bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel study approach on Scutellaria altissima L. cultivated at the Ghirardi Botanic Garden (Lombardy, Italy)
Authors: Giuliani C. , Bottoni M. , Ascrizzi R. , Santagostini L. , Papini A. , Flamini G. , Fico G. 
Published: August 2020

Abstract

Within an Open Science project, research was carried out to describe to the public of the Ghirardi Botanic Garden (BS, Lombardy, Italy) the invisible features of plants. This work is dedicated to Scutellaria altissima L. (Lamiaceae).

Micromorphological, histochemical and phytochemical investigations were conducted on the vegetative and reproductive organs to correlate the structures involved in the emission of substances and their unique productivity. This work reports volatile organic compound (VOC) profiles of leaves and flowers and the composition of essential oil (EO) obtained from aerial parts of plants cultivated in Italy that have never been described before.

Three morphotypes of glandular trichomes were observed: peltate, short‐stalked capitate and long‐stalked capitate. Peltate trichomes were the main producers of terpenes, short‐stalked capitates of polysaccharides and long‐stalked capitates of terpenes and polyphenols. The leaf VOC profile showed heterogeneous composition, with non‐terpene derivatives as the major chemical class (71.04%), while monoterpene hydrocarbons represented almost the totality of the flower (99.73%). The leaf presented a higher number of total (37 versus 11) and exclusive (33 versus 7) compounds. (Z)‐3‐Hexenol acetate was most abundant in the leaf and (E)‐β‐ocimene in the flower. Four common compounds were detected: β‐pinene, β‐caryophyllene, γ‐muurolene and germacrene‐D. The EO contaied 21 compounds, dominated by β‐caryophyllene, linalool and hexahydrofarnesyl acetone.

This research allowed us to correlate morphotypes of the secretory structures with the production of secondary metabolites, with the aim of providing the public of the Ghirardi Botanic Garden with a dedicated iconographic approach, which accounts for olfactory perception linked to S. altissima.
The morphological and physiological basis of delayed pollination overcoming pre‐fertilization cross‐incompatibility in Nicotiana
Authors: Chen S. ‐Y. , Zhang J. ‐W. , Wei X. ‐M. , Tao K. ‐L. , Niu Y. ‐Z. , Pan L , Zheng Y. ‐Y. , Ma W. ‐G. , Wang M. ‐Q. , Ou X. ‐K. , Liao J. ‐G. 
Published: August 2020

Abstract

Delayed pollination is widely used to overcome pre‐fertilization incompatibility, but its regulatory mechanisms are unclear. When Nicotiana tabacum was cross‐pollinated with pollen of N. alata, the incompatibility occurring in the basal 1/4 region of the style (pollinated at anthesis: 0‐day‐old pistil) was overcome by delayed pollination (of 6‐day‐old pistil), and the morphological changes and corresponding physiological basis are explored here.

The structure and ultrastructure of the pistil were observed under fluorescence microscopy and transmission electron microscopy. Differentially expressed proteins were screened with a monoclonal antibody chip for Nicotiana, and protein expression and distribution were analysed by immunofluorescence. Cellulase and pectinase activities were tested using enzyme‐linked immunosorbent assay kits.

The style of Nicotiana is solid in the basal region and pollen tubes grow in the extracellular spaces (ECM) of the transmitting tissue (TTS) cells. Seven of the 22 identified proteins were cell wall‐associated proteins and were expressed at higher levels during pistil senescence. Cellulase and pectinase activities increased. The TTS cells in the basal 1/4 region of the 0‐day‐old style were polygonal and tightly arranged, with narrow ECM, but these were oval or partially dissolved in the 6‐day‐old pistil, leading to wider ECM and richer secretions.

The increased expression of cell wall proteins and enhanced enzyme activity during pistil senescence might partially be responsible for the cells becoming oval and the ECM enlarged, providing the morphological basis for delayed pollination overcoming the pre‐fertilization incompatibility between N. tabacum and N. alata.
Estimating Densities with Non-Linear Support by Using Fisher–Gaussian Kernels
Authors: Mukhopadhyay Minerva , Li Didong , Dunson David B. 
Published: August 2020

SummaryCurrent tools for multivariate density estimation struggle when the density is concentrated near a non-linear subspace or manifold. Most approaches require the choice of a kernel, with the multivariate Gaussian kernel by far the most commonly used. Although heavy-tailed and skewed extensions have been proposed, such kernels cannot capture curvature in the support of the data. This leads to poor performance unless the sample size is very large relative to the dimension of the data. The paper proposes a novel generalization of the Gaussian distribution, which includes an additional curvature parameter. We refer to the proposed class as Fisher–Gaussian kernels, since they arise by sampling from a von Mises–Fisher density on the sphere and adding Gaussian noise. The Fisher–Gaussian density has an analytic form and is amenable to straightforward implementation within Bayesian mixture models by using Markov chain Monte Carlo sampling. We provide theory on large support and illustrate gains relative to competitors in simulated and real data applications.
A Hierarchical Mixed Effect Hurdle Model for Spatiotemporal Count Data and its Application to Identifying Factors Impacting Health Professional Shortages
Authors: Ghosal Soutik , Lau Timothy S. , Gaskins Jeremy , Kong Maiying 
Published: August 2020

SummaryCount data are common in many fields such as public health. Hurdle models have been developed to model count data when the zero count could be either inflated or deflated. However, when data are repeatedly collected over time and spatially correlated, it is very challenging to model the data appropriately. For example, to study health professional shortage areas, the number of primary care physicians along with other demographic characteristics are collected at the county level in the USA and over different years. Since the data are repeatedly collected over time, counties are nested within the state, and adjacent counties are geographically correlated, the dependence structure of the data is very complex. We develop a Bayesian hurdle model with multilayered random effects to incorporate this complex structure. We use a time-varying random effect for each state to capture the time effect at the state level, and a temporal thin plate spline to capture the spatiotemporal correlation across different counties. We use STAN to obtain samples for inference from the posterior distribution. By using the model proposed, we can identify the important factors which impact health professional shortage areas. Simulation studies also confirm the effectiveness of the model.
Autostratigraphic modelling of the growth of alluvial‐shelf systems during steady base‐level cycles: Two‐dimensional tank experiments
Authors: Wang Junhui , Muto Tetsuji 
Published: August 2020

AbstractAutostratigraphy is the stratigraphy generated by large‐scale autogenesis, developed based on the full recognition of the non‐equilibrium behaviour of depositional systems in response to steady external forcing. The existing autostratigraphic concepts were derived mostly from studies of river deltas growing during a single rise or fall of base level (or relative sea level). The present study challenges to extend the autostratigraphic framework to the alluvial‐shelf system growing through steady base‐level cycles by two‐dimensional tank experiments. During each experimental run, the base level was changed symmetrically, wherein through cycles, the rise and fall had the same constant rate (|Rbl|) and period (Tbl), and thus the same constant amplitude (Abl), but with no basin tectonism. In total, nine runs with different combinations of |Rbl| and Abl were performed. The experimental results brought the following implications. (i) The shelf‐transiting active depositional system takes non‐equilibrium responses in earlier base‐level cycles, during each of which the system experiences episodes of degradation with base‐level fall. (ii) After the system has sufficiently grown through cycles, non‐equilibrium responses change into equilibrium responses, whereby the shelf‐transiting alluvial system, whether retrogradational or progradational, is free from degradation and continues to aggrade but with a gradually decreasing rate of aggradation. (iii) The alluvial topset river tentatively but autogenically attains a graded state during the falling limb of an intermediate cycle, which separates the earlier degradation‐inclusive and later aggradation‐sustainable cycles. (iv) The number (or duration) of cycles elapsed prior to this phase‐transition is linearly proportional to the amplitude (or the square of the period) of base‐level cycles, with a coefficient defined by the rates of base‐level change and sediment supply. Such a growth pattern does not necessarily hold when considering long‐term tectonic subsidence or uplift. These notions help to understand the stratigraphic architectures of natural alluvial‐shelf systems evolved through base level cycles.
Cytomegalovirus DNA load monitoring in stool specimens for anticipating the occurrence of intestinal acute graft‐versus‐host disease following allogeneic hematopoietic stem cell transplantation: Is it of any value?
Authors: Bueno Felipe , Albert Eliseo , Giménez Estela , Piñana José Luis , Pérez Ariadna , Gómez María Dolores , Hernández‐Boluda Juan Carlos , Gonzalez‐Barberá Eva María , Montoro Juan , Guerreiro Manuel , Balaguer‐Roselló Aitana , Hernani Rafael , Sanz Jaime , Solano Carlos , Navarro David 
Published: August 2020

AbstractBackgroundData have been published suggesting a bidirectional interaction between cytomegalovirus (CMV) infection and acute graft‐versus‐host disease (aGvHD) in allogeneic hematopoietic stem cell transplant (allo‐HSCT) recipients. Here, we hypothesized that prospective CMV DNA monitoring in stool specimens may be useful for predicting subsequent occurrence of intestinal aGvHD (IaGvHD).MethodsThis two‐center study enrolled 121 consecutive adult patients undergoing any modality of allo‐HSCT. A total of 1,009 stool specimens were collected (a median of 7 specimens/patient; range, 1‐18). CMV DNA monitoring in stools and plasma was performed using real‐time PCR assays.ResultsCMV DNA was detected in stools in 20 patients (cumulative incidence, 16.9%; 95% CI, 6.3%‐31.8%). Median CMV DNA level in stool specimens was 1,258 IU/0.1g (range, 210‐4,087 IU/0.1 g). All these patients and their donors were CMV seropositive, and 16 of the 20 patients also had CMV DNAemia, while 4 patients had CMV DNA detected in stools without CMV DNAemia. No correlation was found between CMV DNA loads in plasma and stools (P = .40). Prior CMV DNAemia, aGvHD, or IaGvHD were not associated with presence of CMV DNA in feces. IaGvHD was present in 30 patients, in 5 of whom CMV DNA was detected in stools. Neither detection of CMV DNA in feces nor in plasma was associated with subsequent IaGvHD (OR, 0.67; 95% CI, 0.18‐2.52; P = .55 and OR, 0.86; 95% CI, 0.38‐1.96; P = .71, respectively). No patient in this cohort had CMV end‐organ disease within the study period.ConclusionOur study failed to provide evidence pointing to a reciprocal interaction between GI CMV infection and IaGvHD. CMV DNA monitoring in stools seems of no value to anticipate occurrence of IaGvHD.
Integrative omic and transgenic analyses reveal the positive effect of ultraviolet‐B irradiation on salvianolic acid biosynthesis through upregulation of SmNAC1
Authors: Yin Xiaojian , Fan Hui , Chen Yan , Li Lan‐Zhu , Song Wei , Fan Yuanming , Zhou Wei , Ma Gaoxiang , Alolga Raphael N. , Li Weiqiang , Zhang Baolong , Li Ping , Tran Lam‐Son P. , Lu Xu , Qi Lian‐Wen 
Published: August 2020

SUMMARYSalvianolic acids (SalAs), a group of secondary metabolites in Salvia miltiorrhiza, are widely used for treating cerebrovascular diseases. Their biosynthesis is modulated by a variety of abiotic factors, including ultraviolet‐B (UV‐B) irradiation; however, the underlying mechanisms remain largely unknown. Here, an integrated metabolomic, proteomic, and transcriptomic approach coupled with transgenic analyses was employed to dissect the mechanisms underlying UV‐B irradiation‐induced SalA biosynthesis. Results of metabolomics showed that 28 metabolites, including 12 SalAs, were elevated in leaves of UV‐B‐treated S. miltiorrhiza. Meanwhile, the contents of several phytohormones, including jasmonic acid and salicylic acid, which positively modulate the biosynthesis of SalAs, also increased in UV‐B‐treated S. miltiorrhiza. Consistently, 20 core biosynthetic enzymes and numerous transcription factors that are involved in SalA biosynthesis were elevated in treated samples as indicated by a comprehensive proteomic analysis. Correlation and gene expression analyses demonstrated that the NAC1 gene, encoding a NAC transcriptional factor, was positively involved in UV‐B‐induced SalA biosynthesis. Accordingly, overexpression and RNA interference of NAC1 increased and decreased SalA contents, respectively, through regulation of key biosynthetic enzymes. Furthermore, ChIP‐qPCR and Dual‐LUC assays showed that NAC1 could directly bind to the CATGTG and CATGTC motifs present in the promoters of the SalA biosynthesis‐related genes PAL3 and TAT3, respectively, and activate their expression. Our results collectively demonstrate that NAC1 plays a crucial role in UV‐B irradiation‐induced SalA biosynthesis. Taken together, our findings provide mechanistic insights into the UV‐B‐induced SalA biosynthesis in S. miltiorrhiza, and shed light on a great potential for the development of SalA‐abundant varieties through genetic engineering.
Effects of a Web‐Based Educational Support Intervention on Total Exercise and Cardiovascular Risk Markers in Adults With Coronary Heart Disease
Authors: Wong Eliza Mi‐Ling , Leung Doris Y. P. , Chair Sek‐Ying , Sit Janet W. H. 
Published: August 2020

AbstractBackgroundeHealth educational programs have proven to be an effective means for health promotion, yet limited studies have been conducted for coronary heart disease (CHD) patients to improve their total physical exercise, self‐efficacy for exercise, and cardiovascular risk factor profile.MethodA prospective randomized controlled trial (RCT) was conducted in two cardiac clinics in Hong Kong. Four hundred thirty‐eight eligible CHD clients were randomly assigned to either the control or the intervention group. All of the participants received standard care, which consisted of regular medical and nursing care in the cardiac clinic. The intervention group received an additional web‐based educational support intervention (eHES), which consisted of a 20‐minute individual educational session on the use of the eHES web link. The eHES web link contains a health information platform related to CHD care and an individual member area with records of health measures and physical exercise data for six months. Data were collected at baseline, at three‐month and six‐month intervals at the cardiac clinic. The primary outcome was the total amount of physical exercise, measured by the Godin–Shephard Leisure‐Time Physical Activity Questionnaire. The secondary outcomes were self‐efficacy for exercise and cardiovascular disease (CVD) risk markers (body weight, blood pressure, lipid profile). The data were analyzed using a generalized estimating equations model.ResultsThe intervention group reported a statistically higher amount of physical exercise and a higher HDL‐C at 3 and 6 months, respectively. There were no statistical differences between the groups in self‐efficacy for exercise and other CVD risk markers.Linking Evidence to ActionThe study demonstrated the effectiveness of the eHES in meeting the challenge of boosting the amount of physical exercise and increase HDL‐C among CHD patients who engaged for over three months. The results provide insight for eHealth development to support and promote exercise among CHD patients in the community.
Generating national projections of dementia cases for Ireland using a calibrated macro-simulation model
Authors: Pierse Tom , Keogh Fiona , O'Neill Stephen 
Published: August 2020

IntroductionEpidemiological data on dementia is not available in many European countries and regions due to the high cost and complexity of conducting large scale dementia screening studies. The available epidemiological studies identify potentially substantial variation in the prevalence of dementia over time and across Europe.MethodsIn this paper we generate simulations of the number of dementia cases in Ireland from 1991 to 2036 using a three-state Markov illness-death model. Parameters values are selected for each simulation from a range using a random parameter search pattern. We employ a novel calibration method which exploits the strong relationship between dementia, ageing and mortality. Simulation weights are generated based on differences between observed and modelled cohorts of older people and the reported number of deaths from dementia. Irish Census data from 1991 to 2016 and the number of recorded deaths due to dementia in 2018 are used as calibration points. A weighted average projection of the number of dementia cases is generated.ResultsWe estimate a weighted average number of cases of dementia in 2016 of 54 877 increasing to 98 946 in 2036; this estimate is substantially lower than the estimates generated using extrapolation methods. We show the wide range of possible outcomes given the range in the available parameter estimates and show that irrespective of whether the incidence rate of dementia is declining the number of cases of dementia is rapidly increasing due to population ageing.ConclusionPrevious studies have used parameter estimates from meta-analyses of the literature or from individual studies. In this paper we supplement these with a calibration approach using observed cause of death and population age structure data. These additional sources of data can be used to generate estimates of dementia prevalence in any country or region which has census data and data on deaths due to dementia.
Associations between antenatal and perinatal risk factors and cerebral palsy: a Swedish cohort study
Authors: Jöud Anna , Sehlstedt Andréa , Källén Karin , Westbom Lena , Rylander Lars 
Published: August 2020

ObjectivesTo investigate known and suggested risk factors associated with cerebral palsy in a Swedish birth cohort, stratified by gestational age.SettingInformation on all births between 1995 and 2014 in Skåne, the southernmost region in Sweden, was extracted from the national birth register.ParticipantsThe cohort comprised a total of 215 217 children. Information on confirmed cerebral palsy and subtype was collected from the national quality register for cerebral palsy (Cerebral Palsy Follow-up Surveillance Programme).Primary and secondary outcome measuresWe calculated the prevalence of risk factors suggested to be associated with cerebral palsy and used logistic regression models to investigate the associations between potential risk factors and cerebral palsy. All analyses were stratified by gestational age; term (≥37 weeks), moderately or late preterm (32–36 weeks) and very preterm (<32 weeks).ResultsIn all, 381 (0.2 %) children were assigned a cerebral palsy diagnosis. Among term children, maternal preobesity/obesity, small for gestational age, malformations, induction, elective and emergency caesarian section, Apgar <7 at 5 min and admission to neonatal care were significantly associated with cerebral palsy (all p values<0.05). Among children born moderately or late preterm, small for gestational age, malformations, elective and emergency caesarian section and admission to neonatal care were all associated with cerebral palsy (all p values <0.05), whereas among children born very preterm no factors were significantly associated with the outcome (all p values>0.05).ConclusionOur results support and strengthen previous findings on factors associated with cerebral palsy. The complete lack of significant associations among children born very preterm probably depends on to the small number of children with cerebral palsy in this group.
Risk factors for pain and functional impairment in people with knee and hip osteoarthritis: a systematic review and meta-analysis
Authors: Sandhar Sandeep , Smith Toby O , Toor Kavanbir , Howe Franklyn , Sofat Nidhi 
Published: August 2020

ObjectiveTo identify risk factors for pain and functional deterioration in people with knee and hip osteoarthritis (OA) to form the basis of a future ‘stratification tool’ for OA development or progression.DesignSystematic review and meta-analysis.MethodsAn electronic search of the literature databases, Medline, Embase, CINAHL, and Web of Science (1990–February 2020), was conducted. Studies that identified risk factors for pain and functional deterioration to knee and hip OA were included. Where data and study heterogeneity permitted, meta-analyses presenting mean difference (MD) and ORs with corresponding 95% CIs were undertaken. Where this was not possible, a narrative analysis was undertaken. The Downs & Black tool assessed methodological quality of selected studies before data extraction. Pooled analysis outcomes were assessed and reported using the Grading of Reccomendation, Assessment, Development and Evaluation (GRADE) approach.Results82 studies (41 810 participants) were included. On meta-analysis: there was moderate quality evidence that knee OA pain was associated with factors including: Kellgren and Lawrence≥2 (MD: 2.04, 95% CI 1.48 to 2.81; p<0.01), increasing age (MD: 1.46, 95% CI 0.26 to 2.66; p=0.02) and whole-organ MRI scoring method (WORMS) knee effusion score ≥1 (OR: 1.35, 95% CI 0.99 to 1.83; p=0.05). On narrative analysis: knee OA pain was associated with factors including WORMS meniscal damage ≥1 (OR: 1.83). Predictors of joint pain in hip OA were large acetabular bone marrow lesions (BML; OR: 5.23), chronic widespread pain (OR: 5.02) and large hip BMLs (OR: 4.43).ConclusionsOur study identified risk factors for clinical pain in OA by imaging measures that can assist in predicting and stratifying people with knee/hip OA. A ‘stratification tool’ combining verified risk factors that we have identified would allow selective stratification based on pain and structural outcomes in OA.PROSPERO registration numberCRD42018117643.