bluuebunny/crossref_metadata_2025 huggingface dataset:
Parallel altitudinal clines reveal trends adaptive evolution of genome size inZea mays
Authors: Bilinski Paul , Albert Patrice S. , Berg Jeremy J , Birchler James A , Grote Mark , Lorant Anne , Quezada Juvenal , Swarts Kelly , Yang Jinliang , Ross-Ibarra Jeffrey
Published: May 2017

While the vast majority of genome size variation in plants is due to differences in repetitive sequence, we know little about how selection acts on repeat content in natural populations. Here we investigate parallel changes in intraspecific genome size and repeat content of domesticated maize (Zea mays) landraces and their wild relative teosinte across altitudinal gradients in Mesoamerica and South America. We combine genotyping, low coverage whole-genome sequence data, and flow cytometry to test for evidence of selection on genome size and individual repeat abundance. We find that population structure alone cannot explain the observed variation, implying that clinal patterns of genome size are maintained by natural selection. Our modeling additionally provides evidence of selection on individual heterochromatic knob repeats, likely due to their large individual contribution to genome size. To better understand the phenotypes driving selection on genome size, we conducted a growth chamber experiment using a population of highland teosinte exhibiting extensive variation in genome size. We find weak support for a positive correlation between genome size and cell size, but stronger support for a negative correlation between genome size and the rate of cell production. Reanalyzing published data of cell counts in maize shoot apical meristems, we then identify a negative correlation between cell production rate and flowering time. Together, our data suggest a model in which variation in genome size is driven by natural selection on flowering time across altitudinal clines, connecting intraspecific variation in repetitive sequence to important differences in adaptive phenotypes.

Author summary

Genome size in plants can vary by orders of magnitude, but this variation has long been considered to be of little to no functional consequence. Studying three independent adaptations to high altitude inZea mays, we find that genome size experiences parallel pressures from natural selection, causing a linear reduction in genome size with increasing altitude. Though reductions in repetitive content are responsible for the genome size change, we find that only those individual loci contributing most to the variation in genome size are individually targeted by selection. To identify the phenotype influenced by genome size, we study how variation in genome size within a single teosinte population impacts leaf growth and cell division. We find that genome size variation correlates negatively with the rate of cell division, suggesting that individuals with larger genomes require longer to complete a mitotic cycle. Finally, we reanalyze data from maize inbreds to show that faster cell division is correlated with earlier flowering, connecting observed variation in genome size to an important adaptive phenotype.
Vimentin plays a functional role in mammary gland regeneration
Authors: Virtakoivu Reetta , Peuhu Emilia , Mai Anja , Wärri Anni , Ivaska Johanna
Published: May 2017

In the mammary gland, vimentin intermediate filaments are expressed in stromal cells and in basal epithelial cell populations including gland-reconstituting mammary stem cells (MaSC), with largely undefined functions. Here, we studied how vimentin deficiency affects mouse mammary gland development. Our results demonstrate that in adult vimentin knockout mice (Vim-/-) mammary ductal outgrowth is delayed. The adultVim-/-glands are characterised by dilated ducts, an imbalance in the proportion of basal to luminal mammary epithelial cells and a reduction in cells expressing Slug (Snai2), an established MaSC regulator. All of these features are indicative of reduced progenitor cell activity. Accordingly, isolatedVim-/-mammary epithelial cells display reduced capacity to form mammospheres, and altered organoid structure, compared to wt counterparts, when plated in a 3D matrixin vitro. Importantly, altered basal epithelial cell number translates into defects inVim-/-mammary gland regenerationin vivoin cleared fat pad transplantation studies. Furthermore, we show that vimentin contributes to stem-like cell properties in triple negative MDA-MB-231 breast cancer cells, wherein vimentin depletion reduces tumorsphere formation and alters expression of breast cancer stem cell-associated surface markers. Together, our findings identify vimentin as a positive regulator of stemness in the developing mouse mammary gland and in breast cancer cells.
Consequences of natural perturbations in the human plasma proteome
Authors: Sun Benjamin B. , Maranville Joseph C. , Peters James E. , Stacey David , Staley James R. , Blackshaw James , Burgess Stephen , Jiang Tao , Paige Ellie , Surendran Praveen , Oliver-Williams Clare , Kamat Mihir A. , Prins Bram P. , Wilcox Sheri K. , Zimmerman Erik S. , Chi An , Bansal Narinder , Spain Sarah L. , Wood Angela M. , Morrell Nicholas W. , Bradley John R. , Janjic Nebojsa , Roberts David J. , Ouwehand Willem H. , Todd John A. , Soranzo Nicole , Suhre Karsten , Paul Dirk S. , Fox Caroline S. , Plenge Robert M. , Danesh John , Runz Heiko , Butterworth Adam S.
Published: May 2017

Proteins are the primary functional units of biology and the direct targets of most drugs, yet there is limited knowledge of the genetic factors determining inter-individual variation in protein levels. Here we reveal the genetic architecture of the human plasma proteome, testing 10.6 million DNA variants against levels of 2,994 proteins in 3,301 individuals. We identify 1,927 genetic associations with 1,478 proteins, a 4-fold increase on existing knowledge, includingtransassociations for 1,104 proteins. To understand consequences of perturbations in plasma protein levels, we introduce an approach that links naturally occurring genetic variation with biological, disease, and drug databases. We provide insights into pathogenesis by uncovering the molecular effects of disease-associated variants. We identify causal roles for protein biomarkers in disease through Mendelian randomization analysis. Our results reveal new drug targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.
Mathematical model for Plant-Insect interaction with dynamic response to PAD4-BIK1 interaction and effect of BIK1 inhibition
Authors: Sanjay  , Ahmad Sabahuddin , Siddiqi M. I. , Raza Khalid
Published: May 2017

Plant-insect interaction system has been a widely studied model of the ecosystem. Attempts have long been made to understand the numerical behaviour of this counter system and make improvements in it from initial simple analogy based approach with predator-prey model to the recently developed mathematical interpretation of plant-insect interaction including concept of plant immune interventions Caughley and Lawton (1981). In our current work, we propose an improvement in the model, based on molecular interactions behind plant defense mechanism and it’s effect on the plant growth and insect herbivory. Motivated from an interaction network of plant biomolecules given by Louis and Shah (2014) and extending the model of Chattopadhyay, et al (2001), we propose here a mathematical model to show how plant insect interaction system is governed by the molecular components inside. Insect infestation mediated induction of Botrytis Induced Kinase-1 (BIK-1) protein causes inhibition of Phyto Alexin Deficient-4 (PAD4) protein. Lowered PAD4, being responsible for initiating plant defense mechanism, results in degraded plant immune potential and thus causes loss of plant quality. We adapt these interactions in our model to show how they influence the plant insect interaction system and also to reveal how silencing BIK-1 may aid in enhanced production of plant biomass by increasing plant immunity mediated by increase in PAD4 and associated antixenotic effects. We hypothesize the significance of BIK-1 inhibition which could result in the improvement of the plant quality. We explain the interaction system in BIK-1 inhibition using mathematical model. Further, we adopted the plethora of computational modeling and simulations techniques to identify the mechanisms of molecular inhibition.
A deep learning and novelty detection framework for rapid phenotyping in high-content screening
Authors: Sommer Christoph , Hoefler Rudolf , Samwer Matthias , Gerlich Daniel W.
Published: May 2017

Supervised machine learning is a powerful and widely used method to analyze high-content screening data. Despite its accuracy, efficiency, and versatility, supervised machine learning has drawbacks, most notably its dependence ona prioriknowledge of expected phenotypes and time-consuming classifier training. We provide a solution to these limitations withCellCognition Explorer, a generic novelty detection and deep learning framework. Application to several large-scale screening data sets on nuclear and mitotic cell morphologies demonstrates thatCellCognition Explorerenables discovery of rare phenotypes without user training, which has broad implications for improved assay development in high-content screening.
Fine stratification of microbial communities through a metagenomic profile of the photic zone
Authors: Haro-Moreno Jose M. , López-Pérez Mario , de la Torre José R. , Picazo Antonio , Camacho Antonio , Rodríguez-Valera Francisco
Published: May 2017

Most marine metagenomic studies of the marine photic zone analyze only samples taken at one or two depths. However, when the water column is stratified, physicochemical parameters change dramatically over relatively short depth intervals. We sampled the photic water column every 15m depth at a single point of an off-shore Mediterranean site during a period of strong stratification (early autumn) to evaluate the effects of small depth increases on the microbiome. Using genomic assembly and metagenomic read recruitment, we found major shifts in the community structure over small variations of depth, with most microbes showing a distribution limited to layers approximately 30 meters thick (stenobathic). Only some representatives of the SAR11 clade and the Sphingomonadaceae appeared to be eurybathic, spanning a greater range of depths. These results were confirmed by studying a single gene (rhodopsin) for which we also found narrow depth distributions. Our results highlight the importance of considering vertical distribution as a major element when analyzing the presence of marine clades and species or comparing the microbiome present at different locations.
How to normalize metatranscriptomic count data for differential expression analysis
Authors: Klingenberg Heiner , Meinicke Peter
Published: May 2017

BACKGROUND

Differential expression analysis on the basis of RNA-Seq count data has become a standard tool in transcriptomics. Several studies have shown that prior normalization of the data is crucial for a reliable detection of transcriptional differences. Until now it is not clear whether and how the transcriptomic approach can be used for differential expression analysis in metatranscriptomics. The potential side effects that may result from direct application of transcriptomic tools to metatranscriptomic count data have not been studied so far.

METHODS

We propose a model for differential expression in metatranscriptomics that explicitly accounts for variations in the taxonomic composition of transcripts across different samples. As a main consequence the correct normalization of metatranscriptomic count data requires the taxonomic separation of the data into organism-specific bins. Then the taxon-specific scaling of organism profiles yields a valid normalization and allows to recombine the scaled profiles into a metatranscriptomic count matrix. This matrix can then be analyzed with statistical tools for transcriptomic count data. For taxon-specific scaling and recombination of scaled counts we provide a simple R script.

RESULTS

When applying transcriptomic tools for differential expression analysis directly to metatranscriptomic data the organism-independent (global) scaling of counts implies a high risk of falsely predicted functional differences. In simulation studies we show that incorrect normalization not only tends to loose significant differences but especially can produce a large number of false positives. In contrast, taxon-specific scaling can equalize the variation of relative library sizes from different organisms and therefore shows a reliable detection of significant differences in all simulations. On real metatranscriptomic data the results from taxon-specific and global scaling can largely differ. In our study, global scaling shows a high number of extra predictions which are not supported by single transcriptome analyses. Inspection of the scaling error suggests that these extra predictions may actually correspond to artifacts of an incorrect normalization.

CONCLUSIONS

As in transcriptomics, a proper normalization of count data is also essential for differential expression analysis in metatranscriptomics. Our model implies a taxon-specific scaling of counts for normalization of the data. The application of taxon-specific scaling consequently removes taxonomic composition variations from functional profiles and therefore effectively prevents the risk of false predictions due to incorrect normalization.
Omics-based Hybrid Prediction in Maize
Authors: Westhues Matthias , Schrag Tobias A. , Heuer Claas , Thaller Georg , Friedrich Utz H. , Schipprack Wolfgang , Thiemann Alexander , Seifert Felix , Ehret Anita , Schlereth Armin , Stitt Mark , Nikoloski Zoran , Willmitzer Lothar , Schön Chris C. , Scholten Stefan , Melchinger Albrecht E.
Published: May 2017

Accurate prediction of traits with complex genetic architecture is crucial for selecting superior candidates in animal and plant breeding and for guiding decisions in personalized medicine. Whole-genome prediction (WGP) has revolutionized these areas but has inherent limitations in incorporating intricate epistatic interactions. Downstream “omics” data are expected to integrate interactions within and between different biological strata and provide the opportunity to improve trait prediction. Yet, predicting traits from parents to progeny has not been addressed by a combination of “omics” data. Here, we evaluate several “omics” predictors — genomic, transcriptomic and metabolic data — measured on parent lines at early developmental stages, and demonstrate that the integration of transcriptomic with genomic data leads to higher success rates in the correct prediction of untested hybrid combinations in maize. Despite the high predictive ability of genomic data, transcriptomic data alone outperformed them and other predictors for the most complex heterotic trait, dry matter yield. An eQTL analysis revealed that transcriptomic data integrate genomic information from both, adjacent and distant sites relative to the expressed genes. Together, these findings suggest that downstream predictors capture physiological epistasis that is transmitted from parents to their hybrid offspring. We conclude that the use of downstream “omics” data in prediction can exploit important information beyond structural genomics for leveraging the efficiency of hybrid breeding.

Key message

Complementing genomic data with other “omics” predictors can increase the probability of success for predicting the best hybrid combinations using complex agronomic traits.

Conflict of Interest

The authors declare that they have no conflict of interest.
Concurrent duplication of the Cid and Cenp-C genes in the Drosophila subgenus with signatures of subfunctionalization and male germline-biased expression
Authors: Teixeira José R. , Dias Guilherme B. , Svartman Marta , Ruiz Alfredo , Kuhn Gustavo C. S.
Published: May 2017

Despite their essential role in the process of chromosome segregation in eukaryotes, kinetochore proteins are highly diverse across species, being lost, duplicated, created, or diversified during evolution. Based on comparative genomics, the duplication of the inner kinetochore proteins CenH3 and Cenp-C, which are interdependent in their roles of stablishing centromere identity and function, can be said to be rare in animals. Surprisingly, theDrosophila CenH3homologCidunderwent four independent duplication events during evolution. Particularly interesting are the highly diverged and subfunctionalizedCid1andCid5paralogs of theDrosophilasubgenus, which show that over one thousandDrosophilaspecies may encode twoCidgenes, making those with a single copy a minority. Given that CenH3 and Cenp-C likely co-evolve as a functional unit, we investigated the molecular evolution ofCenp-Cin species ofDrosophila. We report yet anotherCidduplication within theDrosophilasubgenus and show that not onlyCid, but alsoCenp-Cis duplicated in the entire subgenus. TheCenp-Cparalogs, which we namedCenp-C1andCenp-C2, are highly divergent. The retention of key motifs involved in centromere localization and function by both Cenp-C1 and Cenp-C2 makes neofunctionalization unlikely. In contrast, the alternate conservation of some functional motifs between the proteins is indicative of subfunctionalization. Interestingly, bothCid5andCenp-C2are male germline-biased and evolved adaptively. Our findings point towards a specific inner kinetochore composition in a specific context (i.e., spermatogenesis), which could prove valuable for the understanding of how the extensive kinetochore diversity is related to essential cellular functions.
The effect of Nipped-B-Like (Nipbl) haploinsufficiency on genome-wide cohesin binding and target gene expression: modeling Cornelia de Lange Syndrome
Authors: Newkirk Daniel A. , Chen Yen-Yun , Chien Richard , Zeng Weihua , Biesinger Jacob , Flowers Ebony , Kawauchi Shimako , Santos Rosaysela , Calof Anne L. , Lander Arthur D. , Xie Xiaohui , Yokomori Kyoko
Published: May 2017

Cornelia de Lange Syndrome (CdLS) is a multisystem developmental disorder frequently associated with heterozygous loss-of-function mutations of Nipped-B-like (NIPBL), the human homolog of Drosophila Nipped-B. NIPBL loads cohesin onto chromatin. Cohesin mediates sister chromatid cohesion important for mitosis, but is also increasingly recognized as a regulator of gene expression. In CdLS patient cells and animal models, the presence of multiple gene expression changes with little or no sister chromatid cohesion defect suggests that disruption of gene regulation underlies this disorder. However, the effect of NIPBL haploinsufficiency on cohesin binding, and how this relates to the clinical presentation of CdLS, has not been fully investigated. Nipbl haploinsufficiency causes CdLS-like phenotype in mice. We examined genome-wide cohesin binding and its relationship to gene expression using mouse embryonic fibroblasts (MEFs) from Nipbl +/- mice that recapitulate the CdLS phenotype. We found a global decrease in cohesin binding, including at CCCTC-binding factor (CTCF) binding sites and repeat regions. Cohesin-bound genes were found to be enriched for histone H3 lysine 4 trimethylation (H3K4me3) at their promoters; were disproportionately downregulated in Nipbl mutant MEFs; and displayed evidence of reduced promoter-enhancer interaction. The results suggest that gene activation is the primary cohesin function sensitive to Nipbl reduction. Over 50% of significantly dysregulated transcripts in mutant MEFs come from cohesin target genes, including genes involved in adipogenesis that have been implicated in contributing to the CdLS phenotype. Thus, decreased cohesin binding at the gene regions directly contributes to disease-specific expression changes. Taken together, our Nipbl haploinsufficiency model allows us to analyze the dosage effect of cohesin loading on CdLS development.
Antecedents and consequences of electronic supply chain management diffusion
Authors: Lin Hsiu-Fen
Published: May 2017

Purpose

Grounded in the resource-based view and social exchange theory, the purpose of this paper is to develop a research model that offers a comprehensive understanding of the antecedents and consequences of electronic supply chain management (e-SCM) diffusion.

Design/methodology/approach

Survey data from 142 managers (in charge of e-SCM projects in their companies) of large Taiwanese firms were collected and used to test the hypotheses using hierarchical moderated regression analysis.

Findings

The results indicate that information technology deployment capability, operational capability, human resource capability, and knowledge sharing are important antecedents of e-SCM diffusion. In turn, higher levels of e-SCM diffusion lead to greater competitive performance. This study also finds that knowledge sharing plays a moderating role by strengthening the relationship between organizational capabilities (e.g. operational capability and human resource capability) and e-SCM diffusion.

Practical implications

Managers should recognize that human resource development activities (recruiting, training, and managing valuable e-SCM personnel) are an important source of e-SCM diffusion. Similarly, managers must establish the connection between human resource capabilities and e-SCM diffusion (i.e. “soft-side” e-SCM) such as hiring and retaining skilled e-SCM personnel, training and development for e-SCM personnel, and measuring e-SCM personnel’s global mindset over time.

Originality/value

Theoretically, this study aims to provide a research model that is capable of understanding the antecedents and consequences of e-SCM diffusion. From the managerial perspective, the findings of this study provide valuable decision guides for practitioners to help them identify and develop firm internal capabilities and social mechanisms that foster e-SCM diffusion.
Collaborative process design
Authors: Swanson David , Jin Yao Henry , Fawcett Amydee M. , Fawcett Stanley E.
Published: May 2017

Purpose

Over the past two decades, technological advances have spurred companies to design collaborative processes. Yet most such efforts are difficult to implement, with only a few resulting in sustained competitive advantages. The purpose of this paper is to leverage the tenets of socio-technical theory to examine how collaborative process design may lead to improved collaborative performance.

Design/methodology/approach

The authors employ a multi-method – survey and interview – approach to examine the roles of technical and social initiatives in mitigating resistors to collaborative performance, and identify both the short-term appeals of technology investments and long-term social resistors that inhibit additional performance gains.

Findings

While initial investments in information technology yield alluring gains, performance benefits diminish as social resistors create limiting conditions. The dynamic capability for firms to recognize and respond to the dual and integrative nature of technical and social systems is required for firms to overcome powerful limiting conditions and change resistors through collaborative process design in order to cultivate new value-creation processes.

Originality/value

This study is the first in the discipline to utilize socio-technical systems theory to examine an issue in supply chain process redesign. The multi-method approach elaborates the difficulty inherent in cultivating new value-creation processes. The results collectively illustrate a need for recognizing the influence of both the reinforcing and limiting processes. Whereas, technical initiatives enable new capabilities, social initiatives remove fear, create vision, and inculcate skills, enabling technology adoption and process change.
Measuring returns management orientation
Authors: Chen Haozhe , Anselmi Kenneth , Falasca Mauro , Tian Yu
Published: May 2017

Purpose

The field of returns management has become an important supply chain management topic. The purpose of this paper is to develop a conceptualization of returns management orientation (RMO), a topic that has been largely ignored by the academic community.

Design/methodology/approach

A series of interviews with experts and a review of the literature were used to develop the construct. Empirical survey data were used to validate the proposed RMO measurement scale.

Findings

Statistical results support the validity and reliability of the new RMO construct. Different analyses show that the proposed conceptualization satisfies the criteria of the tests for unidimensionality, construct validity, internal consistency reliability, and nomological validity. Furthermore, the results of this study confirm the positive relationship between a firm’s RMO and returns management performance.

Research limitations/implications

The present study provides a starting-point for further empirical research on returns management from a behavioral perspective.

Practical implications

RMO has a significant impact on returns management performance. The proposed RMO measurement scale provides a useful tool for companies to evaluate their management’s emphasis or recognition of the returns management function.

Originality/value

While the field of returns management has gained increased attention from both academics and practitioners, empirical research efforts on this topic are still limited. In order to address this issue, this study takes a behavioral perspective and follows a well-established approach to operationalize the construct of RMO.
World class sustainable supply chain management: critical review and further research directions
Authors: Dubey Rameshwar , Gunasekaran Angappa , Childe Stephen J. , Papadopoulos Thanos , Fosso Wamba Samuel
Published: May 2017

Purpose

Sustainable supply chain management (SSCM) has attracted considerable interest among academics and practitioners. The purpose of this paper is to present a critical review of the literature, to identify missing links, to argue for the use of world class SSCM (WCSSCM) through a framework, and suggest further research directions.

Design/methodology/approach

In the paper the authors have undertaken an extensive review of literature and classified articles using a novel classification scheme.

Findings

Through the extensive review and identification of research gaps, the paper identifies significant differences between definitions and methodologies in the SSCM literature; and argues for “WCSSCM.” This term is elaborated on via a theoretical framework in which 18 dimensions are classified under six constructs of SSCM. Furthermore, a list of potential research directions for WCSSCM is discussed.

Research limitations/implications

The research is an attempt to critically review literature, argue for WCSSCM, and develop a theoretical framework.

Originality/value

The paper offers a new approach to SSCM literature, arguing for WCSSCM through a framework, and providing further research directions.
Exploring determinants of internationalisation: the case of late starters
Authors: Köhr Christopher Karl , Malorgio Giulio , Aragrande Maurizio
Published: May 2017

Purpose

The purpose of this paper is to explore the determinants of internationalisation among late starters in the wine sector. Strategic implications for small and medium enterprises (SMEs) in a young wine producing region are derived based on the findings.

Design/methodology/approach

Data were collected through a quantitative survey among 38 wineries that are engaged in export activity in the Romagna wine producing area (Italy). Both multivariate analysis of cardinal company data through multiple and fractional regression models as well as nonparametric analysis of Likert-type survey elements were carried out.

Findings

The study identifies several determinants that affect the export intensity of businesses in the sample: Resources within the business turn out to be important, as well as the choice of distribution partners. Characteristics of exported goods were found to differ on comparing intra- and extra-EU exports.

Practical implications

Competitiveness in the international marketplace is closely linked to the product quality, distribution network and productivity of a firm. Regional networks can help businesses to develop these factors, overcome export barriers and strengthen the competitiveness of a region as a whole.

Originality/value

This study investigated the determinants of internationalisation in a wine producing region which is considered a late starter of internationalisation in the wine industry and it is the first one spotlighting on a regional firm-level in the Italian wine industry.
Kudos: bringing your publications to life?
Authors: Williams Ann E.
Published: May 2017

Purpose

The purpose of this article is to provide an overview and evaluation of Kudos, a web-based platform that aims to increase the visibility, reach, and impact of published scholarly works.

Design/methodology/approach

The review chronicles the rise of Kudos and describes the platform’s functionalities and use capabilities.

Findings

The findings detail the strengths and limitations of Kudos and point toward avenues for continued research and development.

Originality/value

This is the first review to provide a substantive evaluation of Kudos for academics to consider when adopting, utilizing and researching the platform.
Antecedents of customer aggressive behavior against healthcare employees
Authors: Gur Amit , Tzafrir Shay S. , Zatzick Christopher D. , L. Dolan Simon , Iverson Roderick
Published: May 2017

Purpose

The purpose of the research was to develop a tool for measuring antecedents of customer aggressive behavior (CAB) in healthcare service settings, by identifying its roots in organizational and interpersonal dynamics.

Design/methodology/approach

Four studies were conducted. In Studies 1 and 2, antecedents of CAB were identified through analysis of internet reader comments and a questionnaire was distributed to students. In Study 3, scenarios were used to validate the findings of the previous studies. Finally, in Study 4, a scale was developed and validated for measuring organization- and person-related triggers of CAB using samples of 477 employees and 579 customers.

Findings

The concept of CAB was conceptualized and validated. In total, 18 items were identified across five dimensions: personal characteristics, uncomfortable environment, aggressive role models, reinforcement of aggressive behavior and aversive treatment. The scale demonstrated good psychometric results.

Research limitations/implications

The research relies mainly on customer perspective. Employees and additional stakeholders should be included to achieve more accurate information that could contribute to a better understanding of CAB and its roots.

Practical implications

Exploring social and organizational antecedents that trigger CAB could help healthcare managers evaluate and proactively manage CAB and its implications within their organization.

Originality/value

This measurement scale is the first comprehensive tool, based on Bandura’s social learning theory (1973), that may identify and measure antecedents of CAB, and could be used to reduce CAB in healthcare service settings.
Transfer and Distribution of Gunshot Residue through Glass Windows
Authors: Greely Dana , Weber Emily
Published: May 2017

Research into the deposition patterns of primer gunshot residue (GSR) beyond a primary target was previously nonexistent. This study aimed to determine the deposition patterns ofGSRonce a bullet passed through an initial target and continued on its path into additional targets. Multiple repetitions were performed to assess theGSRdeposition patterns after a bullet was shot through a closed window into either a dummy or a wall within an enclosed room. Samples were taken from both the primary and secondary target holes as well as from nontarget areas. Significant amounts ofGSRwere found on all samples. The results show thatGSRcontinues to be deposited along the path of the bullet after passing through a primary glass target. These findings reiterate the lack of probative value in collectingGSRsamples from gunshot victims even if they are in an enclosed area separate from the shooter.
National epidemiological study reveals longer paediatric bone and joint infection stays for infants and in general hospitals
Authors: Laurent E , Petit L , Maakaroun‐Vermesse Z , Bernard L , Odent T , Grammatico‐Guillon L
Published: May 2017

Aim

Published studies have suggested that two to five days of intravenous treatment could effectively treat paediatric bone and joint infections (PBJI), allowing a faster discharge. This study analysed the factors associated with PBJI hospital stays lasting longer than five days using the French National Hospital Discharge Database.

Methods

We selected children under 15 years hospitalised in 2013 with haematogenous PBJIs using a validated French algorithm based on specific diagnosis and surgical procedure codes. Risk factors for stays of more than five days were analysed using logistic regression.

Results

In 2013, 2717 children were hospitalised for PBJI, with 49% staying more than five days. The overall incidence of 22 per 100 000, was highest in males and toddlers. The main causes were septic arthritis (50%) and osteomyelitis (46%) and 50% of the pathogens were Staphylococci. The odd ratios for stays of five days or more were infancy, coded bacteria and sickle cell disease (7.0), having spondylodiscitis rather than septic arthritis (2.2) and being hospitalised in a general hospital rather than a teaching hospital (1.6).

Conclusion

Half of the hospital stays exceeded five days, despite scientific evidence supporting a shorter intravenous antibiotherapy regimen. Greater knowledge and widespread use of short treatment regimens are needed.
Misbalance in type III collagen formation/degradation as a novel serological biomarker for penetrating (Montreal B3) Crohn's disease
Authors: van Haaften W. T. , Mortensen J. H. , Karsdal M. A. , Bay‐Jensen A. C. , Dijkstra G. , Olinga P.
Published: May 2017

Background

Misbalances in extracellular matrix turnover are key factors in the development of stricturing (Montreal B2) and penetrating (Montreal B3) Crohn's disease.

Aim

To determine whether serological markers for collagen formation and degradation could serve as biomarkers for complications of Crohn's disease.

Methods

Serum biomarkers for type I, III, V and VI collagen formation (P1NP, Pro‐C3, Pro‐C5, Pro‐C6) and matrix metalloproteinase mediated degradation (C1M, C3M, C5M and C6M) were measured in a retrospective, single centre cohort of 112 patients with Crohn's disease in the terminal ileum (nonstricturing/nonpenetrating: n=40, stricturing: n=55, penetrating: n=17) and 24 healthy controls. Active inflammation was defined as CRP >5 mg/L.

Results

C3M and Pro‐C5 levels were higher in penetrating vs nonpenetrating/nonstricturing and stricturing disease (33.6±5 vs 25.8±2.2 [P=.004] and 27.2±2.3 [P=.018] nmol/L C3M, 1262.7±259.4 vs 902.9±109.9 [P=.005] and 953.0±106.4 [P=.015] nmol/L Pro‐C5). C1M (71.2±26.1 vs 46.2±6.2 nmol/L [P<.001]), C3M (31.6±3.9 vs 26.1±1.6 nmol/L [P=.002] and Pro‐C5 levels (1171.7±171.5 vs 909.6±80.4 nmol/L [P=.002]) were higher in patients with active inflammation vs without active inflammation. Pro‐C3/C3M‐ratios were best to differentiate between penetrating vs nonstricturing/nonpenetrating and stricturing disease with area under the curves of 0.815±0.109 (P<.001) and 0.746±0.114 (P=.002) respectively.

Conclusions

Serological biomarkers show that penetrating Crohn's disease is characterised by increased matrix metalloproteinase‐9 degraded type III collagen and formation of type V collagen. Active inflammation in Crohn's disease is characterised by increased formation of type V collagen and increased matrix metalloproteinase mediated breakdown of type I, III collagen. Pro‐C3/C3M ratios are superior in differentiating between penetrating Crohn's disease vs inflammatory and stricturing Crohn's disease.
Infliximab and adalimumab drug levels in Crohn's disease: contrasting associations with disease activity and influencing factors
Authors: Ward M. G. , Warner B. , Unsworth N. , Chuah S.‐W. , Brownclarke C. , Shieh S. , Parkes M. , Sanderson J. D. , Arkir Z. , Reynolds J. , Gibson P. R. , Irving P. M.
Published: May 2017

Background

Discriminative drug level thresholds for disease activity endpoints in patients with Crohn's disease. have been consistently demonstrated with infliximab, but not adalimumab.

Aims

To identify threshold concentrations for infliximab and adalimumab in Crohn's disease according to different disease endpoints, and factors that influence drug levels.

Methods

We performed a cross‐sectional service evaluation of patients receiving maintenance infliximab or adalimumab for Crohn's disease. Serum drug levels were at trough for infliximab and at any time point for adalimumab. Endpoints included Harvey‐Bradshaw index, C‐reactive protein and faecal calprotectin. 6‐tioguanine nucleotide (TGN) concentrations were measured in patients treated with thiopurines.

Results

A total of 191 patients (96 infliximab, 95 adalimumab) were included. Differences in infliximab levels were observed for clinical (P=.081) and biochemical remission (P=.003) and faecal calprotectin normalisation (P<.0001) with corresponding thresholds identified on ROC analysis of 1.5, 3.4 and 5.7 μg/mL. Adalimumab levels were similar between active disease and remission regardless of the endpoint assessed. Modelling identified that higher infliximab dose, body mass index and colonic disease independently accounted for 31% of the variation in infliximab levels, and weekly dosing, albumin and weight accounted for 23% of variation in adalimumab levels. TGN levels did not correlate with drug levels.

Conclusions

Infliximab drug levels are associated with the depth of response/remission in patients with Crohn's disease, but no such relationship was observed for adalimumab. More data are needed to explain the variation in drug levels.
The Pig‐a Gene Mutation Assay in Mice and Human Cells: A Review
Authors: Olsen Ann‐Karin , Dertinger Stephen D. , Krüger Christopher T. , Eide Dag M. , Instanes Christine , Brunborg Gunnar , Hartwig Andrea , Graupner Anne
Published: May 2017

This MiniReview describes the principle of mutation assays based on the endogenous Pig‐a gene and summarizes results for two species of toxicological interest, mice and human beings. The work summarized here largely avoids rat‐based studies, as are summarized elsewhere. The Pig‐a gene mutation assay has emerged as a valuable tool for quantifying in vivo and in vitro mutational events. The Pig‐a locus is located at the X‐chromosome, giving the advantage that one inactivated allele can give rise to a mutated phenotype, detectable by multicolour flow cytometry. For in vivo studies, only minute blood volumes are required, making it easily incorporated into ongoing studies or experiments with limited biological materials. Low blood volumes also allow individuals to serve as their own controls, providing temporal information of the mutagenic process, and/or outcome of intervention. These characteristics make it a promising exposure marker. To date, the Pig‐a gene mutation assay has been most commonly performed in rats, while reports regarding its usefulness in other species are accumulating. Besides its applicability to in vivo studies, it holds promise for genotoxicity testing using cultured cells, as shown in recent studies. In addition to safety assessment roles, it is becoming a valuable tool in basic research to identify mutagenic effects of different interventions or to understand implications of various gene defects by investigating modified mouse models or cell systems. Human blood‐based assays are also being developed that may be able to identify genotoxic environmental exposures, treatment‐ and lifestyle‐related factors or endogenous host factors that contribute to mutagenesis.
Estimating the Probability of Clonal Relatedness of Pairs of Tumors in Cancer Patients
Authors: Mauguen Audrey , Seshan Venkatraman E. , Ostrovnaya Irina , Begg Colin B.
Published: May 2017

Next generation sequencing panels are being used increasingly in cancer research to study tumor evolution. A specific statistical challenge is to compare the mutational profiles in different tumors from a patient to determine the strength of evidence that the tumors are clonally related, that is, derived from a single, founder clonal cell. The presence of identical mutations in each tumor provides evidence of clonal relatedness, although the strength of evidence from a match is related to how commonly the mutation is seen in the tumor type under investigation. This evidence must be weighed against the evidence in favor of independent tumors from non-matching mutations. In this article, we frame this challenge in the context of diagnosis using a novel random effects model. In this way, by analyzing a set of tumor pairs, we can estimate the proportion of cases that are clonally related in the sample as well as the individual diagnostic probabilities for each case. The method is illustrated using data from a study to determine the clonal relationship of lobular carcinoma in situ with subsequent invasive breast cancers, where each tumor in the pair was subjected to whole exome sequencing. The statistical properties of the method are evaluated using simulations, demonstrating that the key model parameters are estimated with only modest bias in small samples in most configurations.
FPCA-based Method to Select Optimal Sampling Schedules That Capture Between-subject Variability in Longitudinal Studies
Authors: Wu Meihua , Diez-Roux Ana , Raghunathan Trivellore E. , Sánchez Brisa N.
Published: May 2017

A critical component of longitudinal study design involves determining the sampling schedule. Criteria for optimal design often focus on accurate estimation of the mean profile, although capturing the between-subject variance of the longitudinal process is also important since variance patterns may be associated with covariates of interest or predict future outcomes. Existing design approaches have limited applicability when one wishes to optimize sampling schedules to capture between-individual variability. We propose an approach to derive optimal sampling schedules based on functional principal component analysis (FPCA), which separately characterizes the mean and the variability of longitudinal profiles and leads to a parsimonious representation of the temporal pattern of the variability. Simulation studies show that the new design approach performs equally well compared to an existing approach based on parametric mixed model (PMM) when a PMM is adequate for the data, and outperforms the PMM-based approach otherwise. We use the methods to design studies aiming to characterize daily salivary cortisol profiles and identify the optimal days within the menstrual cycle when urinary progesterone should be measured.
A Bayesian Screening Approach for Hepatocellular Carcinoma Using Multiple Longitudinal Biomarkers
Authors: Tayob Nabihah , Stingo Francesco , Do Kim-Anh , Lok Anna S. F. , Feng Ziding
Published: May 2017

Advanced hepatocellular carcinoma (HCC) has limited treatment options and poor survival, therefore early detection is critical to improving the survival of patients with HCC. Current guidelines for high-risk patients include ultrasound screenings every six months, but ultrasounds are operator dependent and not sensitive for early HCC. Serum -Fetoprotein (AFP) is a widely used diagnostic biomarker, but it has limited sensitivity and is not elevated in all HCC cases so, we incorporate a second blood-based biomarker, des’ carboxy-prothrombin (DCP), that has shown potential as a screening marker for HCC. The data from the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) Trial is a valuable source of data to study biomarker screening for HCC. We assume the trajectories of AFP and DCP follow a joint hierarchical mixture model with random changepoints that allows for distinct changepoint times and subsequent trajectories of each biomarker. The changepoint indicators are jointly modeled with a Markov Random Field distribution to help detect borderline changepoints. Markov chain Monte Carlo methods are used to calculate posterior distributions, which are used in risk calculations among future patients and determine whether a patient has a positive screen. The screening algorithm was compared to alternatives in simulations studies under a range of possible scenarios and in the HALT-C Trial using cross-validation.
Conditional Adaptive Bayesian Spectral Analysis of Nonstationary Biomedical Time Series
Authors: Bruce Scott A. , Hall Martica H. , Buysse Daniel J. , Krafty Robert T.
Published: May 2017

Many studies of biomedical time series signals aim to measure the association between frequency-domain properties of time series and clinical and behavioral covariates. However, the time-varying dynamics of these associations are largely ignored due to a lack of methods that can assess the changing nature of the relationship through time. This article introduces a method for the simultaneous and automatic analysis of the association between the time-varying power spectrum and covariates, which we refer to as conditional adaptive Bayesian spectrum analysis (CABS). The procedure adaptively partitions the grid of time and covariate values into an unknown number of approximately stationary blocks and nonparametrically estimates local spectra within blocks through penalized splines. CABS is formulated in a fully Bayesian framework, in which the number and locations of partition points are random, and fit using reversible jump Markov chain Monte Carlo techniques. Estimation and inference averaged over the distribution of partitions allows for the accurate analysis of spectra with both smooth and abrupt changes. The proposed methodology is used to analyze the association between the time-varying spectrum of heart rate variability and self-reported sleep quality in a study of older adults serving as the primary caregiver for their ill spouse.
Prognostic utility of biopsy‐derived cell cycle progression score in patients with National Comprehensive Cancer Network low‐risk prostate cancer undergoing radical prostatectomy: implications for treatment guidance
Authors: Tosoian Jeffrey J. , Chappidi Meera R. , Bishoff Jay T. , Freedland Stephen J. , Reid Julia , Brawer Michael , Stone Steven , Schlomm Thorsten , Ross Ashley E.
Published: May 2017

Objectives

To determine the prognostic utility of the cell cycle progression (CCP) score in men with National Comprehensive Cancer Network (NCCN)‐defined low‐risk prostate cancer (PCa) undergoing radical prostatectomy (RP).

Patients and Methods

Men who underwent RP for Gleason score ≤6 PCa at three institutions (Martini Clinic [MC], Durham Veterans Affairs Medical Center [DVA] and Intermountain Healthcare [IH]) were identified. The CCP score was obtained from diagnostic (DVA, IH) or simulated biopsies (MC). The primary outcome was biochemical recurrence (BCR; prostate‐specific antigen ≥0.2 ng/mL) after RP. The prognostic utility of the CCP score was assessed using Kaplan–Meier analysis and multivariable Cox proportional hazards models in the subset of men meeting NCCN low‐risk criteria and in the overall cohort.

Results

Among the 236 men identified, 80% (188/236) met the NCCN low‐risk criteria. Five‐year BCR‐free survival for the low (<0), intermediate (0–1) and high (>1) CCP score groups was 89.2%, 80.4%, 64.7%, respectively, in the low‐risk cohort (P = 0.03), and 85.9%, 79.1%, 63.1%, respectively, in the overall cohort (P = 0.041). In multivariable models adjusting for clinical and pathological variables with the Cancer of the Prostate Risk Assessment (CAPRA) score, the CCP score was an independent predictor of BCR in the low‐risk (hazard ratio [HR] 1.77 per unit score, 95% confidence interval [CI] 1.21, 2.58; P = 0.003) and overall cohorts (HR 1.41 per unit score, 95% CI 1.02, 1.96; P = 0.039).

Conclusion

In a cohort of men with NCCN‐defined low‐risk PCa, the CCP score improved clinical risk stratification of men who were at increased risk of BCR, which suggests the CCP score could improve the assessment of candidacy for active surveillance and guide optimum treatment selection in these patients with otherwise similar clinical characteristics.