suppl. 2001 2 1011 1015 11675821 55. Vaziri N.D. Roles of oxidative stress and antioxidant therapy in chronic kidney disease and hypertension Curr. Opin. Nephrol. Hypertens. 2004 13 93 99 10.1097/00041552-200401000-00013 15090865 56. Peterson J.R. Sharma R.V. Davisson R.L. Reactive oxygen species in the neuropathogenesis of hypertension Curr. Hypertens. Rep. 2006 8 232 241 10.1007/s11906-006-0056-1 17147922 57. Harrison D.G. Gongora M.C. Oxidative stress and hypertension Med. Clin. N. Am. 2009 93 621 635 10.1016/j.mcna.2009.02.015 19427495 58. Briones A.M. Touyz R.M. Oxidative stress and hypertension: Current concepts Curr. Hypertens. Rep. 2010 12 135 142 10.1007/s11906-010-0100-z 20424957 59. Dong F. Zhang X. Wold L.E. Ren Q. Zhang Z. Ren J. Endothelin-1 enhances oxidative stress, cell proliferation and reduces apoptosis in human umbilical vein endothelial cells: Role of ETB receptor, NADPH oxidase and caveolin-1 Br. J. Pharmacol. 2005 145 323 333 10.1038/sj.bjp.0706193 15765100 60. Duerrschmidt N. Wippich N. Goettsch W. Broemme H.J. Morawietz H. Endothelin-1 induces NAD (P) H oxidase in human endothelial cells Biochem. Biophys. Res. Commun. 2000 269 713 717 10.1006/bbrc.2000.2354 10720482 61. Galle J. Lehmann-Bodem C. Hübner U. Heinloth A. Wanner C. CyA and OxLDL cause endothelial dysfunction in isolated arteries through endothelin-mediated stimulation of O2− formation Nephrol. Dial. Transpl. 2000 15 339 346 10.1093/ndt/15.3.339 62. Loomis E.D. Sullivan J.C. Osmond D.A. Pollock D.M. Pollock J.S. Endothelin mediates superoxide production and vasoconstriction through activation of NADPH oxidase and uncoupled nitric-oxide synthase in the rat aorta J. Pharmacol. Exp. Ther. 2005 315 1058 1064 10.1124/jpet.105.091728 16144972 63. López–Sepúlveda R. Gómez-Guzmán M. Zarzuelo M.J. Romero M. Sánchez M. Quintela A.M. Duarte J. Red wine polyphenols prevent endothelial dysfunction induced by endothelin-1 in rat aorta: Role of NADPH oxidase Clin. Sci. 2011 120 321 333 10.1042/CS20100311 20977430 64. Mohazzab K.M. Kaminski P.M. Wolin M.S. NADH oxidoreductase is a major source of superoxide anion in bovine coronary artery endothelium Am. J. Physiol. Heart Circ. Physiol. 1994 266 H2568 H2572 65. Kamata K. Kanie N. Matsumoto T. Kobayashi T. Endothelin-1-induced impairment of endothelium-dependent relaxation in aortas isolated from controls and diabetic rats J. Cardiovasc. Pharmacol. 2004 44 S186 S190 10.1097/01.fjc.0000166241.49453.e9 15838275 66. Kanie N. Kamata K. Effects of chronic administration of the novel endothelin antagonist J-104132 on endothelial dysfunction in streptozotocin-induced diabetic rat Br. J. Pharmacol. 2002 135 1935 1942 10.1038/sj.bjp.0704659 11959796 67. Camici G.G. Sudano I. Noll G. Tanner F.C. Lüscher T.F. Molecular pathways of aging and hypertension Curr. Opin. Nephrol. Hypertens. 2009 18 134 137 10.1097/MNH.0b013e328326093f 19434051 68. Ergul A. Endothelin–1 and diabetic complications: Focus on the vasculature Pharmacol. Res. 2011 63 477 482 10.1016/j.phrs.2011.01.012 21292003 69. Barton M. Endothelial dysfunction and atherosclerosis: Endothelin receptor antagonists as novel therapeutics Curr. Hypertens. Rep. 2000 2 84 91 10.1007/s11906-000-0064-5 10981133 70. Matsumoto T. Lopes R.A. Taguchi K. Kobayashi T. Tostes R.C. Linking the beneficial effects of current therapeutic approaches in diabetes to the vascular endothelin system Life Sci. 2014 118 129 135 10.1016/j.lfs.2013.12.216 24418002 71. Derosa G. D’angelo A. Tinelli C. Devangelio E. Consoli A. Miccoli R. Cicero A.F.G. Evaluation of metalloproteinase 2 and 9 levels and their inhibitors in diabetic and healthy subjects Diabetes Metab. 2007 33 129 134 10.1016/j.diabet.2006.11.008 17320450 72. Ebihara I. Nakamura T. Shimada N. Koide H. Increased plasma metalloproteinase-9 concentrations precede development of microalbuminuria in non-insulin-dependent diabetes mellitus Am. J. Kidney Dis. 1998 32 544 550 10.1016/S0272-6386(98)70015-0 9774113 73. Giebel S.J. Menicucci G. McGuire P.G. Das A. Matrix metalloproteinases in early diabetic retinopathy and their role in alteration of the blood-retinal barrier Lab. Investig. 2005 85 597 607 10.1038/labinvest.3700251 15711567 74. Santo Signorelli S. Malaponte G. Libra M. Di Pino L. Celotta G. Bevelacqua V. Pennisi G. Plasma levels and zymographic activities of matrix metalloproteinases 2 and 9 in type II diabetics with peripheral arterial disease Vasc. Med. 2005 10 1 6 10.1191/1358863x05vm582oa 15920993 75. Jackson Z.S. Gotlieb A.I. Langille B.L. Wall tissue remodeling regulates longitudinal tension in arteries Circ. Res. 2002 90 918 925 10.1161/01.RES.0000016481.87703.CC 11988494 76. Flamant M. Placier S. Dubroca C. Esposito B. Lopes I. Chatziantoniou C. Lehoux S. Role of matrix metalloproteinases in early hypertensive vascular remodeling Hypertension 2007 50 212 218 10.1161/HYPERTENSIONAHA.107.089631 17515450 77. Watts S.W. Rondelli C. Thakali K. Li X. Uhal B. Pervaiz M.H. Fink G.D. Morphological and biochemical characterization of remodeling in aorta and vena cava of DOCA-salt hypertensive rats Am. J. Physiol Heart Circ. Physiol. 2007 292 H2438 H2448 10.1152/ajpheart.00900.2006 17237246 78. Kostov K. Dimitrova A. Grigoryan A. Tisheva S. Ruseva A. Atanasova M. Gospodinov K. Blazhev A. Changes in the serum levels of endothelin-1, matrix metalloproteinases-2,-9 and c-reactive protein in patients with mild and severe degree of arterial hypertension Cardiovasc. Res. 2014 67 427 434 79. Lehoux S. Lemarié C.A. Esposito B. Lijnen H.R. Tedgui A. Pressure-induced matrix metalloproteinase-9 contributes to early hypertensive remodeling Circulation 2004 109 1041 1047 10.1161/01.CIR.0000115521.95662.7A 14967734 80. Cipollone F. Iezzi A. Fazia M. Zucchelli M. Pini B. Cuccurullo C. Chiarelli F. The receptor RAGE as a progression factor amplifying arachidonate-dependent inflammatory and proteolytic response in human atherosclerotic plaques: Role of glycemic control Circulation 2003 108 1070 1077 10.1161/01.CIR.0000086014.80477.0D 12912808 81. Wang M. Kim S.H. Monticone R.E. Lakatta E.G. Matrix metalloproteinases promote arterial remodeling in aging, hypertension, and atherosclerosis Hypertension 2015 65 698 703 10.1161/HYPERTENSIONAHA.114.03618 25667214 82. Harvey A. Montezano A.C. Touyz R.M. Vascular biology of ageing-Implications in hypertension J. Mol. Cell. Cardiol. 2015 83 112 121 10.1016/j.yjmcc.2015.04.011 25896391 83. Monk B.A. George S.J. The effect of ageing on vascular smooth muscle cell behavior-a mini-review Gerontology 2014 61 416 426 10.1159/000368576 25471382 84. Duca L. Blaise S. Romier B. Laffargue M. Gayral S. El Btaouri H. Maurice P. Matrix ageing and vascular impacts: Focus on elastin fragmentation Cardiovasc. Res. 2016 110 298 308 10.1093/cvr/cvw061 27009176 85. Zaoui P. Cantin J.F. Alimardani–Bessette M. Monier F. Halimi S. Morel F. Cordonnier D. Role of metalloproteases and inhibitors in the occurrence and progression of diabetic renal lesions Diabetes Metab. 2000 26 25 29 10922970

PMC005xxxxxx/PMC5000591.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081193ijms-17-01193ArticleAccumulation and Toxicity of Superparamagnetic Iron Oxide Nanoparticles in Cells and Experimental Animals Jarockyte Greta 1Daugelaite Egle 1Stasys Marius 1Statkute Urte 1Poderys Vilius 1Tseng Ting-Chen 2Hsu Shan-Hui 2Karabanovas Vitalijus 13Rotomskis Ricardas 14*Sivakov Vladimir Academic Editor1 Biomedical Physics Laboratory of National Cancer Institute, Baublio 3B, LT08406 Vilnius, Lithuania; greta.jarockyte@nvi.lt (G.J.); e.daugelaite@gmail.com (E.D.); marius.stalnionis@nvi.lt (M.S.); urtestatkute@gmail.com (U.S.); vilius.poderys@nvi.lt (V.P.); vitaliljus.karabanovas@vgtu.lt (V.K.)2 Institute of Polymer Science and Engineering, National Taiwan University, No. 1, Roosevelt Road Sec. 4, Taipei 10617, Taiwan; bbam1986@hotmail.com (T.-C.T.); shhsu@ntu.edu.tw (S.-H.H.)3 Department of Chemistry and Bioengineering, Vilnius Gediminas Technical University, LT-10223 Vilnius, Lithuania4 Biophotonics group of Laser Research Centre, Vilnius University, Sauletekio 9, c.3, LT-10222 Vilnius, Lithuania* Correspondence: ricardas.rotomskis@nvi.lt; Tel.: +370-5-2190-90819 8 2016 8 2016 17 8 119328 5 2016 18 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).The uptake and distribution of negatively charged superparamagnetic iron oxide (Fe3O4) nanoparticles (SPIONs) in mouse embryonic fibroblasts NIH3T3, and magnetic resonance imaging (MRI) signal influenced by SPIONs injected into experimental animals, were visualized and investigated. Cellular uptake and distribution of the SPIONs in NIH3T3 after staining with Prussian Blue were investigated by a bright-field microscope equipped with digital color camera. SPIONs were localized in vesicles, mostly placed near the nucleus. Toxicity of SPION nanoparticles tested with cell viability assay (XTT) was estimated. The viability of NIH3T3 cells remains approximately 95% within 3–24 h of incubation, and only a slight decrease of viability was observed after 48 h of incubation. MRI studies on Wistar rats using a clinical 1.5 T MRI scanner were showing that SPIONs give a negative contrast in the MRI. The dynamic MRI measurements of the SPION clearance from the injection site shows that SPIONs slowly disappear from injection sites and only a low concentration of nanoparticles was completely eliminated within three weeks. No functionalized SPIONs accumulate in cells by endocytic mechanism, none accumulate in the nucleus, and none are toxic at a desirable concentration. Therefore, they could be used as a dual imaging agent: as contrast agents for MRI and for traditional optical biopsy by using Prussian Blue staining. magnetic nanoparticlesSPIONsiron oxidecellular uptakeMRI-optical dual imagingoptical biopsy of tissues cellsmultifunctional cancer diagnostics ==== Body 1. Introduction Since the first contrast medium for magnetic resonance imaging (MRI) was developed [1,2,3], researchers have kept looking for advanced materials and synthesis methods that could be applied in MRI. MRI is an important tool in medicine, offering detailed spatial resolution and soft tissue contrast without the use of ionizing radiation or potentially harmful radiotracers [4,5]. MRI is a well-established but still growing in availability non-ionizing method of tomographic imaging for diagnostics of various diseases including oncological pathologies [6]. At the moment, there are two main compounds used. Iron oxide based agents that provide “negative” contrast in images and gadolinium based agents that account for the “positive” contrast. “Negative” contrast agents are known for creating strong local magnetic field inhomogeneity that influence bypassing water molecules and induce their rapid T2 and T2* relaxations, which appear as a signal loss in MR images of lesions corresponding to iron oxide accumulation [7,8]. The development of nanoparticles for use in biomedicine has shown great progress over the past two decades, and has been tailored for use as contrast enhancement agents for imaging. Magnetic nanoparticles (MNPs), with their unique magnetic properties and controllable sizes, are being actively investigated as the next generation of magnetic resonance imaging contrast agents. MNPs possess useful properties for a variety of life sciences-related applications, comprising both basic and clinical research [9,10]. A class of nanocompounds that can be manipulated using a magnetic field has been tailored for use as enhancement agents for imaging, drug delivery vehicles, and, most recently, as a therapeutic component in initiating tumor cell death in magnetic and photonic ablation therapies [11]. Iron oxide MNPs with nanocrystaline magnetite (Fe3O4) cores have great potential for use in oncology due to their biocompatibility, biodegradability, facile synthesis, and ease with which they may be tuned and functionalized for specific application [10]. Spherical iron oxide MNPs will exhibit supermagnetic behavior (a property that is exploited to enhance contrast in MRI). Typically, supermagnetic iron oxide nanoparticle (SPION) conjugates are comprised of a magnetite core providing inherent contrast for MRI and a biocompatible coating that provides ample functional groups for conjugation of additional tumor targeting and therapeutic moieties. SPIONs provide negative (hypointense) contrast by darkening T2 and T2*-weighted images in regions of interest (ROIs) corresponding to uptake areas of SPIONs. Ferrous or ferric oxide is the main constituent of magnetic particles, although metals such as cobalt and nickel are used in other fields of application. While SPIONs have historically been used primarily for negative contrast enhancement by darkening T2*-weighted images, they may also be customized to provide positive contrast enhancement in T1-weighted scans [12,13]. Nanoparticles with gadolinium (Gd) complexes are known in MR imaging T1 contrast material, although their sensitivity is relatively low [2]. In addition, the side effects related to Gd, especially in patients with kidney problems, demand the development of more superior, safer substances [14,15]. There are overall desirable features of a “perfect” contrast agent that are still not achieved yet and comprised of: easy administration, nontoxicity, stability of a compound, selectivity, sensitivity, quick elimination from the body after the imaging is complete, minimal to no side effects, and cost-effectiveness. SPIONs offer an advantage over Gd-based agents due to both being nontoxic and superior in providing T1 contrast. For instance, a SPION formulation has been developed exhibiting a twofold improvement of T1 contrast enhancement as compared to a commercial Gd-based clinical standard [13]. Different studies have reported from very small to no toxicity of iron oxide nanoparticles [16,17]. SPIONs have some specific properties such as superparamagnetism, high field irreversibility, high saturation field, extra anisotropy contributions or shifted loops after field cooling [18]. Due to these properties, the particles no longer show magnetic interaction after the external magnetic field is removed. Progress in the field of nanotechnology has led to selective tumor markers, connecting to a variety of complex organic polymers and biomolecules [19,20]. MR contrast agents that are composed of the SPION core can be modified with organic substances (Dextran, PEG) to improve their stability in aqueous solutions and add efficiency to the delivery of the nanoparticles to the tumor site [21]. MNPs can also be used for cancer therapy: hyperthermia therapy and anticancer drug delivery. These two methods could be combined: hyperthermia-based drug delivery is therapy in which an anticancer drug is delivered to the tumor by an external magnetic field, and the drug molecule is then released due to heating [22]. Some formulations of magnetite-based NPs have already gained approval for use in humans as iron deficiency therapeutics and as MRI contrast agents by the Food and Drug Administration (FDA) (e.g., FerahemeR (AMAG Pharmaceuticals, Waltham, MA, USA), Feridex I.V.R (AMAG Pharmaceuticals), and GastromarkR (AMAG Pharmaceuticals)) [11]. Up to this date, iron oxide nanoparticles have been approved for clinical use as liver imaging agents [9]. Various SPIONs were investigated as new MRI contrast agent last decay. For about two decades, MNPs have been used as FDA-approved contrast agents (Dextran-coated EndoremR (Guerbet, Paris, France), Feridex I.V.R) [21] in MRI for the detection of liver pathologies [23]. Recently, a novel formulation of SPIONs coated with a carboxylated shell (FerumoxytolR (AMAG Pharmaceuticals)) has been FDA approved for the treatment of iron deficiency anemia in adults with chronic kidney disease [23]. A wide variety of MNPs are being tested for the in vitro labeling of cultured stem cells and their subsequent in vivo tracking by MRI after transplantation. Several of them are undergoing clinical trials [24,25]. However, the translation of these NP formulations to use in medical clinic fails at a very high rate as can be corroborated with the relative dearth of NPs employed for use in humans [26,27]. Specifically for iron oxide NPs, only a handful of formulations have been approved by FDA, and even the most recent magnetite-based NP to be approved, FerahemeR, does not have intended use as an MRI agent or cancer therapeutic [28]. Other iron oxide NP formulations, although approved by the FDA, have stopped being marketed by their manufacturers (e.g., FeridexI.V.R, and GastromarkR) [11]. Currently, no functionalized SPIONs are used in humans. Nevertheless, despite the obvious impact on MR images, the adverse effect of contrast and artifacts from the magnetization are also factors in determining SPION contrast deficiencies. The darkening of MR images resulting due to SPIONs accumulation in tissue may confuse the clinical diagnosis, judging by the T2 MRI signal. This signal can often be confused with the signal that distinguishes bleeding from the place of metal calcium, derivatives or residues [29]. This indicates that there is still a need for investigation of SPIONs to gather more knowledge about mechanism of their accumulation and biodistribution in cell cultures and in vivo, and revitalization of characteristic appearance on preclinical MRI images [30]. There are not any precise investigations in which the same SPIONs would be used for experiments with cells and continuing on animals. Lack of information of loading capacity and of control over the biodistribution of SPIONs, insufficient evidence about distribution and clearance from the injection site, and migration in the tissue of experimental animals are the major issues holding back their clinical translation. In this study, we aimed to investigate the accumulation of SPION nanoparticles in embryonic fibroblasts of mice (NIH3T3), their effect on proliferation and viability of cells, to examine the MRI signal intensity versus the SPION concentration, and to evaluate MR signal of SPION injection sites in Wistar rats. For iron visualization in cells and tissues with optical microscopy, Prussian Blue Cell Staining was used. MNP accumulation in experimental animals was visualized by the MRI method. Even though SPIONs were specifically developed for use as MRI contrast agents, recent efforts have been made to incorporate additional possibilities to enable complementary imaging modalities. MRI has exceptional spatial resolution but lacks sensitivity. Optical imaging is relatively inexpensive and very sensitive but cannot penetrate deep into all tissues due to the attenuation and to scattering of light. Thus, in the study, we are presenting the evidence of combinations of these imaging modalities providing the anatomical resolution (MRI) and molecular sensitivity (Prussian Blue Cell Staining) needed for accurate diagnoses. 2. Results 2.1. Characterization of Nanoparticles Fe3O4 nanoparticles (NPs) (Figure 1D) were prepared by chemical co-precipitation. After formation of Fe3O4 NPs, NPs were washed by centrifugation and re-dispersion in distilled water for three times. Sodium oleate (1.5 g dissolved in 50 mL distilled water) was added to the Fe3O4 NPs under vigorous stirring for 30 min, and the excess surfactant was removed by dialysis so there was no free surfactant. Topographic atomic force microscopy (AFM) images of Fe3O4 nanoparticles are shown in Figure 1B. On the surface of mica, single particles similar in size can be seen. There are no aggregates of particles on the surface. AFM measurements showed that height of Fe3O4 nanoparticles varies from 10 to 50 nm. Particle height distribution obtained from AFM measurements (Figure 1A) reaches a maximum at 15–20 nm. Hydrodynamic size measurements revealed that the diameter of particles in solution is approximately 50 nm (Figure 1C). As it should be expected, measured hydrodynamic radius is slightly larger than the diameter of nanoparticles measured with AFM. Hydrodynamic diameter shows the diameter of the inorganic core with coating material and the layer of solvent attached to the particle as it moves under the influence of Brownian motion. While estimating size by AFM, the hydration layer is not present; hence, only information only about the inorganic core is obtained. However, results obtained by both techniques are in a good agreement. Zeta potential of magnetic nanoparticles in prepared solutions is about −34.34 ± 1.12 mV. This indicates that solution of nanoparticles should be colloidally stable. Solution is considered colloidally stable when zeta potential is less than −30 mV or more than 30 mV [31]. Fe3O4 nanoparticles from different batches had a similar size range. The average zeta potential was in the range from −50 to −35 mV. 2.2. Accumulation and Toxicity of Nanoparticles in Live Cells Accumulation and biological effects of Fe3O4 nanoparticles were investigated. An accumulation of particles depends on incubating time. After incubating cells with magnetic nanoparticles for less than 6 h, almost no intracellular accumulation was observed (Figure 2A,B). There were only several cells, which were able to internalize nanoparticles during six hours of incubation, and particles are accumulated through the whole cytosol (Figure 2C). There also were not nanoparticles adherent to cytoplasmic membrane. These results show that Fe3O4 nanoparticles do not have a strong affinity to plasma membrane. During short incubation times, nanoparticles could be attached to the membrane of the cells, but these nanoparticles were easily washed out before imaging. In comparison with quantum dots, which accumulate in cell membrane structures after 30–60 min of incubations [32], there are not any magnetic nanoparticles adhered to the plasma membrane after the same time of incubation (Figure 2A,B). After longer times of incubation, particles were observed in all cells, localized in the perinuclear region (Figure 2D–F). Due to SPION coatings and relatively large size of whole nanoparticles, the membrane of the cell needs more time to initiate the process of endocytosis. Magnetic nanoparticles have not accumulated in the nucleus of cells. The same results are obtained after NIH3T3 was incubated with quantum dots for 24 h [32]. After 48 or more hours of incubations, a few new structures (large vesicles, blebs or lipid droplets) were observed in the perinuclear region (Figure 2E,F) According to the literature, magnetic nanoparticles might induce formation of lipid droplets [33]. Morphological changes of cells require investigation of the viability of cells after incubations with Fe3O4 nanoparticles. For assessing cell viability, cells were incubated with two different concentrations of magnetic nanoparticles. No cytotoxicity was observed when cells were incubated with SPIONs for 3 h and 24 h: cell viability remains approximately 95% (Figure 3A). However, a slight decrease of viability was observed after 48 h of incubation. XTT is an indirect method of viability investigation, meaning that, after 48 h of incubation, it decreases the rate of mitochondrial activity. In Figure 3B is shown XTT plate images of NIH3T3 cells after incubation with nanoparticles. 2.3. MR Signal Intensity versus the Fe3O4 Concentration T2-weighted magnetic resonance (T2W MR) coronal slice images of different concentrations of Fe3O4 nanoparticles water solutions are shown in Figure 4A. The MR signal intensity versus the different concentrations in solutions of Fe3O4 are shown in Figure 4B. As shown in Figure 4, a negative enhancement for MR signal was observed for all the tubes when compared to water (dotted line). Starting from the lowest concentration, the reduction of MRI signal was increasing corresponding to the increase of the SPION concentration up to 25 mg/L. At the concentration of 25 mg/L (c3) or higher no MRI signal could be observed at all (absolute suppression). Therefore, it can be concluded that the concentration below 25 mg/L would be enough to provide the “negative” T2 contrast in MR imaging. 2.4. The Migration of SPIONs from the Injection Site T2W MR coronal images of the injection site at the different time moments after intramuscular injection of 520 µg Fe3O4/kg (high dose) in the rat left hind paw (red circles) shown in Figure 5. As shown in Figure 5A, a negative enhancement for MR signal at the injection site was observed in all of the images (black areas in red circles) compared with the control image. The decrease over time was observed, implicating that Fe3O4 nanoparticles were slowly cleared from the injection site. Although, at high doses, even at two months, the Fe3O4 nanoparticles have not been completely eliminated from the injection site. However, after the injection of the low dose of nanoparticles (20.8 µg Fe3O4/kg), SPIONs were fully cleared from the injection site within three weeks (Figure 5B). Figure 6 shows relative MR signal intensity versus time at the injection site (Figure 5, red circles) with different doses of Fe3O4. In the case of low dose injection, the signal intensity by the third week after the injection was equal to control signal intensity (Figure 6, black curve), thus indicating that the low concentration SPIONs were fully metabolized from the injection site. It has been reported and cannot be ignored that exposure to SPION has been associated with significant toxic effects such as inflammation or infection [34,35]. 3. Discussion Lately, SPIONs have been attracting attention as new and perspective MRI contrast agents and anticancer drug carriers. However, there are not any precise investigations of accumulation of SPIONs in cells. Most of the evidence of SPION accumulation in cells is electron microscopy and phase contrast images in which only black dots could be observed. However, it is incorrect to state that these black dots are MNPs because they could be lipid droplets, which are induced after incubating cells with magnetic nanoparticles [33]. Moreover, phase contrast images do not give information about MNPs localization in cells because images of MNPs strongly depend on the focal plane. When the focal plane is changed, black dots, which we assumed were MNPs, became white bubbles, which look like vesicles. In our investigation, we used iron staining, which is used for histological samples to detect the presence of iron in biopsy specimens, such as in bone marrow samples [36]. Confocal fluorescence images taken after incubation of the cells with quantum dots show evolution of the distribution pattern and transport vesicles of carboxyl-coated quantum dots in the cells: phase 1—adherence to the cell membrane; phase 2–formation of granulated clusters spreading in the cytoplasm; phase 3—localization of granulated clusters in the perinuclear region; and phase 4—formation of multivesicular body-like structures and their redistribution in the cytoplasm [32]. In comparison with quantum dots, which accumulate in cell membrane structures after phase 1, there are not any magnetic nanoparticles adhered to plasma membrane at any time during incubation (Figure 2A,B). These results show that SPIONs do not have affinity to plasma membrane of the cells. The granulated pattern of the Prussian Blue absorption in NIH3T3 cells after incubation, indicates that the SPIONs were trapped in vesicular structures. They localized in the perinuclear region, and no SPIONs were detected in the nucleus of the cell. Zhu et al. used Prussian Blue staining to detect SPIONs in mammalian cells; however, they did not analyze the localization of SPIONs in cells [37]. The viabilities of NIH3T3 cells indicate good biocompatibility of SPIONs for potential in vivo imaging. These results coincide with previously reported others investigations of toxicity of SPIONs in different cell lines [38]. SPIONs show significant signal reduction with increasing of SPION concentration in the T2-weighted MRI. Similar results were also reported in [39,40]. Although the in vitro dispersion behavior and imaging performance of nanoparticles are different from those in vivo MRI, the brightening of the image spots of the nanoparticles from the injection site through time indicates an excretion, even though, when it comes to relatively large concentrations of the SPIONs, a rather slow excretion from the injection site is observed. The migration of SPIONs from the injection site was investigated by analyzing T2*W MR coronal slice images at different time moments after intramuscular injection (Figure 5 and Figure 6). When concentration of injected SPIONs solution was high (650 mg/L), only a slow removal of nanoparticles from the injection site was observed. However, the lower concentration (26 mg/L) of nanoparticles was completely eliminated from the injection site within three weeks. The former can be attributed to the aggregations of nanoparticles in vivo and could cause false positive findings because of the artifacts; this study suggests the potential of such Fe3O4 nanoparticles as an effective T2-weighted MRI contrast agents for tumor diagnosis. At the moment, there are still obstacles to overcome until the SPIONs find their niche in the algorithm of clinical routine. We still need to investigate the better biodistribution and excretion pathways of the nanoparticles, as well as to determine the optimal ways of synthesis to achieve a specific purpose. In addition, the experiments in cells and in animals to this date have not yet been shown to translate well from one technique to another. However, this is very important, when thinking about the clinical application of the SPIONs. Adding the staining method of iron used in this study turns SPIONs into dual imaging tracers, for visualization by the means of MRI and optical imaging without the requirement for invasive methods. In contrast to MRI, optical imaging methods such as Prussian Blue staining have relatively good sensitivity but suffer from low tissue penetration depths. Various nanomaterials such as quantum dots (QDs) and SPIONs have been developed for biomedical applications. QDs for example have good photoemission and photostability characteristics. However, QDs, just like Gaddolinium, have been shown to have cytotoxic effects. Each imaging modality has its own advantages and disadvantages. By combining different modalities of imaging methods can compensate for the disadvantages of a single imaging modality. Another already mentioned problem is that there are not any papers about investigations of the same SPIONs both in cells and in animals. Our work was a continuous study of SPIONs’ physical properties, accumulation in cells, and biological effect for cells, in addition to measurements of MRI signals of SPIONs in vitro and in vivo. Furthermore, better theoretical in vitro and animal models will help to predict the optimal MNP formulations for humans. As our understanding of MNP behavior in the biological environment improves, we are optimistic that integrated MR and optical imaging with SPIONs will push forward the clinical use of SPIONs. 4. Materials and Methods 4.1. Synthesis of Fe3O4 Nanoparticles Fe3O4 nanoparticles were synthesized according to previously reported procedure [36]. In addition, 8.95 g FeCl2·4H2O and 18.25 g FeCl3·6H2O were mixed and dissolved in 150 mL distilled water. The solution was stirred while 50 mL of NaOH were slowly added. Solution was stirring until its color changed from light brown to black. Fe3O4 nanoparticles were washed by centrifugation and redispersed in distilled water three times. Then, 1.5 g sodium oleate was dissolved in 50 mL distilled water and added to the Fe3O4 nanoparticles under vigorous stirring for 30 min. The excess surfactant was removed by dialysis. The dialysis membranes with MWCO 3500 (Spectrum Laboratories, Inc., Rancho Dominguez, CA, USA) to dialyze the NPs were used, and, in principle, all unbound surfactant molecules would be removed. 4.2. Characterization of Nanoparticles Fe3O4 NPs were analyzed for phase composition by the X-ray powder diffraction over the 2q range from 20 to 70° at a rate of 1.5°/min, using Cu-Ka radiation. The morphology and size distribution of the Fe3O4 NPs were observed by a transmission electron microscope (TEM, JEOL, Tokyo, Japan). A Fourier-Transform infrared spectrometer (FT-IR; Perkin Elmer, Waltham, MA, USA) was used to analyze the surface composition of the NPs. The zeta potential of Fe3O4 NPs was measured by light scattering using the Delsa™ Nano Zeta Potential and Submicron Particle Size Analyzer (Beckman Coulter, Brea, CA, USA). The weight loss of the dried sample was monitored under N2 from 100 to 800 °C at a heating rate of 10 °C/min by a thermogravimetric analyzer (Perkin Elmer). For AFM measurements, 20 µL of Fe3O4 nanoparticle solution was put on freshly cleaved mica. After 30 s, drops were removed from the surface of mica by spinning the sample (spin drying). AFM measurements were performed using AFM Innova (Veeco Inc., Plainview, NY, USA) in tapping mode. RTESP7 probes (tip radius < 10 nm) were used. Hydrodynamic particle diameter and zeta potential measurements were performed using particle size and zeta potential analyser ZetaPALS (Brookhaven Instruments Inc., Holtsville, NY, USA). 4.3. Cell Culturing Immortalized mouse embryonic fibroblast cell line NIH3T3 was purchased from American Type Culture Collection. Cells were cultured in cell growth medium (DMEM; Gibco, Waltham, MA, USA), supplemented with 10% (v/v) fetal bovine serum (FBS) (Gibco), 100 U/mL penicillin and 100 mg/mL streptomycin. Cells were maintained at 37 °C in a humidified atmosphere containing 5% of CO2. The cells were routinely subcultured 2–3 times a week in 25 cm2 culture dishes. 4.4. Treatment of Cells with Nanoparticles For intracellular imaging studies, cells were seeded into an 8-chambered cover glass plate (Nalge Nunc International, Rochester, NY, USA) with a density of 3 × 104 cells/chamber and subsequently incubated at 37 °C in a humidified atmosphere containing 5% of CO2 for 24 h. For the Fe3O4 uptake dynamics and intracellular localization evaluation, cells were treated with 65 ng/mL of Fe3O4 nanoparticles and incubated for the next 1, 6, 24, 48 or 72 h. Before imaging of nanoparticles, cells were fixed. After removing the growth media with nanoparticles, cells were washed 3 times with 7.4 pH phosphate buffered saline (PBS) (Gibco) adding 200 µL to each well. Cells were fixed by treating them for 15 minutes with sufficient amount of 4% paraformaldehyde (Sigma-Aldrich, St. Louis, MO, USA). Then, the cells were washed again with PBS three times. 4.5. Visualization and Imaging of Fe3O4 in Cells For iron visualization, a Prussian Blue Cell Staining Reagent Pack (Sigma-Aldrich) was used. It consists of two reagents: hydrochloric acid and potassium ferrocyanide. Equal amounts of both reagents were mixed together and added to each well with cells. Fixed cells were treated with working solution for 15 min. During the reaction, any ferric ion present in the cells combines with the ferrocyanide and results in the formation of a bright blue pigment called Prussian blue, or ferric ferrocyanide. Then, the working solution was aspirated and the fixed cells were washed with PBS. The accumulation of nanoparticles in cells was observed using Nikon Eclipse TE2000 (Nikon, Tokyo, Japan) bright-field microscope equipped with a digital color camera Leica DFC290. To gain a better insight on cell structure, we also used differential interference contrast method (DIC). 4.6. Cytotoxicity Measurements XTT cell viability assay was done to analyze toxicity of SPIONs. It is based on the measurement of mitochondrial enzymes activity in viable cells that reduce XTT, which is a tetrazolium derivative. XTT reduction is proportional to the number of viable cells in the sample and can be photometrically quantified at 490 nm [34]. The cells were seeded on a 96-wellplate (BD Falcon, San Jose, CA, USA) at a density of 1.5 × 104 cells/well and incubated for 24 h before the nanoparticles were applied. The old medium was replaced with fresh medium containing nanoparticles, while media alone without nanoparticles was a control. After treatment, the old medium with nanoparticles was carefully aspirated and the cells were washed three times with DPBS (pH 7.0) (Sigma-Aldrich) before 100 μL of growth media were added to each well. To prepare a reaction solution sufficient for one plate (96 wells), 0.1 mL activation solution (N-methyl dibenzopyrazine methyl sulfate) (Biological Industries, Kibbutz Beit-Haemek, Israel) and 5 mL XTT reagent (Biological Industries) were mixed. Then, 50 μL of the reaction solution were added to each well and the plate was incubated in an incubator at 37 °C. After another 4 h of incubation, optical density values at 490 nm were measured using the microplate reader (BioTek, Winooski, VT, USA). After obtaining values of absorbance, they were recalculated as percentage values of viability. Absorbance value of control group was equated to 100% and the rest of the values were calculated proportionally to control. 4.7. MR Imaging In vitro. All MR imaging examinations were performed by using a clinical 1.5 T MR scanner (Philips Achieva, Philips Medical Systems, Best, The Netherlands) with a Sense Flex-M coil (Philips Medical Systems). SPION aqueous solutions were placed in a series of 2 mL plastic Eppendorf test tubes (Sigma-Aldrich) with concentrations varying from 1300 to 0.13 mg/L for imaging. Tubes containing the SPION solutions were arrayed in order of concentration and tube containing water was placed as control. The MR images in vitro were acquired using T2-weighted turbo spin-echo (T2W-TSE) imaging sequence with the following parameters: scanning plane—coronal, repetition time (TR) 1800 ms, echo time (TE)—60 ms, matrix size—256 × 256; field of view (FOV)—150 × 150 mm, slice thickness—2.0 mm, number of acquisitions (NSA)—6. Acquired images were analyzed in order to examine the MR signal intensity (SI) versus the Fe3O4 concentration. Quantitative MR imaging analysis was performed and MR SI values were measured by drawing regions of interest (ROIs) of 57 mm2 over test tubes sliced images using Siemens Syngo workstation’s MI Apps software (Software version: 8.5.10.10 SP3; Siemens Healthcare GmbH, Erlangen, Germany) and calculated in relative units. In vivo. MRI in vivo examinations were performed by using the same equipment as for in vitro studies. In imaging in vivo experiments, anesthesia is necessary in order to ensure the constant restraint of the animals. The animals were anesthetized with an intramuscular injection of 0.1 mL of ketamine hydrochloride per 100 g of body weight. During the MR imaging, it was additionally administrated up to 0.2 mL of ketamine hydrochloride per 100 g of body weight. One imaging session continues up to 3 h. Wistar rats (weighting 200–250 g) were anesthetized and imaged first (as control) and later at different time points (in a period of 2 months) after the intramuscular injection of Fe3O4 nanoparticles solution in the left hind paw. Two different concentrations of the Fe3O4 nanoparticles solution (in volume of 0.2 mL) were chosen for administration: 520 µg Fe3O4/kg (SPION-high dose) and 20.8 µg Fe3O4/kg (SPION-low dose). In addition, physiological saline (0.9% NaCl) was administrated in the right hind paw for the reference. In vivo T2*-weighted MR images were acquired using fast gradient-echo (T2W-FFE) MR imaging sequence with the following parameters: scanning plane—coronal, repetition time (TR) 2000 ms, echo time (TE)—16.12 ms, matrix size—256 × 256; field of view (FOV)—127 × 35 mm, slice thickness—2.0 mm, number of acquisitions (NSA)—4. The acquired images were analyzed in order to evaluate migration of Fe3O4 nanoparticles from the injection site. The MR SI values were obtained by drawing ROIs over the injection site and the background tissue in coronal images using Philips Dicom Viewer software (R3.0-SP3, Philips Medical Systems) and calculating the MR signal relative intensity. 4.8. Animal Models The healthy adult Wistar rats, 6–8 weeks old and 200–250 g weight, were obtained from State Research Institute Centre for Innovative Medicine, Vilnius, Lithuania. All animals were maintained at a constant temperature (22 ± 1 °C), relative humidity (55% ± 10%) and photoperiod (12 h light/dark cycle) in the Open Access Centre at National Cancer Institute, Vilnius, Lithuania. The animals were fed standard rodent chow and purified water ad libitum. All animals’ procedures were performed in accordance with the guidelines established by the Lithuanian Care Committee which approved the study (No.Gd-29). 5. Conclusions This study provides some initial evidence that SPIONs accumulate in NIH3T3 cells and they are nontoxic for cells, according to a standard XTT test. Our findings demonstrate significant signal reduction with increasing of Fe3O4 concentration in the T2-weighted MRI. Moreover, low concentration of SPIONs was completely eliminated from the injection site after three weeks. Our methods utilized for visualization of SPIONs showed that these nanoparticles could be used as dual cancer imaging: for MRI as contrast agents and for traditional optical biopsy in morphology using Prussian Blue staining. Acknowledgments This work was financially supported by the joint Lithuanian-Latvian-Taiwanese Tripartite Cooperation Programme, Grant No. TAP-LLT-13-016. Author Contributions Ricardas Rotomskis and Vitalijus Karabanovas conceived of the study, participated in its design and coordination, and helped to draft the manuscript; Ting-Chen Tseng, Shan-hui Hsu performed synthesis MNPs; Vilius Poderys performed the characterization of MNPs; Greta Jarockyte, Urte Statkute carried out the cell culture studies; Egle Daugelaite, Marius Stasys carried out animal experiments; Greta Jarockyte, Egle Daugelaite, Marius Stasys, Shan-hui Hsu, Vitalijus Karabanovas, Ricardas Rotomskis analysed the data; Greta Jarockyte, Egle Daugelaite, Marius Stasys drafted the manuscript; and all authors read and approved the final manuscript. Conflicts of Interest The authors declare no conflict of interest. Abbreviations SPIONs Superparamagnetic iron oxide nanoparticles MNPs Magnetic nanoparticles MRI Magnetic resonance imaging Figure 1 Topographic atomic force microscopy (AFM) image of Fe3O4 magnetic nanoparticles dispersed on mica surface (B), particle height histogram (A), hydrodynamic size distribution (C) and schematic picture (D) of Fe3O4 magnetic nanoparticles. Figure 2 Fixed NIH3T3 cells after 0.5–72 h of incubation with 65 ng/mL of Fe3O4 (stained with Prussian Blue) (A–F). The accumulation was observed using bright-field microscope equipped with digital color camera. Figure 3 (A) viability of mouse embryonic fibroblasts NIH3T3, incubated with SPIONs for 3, 24 and 48 h. Toxicity of nanoparticles was investigated using XTT cell viability assay; (B) XTT plate images of NIH3T3 cells incubated with 32.5 ng/mL of SPION nanoparticles for 0, 24 and 48 h. Figure 4 (A) T2W MR coronal slice images in vitro of different concentrations of Fe3O4 dissolved in water (from c1 (1300 mg/L) to c15 (13 mg/L)); (B) T2W MR signal intensity plot of aqueous suspensions of Fe3O4 versus the concentration in the solution. Dotted line marks water MR signal. Figure 5 T2W MR coronal slice images of injection site at different time moments after intramuscular injection at dose of (A) 520 µg Fe3O4/kg (in the upper figure) and (B) 20.8 µg Fe3O4/kg (in the lower figure) in the rat left hind paw (red circles). The arrows marks injection site of physiological saline and Fe3O4 nanoparticles solution. Figure 6 Relative MR signal intensity at the injection site versus time at the different doses of Fe3O4 (red curve—520 µg Fe3O4/kg, black—20.8 µg Fe3O4/kg). ==== Refs References 1. Runge V.M. Clanton J.A. Lukehart C.M. Partain C.L. James A.E. Paramagnetic agents for contrast-enhanced NMR imaging: A review AJR Am. J. Roentgenol. 1983 141 1209 1215 10.2214/ajr.141.6.1209 6606318 2. Caravan P. Strategies for increasing the sensitivity of gadolinium based MRI contrast agents Chem. Soc. Rev. 2006 35 512 523 10.1039/b510982p 16729145 3. Edelman R.R. Warach S. Magnetic resonance imaging (1) N. Engl. J. Med. 1993 328 708 716 10.1056/NEJM199303113281008 8433731 4. Mitchell D.G. Cohen M.S. Saunders W.B. MRI Principles Saunders Philadelphia, PA, USA 2004 416 5. Lipinski M.J. Briley-Saebo K.C. Mani V. Fayad Z.A. “Positive contrast” inversion-recovery with oxide nanoparticles-resonant water suppression magnetic resonance imaging JAAC 2008 52 492 494 10.1016/j.jacc.2008.03.062 18672171 6. Hahn P.F. Stark D.D. Lewis J.M. Saini S. Elizondo G. Weissleder R. Fretz C.J. Ferrucci J.T. First clinical trial of a new superparamagnetic iron oxide for use as an oral gastrointestinal contrast agent in MR imaging Radiology 1990 175 695 700 10.1148/radiology.175.3.2343116 2343116 7. Haegele J. Duschka R.L. Graeser M. Schaecke C. Panagiotopoulos N. Lüdtke-Buzug K. Buzug T.M. Barkhausen J. Vogt F.M. Magnetic particle imaging: Kinetics of the intravascular signal in vivo Int. J. Nanomedicine 2014 9 4203 4209 10.2147/IJN.S49976 25214784 8. Stephen Z.R. Kievit F.M. Zhang M. Magnetite nanoparticles for medical MR imaging Mater. Today (Kidlington) 2011 14 330 338 10.1016/S1369-7021(11)70163-8 22389583 9. Mendonca Dias M.H. Lauterbur P.C. Ferromagnetic particles as contrast agents for magnetic resonance imaging of liver and spleen Magn. Reson. Med. 1986 3 328 330 10.1002/mrm.1910030218 3713497 10. Colombo M. Carregal-Romero S. Casula M.F. Gutiérrez L. Morales M.P. Böhm I.B. Heverhagen J.T. Prosperi D. Parak W.J. Biological applications of magnetic nanoparticles Chem. Soc. Rev. 2012 41 4306 4334 10.1039/c2cs15337h 22481569 11. Revia R.A. Zhang M. Magnetite nanoparticles for cancer diagnosis, treatment, and treatment monitoring: Recent advances Mater. Today 2016 19 157 168 10.1016/j.mattod.2015.08.022 12. Tromsdorf U.I. Bruns O.T. Salmen S.C. Beisiegel U. Weller H. A highly effective, nontoxic T1 MR contrast agent based on ultrasmall PEGylated iron oxide nanoparticles Nano Lett. 2009 9 4434 4440 10.1021/nl902715v 19799448 13. Taboada E. Rodríguez A. Roig J. Oro A. Roch R. Muller R.N. Relaxometric and magnetic characterization of ultrasmall iron oxide nanoparticles with high magnetization. Evaluation as potential T1 magnetic resonance imaging contrast agents for molecular imaging Langmuir 2007 23 4583 4588 10.1021/la063415s 17355158 14. Bartolini M.E. Pekar J. Chettle D.R. McNeill F. Scott A. Sykes J. Prato F.S. Moran G.R. An investigation of the toxicity of gadolinium based MRI contrast agents using neutron activation analysis Magn. Reson. Imaging 2003 21 541 544 10.1016/S0730-725X(03)00081-X 12878264 15. Perazella M.A. Gadolinium-contrast toxicity in patients with kidney disease: Nephrotoxicity and nephrogenic systemic fibrosis Curr. Drug Saf. 2008 3 67 75 10.2174/157488608783333989 18690983 16. Karlsson H.L. Cronholm P. Gustafsson J. Möller L. Copper oxide nanoparticles are highly toxic: A comparison between metal oxide nanoparticles and carbon nanotubes Chem. Res. Toxicol. 2008 21 1726 1732 10.1021/tx800064j 18710264 17. Mahmoudi M. Simchi A. Milani A.S. Stroeve P. Cell toxicity of superparamagnetic iron oxide nanoparticles J. Colloid Interface Sci. 2009 336 510 518 10.1016/j.jcis.2009.04.046 19476952 18. Kodama R.H. Berkowitz A.E. Atomic-scale magnetic modeling of oxide nanoparticles Phys. Rev. B 1999 59 6321 6336 10.1103/PhysRevB.59.6321 19. Swanson S.D. Kukowska-Latallo J.F. Patri A.K. Chen C. Ge S. Cao Z. Kotlyar A. East A.T. Baker J.R. Targeted gadolinium-loaded dendrimer nanoparticles for tumor-specific magnetic resonance contrast enhancement Int. J. Nanomed. 2008 3 201 210 20. Morteza Mahmoudi A.S. Superparamagnetic Iron Oxide Nanoparticles with Rigid Cross-linked polyethylene glycol fumarate coating for application in imaging and drug delivery J. Phys. Chem. C 2009 113 8124 8131 10.1021/jp900798r 21. Laurent S. Forge D. Port M. Roch A. Robic C. Vander Elst L. Muller R.N. Magnetic iron oxide nanoparticles: Synthesis, stabilization, vectorization, physicochemical characterizations, and biological applications Chem. Rev. 2008 108 2064 2110 10.1021/cr068445e 18543879 22. Lima-Tenório M.K. Pineda E.A.G. Ahmad N.M. Fessi H. Elaissari A. Magnetic nanoparticles: In vivo cancer diagnosis and therapy Int. J. Pharm. 2015 493 313 327 10.1016/j.ijpharm.2015.07.059 26232700 23. Kowalczyk M. Banach M. Rysz J. Ferumoxytol: A new era of iron deficiency anemia treatment for patients with chronic kidney disease J. Nephrol. 2011 24 717 722 10.5301/jn.5000025 21956770 24. Mahmoudi M. Hosseinkhani H. Hosseinkhani M. Boutry S. Simchi A. Journeay W.S. Subramani K. Laurent S. Magnetic resonance imaging tracking of stem cells in vivo using iron oxide nanoparticles as a tool for the advancement of clinical regenerative medicine Chem. Rev. 2011 111 253 280 10.1021/cr1001832 21077606 25. McColgan P. Sharma P. Bentley P. Stem cell tracking in human trials: A meta-regression Stem Cell. Rev. 2011 7 1031 1040 10.1007/s12015-011-9260-8 21475954 26. Park K. Facing the truth about nanotechnology in drug delivery ACS Nano 2013 7 7442 7447 10.1021/nn404501g 24490875 27. Venditto V. Szoka F.C. Jr. Cancer Nanomedicines: So Many Papers and So Few Drugs! Adv. Drug. Deliv. Rev. 2013 65 80 88 10.1016/j.addr.2012.09.038 23036224 28. Jin R. Lin B. Li D. Ai H. Super paramagnetic iron oxide nanoparticles for MR imaging and therapy: Design considerations and clinical applications Curr. Opin. Pharmacol. 2014 18 18 27 10.1016/j.coph.2014.08.002 25173782 29. Lodhia J. Mandarano G. Ferris N. Eu P. Cowell S. Development and use of iron oxide nanoparticles (Part 1): Synthesis of iron oxide nanoparticles for MRI Biomed. Imaging Interv. J. 2010 6 1193 10.2349/biij.6.2.e12 21611034 30. Wang J. Chen Y. Chen B. Ding J. Xia G. Gao C. Cheng J. Jin N. Zhou Y. Li X. Pharmacokinetic parameters and tissue distribution of magnetic Fe3O4 nanoparticles in mice Int. J. Nanomed. 2010 5 861 866 31. Müller R.H. Jacobs C. Buparvaquone mucoadhesive nanosuspension: Preparation, optimisation and long-term stability Int. J. Pharm. 2002 237 151 161 10.1016/S0378-5173(02)00040-6 11955813 32. Damalakiene L. Karabanovas V. Bagdonas S. Valius M. Rotomskis R. Intracellular distribution of nontargeted quantum dots after natural uptake and microinjection Int. J. Nanomed. 2013 8 555 568 10.2147/IJN.S39658 23429995 33. Marmorato P. Ceccone G. Gianoncelli A. Pascolo L. Ponti J. Rossi F. Salomé M. Kaulich B. Kiskinova M. Cellular distribution and degradation of cobalt ferrite nanoparticles in Balb/3T3 mouse fibroblasts Toxicol. Lett. 2011 207 128 136 10.1016/j.toxlet.2011.08.026 21925252 34. Sadeghiani N. Barbosa L.S. Silva L.P. Azevedo R.B. Morais P.C. Lacava Z.G.M. Genotoxicity and inflammatory investigation in mice treated with magnetite nanoparticles surface coated with polyaspartic acid J. Magn. Magn. Mater. 2005 289 466 468 10.1016/j.jmmm.2004.11.131 35. Neuwelt A. Sidhu N. Hu C.-A.A. Mlady G. Eberhardt S.C. Sillerud L.O. iron-based superparamagnetic nanoparticle contrast agents for MRI of infection and inflammation AJR Am. J. Roentgenol. 2015 204 W302 W313 10.2214/AJR.14.12733 25714316 36. Scudiero D.A. Shoemaker R.H. Paull K.D. Monks A. Tierney S. Nofziger T.H. Currens M.J. Seniff D. Boyd M.R. Evaluation of a soluble tetrazolium/formazan assay for cell growth and drug sensitivity in culture using human and other tumor cell lines Cancer Res. 1988 48 4827 4833 3409223 37. Zhu X.-M. Wang Y.-X.J. Leung K.C.-F. Lee S.-F. Zhao F. Wang D.-W. Lai J.M.Y. Wan C. Cheng C.H.K. Ahuja A.T. Enhanced cellular uptake of aminosilane-coated superparamagnetic iron oxide nanoparticles in mammalian cell lines Int. J. Nanomed. 2012 7 953 964 38. Hsu S. Ho T.-T. Tseng T.-C. Nanoparticle uptake and gene transfer efficiency for MSCs on chitosan and chitosan-hyaluronan substrates Biomaterials 2012 33 3639 3650 10.1016/j.biomaterials.2012.02.005 22364729 39. Dai L. Liu Y. Wang Z. Guo F. Shi D. Zhang B. One-pot facile synthesis of PEGylated superparamagnetic iron oxide nanoparticles for MRI contrast enhancement Mater. Sci. Eng. C 2014 41 161 167 10.1016/j.msec.2014.04.041 24907749 40. Lee C.-M. Jeong H.-J. Kim E.-M. Kim D.W. Lim S.T. Kim H.T. Park I.-K. Jeong Y.Y. Kim J.W. Sohn M.-H. Superparamagnetic iron oxide nanoparticles as a dual imaging probe for targeting hepatocytes in vivo Magn. Reson. Med. 2009 62 1440 1446 10.1002/mrm.22123 19859969

PMC005xxxxxx/PMC5000592.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081194ijms-17-01194ArticleAkt Activation Correlates with Snail Expression and Potentially Determines the Recurrence of Prostate Cancer in Patients at Stage T2 after a Radical Prostatectomy Chen Wei-Yu 123Hua Kuo-Tai 4Lee Wei-Jiunn 56Lin Yung-Wei 7Liu Yen-Nien 8Chen Chi-Long 12*Wen Yu-Ching 67*Chien Ming-Hsien 15*Stephan Carsten Academic Editor1 Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; 1047@tmu.edu.tw2 Department of Pathology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan3 Department of Pathology, Wan Fang Hospital, Taipei Medical University, Taipei 116, Taiwan4 Graduate Institute of Toxicology, College of Medicine, National Taiwan University, Taipei 100, Taiwan; d94447003@gmail.com5 Department of Medical Education and Research, Wan Fang Hospital, Taipei Medical University, Taipei 116, Taiwan; lwj5905@gmail.com6 Department of Urology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan7 Department of Urology, Wan Fang Hospital, Taipei Medical University, Taipei 116, Taiwan; highwei168@gmail.com8 Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan; liuy@tmu.edu.tw* Correspondence: chcl0997@yahoo.com.tw (C.-L.C.); s811007@yahoo.com.tw (Y.-C.W.); mhchien1976@gmail.com (M.-H.C.); Tel.: +886-2-2736-1661 (ext. 3139) (C.-L.C.); +886-2-2930-7930 (ext. 1867) (Y.-C.W.); +886-2-2736-1661 (ext. 3237) (M.-H.C.); Fax: +886-2-2377-0054 (C.-L.C.); +886-2-6628-0167 (Y.-C.W.); +886-2-2739-0500 (M.-H.C.)23 7 2016 8 2016 17 8 119408 6 2016 20 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).Our previous work demonstrated the epithelial-mesenchymal transition factor, Snail, is a potential marker for predicting the recurrence of localized prostate cancer (PCa). Akt activation is important for Snail stabilization and transcription in PCa. The purpose of this study was to retrospectively investigate the relationship between the phosphorylated level of Akt (p-Akt) in radical prostatectomy (RP) specimens and cancer biochemical recurrence (BCR). Using a tissue microarray and immunohistochemistry, the expression of p-Akt was measured in benign and neoplastic tissues from RP specimens in 53 patients whose cancer was pathologically defined as T2 without positive margins. Herein, we observed that the p-Akt level was higher in PCa than in benign tissues and was significantly associated with the Snail level. A high p-Akt image score (≥8) was significantly correlated with a higher histological Gleason sum, Snail image score, and preoperative prostate-specific antigen (PSA) value. Moreover, the high p-Akt image score and Gleason score sum (≥7) showed similar discriminatory abilities for BCR according to a receiver-operator characteristic curve analysis and were correlated with worse recurrence-free survival according to a log-rank test (p < 0.05). To further determine whether a high p-Akt image score could predict the risk of BCR, a Cox proportional hazard model showed that only a high p-Akt image score (hazard ratio (HR): 3.12, p = 0.05) and a high Gleason score sum (≥7) (HR: 1.18, p = 0.05) but not a high preoperative PSA value (HR: 0.62, p = 0.57) were significantly associated with a higher risk of developing BCR. Our data indicate that, for localized PCa patients after an RP, p-Akt can serve as a potential prognostic marker that improves predictions of BCR-free survival. prostate cancerradical prostatectomystage T2AktSnailbiochemical recurrence ==== Body 1. Introduction Globally, prostate cancer (PCa) accounts for 15% of male cancers and 6.6% of total male cancer mortality [1]. A radical prostatectomy (RP) is recognized as the gold standard for treating patients with localized PCa. The most important advantage of an RP is its potential to cure without damaging adjacent tissues and provide accurate staging because of the total removal of the organ. Although most patients are cured after surgery, around 23%–35% of PCa patients progress to biochemical recurrence (BCR) due to serum prostate-specific antigen (PSA) elevation, indicating that they have an increased risk of developing advanced PCa among 10 years after an RP [2,3]. To now, the challenge of PCa patients after an RP has been to determine which patients harbor high-risk disease requiring aggressive/curative therapy and which patients harbor indolent disease that can be managed with active surveillance. Clinical prognostic risk factors such as the Gleason score, pathological stage, a positive surgical margin, and preoperative PSA value are used to estimate patient outcomes postoperatively [4,5]. However, the sensitivity of predicting BCR of individual patients using such parameters is insufficient [4,5]. Hence, novel biomarkers are needed to predict BCR in PCa patients after an RP to help provide better patient counseling, to help with more-precise clinical decision-making, and to search for therapeutic targets. Recently, studies have identified several molecular alterations involved in prostate recurrence. For example, we previously identified that the epithelial-mesenchymal transition (EMT) factor, Snail, is upregulated in PCa and is a predictive factor for subsequent localized PCa recurrence after an RP [6]. However, the precise mechanisms underlying Snail expression in this malignancy has not been fully elucidated. Activation of the serine threonine kinase, Akt (phosphorylated (p)-Akt), was reported to regulate the stability and transcription of Snail in several cancer types, such as colorectal [7], oral [8], and prostate [9] cancers. A previous report indicated that p-Akt was expressed in around 8% of non-neoplastic prostate and 50% of PCa cases, indicative of its overexpression in cancer [10]. Increased Akt phosphorylation was observed in high-Gleason-score PCa and was correlated with proliferation in human PCa as estimated by the expression of the cell proliferation antigen, Ki67 [11,12]. Bedolla et al. recruited 65 PCa patients including T1~T3 stages with positive margins and showed that p-Akt is an important predictor of the risk of BCR [13]. Based on these results, we hypothesized an important role for Akt in PCa recurrence. To further investigate the role of Akt activation in localized PCa recurrence, this study recruited 53 PCa patients at the T2 stage without positive margins after an RP. We evaluated the p-Akt expression pattern in these PCa patients using immunohistochemistry (IHC), and correlated expression levels with Snail and other clinicopathological parameters. We report for the first time that expression of p-Akt was highly correlated with Snail expression in localized PCa, and the cytoplasmic p-Akt protein level has potential to serve as an independent biomarker to improve estimation of localized PCa prognoses. 2. Results In this study, we recruited 76 PCa patients who had not received neoadjuvant therapy and had undergone a whole-mount pathological assessment of their tumor after an RP. Next, we further excluded patients with a positive surgical margin and seminal vesicle invasion, and 53 of 76 patients who had organ-confined disease were ultimately recruited. Demographic and clinical characteristics are summarized in Table 1. Among the 53 PCa patients, the age at the time of the RP ranged 48–88 (mean, 70.7 ± 15.2) years. The histologic type of all tumors was an adenocarcinoma. According to the American Joint Committee on Cancer (AJCC) TNM staging system, tumors were classified into T2a (n = 6), T2b (n = 4), and T2c (n = 43). At a mean follow-up time of 71 months, 25 of 53 patients had BCR. Figure 1A–D shows that p-Akt expression was observed in PCa tissue with a wide distribution of IHC scores. Immunostaining was almost completely restricted to the cytoplasm of epithelial tumor cells, and the pattern of expression was usually homogeneous. The p-Akt score was determined by multiplying the staining intensity (1–3) by the distribution rate (1–4) to represent p-Akt expression in PCa tissues, and representative examples of tumors showing overall low (with an image score of ≤6) and high (with an image score of ≥8) p-Akt expressions are illustrated in Figure 1A–D. In contrast to PCa, non-tumor adjacent tissues or benign prostatic hyperplasia (BPH) expressed p-Akt very weakly or not at all (Figure 1D,E), indicating that high levels of p-Akt were almost exclusively expressed in cancer tissues. Previous studies indicated that Akt activation is important for Snail stabilization and transcription in PCa cells [9,14]. To further examine the correlation between expression levels of p-Akt and Snail in PCa, the same PCa TMA cohort was used. Representative IHC staining of p-Akt and Snail with different image scores on serial section of the same patients are shown in Figure 2A. IHC analysis of PCa specimens revealed a significant positive correlation between p-Akt and Snail expressions (Spearman correlation coefficient r = 0.851, p < 0.0001; Figure 2B). As we showed earlier [6] , staining for Snail was significantly correlated with postoperative BCR of PCa. We further investigated relationships between p-Akt expression and selected clinicopathologic factors. Table 2 shows that among the 53 recruited patients, 32 patients (60.4%) were identified as having a high p-Akt image score (of ≥8), and the remaining 21 patients had a low p-Akt image score (of ≤6). High p-Akt (score of ≥8) expression was significantly associated with a higher histological Gleason sum (score of ≥7) (p = 0.024), Snail image score (score of ≥8) (p = 0.035), and preoperative PSA value (p = 0.026). Moreover, we also observed that high p-Akt expression was significantly correlated with postoperative BCR (p = 0.012). Moreover, according to an ROC analysis, the areas under the ROC curve for high p-Akt image score (score of ≥8) and Gleason score sum (score of ≥7) were similar, indicating that the high p-Akt image score and Gleason score sum showed similar discriminatory capacities for BCR (Figure 3). According to the Kaplan-Meier test, we observed that patients with higher p-Akt expression (with scores of ≥8) had shorter recurrence-free survival times compared to those with lower expression (with scores of ≤6) of the protein (Figure 4A). For patients who had higher p-Akt tumor expression, the median recurrence-free survival was 62 months, whereas for those who demonstrated lower p-Akt tumor expression, it was 88 months (p = 0.03) (Figure 4A). Moreover, results of the Kaplan-Meier test also showed that patients with a higher Gleason score sum (of ≥7) or a higher Snail expression (with a score of ≥8) all had significantly shorter recurrence-free survival times (p = 0.03 and 0.05) (Figure 4B,C). These results showed that the p value of the Kaplan-Meier test used to compare the higher p-Akt group was the same and smaller than the higher Gleason score group and higher Snail group, respectively. A Cox proportional hazard model was conducted to further explore relationships of p-Akt and Snail expressions with recurrence-free survival of the 53 patients with PCa after an RP. Table 3 summarizes the associations between the recurrence-free survival rate of the 53 patients with PCa and clinicopathologic parameters. In this analysis, we only observed that a high p-Akt image score (≥8) (hazard ratio (HR): 3.12, p = 0.05) or a high Gleason score sum (≥7) (HR: 1.18, p = 0.05), but not a high pre-operative PSA value (>10 ng/mL) (HR: 0.62, p = 0.57), was significantly correlated with worse recurrence-free survival (Table 3). In conclusion, our results suggest that a high p-Akt image score and a high histological Gleason score sum but not the preoperative PSA value can predict organ-confined PCa recurrence in our study. Moreover, we observed that patients with a high Snail image score (≥8) also tended to correlate with BCR (HR: 1.31, p = 0.06). Furthermore, our data indicated that patients with a high p-Akt image score (HR: 3.12) showed a higher risk for BRC than patients with a high Gleason score sum (HR: 1.18) or a high Snail image score (HR: 1.31) (Table 3). 3. Discussion PCa is the most common cancer and the second leading cause of male cancer deaths in the United States [15]. This underscores the need for a more-thorough molecular understanding of this resilient disease. Generally, patients with clinically-localized PCa will be cured after receiving radical surgery. However, a fraction of patients with localized PCa harbor microscopic localized or metastatic residual disease. The lethal consequences of PCa are related to its metastasis to other organ sites. Although the preoperative PSA value, surgical margin status, and Gleason score sum have been extensively used in assessing biochemical disease recurrence risk after RP, the sensitivities of these approaches are insufficient [16,17]. Therefore, it is of critical significance to discover a new marker for the early prediction of tumor recurrence, and earlier adjuvant therapy is very important for clinicians. The EMT is a critical cellular mechanism during tumor progression and development of metastasis. It was suggested that the EMT is co-opted by PCa cells during their metastatic dissemination from a primary organ to secondary sites [18]. We previously showed that increased expression of the EMT promoter, Snail, in the prostatic epithelium is a good predictor of BCR following a prostatectomy [6]. The phosphatidylinositol 3’-kinase (PI3K)/Akt pathway is frequently activated in various cancers and plays an important role in promoting the EMT through regulating Snail stability in PCa [9,19]. Our current results indicated that the Akt activation status was significantly correlated with Snail expression levels in tissues from patients with clinically-localized PCa (T2 stage only). Representative IHC staining patterns of p-Akt and Snail from consecutive serial sections were nearly identical in PCa specimens, further implying their highly correlated expressions. Compared to our previous study [6], we extended the postoperative follow-up time (an average of 51 to 71 months) of localized PCa patients and further investigated the correlation between the Akt activation status in PCa specimens and BRC of patients. Our data showed that p-Akt was predominantly expressed in PCa, but not in non-neoplastic tissues. Cox proportional hazard models suggested that the p-Akt index (HR: 3.12, p = 0.05) is a better postoperative marker than the preoperative PSA value (HR: 0.62, p = 0.57) in localized PCa in our patient cohort. Although the Gleason score sum showed a similar discriminatory capacity with the p-Akt index and was also a useful predictor of BRC in our patient cohort, it was not as good as p-Akt. Compared to a high p-Akt image score, a high Gleason score sum showed a lower HR (HR: 1.18, p = 0.05) for BRC. Moreover, our previous study [6] indicated that the Snail index might be a useful predictor of BRC in the same patient cohort. However, after we extended the postoperative follow-up time in this study, the high Snail image score only showed a borderline significant trend (p = 0.06) of correlating with BRC, suggesting that p-Akt might show higher sensitivity than Snail for predicting organ-confined PCa recurrence. In addition to Snail, other transcription factors such as Slug, Zeb1, and Zeb2 are also involved in the control of EMT [20]. A previous report indicated that Akt activation can upregulate Snail and Zeb2 and promote EMT in squamous cell carcinoma [21]. However, the roles of Akt and Zeb2 in prostate cancer progression and recurrence are still unclear and worth further investigation in our future work. High levels of p-Akt are associated with earlier recurrence, clearly indicating that p-Akt is associated with aggressiveness and disease progression in PCa. In addition to the Akt-mediated Snail expression and EMT induction in an androgen-independent PC3 cell line [14], Akt was also shown to be involved in a number of proliferative, metabolic, and antiapoptotic pathways that are dependent on PI3K signaling for activation [22]. Activated Akt was suggested to regulate a number of intracellular targets such as p27Kip1, Bcl-2-associated death promoter (BAD), and caspase-9 which are involved in PCa progression and androgen independence [23,24,25]. Androgen deprivation therapy on androgen-dependent PCa cells such as LNCaP was reported to stimulate Akt activation, which finally resulted in androgen independence of the cells [26]. The pro-survival role of Akt activities was further shown in several clinical studies. For instance, increased levels of Akt or p-Akt expression were associated with a high Gleason grade and a worse prognosis in PCa [27,28,29]. Herein, we also showed that high levels of p-Akt were associated with more-aggressive features of the disease, as patients with high levels of p-Akt were identified as having a high PSA level and a high Gleason score. Although the clinical application of p-Akt in predicting BCR of PCa was previously reported [10,13], the patient cohort recruited in this study was totally different from those of previous studies. Previous studies [10,13] enrolled PCa patients after an RP at different stages (pT1–pT3), and included those with lymph node metastasis, extracapsular extension, positive margins, and seminal vesicle invasion. However, in our study, we excluded PCa patients with positive margins or seminal vesicle involvement and only included true organ-confined PCa patients (pT2a–pT2c) after an RP. To our best knowledge, this is the first report to investigate the relationships of p-Akt and Snail with the prognostic role of p-Akt in patients with clinically-localized PCa. The pathological definition of T2a–T2c stages is involvement of tumor cells in the prostate: in T2a, the tumor involves ≤50% of one lobe; in T2b, the tumor involves >50% of one lobe, but not both lobes; and in T2c, the tumor involves both lobes [30]. A previous report indicated that tumor focality can significantly influence the BCR-free survival rate [31]. However, more-recent reports indicated that tumor focality did not predict the risk of BCR after an RP in men with clinically-localized PCa, even if the tumor involved both lobes of the prostate [32], suggesting that tumor focality might not be a suitable predictive marker for BCR in patients with organ-confined PCa. Our study observed that p-Akt expression level should be a better predictive marker of BCR in this PCa population. In addition to Akt, its downstream signaling pathways such as GSK-3β inactivation and NF-κB activation were also involved in Akt-mediated Snail expression in prostate cancer cells as well as in other cancer types [7,14,21]. Our future work will further investigate the correlation between these downstream effectors and BCR-free survival rate in patients with localized PCa. 4. Materials and Methods 4.1. Patient Selection and Specimen Collection Pathology files of Wan Fang Hospital and Taipei Medical University Hospital were searched, and 76 radical prostatectomy specimens with a pathologic diagnosis of prostatic adenocarcinoma were found from March 1999 to December 2011. The pathologic diagnosis and Gleason scoring were microscopically reconfirmed by pathologists. Each case was pathologically staged using the 2002 American Joint Committee on Cancer TNM staging system. In our recruited patients, 13 patients with advanced stage were excluded. Another 10 patients who had positive surgical margins were also excluded from the study. Ultimately, 53 cases fulfilling the selection criteria were included for further study. Follow-up information was obtained from a cancer registration database. A PSA level of ≥0.2 ng/mL on at least two occasions over a 2-month period was used to define biochemical failure [33]. 4.2. Tissue Microarrays (TMAs) Two independent PCa TMA sets were used in this study. PCa samples from patients were obtained with informed consent (Taipei Medical University-Wan Fang Hospital Institutional Review Board No. 99049). TMAs were constructed using a manual tissue-arraying instrument (Beecher Instruments, Sun Prairie, WI, USA). Briefly, carcinoma areas were manually punched, and duplicate tissue cores measuring 2.5 mm in diameter were inserted into recipient paraffin blocks. Sections measuring 5 μm in thickness were cut and transferred to glass slides. The presence of tumor tissue was further verified on a hematoxylin and eosin (H and E)-stained section. 4.3. Immunohistochemical (IHC) Staining In brief, tissue microarray (TMA) sections were deparaffinized and immersed in 10 mM sodium citrate buffer (pH 6.0) in a microwave oven twice for 5 min to enhance antigen retrieval. After washing, slides were incubated with 0.3% H2O2 in methanol to quench the endogenous peroxidase activity. Slides were washed with phosphate-buffered saline (PBS) and incubated with anti-p-Akt (rabbit polyclonal antibody, Santa Cruz Biotechnology, Santa Cruz, CA, USA), anti-Snail (monoclonal mouse anti-Snail antibody, Biorbyt, Cambridge, UK), and appropriate negative control antibodies for 2 h at room temperature. After washing in PBS, slides were developed with a VECTASTAIN® ABC (avidin-biotin complex) peroxidase kit (Vector Laboratories, Burlingame, CA, USA) and a 3,3,9-diaminobenzidine (DAB) peroxidase substrate kit (Vector Laboratories) according to the manufacturer’s instructions. All specimens were stained with H and E, which was used as a light counterstain. 4.4. Scoring of Immunoexpression IHC results of p-Akt and Snail were classified into two groups according to the intensity and extent of staining. The intensity was scored semi-quantitatively as 0, negative; 1 point, weakly positive; 2 points, moderately positive; or 3 points, strongly positive. To determine the extent of Snail expression, 1000 consecutive malignant cells were counted in the area of the strongest staining. Numbers of cells with positive cytoplasmic staining for p-Akt and positive cytoplasmic and nuclear staining for Snail were recorded. The extent of p-Akt and Snail staining was semi-quantitatively scored as 0, positive in <1% of cells; 1 point, positive in 1%–25% of cells; 2 points, positive in 25%–50% of cells; 3 points, positive in 50%–75% of cells; or 4 points, positive in 75%–100% of cells. We then developed a p-Akt or Snail image score as previously described [6] by multiplying the intensity score (0–3 points) by the extent score (0–4 points) to represent the expression of p-Akt or Snail in cancer tissues. Low and high expression levels of p-Akt or Snail were respectively defined as 0–6 and 8–12 points. All sections were independently scored by the authors. 4.5. Statistical Analysis SPSS 17.0 statistical software (SPSS, Chicago, IL, USA) was used for all statistical analyses. Differences in the clinicopathological features and Akt image scores of the tumors were assessed using paired t-tests for continuous and categorical variables. A Cox proportional hazards regression model was used for a univariate analysis when assessing predictors of biochemical progression. The Kaplan-Meier method was used to compare the time to recurrence among the groups. The diagnostic value of potential biomarkers as predictors of biochemical failure was evaluated with receiver-operator characteristic (ROC) curves. The area under the ROC curve (AUC) was determined from the plot of sensitivity versus 1–specificity (true positive rate versus false positive rate) and is a measure of the predictability of a test. Statistical significance was defined at p < 0.05. 5. Conclusions Our data demonstrate, for the first time, that p-Akt expression is highly correlated with Snail expression in a Taiwanese population with primary localized PCa. We also documented that p-Akt exerts its tumor-promoting role because of its associations with various aggressive clinicopathological characteristics and BCR in men with clinically-localized PCa. Our results highlight that, in patients with clinically-localized PCa, and a high p-Akt image score in cancer tissues, adjuvant radiotherapy or hormone therapy might be suggested to prevent early BCR. However, larger prospective cohorts and experimental studies are needed for comprehensive functional validation and better understanding of the clinical significance of p-Akt and Snail expression in PCa. Acknowledgments This study was supported by grant numbers DOH-TD-B-111-003 and DOH102-TD-C-111-008 from Taipei Medical University and 105TMU-WFH-04 from Wan Fang Hospital, Taipei Medical University. Author Contributions Yu-Ching Wen, Kuo-Tai Hua, and Ming-Hsien Chien conceived and designed the experiments, contributed materials, and analyzed the data; Wei-Yu Chen and Chi-Long Chen performed the IHC experiments; Yen-Nien Liu contributed analytical tools; Ming-Hsien Chien, Yu-Ching Wen, and Wei-Jiunn Lee contributed reagents and wrote the paper. Conflicts of Interest The authors state that there are no conflicts of interest. Abbreviations BPH Benign prostatic hyperplasia BCR Biochemical recurrence EMT Epithelial-mesenchymal transition PCa Prostate cancer PI3K Phosphatidylinositol 3′-kinase PSA Prostate-specific antigen RP Radical prostatectomy TMA Tissue microarrays Figure 1 Phosphorylated (p)-Akt expression levels in representative primary prostate cancer (PCa) and non-neoplastic prostate tissues. Tissue microarrays (TMAs) of primary PCa and non-neoplastic prostate (benign prostatic hyperplasia; BPH) tissues were immunohistochemistry (IHC) analyzed for p-Akt. (A) Patient with a weak p-Akt expression level (intensity score 1 × extent score 1 = p-Akt image score 1); (B) Patient with T2cN0M0 cancer, a Gleason score of 3 + 4 = 7, and a moderate p-Akt expression level (intensity score 2 × extent score 3 = p-Akt image score 6); (C) Patient with T2cN0M0 cancer, a Gleason score of 4 + 3 = 7, and marked p-Akt immunostaining in the cytoplasm (intensity score 2 × extent score 4 = Snail image score 8); (D) Patient with T2cN0M0 cancer and a Gleason score of 4 + 5 = 9 and who displayed marked p-Akt immunostaining in the cytoplasm and discrete, diffuse staining in the nucleus (intensity score 3 × extent score 4 = image score 12) (200×); (E,F) No p-Akt immunostaining signal was detected in non-tumor adjacent tissues (E) or BPH (F). The high-power fields (200×) are magnified fields in the black boxed area in the right panel. Figure 2 Phosphorylated (p)-Akt expression is positively correlated with Snail protein levels of patients with localized prostate cancer (PCa). (A) IHC staining analysis of p-Akt and Snail proteins in serial sections (200× magnification). Note the positive correlation of p-Akt and Snail protein expressions in tumor cells; (B) A significant positive correlation was observed between p-Akt expression levels and Snail expression levels (Spearman’s correlation coefficients: r = 0.851, p < 0.0001). Figure 3 Sensitivity and specificity of gain of a high Gleason score or high p-Akt in specimens with respect to biochemical recurrence (BRC). Areas under the ROC (AUC) for high p-Akt image score (≥8) and high Gleason score (≥7) were 0.62 and 0.624, indicating similar discriminatory abilities for BRC. Figure 4 Kaplan-Meier survival curves showing relationships of the phosphorylated (p)-Akt image score (A), Gleason score sum (B), and Snail image score (C) in primary tumors with recurrence-free survival in 53 patients with clinically-localized prostate cancer. The recurrence-free survival of patients with a higher p-Akt, Snail image score (≥8) or Gleason score sum (≥7) was significantly lower than that of patients with a lower p-Akt, Snail image score (≤6) or Gleason score sum (≤6) (p ≤ 0.05, log-rank test). ijms-17-01194-t001_Table 1Table 1 Characteristics of prostate cancer (PCa) patients at the pT2 stage who underwent a radical prostatectomy (RP). Characteristic Total (%) Total number of patients 53 Median age at RP (years) 71, mean 70.7 ± 15.2 (48–88 y/o) Mean preoperative PSA level (ng/mL) 10.31 (1–21.64 ng/mL) Biochemical failure 25 (47.2) Pathological stage T2a 6 (11.3) T2b 4 (7.5) T2c 43 (81.2) Gleason score ≥7 34 (64.2) ≤6 19 (35.8) Snail image score ≥8 35 (66) ≤6 18 (34) Phosphorylated-Akt image score ≥8 32 (60.4) ≤6 21 (39.1) Median follow-up time (months) 99, mean: 71 ± 49.5 (53–184 m) RP, radical prostatectomy; PSA, prostate specific antigen; y/o, years old; m, months. ijms-17-01194-t002_Table 2Table 2 The association of phosphorylated (p)-Akt staining and clinicopathological features of prostate cancer (PCa) patients. Characteristic No. of Patients (%) p Value pAkt Score ≥ 8 pAkt Score ≤ 6 Total number of patients 32 (60.4) 21 (39.6) Age (years) <50 1 0 50–59 5 3 60–69 11 6 ≥70 15 12 Pathological stage T2a 2 (6.25) 3 (14.3) 0.540 T2b 2 (6.25) 2 (9.5) T2c 28 (87.5) 16 (76.2) Gleason score ≥7 28 (87.5) 8 (38.1) 0.024 ≤6 4 (12.5) 13 (61.9) Snail image score ≥8 29 (90.6) 6 (28.6) 0.035 ≤6 3 (9.4) 15 (71.4) Recurrence 18 (56.3) 7 (33.3) 0.012 PSA, mean (ng/mL) 29.9 12.1 0.026 PSA: prostate specific antigen. ijms-17-01194-t003_Table 3Table 3 Survival analyses of biochemical progression predictors in patients with prostate cancer at pT2 who underwent a radical prostatectomy (RP) according to a Cox proportional hazards regression model. Factor Hazard Ratio (95% CI) p Value PSA > 10 ng/mL 0.62 (0.12–3.19) 0.57 Pathological Gleason sum ≥ 7 1.18 (0.23–1.32) 0.05 Snail image score ≥ 8 1.31 (0.09–3.03) 0.06 P-Akt image score ≥ 8 3.12 (0.95–10.27) 0.05 ==== Refs References 1. Ferlay J. Soerjomataram I. Dikshit R. Eser S. Mathers C. Rebelo M. Parkin D.M. Forman D. Bray F. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012 Int. J. Cancer 2015 136 E359 E386 10.1002/ijc.29210 25220842 2. Stephenson A.J. Scardino P.T. Eastham J.A. Bianco F.J. Jr. Dotan Z.A. Fearn P.A. Kattan M.W. Preoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy J. Natl. Cancer Inst. 2006 98 715 717 10.1093/jnci/djj190 16705126 3. Hull G.W. Rabbani F. Abbas F. Wheeler T.M. Kattan M.W. Scardino P.T. Cancer control with radical prostatectomy alone in 1000 consecutive patients J. Urol. 2002 167 528 534 10.1016/S0022-5347(01)69079-7 11792912 4. Stephenson A.J. Scardino P.T. Eastham J.A. Bianco F.J. Jr. Dotan Z.A. DiBlasio C.J. Reuther A. Klein E.A. Kattan M.W. Postoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy J. Clin. Oncol. 2005 23 7005 7012 10.1200/JCO.2005.01.867 16192588 5. Kotb A.F. Elabbady A.A. Prognostic factors for the development of biochemical recurrence after radical prostatectomy Prostate Cancer 2011 2011 485189 10.1155/2011/485189 22110987 6. Wen Y.C. Chen W.Y. Lee W.J. Yang S.F. Lee L.M. Chien M.H. Snail as a potential marker for predicting the recurrence of prostate cancer in patients at stage T2 after radical prostatectomy Clin. Chim. Acta 2014 431 169 173 10.1016/j.cca.2014.01.036 24513541 7. Wang H. Wang H.S. Zhou B.H. Li C.L. Zhang F. Wang X.F. Zhang G. Bu X.Z. Cai S.H. Du J. Epithelial-mesenchymal transition (EMT) induced by TNF-α requires AKT/GSK-3β-mediated stabilization of snail in colorectal cancer PLoS ONE 2013 8 1194 10.1371/journal.pone.0056664 23431386 8. Grille S.J. Bellacosa A. Upson J. Klein-Szanto A.J. van Roy F. Lee-Kwon W. Donowitz M. Tsichlis P.N. Larue L. The protein kinase Akt induces epithelial mesenchymal transition and promotes enhanced motility and invasiveness of squamous cell carcinoma lines Cancer Res. 2003 63 2172 2178 12727836 9. Liu Z.C. Wang H.S. Zhang G. Liu H. Chen X.H. Zhang F. Chen D.Y. Cai S.H. Du J. AKT/GSK-3β regulates stability and transcription of snail which is crucial for bFGF-induced epithelial-mesenchymal transition of prostate cancer cells Biochim. Biophys. Acta 2014 1840 3096 3105 10.1016/j.bbagen.2014.07.018 25088797 10. Ayala G. Thompson T. Yang G. Frolov A. Li R. Scardino P. Ohori M. Wheeler T. Harper W. High levels of phosphorylated form of Akt-1 in prostate cancer and non-neoplastic prostate tissues are strong predictors of biochemical recurrence Clin. Cancer Res. 2004 10 6572 6578 10.1158/1078-0432.CCR-04-0477 15475446 11. Malik S.N. Brattain M. Ghosh P.M. Troyer D.A. Prihoda T. Bedolla R. Kreisberg J.I. Immunohistochemical demonstration of phospho-Akt in high Gleason grade prostate cancer Clin. Cancer Res. 2002 8 1168 1171 11948129 12. Ghosh P.M. Malik S.N. Bedolla R.G. Wang Y. Mikhailova M. Prihoda T.J. Troyer D.A. Kreisberg J.I. Signal transduction pathways in androgen-dependent and -independent prostate cancer cell proliferation Endocr. Relat. Cancer 2005 12 119 134 10.1677/erc.1.00835 15788644 13. Bedolla R. Prihoda T.J. Kreisberg J.I. Malik S.N. Krishnegowda N.K. Troyer D.A. Ghosh P.M. Determining risk of biochemical recurrence in prostate cancer by immunohistochemical detection of PTEN expression and Akt activation Clin. Cancer Res. 2007 13 3860 3867 10.1158/1078-0432.CCR-07-0091 17606718 14. Wang H. Fang R. Wang X.F. Zhang F. Chen D.Y. Zhou B. Wang H.S. Cai S.H. Du J. Stabilization of Snail through AKT/GSK-3β signaling pathway is required for TNF-α-induced epithelial-mesenchymal transition in prostate cancer PC3 cells Eur. J. Pharmacol. 2013 714 48 55 10.1016/j.ejphar.2013.05.046 23769744 15. Siegel R.L. Miller K.D. Jemal A. Cancer statistics, 2015 CA Cancer J. Clin. 2015 65 5 29 10.3322/caac.21254 25559415 16. Kattan M.W. Nomograms are superior to staging and risk grouping systems for identifying high-risk patients: preoperative application in prostate cancer Curr. Opin. Urol. 2003 13 111 116 10.1097/00042307-200303000-00005 12584470 17. Chun F.K. Steuber T. Erbersdobler A. Currlin E. Walz J. Schlomm T. Haese A. Heinzer H. McCormack M. Huland H. Development and internal validation of a nomogram predicting the probability of prostate cancer Gleason sum upgrading between biopsy and radical prostatectomy pathology Eur. Urol. 2006 49 820 826 10.1016/j.eururo.2005.11.007 16439050 18. Matuszak E.A. Kyprianou N. Androgen regulation of epithelial-mesenchymal transition in prostate tumorigenesis Expert Rev. Endocrinol. Metab. 2011 6 469 482 10.1586/eem.11.32 23667383 19. Larue L. Bellacosa A. Epithelial-mesenchymal transition in development and cancer: Role of phosphatidylinositol 3′ kinase/AKT pathways Oncogene 2005 24 7443 7454 10.1038/sj.onc.1209091 16288291 20. Peinado H. Olmeda D. Cano A. Snail, Zeb and bHLH factors in tumour progression: An alliance against the epithelial phenotype? Nat. Rev. Cancer 2007 7 415 428 10.1038/nrc2131 17508028 21. Julien S. Puig I. Caretti E. Bonaventure J. Nelles L. van Roy F. Dargemont C. de Herreros A.G. Bellacosa A. Larue L. Activation of NF-κB by Akt upregulates Snail expression and induces epithelium mesenchyme transition Oncogene 2007 26 7445 7456 10.1038/sj.onc.1210546 17563753 22. Alessi D.R. Cohen P. Mechanism of activation and function of protein kinase B Curr. Opin. Genet. Dev. 1998 8 55 62 10.1016/S0959-437X(98)80062-2 9529606 23. Graff J.R. Konicek B.W. McNulty A.M. Wang Z. Houck K. Allen S. Paul J.D. Hbaiu A. Goode R.G. Sandusky G.E. Increased AKT activity contributes to prostate cancer progression by dramatically accelerating prostate tumor growth and diminishing p27Kip1 expression J. Biol. Chem. 2000 275 24500 24505 10.1074/jbc.M003145200 10827191 24. Graff J.R. Emerging targets in the AKT pathway for treatment of androgen-independent prostatic adenocarcinoma Expert Opin. Ther. Targets 2002 6 103 113 10.1517/14728222.6.1.103 11901476 25. Datta S.R. Dudek H. Tao X. Masters S. Fu H. Gotoh Y. Greenberg M.E. Akt phosphorylation of BAD couples survival signals to the cell-intrinsic death machinery Cell 1997 91 231 241 10.1016/S0092-8674(00)80405-5 9346240 26. Murillo H. Huang H. Schmidt L.J. Smith D.I. Tindall D.J. Role of PI3K signaling in survival and progression of LNCaP prostate cancer cells to the androgen refractory state Endocrinology 2001 142 4795 4805 10.1210/endo.142.11.8467 11606446 27. Le Page C. Koumakpayi I.H. Alam-Fahmy M. Mes-Masson A.M. Saad F. Expression and localisation of Akt-1, Akt-2 and Akt-3 correlate with clinical outcome of prostate cancer patients Br. J. Cancer 2006 94 1906 1912 10.1038/sj.bjc.6603184 16721361 28. Liao Y. Grobholz R. Abel U. Trojan L. Michel M.S. Angel P. Mayer D. Increase of AKT/PKB expression correlates with Gleason pattern in human prostate cancer Int. J. Cancer 2003 107 676 680 10.1002/ijc.11471 14520710 29. Kreisberg J.I. Malik S.N. Prihoda T.J. Bedolla R.G. Troyer D.A. Kreisberg S. Ghosh P.M. Phosphorylation of Akt (Ser473) is an excellent predictor of poor clinical outcome in prostate cancer Cancer Res. 2004 64 5232 5236 10.1158/0008-5472.CAN-04-0272 15289328 30. Koh H. Maru N. Muramoto M. Wheeler T.M. Scardino P.T. Ohori M. The 1992 TNM classification of T2 prostate cancer predicts pathologic stage and prognosis better than the revised 1997 classification Nihon Hinyokika Gakkai Zasshi 2002 93 595 601 10.5980/jpnjurol1989.93.595 12174634 31. Rice K.R. Furusato B. Chen Y. McLeod D.G. Sesterhenn I.A. Brassell S.A. Clinicopathological behavior of single focus prostate adenocarcinoma J. Urol. 2009 182 2689 2694 10.1016/j.juro.2009.08.055 19836800 32. Masterson T.A. Cheng L. Mehan R.M. Koch M.O. Tumor focality does not predict biochemical recurrence after radical prostatectomy in men with clinically localized prostate cancer J. Urol. 2011 186 506 510 10.1016/j.juro.2011.03.106 21679993 33. Freedland S.J. Sutter M.E. Dorey F. Aronson W.J. Defining the ideal cutpoint for determining PSA recurrence after radical prostatectomy: Prostate-specific antigen Urology 2003 61 365 369 10.1016/S0090-4295(02)02268-9 12597949

PMC005xxxxxx/PMC5000593.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081195ijms-17-01195ArticleComparative Analysis for the Presence of IgG Anti-Aquaporin-1 in Patients with NMO-Spectrum Disorders Sánchez Gomar Ismael 1Díaz Sánchez María 2Uclés Sánchez Antonio José 2Casado Chocán José Luis 2Suárez-Luna Nela 1Ramírez-Lorca Reposo 1Villadiego Javier 1Toledo-Aral Juan José 13Echevarría Miriam 14*Ishibashi Kenichi Academic Editor1 Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville 41013, Spain; ismael_sg84@hotmail.com (I.S.G.); neluqui@yahoo.es (N.S.-L.); reporamirez@us.es (R.R.-L.); fvilladiego@us.es (J.V.); juanjo@us.es (J.J.T.-A.)2 Unidad de Gestión Clínica de Neurociencias, Servicio de Neurología del Hospital Universitario Virgen del Rocío, Seville 41013, Spain; mariadiazsanchez@hotmail.com (M.D.S.); antonioj.ucles@gmail.com (A.J.U.S.); jcasadoch@gmail.com (J.L.C.C.)3 Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid 28029, Spain4 Centro de Investigación Biomédica en Red sobre Enfermedades Respiratorias (CIBERES), Madrid 28029, Spain* Correspondence: irusta@us.es; Tel.: +34-955-923-03623 7 2016 8 2016 17 8 119531 5 2016 19 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).Detection of IgG anti-Aquaporin-4 (AQP4) in serum of patients with Neuromyelitis optica syndrome disorders (NMOSD) has improved diagnosis of these processes and differentiation from Multiple sclerosis (MS). Recent findings also claim that a subgroup of patients with NMOSD, serum negative for IgG-anti-AQP4, present antibodies anti-AQP1 instead. Explore the presence of IgG-anti-AQP1 using a previously developed cell-based assay (CBA) highly sensitive to IgG-anti-AQP4. Serum of 205 patients diagnosed as NMOSD (8), multiple sclerosis (94), optic neuritis (39), idiopathic myelitis (29), other idiopathic demyelinating disorders of the central nervous system (9), other neurological diseases (18) and healthy controls (8), were used in a CBA over fixed HEK cells transfected with hAQP1-EGFP or hM23-AQP4-EGFP, treated with Triton X-100 and untreated. ELISA was also performed. Analysis of serum with our CBA indicated absence of anti-AQP1 antibodies, whereas in cells pretreated with detergent, noisy signal made reliable detection impossible. ELISA showed positive results in few serums. The low number of NMOSD serums included in our study reduces its power to conclude the specificity of AQP1 antibodies as new biomarkers of NMOSD. Our study does not sustain detection of anti-AQP1 in serum of NMOSD patients but further experiments are expected. AQP1AQP4NMO-IgGHEK cellsneuromyelitis optica ==== Body 1. Introduction Neuromyelitis optica (NMO) is an autoimmune, inflammatory and demyelinating disease of the central nervous system (CNS) that primarily affects the optic nerves and spinal cord. Patients with this disease, also known as Devic syndrome, present recurrent episodes of optic neuritis and acute myelitis that conduce to a loss of uni- or bilateral vision and to a sensitive and motor compromise below the affected medullar level with frequent loss of sphincters control [1,2]. Although it was considered for a long time as a variant of multiple sclerosis (MS), new pathological and serological tests have contributed to identify this disorder as a different disease [3]. The main evidence for such distinction was provided by Lennon et al. [3,4,5] when they discovered the presence of specific immunoglobulins (IgG-NMO) in serum of NMO patients, IgG that were usually absent in classical forms of MS. The antigen recognized for IgG-NMO is Aquaporin-4 (AQP4), the most abundantly expressed aquaporin in the CNS [6,7,8], highly localized in astrocytes membrane facing blood vessels, in ependymal cells of brain ventricles, and layers of the meninges surrounding the brain and spinal cord [4]. Recent works present convincing evidences supporting a direct involvement of AQP4 autoantibodies (IgG-NMO) in the development of NMO disease [4,9,10,11]. These antibodies have also been identified in patients with limited forms of this disease (recurrent idiopathic optic neuritis, etc.), but with a high risk of suffering subsequent clinical episodes. In this sense, last year, the International Panel for NMO diagnosis was convened to develop revised diagnostic criteria to include these limited forms of the disease in order to facilitate a diagnosis consensus. The new nomenclature defines the unifying term NMO spectrum disorder (NMOSD) that is stratified further by the presence or absence of IgG-NMO and the presence of an isolated or several clinical events [12]. Unfortunately, little more than 20% of patients included in the group of demyelinating disorders of the NMOSD are seronegative for anti-AQP4 antibodies [12,13]. Besides AQP4, human astrocytes in the CNS also express Aquaporin-1 (AQP1), and specifically a large expression of this protein has been detected in areas with proclivity to develop NMO-like lesions as in the spinal cord, optic nerves and in the white matter of the brain [14,15,16,17]. In the last few years, several groups [17,18,19,20] have actively searched for the presence of anti-AQP1 antibodies in the serum of patients with chronic demyelinating process of the CNS using different methods, and some conflicting findings have raised in this respect. On one side, two groups [17,18,19], one based in protein immunobloting and ELISA [17,18] and the other in results obtained from a cell based assay (CBA) using fixed HEK cells pretreated with triton [19], have demonstrated that a subgroup of patients, some of them seronegative for anti-AQP4, present antibodies anti AQP1 in serum. Such results allowed these authors to suggest that this antibody may be taken as another new classifying biomarker for these demyelinating disorders. In contrast to this, Schanda et al., [20] failed to confirm the presence of AQP1 antibodies in NMOSD patients using a live cell immunofluorescence assay. Therefore, given this scenario, we decided to explore in a cohort of 205 serums, between healthy and patients, recruited from the Neurology Service of Hospital Universitario Virgen del Rocío, the biggest hospital of Andalusia, Spain; for the presence of anti-AQP1 antibodies, with the aim of helping to establish a simple assay to identify with specificity the presence of these antibodies and contribute to clarify whether or not AQP1-antibody, should be considered as a new protagonist for the origin of NMOSD pathology. In the present work we show the results obtained using a protocol of fixed CBA with HEK cells, as published in our previous work [21], to identify presence of anti-AQP4 antibodies, after adapting the protocol in order to look for AQP1 expression as well. Serum of patients were analyzed: 8 NMOSD, 94 MS, 39 optic neuritis (ON), 29 idiopathic myelitis, 9 other idiopathic demyelinating processes of CNS, 18 other neurological disorders and 8 controls, and the assay was performed over AQP1- or AQP4-transfected HEK293 cells, either permeabilized with triton X-100 or untreated. We conclude from our results that the CBA as described in the present work or by others [20,21] does not give a specific signal that can allow for the detection of anti-AQP1 antibodies in the serum patients. However, the low number of NMOSD serums included in our analysis reduces the strength of more definitive conclusions, and we think that it would be still worth to dedicate some additional efforts to clarify whether or not anti-AQP1 antibodies are present in serum of patients, and if so, whether the presence of these antibodies may be used as a new biomarker, that could be widely used as a complement to the anti-AQP4 antibody assay that still remains as a paradigm biomarker of NMOSD diagnosis. 2. Results and Discussion Recent works have provided convincing evidences that implicate the direct participation of anti-AQP4 antibodies in the pathogenesis and diagnosis of the NMOSD [9,10,11]. Detection of IgG-anti-AQP4 in the serum of patients has become a decisive biomarker for diagnosis of most NMOSD patients but unfortunately still around 20% of NMOSD patients result in serum-negative for these antibodies [12,13]. Finding another biomarker for these disorders in these NMO-AQP4 serum negative patients would be highly desirable and has led investigators to turn their attention to AQP1, another protein of the same family of integral membrane proteins, whose expression has also been observed in the CNS in a natural way, but it is, fascinatingly, overexpressed when injury of the nervous tissue occurs [14,15,16]. Two previous works, Tzartos et al., [17] and Long et al., [19], indicated that anti-AQP1 antibodies are present in the serum of patients with NMOSD. We decided therefore to explore the presence of these antibodies in the serum of a large repertoire of patients for which detection of IgG-anti-AQP4 was previously tested using a method described in our laboratory [21], that was previously validated contrasting our results against those obtained for the same serums, by the only center of reference for diagnosis of anti-NMO antibodies in Spain (Hospital Clínic, Barcelona, Spain). We initiated the screening using the same protocol for CBA previously described [21] but now, HEK cells were transfected with human AQP1-EGFP plasmid to produce a large expression of AQP1 in the cell membrane. Readout of AQP1 expression was followed by direct appearance of green fluorescent signal coming from the EGFP fused to AQP1 (Figure 1, hAQP1-EGFP). As shown in Figure 1, total absence of AQP1 antibodies was obtained after analysis of 205 serums obtained from patients and controls (Table 1). Independently of whether the serum came from a patient diagnosed as NMOSD or not, the result was always the same: absence of fluorescent signal. The high specificity and sensitivity of the CBA used here was further verified in parallel experiments in which HEK cells were transfected with human AQP4 (Figure 1, hAQP4-EGFP), and by doing so, AQP4 antibodies were clearly detected in the serum of NMOSD patients, while they were never observed in patients with other diseases and healthy controls. Then, assuming that the discrepancy with the results obtained by others [17,18,19] was due to differences in the permeabilization procedure, we treated HEK cells with triton X-100 as indicated by Long et al. [19]. Using their permeabilization protocol, we obtained a large fluorescence signal, but it was highly unspecific, and coming from all cells in the plate regardless of whether they expressed or not AQP1 or AQP4 (Figure 2). These noisy results obtained in our hands with such a procedure led us to conclude that it is not accurate enough for the detection neither of AQP1 nor AQP4 antibodies in the serum of patients. As seen in Figure 1 and Figure 2, an apparently normal expression of the fluorescent protein hAQP1-EGFP was being produced in the transfected HEK cells. However, to further discard the possibility that AQP1 was not being inserted in an appropriate way into the plasma membrane of cells, hindering the natural recognition by antibodies which could explain the lack of immune reaction and consequent detection of AQP1 antibodies, we performed experiments using a commercial primary antibody for AQP1. Results from these analyses are shown in Figure 3. A red fluorescent signal with the IgG-antihuman AQP1 commercial was observed clearly labeling all cells expressing hAQP1-EGFP and stained in green, resulting in a perfect overlapping merge of fluorescence signals. Thereby, these results demonstrate two important findings: First, that expression of AQP1 in an antigenic way occurs in HEK cells and second, that human serums either from the NMOSD subjects or not, did not present IgG anti-AQP1 or at least not enough levels, to allow differentiation among these patients by our CBA procedure. We conclude then that the absence of anti-AQP1 antibodies observed in all the 205 serums analyzed with the CBA assay is not due to the lack of AQP1 expression in the cells, but instead is likely due to a true absence of these antibodies in the serum, at least at levels detectable with our protocol of CBA. A previous study [20], using a live CBA assay with a protocol that allowed authors for a nice detection of AQP4 antibodies in human serum, also failed to confirm the presence of AQP1 antibodies in NMOSD in agreement with results presented here by us. As indicated by Schanda et al., [20] we also agree that AQP1 antibodies in patients must react against intracellular epitopes of AQP1, otherwise patients would suffer of severe anemia due to the hemolytic action of antibodies reacting over the Colton blood group antigen present on the erythrocytes membrane, and that is not the case in any of our patients. Alternative conformational ways for expression of AQP1 in astrocytes compare to the way the protein is expressed in HEK293 cells, as indicated by Schanda et al., [20] could still offer some explanation for the lack of positive results when using CBA assays for detection of AQP1 antibodies, but all these explanations will need further experimental analysis using different experimental approaches. In that sense, we carried out experiments of ELISA to further clear this apparent discrepancy in the field and, although in few serums values of anti-AQP1 antibodies were detected (Figure 4), the overall comparative analysis of the levels of anti-AQP1 antibodies among all groups analyzed revealed no statistical differences among them, making impossible at this state for us any discussion about presence of AQP1 antibodies in those serums. Therefore, our findings with the ELISA are inconsistent with an association between presence of anti-AQP1 antibodies and NMOSD pathology. We are aware that a larger number of samples in our analysis would be desirable to increase the power of our conclusions, and for allowing us determination of the cut-off level of anti-AQP1 antibody in ELISA, but such aim was unfortunately impossible at the time of the study. Our general impression, given these results, is that AQP1 antibodies does not represent another specific biomarker of the NMOSD but its rare presence in serum of some patients as indicated by other authors [17,18,19] may probably be associated with an increased autoimmune humoral response as previously observed in patients with MS in which presence of antinuclear (ANA), anticardiolipin (ACA) and anti-Ro (SS-A) antibodies have been detected [22,23]. Like these antibodies, the presence of anti-AQP1 antibodies may be indicative of an underlying autoimmune disease; but more than associated to particular aspects of any of these diseases, it appears as an epiphenomenon of a more diffuse immunological dysfunction. Nevertheless, further analysis with the ELISA, or other immune assays, especially those with detection of the protein in suspension, accompanied with more analysis including larger number of patients on each subgroup of these diverse pathologies as well as more cases of the NMOSD would be necessary to strength our incipient hypothesis. 3. Materials and Methods 3.1. Subjects and Serum Recollection The study includes 205 subjects (135 female) classified into 7 groups based on their medical diagnosis (Table 1). Group 1 comprised 8 patients with NMOSD according to the current diagnostic criteria [12]. Group 2 consisted of 94 patients with MS according to 2010-reviewed McDonald criteria [24]. In relation to the MS course, we further divided this group into 85 patients with remitting-relapsing MS, 7 with primary progressive MS and 2 with secondary progressive form. Group 3 was composed of 39 patients with optica neuritis. Twenty-nine patients with myelitis formed group 4. Concerning to the length of the spinal cord lesion, we distinguished between patients whose lesions extended more than 3 vertebral segments (longitudinally extensive myelitis) and those with spinal plaques extended up to 3 vertebral segments (10 and 16 patients, respectively). Besides, we categorized the patients of the latter two groups depending whether they suffered an isolated episode or several relapses. Group 5 comprised 9 patients with other demyelinating idiopathic disorders of the CNS and group 6 formed by subjects with other neurological disorders, both groups described in Table 1. Besides the MRI (magnetic resonance imaging) scans and the cerebrospinal fluid analysis, peripheral blood exam that included blood count, biochemistry, erythrocyte sedimentation rate, vitamins, thyroid hormones, long chain fatty acids, angiotensin converting enzyme, immunological and serological examinations were conducted in all patients in order to exclude alternative etiologies to their final diagnosis. Finally, group 7 was composed of 8 healthy controls. 3.2. Plasmid Construction, Cell Culture and Cell Transfection The pCMV6-AC-AQP1-GFP (human AQP1-GFP) was purchased from OriGene Technologies Inc. (Rockville, MD, USA) as a plasmid ready to use in mammalian cells and the human M23-AQP4 isoform was amplified by PCR from the commercial vector pDNR-LIB cDNA (Takara Bio Europe/Clontech, Saint-Germain-en-Laye, France) using specific primers and cloned into pEGFP-N1 (Takara), for transfection and expression in the HEK293T cell line as previously described [20]. Both AQP-EGFP constructs allow synthesis of either AQP1 or AQP4 fusion fluorescent proteins with the enhanced-green-fluorescent-protein-EGFP bound to its carboxyl ends. HEK293T cells were cultured in DMEM with 10% FCS and 1% penicillin/streptomycin (37 °C, 5% CO2). Cells (2 × 105) were seeded in 35 mm dishes for transfection with Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA) as described before [21,25].Transfected cells were maintained for 25–30 passages until fluorescence signal of AQPs expression decrease below 90%. 3.3. Immunofluorescence Assay Based in a method described previously we evaluated presence of AQP1- and AQP4-Abs in the serum of patients using a protocol that we called basic assay [21]. The protocol combines expression of a fusion green fluorescent protein (AQP1- or AQP4-EGFP) with the use of a red fluorescent goat anti-human secondary antibody that, by dual labeling (green and red fluorescence), constitutes a method with extremely high sensitivity and specificity to identify positive patients for any of those antibodies. Briefly, 24 h before starting the immune-assay, HEK293T plated cells at about 80% of confluence were transfected with either AQP1- or AQP4-EGFP constructs. Then two different pretreatments were performed separately, one that we called “permeabilization” protocol, and another one called “without permeabilization”, equivalent to the original protocol described initially [21]. In the permeabilization protocol the cells were fixed with paraformaldehyde 4% (5 min) and then washed with triton X-100 2% (SIGMA, St. Louis, MO, USA) in PBS (PBTx, 10 min), before incubating (1 h) in FCS 10% with 1 mg/mL BSA in PBTx for the blocking step. Afterward, incubation with the serum’s patient (1:10 dilution for detection of anti-AQP1 and 1:50 dilution for detection of anti-AQP4, 1 h at room temperature) or with an anti-Aquaporin 1 antibody (ab 117970, ABCAM, Cambridge, UK) (1:500 dilution) raised against a full length recombinant human Aquaporin 1 produced in HEK293T cells, was followed by three times washes with PBS and then 30 min of incubation with Alexa Fluor 568 goat anti-human secondary antibody (Invitrogen, Carlsbad, CA, USA). In the method in which the cells were not permeabilized, the Triton X-100 was removed from each step. So, after fixing the cells with paraformaldehyde 4% (5 min), a washing step in PBS of 5 min was followed for a blocking period (1 h) in 10% FCS with 1 mg/mL BSA in PBS, and finally the cells were fixed (1 min), after the secondary antibody incubation, with a mixture of ethanol 95% and acetic acid 5%. Nuclei were stained with 4′,6′-diamidino-2-phenylindole (DAPI, 1:1000) and a Leica DM IRBE confocal microscope (Leica, Wetzlar, Germany) was used to observe the slides. Five photos (40×) per sample were randomly taken and the NIH ImageJ software (NIH, Bethesda, MD, USA) used for densitometry analysis of fluorescence. 3.4. ELISA for AQP1 (Aquaporin-1) 3.4.1. Preparation of AQP1 Protein Homogenate HEK293T cells were transfected with a pcDNA3-AQP1 for expression of human AQP1 protein as previously used [26,27]. After 24–48 h of transfection cells were washed with cold PBS and treated with trypsin 0.25% (GIBCO, Paisley, UK) for collection. The cell pellet was resuspended in 1 mL of cold PBS and centrifuged at 300× g for 5 min at 4 °C. For whole-cell protein extract, pellet was dissolved in 500 μL of lysis buffer: 137 mM NaCl, 20 mM Tris (pH: 8); 1% IGEPAL-CA630 (Sigma Aldrich, St. Louis, MO, USA), a nonionic, non-denaturing detergent; 10% Glycerol and 10 μL/mL of complete protease inhibitors cocktail (Sigma Aldrich). The homogenate was left on ice 15 min, vortex, and then centrifuged at 16,000× g for 15 min at 4 °C, and extracted proteins remain in the supernatant. Protein concentration was analyzed with the Bradford method (BioRad Protein Assay, BioRad, Berkeley, CA, USA) and kept at −20 °C until loading into plates for ELISA assay. 3.4.2. Adhesion of AQP1 Protein for ELISA Assay General guidelines for ELISA assay have been described elsewhere [28]. Proteins prepared as before were diluted at 20 μg/mL final concentration in 0.01 M buffer carbonate and 50 μL per well of protein suspension were loaded into a 96 well plate for ELISA (Microwell MaxiSorp, Nunc, Waltham, MA, USA), afterwards the plate was covered with a plastic film and left overnight at 4 °C. The next day the solution was removed and the plate washed three times by filling the wells with 200 μL PBS1X + 0.05% Tween and once with PBS1X. Blocking: To block the remaining protein-binding sites in the coated wells 200 μL of SuperBlock Blocking Buffer (ThermoScientific, Vantaa, Finland) were added per well and incubated at room temperature for 1 h, maintaining the plate cover with plastic film. Then, blocking solution was removed and the plate was washed three times by filling the wells again with 200 μL PBS1X + 0.05% Tween and once with PBS1X. 3.4.3. Incubation with Primary and Secondary Antibodies Two primary antibodies, 100 μL per well, were used; a commercial antibody anti-AQP1 (ab15080, ABCAM) diluted 1:10,000 in PBS with 2% BSA, that serves as a control to set the assay conditions, and the patient serums without dilution. The incubation was allowed to proceed over night at 4 °C and the next day plates were washed as indicated for removing the blocking solution mentioned above. Then, incubation with the secondary antibodies for 1 h at room temperature was carried out. Horseradish peroxidase conjugated goat anti-rabbit IgG antibody diluted (1:5000) in PBS with 2% BSA for the AQP1 commercial antibody, and horseradish peroxidase conjugated chicken anti-human IgG antibody for the patient serum antibodies were used. Wash of plates at the end was again carried out as before. 3.4.4. Signal Detection: Per Well, 100 μL of 3,3′,5,5′-Tetramethylbenzidine (TMB) TMBOne solution (Promega, Madison, WI, USA) was added and incubated at room temperature for 15 min to allow enzymatic reaction and developing of colored substrate. Then, 100 μL of HCl 1N were added per well to stop the reaction and absorbance at 450 nm was measured in a plate reader system (Multiskan Spectrum-Thermo, Vantaa, Finland). 3.5. Statistical Analysis Data are presented as mean ± standard error of the mean, and analyzed using the Statistical Package for Social Sciences (SPSS Inc., Chicago, IL, USA), version 19.0. Data with a non-normal distribution were analyzed using analysis of variance (ANOVA) for non-parametric data with the Kruskal–Wallis H test. 4. Conclusions Our study does not show sustained detection of anti-AQP1 in serum of NMOSD patients analyzed by our fixed cell based assay or ELISA protocol. To our understanding, these antibodies do not seem to allow confirmation of specific immune disorders associated with NMOSD. Acknowledgments Grants from “La Junta de Andalucía, Consejería de Innovación Ciencia y Empresa” (P08-CTS-03574) and Consejería de Salud (PI0298-2010), and from the “Instituto de Salud Carlos III” (Exp. PI12/01882) to Miriam Echevarría funded this work. We thank Genzyme Foundation in multiple sclerosis for giving to Miriam Echevarría one of their 2012 fellowships. We thank Juan Manuel Praena for his help with data plotting and statistical analysis, and Roberto Garcia Swinburn for his help with English correction of the manuscript. Author Contributions Ismael Sánchez Gomar performed and designed the experiments; María Díaz Sánchez, Antonio José Uclés Sánchez and José Luis Casado Chocán were the physicians that diagnosed and treated all patients included in the study; Nela Suárez-Luna, Javier Villadiego and Reposo Ramírez-Lorca helped with design and performed some experiments; Juan José Toledo-Aral and Miriam Echevarría contributed reagents/materials/analysis tools; María Díaz Sánchez and Miriam Echevarría, analyzed the data and wrote the paper. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Immunofluorescence assay in HEK cells expressing AQP1 or AQP4 with serum of patients. The fluorescence signal from HEK cells expressing human AQP1 (hAQP1-EGFP) or AQP4 (hAQP4-EGFP) fused to GFP is shown in green (left column). In the central panels the immune reaction produced by serum patients either from the Neuromyelitis optica spectrum disorder (+NMOSD) or not (−NMOSD) over AQP1 expressing cells revealed absence of anti-AQP1 antibodies in analyzed serums. In contrast, serum from a positive anti-AQP4 antibody patient (+NMOSD) showed clear reactivity over AQP4 expressing cells (yellow signal), while negative results are obtained in the absence of IgG anti-AQP4 in a patient (−NMOSD). The merge image of both fluorescent signals is shown in the right column. Scale bar = 50 µm. Figure 2 Immunofluorescence assay in HEK cells treated with Triton X-100. Panels are as indicated in Figure 1, but here experiments were done using a protocol of permeabilization with triton X-100 as indicated in the text (material and methods section). High background of fluorescent signal (middle column panels) was detected over all cells in the plate regardless expression or not of AQPs in them, confirming unspecific reaction. Scale bar = 20 µm Figure 3 Immunofluorescence assay with commercial antibody for AQP1. HEK cells expressing AQP1 in green (left column) immune reacted with a commercial IgG-anti-AQP1 (top middle panel, red signal), using fixed cells and without triton permeabilization. A clear and specific immune reaction was detected only in cells expressing AQP1 (merge signal in orange, top right panel). Absence of IgG anti-AQP1 was revealed in all rest of conditions tested: with an anti-human IgG secondary antibody; with human serum from a patient with NMOSD (+NMOSD); and with human serum from a patient negative for NMOSD (−NMOSD). Merge of fluorescence signal can only be seen when the commercial antibody for AQP1 was used (orange/yellow signal, top right panel). Scale bar = 15 µm. Figure 4 Detection by ELISA assay of anti-AQP1 antibodies in serum of patients. Serums from different pathologies according to the classification shown in Table 1 were analyzed including a group with the NMO spectrum disorder (+NMOSD). Abbreviations of pathologies are as indicated in Table 1. Insignificant differences were obtained among groups by analysis of variance for nonparametric data using the Kruskal–Wallis test (p = 0.067). Medians and interquartile range are represented and the number of patients analyzed per group were as follows: 8 NMOSD; 6 ON r. (Optic neuritis recurrent); 2 Sjörgen; 9 LETM (Longitudinally extensive transverse myelitis); 3 Myelitis repetition; 18 MS (Multiple sclerosis); 5 ON (Optic neuritis); 4 Control (Healthy). Circle, correspond to an outsider data point. ijms-17-01195-t001_Table 1Table 1 Demographic and clinical variables of 205 patients. Diagnosis Number of Patients (205) Gender Female/Male Mean Age at Inclusion ± SD (range) AQP4+ Antibodies AQP1+ Antibodies 1. NMOSD 8 7/1 57.14 ± 13.52 (40–80) 6 0 2. MS 94 66/28 39.87 ± 11.84 (18–76) 0 0 * RRMS 85 59/26 0 0 * PPMS 7 5/2 0 0 * SPMS 2 2/0 0 0 3. Idiopathic ON 39 27/12 39.55 ± 13.02 (14–68) 0 0 * Isolated episode 30 22/8 0 0 * Recurrent idiopathic ON 9 5/4 0 0 4. Idiopathic myelitis 29 19/10 45.13 ± 13.58 (21–69) 0 0 * Isolated episode: 26 17/9 0 0 >3 vertebral segments 10 5/5 0 0 <3 vertebral segments 16 12/4 0 0 * Recurrent idiopathic myelitis 3 2/1 0 0 5. OIDD of the CNS 9 5/4 48.88 ± 10.37 (26–60) 0 0 * ADEM 2 0/2 0 0 * Infratentorial CIS 4 2/2 0 0 * RIS 3 3/0 0 0 6. Other neurology disorders 18 8/10 51.35 ± 12.79 (26–79) 0 0 * Myelitis associated with lupus 3 3/0 0 0 * Myelitis associated with sarcoidosis 1 0/1 0 0 * ON associated with Sjögren syndrome 1 1/0 0 0 * Multifocal motor neuropathy 3 0/3 0 0 * CIDP 1 1/0 0 0 * Hereditary spastic paraparesis 1 1/0 0 0 * Spinal infraction 2 1/1 0 0 * Ischemic optic neuropathy 6 1/5 0 0 7. Healthy controls 8 6/2 36.42 ± 8.12 (27–47) 0 0 AQP: Aquaporin; CNS: central nervous system; SD: Standard deviation; NMOSD: Neuromyelitis optica syndrome disorder; ON: Optic neuritis; MS: Multiple sclerosis; RRMS: Remitting relapsing multiple sclerosis; SPMS: Secondary progressive multiple sclerosis; PPMS: Primary progressive multiple sclerosis; ADEM: Acute disseminated encephalomyelitis; CIDP: Chronic inflammatory demyelinating polyneuropathy, CIS: Clinically isolated syndrome, RIS: Radiological isolated syndrome; OIDD: Other idiopathic demyelinating disorders of the CNS. * correspond to further division of the MS group. ==== Refs References 1. Wingerchuk D.M. Lennon V.A. Lucchinetti C.F. Pittock S.J. Weinshenker B.G. The spectrum of neuromyelitis optica Lancet Neurol. 2007 6 805 815 10.1016/S1474-4422(07)70216-8 17706564 2. Uzawa A. Mori M. Kuwabara S. Neuromyelitis optica: Concept, immunology and treatment J. Clin. Neurosci. 2014 21 12 21 10.1016/j.jocn.2012.12.022 23916471 3. Lennon V.A. Wingerchuk D.M. Kryzer T.J. Pittock S.J. Lucchinetti C.F. Fujihara K. Nakashima I. Weinshenker B.G. A serum autoantibody marker of neuromyelitis optica: Distinction from multiple sclerosis Lancet 2004 364 2106 2112 10.1016/S0140-6736(04)17551-X 15589308 4. Pittock S.J. Weinshenker B.G. Lucchinetti C.F. Wingerchuk D.M. Corboy J.R. Lennon V.A. Neuromyelitis optica brain lesions localized at sites of high aquaporin 4 expression Arch. Neurol. 2006 63 964 968 10.1001/archneur.63.7.964 16831965 5. Weinshenker B.G. Wingerchuk D.M. Neuromyelitis optica: Clinical syndrome and the NMO-IgG autoantibody marker Curr. Top. Microbiol. Immunol. 2008 318 343 356 18219825 6. Amiry-Moghaddam M. Hoddevik E.H. Ottersen O.P. Aquaporins: Multifarious roles in brain Neuroscience 2010 168 859 861 10.1016/j.neuroscience.2010.04.071 20450960 7. Venero J.L. Vizuete M.L. Ilundain A.A. Machado A. Echevarria M. Cano J. Detailed localization of aquaporin-4 messenger rna in the CNS: Preferential expression in periventricular organs Neuroscience 1999 94 239 250 10.1016/S0306-4522(99)00182-7 10613514 8. Verkman A.S. Phuan P.W. Asavapanumas N. Tradtrantip L. Biology of AQP4 and anti-AQP4 antibody: Therapeutic implications for NMO Brain Pathol. 2013 23 684 695 10.1111/bpa.12085 24118484 9. Cayrol R. Saikali P. Vincent T. Effector functions of antiaquaporin-4 autoantibodies in neuromyelitis optica Ann. N. Y. Acad. Sci. 2009 1173 478 486 10.1111/j.1749-6632.2009.04871.x 19758189 10. Fujihara K. Neuromyelitis optica and astrocytic damage in its pathogenesis J. Neurol. Sci. 2011 306 183 187 10.1016/j.jns.2011.02.018 21396661 11. Lucchinetti C.F. Mandler R.N. McGavern D. Bruck W. Gleich G. Ransohoff R.M. Trebst C. Weinshenker B. Wingerchuk D. Parisi J.E. A role for humoral mechanisms in the pathogenesis of Devic’s neuromyelitis optica Brain 2002 125 1450 1461 10.1093/brain/awf151 12076996 12. Wingerchuk D.M. Banwell B. Bennett J.L. Cabre P. Carroll W. Chitnis T. de Seze J. Fujihara K. Greenberg B. Jacob A. International consensus diagnostic criteria for neuromyelitis optica spectrum disorders Neurology 2015 85 177 189 10.1212/WNL.0000000000001729 26092914 13. Melamed E. Levy M. Waters P.J. Sato D.K. Bennett J.L. John G.R. Hooper D.C. Saiz A. Bar-Or A. Kim H.J. Update on biomarkers in neuromyelitis optica Neurol. Neuroimmunol. Neuroinflamm. 2015 2 e134 10.1212/NXI.0000000000000134 26236760 14. Badaut J. Brunet J.F. Grollimund L. Hamou M.F. Magistretti P.J. Villemure J.G. Regli L. Aquaporin 1 and aquaporin 4 expression in human brain after subarachnoid hemorrhage and in peritumoral tissue Acta Neurochir. Suppl. 2003 86 495 498 14753493 15. Oshio K. Binder D.K. Liang Y. Bollen A. Feuerstein B. Berger M.S. Manley G.T. Expression of the aquaporin-1 water channel in human glial tumors Neurosurgery 2005 56 375 381 10.1227/01.NEU.0000148904.57841.6B 15670385 16. Suzuki R. Okuda M. Asai J. Nagashima G. Itokawa H. Matsunaga A. Fujimoto T. Suzuki T. Astrocytes co-express aquaporin-1, -4, and vascular endothelial growth factor in brain edema tissue associated with brain contusion Acta Neurochir. Suppl. 2006 96 398 401 16671493 17. Tzartos J.S. Stergiou C. Kilidireas K. Zisimopoulou P. Thomaidis T. Tzartos S.J. Anti-aquaporin-1 autoantibodies in patients with neuromyelitis optica spectrum disorders PLoS ONE 2013 8 1195 10.1371/journal.pone.0074773 18. Tuzun E. Tzartos J. Ekizoglu E. Stergiou C. Zisimopoulou P. Coban A. Shugaiv E. Turkoglu R. Kurtuncu M. Baykan B. Aquaporin-1 antibody in neuromyelitis optical patients Eur. Neurol. 2014 72 271 272 10.1159/000364904 25277962 19. Long Y. Zheng Y. Shan F. Chen M. Fan Y. Zhang B. Gao C. Gao Q. Yang N. Development of a cell-based assay for the detection of anti-aquaporin 1 antibodies in neuromyelitis optica spectrum disorders J. Neuroimmunol. 2014 273 103 110 10.1016/j.jneuroim.2014.06.003 24972850 20. Schanda K. Waters P. Holzer H. Aboulenein-Djamshidian F. Leite M.I. Palace J. Vukusic S. Marignier R. Berger T. Reindl M. Antibodies to aquaporin-1 are not present in neuromyelitis optica Neurol. Neuroimmunol. Neuroinflamm. 2015 2 e160 10.1212/NXI.0000000000000160 26468473 21. Sanchez Gomar I. Diaz Sanchez M. Ucles Sanchez A.J. Casado Chocan J.L. Ramirez-Lorca R. Serna A. Villadiego J. Toledo-Aral J.J. Echevarria M. An immunoassay that distinguishes real neuromyelitis optica signals from a labeling detected in patients receiving natalizumab BMC Neurol. 2014 14 1195 10.1186/1471-2377-14-139 24980919 22. De Andres C. Guillem A. Rodriguez-Mahou M. Lopez Longo F.J. Frequency and significance of anti-Ro (SS-A) antibodies in multiple sclerosis patients Acta Neurol. Scand. 2001 104 83 87 10.1034/j.1600-0404.2001.104002083.x 11493223 23. Szmyrka-Kaczmarek M. Pokryszko-Dragan A. Pawlik B. Gruszka E. Korman L. Podemski R. Wiland P. Szechinski J. Antinuclear and antiphospholipid antibodies in patients with multiple sclerosis Lupus 2012 21 412 420 10.1177/0961203311427550 22074845 24. Polman C.H. Reingold S.C. Banwell B. Clanet M. Cohen J.A. Filippi M. Fujihara K. Havrdova E. Hutchinson M. Kappos L. Diagnostic criteria for multiple sclerosis: 2010 revisions to the Mcdonald criteria Ann. Neurol. 2011 69 292 302 10.1002/ana.22366 21387374 25. Abreu-Rodriguez I. Sanchez Silva R. Martins A.P. Soveral G. Toledo-Aral J.J. Lopez-Barneo J. Echevarria M. Functional and transcriptional induction of aquaporin-1 gene by hypoxia; analysis of promoter and role of Hif-1α PLoS ONE 2011 6 1195 10.1371/journal.pone.0028385 22174795 26. Galan-Cobo A. Ramirez-Lorca R. Toledo-Aral J.J. Echevarria M. Aquaporin-1 plays important role in proliferation by affecting cell cycle progression J. Cell. Physiol. 2016 231 243 256 10.1002/jcp.25078 26081645 27. Serna A. Galan-Cobo A. Rodrigues C. Sanchez-Gomar I. Toledo-Aral J.J. Moura T.F. Casini A. Soveral G. Echevarria M. Functional inhibition of aquaporin-3 with a gold-based compound induces blockage of cell proliferation J. Cell. Physiol. 2014 229 1787 1801 10.1002/jcp.24632 24676973 28. Villadiego J. Mendez-Ferrer S. Valdes-Sanchez T. Silos-Santiago I. Farinas I. Lopez-Barneo J. Toledo-Aral J.J. Selective glial cell line-derived neurotrophic factor production in adult dopaminergic carotid body cells in situ and after intrastriatal transplantation J. Neurosci. 2005 25 4091 4098 10.1523/JNEUROSCI.4312-04.2005 15843611

PMC005xxxxxx/PMC5000594.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081196ijms-17-01196ArticleHomocysteine Aggravates Cortical Neural Cell Injury through Neuronal Autophagy Overactivation following Rat Cerebral Ischemia-Reperfusion Zhao Yaqian Huang Guowei Chen Shuang Gou Yun Dong Zhiping Zhang Xumei *Harry G. Jean Academic EditorDepartment of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin 30070, China; zyq0926@126.com (Y.Z.); huangguowei@tmu.edu.cn (G.H.); chenshuang050109@126.com (S.C.); gou.yun1990@163.com (Y.G.); dongjulia@163.com (Z.D.)* Correspondence: zhangxumei@tmu.edu.cn; Tel.: +86-22-8333-661523 7 2016 8 2016 17 8 119623 5 2016 19 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).Elevated homocysteine (Hcy) levels have been reported to be involved in neurotoxicity after ischemic stroke. However, the underlying mechanisms remain incompletely understood to date. In the current study, we hypothesized that neuronal autophagy activation may be involved in the toxic effect of Hcy on cortical neurons following cerebral ischemia. Brain cell injury was determined by hematoxylin-eosin (HE) staining and TdT-mediated dUTP Nick-End Labeling (TUNEL) staining. The level and localization of autophagy were detected by transmission electron microscopy, western blot and immunofluorescence double labeling. The oxidative DNA damage was revealed by immunofluorescence of 8-Hydroxy-2′-deoxyguanosine (8-OHdG). Hcy treatment aggravated neuronal cell death, significantly increased the formation of autophagosomes and the expression of LC3B and Beclin-1 in the brain cortex after middle cerebral artery occlusion-reperfusion (MCAO). Immunofluorescence analysis of LC3B and Beclin-1 distribution indicated that their expression occurred mainly in neurons (NeuN-positive) and hardly in astrocytes (GFAP-positive). 8-OHdG expression was also increased in the ischemic cortex of Hcy-treated animals. Conversely, LC3B and Beclin-1 overexpression and autophagosome accumulation caused by Hcy were partially blocked by the autophagy inhibitor 3-methyladenine (3-MA). Hcy administration enhanced neuronal autophagy, which contributes to cell death following cerebral ischemia. The oxidative damage-mediated autophagy may be a molecular mechanism underlying neuronal cell toxicity of elevated Hcy level. homocysteineautophagyreperfusion injuryneuronsoxidative stress ==== Body 1. Introduction Stroke is one of the world’s leading causes of death and disability. Ischemic stroke, which accounts for approximately 85% of all strokes, occurs when there is an acute blockage of arterial blood flow to the brain tissue [1]. Homocysteine (Hcy), a sulphur-containing amino acid, does not appear to have any inherent function in the body except as a part of the methionine pathway [2]. However, it is known to have various toxic effects in the body, so any accumulation can be detrimental. The accumulation of Hcy not only increases stroke incidence but also provokes neurological deficit after stroke [3,4]. Elevated Hcy levels directly augment brain damage and induce neuronal cell death after cerebral ischemia/reperfusion [5]. It has been reported that the underlying molecular mechanisms for the neurotoxic effects of Hcy may involve the excessive activation of glutamate receptors, a rise in free calcium concentration, the disruption of DNA and the generation of reactive oxygen species (ROS) [6,7,8]. Despite this valuable study evidence, the understanding of Hcy toxicity remains incomplete. Elucidating the link between Hcy and brain cell injury is vital for improving the prevention and treatment of homocysteine-related central nervous system (CNS) disorders. Autophagy is a highly regulated process that breaks down organelles and macromolecules through lysosomal degradation. Recently, it was shown that autophagy also plays an important role in regulating neuronal survival or death in cerebral ischemia [9]. However, whether the autophagy is cell-protective or cell-destructive is still under debate. Carloni et al. indicated that activation of autophagy protects neurons from ischemia-induced death [10], whereas another study indicated that the excessive autophagy contributes to neuron damage or death in cerebral ischemia with increased levels of light chain 3 (LC3)-II and Beclin-1 [11]. In addition to the dual role, the possible regulation of autophagic cell death after cerebral ischemia is also largely unknown. It is widely accepted that accumulation of ROS induces autophagy, and that autophagy, in turn, serves to reduce ROS levels. On the other hand, one of homocysteine’s main mechanisms of neurotoxicity is oxidative stress, which involves the formation of ROS [12]. Therefore, it is possible that ROS-mediated autophagy may be related to the neurotoxicity of Hcy in ischemia brain. Furthermore, in cardiomyocytes, Hcy has been reported to activate mitochondrial autophagy through cardiac-specific NMDA-R1 receptor [13]. There is currently no information concerning a possible association between Hcy and autophagy in ischemia brain cells. Therefore, we hypothesize that the changes in autophagy level may be involved in Hcy-induced brain damage after ischemia stroke, and ROS may be a possible link between Hcy and autophagy. The present study was designed to elucidate the neurotoxic effect of Hcy on ischemia brain and to determine its underlying mechanisms. Here, we provide evidence that Hcy-triggered autophagy contributes to brain neuronal cell injury and show it was accompanied by oxidative damage. 2. Results 2.1. Serum Hcy Concentration of Rats The treatment of Hcy for 3 wk resulted in a notably higher plasma Hcy concentration in middle cerebral artery occlusion-reperfusion + homocysteine (MCAO + HCY) group and MCAO + HCY + 3-methyladenine (3MA) group, compared with MCAO animals (p < 0.05). The serum Hcy level after intervention was also significantly higher than the Hcy concentration before intervention (p < 0.05) (Table 1). 2.2. Hcy-Induced Neural Cell Injury in Ischemia Brain by Observation of Pathological Morphology and Apoptosis Neuronal morphology of the rat brain was observed 72 h after MCAO by HE staining (Figure 1A). The neuronal cells in the SHAM group were arranged regularly, and the structures of neurons were clear with round, large and regular nuclei. After MCAO, most cells were arranged disorderly, with pyknotic or severely shrunken nuclei in the penumbral region. The morphology changes in the MCAO + HCY group were more severe than in the MCAO group. Compared with the MCAO + HCY group, less cellular damage was observed, and some neurons showed slightly shrunken perikarya and nuclei in the MCAO + HCY + 3MA group. TUNEL staining was used to detect cellular apoptosis in ischemic rat brain. Apoptotic cells had typical dark brown apoptotic bodies as shown in Figure 1B,D. Compared with the SHAM group, the apoptosis rate in the brain was significantly increased following brain injury (p < 0.05). The increase in the apoptosis rate was more significant in the MCAO + HCY group (p < 0.05, vs. MCAO group). Moreover, compared with the MCAO + HCY group, the apoptosis rate was significantly decreased in the MCAO + HCY + 3MA group (p < 0.05). These analyses showed that Hcy could cause brain injury, whereas 3-MA partially blocked the toxic effects of Hcy on brain cells after ischemic attack. 2.3. Hcy Induced Autophagosomes Accumulation and Protein Expression of LC3B and Beclin-1 in Cortex Neurons Following MCAO Injury Autophagy is the main pathway leading to the sequestration of the cytoplasm into the lysosome. To show whether autophagy is involved in cell death in Hcy-treated MCAO rats, transmission electron microscope (TEM) was used to directly observe the formation of autophagosomes 24 h after brain injury. As shown in Figure 2A, the TEM image of the SHAM group displayed healthy nuclei and mitochondria, abundant endoplasmic reticula, some lysosomes and many free ribosomes. In contrast, in the MCAO group, the mitochondria were visibly swollen with partially broken or disorganized cristae, the rough endoplasmic reticula developed cystic degeneration and free ribosomes decreased significantly. A few double membrane-bound compartments that contained cytoplasmic material (autophagosomes) were visible. Neuronal damage was more pronounced accompanied by more organelle lysis, and autophagosomes were frequently observed in the MCAO + HCY group than that in the MCAO group. The appearance of neurons and their organelles were less damaged, and the number of autophagosomes was also reduced in the MCAO + HCY + 3MA group compared with the MCAO + HCY group. To further confirm that Hcy enhanced autophagic activity in the ischemia brain, we analyzed the expression of microtubule-associated protein 1A light chain 3 (LC3B) and Beclin-1 proteins in the ischemic cortex 24 h after brain injury by western blot. Ischemia injury resulted in a significant increase in LC3B and Beclin-1 protein expression compared to the SHAM group (p < 0.05) (Figure 2B,C). The protein levels of LC3B and Beclin-1 were increased in the MCAO + HCY group compared with the MCAO group (p < 0.05). There was also a significant difference in the level of LC3B (Beclin-1) between the MCAO + HCY group and MCAO + HCY + 3MA group (p < 0.05). These findings further suggest that Hcy increased the protein expression of autophagy-related markers. However, 3MA treatment can reverse the effects of Hcy on autophagy in damaged brain. 2.4. Hcy Induced LC3B and Beclin-1 Protein Accumulation in Neurons Not Astrocytes Following Ischemia by Immunofluorescence To determine whether high levels of LC3B and Beclin-1 by Hcy treatment occur in a specific population of cells after cerebral ischemia, we co-stained for LC3B (or Beclin-1) and NeuN (neuron marker) (or glial fibrillary acidic protein (GFAP, astrocyte marker)). Co-staining with NeuN and LC3B (or Beclin-1) demonstrated that LC3B (or Beclin-1) was mostly present in neurons of the ischemic penumbra of cortex, and the ratio of LC3B (or Beclin-1) positive neurons and all LC3B (or Beclin-1) positive cells was close to 100% (Figure 3A,B). However, LC3B (or Beclin-1) and GFAP were not expressed in the same cell (Figure 4A,B). Moreover, immunofluorescent staining of LC3B (or Beclin-1) and NeuN showed that the number of LC3B (or Beclin-1) positive neurons in the MCAO group was significantly higher than that in the SHAM group. There was also a marked increase in the number of LC3B (or Beclin-1) and NeuN double-positive cells in the MCAO + HCY group (vs. the MCAO group, p < 0.05). However, the administration of 3MA and Hcy caused a significant reduction in the number of both LC3B positive and Beclin-1 positive neurons (vs. the MCAO + HCY group, p < 0.05). High expression levels of LC3B and Beclin-1 in the MCAO + HCY group suggested that Hcy significantly enhanced ischemia-induced activation of neuronal autophagy. 2.5. Hcy Increased 8-OHdG Protein Expression Following Ischemia The molecular mechanisms underlying Hcy-induced autophagy in rat brain remain to be determined. 8-OHdG is a sensitive marker of oxidative DNA damage and oxidative stress. In this study, we examined whether the injured neural cells were oxidatively stressed by a high level of Hcy using 8-OHdG as a marker. Immunofluorescent staining of 8-OHdG showed that numbers of 8-OHdG positive cells were significantly higher in the MCAO + HCY group, compared with the MCAO group. However, autophagy inhibitor 3-MA and Hcy joint intervention reduced 8-OHdG expression (Figure 5). 3. Discussion As a risk factor for cerebral ischemia, homocysteine has attracted great attention, yet its neurotoxicity in the ischemia brain is unclear. In the present study, we used the model of focal ischemia to examine neural cell injury and the level of autophagy following Hcy treatment. Our results demonstrated that focal cerebral ischemia-reperfusion significantly induced brain neuronal injury. The cortex damage of the MCAO + HCY group was more severe than in the MCAO group, indicating that hyperhomocysteinemia aggravated cortex damage after ischemia-reperfusion. Hcy could also induce autophagosome accumulation, upregulate LC3B/Beclin-1 protein expression, and increase the generation of 8-OHdG. We consistently observed that autophagy stimulation by Hcy occurred mainly in cortex neurons, but not in the astrocytes with the upregulation of LC3B/Beclin-1. This study demonstrated for the first time that Hcy caused autophagy overactivation in cortical neurons following brain injury. The autophagy-promoting effects of Hcy were significantly ameliorated by inhibition of autophagy. Our results suggested that autophagy plays a crucial role in Hcy-induced injury of cells, and the oxidative damage may be involved in the mechanism. Autophagy is an evolutionarily conserved lysosomal degradation process that serves an important mechanism for protein turnover, organelle maintenance, and the cellular stress response and is therefore essential for neuronal survival and function [14]. Previous studies in several models of cerebral ischemia (transient global ischemia [15], focal ischemia [16], and cerebral ischemia-hypoxia [17]) indicated that autophagy is involved in the ischemic brain injury, but whether it protects from or causes disease is unclear [18,19]. Autophagy activation is associated with neuroprotection in a rat model of focal cerebral ischemic preconditioning [18]. Zhang et al. showed that autophagy plays different roles in cerebral ischemia and subsequent reperfusion, and the elevated autophagy in the reperfusion phase after ischemia protects against neuronal injury by mitochondrial clearance [20]. On the other hand, it has shown that combination of ischemia and hypoxia is a powerful stimulus for autophagic lysosomal cell death in brain [21,22]. In this study, we found that the formation of autophagosomes and neuronal cell injuries were significantly increased in the brain cortex after MCAO. These effects were magnified by the increased Hcy levels. Taken together, the results suggest hyperhomocysteinemia may cause an overactivation of autophagy, which seems to be harmful for the ischemia brain. Conversely, the autophagic inhibitor 3-MA provided protection against cortical neuronal death and inhibited Hcy-enhanced autophagy after ischemia. Thus, whether autophagy is beneficial or destructive seems to depend on different types of external stimuli or the extent of autophagy, which may represent a master switch between cell death and survival after brain ischemia. It has been reported that several key proteins govern the autophagy pathway, including Beclin-1 and LC3 [14]. Beclin-1, central to the regulation of autophagy, is involved in the formation of autophagosomes via membrane recruitment [23]. LC3 is another important molecule for autophagy as a constituent of the autophagosome membrane [24]. LC3 alone or together with Beclin-1 is often used as the marker of autophagy [25]. The enhanced expression of Beclin-1 and LC3 has been observed in brain cells after focal ischemia [22]. Consistent with the previous study, we also found that the levels of LC3B and Beclin-1 were increased after cerebral ischemia. Furthermore, we showed that Hcy treatment enhanced the autophagy with the increased levels of LC3B and Beclin-1 protein after cerebral ischemia. Double staining with NeuN (GFAP) and LC3B (Beclin-1) demonstrated that increased LC3B (Beclin-1) expression was mainly present in the neurons as opposed to the astrocytes of the ischemic penumbra of cortex. It is suggested that the elevated autophagy, which was localized primarily in neurons, may be at least partly responsible for neural injuries caused by Hcy treatment. The neurons seem to be more sensitive to Hcy than the other cell types in the brain cortex and exhibit a stronger autophagic response to Hcy stress. It has been extensively reported that the autophagic inhibitor 3-MA exhibits neuroprotective effects in cerebral ischemia animal models. Previous studies in several models of cerebral ischemia (permanent focal cerebral ischemia [26], cerebral ischemia/reperfusion injury [27,28]) indicated that treatment of 3-MA significantly reduced the brain infarct volume. Xing et al. reported that 3-MA treatment decreased the neuronal loss and apoptosis in the ipsilateral thalamus following focal cerebral infarction [19]. In our study, we focus on the regulatory role of Hcy in neural cell injury by autophagy, so a control group of MCAO + 3-MA could not be set alone. Despite this, it would be more helpful to elucidate the neurotoxic mechanisms of homocysteine if the MCAO + 3MA group had been set. In addition, our data obtained with LC3 and Beclin-1 by western blot are markedly different from those observed in immunofluorescence studies. The lack of parallel increase in LC3 and Beclin-1 density in immunofluorescence and western blot levels may be due to differences in the cortical areas analyzed. For western blot, the intact cortex was separated from the rat brain, while for immunofluorescence staining, cell counting was performed in two selected cortical areas which may not represent the intact cortex. Cellular oxidative stress or increased generation of ROS has been reported to modulate autophagy activation in response to various stressful stimuli such as nutrient deprivation, ischemia/reperfusion and hypoxia [29,30,31,32]. For instance, an activation of autophagy contributes to neuronal cell death in neonatal rat brain exposed to hypoxia ischemia, and this is oxidative stress dependent [33]. On the other hand, oxidative stress is considered as one of the earliest events and a pathological mechanism through which hyperhomocysteinemia contributes to neurodegenerative diseases [34,35]. Oxidative damage to the cells has been reported to be associated with the autooxidation of Hcy and triggers the production of ROS [36]. The oxidized product of DNA, 8-OHdG, is the most frequently measured biomarker of the oxidative stress [37]. In this study, we found that a high Hcy level led to an increase in the 8-OHdG level and caused neural injury in the MCAO model. It is suggested that oxidative stress generation may be involved in Hcy-induced autophagy in ischemia brains. Further investigations are required to clarify the precise molecular mechanisms through which Hcy activates the oxidative stress pathway and induces autophagy in neuronal cells. In summary, the present study demonstrated that an elevated Hcy level could enhance autophagy and aggravate neuronal cell injury following focal cerebral ischemia-reperfusion with the generation of autophagosomes and the upregulation of LC3B/Beclin-1 protein expression in neurons. Conversely, the autophagic inhibitor 3-MA could inhibit autophagy activation and ameliorate the ischemic injury caused by Hcy treatment. The oxidative stress might serve as a possible link between the overactivation of autophagy and the elevated Hcy level for ischemic stroke. Furthermore, our results supported the notion that a moderate level of autophagy may be the key for neuronal survival, while excessive induction of autophagy may aggravate cell injury or death in ischemia brain. The study may be helpful for future therapeutic efforts for autophagy-related diseases. 4. Materials and Methods 4.1. Experimental Design Eighty male Sprague Dawley rats weighing 180–200 g (Grade SPF, Certificate Number SCXK (Jing) 20120001) were purchased from the Peking Weitonglihua Laboratory Animal Center (Beijing, China). Animal housing and application of experimental procedures were in accordance with institutional guidelines under approved protocols. All animal protocols were approved by the Institutional Animal Care and Use Committee of Tianjin Medical University (Number: TMUaMEC2012016). The rats were randomly assigned to four groups: sham operation control group (SHAM), middle cerebral artery occlusion-reperfusion group (MCAO), MCAO plus homocysteine (Sigma, St. Louis, MO, USA; 1.6 mg/kg/day) group (MCAO + HCY), and MCAO, homocysteine (1.6 mg/kg/day) plus 3-methyladenine (Sigma, 5 mmol/L, 4 mL/kg/day) group (MCAO + HCY + 3MA). Homocysteine was administered by tail vein injection for 21 days prior to SHAM or MCAO operation. The 3-methyladenine was administered by tail vein injection for 5 days prior to SHAM or MCAO operation. 4.2. Surgical Procedures The rats were anesthetized with 10% chloral hydrate (3 mL/kg). Temporary focal middle cerebral artery occlusion-reperfusion (MCAO) was induced by the modified Longa method [38]. The left external carotid artery was tied up and the internal carotid artery was closed. A nylon thread was advanced through the left internal carotid artery to the origin of the middle cerebral artery (MCA). One hour after the operation, the thread was pulled out 1 cm and cut off. Rats subjected to the SHAM operation were treated similarly, while the thread was not advanced to the origin of the MCA. The animals were separately sacrificed at 24 and 72 h after reperfusion for the following experiments. The modified Longa method was used to assess the neurological deficit [38]. A neurological score was assigned to each rat as follows: 0 = no deficit; 1 = contralateral forelimb weakness; 2 = circling to contralateral side; 3 = partial paralysis on contralateral side; and 4 = no spontaneous motor activity. Rats treated with the MCAO procedure with neurological deficit scores of 1–3 were selected for subsequent experiments. 4.3. Serum Homocysteine Concentration Blood (1 mL) was taken from rats by the angular vein before intervention and the surgical operation, and centrifugalized at 3000 rpm for 10 min. The supernatant was collected. The serum Hcy was measured using a cycling enzymatic method with a commercially available kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, China), and analyzed with an automatic biochemical analyzer (CS T300, Dirui Medical Technology Ltd., Changchun, China). 4.4. Transmission Electron Microscopy (TEM) Transmission electron microscopy was used to identify ultrastructural changes in cortical neurons 24 h after brain injury. Fragments of the cerebral cortex were fixed with 2.5% glutaraldehyde solution, fixed with 1% osmic acid, gradient acetone dehydrated, and then the samples were embedded in an Epon/Araldite mixture. Embedded fragments were then sliced and stained with uranyl acetate and lead citrate, and viewed under a HT-7700 TEM (Hitachi, Tokyo, Japan). 4.5. Preparation of Paraffin Section Rats were separately anaesthetized 24 and 72 h after reperfusion (24 h for immunofluorescence and 72 h for HE and TUNEL). Then, the rats were perfused with 0.9% saline solution followed by 4% phosphate-buffered paraformaldehyde (PFA). Afterwards, brains were removed, postfixed, equilibrated in 30% sucrose in phosphate-buffered saline and embedded in paraffin. Coronal sections at 6 μm were used for immunofluorescence, HE and TUNEL. 4.6. HE and TUNEL Staining Brain cortex paraffin sections were stained with HE for routine examinations and photographed using a light microscope (IX81; Olympus, Tokyo, Japan). Apoptotic cells in brain tissue sections were identified by in situ cell death detection kit (Roche Company, Basel, Switzerland) as described previously [39]. Paraffin sections were deparaffinized, treated with 3% hydrogen peroxide and TdT-enzyme, incubated with digoxigenin-conjugated antibodies and colorized with DAB (Solarbio, Beijing, China). Sections were photographed using a light microscope (IX81; Olympus). Positive neurons were counted using Image Pro Plus 6.0 (Media Cybernetics, Silver Spring, MD, USA). 4.7. Immunofluorescence Sections were de-waxed and hydrated to dispose 3% H2O2 for 10 min at room temperature, then repaired by citric acid antigen, blocked with goat serum for 40 min at 37 °C, incubated with the first antibody (LC3B (1:400; Cell Signaling Technology, Boston, MA, USA), Beclin-1 (1:200; Abcam, Cambridge, MA, USA), 8-Hydroxyguanosine (8-OHdG; 1:500; Abcam), NeuN (1:1000; Abcam) and GFAP (1:100; Abcam)) overnight at 4 °C and incubated with the goat anti-rabbit or goat anti-mouse secondary antibodies (1:100; Zhongshan Goldbridge Biotechnology, Beijing, China) for 1 h at 25 °C. A fluorescence microscope (IX81; Olympus) was used to observe and photograph. Positive cells were counted by Image Pro Plus 6.0. 4.8. Western Blot Rats were sacrificed 24 h after reperfusion. Western blot was used to analyze protein expression in the ischemic cortex. In brief, the brain tissues were homogenized in RIPA buffer (20 mmol/L TRIS-HCl pH 7.5, 150 mmol/L NaCl, 1 mmol/L EDTA, 1% Triton-X100, 0.5% sodium deoxycholate, 1 mmol/L PMSF and 10 µg/mL leupeptin), incubated on ice for 30 min, and centrifuged at 14,000× g for 25 min at 4 °C. The supernatants were collected, and protein concentration was detected with BSA as a standard according to the Bradford method [40]. Equal amounts of protein from each sample were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to nitrocellulose blotting membranes (NC membranes; Millipore, Bedford, MA, USA) by the wet electrical transfer method. The membranes were then blocked with 5% milk (Sigma) in 1× TBST for 1 h at room temperature, followed by incubation with the primary antibodies (LC3B 1:1000, Beclin-1 1:500, β-actin (1:10,000; Abcam)) overnight at 4 °C and incubated with the goat anti-rabbit or goat anti-mouse secondary antibodies (1:10000; Zhongshan Goldbridge Biotechnology) for 1 h at 25 °C. Then, the blots were developed by immobilon western chemiluminescent horseradish peroxidase substrate (Millipore) and observed using a ChemiDocTM XRS+ Imaging System (Bio-RAD, Hercules, CA, USA). The protein levels were quantified by densitometry using Image J 1.4.3 Software (National Institutes of Health, Bethesda, MD, USA) and calculated according to the reference bands of β-actin. 4.9. Statistical Analysis Statistical analysis was performed using SPSS, version 19.0 (SPSS, Chicago, IL, USA). The results are presented as mean ± standard deviation (x¯ ± s). Differences between means were evaluated by one-way analysis of variance (ANOVA) followed by Least Significant Difference (LSD) multiple range test if data conformed to normality and homogeneity of variance, or using a non-parametric method (Kruskal–Wallis test) followed by the Mann–Whitney U-test using Bonferroni correction if not. p < 0.05 was considered to be statistically significant. Acknowledgments This work was supported by grants from the National Natural Science Foundation of China (81373003) and the China Postdoctoral Science Foundation (2014M550148). Author Contributions Xumei Zhang, Guowei Huang, Yaqian Zhao conceived and designed the study. Yaqian Zhao, Shuang Chen, Yun Gou, Zhiping Dong performed experiments. Yaqian Zhao analyzed data. Yaqian Zhao and Xumei Zhang wrote the manuscript. All authors edited the manuscript and approved the submitted version. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The effect of Hcy on neuronal death in ipsilateral cortex penumbra after rat focal cerebral ischemia-reperfusion. (A) Histologic outcomes of HE staining; (B) Photomicrographs of the cortex penumbra of rat brains used for the TUNEL assay. The positive cells were stained in dark brown and are indicated by arrows; (C) Schematic showing examples of the areas (black squares) that were selected for counting of apoptotic cells in the cortex penumbra; (D) Quantification of apoptotic cells by the TUNEL assay. Apoptosis was expressed as the ratio of apoptotic cells to total cells. The data are expressed as x¯ ± s. a p < 0.05 vs. SHAM group; b p < 0.05 vs. MCAO group; c p < 0.05 vs. MCAO + HCY group. n = 3/group. Scale bars = 50 μm. Figure 2 The effect of Hcy on neuronal ultrastructure and autophagic-related protein expression in the cortex after rat focal cerebral ischemia-reperfusion. (A) The TEM analysis of ultrastructural changes in cortical neurons 24 h after the reperfusion (n = 3 for each group). Arrows indicate autophagosomes. N represents the nucleus. Scale bars = 1 μm; (B,C) Representative western blots for LC3B and Beclin-1 and bar graphs show semiquantitative levels of LC3B/β-actin and Beclin-1/β-actin by band density analysis. The data are presented as the x¯ ± s. a p < 0.05 vs. SHAM group, b p < 0.05 vs. MCAO group, c p < 0.05 vs. MCAO + HCY group. n = 4 for each group. Figure 3 Immunofluorescence of LC3B and Beclin-1 in neurons after cerebral ischemia -reperfusion injury. (A,B) Double staining for LC3B/Beclin-1 (green) and NeuN (red) showed that increased expression of LC3B/Beclin-1 occurred mostly in cortical neurons; (C) Schematic showing examples of the areas (black squares) that were selected for counting of LC3B/Beclin-1 positive neurons in the ipsilateral cortex penumbra; (D,E) Quantitative assessment of LC3B/Beclin-1 positive neurons in rat brain cortex penumbra per field. Four rats in each group and 10 fields for each rat were examined. Data are expressed as x¯ ± s. a p < 0.05 vs. SHAM group, b p < 0.05 vs. MCAO group, c p < 0.05 vs. MCAO + HCY group. Scale bars = 50 μm. Figure 4 Immunofluorescence of LC3B and Beclin-1 in astrocytes after cerebral ischemia -reperfusion injury. (A,B) The analysis of the triple staining for LC3B/Beclin-1 (green), GFAP (red) and DAPI (nuclei marker, blue) of sections in the cortex indicates that LC3B/Beclin-1 was hardly expressed in astrocytes. Scale bars = 50 μm. n = 4/group. Figure 5 Immunofluorescence of 8-OHdG in the cortex penumbra after ischemia-reperfusion injury. (A) Double staining for 8-OHdG (red) and DAPI (blue) in cortex penumbra; (B) Quantitative assessment of 8-OHdG positive cells per field. Four rats in each group and 10 fields for each rat were examined. Data are expressed as x¯ ± s. a p < 0.05 vs. SHAM group, b p < 0.05 vs. MCAO group, c p < 0.05 vs. MCAO + HCY group. Scale bars = 50 μm. ijms-17-01196-t001_Table 1Table 1 The concentration of serum Hcy before and after intervention in rats. Groups Before Intervention (μM) After Intervention (μM) SHAM 5.40 ± 2.72 5.20 ± 2.02 MCAO 7.20 ± 0.80 6.90 ± 2.47 MCAO + HCY 7.00 ± 1.77 15.07 ± 2.66 a,b,* MCAO + HCY + 3MA 6.40 ± 2.26 10.53±0.83 a,b,* Data are expressed as x¯ ± s (n = 5). a p < 0.05 vs. the sham operation control (SHAM) group, b p < 0.05 vs. MCAO group, * p < 0.05 vs. the concentration of Hcy before intervention. ==== Refs References 1. Yang Y. Gao K. Hu Z. Li W. Davies H. Ling S. Rudd J.A. Fang M. Autophagy upregulation and apoptosis downregulation in DAHP and triptolide treated cerebral ischemia Mediat. Inflamm. 2015 2015 120 198 10.1155/2015/120198 25729215 2. Savage S. Ma D. The neurotoxicity of nitrous oxide: The facts and “putative” mechanisms Brain Sci. 2014 4 73 90 10.3390/brainsci4010073 24961701 3. Bostom A.G. Rosenberg I.H. Silbershatz H. Jacques P.F. Selhub J. D’Agostino R.B. Wilson P.W. Wolf P.A. Nonfasting plasma total homocysteine levels and stroke incidence in elderly persons: The Framingham Study Ann. Intern. Med. 1999 131 352 355 10.7326/0003-4819-131-5-199909070-00006 10475888 4. Jiang B. Chen Y.M. Yao G.E. Yao C.S. Zhao H.M. Jia X.D. Zhang Y.Y. Ge J.L. Qiu E.C. Ding C.Y. Effects of differences in serum total homocysteine, folate, and vitamin B12 on cognitive impairment in stroke patients BMC Neurol. 2014 14 10.1186/s12883-014-0217-9 25433800 5. Waeckel L. Bignon J. Liu J.M. Markovits D. Ebrahimian T.G. Vilar J. Mees B. Blanc-Brude O. Barateau V. Le Ricousse-Roussanne S. Tetrapeptide AcSDKP induces postischemic neovascularization through monocyte chemoattractant protein-1 signaling Arterioscler. Thromb. Vasc. Biol. 2006 26 773 779 10.1161/01.ATV.0000203510.96492.14 16410461 6. Obeid R. Herrmann W. Mechanisms of homocysteine neurotoxicity in neurodegenerative diseases with special reference to dementia FEBS Lett. 2006 580 2994 3005 10.1016/j.febslet.2006.04.088 16697371 7. Poddar R. Paul S. Homocysteine-NMDA receptor-mediated activation of extracellular signal-regulated kinase leads to neuronal cell death J. Neurochem. 2009 110 1095 1106 10.1111/j.1471-4159.2009.06207.x 19508427 8. Kruman I.I. Culmsee C. Chan S.L. Mattson M.P. Homocysteine elicits a DNA damage response in neurons that promotes apoptosis and hypersensitivity to excitotoxicity J. Neurosci. 2000 20 6920 6926 10995836 9. Ginet V. Spiehlmann A. Rummel C. Rudinskiy N. Grishchuk Y. Luthi-Carter R. Clarke P.G. Truttmann A.C. Puyal J. Involvement of autophagy in hypoxic-excitotoxic neuronal death Autophagy 2014 10 846 860 10.4161/auto.28264 24674959 10. Carloni S. Buonocore G. Balduini W. Protective role of autophagy in neonatal hypoxia-ischemia induced brain injury Neurobiol. Dis. 2008 32 329 339 10.1016/j.nbd.2008.07.022 18760364 11. Shi R. Weng J. Zhao L. Li X.M. Gao T.M. Kong J. Excessive autophagy contributes to neuron death in cerebral ischemia CNS Neurosci. Ther. 2012 18 250 260 10.1111/j.1755-5949.2012.00295.x 22449108 12. Guidi I. Galimberti D. Lonati S. Novembrino C. Bamonti F. Tiriticco M. Fenoglio C. Venturelli E. Baron P. Bresolin N. Oxidative imbalance in patients with mild cognitive impairment and Alzheimer’s disease Neurobiol. Aging 2006 27 262 269 10.1016/j.neurobiolaging.2005.01.001 16399211 13. Tyagi N. Vacek J.C. Givvimani S. Sen U. Tyagi S.C. Cardiac specific deletion of N -methyl-d -aspartate receptor 1 ameliorates mtMMP-9 mediated autophagy/mitophagy in hyperhomocysteinemia J. Recept. Signal Transduct. Res. 2010 30 78 87 10.3109/10799891003614808 20170426 14. Merenlender-Wagner A. Malishkevich A. Shemer Z. Udawela M. Gibbons A. Scarr E. Dean B. Levine J. Agam G. Gozes I. Autophagy has a key role in the pathophysiology of schizophrenia Mol. Psychiatry 2015 20 126 132 10.1038/mp.2013.174 24365867 15. Nitatori T. Sato N. Waguri S. Karasawa Y. Araki H. Shibanai K. Kominami E. Uchiyama Y. Delayed neuronal death in the CA1 pyramidal cell layer of the gerbil hippocampus following transient ischemia is apoptosis J. Neurosci. 1995 15 1001 1011 7869078 16. Adhami F. Schloemer A. Kuan C.K. The roles of autophagy in cerebral ischemia Autophagy 2007 3 42 44 10.4161/auto.3412 17035724 17. Zhu C. Wang X. Xu F. Bahr B.A. Shibata M. Uchiyama Y. Hagberg H. Blomgren K. The influence of age on apoptotic and other mechanisms of cell death after cerebral hypoxia-ischemia Cell Death Differ. 2005 12 162 176 10.1038/sj.cdd.4401545 15592434 18. Yan W. Zhang H. Bai X. Lu Y. Dong H. Xiong L. Autophagy activation is involved in neuroprotection induced by hyperbaric oxygen preconditioning against focal cerebral ischemia in rats Brain Res. 2011 1402 109 121 10.1016/j.brainres.2011.05.049 21684529 19. Xing S. Zhang Y. Li J. Zhang J. Li Y. Dang C. Li C. Fan Y. Yu J. Pei Z. Beclin 1 knockdown inhibits autophagic activation and prevents the secondary neurodegenerative damage in the ipsilateral thalamus following focal cerebral infarction Autophagy 2012 8 63 76 10.4161/auto.8.1.18217 22108007 20. Zhang X. Yan H. Yuan Y. Gao J. Shen Z. Cheng Y. Shen Y. Wang R.R. Wang X. Hu W.W. Cerebral ischemia-reperfusion-induced autophagy protects against neuronal injury by mitochondrial clearance Autophagy 2013 9 1321 1333 10.4161/auto.25132 23800795 21. Adhami F. Liao G. Morozov Y.M. Schloemer A. Schmithorst V.J. Lorenz J.N. Dunn R.S. Vorhees C.V. Wills-Karp M. Degen J.L. Cerebral ischemia-hypoxia induces intravascular coagulation and autophagy Am. J. Pathol. 2006 169 566 583 10.2353/ajpath.2006.051066 16877357 22. Rami A. Langhagen A. Steiger S. Focal cerebral ischemia induces upregulation of Beclin 1 and autophagy-like cell death Neurobiol. Dis. 2008 29 132 141 10.1016/j.nbd.2007.08.005 17936001 23. Choubey V. Cagalinec M. Liiv J. Safiulina D. Hickey M.A. Kuum M. Liiv M. Anwar T. Eskelinen E.L. Kaasik A. BECN1 is involved in the initiation of mitophagy: It facilitates PARK2 translocation to mitochondria Autophagy 2014 10 1105 1119 10.4161/auto.28615 24879156 24. Liao W. Sun L. Wang C. Huang H. Liu J. Liao W. Shi M. LC3A-positive “stone-like” structures predict an adverse prognosis of gastric cancer Anat. Rec. 2014 297 653 662 10.1002/ar.22895 24532538 25. Deng Q. Wang Z. Wang L. Zhang L. Xiang X. Wang Z. Chong T. Lower mRNA and protein expression levels of LC3 and Beclin1, markers of autophagy, were correlated with progression of renal clear cell carcinoma Jpn. J. Clin. Oncol. 2013 43 1261 1268 10.1093/jjco/hyt160 24186908 26. Wen Y.D. Sheng R. Zhang L.S. Han R. Zhang X. Zhang X.D. Han F. Fukunaga K. Qin Z.H. Neuronal injury in rat model of permanent focal cerebral ischemia is associated with activation of autophagic and lysosomal pathways Autophagy 2008 4 762 769 10.4161/auto.6412 18567942 27. Lu T. Jiang Y. Zhou Z. Yue X. Wei N. Chen Z. Ma M. Xu G. Liu X. Intranasal ginsenoside Rb1 targets the brain and ameliorates cerebral ischemia/reperfusion injury in rats Biol. Pharm. Bull. 2011 34 1319 1324 10.1248/bpb.34.1319 21804225 28. Xu F. Li J. Ni W. Shen Y.W. Zhang X.P. Peroxisome proliferator-activated receptor-γ agonist 15d-prostaglandin J2 mediates neuronal autophagy after cerebral ischemia-reperfusion injury PLoS ONE 2013 8 10.1371/journal.pone.0055080 23372817 29. Scherz-Shouval R. Shvets E. Fass E. Shorer H. Gil L. Elazar Z. Reactive oxygen species are essential for autophagy and specifically regulate the activity of Atg4 EMBO J. 2007 26 1749 1760 10.1038/sj.emboj.7601623 17347651 30. Wu H.H. Hsiao T.Y. Chien C.T. Lai M.K. Ischemic conditioning by short periods of reperfusion attenuates renal ischemia/reperfusion induced apoptosis and autophagy in the rat J. Biomed. Sci. 2009 16 19 10.1186/1423-0127-16-19 19272187 31. Azad M.B. Chen Y. Gibson S.B. Regulation of autophagy by reactive oxygen species (ROS): Implications for cancer progression and treatment Antioxid. Redox Signal. 2009 11 777 790 10.1089/ars.2008.2270 18828708 32. Moore M.N. Viarengo A. Donkin P. Hawkins A.J. Autophagic and lysosomal reactions to stress in the hepatopancreas of blue mussels Aquat. Toxicol. 2007 84 80 91 10.1016/j.aquatox.2007.06.007 17659356 33. Lu Q. Harris V.A. Kumar S. Mansour H.M. Black S.M. Autophagy in neonatal hypoxia ischemic brain is associated with oxidative stress Redox Biol. 2015 6 516 523 10.1016/j.redox.2015.06.016 26454246 34. Tyagi N. Sedoris K.C. Steed M. Ovechkin A.V. Moshal K.S. Tyagi S.C. Mechanisms of homocysteine-induced oxidative stress Am. J. Physiol. Heart Circ. Physiol. 2005 289 H2649 H2656 16085680 35. Ho P.I. Ashline D. Dhitavat S. Ortiz D. Collins S.C. Shea T.B. Rogers E. Folate deprivation induces neurodegeneration: Roles of oxidative stress and increased homocysteine Neurobiol. Dis. 2003 14 32 42 10.1016/S0969-9961(03)00070-6 13678664 36. Tyagi N. Moshal K.S. Sen U. Vacek T.P. Kumar M. Hughes W.M. Jr. Kundu S. Tyagi S.C. H2S protects against methionine-induced oxidative stress in brain endothelial cells Antioxid. Redox Signal. 2009 11 25 33 10.1089/ars.2008.2073 18837652 37. Plachetka A. Adamek B. Strzelczyk JK. Krakowczyk Ł. Migula P. Nowak P. Wiczkowski A. 8-hydroxy-2′-deoxyguanosine in colorectal adenocarcinoma—Is it a result of oxidative stress? Med. Sci. Monit. 2013 19 690 695 23963109 38. Longa E.Z. Weinstein P.R. Carlson S. Cummins R. Reversible middle cerebral artery occlusion without craniectomy in rats Stroke 1989 20 84 91 10.1161/01.STR.20.1.84 2643202 39. Chen X.Y. Gu C. Ma M. Cong Q. Guo T. Ma D. Li B. A mouse model of premature ovarian insufficiency induced by tripterygium glycoside via subcutaneous injection Int. J. Clin. Exp. Pathol. 2014 7 144 151 24427334 40. Bradford M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding Anal. Biochem. 1976 72 248 254 10.1016/0003-2697(76)90527-3 942051

PMC005xxxxxx/PMC5000595.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081197ijms-17-01197CommunicationExpression Analysis of PIN Genes in Root Tips and Nodules of Medicago truncatula Sańko-Sawczenko Izabela Łotocka Barbara Czarnocka Weronika *Gresshoff Peter M. Academic EditorFerguson Brett Academic EditorDepartment of Botany, Faculty of Agriculture and Biology, Warsaw University of Life Sciences—SGGW, Nowoursynowska 159, 02-776 Warsaw, Poland; izabela_sanko_sawczenko@sggw.pl (I.S.-S.); barbara_lotocka@sggw.pl (B.Ł.)* Correspondence: weronika_czarnocka@sggw.pl; Tel.: +48-22-59-326-6125 7 2016 8 2016 17 8 119706 5 2016 15 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).Polar auxin transport is dependent on the family of PIN-formed proteins (PINs), which are membrane transporters of anionic indole-3-acetic acid (IAA−). It is assumed that polar auxin transport may be essential in the development and meristematic activity maintenance of Medicago truncatula (M. truncatula) root nodules. However, little is known about the involvement of specific PIN proteins in M. truncatula nodulation. Using real-time quantitative PCR, we analyzed the expression patterns of all previously identified MtPIN genes and compared them between root nodules and root tips of M. truncatula. Our results demonstrated significant differences in the expression level of all 11 genes (MtPIN1–MtPIN11) between examined organs. Interestingly, MtPIN9 was the only PIN gene with higher expression level in root nodules compared to root tips. This result is the first indication of PIN9 transporter potential involvement in M. truncatula nodulation. Moreover, relatively high expression level in root nodules was attributed to MtPINs encoding orthologs of Arabidopsis thaliana PIN5 subclade. PIN proteins from this subclade have been found to localize in the endoplasmic reticulum, which may indicate that the development and meristematic activity maintenance of M. truncatula root nodules is associated with intracellular homeostasis of auxins level and their metabolism in the endoplasmic reticulum. Medicago truncatularoot noduleauxinPIN ==== Body 1. Introduction Nitrogen is the primary and most important nutrient for plants, since it is an element for amino acids and nucleobases biosynthesis. Its availability in soil is frequently a major limiting factor for plant growth and, consequently, crop yield. The Earth’s atmosphere is a rich source of dinitrogen, but, unfortunately, plants cannot directly assimilate it in this form. However, plant species from the Fabaceae family have evolved an ability of establishing symbiosis with nitrogen-fixing bacteria, collectively called rhizobia, which allows them to exploit atmospheric nitrogen sources. This type of symbiosis is an effective evolutionary adaptation, which enables fabaceans to accumulate high levels of nitrogen in their tissues [1]. Medicago truncatula is a model fabacean species in the studies of plant interactions with rhizobia. The symbiosis initiates with a molecular dialogue in the rhizosphere between microorganisms and plant’s roots. Such molecular communication enables rhizobia to find their compatible host plant. Flavonoids, which are secreted by fabacean roots, induce bacterial Nod factors synthesis in rhizobia [2]. The recognition of specific Nod factors triggers root hair deformation relying on their curling around microsymbionts’ cells [3]. Subsequently, rhizobia induce local plant cell wall rebuilding, which gives rise to the infection thread, allowing bacteria the colonization of host tissues. At the same time, the nodule primordium starts to develop. When the infection thread reaches the nodule primordium, rhizobia are endocytosed by host cells. Each bacterial cell is surrounded by a peribacteroid membrane originating from the infection thread’s plasma membrane. This structure is called the symbiosome, and the bacteria located inside—bacteroid [4]. In bacteroids, metabolism shifts from the processes specific for free-living bacteria to increased activity of proteins associated with dinitrogen fixation and ATP synthesis, which is crucial for dinitrogen reduction [5]. Host plants provide to bacteroids the energy source and metabolites essential for dinitrogen fixation. The main carbon sources supplied are C4-dicarboxylic acids such as malate, which are intermediates in the citric acid cycle [6]. Furthermore, the host plant needs to ensure a microaerobic environment in the infected cells. This is indispensable for the proper activity of nitrogenase, an oxygen-labile enzyme directly responsible for the dinitrogen fixation. Such an environment is created by the presence of symbiotic leghemoglobins, hemoproteins present in root nodules. Like human hemoglobin, they have strong affinity towards oxygen, and thus effectively decrease their concentration in nodule tissues [7]. In symbiosomes, dinitrogen is converted into ammonium and subsequently secreted for the uptake by plant tissues. Since ammonium is toxic to plant cells, it is immediately assimilated by presumably three interdependent metabolic pathways engaging asparagine synthetase, glutamine synthetase or glutamate dehydrogenase [8]. A mature Medicago truncatula (M. truncatula) root nodule has several distinct zones. From the apical part of the nodule, the following developmental zones can be distinguished: (I) the rhizobial-free meristematic zone, providing indeterminate nodule growth; (II) the infection zone, in which bacterial cells are released from the infection threads and cell differentiation begins; (II/III) the interzone, usually consisting of one to three layers of cells that accumulate starch rapidly; (III) the dinitrogen-fixing zone with mature bacteroids; (IV) the senescence zone, which contains degenerated symbiosomes [9]; and (V) the saprophytic zone with rod-shaped rhizobia colonizing degraded host’s cells [10]. The nodule meristem—together with the bacteroid-containing tissue are surrounded with lateral nodule tissues—an inner cortex with vascular bundles, a nodule endodermis and an outer cortex [9]. An essential role of auxins (principally indole-3-acetic acid—IAA) in nodulation has been assumed for a long time. These plant hormones are involved in numerous, sometimes very divergent physiological processes, such as embryogenesis, organogenesis, plant tropisms, maintenance of meristematic activity, differentiation of vascular tissues, root elongation, fruit development, apical dominance and responses to many environmental stimuli. This phenomenon can be explained by the ability of auxins to be directionally transported and accumulated in particular cells and tissues. Auxins are synthesized in young apical tissues and can be transported by two different pathways: by phloem parenchyma cells (non-polar transport) or by cell-to-cell transport as a result of polar auxin transport (PAT). The second pathway is crucial for the local accumulation of these hormones and is dependent on polar auxin transporters such as auxin efflux carriers—PIN-formed proteins (PINs), PGP proteins that work both as influx and efflux carriers, as well as auxin influx carriers—AUX1/LAX [11]. The protonated form of IAA (IAAH) has the ability to penetrate cell membranes in accordance with the concentration gradient. In cytosolic environments (pH = 7), IAAH dissociates into IAA– and H+. Deprotonated IAA− is trapped inside the cell and cannot passively diffuse through the plasma membrane. Thus, auxin efflux carriers (PINs) are needed to transport IAA– from the cell [11,12,13]. PIN proteins are polar carriers, which means that their location in the plasma membrane of transport-competent cells is asymmetric. They are predominantly positioned on only one side of the cell, which empowers required direction of auxin transport [13]. However, in Arabidopsis thaliana (A. thaliana) cells, PIN proteins have also been found to localize in endoplasmic reticulum (ER) membranes. AtPIN5, AtPIN6 and AtPIN8, belonging to PIN5 subclade, mediate auxins transport from cytosol to ER lumen [14,15,16,17]. Eleven genes encoding PIN proteins have been characterized in M. truncatula: MtPIN1–MtPIN11 [18,19]. Insightful phylogenetic analyses of genomic and protein sequences of MtPINs revealed conserved N- and C-terminal regions of transmembrane domains and variable middle region of cytoplasmic domain. Evolutionary relations and possible origins of MtPINs have also been explained, which enabled identification of A. thaliana and M. truncatula probable orthologs [18,19]. The subcellular localization of PIN proteins, their mode of action, and involvement in specific molecular pathways are well-known in A. thaliana. However, our knowledge concerning PIN proteins in M. truncatula, especially their function in the nodulation process, is still very limited. Although there are some data indicating the role of auxins in the nodulation [20,21,22,23,24,25], and there is a huge gap regarding detailed analysis of PIN involvement in nodule formation and maintenance of their meristematic activity. In this study, we performed a comprehensive analysis of PIN expression, by examining their transcription levels in M. truncatula root tips and nodules. Our results indicate the importance of polar auxins transporters in the nodulation. Based on collected data, we identified these auxin transporters, which may play a crucial role in the nodulation. Our study is the first such detailed one concerning expression of PIN-encoding genes in the model species for rhizobium-fabacean symbiosis—M. truncatula. 2. Results To perform a detailed expression analysis of PIN genes in M. truncatula root tips and nodules, we employed the real-time quantitative PCR (qPCR) technique. Primers were designed for 11 MtPINs identified previously [18,19]. In order to unambiguously identify the phylogenetic relationship between M. truncatula and A. thaliana orthologs, we performed a BLAST alignment of each MtPIN’s coding DNA sequence (CDS) and full protein sequence with the A. thaliana nucleotide or protein database, respectively. On the basis of this comparison, we identified A. thaliana orthologs that are most closely related to the corresponding MtPINs (Table 1). Our results proved some minor differences between previously identified A. thaliana and M. truncatula orthologs [18,19] and our data. For instance, based on protein alignment, MtPIN7 appeared to be most closely related to AtPIN7, not AtPIN2, as previously described [18,19]. Absolute, normalized level of MtPINs expression in root tips is presented in Figure 1. Results revealed that all 11 MtPINs were expressed in root tips. However, their expression level differed remarkably. MtPIN1 to MtPIN4 had significantly higher expression level than the other seven MtPINs. The highest expression was found for MtPIN2, whereas the lowest was for MtPIN7 and MtPIN8. The absolute, normalized level of MtPINs expression in root nodules is presented in Figure 2. Similarly to the results obtained for root tips, the abundance of various PIN transcripts in root nodules differed significantly. The highest expression level, compared to the other MtPINs, was attributed to MtPIN9. Moreover, MtPIN11, MtPIN6 and MtPIN1 had also relatively high expression in root nodules. Expression of the other PIN genes was marginal, besides MtPIN8, which was the only MtPIN for which transcription was not detected at all. To compare transcription patterns of MtPINs between root nodules and root tips, relative expression quantification was performed. Statistically significant differences were found for all tested MtPIN genes. Ten out of eleven MtPINs were downregulated in nodules, compared to root tips. The only PIN gene that was up-regulated was MtPIN9 (Table 2). Although expressed at lower levels in nodules in comparison to roots (Table 2), MtPIN11, MtPIN6 and MtPIN1 transcript abundance was relatively high in comparison to the remaining PINs (Figure 2). These results imply the highest significance of MtPIN1, MtPIN6, MtPIN9 and MtPIN11, which are the orthologs of Arabidopsis AtPIN4, AtPIN6, AtPIN5 and AtPIN8, respectively, in the nodulation process in M. truncatula. 3. Discussion It has been shown that PIN-formed proteins play the essential role in the root apical meristem (RAM) activity regulation. By restricting the expression of auxin-inducible PLETHORA genes (main determinants for root stem cells differentiation) in the basal part of embryo, PINs lead to the initiation of root primordium formation [28]. Our data showed that MtPIN2 is the most highly expressed MtPIN gene in root tips. It has been previously found that MtPIN2 expression is upregulated in M. truncatula RAM [29], which is consistent with our results. In A. thaliana, PIN2 plays a pivotal role in the induction of optimal root tip gravitropic response by directional auxins transport from the tip to the root elongation zone [30,31]. Considering such high abundance of MtPIN2 in M. truncatula root tips, it can be concluded that its role is parallel to its A. thaliana ortholog. AtPIN3 has been also demonstrated to be expressed in gravity-sensing tissues [32], thus the high expression of its M. truncatula ortholog, MtPIN3, in root tips seems to be reasonable. Moreover, A. thaliana PIN4 is highly expressed and involved in the establishment and maintenance of auxins gradient within root tip [33]. Previous phylogenetic studies and our comparison of A. thaliana and M. truncatula protein sequences allowed to define MtPIN1 to be most closely related to AtPIN4. In our study, MtPIN1 expression was also relatively high, compared to other MtPINs in root tips. High transcription level was also attributed to MtPIN4—the ortholog of AtPIN1, which is abundantly expressed in vascular tissues [33,34]. Thus, a relatively high expression level of MtPIN4 in root tips was most likely caused by its ubiquity. Furthermore, MtPIN9 has been found to be preferentially expressed in the non-meristematic parts of the root [29], which could explain its almost indiscernible expression in root tips. Nevertheless, based on our results proving high expression of MtPIN9 in indeterminate root nodules, it cannot be excluded that MtPIN9 may play an important role in the nodule meristem functioning. Additionally, insightful analysis of real-time qPCR results, presented in this study, revealed some interesting facts, especially compared to previous reports. Firstly, our results indicated that, although on a relatively low level, MtPIN5 transcript was detectable in root tips and nodules, in both examined biological repetitions. A previous study by Schnabel and Frugoli from 2004 suggested that MtPIN5 is not expressed in plant tissues, since it originated as a result of MtPIN4 duplication and thus MtPIN5 expression could be silenced, as the one possible fate of duplicated genes [18]. Moreover, the same study reported that expression of MtPIN2 was detected in nodulating roots [18]. However, our analysis showed that although MtPIN2 is highly expressed in root tips, its transcript abundance is very low in mature nodules. Therefore, its contribution in nodulation and meristematic activity maintenance of nodules is uncertain. On the other hand, it should be noted that during our experiment we tested fully differentiated nodules, in which the expression of MtPIN2 could be already suppressed. There are some data demonstrating MtPIN2 expression only in the center and outer cortex of nodules 120 hours after inoculation and in the basal part of nodules 12 days after inoculation, but never in the mature root nodules of M. truncatula. Additionally, silencing MtPIN2, MtPIN3 or MtPIN4 by RNAi resulted in lower number of nodules in M. truncatula roots compared to control plants [21]. Therefore, it has been suggested that these PINs are involved specifically in the regulation of root nodules development. Therefore, this could be the reason why MtPIN2, MtPIN3 and MtPIN4 were no longer highly expressed in mature root nodules tissue in our study. Moreover, a recent report has shown that most MtPIN and MtLAX genes are upregulated in M. truncatula roots after Sinorhizobium meliloti infection, while downregulated in the shoots. The same genes were downregulated in both shoots and roots in dmi3 mutant, which is an infection-resistant mutant of M. truncatula, suggesting the important role of PINs in nodulation. However, that study examined nodulating roots, not root nodules themselves, thus it is hard to draw conclusions from comparing it to our data [23]. Besides MtPIN1, relatively high expression level in root nodules was attributed to MtPIN6, MtPIN9 and MtPIN11, which are the orthologs of A. thaliana AtPIN6, AtPIN5 and AtPIN8, respectively, and encode proteins belonging to the so-called PIN5 subclade. In A. thaliana, PIN proteins from this subclade have been found to localize in the ER [14,15,16,17]. Our results indicated that especially MtPIN9, which is the ortholog of AtPIN5, might be involved in the nodulation in M. truncatula. From all MtPIN genes, MtPIN9 was the only one with statistically significant higher expression level in root nodules in comparison to root tips. Proteins belonging to the PIN5 subclade are responsible for auxins transport from the cytosol to ER lumen, where the enzymes of IAA metabolism pathways are located [35]. Auxins inflow to ER lumen is believed to cause a self-regulation of their metabolism. This particular, intracellular transport results in a decrease of auxins cytosolic concentration, and, consequently, in a decrease of their intercellular flow [14]. Since MtPIN6, MtPIN9 and MtPIN11 are homologous to the transporters from A. thaliana PIN5 subclade, it can be assumed that their subcellular location is the same. This may indicate the essential role of intracellular homeostasis and auxins’ metabolism in ER compartments in the development and meristematic activity maintenance of M. truncatula root nodules. Furthermore, relatively high expression of MtPIN11 in nodules might have influenced low transcript abundance of MtPIN8. Both of these genes are considered as orthologs of AtPIN8 and probably encode proteins with the same or similar functions, which may result in decreased expression of one of them. There is some strong evidence indicating the role of auxins and their transporters in the development of indeterminate-type root nodules. Research conducted in 2005 on M. truncatula demonstrated that, in the apical parts of root nodules, de novo IAA synthesis occurs [36]. Moreover, Medicago sativa plants treated with polar auxin transport inhibitors: 1-N-naphthylphthalamic acid (NPA) or 2,3,5-triiodobenzoic acid (TIBA) were shown to produce pseudonodules—structures lacking rhizobia and ineffective in dinitrogen fixation [20]. Similar experiments conducted on M. truncatula plants gave the same results [37]. Interestingly, auxin accumulation in developing Trifolium repens nodules was shown to be preceded by inhibition of PAT [38]. Initial inhibition of auxin flow in the earliest stage of nodulation was demonstrated also in the ethylene-insensitive sickle mutant of M. truncatula. However, 24 h after inoculation, the expression of MtPIN1 and MtPIN2 in M. truncatula sickle mutant roots was increased, which led to boosted auxins accumulation just above the infection site and resulted in a significantly higher number of effective nodules, compared to the wild type [39]. It is also possible that flavonoids, acting as PAT regulators, are essential for nodules formation in M. truncatula. Flavonoid-deficient roots, with reduced abundance of chalcone synthase (CHS), the key enzyme in flavonoids biosynthesis pathway, demonstrated increased auxin transport. These M. truncatula plants were unable to trigger initial reduction of auxin transport and to form root nodules [22]. In 2004, Schnabel and Frugoli identified five M. truncatula genes encoding auxin transporter-like proteins (LAX), which are the auxins influx carriers [18]. Previous research revealed that MtLAX1 is expressed in young, elongating nodule primordia, specifically in their cortical tissues, where the vasculature is formed [40]. Auxins contribution to nodulation of M. truncatula was also indicated by the changes in expression of ARFs (Auxin Response Factors) during the response to S. meliloti infection [23,24,25]. ARFs are transcription factors in auxins signaling cascades, and binding to auxin response elements (AuxREs) in genes promoter regions. There are 24 characterized MtARFs, while AuxREs were found in the promoters of many genes involved in the initiation of nodulation—rhizobial infection response genes [23]. There is also a set of evidence that during symbiosis initiation some phytohormones can be produced by prokaryotic organisms [41]. In a recent study, genetically modified S. meliloti bacteria producing a high amount of IAA were tested in M. sativa inoculation. The results demonstrated that prokaryotic auxins were still detectable after bacteria endocytosis from infection threads, also in IV zone of root nodules. Moreover, such plants showed a higher number of nodules than M. sativa inoculated by wild-type strain, and their transgenic bacteroids had higher expressions of nifH gene, encoding subunits of nitrogenase. These plants also showed up to a 73% increase in the shoot fresh weight and more-branched root system [42]. 4. Experimental Section 4.1. Plant Material, Inoculation with Rhizobia and Growth Conditions Medicago truncatula cv. Jemalong A17 seeds were scarified with 96% sulfuric acid (H2SO4) for 15 min and subsequently washed for five times in sterile water. Seeds were placed in Petri dishes containing 0.8% water agar and stratified for 12 h in the darkness at 4 °C. After stratification, plates were moved to the growth chambers and grown in the following conditions: 16 h photoperiod, photosynthetic photon flux density (PPFD) of 80–100 µE·m−2·s−1 and temperature 25 °C. Root tips were harvested from two-day-old seedlings. To obtain root nodules, four-day-old seedlings were inoculated with Sinorhizobium meliloti strain 1021 culture, which was grown on Tryptone-Yeast (TY) medium until the optical density at 600 nm (OD600) of culture was between 0.6 and 0.8. After inoculation, seedlings were placed in pots filled with perlite and watered with nitrogen-free Fahraeus medium [43] containing 60-times diluted inoculum. Pots were covered with transparent foil for 10 days to ensure seedlings high humidity. Plants were grown for 6 weeks in a 16 h photoperiod, PPFD of 110–170 µE·m−2·s−1 and at 22 °C until fully developed nodules (>1 mm in diameter) were formed. Plants were watered three times per week: twice with distilled water and once with nitrogen-free Fahraeus medium. 4.2. RNA Isolation and cDNA Synthesis RNA was obtained from M. truncatula root nodules harvested six weeks after inoculation and, separately, from root tips of two-day-old seedlings with primary root active meristems. The reason for using plant material from different developmental stages was that in six-week-old M. truncatula plants, with expanded lateral roots system, the primary root could be delayed in growth and thus difficult to distinguish. Since lateral roots have distinctive root apical meristem (RAM) and geotropism, their PIN distribution can differ from the primary root tip. In order to compare PIN expression level in nodules to a reliable reference point, we used primary roots from young seedlings as well-described control. Total RNA isolation was performed using the GeneMATRIX Universal RNA Purification Kit (EURX, Gdańsk, Poland) with the additional step of on-column DNAse I treatment. RNA concentration, purity and integrity was tested by the spectrophotometric method with Nanodrop 2000 (Thermo Scientific, Waltham, MA, USA) and electrophoretic separation in 1% agarose gel. After equalization of RNA concentration, samples were used for cDNA synthesis using High Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific, Waltham, MA, USA). 4.3. Real-Time Quantitative PCR Primers used in this study were designed with the help of Primer3 software (Primer3Plus, Free Software Foundation, Inc., Boston, MA, USA) [44] for 11 MtPINs described previously [18,19]. In order to unambiguously identify the phylogenetic relationship between M. truncatula and A. thaliana orthologs, we used the Basic Local Alignment Search Tool (BLAST) [45] within the NCBI database. BLAST alignment was performed for each MtPIN’s coding DNA sequence (CDS) and full protein sequence with the A. thaliana nucleotide or protein database, respectively. For CDSs alignment, we used discontiguous megablast, while, for protein alignment, blastp algorithm. Orthologs were selected according to the highest query cover score. On the basis of this comparison, we identified A. thaliana orthologs that are most closely related to the corresponding MtPINs (Table 1). Each primer pair was designed to amplify 60 to 100 nucleotides long fragments of the first exon of particular MtPIN sequence. Real-time qPCR was conducted in the 7500 Fast Real-Time PCR System (Applied Biosystems, Waltham, MA, USA) using Power SYBR Green Master Mix (Thermo Fisher Scientific), according to the manufacturer’s instruction. Reaction conditions and primers sequences are presented in Table 3 and Table 4, respectively. Each PIN expression was tested for two biological replicates and three technical repetitions. Gene encoding subunit of M. truncatula ribosomal protein S7 (RPS7b) was used as the endogenous reference. The specificity of amplified PCR products was verified by melting curve analysis. Statistical analysis of the results was performed using LinRegPCR [26] (calculation of reaction efficiency) and REST2009 [27] (calculation of relative gene expression level and statistical significance of their differences). 5. Conclusions To conclude, our research revealed possible involvement of MtPIN9 transporter in M. truncatula nodulation, which was not shown ever before. Furthermore, based on the relatively high expression in root nodules of MtPINs, which are the A. thaliana orthologs of genes encoding PIN proteins located in the ER, it can be assumed that development and meristematic activity maintenance of M. truncatula root nodules may be associated with intracellular homeostasis of auxins level and their metabolism in the ER. Our work further supports the hypothesis that M. truncatula nodulation depends on the auxin level. However, further studies are needed to determine auxins role in different developmental stages and particular zones of the nodules. Elucidation of specific auxin transporters functions in nodules formation and maintenance of their meristematic activity should be of great interest in order to fully understand the auxins mode of action during nodulation process. Acknowledgments This work was supported by the 0512/IP1/2015/73 project operating within the Iuventus Plus Initiative in years 2015–2017, financed by the Polish Ministry of Science and Higher Education. Author Contributions Weronika Czarnocka conceived and designed the experiments; Izabela Sańko-Sawczenko prepared plant material, harvested nodules and root tips, isolated RNA, and performed cDNA synthesis and real-time qPCRs with the help of Weronika Czarnocka; Izabela Sańko-Sawczenko and Weronika Czarnocka analyzed the data with the help of Barbara Łotocka; Izabela Sańko-Sawczenko wrote the manuscript with the help of Barbara Łotocka and Weronika Czarnocka. Conflicts of Interest The authors declare no conflict of interest. The founding sponsors had no role in the design of the study, in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results. Abbreviations ATP adenosine triphosphate AUX1 AUXIN1 BLAST basic local alignment search tool bp base pair CDS coding DNA sequence cv. cultivar ER endoplasmic reticulum IAA− anionic indole-3-acetic acid IAAH protonated form of IAA LAX LIKE AUX1 NCBI national center for biotechnology information PAT polar auxin transport PCR polymerase chain reaction PGP P-glycoprotein qPCR quantitative polymerase chain reaction RAM root apical meristem SE standard error Figure 1 Absolute, normalized level of PIN expression in M. truncatula root tips. Mean values (±SE) are derived from two biological replicates, for which three individual qPCR reactions were performed (n = 6). Expression level for each PIN was normalized to the endogenous control. Figure 2 Absolute, normalized level of PINs expression in M. truncatula root nodules. Mean values (±SE) are derived from two biological replicates for which three individual qPCR reactions were performed (n = 6). Expression levels for each PIN was normalized to the endogenous control. ijms-17-01197-t001_Table 1Table 1 The relationship of M. truncatula PINs and their A. thaliana orthologs according to Schnabel and Frugoli and Peng et al. [18,19] or identified using BLAST search. M. truncatula Gene/Protein A. thaliana Orthologous Gene according to Schnabel and Frugoli and Peng et al. A. thaliana Orthologous Coding DNA Sequences (CDS) Identified Using BLAST Search A. thaliana Orthologous Protein Sequences Identified Using BLAST Search MtPIN1 AtPIN3 AtPIN4 AtPIN4 AtPIN4 AtPIN7 MtPIN2 AtPIN2 AtPIN2 AtPIN2 MtPIN3 AtPIN3 AtPIN3 AtPIN3 AtPIN4 AtPIN7 MtPIN4 AtPIN1 AtPIN1 AtPIN1 MtPIN5 AtPIN1 AtPIN1 AtPIN1 MtPIN6 AtPIN6 AtPIN6 AtPIN6 MtPIN7 AtPIN2 AtPIN2 AtPIN7 AtPIN7 MtPIN8 AtPIN8 AtPIN8 AtPIN8 MtPIN9 AtPIN5 AtPIN5 AtPIN5 MtPIN10 AtPIN1 AtPIN1 AtPIN1 MtPIN11 AtPIN8 AtPIN8 AtPIN8 ijms-17-01197-t002_Table 2Table 2 Comparison of MtPINs expression pattern in root nodules relative to root tips. Statistical analysis was conducted in LinRegPCR [26] and REST2009 [27]. MtRPS7b, encoding ribosomal protein S7, was used as the endogenous reference gene. “DOWN” or “UP” means that particular MtPIN’s expression in nodules in comparison to root tips is significantly lower or higher, respectively. Gene Type Reaction Efficiency Expression Standard Error 95% Confidence Interval p-Value Result MtRPS7b Reference gene 0.8951 1.000 MtPIN1 Target gene 0.7752 0.107 0.090–0.123 0.085–0.137 0.001 DOWN MtPIN2 Target gene 0.9265 0.001 0.001–0.002 0.001–0.002 0.000 DOWN MtPIN3 Target gene 0.9236 0.007 0.006–0.011 0.004–0.012 0.000 DOWN MtPIN4 Target gene 0.9509 0.010 0.007–0.017 0.004–0.023 0.000 DOWN MtPIN5 Target gene 0.9748 0.288 0.194–0.445 0.117–0.576 0.000 DOWN MtPIN6 Target gene 0.9849 0.235 0.151–0.351 0.105–0.440 0.000 DOWN MtPIN7 Target gene 0.8672 0.146 0.098–0.215 0.079–0.300 0.001 DOWN MtPIN8 Target gene 0.7412 0.012 0.009–0.016 0.007–0.019 0.002 DOWN MtPIN9 Target gene 1.0000 29.32 19.258–40.578 15.769–55.179 0.000 UP MtPIN10 Target gene 0.9001 0.044 0.033–0.055 0.023–0.090 0.002 DOWN MtPIN11 Target gene 0.9686 0.445 0.263–0.658 0.179–1.515 0.007 DOWN ijms-17-01197-t003_Table 3Table 3 Real-time qPCR conditions. Temperature Time PCR 50 °C 20 s 95 °C 10 min 40 Cycles: 95 °C 15 s 60 °C 1 min Melting curve 95 °C 15 s 60 °C 1 min 95 °C 30 s 60 °C 15 s ijms-17-01197-t004_Table 4Table 4 Accessions of genes and primers sequences used for real-time qPCR. The exact sequence of each MtPIN first exon fragment that was used for the primer design is also shown (primers binding sites are marked by shading). Underlines represent start codon of each PIN gene and dots (…) represent the discontinuity within the sequence. bp: base pairs. Gene/ID Forward (F) and Reverse (R) Primer Sequence Sequence of Each MtPIN First Exon Fragment Product Length 5′–3′ (bp) MtPIN1 (MTR_4g084870) F: TCCACTTTACGTAGCCATGATCT ATGATAACCTGGCACGATCTATACACAGTTTTAACCGCAGTAGTTCCACTTTACGTAGCCATGATCTTAGCCTATGGCTCCGTACGGTGGTGGAAAATATTCTCACCGGACCAATGTTCCGGCATAAACCGTTTCGTCGC 74 R: AACATTGGTCCGGTGAGAAT MtPIN2 (MTR_4g127100) F: CGAAGATGAGACATTGAGGATG ATGATTACCGGTAAGGATATATACGATGTTTTCGCA...CGAAGATGAGACATTGAGGATGCATAAGAAAAGGGGAGGGAGGAGTATGAGTGGTGAGTTGTTCAATAATGGTGGTTCTTACCCTCCTCCAAATCCTATGC 74 R: CACCATTATTGAACAACTCACCA MtPIN3 (MTR_1g030890) F: CTGGCCTCAACGTGTTCC ATGATAACACTAAAAGATCTTTACACTGTCTTAACAGCAGTGGTTCCA...CTGGCCTCAACGTGTTCCGAAATTCGGAACAATCGGAAGAGGGTGCTAAGGAGATCAGGATGGTGGTGGCTGATGAACATAATCAAAA 68 R: CACCACCATCCTGATCTCCT MtPIN4 (MTR_6g069510) F: TGGTGCCACTTTATGTAGCTATG ATGATCACTTTAACAGATTTCTACCATGTCATGACAGCAATGGTGCCACTTTATGTAGCTATGATCTTAGCTTATGGATCAGTAAAATGGTGGAAAATATTTTCACCTGATCAATGTTCAGGAATCAACCGTTTTGTTGCA 92 R: ACGGTTGATTCCTGAACATTG MtPIN5 (MTR_8g107360) F: CGTGGCTATGATATTAGCTTATGG ATGATAACGTTAACAGATTTCTACCATGTGATGACATCAATGGTGCCACTTTACGTGGCTATGATATTAGCTTATGGTTCAGTGAAATGGTGGAAGATATTCTCTCCCGATCAATGCTCCGGCATCAATCGCTTCGTTGCT 66 R: GAGCATTGATCGGGAGAGAA MtPIN6 (MTR_1g029190) F: TAAACCGATTCGTCGCAGTT ATGGTGACAAGAGAAGATTTATACAACGTGATGTGTGCAATGGTACCTC...TAAACCGATTCGTCGCAGTTTTTGCTGTTCCAGTTCTATCTTTTCACTTCATTTCTCTCAACAATCCTTATCAAATGGACACAAAATTTAT 67 R: GGATTGTTGAGAGAAATGAAGTGA MtPIN7 (MTR_4g127090) F: TTGTGCCACTATATGTCGCTATG ATGATTACCGGCAAGGACATATACAATGTTTTAGCGGCGATTGTGCCACTATATGTCGCTATGATATTAGCATATGGTTCGGTCCGATGGTGGAAAATCTTCACACCAGATCAATGTTCTGGAATAAACCGTTTTGTCTC 94 R: AAACGGTTTATTCCAGAACATTG MtPIN8 (MTR_7g009370) F: TTTCCTTAGCCAATGTTTATCATGT ATGATTTCCTTAGCCAATGTTTATCATGTAATAACAACAACTGTCCCATTATATGTAACAATGATACTAGCCTATGTCTCAGTGAAATGGTTTAAGATCTTCACACAAGAACAATGTTCAGGAATAAACAAATTTGTTGC 95 R: GATCTTAAACCATTTCACTGAGACATA MtPIN9 (MTR_7g079720) F: AGCAGTGGTGCCACTCTATTTT ATGATTGGGTGGGAAGACGTGTACAAAGTTATTGTAGCAGTGGTGCCACTCTATTTTGCACTAATATTAGGCTATGGTTCTGTAAGGTGGTGGAAAATTTTCACAAGAGAACAATGTGATGCAATAAACAAACTAGTTT 96 R: TTGTTTATTGCATCACATTGTTCTC MtPIN10 (MTR_7g089360) F: TGGTGTTGCTAAAGCTAATGGA ATGATAAGTGCTTTAGACTTATACCATGTCCTCACAGCAGTAGTACC...TGGTGTTGCTAAAGCTAATGGAAATGGTGGAAATGGCTACCCTGCTCCTCATAGTGCAGGGATTTTTTCACCTGTGGCTAATAAGAAAAA 61 R: CCCTGCACTATGAGGAGCA MtPIN11 (MTR_6g011400) F: ACAGCCACTGTCCCATTATATGT ATGATTTCCTTAATTGATGTCTATCATGTAGTAACAGCCACTGTCCCATTATATGTAACTATGTTACTAGCATACATTTGTGTTAAATGGTGGAAACTTTTCACACCAGATCAATGTGCAGGCATAAACAAATTTGTAGC 87 R: TGCACATTGATCTGGTGTGA MtRPS7b (MTR_8g087480) F: GAAACAACACTGCAATTTACAGGA ATGACCTTACCATACCCATACCATCACCATTGTTGT...GAAACAACACTGCAATTTACAGGAAACTATCAGGCAAAGATGTTGTCTTTAGTATCCCGTTACTGAGGCTTAGGTTCTGTTTCTCAATTTTGATTTTGTTTCATG 74 R: CCTAAGCCTCAGTAACGGGATA ==== Refs References 1. Sprent J.I. Sprent P. Nitrogen Fixing Organisms: Pure and Applied Aspects Chapman and Hall London, UK 1990 2. Perret X. Staehelin C. Broughton W.J. Molecular basis of symbiotic promiscuity Microbiol. Mol. Biol. Rev. 2000 64 180 201 10.1128/MMBR.64.1.180-201.2000 10704479 3. Esseling J.J. Lhuissier F.G.P. Emons A.M.C. Nod factor-induced root hair curling: Continuous polar growth towards the point of nod factor application Plant Physiol. 2003 132 1982 1988 10.1104/pp.103.021634 12913154 4. Brewin N.J. Plant cell wall remodelling in the rhizobium-legume symbiosis Crit. Rev. Plant Sci. 2004 23 293 316 10.1080/07352680490480734 5. Barnett M.J. Fisher R.F. Global gene expression in the rhizobial-legume symbiosis Symbiosis 2006 42 1 24 6. Poole P. Allaway D. Carbon and nitrogen metabolism in Rhizobium Adv. Microb. Physiol. 2000 43 117 163 10907556 7. Ott T. van Dongen J.T. Guenther C. Krusell L. Desbrosses G. Vigeolas H. Bock V. Czechowski T. Geigenberger P. Udvardi M.K. Symbiotic leghemoglobins are crucial for nitrogen fixation in legume root nodules but not for general plant growth and development Curr. Biol. 2005 15 531 535 10.1016/j.cub.2005.01.042 15797021 8. Barsch A. Carvalho H.G. Cullimore J.V. Niehaus K. GC-MS based metabolite profiling implies three interdependent ways of ammonium assimilation in Medicago truncatula root nodules J. Biotechnol. 2006 127 79 83 10.1016/j.jbiotec.2006.06.007 16870293 9. Vasse J. de Billy F. Camut S. Truchet G. Correlation between ultrastructural differentiation of bacteroids and nitrogen fixation in alfalfa nodules J. Bacteriol. 1990 172 4295 4306 2376562 10. Timmers A.C.J. Soupéne E. Auriac M.C. de Billy F. Vasse J. Boistard P. Truchet G. Saprophytic intracellular rhizobia in alfalfa nodules Mol. Plant Microbe Interact. 2000 13 1204 1213 10.1094/MPMI.2000.13.11.1204 11059487 11. Vieten A. Sauer M. Brewer P.B. Friml J. Molecular and cellular aspects of auxin-transport-mediated development Trends Plant Sci. 2007 12 160 168 10.1016/j.tplants.2007.03.006 17369077 12. Li J. Yang H. Peer W.A. Richter G. Blakeslee J.J. Bhandyopadhyay A. Titapiwatanakun B. Undurraga S. Khodakovskaya M. Richards E.L. Arabidopsis H+ -PPase AVP1 regulates auxin-mediated organ development Science 2005 310 121 125 10.1126/science.1115711 16210544 13. Michniewicz M. Brewer P.B. Friml J. Polar auxin transport and asymmetric auxin distribution The Arabidopsis Book Last R. American Society of Plant Biologists Rockville, MD, USA 2007 1 28 14. Mravec J. Skůpa P. Bailly A. Hoyerová K. Křeček P. Bielach A. Petrasek J. Zhang J. Gaykova V. Stierhof Y.-D. Subcellular homeostasis of phytohormone auxin is mediated by the ER-localized PIN5 transporter Nature 2009 459 1136 1140 10.1038/nature08066 19506555 15. Ding Z. Wang B. Moreno I. Dupláková N. Simon S. Carraro N. Reemmer J. Pěnčik A. Chen X. Tejos R. ER-localized auxin transporter PIN8 regulates auxin homeostasis and male gametophyte development in Arabidopsis Nat. Commun. 2012 3 941 10.1038/ncomms1941 22760640 16. Sawchuk M.G. Edgar A. Scarpella E. Patterning of leaf vein networks by convergent auxin transport pathways PLoS Genet. 2013 9 1197 10.1371/journal.pgen.1003294 23437008 17. Friml J. Jones A.R. Endoplasmic reticulum: The rising compartment in auxin biology Plant Physiol. 2010 154 458 462 10.1104/pp.110.161380 20921163 18. Schnabel E.L. Frugoli J. The PIN and LAX families of auxin transport genes in Medicago truncatula Mol. Genet. Genom. 2004 272 420 432 10.1007/s00438-004-1057-x 15375694 19. Peng J. Ge L. Wang Y. Chen R. Signaling and transport of auxin and plant development Polar Auxin Transport Chen R. Baluška F. Springer Berlin & Heidelberg, Germany 2013 239 258 20. Hirsch A.M. Bhuvaneswari T.V. Torrey J.G. Bisseling T. Early nodulin genes are induced in alfalfa root outgrowths elicited by auxin transport inhibitors Proc. Natl. Acad. Sci. USA 1989 86 1244 1248 10.1073/pnas.86.4.1244 16594017 21. Huo X. Schnabel E. Hughes K. Frugoli J. RNAi phenotypes and the localization of a protein: GUS fusion imply a role for Medicago truncatula PIN genes in nodulation J. Plant Growth Regul. 2006 25 156 165 10.1007/s00344-005-0106-y 19444321 22. Wasson A.P. Pellerone F.I. Mathesius U. Silencing the flavonoid pathway in Medicago truncatula inhibits root nodule formation and prevents auxin transport regulation by rhizobia Plant Cell 2006 18 1617 1629 10.1105/tpc.105.038232 16751348 23. Shen C. Yue R. Bai Y. Feng R. Sun T. Wang X. Yang Y. Tie S. Wang H. Identification and analysis of Medicago truncatula auxin transporter gene families uncover their roles in responses to Sinorhizobium meliloti infection Plant Cell Physiol. 2015 56 1930 1943 10.1093/pcp/pcv113 26228273 24. Bustos-Sanmamed P. Mao G. Deng Y. Elouet M. Khan G.A. Bazin J. Turner M. Subramanian S. Yu O. Crespi M. Overexpression of miR160 affects root growth and nitrogen-fixing nodule number in Medicago truncatula Funct. Plant Biol. 2013 40 1208 1220 10.1071/FP13123 25. Breakspear A. Liu C. Roy S. Stacey N. Rogers C. Trick M. Morieri G. Mysore K.S. Wen J. Oldroyd G.E.D. The root hair “infectome” of Medicago truncatula uncovers changes in cell cycle genes and reveals a requirement for Auxin signaling in rhizobial infection Plant Cell 2014 26 4680 4701 10.1105/tpc.114.133496 25527707 26. Ramakers C. Ruijter J.M. Deprez R.H. Moorman A.F. Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data Neurosci. Lett. 2003 339 62 66 10.1016/S0304-3940(02)01423-4 12618301 27. Pfaffl M.W. Horgan G.W. Dempfle L. Relative expression software tool (REST) for group-wise comparison and statistical analysis of relative expression results in real-time PCR Nucleic Acids Res. 2002 30 e36 10.1093/nar/30.9.e36 11972351 28. Blilou I. Xu J. Wildwater M. Willemsen V. Paponov I. Friml J. Heidstra R. Aida M. Palme K. Scheres B. The PIN auxin efflux facilitator network controls growth and patterning in Arabidopsis roots Nature 2005 433 39 44 10.1038/nature03184 15635403 29. Holmes P. Goffard N. Weiller G.F. Rolfe B.G. Imin N. Transcriptional profiling of Medicago truncatula meristematic root cells BMC Plant Biol. 2008 8 1197 10.1186/1471-2229-8-21 18302802 30. Müller A. Guan C. Gälweiler L. Tänzler P. Huijser P. Marchant A. Parry G. Bennett M. Wisman E. Palme K. AtPIN2 defines a locus of Arabidopsis for root gravitropism control EMBO J. 1998 17 6903 6911 10.1093/emboj/17.23.6903 9843496 31. Rahman A. Takahashi M. Shibasaki K. Wu S. Inaba T. Tsurumi S. Baskin T.I. Gravitropism of Arabidopsis thaliana roots requires the polarization of PIN2 toward the root tip in meristematic cortical cells Plant Cell 2010 22 1762 1776 10.1105/tpc.110.075317 20562236 32. Friml J. Wiśniewska J. Benková E. Mendgen K. Palme K. Lateral relocation of auxin efflux regulator PIN3 mediates tropism in Arabidopsis Nature 2002 415 806 809 10.1038/415806a 11845211 33. Friml J. Benková E. Blilou I. Wisniewska J. Hamann T. Ljung K. Woody S. Sandberg G. Scheres B. Jürgens G. AtPIN4 mediates sink-driven auxin gradients and root patterning in Arabidopsis Cell 2002 108 661 673 10.1016/S0092-8674(02)00656-6 11893337 34. Gälweiler L. Guan C. Müller A. Wisman E. Mendgen K. Yephremov A. Palme K. Regulation of polar auxin transport by AtPIN1 in Arabidopsis vascular tissue Science 1998 282 2226 2230 9856939 35. Woodward A.W. Bartel B. Auxin: Regulation, action, and interaction Ann. Bot. 2005 95 707 735 10.1093/aob/mci083 15749753 36. Fedorova E.E. Redondo F.J. Koshiba T. Pueyo J.J. de Felipe M.R. Lucas M.M. Aldehyde oxidase (AO) in the root nodules of Lupinus albus and Medicago truncatula : Identification of AO in meristematic and infection zones Mol. Plant Microbe Interact. 2005 18 405 413 10.1094/MPMI-18-0405 15915639 37. Rightmyer A.P. Long S.R. Pseudonodule formation by wild-type and asymbiotic mutant Medicago truncatula in response to auxin transport inhibitors Mol. Plant Microbe Interact. 2011 24 1372 1384 10.1094/MPMI-04-11-0103 21809981 38. Mathesius U. Bayliss C. Weinman J. Schlaman H.R.M. Spaink H.P. Rolfe B.G. McCully M.E. Djordjevic M.A. Flavonoids synthesized in cortical cells during nodule initiation are early developmental markers in white clover Mol. Plant Microbe Interact. 1998 11 1223 1232 10.1094/MPMI.1998.11.12.1223 39. Prayitno J. Rolfe B.G. Mathesius U. The ethylene-insensitive sickle mutant of Medicago truncatula shows altered auxin transport regulation during nodulation Plant Physiol. 2006 142 168 180 10.1104/pp.106.080093 16844840 40. De Billy F. Grosjean C. May S. Bennett M. Cullimore J.V. Expression studies on AUX1-like genes in Medicago truncatula suggest that auxin is required at two steps in early nodule development Mol. Plant Microbe Interact. 2001 14 267 277 10.1094/MPMI.2001.14.3.267 11277424 41. Spaepen S. Vanderleyden J. Remans R. Indole-3-acetic acid in microbial and microorganism-plant signaling FEMS Microbiol. Rev. 2007 31 425 448 10.1111/j.1574-6976.2007.00072.x 17509086 42. Bianco C. Senatore B. Arbucci S. Pieraccini G. Defez R. Modulation of endogenous indole-3-acetic acid biosynthesis in bacteroids within Medicago sativa nodules Appl. Environ. Microbiol. 2014 80 4286 4293 10.1128/AEM.00597-14 24814784 43. Vincent J.M. A Manual for the Practical Study of Root Nodule Bacteria Blackwell Scientific Publications Ltd. Oxford, UK 1970 44. Untergasser A. Nijveen H. Rao X. Bisseling T. Geurts R. Leunissen J.A.M. Primer3Plus, an enhanced web interface to Primer3 Nucleic Acids Res. 2007 35 W71 W74 10.1093/nar/gkm306 17485472 45. Altschul S.F. Gish W. Miller W. Myers E.W. Lipman D.J. Basic local alignment search tool J. Mol. Biol. 1990 215 403 410 10.1016/S0022-2836(05)80360-2 2231712

PMC005xxxxxx/PMC5000596.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081198ijms-17-01198ArticleScreening and Validation of Housekeeping Genes of the Root and Cotyledon of Cunninghamia lanceolata under Abiotic Stresses by Using Quantitative Real-Time PCR Bao Wenlong †Qu Yanli †Shan Xiaoyi *Wan Yinglang *Zhu Jianhua Academic EditorCollege of Biological Sciences and Biotechnology, Beijing Forestry University, 35 Qinghua East Road, Haidian District, Beijing 100083, China; baowenlong@bjfu.edu.cn (W.B.); quyanli@bjfu.edu.cn (Y.Q.)* Correspondence: shanxy@bjfu.edu.cn (X.S.); ylwan@bjfu.edu.cn (Y.W.); Tel.: +86-10-6233-6308 (X.S.); +86-10-6233-6409 (Y.W.)† These authors contributed equally to this work. 28 7 2016 8 2016 17 8 119828 5 2016 15 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).Cunninghamia lanceolata (Chinese fir) is a fast-growing and commercially important conifer of the Cupressaceae family. Due to the unavailability of complete genome sequences and relatively poor genetic background information of the Chinese fir, it is necessary to identify and analyze the expression levels of suitable housekeeping genes (HKGs) as internal reference for precise analysis. Based on the results of database analysis and transcriptome sequencing, we have chosen five candidate HKGs (Actin, GAPDH, EF1a, 18S rRNA, and UBQ) with conservative sequences in the Chinese fir and related species for quantitative analysis. The expression levels of these HKGs in roots and cotyledons under five different abiotic stresses in different time intervals were measured by qRT-PCR. The data were statistically analyzed using the following algorithms: NormFinder, BestKeeper, and geNorm. Finally, RankAggreg was applied to merge the sequences generated from three programs and rank these according to consensus sequences. The expression levels of these HKGs showed variable stabilities under different abiotic stresses. Among these, Actin was the most stable internal control in root, and GAPDH was the most stable housekeeping gene in cotyledon. We have also described an experimental procedure for selecting HKGs based on the de novo sequencing database of other non-model plants. Chinese firhousekeeping geneNormFinderBestKeepergeNormRankAggreg ==== Body 1. Introduction The conifers of division Pinophyta are considered to be of great ecological importance in most areas of the northern hemisphere. From the temperate zone to the northern tundra, conifers are predominant plants of temperate coniferous and boreal forests [1,2,3]. The conifers do not only have indispensable ecological roles in the Earth’s biosphere, but also have critical economic contribution to various countries. The Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) is one of the most extensively cultured evergreen conifers in south China. It is native to China and also widely distributed in temperate regions in the north of Vietnam. Chinese fir is a fast-growing conifer that belongs to family Cupressaceae, and is a commercially important tree of the lumber, pulp, and paper industry. Biological studies have recently revealed the molecular mechanism underlying the control of the developmental processes and physiological responses of the Chinese fir [4,5]. As a perennial woody plant that differs from herbaceous plants, the Chinese fir can live for hundreds of years. During this long life cycle, it is subjected to various changes in its natural environment, including temperature, water, and soil nutrients. Early studies investigated the effects of growth conditions on its morphological characters and biochemical components [3,6]. Using advanced genetic approaches, researchers have recently focused on elucidating the molecular mechanisms underlying the regulation of physiological responses, including analyses of gene function [7,8], transcriptome [4,9], or small non-coding RNA and miRNA identification [5,10]. Although next-generation sequencing (NGS) technologies allow ultrahigh-throughput and highly accurate quantification of gene expression levels, the associated high cost of sequencing and post-verification on extensive amounts of nucleic acids (DNA or RNA) limit its widespread use [11,12,13]. In this context, quantitative real-time polymerase chain reaction (qRT-PCR) analysis is a conventional choice for post-verification of the transcriptome data and to facilitate in-depth expression studies of smaller sets of genes, including studies of alternative splicing, verification of microarray expression results, and molecular diagnostics [14,15,16,17]. qRT-PCR is a well-established technique for quantifying the expression levels of target genes [9,18]. Approaches for detection of the PCR products amount (amplicon) using qRT-PCR are classified into two categories: relative quantification based on housekeeping genes (HKGs) and absolute quantification achieved with DNA standards via calibration curve [19]. Relative quantification is one of the most straightforward and robust methods for accurately quantifying subtle changes in gene expression. To avoid biased results and erroneous interpretations, a critical component of relative quantification analysis is to normalize data by measuring in parallel the expression of HKGs from the same specimen [20,21,22,23]. HKGs that are constitutively expressed to maintain cellular function, often referred to as reference genes or internal controls, are expressed at constant levels in different tissues and organs of specimens under various biotic and abiotic circumstances. As a basic prerequisite for relative quantification, HKGs have been extensively used to normalize transcript data generated by qRT-PCR as well as microarrays [24,25]. NGS data mining and HKGs identification in model species have shown that those of internal controls exhibited not only species-specific expression, but also tissue-specific expression. Furthermore, their expression levels are also influenced by environmental factors (water, light, and temperature), as well as specific experimental conditions [19,24,26,27,28]. In general, HKGs such as 18S ribosomal RNA (18SrRNA), beta-actin (β-actin), elongation factor-1 alpha (EF1a), ubiquitin (UBQ), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) have been widely adopted for normalization [29,30]. However, it has been suggested that UBQ10 and G6PD should be avoided for gene expression normalization in soybean [31]. Therefore, two or more HKGs are used to normalize relative quantified data generated from qRT-PCR, which are expressed at constant levels under various experimental conditions [25,28]. Furthermore, there is an increasing number of attempts for HKG identification, including that of Carica papaya [32], Solanum tuberosum [33], Linum usitatissimum [19], Kosteletzkya virginica [29], Oryza sativa [16], Lycopersicon esculentum [34], Triticum aestivum [35], Eucalyptus robusta [36], Arabidopsis thaliana [37], Sesamum indicum [38], and Populus euphratica [39]. Conifers have the most complex and largest genomes, as well as diverse and highly diverged repetitive sequences among all living organisms; and therefore, sequencing and assembly of their complete genomes have been described as highly challenging [40,41,42]. Thus, it is essential to provide reliable methods for determining the gene expression pattern of conifers. However, only one study has screened HKGs in the Pinus pinaster [43]. Among 10 candidate endogenous references, adenosine kinase and UBQ were determined to be acceptable options, based on the observed low level of variation in Ct values and M values in the three developmental stages of Pinus pinaster. In contrast, several genes showed variable levels of expression with various conditions. However, no validation of HKGs upon abiotic stresses in conifers has been reported, and information on these particular genes in stress-tolerant herbaceous plants is limited. Because abiotic stresses such as heat, cold, salinity, and drought cause considerable losses in plant biomass and retard plant growth, it is important to breed stress-resistant plants. Chinese fir is one of the most important conifers; however, its genomic information and systematic studies on validating HKGs for qRT-PCR studies are largely unknown, thereby hindering in-depth investigations on the functions of its gene. Herein, based on the transcriptomic data (GenBank Accession Numbers SRR2087198 and SRR2087918) from our previous study, we selected five common HKGs and used them to conduct BLAST analysis to identify highly conserved sequences. We then evaluated the following genes, Actin, GAPDH, EF1a, 18S rRNA, and UBQ, in the roots and cotyledons of Chinese fir seedlings under five different abiotic stresses, namely, cold, high temperature (HT), abscisic acid (ABA), polyethylene glycol (PEG), and sodium chloride (NaCl). The data generated from qRT-PCR were then further analyzed using comprehensive and accurate tools for statistical analysis, such as NormFinder [28], geNorm [44], BestKeeper [45], and RankAggreg [46], to determine the most appropriate one. 2. Results 2.1. Quality Control We selected the cotyledon and root section of Chinese fir, which were marked in Figure 1A and all data were analyzed according to the flow chart presented in Figure 1B. RNA samples were evaluated by the following quality controls: (1) We used NanoDrop2000 spectrophotometer (Thermo, Waltham, MA, USA) to measure the OD260/OD280 and OD260/OD230 ratios. As measured, the OD260/OD280 ratio was between 1.8 and 2.0, and the OD260/OD230 ratio was >1.7; (2) 25S ribosomal RNA bands in the electrophoresis gel were about two-fold sharper than the 18S ribosomal RNA bands (Figure S1); (3) Amplicons generated from RT-PCR showed the predicted monomer size and did not form any primer-dimers (Figure S2A). The PCR products of these candidate HKGs were then subcloned into a T-vector for sequencing. In addition, primer specificity was further validated using melting curve analysis (Figure S2B–F) and sequencing consequences. The PCR efficiencies of these five candidate HKGs varied from 1.92 to 2.08, of which EF1a had the lowest amplification efficiency and GAPDH showed the highest efficiency, followed by Actin, UBQ, and 18S. The transcriptome ID, Arabidopsis orthologous locus, primer sequences, amplicon length, and PCR efficiencies of the five candidate HKGs in Chinese fir are listed in Table S1. 2.2. Transcriptional Patterns The raw cycle threshold [47] values generated from qRT-PCR were analyzed and results showed variation among candidate HKGs in all tested samples. In roots, the average Ct values of the five HKGs that were subjected to different treatments ranged from 13.63 to 28.92 (Figure 2A). The gene encoding GAPDH had the highest expression level, which reached its cycle threshold after only 13.63 amplification cycles, whereas the Ct value of Actin with 28.92 exhibited the lowest transcript abundance. Unlike the root, the Ct values of these genes in cotyledon samples were between 21.78 (EF1a) and 28.45 (Actin) (Figure 2B). In all tested samples, Actin showed the highest Ct values in both roots and cotyledons. Each HKG displayed different levels of expression in various tissues under the same treatment. GAPDH and EF1a showed a higher expression level in root samples than in cotyledon samples. Furthermore, except for the Ct values of GAPDH and EF1a in roots, the rest of the Ct values of HKGs were within the range of 22–29. The data distribution is shown as a box-whisker in Figure 3; in roots, the Actin (SD = ±0.53) had the least variable transcript abundance, which is reflected by its low SD values. On the contrary, GAPDH showed the most variable transcript abundance (SD = ±1.47) (Figure 3A). In cotyledons, the greatest expression variation was observed in EF1a (SD = ±1.16), whereas that of 18S (SD = ±0.75) was the most stable (Figure 3B). These results indicated that no single candidate HKG had a constant expression level in different Chinese fir samples under five abiotic stresses, and thus it is of great importance to screen the best HKG(s) for gene expression normalization under certain experimental conditions in Chinese fir. 2.3. Statistical Analysis 2.3.1. NormFinder NormFinder was used to evaluate the expression stability of the candidate HKGs on the experimental samples. Raw Ct values were first log-transformed and used as input for the NormFinder. This algorithm takes into account the intra- and inter-group variations for normalization factors (NFs), which requires input data from a minimum of three candidate HKGs and a minimum of two tested samples per group. The calculated results of this software were not influenced by random co-regulated genes. The best candidate HKG displayed higher stability values that were close to zero. Table 1 and Table 2 present the stability values of tissue-specific and condition-dependent HKGs. With cold treatment, the best HKG in root was Actin (stability value: 0.009), whereas in the cotyledon it was UBQ (0.008). With HT treatment, in root, the best HKGs were Actin and 18S (0.007), and these two genes were also identified as the most stably expressed genes during NaCl treatment. In the cotyledon, EF1a (0.006) was the optimal HKG during HT stress, and GAPDH and 18S (0.012) were the most stable HKGs during NaCl stress. The GAPDH showed to be the optimal candidate in roots under the ABA treatment, which was also evaluated as the best candidate in cotyledons under the PEG treatment. UBQ (0.006) was the best HKG in the root during PEG stress, and EF1a (0.008) was the most stable gene in the cotyledon during ABA stress. Among all treatments, Actin (0.017) was the most stable candidate in root samples and GAPDH (0.095) was the least stable. Furthermore, GAPDH (0.021) showed the least variation in cotyledon samples and Actin had the highest (0.043). 2.3.2. BestKeeper BestKeeper was applied to rank the stability values by calculating the coefficient of variance (CV). The candidate HKGs are considered to be the most stably expressed genes when they present the lowest CV. The BestKeeper index reflects another function of the BestKeeper program, which is conducted using the coefficient of determination (r2). The r2 is calculated to identify a credible NF, but not to estimate the goodness of each HKG independently. Therefore, the closer r2 is to 1, the better. In the present study, we applied both CV and r2 to rank the stability values of five candidate HKGs. According to CV values generated from BestKeeper, Actin was identified as the best HKG for cold-, PEG-, and NaCl-treated root, and UBQ and GAPDH showed the greatest stability in HT- and ABA-treated root, respectively (Table 3). As shown in Table 4, except for 18S in NaCl-treated cotyledon, none of the candidate genes in all of the sample sets tested were ranked as the best one by both CV and r2. For example, for the root under PEG stress, only considering the CV, Actin showed the most stable expression pattern, but based on r2 ranking, EF1a was the best (Table 3). In the cotyledon, the best HKG in PEG, ABA, and NaCl treatments was 18S, and GAPDH was the most stably expressed gene in both HT and cold treatment (Table 4). Altogether, based on CV values, Actin was identified as the best HKG in all tested root samples (Table 3), whereas 18S was the most stably expressed gene in all tested cotyledon samples (Table 4). However, as ranked by r2, EF1a was the best HKG for cold-, PEG-, and ABA-treated roots, and GAPDH and UBQ showed the greatest stability in HT- and NaCl-treated roots, respectively (Table 3). In cold- and ABA-treated cotyledons, EF1a was the best HKG, whereas the genes Actin, GAPDH, and 18S showed the greatest stability in HT-, PEG- and NaCl-treated cotyledons, respectively (Table 4). In conclusion, according to r2, EF1a was the most stable HKG in all root samples, and GAPDH exhibited the lowest variability in all cotyledon sample sets (See the specific data of CV and r2 in Tables S2 and S3). 2.3.3. geNorm geNorm (Version 3.5, Ghent, Flanders, Belgium) was used to identify the expression stability of candidate HKGs based on the M value, which is defined as the average variation of a certain gene with regard to all other candidate HKGs. The gene with the lowest M value is considered to have the more stable expression, or conversely. According to this principle, the geNorm program will stepwisely exclude the least stable gene and be repeated until only two genes remain. The M values of the candidate HKGs are presented in Figure 4. In the ABA treatment, the Actin and GAPDH genes were ranked lowest in root samples, with an M value of 0.0271 (Figure 4A), whereas the UBQ and 18S genes were most stably expressed in cotyledon samples, with an M value of 0.0063 (Figure 4B). For cold/HT/NaCl-treated root samples, the most stable genes were Actin and 18S with M values of 0.0252, 0.02, and 0.0263, respectively (Figure 4A). The same most stably expressed HKGs were GAPDH and 18S in HT/NaCl/PEG-treated cotyledon samples, with M values of 0.085, 0.0351, and 0.0207, respectively (Figure 4B). The Actin and UBQ genes performed best in PEG-treated root samples, with an M value of 0.0169 (Figure 4A), whereas the Actin and GAPDH genes were ranked lowest, with an M value of 0.0199, in cold-treated cotyledon samples (Figure 4B). For all tested sample sets, the genes encoding Actin and 18S, with an M value of 0.0494, showed the most stable expression HKGs in roots (Figure 4A). Furthermore, GAPDH and UBQ were ranked lowest in cotyledon under different abiotic stresses, with an M value of 0.0392 (Figure 4B). In most tested samples, the results of geNorm were in high agreement with the results of NormFinder, although with slight variations in the ranking sequence of genes. In addition, regardless of the variations in ranking, these programs identified the same most stably expressed gene in all experimental samples. To determine the optimal number of HKGs for accurate normalization in different sample sets, we applied the geNorm program to further calculate the pairwise variation (PV) of two sequential normalization factors (NFs) (Vn/Vn+1) as standard deviation (SD) of the log-transformed NFn/NFn+1 ratios [44]. The NF is calculated according to the geometric mean of the number of candidate HKGs and the stepwise inclusion of other genes that were ranked based on its expression stability. Once the PV value of a candidate HKG is higher than the default cutoff value of 0.15, the additional HKG is considered to have a significant effect on normalization. Figure 5 shows the results of PV analysis, suggesting that normalization requires the adoption of only two HKGs in all tested samples because the V2/3 value of all tested samples was <0.15, the default cutoff value. 2.3.4. RankAggreg To determine the suitability of HKGs for normalization of target gene transcript abundance, the ranking patterns of the three Excel-based programs were compared. To avoid discrepancies, ranking in candidate HKGs due to the use of different algorithms (Tables S4 and S5), we applied the RankAggreg approach to generate a consensus list. We combined the four outputs (M values from geNorm, stability values from NormFinder, and CV and r2 values from BestKeeper) for comprehensive ranking analysis. The merged data revealed that the best HKGs for normalization were: GAPDH for cold- (Figure 6A), HT- (Figure 6B), and PEG-treated cotyledon (Figure 6E) and HT- (Figure 6H), and ABA-treated root (Figure 6I); EF1a for ABA-treated cotyledon (Figure 6C) and PEG-treated root (Figure 6K); Actin for cold- (Figure 6G) and NaCl-treated root (Figure 6J); and 18S for NaCl-treated cotyledon (Figure 6D). Considering all of the treatments, GAPDH was the best HKG for the cotyledon (Figure 6F), and Actin was the most stable HKG for the root (Figure 6L). On the basis of the HKGs number to use suggested by geNorm and the ranking list indicated by RankAggreg, the best combination of candidate HKGs in each treatment is presented in Table 5. 3. Discussion Chinese fir is one of the most commercially important trees in China. Its lack of complete genome information has hindered the in-depth functional analysis of its genes. To provide a powerful tool for the quantitative analysis of this long-living tree, we evaluated five candidate HKGs in the cotyledon and root of the Chinese fir under various abiotic stresses. Based on the transcriptomic data of our previous study, we selected five candidate HKGs and BLASTed these with the genome sequences of other coniferous trees, including Picea abies and Pinus taeda in NCBI. We then obtained highly conserved sequences and used these in designing primers and cloning gene segments. This strategy not only provided reliable gene segments for cloning HKGs in Chinese fir, but also served as a foundation for cloning of these genes in other species. As a sessile organism, the Chinese fir has to tolerate various abiotic and biotic changes in the environment such as light intensity, temperature, water, and nutrients, which are the most crucial signals that influence the metabolism, gene expression patterns, morphology, and development of plants [48,49]. Previous reports have shown that plants are equipped with an induction system for various stresses with miscellaneous sensors, including membrane proteins, second messengers, and transcription factors [50,51]. Under the stress stimuli, these sensors translate the signals to a downstream response to resist tolerance, which is then followed by unpredictable changes in transcript abundance of essential genes. In the present study, Actin in the root showed minimal variation under the five stresses, and GAPDH in the cotyledon was the most stably expressed gene in these abiotic treatments. Generally, housekeeping genes such as Actin, GAPDH, UBQ, 18S, and EF1a, which are used as endogenous reference genes in Arabidopsis, are also found to shift in some experimental sets [52]. Therefore, the identification of the HKGs in specific experimental conditions is necessary. To avoid erroneous expression estimates, we adopted three well-established statistical algorithms in our analysis, which are Excel-extended macro programs, Normfinder, Bestkeeper, and geNorm. In these three programs, NormFinder and BestKeeper test raw Ct values, whereas geNorm performs relative quantification, and the results thus identify discrepancies in PCR efficiency that may influence the validation of stability. We eliminated the influence of bias by using the two different statistical indices (Ct-based CV and RQ-based r2) generated from BestKeeper, and combined the evaluation statistics. As identified previously from Oryza sativa [53], Arabidopsis thaliana [37], one of the most common HKGs, UBQ, was screened as the best HKG for PEG-treated root and cold-treated cotyledons. Another common HKG, EF1a, was validated as one of the best choices for Brachiaria brizantha [54]. In previous studies, scientists have applied and identified HKGs as internal control genes in different tissues of Chinese fir, including leaves, shoot apical meristems, stems, barks, xylems and vascular cambiums [4,5,55,56]. However, identification of HKGs in Chinese fir seedlings upon different abiotic stresses has not been reported. Our study showed that the EF1a was the best candidate as HKG for ABA-treated cotyledons (Figure 6C) and PEG-treated roots (Figure 6K). We then may infer that the HKGs identified in Chinese fir essentially correspond to the species mentioned above. Meanwhile, some HKGs suitable for qRT-PCR normalization were also identified in Chinese fir such as Actin for cold- (Figure 6G) and NaCl-treated roots (Figure 6J) and 18S for NaCl-treated cotyledon (Figure 6D). To avoid the biased results of different excel-based programs, we further used RankAggreg to merge the datasets. When considering all the treatments, the comprehensive results recommend that GAPDH is the best HKG for the cotyledon (Figure 6F) and Actin is the most stable HKG for the root (Figure 6L). According to the number of HKGs to use as calculated by geNorm and the consensus list suggested by RankAggreg, the best combination of candidate HKGs varied with treatment and tissues. For example, GAPDH and UBQ were the best HKGs for the cold-treated cotyledon, but Actin and EF1a were the best choice for the cold-treated root (Table 5). Taken together, these results indicate that HKGs show similar expression profiles in different tissues because these are involved in basic intracellular functions. However, in different species, some HKGs exhibited distinct expression patterns because each species has its own gene expression regulatory network. Therefore, it is necessary to systematically screen HKGs prior to its adoption in qRT-PCR normalization for specific organisms, even for different tissues, and developmental stages of identical species in certain experimental conditions. To ensure accurate normalization, several authors have recommended the adoption of multiple HKGs in the analysis of gene expression [20,57,58,59]. For the Chinese fir abiotic stress study, we mainly focused on the impact of five abiotic treatments on the transcript stability of these HKGs. As expected, these candidate HKGs varied across different sample sets. Therefore, as PV values of V2/3 across all tested samples were <0.15 (Figure 5), we advocated two HKGs to be used for accurate quantification. Our findings, based on the RankAggreg data merged from three adequate estimated programs, reveal that the GAPDH gene may be used for normalization in cotyledon samples, whereas the Actin gene is the best internal control gene in roots. These results showed that gene expression stability is highly tissue-specific and external condition-dependent. 4. Materials and Methods 4.1. Sampling The seeds of Chinese fir were obtained from Fujian Province, China. After 7 days of germination at 4 °C, the seeds were disinfected with 1% KMnO4 for 30 min and 0.2% HgCl2 for 10 min. Then, the seedlings were planted in sterile glass bottles under controlled conditions (28 °C/26 °C, 16-h-day/8-h-night cycle). There were 6 to 8 individuals in each glass bottle. After growth for 30 days, when the seedlings showed fully opened cotyledons and some true leaves, the plants were subjected to five different stress treatments: high temperature (37 °C), low temperature (4 °C), 100 μM abscisic acid (ABA), 250 mM sodium chloride (NaCl), and drought stress (20% polyethyleneglycol 4000, PEG4000). The specimens were sampled at 4, 8, 12 h after treatment. Moreover, for each sampling, the seedlings were separated to collect tissue samples of the roots and cotyledons. On the other hand, the seedlings, which were not subjected to stress treatment, were collected and marked as controls. All specimens were immediately frozen in liquid nitrogen and stored at −80 °C until analysis. 4.2. Total RNAs Extraction Total RNAs were extracted from Chinese fir using a plant RNA purification reagent (Invitrogen, Carlsbad, CA, USA). First, frozen specimens were ground in liquid nitrogen to a fine powder with a pestle and a mortar. Second, the powder was completely dissolved in the plant purification reagent, and the mixture was centrifuged at 12,000× g at 4 °C for 2 min. This was then followed by the addition of chloroform to remove the DNA and isopropyl alcohol to recover the RNAs. Finally, the obtained RNA samples were examined by 2.5% agarose gel electrophoresis for 10 min. 4.3. cDNA Synthesis Complementary DNA (cDNA) was synthesized using the Fast Quant RT Kit (TIANGEN, Beijing, China), following the manufacturer’s protocol. The reverse transcription system was based on 5 μg of total RNA, which generated approximately 20 μL of cDNA by using random primers. The resulting cDNAs were diluted to a ratio of 1:5 with nuclease-free water. Additionally, all of the cDNAs were stored at −20 °C until analysis. 4.4. Primer Design As the complete genomes of Chinese fir were not published, we obtained the sequences of five genes from NCBI Sequence Read Archive SRA (GenBank Accession Numbers SRR2087198 and SRR2087918 for light- and dark-grown samples, respectively). The selected genes were used in BLAST analysis to identify highly conserved sequences, which were then used in designing primers with the Primer Premier 5. The length of the amplified fragments ranged from 150 to 200 bp. Finally, the control cDNAs was used as template to test the five pairs of primers by PCR to make sure that the primers were usable. The PCR products were extracted and cloned using a T vector and sequenced. 4.5. Quantitative Real-Time PCR (qRT-PCR) qRT-PCR was implemented using the Kit (SuperRealPreMix Plus with SYBR Green from TIANGEN, Beijing, China) on a Real-Time PCR Detection System CFX96 (Bio-Rad, Hercules, CA USA). In addition, all cDNA templates used in the experiment were of the same concentration. Twenty microliters reaction systems were preparing using with following: 1 μL of the cDNA template, 7.4 μL of water, 10 μL of 2× SuperRealPreMix Plus, 0.4 μL of 50× ROX Reference Dye, and 0.6 μL of the forward and reverse primers. The PCR program involved a two-step process that was run for 40 cycles: 95 °C for 10 min, then denaturation at 95 °C for 10 s, annealing at 60 °C for 32 s, and extension at 72 °C for 10 s. Each reaction had four replicates. Melting curve data were gathered from 65 °C to 95 °C in 0.5 °C increments. The standard curve of each primer pair was established with serial dilutions of cDNA ((1/5)0, (1/5)1, (1/5)2, (1/5)3, (1/5)4 and (1/5)5). The amplification efficiency (E) of qRT-PCR was determined according to the equation: E = 10−1/K, where K represents the slope of the standard curve. 4.6. Bioinformatics and Statistical Analysis of Data Excel-based programs were used in the present study, including geNorm, NormFinder and Best-Keeper. The RankAggreg package of the R program was applied to combine the four outputs, “Stab”, “CV”, “r2”, and “M”, which were generated from three Excel-based programs as earlier described. Based on the order of ranking, we employed a Monte Carlo algorithm to calculate and rank using a line chart. Because geNorm generated the same M value in the chart for the two least variable genes, we identified these two genes’ ranking with the initial M value that was calculated as the normalization factor (NF) value. 5. Conclusions In summary, this work is the first in-depth study that has attempted to identify the optimal HKGs for the relative quantification of transcript abundance in Chinese fir using various abiotic stresses by means of qRT-PCR technology. We have validated the expression stabilities of five candidate HKGs in root and cotyledon sample sets from Chinese fir under five abiotic treatments in different time intervals. As a consequence, we recommend Actin and GAPDH for all tested root and cotyledon samples respectively as superior internal controls for normalization of qRT-PCR. In addition, our results indicated that different appropriate HKGs or a combination of HKGs for normalization should be screened based on different external conditions. We have also provided reliable HKG sequences and a solid foundation for the screening of HKGs in quantitative RT-PCR studies of transcript abundance in Chinese fir. Acknowledgments This work is supported by the Fundamental Research Funds for the Central Universities (JC-2013-2, BLX2012038), Program for Changjiang Scholars and Innovative Research Team in University (IRT13047), the National Natural Science Foundation of China (31271433, 31400221). Supplementary Materials Supplementary materials can be found at http://www.mdpi.com/1422-0067/17/8/1198/s1. Click here for additional data file. Author Contributions Wenlong Bao and Yanli Qu conducted the experiments and prepared the manuscript; and Xiaoyi Shan and Yinglang Wan proposed the idea, designed the experiments, analyzed the data, and prepared the manuscripts. Conflicts of Interest The authors declare no Conflicts of Interest. Figure 1 Sample sets and data analysis flow chart: (A) different section of Chinese fir used in experiment; and (B) data analysis flow chart. Cycle threshold (Ct) values were calculated using different algorithms. Each candidate HKG has one efficiency value. The Ct data were checked for distribution by scatter plot and box whisker. The statistical results from three excel-based program were merged with RankAggreg. Abbreviations: Stab.: NormFinder stability value; r2: determination coefficient-regression from BestKeeper; CV: coefficient of variance from BestKeeper; M: classical stability value from geNorm; PV: pairwise variation from geNorm. Figure 2 Transcription abundance levels of HKGs tested in Chinese fir root (A) and cotyledon (B), shown as Ct mean value ± Standard Deviation (SD). Abbreviations: HT: High Temperature treatment; Cold: Cold treatment; ABA: Abscisic Acid treatment; NaCl: Sodium Chloride treatment; PEG: Polyethylene Glycol treatment. Figure 3 Ct variation among experimental sets of Chinese fir root (A) and cotyledon (B), shown as Box-whisker plot. The median is presented as the line across the box. The upper and lower edges bordered in each box are interquartile range, which indicate the 25th and 75th percentiles. Figure 4 M values (average expression stability) and ranking of the candidate HKGs in Chinese fir root (A) and cotyledon (B) as calculated by geNorm. A lower M value indicates more stable expression. HT: High Temperature treatment; Cold: Cold treatment; ABA: Abscisic Acid treatment; NaCl: Sodium Chloride treatment; PEG: Polyethylene Glycol treatment. Figure 5 Pairwise variation (PV) to identify the optimal number of HKGs for precise normalization. The PV (Vn/Vn+1) was analyzed between the NFs (Normalization Factors) NFn and NFn+1 using geNorm program. Abbreviations: HT: High Temperature treatment; Cold: Cold treatment; ABA: Abscisic Acid treatment; NaCl: Sodium Chloride treatment; PEG: Polyethylene Glycol treatment. Figure 6 Rank aggregation of gene lists using the Monte Carlo algorithm. Visual representation of rank aggregation using Monte Carlo algorithm with the Spearman foot rule distances: (A–F) different treatments for cotyledon ((A) cold-treated; (B) HT-treated; (C) ABA-treated; (D) NaCl-treated; (E) PEG-treated; and (F) total); and (G–L) different treatments for roots ((G) cold-treated; (H) HT-treated; (I) ABA-treated; (J) NaCl-treated; (K) PEG-treated; and (L) total). Different lines in the plot represent the following: gray lines, stability measurement; black lines, rank position; and red lines, model computed by the Monte Carlo algorithm. Abbreviations: HT: High Temperature treatment; Cold: Cold treatment; ABA: Abscisic Acid treatment; NaCl: Sodium Chloride treatment; PEG: Polyethylene Glycol treatment. ijms-17-01198-t001_Table 1Table 1 Expression stability values and ranking of HKGs in Chinese fir root as calculated by the NormFinder. Rank Position Cold-Root HT-Root NaCl-Root ABA-Root PEG-Root Total-Root Gene Stab. Gene Stab. Gene Stab. Gene Stab. Gene Stab. Gene Stab. 1 Actin 0.009 Actin 0.007 Actin 0.009 GAPDH 0.009 UBQ 0.006 Actin 0.017 2 18S 0.023 18S 0.007 18S 0.009 Actin 0.016 Actin 0.017 18S 0.020 3 UBQ 0.038 EF1a 0.026 UBQ 0.043 18S 0.027 18S 0.042 UBQ 0.047 4 GAPDH 0.097 UBQ 0.087 EF1a 0.056 EF1a 0.035 GAPDH 0.042 EF1a 0.074 5 EF1a 0.126 GAPDH 0.174 GAPDH 0.070 UBQ 0.036 EF1a 0.043 GAPDH 0.095 Best gene Actin Actin and 18S Actin and 18S GAPDH UBQ Actin 0.009 0.007 0.009 0.009 0.006 0.017 Abbreviation: HT: High Temperature treatment; Cold: Cold treatment; ABA: Abscisic Acid treatment; NaCl: Sodium Chloride treatment; PEG: Polyethylene Glycol treatment; Stab.: NormFinder stability value. ijms-17-01198-t002_Table 2Table 2 Expression stability values and ranking of HKGs in Chinese fir cotyledon as calculated by the NormFinder. Rank Position Cold-Cotyledon HT-Cotyledon NaCl-Cotyledon ABA-Cotyledon PEG-Cotyledon Total-Cotyledon Gene Stab. Gene Stab. Gene Stab. Gene Stab. Gene Stab. Gene Stab. 1 UBQ 0.008 EF1a 0.006 GAPDH 0.012 EF1a 0.008 GAPDH 0.007 GAPDH 0.021 2 GAPDH 0.016 18S 0.010 18S 0.012 UBQ 0.012 18S 0.019 UBQ 0.024 3 Actin 0.030 UBQ 0.013 UBQ 0.044 Actin 0.016 EF1a 0.024 18S 0.029 4 18S 0.030 GAPDH 0.019 EF1a 0.078 18S 0.017 UBQ 0.031 EF1a 0.035 5 EF1a 0.031 Actin 0.023 Actin 0.092 GAPDH 0.026 Actin 0.040 Actin 0.043 Best combination UBQ EF1a GAPDH and 18S EF1a GAPDH GAPDH 0.008 0.006 0.012 0.008 0.007 0.021 Abbreviation: HT: High Temperature treatment; Cold: Cold treatment; ABA: Abscisic Acid treatment; NaCl: Sodium Chloride treatment; PEG: Polyethylene Glycol treatment; Stab.: NormFinder stability value. ijms-17-01198-t003_Table 3Table 3 Expression stability values and ranking of HKGs in Chinese fir root as calculated by BestKeeper. Rank Position HT-Root Cold-Root PEG-Root ABA-Root NaCl-Root Total-Root CV r2 CV r2 CV r2 CV r2 CV r2 CV r2 1 UBQ EF1a Actin GAPDH Actin UBQ GAPDH Actin Actin GAPDH Actin UBQ 2 18S Actin 18S 18S UBQ GAPDH Actin GAPDH 18S EF1a 18S 18S 3 Actin UBQ UBQ UBQ GAPDH 18S UBQ 18S EF1a Actin UBQ GAPDH 4 EF1a 18S GAPDH Actin 18S Actin 18S UBQ UBQ 18S EF1a Actin 5 GAPDH GAPDH EF1a EF1a EF1a EF1a EF1a EF1a GAPDH UBQ GAPDH EF1a Abbreviation: HT: High Temperature treatment; Cold: Cold treatment; ABA: Abscisic Acid treatment; NaCl: Sodium Chloride treatment; PEG: Polyethylene Glycol treatment; CV: Coefficient of Variance; r2: Coefficient of Determination. ijms-17-01198-t004_Table 4Table 4 Expression stability values and ranking of HKGs in Chinese fir cotyledon as calculated by BestKeeper. Rank Position HT-Cotyledon Cold-Cotyledon PEG-Cotyledon ABA-Cotyledon NaCl-Cotyledon Total-Cotyledon CV r2 CV r2 CV r2 CV r2 CV r2 CV r2 1 GAPDH GAPDH GAPDH Actin 18S EF1a 18S 18S 18S EF1a 18S Actin 2 18S EF1a UBQ GAPDH EF1a 18S UBQ Actin GAPDH UBQ Actin 18S 3 EF1a UBQ Actin 18S GAPDH UBQ Actin UBQ UBQ Actin UBQ EF1a 4 UBQ 18S 18S UBQ UBQ Actin EF1a GAPDH Actin GAPDH GAPDH UBQ 5 Actin Actin EF1a EF1a Actin GAPDH GAPDH EF1a EF1a 18S EF1a GAPDH Abbreviation: HT: High Temperature treatment; Cold: Cold treatment; ABA: Abscisic Acid treatment; NaCl: Sodium Chloride treatment; PEG: Polyethylene Glycol treatment; CV: Coefficient of Variance; r2: Coefficient of Determination. ijms-17-01198-t005_Table 5Table 5 Best combination of HKGs based on the geNorm and RankAggreg programs. Different Tissue Treatment Cold HT ABA NaCl PEG Total Cotyledon GAPDH GAPDH EF1a 18S GAPDH GAPDH UBQ UBQ UBQ GAPDH EF1a UBQ Root Actin GAPDH GAPDH Actin EF1a Actin EF1a 18S UBQ 18S Actin EF1a Abbreviations: HT: High Temperature treatment; Cold: Cold treatment; ABA: Abscisic Acid treatment; NaCl: Sodium Chloride treatment; PEG: Polyethylene Glycol treatment. ==== Refs References 1. Pan Y.D. Birdsey R.A. Phillips O.L. Jackson R.B. The structure, distribution, and biomass of the world’s forests Annu. Rev. Ecol. Evol. Syst. 2013 44 593 622 10.1146/annurev-ecolsys-110512-135914 2. McKinley D.C. Ryan M.G. Birdsey R.A. Giardina C.P. Harmon M.E. Heath L.S. Houghton R.A. Jackson R.B. Morrison J.F. Murray B.C. A synthesis of current knowledge on forests and carbon storage in the united states Ecol. Appl. 2011 21 1902 1924 10.1890/10-0697.1 21939033 3. Pan Y.D. Birdsey R.A. Fang J.Y. Houghton R. Kauppi P.E. Kurz W.A. Phillips O.L. Shvidenko A. Lewis S.L. Canadell J.G. A large and persistent carbon sink in the world’s forests Science 2011 333 988 993 10.1126/science.1201609 21764754 4. Huang H.H. Xu L.L. Tong Z.K. Lin E.P. Liu Q.P. Cheng L.J. Zhu M.Y. De novo characterization of the chinese fir (Cunninghamia lanceolata ) transcriptome and analysis of candidate genes involved in cellulose and lignin biosynthesis BMC Genom. 2012 13 10.1186/1471-2164-13-648 23171398 5. Qiu Z. Li X. Zhao Y. Zhang M. Wan Y. Cao D. Genome-wide analysis reveals dynamic changes in expression of microRNAs during vascular cambium development in Chinese fir, Cunninghamia lanceolata J. Exp. Bot. 2015 66 3041 3054 10.1093/jxb/erv103 25795740 6. Shi J.S. Zhen Y. Zheng R.H. Proteome profiling of early seed development in Cunninghamia lanceolata (lamb.) hook J. Exp. Bot. 2010 61 2367 2381 10.1093/jxb/erq066 20363864 7. Gao Y. Bian L.M. Shi J.S. Xu J. Xi M.L. Wang G.F. Expression of a conifer COBRA-like gene CLCOBL1 from Chinese fir (Cunninghamia lanceolata ) alters the leaf architecture in tobacco Plant Physiol. Biochem. 2013 70 483 491 10.1016/j.plaphy.2013.06.013 23851362 8. Li X. Su Q. Zheng R.H. Liu G.X. Lu Y. Bian L.M. Chen J.H. Shi J.S. CLRTL1 encodes a Chinese fir RNAse III-like protein involved in regulating shoot branching Int. J. Mol. Sci. 2015 16 25691 25710 10.3390/ijms161025691 26516842 9. Qiu Z.B. Wan L.C. Chen T. Wan Y.L. He X.Q. Lu S.F. Wang Y.W. Lin J.X. The regulation of cambial activity in Chinese fir (Cunninghamia lanceolata ) involves extensive transcriptome remodeling New Phytol. 2013 199 708 719 10.1111/nph.12301 23638988 10. Wan L.C. Wang F. Guo X.Q. Lu S.F. Qiu Z.B. Zhao Y.Y. Zhang H.Y. Lin J.X. Identification and characterization of small non-coding RNAs from Chinese fir by high throughput sequencing BMC Plant Biol. 2012 12 10.1186/1471-2229-12-146 22894611 11. Li R.Q. Zhu H.M. Ruan J. Qian W.B. Fang X.D. Shi Z.B. Li Y.R. Li S.T. Shan G. Kristiansen K. De novo assembly of human genomes with massively parallel short read sequencing Genome Res. 2010 20 265 272 10.1101/gr.097261.109 20019144 12. Ozsolak F. Milos P.M. RNA sequencing: Advances, challenges and opportunities Nat. Rev. Genet. 2011 12 87 98 10.1038/nrg2934 21191423 13. Nagarajan N. Pop M. Sequence assembly demystified Nat. Rev. Genet. 2013 14 157 167 10.1038/nrg3367 23358380 14. Nolan T. Hands R.E. Bustin S.A. Quantification of mRNA using real-time RT-PCR Nat. Protoc. 2006 1 1559 1582 10.1038/nprot.2006.236 17406449 15. Kumar K. Muthamilarasan M. Prasad M. Reference genes for quantitative real-time PCR analysis in the model plant foxtail millet (Setaria italica L.) subjected to abiotic stress conditions Plant Cell Tissue Org. Cult. 2013 115 13 22 10.1007/s11240-013-0335-x 16. Jain M. Nijhawan A. Tyagi A.K. Khurana J.P. Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR Biochem. Biophys. Res. Commun. 2006 345 646 651 10.1016/j.bbrc.2006.04.140 16690022 17. Lambret-Frotte J. de Almeida L.C.S. de Moura S.M. Souza F.L.F. Linhares F.S. Alves-Ferreira M. Validating internal control genes for the accurate normalization of qPCR expression analysis of the novel model plant Setaria viridis PLoS ONE 2015 10 10.1371/journal.pone.0135006 26247784 18. Ponchel F. Toomes C. Bransfield K. Leong F.T. Douglas S.H. Field S.L. Bell S.M. Combaret V. Puisieux A. Mighell A.J. Real-time PCR based on SYBR-green I fluorescence: An alternative to the taqman assay for a relative quantification of gene rearrangements, gene amplifications and micro gene deletions BMC Biotechnol. 2003 3 1198 10.1186/1472-6750-3-18 14552656 19. Huis R. Hawkins S. Neutelings G. Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.) BMC Plant Biol. 2010 10 10.1186/1471-2229-10-71 20403198 20. Yang C.X. Pan H.P. Liu Y. Zhou X.G. Stably expressed housekeeping genes across developmental stages in the two-spotted spider mite, tetranychus urticae PLoS ONE 2015 10 10.1371/journal.pone.0120833 25822495 21. Bustin S.A. Benes V. Nolan T. Pfaffl M.W. Quantitative real-time RT-PCR—A perspective J. Mol. Endocrinol. 2005 34 597 601 10.1677/jme.1.01755 15956331 22. Strube C. Buschbaum S. Wolken S. Schnieder T. Evaluation of reference genes for quantitative real-time PCR to investigate protein disulfide isomerase transcription pattern in the bovine lungworm Dictyocaulus viviparus Gene 2008 425 36 43 10.1016/j.gene.2008.08.001 18761062 23. Dheda K. Huggett J.F. Chang J.S. Kim L.U. Bustin S.A. Johnson M.A. Rook G.A.W. Zumla A. The implications of using an inappropriate reference gene for real-time reverse transcription PCR data normalization Anal. Biochem. 2005 344 141 143 10.1016/j.ab.2005.05.022 16054107 24. Guenin S. Mauriat M. Pelloux J. Van Wuytswinkel O. Bellini C. Gutierrez L. Normalization of QRT-PCR data: The necessity of adopting a systematic, experimental conditions-specific, validation of references J. Exp. Bot. 2009 60 487 493 10.1093/jxb/ern305 19264760 25. Guo J.L. Ling H. Wu Q.B. Xu L.P. Que Y.X. The choice of reference genes for assessing gene expression in sugarcane under salinity and drought stresses Sci. Rep. 2014 4 7042 10.1038/srep07042 25391499 26. Pfaffl M.W. Prgomet C. Schmitz S. Meyer H.H.D. Bruckmaier R.M. LPS effects on the mRNA expression of inflammatory factors in the mammary gland: Quantitative transcriptomics in various cell types using real-time RT-PCR Tissue Antigens 2004 64 326 327 27. Podevin N. Krauss A. Henry I. Swennen R. Remy S. Selection and validation of reference genes for quantitative RT-PCR expression studies of the non-model crop musa Mol. Breed. 2012 30 1237 1252 10.1007/s11032-012-9711-1 23024595 28. Andersen C.L. Jensen J.L. Orntoft T.F. Normalization of real-time quantitative reverse transcription-PCR data: A model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets Cancer Res. 2004 64 5245 5250 10.1158/0008-5472.CAN-04-0496 15289330 29. Tang X.L. Wang H.Y. Shao C.Y. Shao H.B. Reference gene selection for qPCR normalization of kosteletzkya virginica under salt stress BioMed Res. Int. 2015 2015 10.1155/2015/823806 26581422 30. Lu Y.H. Yuan M. Gao X.W. Kang T.H. Zhan S. Wan H. Li J.H. Identification and validation of reference genes for gene expression analysis using quantitative PCR in spodoptera litura (Lepidoptera: Noctuidae) PLoS ONE 2013 8 10.1371/journal.pone.0068059 23874494 31. Jian B. Liu B. Bi Y.R. Hou W.S. Wu C.X. Han T.F. Validation of internal control for gene expression study in soybean by quantitative real-time PCR BMC Mol. Biol. 2008 9 10.1186/1471-2199-9-59 18573215 32. Zhu X.Y. Li X.P. Chen W.X. Chen J.Y. Lu W.J. Chen L. Fu D.W. Evaluation of new reference genes in papaya for accurate transcript normalization under different experimental conditions PLoS ONE 2012 7 10.1371/journal.pone.0044405 22952972 33. Nicot N. Hausman J.F. Hoffmann L. Evers D. Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress J. Exp. Bot. 2005 56 2907 2914 10.1093/jxb/eri285 16188960 34. Exposito-Rodriguez M. Borges A.A. Borges-Perez A. Perez J.A. Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process BMC Plant Biol. 2008 8 10.1186/1471-2229-8-131 19102748 35. Paolacci A.R. Tanzarella O.A. Porceddu E. Ciaffi M. Identification and validation of reference genes for quantitative RT-PCR normalization in wheat BMC Mol. Biol. 2009 10 10.1186/1471-2199-10-11 19232096 36. de Oliveira L.A. Breton M.C. Bastolla F.M. Camargo S.D. Margis R. Frazzon J. Pasquali G. Reference genes for the normalization of gene expression in eucalyptus species Plant Cell Physiol. 2012 53 405 422 10.1093/pcp/pcr187 22197885 37. Czechowski T. Stitt M. Altmann T. Udvardi M.K. Scheible W.R. Genome-wide identification and testing of superior reference genes for transcript normalization in arabidopsis Plant Physiol. 2005 139 5 17 10.1104/pp.105.063743 16166256 38. Wei L.B. Miao H.M. Zhao R.H. Han X.H. Zhang T.D. Zhang H.Y. Identification and testing of reference genes for sesame gene expression analysis by quantitative real-time PCR Planta 2013 237 873 889 10.1007/s00425-012-1805-9 23229061 39. Wang H.L. Chen J.H. Tian Q.Q. Wang S. Xia X.L. Yin W.L. Identification and validation of reference genes for Populus euphratica gene expression analysis during abiotic stresses by quantitative real-time PCR Physiol. Plant. 2014 152 529 545 10.1111/ppl.12206 24720378 40. Morse A.M. Peterson D.G. Islam-Faridi M.N. Smith K.E. Magbanua Z. Garcia S.A. Kubisiak T.L. Amerson H.V. Carlson J.E. Nelson C.D. Evolution of genome size and complexity in pinus PLoS ONE 2009 4 1198 10.1371/journal.pone.0004332 19194510 41. Kovach A. Wegrzyn J.L. Parra G. Holt C. Bruening G.E. Loopstra C.A. Hartigan J. Yandell M. Langley C.H. Korf I. The Pinus taeda genome is characterized by diverse and highly diverged repetitive sequences BMC Genom. 2010 11 10.1186/1471-2164-11-420 20609256 42. Nystedt B. Street N.R. Wetterbom A. Zuccolo A. Lin Y.C. Scofield D.G. Vezzi F. Delhomme N. Giacomello S. Alexeyenko A. The norway spruce genome sequence and conifer genome evolution Nature 2013 497 579 584 10.1038/nature12211 23698360 43. Javier de Vega-Bartol J. Santos R. Simões M. Miguel C. Evaluation of reference genes for quantitative PCR analysis during somatic embryogenesis in conifers BMC Proc. 2011 5 10.1186/1753-6561-5-S7-O44 44. Vandesompele J. de Preter K. Pattyn F. Poppe B. Van Roy N. de Paepe A. Speleman F. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes Genome Biol. 2002 3 10.1186/gb-2002-3-7-research0034 45. Pfaffl M.W. Tichopad A. Prgomet C. Neuvians T.P. Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: Bestkeeper-excel-based tool using pair-wise correlations Biotechnol. Lett. 2004 26 509 515 10.1023/B:BILE.0000019559.84305.47 15127793 46. Pihur V. Datta S. Rankaggreg, an R package for weighted rank aggregation BMC Bioinform. 2009 10 1198 10.1186/1471-2105-10-62 19228411 47. Bustin S.A. Benes V. Garson J.A. Hellemans J. Huggett J. Kubista M. Mueller R. Nolan T. Pfaffl M.W. Shipley G.L. The MIQE guidelines: Minimum information for publication of quantitative real-time PCR experiments Clin. Chem. 2009 55 611 622 10.1373/clinchem.2008.112797 19246619 48. Hung S.H. Yu C.W. Lin C.H. Hydrogen peroxide functions as a stress signal in plants Bot. Bull. Acad. Sin. 2005 46 1 10 49. Wasternack C. Kombrink E. Jasmonates: Structural requirements for lipid-derived signals active in plant stress responses and development ACS Chem. Biol. 2010 5 63 77 10.1021/cb900269u 20025249 50. Mahajan S. Pandey G.K. Tuteja N. Calcium- and salt-stress signaling in plants: Shedding light on SOS pathway Arch. Biochem. Biophys. 2008 471 146 158 10.1016/j.abb.2008.01.010 18241665 51. Zhu J.K. Salt and drought stress signal transduction in plants Annu. Rev. Plant Biol. 2002 53 247 273 10.1146/annurev.arplant.53.091401.143329 12221975 52. Gutierrez L. Mauriat M. Pelloux J. Bellini C. van Wuytswinkel O. Towards a systematic validation of references in real-time RT-PCR Plant Cell 2008 20 1734 1735 10.1105/tpc.108.059774 18664615 53. Narsai R. Ivanova A. Ng S. Whelan J. Defining reference genes in Oryza sativa using organ, development, biotic and abiotic transcriptome datasets BMC Plant Biol. 2010 10 10.1186/1471-2229-10-56 20353606 54. Silveira E.D. Alves-Ferreira M. Guimaraes L.A. da Silva F.R. Carneiro V.T. Selection of reference genes for quantitative real-time PCR expression studies in the apomictic and sexual grass Brachiaria brizantha BMC Plant Biol. 2009 9 1198 10.1186/1471-2229-9-84 19573233 55. Xu H. Cao D. Chen Y. Wei D. Wang Y. Stevenson R.A. Zhu Y. Lin J. Gene expression and proteomic analysis of shoot apical meristem transition from dormancy to activation in Cunninghamia lanceolata (lamb.) hook Sci. Rep. 2016 6 19938 10.1038/srep19938 26832850 56. Wang Z. Chen J. Liu W. Luo Z. Wang P. Zhang Y. Zheng R. Shi J. Transcriptome characteristics and six alternative expressed genes positively correlated with the phase transition of annual cambial activities in Chinese fir (Cunninghamia lanceolata (lamb.) hook) PLoS ONE 2013 8 1198 10.1371/journal.pone.0071562 23951189 57. Jacob F. Guertler R. Naim S. Nixdorf S. Fedier A. Hacker N.F. Heinzelmann-Schwarz V. Careful selection of reference genes is required for reliable performance of RT-qPCR in human normal and cancer cell lines PLoS ONE 2013 8 10.1371/journal.pone.0059180 23554992 58. Sinha D.K. Smith C.M. Selection of reference genes for expression analysis in Diuraphis noxia (hemiptera: Aphididae) fed on resistant and susceptible wheat plants Sci. Rep. 2014 4 10.1038/srep05059 24862828 59. Yang C.X. Pan H.P. Liu Y. Zhou X.G. Selection of reference genes for expression analysis using quantitative real-time PCR in the pea aphid, Acyrthosiphon pisum (harris) (hemiptera, aphidiae) PLoS ONE 2014 9 10.1371/journal.pone.0110454 25423476

PMC005xxxxxx/PMC5000597.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081199ijms-17-01199ArticleMoracin C, A Phenolic Compound Isolated from Artocarpus heterophyllus, Suppresses Lipopolysaccharide-Activated Inflammatory Responses in Murine Raw264.7 Macrophages Yao Xue 1†Wu Dang 1†Dong Ningning 1Ouyang Ping 1Pu Jiaqian 1Hu Qian 1Wang Jingyuan 1Lu Weiqiang 2*Huang Jin 1*Paliyath Gopinadhan Academic EditorBattino Maurizio Academic Editor1 Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Mei Long Road, Shanghai 200237, China; shirleyyao715@gmail.com (X.Y.); wudang19891013@163.com (D.W.); zoednn@126.com (N.D.); ouyangping2012@yeah.net (P.O.); pujiaqian2014@163.com (J.P.); huqian_ECUST@163.com (Q.H.); joan_wangjy@outlook.com (J.W.)2 Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China* Correspondence: wqlu@bio.ecnu.edu.cn (W.L.); huangjin@ecust.edu.cn (J.H.); Tel.: +86-21-2420-7041 (W.L.); +86-21-6425-3681 (J.H.)† These authors contributed equally to this manuscript. 25 7 2016 8 2016 17 8 119904 5 2016 18 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).Artocarpus heterophyllus, a popular tropical fruit commonly known as the jackfruit tree, is normally planted in subtropical or tropical areas. Since a variety of phytochemicals isolated from A. heterophyllus have been found to possess potently anti-inflammatory, antiviral and antimalarial activities, researchers have devoted much interest to its potential pharmaceutical value. However, the exact mechanism underlying its anti-inflammatory activity is not well characterized. In this study, seven natural products isolated from A. heterophyllus, including 25-Hydroxycycloart-23-en-3-one (HY), Artocarpin (AR), Dadahol A (DA), Morachalcone A (MA), Artoheterophyllin B (AB), Cycloheterophyllin (CY) and Moracin C (MC) were collected. Lipopolysaccharide (LPS)-stimulated inflammatory response in RAW264.7 macrophages were used in this study. Among these compounds, MC significantly inhibited LPS-activated reactive oxygen species (ROS) and nitric oxide (NO) release without marked cytotoxicity. Furthermore, MC effectively reduced LPS stimulated up-regulation of mRNA and protein expression of inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), and serval pro-inflammatory cytokines (interleukin-1β (IL-1β), interleukin-6 (IL-6) and tumor necrosis factor α (TNF-α)). Mechanistic studies revealed that the anti-inflammatory effect of MC was associated with the activation of the mitogen activated protein kinases (MAPKs) (including p38, ERK and JNK) and nuclear factor-κB (NF-κB) pathways, especially reducing the nuclear translocation of NF-κB p65 subunit as revealed by nuclear separation experiment and confocal microscopy. inflammationMAPKsMoracin CNF-κBphenols ==== Body 1. Introduction Inflammation is a complex and highly orchestrated network of immunological, physiological, and behavioral events that takes place following exposure to various harmful stimuli from intrinsic and extrinsic sources including tissue injury, extreme temperature, stimulant, infection of pathogens, and metabolic disorder [1,2]. The primary function of inflammation is to eliminate underlying disturbance and restore tissue homeostasis [3]. However, inappropriate inflammatory response can become an inherent risk and a pivotal driver of countless major diseases such as rheumatoid arthritis, chronic inflammatory bowel diseases, type II diabetes mellitus, and psoriasis [1,4]. Overproduction of the multiple pro-inflammatory mediators, which are released by various immune cells, may contribute to the excessive inflammation in the body [5]. Releasing of inflammatory mediators during chronic inflammatory diseases is controlled by activation of intracellular signaling cascades. Toll-like receptors complex (TLRs) signal pathway is activated by the binding of LPS, which triggers downstream of nuclear factor κB (NF-κB) and the mitogen activated protein kinases (MAPKs) pathways [6,7]. NF-κB, representing a five-member collection of transcription factors, has been involved in both physiological and pathophysiological inflammatory responses [1]. Normally, NF-κB as an inactivated dimer composed of its p65 and p50 subunits stays in the cytoplasm [8]. Once the encountered inflammatory stimuli such as LPS, IκB is phosphorylated and degraded, NF-κB is released and transferred from the cytoplasm to the nucleus, which leads to the overexpression of several inflammatory mediators, including cyclooxygenase-2 (COX-2), inducible nitric oxide synthase (iNOS), tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) [7,9]. On the other hand, it has been recognized that MAPKs, consisting of p38 MAPK, extracellular signal-regulated kinase (ERK) and c-Jun N-terminal kinase (JNK), play a pivotal role in the pathogenesis of many inflammatory disorders [10]. The MAPKs signal pathway can activate the NF-κB pathway and work together with NF-κB pathway to aggravate the inflammatory diseases [10,11]. Therefore, the NF-κB pathway, as well as MAPKs, are emerging as potential therapeutic targets for the remedy of inflammatory diseases [12]. Natural products, especially polyphenolic compounds, have provided considerable value to chemical diversity for anti-inflammatory molecules over the past century [13,14,15]. A. heterophyllus is an important genus of Moraceae, which is known to be a rich resource of various beneficial polyphenols and is commonly used as a traditional medicine for malaria and fever in China [16]. A. heterophyllus, because of the nutritive value of its fruits and their biopharmaceutical activities, has attracted much research interest for decades. Extracts of this species, the chemical constituents of which are mainly flavonoids, especially flavones, isoflavones, chalcones, xanthones and prenylated stilbenes, have been reported to possess several positive effects, such as anti-inflammatory [17], antioxidant, anti-hyperglycemic, antiviral [18], and antimalarial activities [19]. However, the exact molecular mechanisms of those compounds are still unknown. In this study, we used an LPS-induced RAW 264.7 cell as an inflammatory model to investigate the anti-inflammatory effects of multiple natural phenols isolated from A. heterophyllus and we discovered that only MC significantly restrained the production of NO and was in a positive relationship with the dosage, indicating that MC may possess an anti-inflammatory property. Additionally, our study further showed that MC may exert this anti-inflammatory activity by interfering with NF-κB and MAPKs pathways. Our findings implied that MC might represent a potential therapy for treatment of inflammatory diseases. 2. Results 2.1. Cytotoxicity on Macrophage Seven compounds isolated from A. heterophyllus were collected as shown in Figure 1. In addition to HY were the cycloartane derivatives [20]. All other compounds are polyphenolic compounds. Compound AR, AB and CY were proposed for the structure of prenylflavonoids [21,22,23]. Firstly, the cytotoxicity of all seven compounds were measured using RAW 264.7 cells. As shown in Figure 2, of these compounds, only AR exerted a significant cytotoxicity on RAW 264.7 cells after treatment at 48 or 72 h with or without LPS. 2.2. Effect of Natural Products on the Generation of NO To determine the effect of HY, AR, DA, MA, AB, CY and MC on NO generation, Griess reaction was performed. As shown in Figure 3A, the NO generation, measured as nitrite, rose observably from 6.2 µM of the vehicle to 47.8 µM when RAW 264.7 cells were treated with 1 µg/mL LPS. Among all tested compounds, only MC significantly suppressed the production of NO (IC50 = 7.70 µM) as shown in Figure 3B. Given that MC (50 µM) exhibited minor damage on the viability of RAW 264.7 cells in Figure 3C, the inhibitory action on NO production may not be attributable to cytotoxic effects. Taken together, MC was selected for subsequent anti-inflammatory activity and mechanism studies. 2.3. MC Reduces LPS-Induced ROS Production We next determined whether MC could inhibit ROS production using the oxidation-sensitive probe DCFH-DA. The effect of MC on ROS generation induced by LPS in RAW 264.7 macrophages was demonstrated in Figure 3D. Treatment of cells with MC at 25 and 50 µM significantly inhibited LPS induced ROS generation, indicating that MC could significantly affect the ROS production in LPS-stimulated cells (Figure 3D), and act as an anti-oxidative compound to scavenge reactive radicals. 2.4. MC Inhibits LPS-Induced mRNA and Protein Expression of iNOS and COX-2 In order to further explore the molecular mechanism by which MC inhibits inflammatory reaction in response to LPS, we measured the mRNA and protein expression levels of iNOS and COX-2 through RT-PCR and western blotting assay, respectively. As shown in Figure 4, stimulation of RAW264.7 cells with 1 µg/mL LPS resulted in a dramatic increasing in mRNA and protein production level of iNOS and COX-2. Importantly, pretreatment with 1, 10, 25, and 50 µM MC respectively, could restrain the mRNA expression of both iNOS and COX-2 stimulated by LPS (Figure 4A,B), which revealed that MC may inhibit LPS-induced transcription of iNOS and COX-2. Additionally, the results of our Western blotting demonstrated that pretreatment with 10, 25, and 50 µM MC could affect the protein expression of both COX-2 and iNOS mediated by LPS (Figure 4C,D). In summary, these results demonstrated that MC was capable of reducing LPS stimulated mRNA and protein expression of both iNOS and COX-2. 2.5. MC Suppresses LPS-Induced Pro-Inflammatory Cytokines Expression The release of pro-inflammatory cytokines is one of the most important features of the LPS-induced inflammatory response, such as IL-1β, IL-6 and TNF-α. To clarify whether MC affect cytokine production, we conducted the ELISAs assay. As expected, LPS significantly induced the expression of IL-1β (5.7-fold, p < 0.005), IL-6 (253.0-fold, p < 0.005), and TNF-α (9.7-fold, p < 0.005). Pretreatment with 25 µM MC could reduce the secretion of IL-1β and IL-6 induced by LPS (Figure 5A,B) while LPS-mediated up-regulation of TNF-α was significantly reduced by 50 µM MC by 70.6% (Figure 5C). We simultaneously determined the function of MC on the mRNA expression of IL-1β, IL-6 and TNF-α in LPS-induced RAW 264.7 cells by RT-PCR. As shown in Figure 5D–F, LPS up-regulated the mRNA expression of pro-inflammatory cytokines over that vehicle-treated cells while the mRNA levels of IL-1β, IL-6 and TNF-α were dramatically down-regulated in a dose-dependent manner when treated with MC. 2.6. MC Inhibits LPS-Induced TLR4 Expression and NF-κB Activation Toll-like receptors (TLRs), particularly TLR4, play a crucial role in the well-known LPS-induced inflammatory pathways [24]. It has been reported TLR4 recognizes the lipid A component of LPS and induces the initiation of the activation of downstream signaling pathways like transcription factor NF-κB [25]. NF-κB is inactive when it was in the cytosol because of its inhibitor IκB, which was phosphorylated on LPS induction to release NF-κB, and IKK can phosphorylates IκB, as the upstream kinases of IκB in the NF-κB signal pathway [26]. To further investigate the mechanism of MC-induced inhibition of iNOS, COX-2 and pro-inflammatory cytokines expression, in our study, western blotting was utilized to measure the expression of TLR4 and phosphorylation of IκB and IKK. As shown in Figure 6A, MC treatment for 24 h evidently blocked the LPS-mediated TLR4 expression, which may suggest that MC inhibits the expression of cell surface receptors TLR4 on RAW 264.7 macrophages. Figure 6B manifested that LPS markedly aroused the phosphorylation of IκB and IKK when exposing RAW 264.7 cells with 1 µg/mL LPS for 30 min. MC pretreating effectively suppressed these processes in a dose dependent manner. All of these results indicated that MC could effectively inhibit the activation of NF-κB and reduce TLR4 expression in LPS-induced RAW 264.7 macrophages (Figure 6A,B). Furthermore, p65 subunits of NF-κB activated by LPS can be transferred into the nucleus and bind to the NF-κB binding site so as to enhance transcriptional activity of NF-κB [27]. Hence, pNF-κB-Luc reporter gene was used in the following study to determine whether MC affected the transcriptional activity of NF-κB. As we expected, NF-κB activity in LPS-stimulated RAW264.7 cells and 293T cells were 2.7-fold and 11.0-fold, respectively, as compared to the control group. Treatment with MC could repress the NF-κB-driven transcriptional activity both in RAW264.7 and 293T cells in a dose-dependent manner (Figure 6B). In addition, given that releasing of NF-κB from the restraint of IκBα and the transsituation of NF-κB p65 into the nucleus is the most important process for the pro-inflammatory gene transcription, we determined the influence of MC on LPS-induced translocation of NF-κB p65 subunit. Western blotting revealed that MC dose-dependently attenuated p65 levels in nuclear fractions (Figure 7A). Confocal microscopy was used to disclose that in the control group without LPS stimulation, NF-κB p65 (red) mainly appeared in the cytoplasm. As shown by strong NF-κB p65 staining in the nucleus (Figure 7B), LPS treatment resulted in the translocation of p65 subunit from the cytoplasm to the nucleus (blue). The expression of p65 in the nucleus was distinctly inhibited by MC (50 µM). Our findings indicated that through preventing the LPS-induced nuclear translocation of p65, MC inhibited activation of NF-κB. 2.7. MC Inhibits LPS-Induced MAPKs Pathways Activation Accumulated evidence indicated that the MAPKs havebeen involved in the expression of a great deal of pro-inflammatory cytokines and the activation of NF-κB in response to LPS [28,29]. Therefore, we investigated the activation of the distinct MAPKs pathways to assess their potential involvement in the anti-inflammatory activities of MC by Western blotting analyses. As expected, the levels of activated p38, ERK and JNK were very low in the control group, but dramatically improved in cells following LPS stimulation. Pretreatment with MC markedly reduced phosphorylated p38, ERK and JNK levels in a dose-dependent manner as shown in Figure 8, implying that inhibitory effect of MC on activation of p38, ERK and JNK pathway was associated with the suppression of MC on LPS-initiated inflammatory responses. 3. Discussion Chronic inflammation, a pivotal factor of pathogenesis of multiple diseases, has attracted wide concerns about public health and medical finance [30]. A continual increase in the incidence of inflammatory diseases has been observed worldwide, and great interest has been focused on identifying alternative approaches to regulate the inflammatory response. Natural products, especially dietary products, provide a promising future to the cure of chronic inflammatory diseases. In this study, we have screened the anti-inflammatory activity of seven natural products extracted from A. heterophyllus, and investigated the mechanism of action of MC. Our study demonstrated that MC markedly restrained inflammatory responses induced by LPS in RAW 264.7 cells through down-regulation of NF-κB and MAPKs pathways. A. heterophyllus, (also known as the jackfruit tree), is popular in South-East Asian regions as a kind of tropical fruit. It has drawn much interest form researchers because of its potential pharmaceutical value as crude extracts and varied phytochemicals isolated from A. heterophyllus have been found to possess anti-inflammatory activity, which can be explained by the phenolic compounds including flavonoids, stilbenoids, and arylbenzofurons [31]. In this study, seven natural products HY, AR, DA, MA, AB, CY and MC, extracted from A. heterophyllus by BioBioPha (unpublished data), were collected to investigate their anti-inflammatory property using LPS-stimulated RAW264.7 macrophages. AR, MA, and MC have been reported to have inhibitory effects on NO production in LPS induced RAW 264.7 cells with the IC50 values of 18.7, 16.4 and 8.0 µM, respectively [23,32]. However, further investigation of the anti-inflammatory property and the specific mechanism of action have not been explained. In the present study, among all of the seven compounds, only MC, a phenolic compound, dramatically inhibited the overproduction of NO induced by LPS with an IC50 value of 7.70 µM with minor cytotoxicity (Figure 2) which was in accordance with the literature data (IC50 = 8.0 µM) [32]. Hence, we selected MC, as a potential agent, to further investigate the potential mechanism of the anti-inflammatory activity. An abundance of researches have confirmed that NF-κB can regulate the expression of cytokines, growth factors, effector enzymes and genes, which is an indispensable process in the pathogenesis of inflammatory response [28,33]. As a consequence, to evaluate the specific mechanism of MC on NF-κB pathway, we detected the phosphorylation of IκB and IKK, which are two vital events of NF-κB activation. We found that LPS induction dramatically improved the phosphorylation levels of IκB and IKK, which was significantly blocked by pretreatment of MC (Figure 6A,B). Luciferase reporter assay was conducted to investigate the transcriptional activity and we found that MC significantly inhibited TNF-α-induced and LPS-induced NF-κB expression (Figure 6C). Moreover, as shown in Figure 7, LPS could markedly promote the translocation of p65 subunit of NF-κB and MC greatly blocked this effect of LPS. The TLR family are essential in the process of pathogen recognition and initiation of innate immunity. Moreover, signal transduction events induced by LPS are also involved with this receptor. We discovered that pretreatment of MC can clearly reduce the protein content of TLR4 in RAW264.7 macrophages. These findings suggested that MC could inhibit the expression of the membrane receptor TLR4, and suppress LPS-induced the activation of NF-κB pathway, especially the translocation of p65 subunit. MAPKs are a highly conserved family of serine/threonine protein kinases that regulate basic physiological processes and cellular responses to extrinsic forces [34]. Much attention has been focused on development of MAPKs’ inhibitors since they can adjust the generation of various pro-inflammatory cytokines (for instance IL-1, IL-6, and TNF-α). Additionally, they play crucial roles in TLR, IL-1, IL-17 and TNF-α receptors-mediated signaling pathways, too. Moreover, LPS-induced iNOS and COX-2 production has been reported to be partly controlled by MAPKs [35]. Thus, we estimated the effect of MC on LPS-stimulated phosphorylation of p38, JNK and ERK to further explain the potential anti-inflammatory mechanism of MC. Figure 8 showed that MC inhibited the activation of p38, JNK and ERK in LPS-activated RAW 264.7, which suggests that p38, JNK and ERK are associated with the inhibition of LPS-mediated inflammation by MC. Inhibition of NF-κB and MAPKs pathways has been proposed as the two major mechanisms to explain the restraint of LPS-initiated inflammatory cytokine production including the encoding cytokines of IL-1β, IL-6 and TNF-α, as well as inflammation associated enzymes including COX-2 and iNOS [36,37]. It has been reported that cytokines, especially TNF-α, can play a necessary synergistic role with LPS in induction of NO synthesis in macrophages. Suppression of inflammatory cytokines such as IL-1β, IL-6 and TNF-α are regarded as a treatment strategy on inflammatory diseases [38]. In our results, MC restrained overproduction of LPS induced NO related to the down-regulation of iNOS mRNA expression, as well as pro-inflammatory cytokines expression (IL-1β, IL-6 and TNF-α), in a dose dependent manner, which was in accordance with our results that MC inhibited the activation of NF-κB and MAPKs pathways. In this study, we also measured the effect of MC on the generation of ROS using LPS-induced RAW264.7 macrophages and found that MC down-regulated the content of ROS in a dose-dependent manner. ROS is generated by inflammatory cells and accumulated in both allergic and non-allergic inflammation to kill the invading agents. However, overproduction of ROS in cells can also lead to inflammation and unavoidable tissue injury, which is crucial for the mechanism of inflammation [39,40,41]. Hence, suppression of ROS was helpful for the therapy of inflammatory diseases, especially for alleviation of tissue damages [42]. It has been reported that various pro-inflammatory mediators (IL-1β, IL-6, and TNF-α) regulated by NF-κB, can result in a massive generation of ROS. In turn, overproduction of ROS can lead to the activation of complex inflammatory regulating pathways (NF-κB pathways) [43]. Our study simply checked the effect of MC on the total production of ROS. We still need further studies to determine the detailed mechanism of the antioxidant activity as well as the relation between the antioxidant and anti-inflammatory activities of MC. Our findings clearly demonstrate that MC modulates the inflammatory response of macrophages potently via signaling pathways involved with the NF-κB and MAPKs pathways. Considering that there are, unfortunately, often differences between the therapeutic effect in vitro and in vivo, the current evidence is limited to in vitro data, and more investigations are therefore needed to elucidate the in vivo relevance of our findings. In conclusion, we found MC, a natural phenolic product isolated from A. heterophyllus, exhibited a potent protective effect against LPS-induced inflammation response through reducing iNOS, COX-2, IL-1β, IL-6 and TNF-α protein production by suppressing the NF-κB and MAPKs activation. Hence, the findings from the current study support further investigations of MC for its anti-inflammatory potential. 4. Experimental Section 4.1. Materials and Reagents All compounds isolated from A. heterophyllus were purchased from Yunnan BioBioPha (Kunming, China). Before use, all of the compounds were stored at −20 °C with a solvent of DMSO. LPS (from Escherichia coli, 055:B5), MTT, DCFH-DA and Griess reagent were obtained from Sigma-Aldrich (St. Louis, MO, USA). 5× mix RT master and AceQ qPCR SYBR Green Master Mix were purchased from TOYOBO (Wako, Osaka, Japan). TRIZOL reagent and lipofectamine 2000 were purchased from Invitrogen (Carlsbad, CA, USA). Primary antibody of iNOS and GAPDH were purchased from Santa Cruz (Santa Cruz, CA, USA). Antibodies against COX-2, p-IKK, p-IκB, ERK, p-ERK, JNK, p-JNK, p38, p-p38 were obtained from Bioworld (Nanjing, China). Primary antibodies of TLR4, NF-κB p65 were donated from Abway (Shanghai, China). Alexa Fluor 555-conjugated secondary anti-rabbit IgG antibody and Hoechst 33342 were obtained from Beyotime Biotechnology (Wuhan, China). Dual-Glo Luciferase Assay System was purchased from Promega (Madison, CA, USA). 4.2. Cell Culture RAW 264.7 cells and HEK293T cells were purchased from the Institute of Biochemistry and Cell Biochemistry and Cell Biology (Shanghai, China) and were cultured in Dulbecco’s modified Eagle’s medium, supplemented with 2 mM l-glutamine, and 10% FBS, and maintained at 37 °C under 5% CO2 atmosphere. 4.3. Nitrite Assay RAW 264.7 macrophages were seeded at a density of 1 × 105 cells/well with 500 µL of DMEM plus 10% FBS in 24-well plates before incubation for 6 h. Then the cells were firstly incubated with tested compounds for 2 h and then stimulated with 1 µg/mL LPS for 18 h. Griess reaction was used to measure the NO concentration in the medium [33]. In details, 100 µL of cell culture supernant was added into equal volume of Griess reagent (0.1% naphthylethylenediamine dihydrochloride and 1% sulphanilamide in 5% phosphoric acid) in 96-well plates, and using a Synergy 2 Multi-Mode Microplate Reader (BioTek, Winooski, VT, USA), the absorbance at 540 nm was detected. By comparison with the OD540 values of a standard solution of sodium nitrite prepared in culture medium. Concentrations of nitrite in tested wells were calculated. 4.4. Cell Viability Assay Cell viability was accessed by MTT assay. Detailed, RAW 264.7 cells were seeded in a 96-well plate (8 × 103 per well) and incubated at 37 °C overnight. Then these RAW264.7 cells were treated with 10 µM of tested compounds or vehicle alone. After a serial time (12, 24, 48, and 72 h) of incubation at 37 °C, 20 µL of the MTT solution dissolved in PBS at 5 mg/mL was added to each well and incubated. Discarding the medium after 4 h and adding 100 µL DMSO into every well to dissolve the formazan precipitate [4], the absorption at the wavelength of 570 nm of the plates were measured on a Synergy 2 Multi-Mode Microplate Reader (BioTek, Winooski, VT, USA). 4.5. Measurement of the Content of ROS The intracellular ROS generation was measured using a well-established probe, the oxidant-sensitive probe 2’,7’-dichlorofluorescein diacetate (DCFH-DA), to determine and quantify intracellular produced hydrogen peroxide [39,44]. RAW 264.7 cells were incubated with MC for 2 h and stimulated with LPS (1 µg/mL) for another 30 min. Then the cells were incubated with 10 µM DCFH-DA for 30 min, and washed twice with PBS solution. The fluorescence of DCF was observed using an inverted fluorescence microscope (Nikon, Tokyo, Japan) with a digital camera. 4.6. Cytokine Quantification RAW 264.7 mouse macrophages were seeded in 24-well plates (at a density of 1 × 105 cells per well) and incubated for 6 h. Before stimulated with 1 µg/mL LPS for 24 h, the cells were treated with MC for 2 h. The concentration of IL-1β, IL-6 and TNF-α in supernatants were determined using commercially available ELISA kits (Neobioscience Technology, Shenzhen, China) according to the manufacturer’s instructions. 4.7. RNA Extraction and Reverse Transcriptase (RT-PCR) Total RNA were extracted using TRIZOL reagent in accordance to the manufacturer’s instruction. Then the total RNA was reverse-transcribed into cDNA using 5 × mix RT master (FSQ-201) under the following conditions: 37 °C for 15 min, 50 °C for 5 min, 98 °C for 5 min and 4 °C forever. The sense and antisense primers for iNOS were 5′-CCTGGTACGGGCATTGCT-3′ and 5′-GCTCATGCGGCCTCCTTT-3′, respectively. The sense and antisense primers for COX-2 were 5′-ATGCTCCTGCTTGAGTATGT-3′ and 5′-CACTACATCCTGACCCACTT-3′, respectively. The sense and antisense primers for TNF-α were 5′-CTGTAGCCCACGTCGTAGC-3′ and 5′-TTGAGATCCATGCCGTTG-3′, respectively. The sense and antisense primers for IL-6 were 5′-TGGAGTCACAGAAGAAGTGGCTAAG-3′ and 5′-TCTGACCACAGTGAGGAATGTCCAC-3′, respectively. The sense and antisense primers for IL-1β were 5′-ACTCCTTAGTCCTCGGCCA-3′ and 5′-CCATCAGAGGCAAGGAGGAA-3′, respectively. The sense and antisense primers for GAPDH were 5′-TGAAGCAGGCATCTGAGGG-3′ and 5′-CGAAGG TGGAAGAGTGGGAG-3′, respectively [45]. Q-PCR was performed using the AceQ qPCR SYBR Green Master Mix in accordance with the manufacturer’s protocol. GAPDH was used in this experiment to normalize the PCR amounts of every group. 4.8. Extraction of Total, Cytosol, and Nuclear Proteins RAW 264.7 cells were pretreated with MC for 2 h. After induced by 1 µg/mL LPS for 60 min, the protein of cytosol and nuclear were harvested. Using a nuclear protein extraction kit (Beyotime Biotechnology, Wuhan, China), we isolated the cytoplasmic component from nuclear one form RAW 264.7 cells. All above procedures should be performed on ice. In addition, total proteins were also extracted from RAW 264.7 cells with RIPA buffer (Beyotime Biotechnology, Wuhan, China) and the bicinchoninic acid assay (BCA) was used to determine the protein concentration. 4.9. Western Blot Analysis Protein samples after being quantified, were loaded, and separated by 10% sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE), then transferred to a PVDF membrane (GE Healthcare, Buckinghamshire, UK). After transfer, 5% BSA (in TBST buffer) was used to block the membrane at room temperature for 1 h [4]. Then the membranes were pre-incubated with primary antibody at 4 °C overnight and then incubated with secondary antibody following washing with TBST three times. Blots were visualized and quantified using Bio-Imaging System (BioTek, Winooski, VT, USA). The equivalent loading of proteins in each well was confirmed by GAPDH or histone control. The Image J software version 1.43u (National Institutes of Health, Bethesda, MD, USA) was used to quantified the gels. 4.10. NF-κB Luciferase Reporter Assay The luciferase assay was performed as described with some modifications [46]. Mouse macrophages RAW 264.7 and HEK293T cells were used in our experiment and when we observed the confluence of the cells, transiently transfected was performed with the mouse pNF-κB-luc reporter plasmid using lipofectamine 2000 reagents. After another 6 h, we trypsinized the cells and equal numbers of cells (1.2 × 104) were seeded in 96-well plates for 18 h. Different concentrations (1, 10, 25, and 50 µM, respectively) of MC or DMSO were added to the cells, and followed by stimulation with 1 µg/mL LPS for 6 h. Cells in each well were then washed twice with cold PBS and harvested in 150 µL of passive lysis buffer (0.5 M HEPES pH 7.8, 1% Triton N-101, 1 mM CaCl2, and 1 mM MgCl2) for luciferase assays (Promega, Madison, WI, USA). Transfection experiments were performed in triplicate and repeated at least three times. 4.11. Immunofluorescence Analysis To examine nuclear location of NF-κB p65 subunit, we cultured RAW 264.7 cells onto glass coverslips in 6-well plates for 24 h. Before being treated with 1 µg/mL LPS for 1 h, the cells were pre-incubated with 50 µM of MC for 2 h. After that, we fixed the cells with 4.0% (w/v) paraformaldehyde for 15 min at room temperature. 0.5% (v/v) Triton X-100 was used to permeabilize the cells prior to blocking in 1% (w/v) goat serum in PBS for 1h. The cells were then treated with anti-NF-κB p65 antibody (1:400 in 1% goat serum/PBS) overnight at 4 °C following three washings with PBS. After Alexa Fluor 555-conjugated secondary anti-rabbit antibody (1:500) treatment for 2 h at room temperature, we stained the nuclei with 10 µg/mL Hoechst 33342 (Beyotime Biotechnology, Wuhan, China). The immunofluorescence analysis was performed using an A1R Confocal Microscope (Nikon, Tokyo, Japan). 4.12. Statistical Analysis Data were expressed as the mean ± S.E.M from at least three independent experiments. One-way ANOVA and two-tailed Student’s t-test were performed. p values less than 0.05 were considered as statistically significant. All statistical tests were carried out using GraphPad Prism software (GraphPad Inc., San Diego, CA, USA). 5. Conclusions In this study, we found that MC, a natural phenolic product isolated from A. heterophyllus, possess a potent protective effect against LPS-induced inflammatory responses in RAW264.7 macrophages, through suppressing the NF-κB and MAPKs activation. This may bring hope to the treatment of various inflammatory diseases. Acknowledgments This work was supported by grants from the National Natural Science Foundation of China (grants 81402482), the Shanghai Committee of Science and Technology (grants 14ZR1411100, 15431902000), China Postdoctoral Science Foundation grant (2014M551361, 2015T80415). Author Contributions Jin Huang conceived and directed the project. Weiqiang Lu and Jin Huang designed the study. Xue Yao, Ningning Dong, Dang Wu and Jiaqian Pu, Ping Ouyang, Qian Hu and Jingyuan Wang collected the materials and carried out the experiments. Xue Yao analyzed the data. Xue Yao, Ningning Dong, Dang Wu, Weiqiang Lu and Jin Huang interpreted the results and wrote the manuscript. All authors read and approved the finalized manuscript. Conflicts of Interest The authors have declared that no conflict of interest exists. Abbreviations AB Artoheterophyllin B AR Artocarpin COX-2 cyclooxygenase-2 CY Cycloheterophyllin DA Dadahol A ERK extracellular signal-regulated kinase FBS fetal bovine serum HY 25-Hydroxycycloart-23-en-3-one IL-1β interleukin-1β IL-6 interleukin-6 iNOS inducible nitric oxide synthase JNK c-Jun N-terminal kinase LPS lipopolysaccharide MA Morachalcone A MAPKs mitogen activated protein kinases MC Moracin C NO nitric oxide NF-κB Nuclear Factor-κB ROS reactive oxygen species TLRs Toll-like receptors TNF-α tumor necrosis factor α Figure 1 Chemical structure of compounds isolated from A. heterophyllus. Figure 2 Effects of the seven compounds on the cell viability of RAW 264.7 cells. (A–D) RAW 264.7 cells incubated with 10 µM compounds for different times (12, 24, 48, and 72 h), with or without LPS treatment (1 µg/mL), respectively. The cell viability was measured using a MTT assay. Mean ± SEM, * p < 0.05, ** p < 0.01, *** p < 0.001. Figure 3 Effects of compounds on nitric oxide (NO) and reactive oxygen species (ROS) production in lipopolysaccharide (LPS)-activated RAW264.7 cells. (A,B) Cells were treated with 1 µg/mL LPS for 18 h. The nitrite concentration in the culture supernatant was detected to indicate NO production; (C) Cells incubated with 1, 10, 25 and 50 µM MC for 24 h. The cell viability was measured using a MTT assay; (D) Cells were treated with 1 µg/mL LPS for 1 h. The ROS content in the cell was detected using an oxidant-sensing fluorescent probe 2’,7’-dichlorofluorescein diacetate (DCFH-DA). Left: the images were observed using an inverted fluorescence microscope (Scale bar: 100 µm); Right: The quantitative data of fluorescent signal. Mean ± SEM, * p < 0.05, ** p < 0.01, *** p < 0.001. Figure 4 Effects of MC on mRNA and protein expression of iNOS and COX-2 in LPS-activated RAW 264.7 cells. Cells preincubated with 1, 10, 25 and 50 µM MC for 2 h were exposed to 1 µg/mL LPS for 24 h. Whole RNA was extracted for RT-PCR. Relative inducible nitric oxide synthase (iNOS) (A) and cyclooxygenase-2 (COX-2) (B) mRNA levels were calculated with reference to the LPS-treated group. The expressions of iNOS, COX-2, and GAPDH proteins were detected by Western blotting analysis. Relative iNOS (C) and COX-2 (D) protein levels were calculated with reference to the LPS-treated group. Mean ± SEM, * p < 0.05, ** p < 0.01, *** p < 0.001. Figure 5 Effects of MC on pro-inflammatory cytokine productions in LPS-activated RAW 264.7 cells. Cells were treated with 1 µg/mL LPS for 24 h. IL-1β (A); IL-6 (B); and TNF-α (C) in the supernatant were detected by ELISA kits. Whole RNA was extracted for RT-PCR. Relative interleukin-1β (IL-1β) (D); interleukin-6 (IL-6) (E); and tumor necrosis factor α (TNF-α) (F) mRNA levels were calculated with reference to the LPS-treated group. Mean ± SEM, * p < 0.05, ** p < 0.01, *** p < 0.001. Figure 6 Effects of MC on LPS-induced activation of NF-κB pathway. (A) Western blotting analysis of the expression of TLR4 induced by LPS. Cells were treated with 1 µg/mL LPS for 24 h and total cell lysates were extracted and measured by Western blotting analysis; (B) Western blotting analysis of the phosphorylation of IκB and IKK expression induced by LPS. Cells were treated with 1 µg/mL LPS for 30 min and total cell lysates were extracted and measured by Western blotting analysis; (C) pNF-κB-luc were transfected into RAW 264.7 macrophages (upper) and HEK293T cells (bottom). Twenty-four hours after transfection, cells pretreated with MC for 2 h were treated with 1 µg/mL LPS for 6 h, the luciferase activity was determined. Mean ± SEM, * p < 0.05, ** p < 0.01, *** p < 0.001. Figure 7 Effects of MC on LPS-induced translocation of NF-κB subunit p65. Cells preincubated with 50 µM MC for 2 h, were treated with 1 µg/mL LPS for 1 h. (A) Expression of NF-κB p65 protein was detected by Western blotting analysis; (B) The immunofluorescence analysis was performed with rabbit anti-NF-κB p65 antibody and an Alexa Fluor 555-conjugated anti-rabbit IgG antibody (red). Hoechst 33342 was used to label the nuclei (blue). The images were captured by confocal microscopy (Scale bar = 10 µm). The translocation of NF-κB p65 was marked by the arrows. The representative images from three independent experiments are shown here. Mean ± SEM, * p < 0.05, ** p < 0.01, *** p < 0.001. Figure 8 Effects of MC on the phosphorylation of MAPKs. (A) Cells preincubated with 1, 10, 25 and 50 µM MC for 2 h were exposed to 1 µg/mL LPS for 30 min, for the detection of phosphorylated and total p38, ERK and JNK, cell lysates were extracted and measured by Western blotting analysis; (B) The ratio of the phosphorylation and the non-phosphorylation of MAPKs. The representative Western blotting bands from three independent experiments are shown here. Mean ± SEM, ** p < 0.01, *** p < 0.001. ==== Refs References 1. Killeen M.J. Linder M. Pontoniere P. Crea R. NF-κβ signaling and chronic inflammatory diseases: Exploring the potential of natural products to drive new therapeutic opportunities Drug Discov. Today 2014 19 373 378 10.1016/j.drudis.2013.11.002 24246683 2. Jayasooriya R.G.P.T. Lee K.-T. Lee H.-J. Choi Y.H. Jeong J.-W. Kim G.-Y. Anti-inflammatory effects of β-hydroxyisovalerylshikonin in BV2 microglia are mediated through suppression of the PI3K/Akt/NF-κB pathway and activation of the Nrf2/HO-1 pathway Food Chem. Toxicol. 2014 65 82 89 10.1016/j.fct.2013.12.011 24365262 3. Nathan C. Points of control in inflammation Nature 2002 420 846 852 10.1038/nature01320 12490957 4. Wang Q.-S. Xiang Y. Cui Y.-L. Lin K.-M. Zhang X.-F. Dietary blue pigments derived from genipin, attenuate inflammation by inhibiting LPS-induced iNOS and COX-2 expression via the NF-κB inactivation PLoS ONE 2012 7 1199 10.1371/journal.pone.0034122 22479539 5. Pan M.H. Hong H.M. Lin C.L. Jhang A.Z. Tsai J.H. Badmaev V. Nagabhushanam K. Ho C.T. Chen W.J. Se-methylselenocysteine inhibits lipopolysaccharide-induced NF-κB activation and iNOS induction in RAW 264.7 murine macrophages Mol. Nutr. Food Res. 2011 55 723 732 10.1002/mnfr.201000481 21213327 6. McInturff J.E. Modlin R.L. Kim J. The role of toll-like receptors in the pathogenesis and treatment of dermatological disease J. Investig. Dermatol. 2005 125 1 8 10.1111/j.0022-202X.2004.23459.x 15982296 7. Tak P.P. Firestein G.S. NF-κB: A key role in inflammatory diseases J. Clin. Investig. 2001 107 7 10.1172/JCI11830 11134171 8. Viatour P. Merville M.-P. Bours V. Chariot A. Phosphorylation of NF-κB and IκB proteins: Implications in cancer and inflammation Trends Biochem. Sci. 2005 30 43 52 10.1016/j.tibs.2004.11.009 15653325 9. Lawrence T. Fong C. The resolution of inflammation: Anti-inflammatory roles for NF-κB Int. J. Biochem. Cell Biol. 2010 42 519 523 10.1016/j.biocel.2009.12.016 20026420 10. Thalhamer T. McGrath M. Harnett M. MAPKs and their relevance to arthritis and inflammation Rheumatology 2008 47 409 414 10.1093/rheumatology/kem297 18187523 11. DebRoy A. Vogel S.M. Soni D. Sundivakkam P.C. Malik A.B. Tiruppathi C. Endotoxin-induced STIM1 expression in endothelial cells requires cooperative signaling of transcription factors NF-κB and AP1/c-Fos and mediates lung vascular hyper-permeability J. Biol. Chem. 2014 289 24188 24201 10.1074/jbc.M114.570051 25016017 12. Hwang P.-A. Chien S.-Y. Chan Y.-L. Lu M.-K. Wu C.-H. Kong Z.-L. Wu C.-J. Inhibition of lipopolysaccharide (LPS)-induced inflammatory responses by sargassum hemiphyllum sulfated polysaccharide extract in RAW 264.7 macrophage cells J. Agric. Food Chem. 2011 59 2062 2068 10.1021/jf1043647 21322561 13. Baker D.D. Chu M. Oza U. Rajgarhia V. The value of natural products to future pharmaceutical discovery Nat. Prod. Rep. 2007 24 1225 1244 10.1039/b602241n 18033577 14. Li J.W.-H. Vederas J.C. Drug discovery and natural products: End of an era or an endless frontier? Science 2009 325 161 165 10.1126/science.1168243 19589993 15. Shanmugam K. Holmquist L. Steele M. Stuchbury G. Berbaum K. Schulz O. Benavente García O. Castillo J. Burnell J. Garcia Rivas V. Plant-derived polyphenols attenuate lipopolysaccharide-induced nitric oxide and tumour necrosis factor production in murine microglia and macrophages Mol. Nutr. Food Res. 2008 52 427 438 10.1002/mnfr.200700180 18186104 16. Baliga M.S. Shivashankara A.R. Haniadka R. Dsouza J. Bhat H.P. Phytochemistry, nutritional and pharmacological properties of Artocarpus heterophyllus Lam (jackfruit): A review Food Res. Int. 2011 44 1800 1811 10.1016/j.foodres.2011.02.035 17. Wei B.-L. Weng J.-R. Chiu P.-H. Hung C.-F. Wang J.-P. Lin C.-N. Antiinflammatory flavonoids from artocarpus heterophyllus and artocarpus communis J. Agric. Food Chem. 2005 53 3867 3871 10.1021/jf047873n 15884809 18. Likhitwitayawuid K. Sritularak B. Benchanak K. Lipipun V. Mathew J. Schinazi R.F. Phenolics with antiviral activity from Millettia erythrocalyx and Artocarpus lakoocha Nat. Prod. Res. 2005 19 177 182 10.1080/14786410410001704813 15715263 19. Widyawaruyanti A. Kalauni S.K. Awale S. Nindatu M. Zaini N.C. Syafruddin D. Asih P.B.S. Tezuka Y. Kadota S. New prenylated flavones from Artocarpus champeden, and their antimalarial activity in vitro J. Nat. Med. 2007 61 410 413 10.1007/s11418-007-0153-8 20. Furlan M. Roque N.F. Wolter Filho W. Cycloartane derivatives from guarea trichilioides Phytochemistry 1993 32 1519 1522 10.1016/0031-9422(93)85170-V 21. Ko F.N. Cheng Z.J. Lin C.N. Teng C.M. Scavenger and antioxidant properties of prenylflavones isolated from artocarpus heterophyllus Free Radic. Biol. Med. 1998 25 160 168 10.1016/S0891-5849(98)00031-8 9667491 22. Zheng Z.-P. Chen S. Wang S. Wang X.-C. Cheng K.-W. Wu J.-J. Yang D. Wang M. Chemical components and tyrosinase inhibitors from the twigs of artocarpus heterophyllus J. Agric. Food Chem. 2009 57 6649 6655 10.1021/jf9014685 19588925 23. Han A.-R. Kang Y.-J. Windono T. Lee S.K. Seo E.-K. Prenylated Flavonoids from the Heartwood of artocarpus c ommunis with Inhibitory Activity on Lipopolysaccharide-Induced Nitric Oxide Production J. Nat. Prod. 2006 69 719 721 10.1021/np0600346 16643064 24. Lucas K. Maes M. Role of the Toll Like receptor (TLR) radical cycle in chronic inflammation: Possible treatments targeting the TLR4 pathway Mol. Neurobiol. 2013 48 190 204 10.1007/s12035-013-8425-7 23436141 25. Xie Q.-W. Nathan C. The high-output nitric oxide pathway: Role and regulation J. Leukoc. Biol. 1994 56 576 582 7525816 26. Ghosh S. Karin M. Missing pieces in the NF-κB puzzle Cell 2002 109 81 96 10.1016/S0092-8674(02)00703-1 27. Kim K.-S. Cui X. Lee D.-S. Ko W. Sohn J.H. Yim J.H. An R.-B. Kim Y.-C. Oh H. Inhibitory effects of benzaldehyde derivatives from the marine fungus Eurotium sp. SF-5989 on inflammatory mediators via the induction of heme oxygenase-1 in lipopolysaccharide-stimulated RAW264. 7 macrophages Int. J. Mol. Sci. 2014 15 23749 23765 10.3390/ijms151223749 25535073 28. You R. Long W. Lai Z. Sha L. Wu K. Yu X. Lai Y. Ji H. Huang Z. Zhang Y. Discovery of a potential anti-inflammatory agent: 3-oxo-29-noroleana-1, 9 (11), 12-trien-2, 20-dicarbonitrile J. Med. Chem. 2013 56 1984 1995 10.1021/jm301652t 23373965 29. Carter A.B. Knudtson K.L. Monick M.M. Hunninghake G.W. The p38 mitogen-activated protein kinase is required for NF-κB-dependent gene expression THE ROLE OF TATA-BINDING PROTEIN (TBP) J. Biol. Chem. 1999 274 30858 30863 10.1074/jbc.274.43.30858 10521478 30. Franceschi C. Campisi J. Chronic inflammation (inflammaging) and its potential contribution to age-associated diseases J. Gerontol. A Biol. Sci. Med. Sci. 2014 69 S4 S9 10.1093/gerona/glu057 24833586 31. Jagtap U. Bapat V. Artocarpus: A review of its traditional uses, phytochemistry and pharmacology J. Ethnopharmacol. 2010 129 142 166 10.1016/j.jep.2010.03.031 20380874 32. Yang Z.-G. Matsuzaki K. Takamatsu S. Kitanaka S. Inhibitory effects of constituents from morus alba var. multicaulis on differentiation of 3T3-L1 cells and nitric oxide production in RAW264. 7 cells Molecules 2011 16 6010 6022 10.3390/molecules16076010 21772233 33. Baeuerle P.A. Baltimore D. NF-κB: Ten years after Cell 1996 87 13 20 10.1016/S0092-8674(00)81318-5 8858144 34. Kaminska B. MAPK signalling pathways as molecular targets for anti-inflammatory therapy—From molecular mechanisms to therapeutic benefits BBA-Proteins Proteom. 2005 1754 253 262 10.1016/j.bbapap.2005.08.017 16198162 35. Rajapakse N. Kim M.M. Mendis E. Kim S.K. Inhibition of inducible nitric oxide synthase and cyclooxygenase-2 in lipopolysaccharide-stimulated RAW264. 7 cells by carboxybutyrylated glucosamine takes place via down-regulation of mitogen-activated protein kinase-mediated nuclear factor-κB signaling Immunology 2008 123 348 357 10.1111/j.1365-2567.2007.02683.x 18205790 36. Bhaskar S. Shalini V. Helen A. Quercetin regulates oxidized LDL induced inflammatory changes in human PBMCs by modulating the TLR-NF-κB signaling pathway Immunobiology 2011 216 367 373 10.1016/j.imbio.2010.07.011 20828867 37. Qureshi A.A. Guan X.Q. Reis J.C. Papasian C.J. Jabre S. Morrison D.C. Qureshi N. Inhibition of nitric oxide and inflammatory cytokines in LPS-stimulated murine macrophages by resveratrol, a potent proteasome inhibitor Lipids Health Dis. 2012 11 1 17 10.1186/1476-511X-11-76 22221411 38. Bone R.C. Toward a theory regarding the pathogenesis of the systemic inflammatory response syndrome: What we do and do not know about cytokine regulation Crit. Care Med. 1996 24 163 172 10.1097/00003246-199601000-00026 8565523 39. Chow C.-W. Herrera Abreu M.T. Suzuki T. Downey G.P. Oxidative stress and acute lung injury Am. J. Respir. Cell Mol. Biol. 2003 29 427 431 10.1165/rcmb.F278 14500253 40. Seifert U. Bialy L.P. Ebstein F. Bech-Otschir D. Voigt A. Schröter F. Prozorovski T. Lange N. Steffen J. Rieger M. Immunoproteasomes preserve protein homeostasis upon interferon-induced oxidative stress Cell 2010 142 613 624 10.1016/j.cell.2010.07.036 20723761 41. Medzhitov R. Origin and physiological roles of inflammation Nature 2008 454 428 435 10.1038/nature07201 18650913 42. Di A. Gao X.-P. Qian F. Kawamura T. Han J. Hecquet C. Richard D.Y. Vogel S.M. Malik A.B. The redox-sensitive cation channel TRPM2 modulates phagocyte ROS production and inflammation Nat. Immunol. 2012 13 29 34 10.1038/ni.2171 22101731 43. Bayr H. Reactive oxygen species Crit. Care Med. 2005 33 498 501 10.1097/01.CCM.0000186787.64500.12 44. LeBel C.P. Ischiropoulos H. Bondy S.C. Evaluation of the probe 2′,7′-dichlorofluorescin as an indicator of reactive oxygen species formation and oxidative stress Chem. Res. Toxicol. 1992 5 227 231 10.1021/tx00026a012 1322737 45. Wang H. Khor T.O. Saw C.L.L. Lin W. Wu T. Huang Y. Kong A.-N.T. Role of Nrf2 in suppressing LPS-induced inflammation in mouse peritoneal macrophages by polyunsaturated fatty acids docosahexaenoic acid and eicosapentaenoic acid Mol. Pharm. 2010 7 2185 2193 10.1021/mp100199m 20831192 46. Trompouki E. Hatzivassiliou E. Tsichritzis T. Farmer H. Ashworth A. Mosialos G. CYLD is a deubiquitinating enzyme that negatively regulates NF-κB activation by TNFR family members Nature 2003 424 793 796 10.1038/nature01803 12917689

PMC005xxxxxx/PMC5000598.txt

==== Front Int J Mol SciInt J Mol SciijmsInternational Journal of Molecular Sciences1422-0067MDPI 10.3390/ijms17081200ijms-17-01200ArticleNon-Ligand-Induced Dimerization is Sufficient to Initiate the Signalling and Endocytosis of EGF Receptor Kourouniotis George †Wang Yi †Pennock Steven Chen Xinmei Wang Zhixiang *Tikkanen Ritva Academic EditorDepartment of Medical Genetics and Signal Transduction Research Group, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2H7, Canada; kourouniotis.george@gmail.com (G.K.); yi.wang@cnl.ca (Y.W.); spennock76@gmail.com (S.P.); xinmei.chen@ualberta.ca (X.C.)* Correspondence: zhixiang.wang@ualberta.ca; Tel.: +1-780-492-0710; Fax: +1-780-492-1998† These authors contributed equally to this work. 25 7 2016 8 2016 17 8 120006 6 2016 19 7 2016 © 2016 by the authors; licensee MDPI, Basel, Switzerland.2016This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).The binding of epidermal growth factor (EGF) to EGF receptor (EGFR) stimulates cell mitogenesis and survival through various signalling cascades. EGF also stimulates rapid EGFR endocytosis and its eventual degradation in lysosomes. The immediate events induced by ligand binding include receptor dimerization, activation of intrinsic tyrosine kinase and autophosphorylation. However, in spite of intensified efforts, the results regarding the roles of these events in EGFR signalling and internalization is still very controversial. In this study, we constructed a chimeric EGFR by replacing its extracellular domain with leucine zipper (LZ) and tagged a green fluorescent protein (GFP) at its C-terminus. We showed that the chimeric LZ-EGFR-GFP was constitutively dimerized. The LZ-EGFR-GFP dimer autophosphorylated each of its five well-defined C-terminal tyrosine residues as the ligand-induced EGFR dimer does. Phosphorylated LZ-EGFR-GFP was localized to both the plasma membrane and endosomes, suggesting it is capable of endocytosis. We also showed that LZ-EGFR-GFP activated major signalling proteins including Src homology collagen-like (Shc), extracellular signal-regulated kinase (ERK) and Akt. Moreover, LZ-EGFR-GFP was able to stimulate cell proliferation. These results indicate that non-ligand induced dimerization is sufficient to activate EGFR and initiate cell signalling and EGFR endocytosis. We conclude that receptor dimerization is a critical event in EGF-induced cell signalling and EGFR endocytosis. EGF receptorsendocytosissignal transductionleucine zipperdimerization ==== Body 1. Introduction The epidermal growth factor (EGF) receptor (EGFR) (also named as HER1 and ErbB1) is a membrane receptor with intrinsic tyrosine kinase activity. EGFR is expressed in many cell types and regulates many cell functions [1,2]. EGFR is a 170 kDa membrane glycoprotein with three domains. The extracellular domain is heavily glycosylated with 622 amino acids, which is responsible for ligand binding and receptor dimerization. The transmembrane domain is an α-helical peptide of 23 amino acids. The 542-residue intracellular domain is composed of a conserved tyrosine kinase domain followed by a regulatory C-terminal tail. While EGFR signalling is critical for the control of many normal cell functions, the aberrant activity of EGFR by mutation and overexpression has played a key role in the origin and development of tumour cells [3,4,5]. Binding of EGF to EGFR stimulates cell mitogenesis and survival through various signalling cascades. EGF also stimulates rapid EGFR endocytosis into endosomes (EN) and its eventual degradation in lysosomes [1,2]. The immediate events induced by EGF binding include receptor dimerization, activation of intrinsic tyrosine kinase and autophosphorylation. The phosphorylated EGFR interacts with many signalling proteins, including Grb2, Shc, phospholipase C-γ1 (PLC-γ1), the p85 subunit of PI3K (p85), and Src, which initiates the activation of various signalling cascades [3,4,5]. For example, the interaction between EGFR and Shc/Grb2 results in the activation of Ras/ERK signalling pathways [2]. Clearly, the early events following EGF binding including receptor dimerization, kinase activation, autophosphorylation, and association with various binding proteins are essential for EGFR signalling and endocytosis. However, little is known whether ligand binding is required for all of these post-binding events or only required for dimerization, or whether dimerization is sufficient to stimulate kinase activation, autophosphorylation, and the binding of downstream proteins. It has been shown that inhibition of EGF-stimulated dimerization of EGFR does not impair receptor autophosphorylation or transmembrane signaling [6], which suggests that ligand-induced dimerization is not necessary for the activation of EGFR and downstream signalling. On the other hand, it has been reported that oncogenic ErbB2 is constitutively dimerized and permanently active [7,8,9]. Constitutively active ErbB2 homodimers lack the ability to bind ligand are much like ligand-activated EGFR in that they internalize rapidly and bind various downstream signalling proteins including Grb2 and Shc [10]. This suggests that ligand binding serves only to dimerize receptors, and that dimerization itself may mediate downstream events, such as recruitment of the receptor to coated pits and clathrin mediated endocytosis. Crystallographic investigation of EGFR implies that ligand binding induces the conformational change in its extracellular domain necessary to render EGFR competent for dimerization [11,12]. Mutant EGFR with the deletion of the dimerization loop weakly bind to EGF, but fails to be phosphorylated [11]. We have shown that the internalization of EGFR is controlled by EGFR dimerization, rather than the activation of EGFR kinase, and EGFR C-terminal sequences 1005–1017 and dileucine (LL) motif at 1010–1011 function as endocytic codes to mediate dimerization-driven EGFR endocytosis, independent of receptor kinase activity [13,14]. By using a controllable system to specifically form homodimers and heterodimers among ErbB receptors, we further showed that the heterodimer of ErbB2 and ErbB3 is deficient in endocytosis due to the lack of endocytic codes in their C-terminus. We also showed that two compatible sets of endocytic codes are essential for receptor endocytosis. Moreover, to mediate endocytosis, these two compatible sets of endocytic codes, each contained in one receptor molecule of the dimer, need be coordinated spatially [15]. Furthermore, we showed that dimerization of platelet-derived growth factor receptor (PDGFR) through its C-terminal fused FK506-binding protein (FKBP) induces PDGFR internalization [16]. However, the controllable system that we used dimerizes the receptors intracellularly, which is very different from ligand-induced dimerization. This difference may affect the status of the dimer resulting in a different EGFR endocytosis and downstream signalling. To overcome these potential problems, in this study we chose to artificially dimerize EGFR extracellularly and then examine the effects on EGFR endocytosis and activation, and the activation of signalling cascades downstream of EGFR. To this end, we examined whether EGFR is activated simply by dimerizing its transmembrane and cytoplasmic domains extracellularly via leucine zippers (LZ). A LZ is an α helix with leucine repeats (usually five residues long) spaced at every 7th position along its length. Due to the strong hydrophobic force of leucines, two complimentary zippers form high affinity dimers in solution. Certain transcription factors, such as c-Jun and c-Fos, contain LZs [17]. Recently, the dimerization of growth hormone receptor (GHR) was reported using LZs [18]. Based on these results, we replaced the EGFR extracellular domain with a c-Fos LZ domain and tagged this chimeric receptor with EGFP. We show that chimeric LZ-EGFR-GFP is constitutively dimerized and autophosphorylated. In a manner similar to ligand-induced EGFR phosphorylation, LZ-EGFR is phosphorylated at all five of its principle C-terminal tyrosines. The phosphorylated LZ-EGFR is localized at both the plasma membrane and endosomes, suggesting it is capable of being endocytosed. Moreover, LZ-EGFR activates signalling pathways involving Shc ERK and Akt. These signals are physiologically potent, eventually leading to cell proliferation. 2. Results 2.1. Expression and Dimerization of Leucine Zipper (LZ)-Epidermal Growth Factor Receptor (EGFR)-Green Fluorescent Protein (GFP) Several EGFR plasmids were constructed (described in Materials and Methods) as shown in Figure 1. To determine whether the introduction of a LZ into EGFR results in constitutive dimerization of EGFR transmembrane and intracellular domains, we transiently transfected 293T cells with a plasmid encoding LZ-EGFR-GFP. 293T cells transfected with EGFR-GFP were used as a control. Immunoblotting of the total lysates with anti-EGFR and anti-GFP antibodies showed the presence of a strong band at 105 kD for cells transfected with LZ-EGFR-GFP, and at 210 kD for cells transfected with EGFR-GFP (Figure 2A). This indicates both LZ-EGF-GFP and EGFR-GFP were well expressed with the expected molecular weight. To determine whether the introduction of a LZ results in the dimerization of EGFR, 293T cells transiently transfected with LZ-EGFR-GFP or EGFR-GFP were crosslinked with disulfosuccinimidyl suberate (DSS). Immunoblotting with anti-EGFR and anti-GFP antibodies revealed that most of the LZ-EGFR-GFP dimerized (Figure 2B,C). As a positive control, we showed that EGFR-GFP dimerized following EGF stimulation as expected (Figure 2B,C). 2.2. Subcellular Distribution of LZ-EGFR-GFP We next determined the subcellular distribution of LZ-EGFR-GFP by fluorescence microscopy. 293T cells were transfected with LZ-EGFR-GFP, and cellular localization was determined by visualizing the intrinsic fluorescence of EGFP. 293T cells transfected with EGFR-GFP were used as the control. In all cases, cells were deprived of serum for 24 h prior to treatment/fixation to ensure that most receptors were coordinated at the plasma membrane. As shown in Figure 3A, consistent with previous findings, EGFR-GFP was localized to the plasma membrane without EGF, and then to endosomes following EGF stimulation for 30 min. LZ-EGFR-GFP, however, was localized at both the plasma membrane and intracellularly on a sub-population of vesicular structures indicative of endosomes (Figure 3A); this occurred in the absence of EGF, which is not bound by this chimeric protein in any case.. To demonstrate the localization of LZ-EGFR-GFP in endosomes, 293T cells were co-transfected with LZ-EGFR-GFP and DsRed-tagged wtRab5 (Figure 3B). A portion of LZ-EGFR-GFP co-localized with DsRed-Rab5, as shown by yellow vesicular structures, indicating that a portion of LZ-EGFR-GFP was localized to Rab5-positive endosomes. In control cells co-transfected with EGFR-GFP and DsRed-Rab5, the receptor co-localized with DsRed-Rab5 following 30 min of EGF stimulation, as expected (Figure 3B). These results suggest that a portion of LZ-EGFR-GFP is being constitutively endocytosed from the plasma membrane to endosomes, independent of ligand. The plasma membrane and endosome localization of LZ-EGFR-GFP was further analyzed by subcellular fractionation. Immunoblotting demonstrated that LZ-EGFR-GFP localized to both the plasma membrane and endosome fractions (Figure 3C,D). The early endosome antigen 1 (EEA1) was used as a marker for endosomes. As a control, wild type EGFR, pre-localized to the plasma membrane through serum-deprivation, localized to the endosomes following EGF stimulation for 30 min. 2.3. Kinase Activation and Phosphorylation of LZ-EGFR-GFP We next determined whether dimerization of EGFR by LZ resulted in the activation (phosphorylation) of the receptor. As shown in Figure 4A, immunoblotting with anti-phospho-EGFR (pEGFR) antibody revealed that both dimer and monomer of LZ-EGFR-GFP were phosphorylated. To demonstrate that this phosphorylation is induced by the intrinsic kinase activity of EGFR, we blocked EGFR kinase activity with the EGFR tyrosine kinase inhibitor AG1478 and examined the phosphorylation status of LZ-EGFR-GFP. We showed that the phosphorylation of LZ-EGFR-GFP was blocked following treatment with AG1478 (Figure 4A). This indicates that LZ-EGFR-GFP is phosphorylated by its intrinsic tyrosine kinase activity alone. This finding was further supported by indirect immunofluorescence. 293T cells were transiently transfected with LZ-EGFR-GFP or EGFR-GFP and subjected to indirect immunofluorescence with antibody to pEGFR followed with a secondary antibody conjugated with Tetramethylrhodamine (TRITC) (Figure 4B). We showed that LZ-EGFR-GFP was phosphorylated and localized to both the plasma membrane and endosomes as indicated in yellow. As expected for our control experiment, EGFR-GFP was not phosphorylated and localized to the plasma membrane prior to EGF stimulation. Following EGF stimulation for 30 min, however, the receptor was phosphorylated and internalized into endosomes. Moreover, inhibition of EGFR kinase activity by AG1478 blocked phosphorylation of both LZ-EGFR-GFP and EGFR-GFP (Figure 4B). This reinforces our finding that phosphorylation of LZ-EGFR-GFP is due to its intrinsic kinase activity. It should be noted, however, that inhibition of EGFR kinase activation by AG1478 did not inhibit the endosome localization of LZ-EGFR-GFP, consistent with our previous finding that EGFR kinase activation is not required for its internalization [19]. To eliminate the possibility that the observed activation of LZ-EGFR-GFP is due the introduction of LZ rather than the deletion of EGFR extracellular domain, we deleted LZ from LZ-EGFR-GFP and transfected 293T cells with this mutant (ΔED-EGFR-GFP). We showed that ΔED-EGFR-GFP is not phosphorylated and is only localized at the plasma membrane (Figure 5). This indicates that deletion of EGFR extracellular domain itself is not sufficient to activate EGFR and stimulate its endocytosis. Together, our results indicate that fusion of a LZ with the transmembrane and intracellular domain of EGFR leads to the dimerization of this chimeric receptor. Such dimerization then results in constitutive activation of intrinsic tyrosine kinase function and the subsequent phosphorylation of carboxyl terminal tyrosine residues. 2.4. LZ-EGFR-GFP Is Fully Activated We next compared the specific tyrosine phosphorylation status of LZ-EGFR-GFP and EGF-activated EGFR-GFP. It is well established that EGF induces the phosphorylation of multiple tyrosine residues at the C-terminus of EGFR. These tyrosine residues include Y992, Y1068, Y1086, Y1148 and Y1173. Indeed, immunoblotting of 293T cells transfected with EGFR-GFP with these five phosphotyrosine-specific antibodies revealed that all of them were activated in response to EGF stimulation. Similarly, all five tyrosine residues were phosphorylated in LZ-EGFR-GFP without EGF stimulation (Figure 6). Despite the use of SDS in our gels, a small fraction of the LZ-EGFR remained dimerized, attributable to the strength of the di-LZ association. Though the phosphorylation of LZ-EGFR dimers at tyrosine residues 1068, 1086, and 1148 were very weak, this is due to differing sensitivities of our phospho-specific EGFR, and overexposure of these membranes reveals the activated dimer (data not shown). These results indicate that constitutive dimerization induced by LZ fully activates EGFR tyrosine kinase and phosphorylates its C-terminal tyrosine residues. 2.5. Activation of Various Signalling Pathways by LZ-EGFR-GFP These five phosphorylated tyrosine residues have been shown to bind and subsequently activate numerous signalling proteins/pathways including Grb2/Shc/Ras/ERK, PI3K/Akt, and PLC-γ1 pathways [5]. We next determined the phosphorylation status of these signalling proteins in 293T cells transiently transfected with LZ-EGFR-GFP. As shown in Figure 7A, control cells transfected with EGFR-GFP and stimulated with EGF resulted in the up-shift of the Shc p66 isoform, marking it as phosphorylated. A similar up-shift of the Shc p66 isoform was observed for the cells transiently transfected with LZ-EGFR-GFP, indicating that constitutive activation of LZ-EGFR results in the activation of Shc. We next determined whether constitutively activated LZ-EGFR stimulated downstream signalling proteins including PLC-γ1, ERK, and Akt by immunoblotting with antibodies specific to phosphorylated PLC-γ1, ERK, and Akt. We showed that constitutively activated LZ-EGFR, and EGF-activated EGFR, phosphorylated PLC-γ1, ERK, and Akt (Figure 7A,B). These data indicate that non-ligand-induced dimerization of EGFR through LZ is sufficient to activate the major signalling pathways critical for various cell functions including mitogenesis and anti-apoptosis. It is interesting to note that even though the LZ-EGFR dimer is constitutively active, and leads to significant stimulation of downstream proteins, EGF induces a more robust phosphorylation of these factors. 2.6. Stimulation of Cell Proliferation by LZ-EGFR Since constitutively activated LZ-EGFR-GFP stimulates numerous signalling proteins implicated in cell mitogenesis, we determined whether LZ-EGFR-GFP induced cell proliferation. 293T cells transiently transfected with EGFR-GFP or LZ-EGFR-GFP were analyzed for cell proliferation using Bromodeoxyuridine (BrdU) incorporation experiments. As shown in Figure 8 in cells expressing EGFR-GFP, EGF stimulates strong BrdU incorporation (61%), whereas in the absence of EGF stimulation the BrdU incorporation rate is very low (17%). Expression of LZ-EGFR-GFP stimulated strong BrdU incorporation without the requirement for EGF stimulation (42%). This suggests that LZ-EGFR-GFP functions similarly to EGF-activated EGFR-GFP in promoting cell proliferation. Furthermore, to demonstrate that the strong BrdU incorporation is indeed due to the expression and kinase activity of LZ-EGFR-GFP, we treated cells with AG1478 to block the specific EGFR tyrosine kinase activity of LZ-EGFR-GFP. We showed that AG1478 reduced BrdU incorporation level to 9% in cells expressing LZ-EGFR-GFP and to 11% in EGF-stimulated cells expressing EGFR-GFP (Figure 8). Together, our results indicate that expression of LZ-EGFR-GFP stimulates cell proliferation in a manner similar to EGF-activated EGFR-GFP. These results strongly suggest dimerization of LZ-EGFR and its subsequent activation is sufficient to cause a physiological outcome such as cell mitogenesis. 3. Discussion The binding of EGF to EGFR results in the receptor dimerization, intrinsic kinase activation, C-terminal autophosphorylation, and the association with downstream signalling proteins. The early events following ligand binding are essential for EGFR to initiate cell signalling cascades, and for its endocytosis and routing to the lysosome for degradation [1]. However, it is not known whether ligand binding directly controls all of these post-binding events or whether ligand binding only controls dimerization of the receptors, while ligand-independent receptor dimerization controls EGFR kinase activation, autophosphorylation, and binding to downstream proteins. The objective of this study was to determine whether EGFR dimerization itself is sufficient to fully activate EGFR, stimulate various signalling pathways, and cause its endocytosis. To achieve this objective, we first established a system to allow EGFR to dimerize in the absence of ligand. As demonstrated in this study, we accomplished this through swapping in a LZ in place of the native extracellular domain of EGFR. Previous studies have shown that high affinity dimers form when two complimentary zippers are in close proximity to one another [17]. It was reported that the replacement of the entire extracellular domain of the growth hormone receptor (GHR) by LZ of c-Jun or c-Fos resulted in the forced dimerization of GHR. The dimerization leads to the constitutive activation of various GHR signalling pathways [18]. Using a similar approach, we fused the c-Fos LZ to the transmembrane and cytoplasmic domains of EGFR. We showed that LZ-EGFR-GFP was constitutively dimerized when transiently expressed in 293T cells (Figure 2). The dimer induced by the LZ is very stable, as we frequently observed dimerized LZ-EGFR-GFP even after SDS-PAGE under reducing conditions (Figure 5). Similar phenomena have been observed for LZ-fused growth hormone receptors [18]. A strong and stable dimerization induced by LZs provides a good model to study the role of non-ligand induced dimerization on EGFR-mediated signalling and endocytosis. By using this system, we first determined whether LZ-induced dimerization of EGFR is able to activate EGFR kinase activity and result in the autophosphorylation of EGFR C-terminal tyrosine residues. We showed that LZ-EGFR-GFP was strongly phosphorylated and this phosphorylation is dependent on the intrinsic kinase activity of EGFR (Figure 4). Moreover, the phosphorylation pattern of LZ-EGFR-GFP is very similar to that of EGF-stimulated EGFR. It is well established that EGF stimulates the phosphorylation of five major tyrosine residues at the EGFR C-terminus, including Y992, Y1068, Y1086, Y1148 and Y1173. We showed that all five tyrosine residues were phosphorylated in LZ-EGFR-GFP (Figure 6). Together, these results suggest that LZ-induced dimerization of EGFR activates EGFR kinase activity, resulting in the phosphorylation of the EGFR C-terminus to the same extent as that induced by EGF. We next determined whether LZ-induced dimerization of EGFR stimulates EGFR endocytosis and EGFR-mediated cell signalling. We showed, using both fluorescence microscopy and subcellular fractionation, that constitutive dimerization of EGFR by the LZ leads to the receptor’s internalization into endosomes in the absence of EGF (Figure 3 and Figure 4). Moreover, LZ-EGFR-GFP remains phosphorylated at both the plasma membrane and endosomes (Figure 4). Endocytosis of EGFR can therefore be achieved in the absence of ligand as long as it is dimerized, as we have demonstrated previously [19]. We have also shown that the observed constitutive activation of LZ-EGFR-GFP is indeed due to LZ-induced dimerization, rather than the deletion of the extracellular domain of EGFR (Figure 5). We further showed that constitutively active LZ-EGFR-GFP is able to stimulate many signalling proteins including SHC, PLC-γ1, Erk and Akt (Figure 7). Moreover, expression of LZ-EGFR-GFP in 293T cells induced cell proliferation in the absence of serum or EGF (Figure 8). This shows that LZ-induced dimerization of EGFR alone is sufficient to activate EGFR, induce EGFR endocytosis, stimulate various signalling pathways, and eventually cause cell proliferation. While the phosphorylation level of LZ-EGFR-GFP is similar to that of EGFR-GFP following EGF stimulation, LZ-EGFR-GFP activates downstream signalling proteins and stimulates cell proliferation to a lower extent. The diminished potency of LZ-EGFR-GFP signalling outcomes may be attributable to a couple factors. First, LZ-EGFR-GFP is constitutively endocytosed and targeted to lysosomes for degradation, which may result in the quick termination of a substantial fraction of LZ-EGFR-GFP-mediated signalling. Second, downstream signalling proteins are being constantly activated by LZ-EGFR-GFP, and thus activation levels of these signalling proteins will likely be reduced with time. Therefore, it is very reasonable to observe sustained but low levels of signalling protein activation in cells transfected with LZ-EGFR-GFP. A third factor is that the truncation and substitution of the EGFR extracellular domain may result in the slight conformation change of LZ-EGFR-GFP and consequentially a reduction in the receptor’s stimulatory potency. It is intriguing to compare LZ-EGFR-GFP with oncogenic ErbB2. It has been reported that oncogenic ErbB2 possessing a single mutation at its transmembrane domain (V664E) is constitutively dimerized and permanently active [8]. Like EGFR, this activated ErbB2 homodimer is internalized rapidly, though independent of ligand [7,10]. The constitutively activated ErbB2 also binds various downstream signalling proteins including Grb2 and Shc [20]. Similar to LZ-EGFR-GFP, ligand binding is not required for the activation, trafficking and signalling of oncogenic ErbB2, suggesting that the mutation-induced dimerization may be the principle driving force behind its activation, trafficking, and signalling potential. Other evidence supporting a role of dimerization in the activation of receptors comes from studies on a type-III deletion variant of the EGFR (EGFRvIII). EGFRvIII is devoid of amino acids 6–273, which spans the receptors EGF binding domain. Consequently, EGFRvIII is constitutively active and dimerized [21], which implies that dimerization is the key driving force for the activation of EGFRvIII. In other studies, leucine-zipper-induced dimerization of human growth hormone receptor (GHR) also leads to full activation of receptor in the absence of ligand [18]. All of these results lean towards the importance of receptor dimerization, rather than ligand binding, in receptor activation, cell signal initiation, and receptor trafficking. Various ligands including EGF and TGF-α are able to dimerize EGFR and activate EGFR tyrosine kinase activity; however, they result in modulated binding affinities to downstream proteins and different rates of EGFR endocytosis. These results may suggest that ligand binding is not only required for receptor dimerization, but also determines certain signalling outcomes following dimerization. For example, signals derived from TGF-α binding to EGFR will not lead to cell proliferation via EGFR, while EGF is sufficient to cause cell proliferation [22]. A possible explanation for the different effects of EGF and TGF-α may be different dimer stabilities affected by these two ligands. Indeed, it has been shown that binding between TGF-α and EGFR is less resistant to low pH than binding between EGF and EGFR. In early endosomes, the EGFR-TGF-α complex dissociates and EGFR recycles back to the plasma membrane [22]. It is very likely that the TGF-α-induced EGFR dimer dissociates following the uncoupling of TGF-α from EGFR; dissociation of the EGFR dimer then results in the altered trafficking and interactions with downstream signalling proteins. We have shown previously that EGFR dimerization is necessary to stimulate EGFR internalization [13]. Our results with LZ-EGFR-GFP clearly demonstrate that the dimerization of EGFR in the absence of ligand is also sufficient to activate EGFR, stimulate its endocytosis, and effect signalling. 4. Materials and Methods 4.1. Antibodies and Chemicals Rabbit polyclonal antibodies to EGFR, ERK, phosphor Akt, and Shc were purchased from Santa Cruz Biotech (Santa Cruz, CA, USA). Mouse monoclonal antibody to phospho-EGFR was from Upstate Biotechnology Inc. (Lake Placid, NY, USA). Mouse anti-phospho-PLC-γ1 antibody was from Medicore (Montreal, QC, Canada). Mouse anti-EEA1 antibodies were from BD Signal Transduction (San Jose, CA, USA). AG1478 and monensin were from Calbiochem (La Jolla, CA, USA). EGF was from Upstate Biotechnology. Unless otherwise specified, all the chemicals were purchased from Sigma (Oakville, ON, Canada). 4.2. The Plasmids The chimeric EGFR-GFP vector was engineered by inserting in frame the full-length EGFR into the pEGFP-N3 mammalian expression vector (Clontech, Palo Alto, CA, USA). A XhoI site and a KpnI site were introduce into the 5′ end and 3′ end of the full length EGFR by polymerase chain reaction (PCR), respectively. The fragment was then ligated and inserted in frame into the pEGFP-N3 mammalian expression vector. The chimeric LZ-EGFR-GFP receptor was engineered by joining the EGFR signal sequence (corresponding to amino acids-24-1 according to [23]) to the c-Fos LZ domain (corresponding to amino acids 160–200 according to author of [24]), followed by the transmembrane and intracellular domain of EGFR (corresponding to 623–1210 residues according to the authors of [23]). An XhoI site was introduce into the 5′ end and a HindIII site was introduced into the 3′ end of the EGFR signal sequence. A HindIII site and a SalI site were introduced into the c-Fos LZ 5′ end and the 3′ end by PCR, respectively. Similarly, a SalI site and a KpnI site were introduced into the 5′ end the 3′ end of the EGFR transmembrane and intracellular domain by PCR, respectively. Purified EGFR signal sequence, c-Fos LZ domain and the EGFR transmembrane and intracellular membrane domain fragments were then ligated and inserted in frame into the pEGFP-N3 vector (Clontech Laboratories, Palo Alto, CA, USA) (Figure 1). Sequence of this construct indicates the presence of EGFR leading sequence, LZ, some restriction sites and the EGFR transmembrane and intracellular domain followed by GFP. As a control, we made another construct by deleting LZ from LZ-EGFR-GFP. We termed this construct as ΔED-EGFR-GFP (Figure 1). To make ΔED-EGFR-GFP, the 3′ end SalI site of transmembrane and intracellular domain of LZ-EGFR-GFP was mutated to HindIII by PCR. Purified EGFR transmembrane and intracellular domain was then ligated with EGFR signal sequence and pEGFP-N3 vector that were excised directly from LZ-EGFR-GFP using KpnI and HindIII. The sequence of DNT-EGFR-GFP was proved by DNA sequencing. The chimeric DsRed-Rab5 vector was engineered by inserting in frame the complete Rab5 into the pDsRed-C1 mammalian expression vector (Clontech, Palo Alto, CA, USA). 4.3. Cell Culture and Treatment Human embryonic kidney 293T cells were cultured at 37 °C with Dulbecco’s Modified Eagle’s Medium (DMEM) with 10% foetal bovine serum (FBS) in a 5% CO2 atmosphere. To activate the transiently expressed chimeras, transfected cells were serum starved for 24 h. EGF was then added to a final concentration of 100 ng/mL for 30 min. For cells treated with EGFR specific tyrosine kinase inhibitor AG1478, cells transiently expressing for 48 h were treated with 0.5 µM AG1478 for 2 h and EGF was added accordingly to a final concentration of 100 ng/mL in the last 30 min. Transient transfection was carried out by calcium phosphate precipitation. 4.4. Subcellular Fractionation and Total Cell Lysates Subcellular fractionation was conducted by the method described previously [25]. Briefly, following treatment cells were scraped and homogenized inhomogenization buffer (0.25 M sucrose, 20 mM Tris-HCl, pH 7, 1 mM MgCl2, 0.5 mM Na3VO4, 0.02% NaN3, 0.1 mM 4-(2-aminoethyl)-benzenesulfonyl fluoride, 4 mM NaF, 10 g/mL aprotinin, 1 µM pepstatin A). The homogenates were centrifuged at 200× g for 5 min to remove nuclei and other cell debris (P1). Then, the post-nuclear supernatant (S1) was centrifuged for 10 min at 1500× g to generate a supernatant (S2) and a pellet (P2). Afterwards, P2 was redissolved in homogenization buffer and overlaid with an equal volume of 1.42 M sucrose buffer. Following the centrifugation at 82,000× g for 1 h the pellicule at the interface of 0.25–1.42 M was collected as the plasma membrane (PM) fraction. With further centrifugation (100,000× g for 30 min) of the S2 fraction, a soluble CY fraction and a microsomal pellet were produced. The resulting pellet was resuspended in 0.25 M sucrose buffer and overlaid on top of a discontinuous sucrose gradient containing equal volumes of 1.00 and 1.15 M sucrose in homogenization buffer. After centrifugation at 200,000× g for 1.5 h, an EN fraction at the 0.25–1.00 M interface was collected. For a typical experiment, the total yielding is 30 µg for the plasma membrane, 30 g for the EN fraction and 1 mg for the cytosol fraction. The yielding of each fraction was quite consistent under all of the treatments. For the total cell lysates, transiently expressing cells were lysed with 0.4% Triton X-100 lysis buffer (0.4% triton X-100, 140 mM NaCl, 50 mM Tris-Cl, pH 7.2, 1 mM EGTA) in the presence of protease inhibitors (0.1 mM 4-(2-aminoethyl)-benzenesulfonyl fluoride, 10 µg/mL aprotinin, 1 µM pepstatin A) for 1 h at 4 °C. Lysates were then cleared by subjection to centrifugation at 20,000× g for 30 min. The supernatant was then boiled in SDS-loading buffer (250 mM Tris-Cl, 40% glycerol, 8% sodium dodecyl sulfate, 20% β-mercaptoethanol, 2% bromophenol blue) at 95 °C for 5 min. 4.5. Immunoblotting Protein samples were separated by SDS-PAGE and then transferred onto nitrocellulose membranes (BioRad, Hercules, CA, USA) electrophoretically by a semi-dry blotting apparatus at 15 mA per minigel for 45 min in transfer buffer. Membranes were then probed with the various primary antibody followed by respective horseradish peroxidase (HRP)-conjugated secondary antibody. The protein bands were detected by enhanced chemiluminescence and exposure to X-ray film. 4.6. Dimerization Assay 293T cells were harvested and pelleted following treatment. Cell pellets were resuspended in PBS in the presence of 0.5 mM Na3VO4, 0.02% NaN3, 0.1 mM AEBSF, 10 µg/mL aprotinin, 1 µM pepstatin A. Resuspensions were then homogenized in a glass homogenizer and collected. To these homogenates the crosslinker, Disulfosuccinimidyl suberate (DSS), was added to a final concentration of 6 mM. The mixture was then incubated at room temperature for 30 min after which the reaction was quenched with 250 mM glycine for an additional 15 min at room temperature. The treated homogenate was then subjected to ultra centrifugation at 100,000× g for 1 h. The pellet collected was then lysed in 0.4% Triton X-100 lysis buffer as described above overnight at 4 °C. Lysates were then cleared by subjection to centrifugation at 20,000× g for 30 min. The supernatant was then boiled in 4× SDS-loading buffer at 95 °C for 5 min prior to SDS-PAGE. 4.7. Fluorescence Microscopy 293T cells were seeded on glass coverslips. At 70% confluency, the cells were serum starved for 24 h. Following various treatment, the cells were fixed by methanol of −20 °C. To detect EGFR-GFP and LZ-EGFR-GFP alone, fluorescence excitation of the GFP tag was visualized with a Zeiss, Axiovert 200 fluorescent microscope (Zeiss Germany, Oberkochen, Germany). Co-localization of the GFP tagged chimera with a DsRed tagged Rab5 was done following the co-transfection of both fluorescent tag-encoding vectors into 293T cells. To stain pEGFR, cells were incubated with anti-pEGFR antibody at room temperature for 1 h followed by TRITC-conjugated secondary antibody for 1 h. 4.8. Bromodeoxyuridine (BrdU) Incorporation Assay DNA synthesis was examined by bromodeoxyuridine (BrdU) incorporation. 293T cells were plated upon glass coverslips and transiently transfected with the chimeric constructs. Following expression for 48 h, cells were washed three times with PBS and serum starved for 24 h. Cells were then treated with EGF and/orAG1478 for 16 h. After incubation with BrdU (25 µM) for 8 h, cells were washed and fixed. DNA was denatured with 2 N HCl for 30 min at room temperature. To stain BrdU cells were incubated with mouse antibody to BrdU for 1 h followed by FITC-conjugated secondary antibody for 1 h. Total DNA was stained by propidium iodide (50 µg/mL). The percentage of cells with positive DNA synthesis was calculated as the ratio between the number of BrdU positive cells and the total number of cells (propidium iodide positive) × 100. For each experimental treatment, a minimum of 300 cells were counted. 5. Conclusions In conclusion, we show that substitution of the complete extracellular domain with a c-fos LZ domain results in the dimerization of EGFR. This non-ligand-induced dimerization of EGFR results in the constitutive activation of EGFR tyrosine kinase and phosphorylation at the five major tyrosine residues in the C-terminus. Constitutively activated LZ-EGFR-GFP is also constitutively endocytosed into endosomes and is able to activate several signalling pathways, including those leading to the stimulation of cell proliferation. We conclude that receptor dimerization is a critical event in EGFR activation, trafficking, and subsequent downstream signalling. Acknowledgments This work was supported in part by grants from the Canadian Institutes of Health Research (CIHR). Author Contributions All authors including George Kourouniotis, Yi Wang, Steven Pennock, Xinmei Chen and Zhixiang Wang conceived and designed the experiments, performed the experiments, analyzed the data, and participate in writing the paper. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Schematic illustration of EGFR-GFP, LZ-EGFR-GFP and ΔED-(extracellular-domain deleted)-EGFR-GFP as compared to wild type EGFR (wtEGFR). The chimeric construct LZ-EGFR-GFP started with the signal sequence of wtEGFR (line), followed by a LZ sequence that replaced the complete extracellular domain of EGFR. ΔED-EGFR-GFP is a truncated EGFR with the deletion of its entire extracellular domain. The green fluorescent protein (GFP) is tagged to the C-terminus of EGFR. Figure 2 Expression and dimerization of LZ-EGFR-GFP. 293T cells were transiently transfected with LZ-EGFR-GFP, EGFR-GFP or empty vector (GFP). (A) EGFR-GFP and LZ-EGFR-GFP were visualized by immunoblotting of the total lysates with antibodies to either EGFR or GFP; (B) Cells were crosslinked with disulfosuccinimidyl suberate (DSS). Both LZ-EGFR-GFP monomer (105 kD) and dimer (210 kD) were visible in the resulting immunoblots. EGFR-GFP dimerized only after EGF stimulation, as expected; (C) Quantification of the data from (B). The band is quantitated by densitometry with image J software (National Institute of Health, Bethesda, MD, USA) and the receptor dimerization was expressed as the percentage of dimers among the total receptor proteins. Each value is the mean of at least three independent experiments and the error bar represents the standard error. Figure 3 Subcellular distribution of LZ-EGFR-GFP. (A,B) Fluorescence analysis of subcellular EGFR localization. 293T cells were transiently transfected with LZ-EGFR-GFP or EGFR-GFP (A), or co-transfected with DsRed-Rab5 and LZ-EGFR-GFP or EGFR-GFP (B). The cells were treated with or without EGF. The subcellular localization of EGFR and Rab5 was revealed by the intrinsic fluorescence of GFP and DsRed. Co-localization of EGFR and Rab5 was indicated by yellow. Arrows denote endosomes and arrowheads denote plasma membrane regions. Size bar = 20 µm; (C) Subcellular fractionation and immunoblotting analysis. 293T cells transiently expressing LZ-EGFR-GFP were homogenized and subcellularly fractionated into cytoplasmic (CY), endosomal (EN) and plasma membrane (PM) fractions, confirmed by immunobloting the cooresponding fraction lysates with antibodies to EGFR, GFP and early endosome antigen 1 (EEA-1), respectively. 293T cells transfected with EGFR-GFP were used as controls; (D) Quantification of the data from (C). Bands were quantitated by densitometry with image J software and subcellular distribution of the proteins among the three fractions (CY, EN, and PM) was expressed as percentage of the total protein content of all three fractions combined.Each value is the average of at least three independent experiments and the error bar is the standard error. Figure 4 Phosphorylation of LZ-EGFR-GFP and the dependence on intrinsic tyrosine kinase activity. (A) Immunoblotting. 293T cells were transiently transfected with EGFR-GFP or LZ-EGFR-GFP. The cells were serum starved for 24 h and then were treated with EGF and/or AG1478 as indicated. Cell lysates were subjected to immunoblotting analysis with mouse anti-pEGFR antibody; (B) Immunofluorescence. 293T cells transiently transfected with either LZ-EGFR-GFP or EGFR-GFP were serum starved for 24 h. The cells were then treated with EGF and/or AG1478 as indicated. EGFR phosphorylation was examined by anti-pEGFR antibody followed by the secondary antibody conjugated with TRITC. Co-localization (yellow) of LZ-EGFR-GFP or EGFR-GFP (green) with p-EGFR (red) was determined by indirect immunofluorescence. Size bar = 20 µm. Figure 5 Expression, phosphorylation and subcellular localization of ΔED-EGFR-GFP. 293T cells were transiently transfected with ΔED-EGFR-GFP. (A) The expression and phosphorylation of ΔED-EGFR-GFP. Following the transfection for 48 h, the cell were lysed and total cell lysates were used to determine the expression and phosphorylation of ΔED-EGFR-GFP by immunoblotting; (B) Subcellular distribution of ΔED-EGFR-GFP. Following the transfection for 48 h, the subcellular localization of ΔED-EGFR-GFP was revealed by the intrinsic GFP and by anti-EGFR antibody followed by TRITC-conjugated secondary antibody; (C) The phosphorylation of ΔED-EGFR-GFP. Following the transfection for 48 h, the phosphorylation of ΔED-EGFR-GFP was revealed by anti-pEGFR antibody followed by TRITC-conjugated secondary antibody. Size bar = 20 µm. Figure 6 Phosphorylation of the five major C-terminal tyrosine residues of EGFR-GFP and LZ-EGFR-GFP. (A) 293T cells were transiently transfected with EGFR-GFP or LZ-EGFR-GFP. Following serum starvation for 24 h, cells were treated with or without EGF. The cell lysates were subjected to immunoblotting analysis with rabbit anti-pEGFR (pY992), anti-pEGFR (pY1068), anti-pEGFR (pY1086), anti-pEGFR (pY1148) and anti-pEGFR (pY1173) antibodies; (B) Quantification of the data from (A). The band is quantitated by densitometry with image J software. The phosphorylation level of the control (EGFR-GFP, without EGF treatment) was set to 1 and the phosphorylation of the receptors under other conditions was expressed as the fold increase compared to control. Each value is the average of at least three independent experiments and the error bar is the standard error. **: p < 0.01. Figure 7 Stimulation of various signal transduction pathways by activation of EGFR-GFP or LZ-EGFR-GFP. (A) 293T cells were transiently transfected with EGFR-GFP or LZ-EGFR-GFP. Following serum starvation for 24 h, cells were treated with or without EGF. The cell lysates were subjected to immunoblotting analysis with rabbit anti-SHC, rabbit anti-phospho-PLC-γ1, rabbit anti-PLC-γ1, mouse anti-phospho-ERK1/2, mouse anti-Erk1/2, rabbit anti-phospho-Akt and rabbit anti-Akt antibodies; (B) Quantification of the data from (A). The band is quantitated by densitometry with image J software. The protein phosphorylation level of the control (EGFR-GFP, without EGF treatment) was set to 1 and the phosphorylation of the proteins under other conditions was expressed as the fold increase compared to control. Each value is the average of at least three independent experiments and the error bar is the standard error. **: p < 0.01. Figure 8 Stimulation of DNA synthesis by LZ-EGFR-GFP. 293T cells were transiently transfected with EGFR-GFP or LZ-EGFR-GFP. Following serum starvation for 24 h, cells were treated with EGF and/or AG1478 as indicated. DNA synthesis was determined by BrdU incorporation as described in the Materials and methods. Cells were counted at 300 per sample and data was plotted as the mean of at least three experiments. The error bar is the standard error. **: p < 0.01. ==== Refs References 1. Sorkin A. Goh L.K. Endocytosis and intracellular trafficking of ErbBs Exp. Cell Res. 2009 315 683 696 10.1016/j.yexcr.2008.07.029 19278030 2. Lemmon M.A. Schlessinger J. Cell signaling by receptor tyrosine kinases 1 Cell 2010 141 1117 1134 10.1016/j.cell.2010.06.011 20602996 3. Pawson T. Protein modules and signalling networks Nature 1995 373 573 580 10.1038/373573a0 7531822 4. Pawson T. New impressions of SRC and HCK [news; comment] Nature 1997 385 582 583 10.1038/385582b0 9024653 5. Yarden Y. Sliwkowski M.X. Untangling the ErbB signalling network Nat. Rev. Mol. Cell Biol. 2001 2 127 137 10.1038/35052073 11252954 6. Carraway K.L. 3rd Cerione R.A. Inhibition of epidermal growth factor receptor aggregation by an antibody directed against the epidermal growth factor receptor extracellular domain J. Biol. Chem. 1993 268 23860 23867 8226925 7. Bargmann C.I. Hung M.C. Weinberg R.A. Multiple independent activations of the neu oncogene by a point mutation altering the transmembrane domain of p185 Cell 1986 45 649 657 10.1016/0092-8674(86)90779-8 2871941 8. Stern D.F. Kamps M.P. Cao H. Oncogenic activation of p185neu stimulates tyrosine phosphorylation in vivo Mol. Cell. Biol. 1988 8 3969 3973 10.1128/MCB.8.9.3969 2464744 9. Weiner D.B. Liu J. Cohen J.A. Williams W.V. Greene M.I. A point mutation in the neu oncogene mimics ligand induction of receptor aggregation Nature 1989 339 230 231 10.1038/339230a0 2654648 10. Gilboa L. Ben-Levy R. Yarden Y. Henis Y.I. Roles for a cytoplasmic tyrosine and tyrosine kinase activity in the interactions of neu receptors with coated pits J. Biol. Chem. 1995 270 7061 7067 7706244 11. Garrett T.P. McKern N.M. Lou M. Elleman T.C. Adams T.E. Lovrecz G.O. Zhu H.J. Walker F. Frenkel M.J. Hoyne P.A. Crystal structure of a truncated epidermal growth factor receptor extracellular domain bound to transforming growth factor α Cell 2002 110 763 773 10.1016/S0092-8674(02)00940-6 12297049 12. Ogiso H. Ishitani R. Nureki O. Fukai S. Yamanaka M. Kim J.H. Saito K. Sakamoto A. Inoue M. Shirouzu M. Crystal structure of the complex of human epidermal growth factor and receptor extracellular domains Cell 2002 110 775 787 10.1016/S0092-8674(02)00963-7 12297050 13. Wang Q. Villeneuve G. Wang Z. Control of epidermal growth factor receptor endocytosis by receptor dimerization, rather than receptor kinase activation EMBO Rep. 2005 6 942 948 10.1038/sj.embor.7400491 16113650 14. Wang Q. Zhu F. Wang Z. Identification of EGF receptor C-terminal sequences 1005–1017 and di-leucine motif 1010 LL1011 as essential in EGF receptor endocytosis Exp. Cell Res. 2007 313 3349 3363 10.1016/j.yexcr.2007.06.014 17643422 15. Wang Q. Chen X. Wang Z. Dimerization drives EGF receptor endocytosis through two sets of compatible endocytic codes J. Cell Sci. 2015 128 935 950 10.1242/jcs.160374 25588832 16. Pahara J. Shi H. Chen X. Wang Z. Dimerization drives PDGF receptor endocytosis through a C-terminal hydrophobic motif shared by EGF receptor Exp. Cell Res. 2010 316 2237 2250 10.1016/j.yexcr.2010.05.012 20580638 17. O’Shea E.K. Rutkowski R. Kim P.S. Evidence that the leucine zipper is a coiled coil Science 1989 243 538 542 10.1126/science.2911757 2911757 18. Behncken S.N. Billestrup N. Brown R. Amstrup J. Conway-Campbell B. Waters M.J. Growth hormone (GH)-independent dimerization of GH receptor by a leucine zipper results in constitutive activation J. Biol. Chem. 2000 275 17000 17007 10.1074/jbc.275.22.17000 10828073 19. Wang Y. Pennock S. Chen X. Wang Z. Endosomal signaling of epidermal growth factor receptor stimulates signal transduction pathways leading to cell survival Mol. Cell. Biol. 2002 22 7279 7290 10.1128/MCB.22.20.7279-7290.2002 12242303 20. Dankort D.L. Wang Z. Blackmore V. Moran M.F. Muller W.J. Distinct tyrosine autophosphorylation sites negatively and positively modulate neu-mediated transformation Mol. Cell. Biol. 1997 17 5410 5425 10.1128/MCB.17.9.5410 9271418 21. Fernandes H. Cohen S. Bishayee S. Glycosylation-induced conformational modification positively regulates receptor-receptor association: A study with an aberrant epidermal growth factor receptor (EGFRVIII/ΔEGFR) expressed in cancer cells J. Biol. Chem. 2001 276 5375 5383 10.1074/jbc.M005599200 11087732 22. Lenferink A.E. Kramer R.H. van Vugt M.J. Konigswieser M. di Fiore P.P. van Zoelen E.J. van de Poll M.L. Superagonistic behaviour of epidermal growth factor/transforming growth factor-α chimaeras: Correlation with receptor routing after ligand-induced internalization Biochem. J. 1997 327 859 865 10.1042/bj3270859 9581567 23. Ullrich A. Coussens L. Hayflick J.S. Dull T.J. Gray A. Tam A.W. Lee J. Yarden Y. Libermann T.A. Schlessinger J. Human epidermal growth factor receptor cDNA sequence and aberrant expression of the amplified gene in A431 epidermoid carcinoma cells Nature 1984 309 418 425 10.1038/309418a0 6328312 24. Van Beveren C. van Straaten F. Curran T. Muller R. Verma I.M. Analysis of fbj-musv provirus and c-fos (mouse) gene reveals that viral and cellular fos gene products have different carboxy termini Cell 1983 32 1241 1255 10.1016/0092-8674(83)90306-9 6301687 25. Wang Z. Zhang L. Yeung T.K. Chen X. Endocytosis deficiency of epidermal growth factor (EGF) receptor-ErbB2 heterodimers in response to EGF stimulation Mol. Biol. Cell 1999 10 1621 1636 10.1091/mbc.10.5.1621 10233167