bluuebunny/crossref_metadata_2025_split huggingface dataset:
To act or not to act: responses to electronic health record prompts by family medicine clinicians
Authors: Zazove Philip , McKee Michael , Schleicher Lauren , Green Lee , Kileny Paul , Rapai Mary , Mulhem Elie 
Published: December 2016

Objective: A major focus of health care today is a strong emphasis on improving the health and quality of care for entire patient populations. One common approach utilizes electronic clinical alerts to prompt clinicians when certain interventions are due for individual patients being seen. However, these alerts have not been consistently effective, particularly for less visible (though important) conditions such as hearing loss (HL) screening.Materials and Methods: We conducted hour-long cognitive task analysis interviews to explore how family medicine clinicians view, perceive, and use electronic clinical alerts, and to utilize this information to design a more effective alert using HL identification and referral as a model diagnosis.Results: Four key direct barriers were identified that impeded alert use: poor standardization and formatting, time pressures in primary care, clinic workflow variations, and mental models of the condition being prompted (in this case, HL). One indirect barrier was identified: electronic health record and institution/government regulations. We identified that clinicians’ mental model of the condition being prompted was probably the major barrier, though this was often expressed as time pressure. We discuss solutions to each of the 5 identified barriers, such as addressing physicians’ mental models, by focusing on physicians’ expertise rather than knowledge to improve their comfort when caring for patients with the conditions being prompted.Conclusions: To unleash the potential of electronic clinical alerts, electronic health record and health care institutions need to address some key barriers. We outline these barriers and propose solutions.
Mechanobiological implications of articular cartilage crystals
Authors: Carlson Alyssa K. , McCutchen Carley N. , June Ronald K. 
Published: December 2016

Purpose of review
Calcium crystals exist in both pathological and normal articular cartilage. The prevalence of these crystals dramatically increases with age, and crystals are typically found in osteoarthritic cartilage and synovial fluid. Relatively few studies have examined the effects of crystals on cartilage biomechanics or chondrocyte mechanotransduction. The purpose of this review is to describe how crystals could influence cartilage biomechanics and mechanotransduction in osteoarthritis.

Recent findings
Crystals are found in both loaded and unloaded regions of articular cartilage. Exogenous crystals, in combination with joint motion, result in substantial joint inflammation. Articular cartilage vesicles promote crystal formation, and these vesicles are found near the periphery of chondrocytes. Crystallographic studies report monoclinic symmetry for synthetic crystals, suggesting that crystals will have a large stiffness compared with the cartilage extracellular matrix, the pericellular matrix, or the chondrocyte. This stiffness imbalance may cause crystal-induced dysregulation of chondrocyte mechanotransduction promoting both aging and osteoarthritis chondrocyte phenotypes.

Summary
Because of their high stiffness compared with cartilage matrix, crystals likely alter chondrocyte mechanotransduction, and high concentrations of crystals within cartilage may alter macroscale biomechanics. Future studies should focus on understanding the mechanical properties of joint crystals and developing methods to understand how crystals affect chondrocyte mechanotransduction.
Short article: Capsule endoscopy in graft-versus-host disease
Authors: Pérez-Cuadrado-Robles Enrique , Castilla-Llorente Cristina , Quénéhervé Lucille , López-Higueras Antonio , Pérez-Cuadrado-Martínez Enrique 
Published: December 2016

Introduction
The gold standard in the diagnosis of gastrointestinal graft-versus-host disease (GVHD) after allogenic hematopoietic stem cell transplantation is conventional endoscopy with histopathological assessment. The role of capsule endoscopy (CE) is uncertain. The aim of the present study was to investigate the accuracy of CE in this setting, comparing the clinical, endoscopic and histological data.

Methods
This was a retrospective single-centre study that included 57 (mean age: 47.18±15.05 years, 57.89% men) patients presenting with GVHD who underwent a valid CE and histopathological analysis by conventional endoscopy between January 2004 and July 2016. The endoscopic scored findings, clinical data and histopathological diagnosis were compared using duodenal histology as the gold standard.

Results
CE detected mild (n=4, 7.02%), moderate (n=6, 10.53%) and severe (n=21, 36.84%) grades, with a higher diagnostic yield than conventional endoscopy (54.39 vs. 28.07%, P<0.001). A positive CE predicted positive histology (80.64 vs. 15.38%, P<0.001) with a sensitivity, specificity, negative predictive value and accuracy of 86.21, 78.57, 84.62 and 82.46%. This procedure detected more mild-to-moderate histological lesions than conventional endoscopy (8.77 vs. 3.51%, P=0.25). In addition, 16% of patients with a previous normal endoscopy with biopsies had a pathological CE and there were eight (25.81%) patients with positive CE images unreachable by conventional endoscopy.

Conclusion
CE is a useful device in GVHD, achieving high accuracy values and diagnostic yield. However, its results may be interpreted in conjunction with clinical and histological features, particularly in mild-to-moderate stages.
MultiCellDS: a standard and a community for sharing multicellular data
Authors: Friedman Samuel H. , Anderson Alexander R. A. , Bortz David M. , Fletcher Alexander G. , Frieboes Hermann B. , Ghaffarizadeh Ahmadreza , Grimes David Robert , Hawkins-Daarud Andrea , Hoehme Stefan , Juarez Edwin F. , Kesselman Carl , Merks Roeland M.H. , Mumenthaler Shannon M. , Newton Paul K. , Norton Kerri-Ann , Rawat Rishi , Rockne Russell C. , Ruderman Daniel , Scott Jacob , Sindi Suzanne S. , Sparks Jessica L. , Swanson Kristin , Agus David B. , Macklin Paul 
Published: December 2016

AbstractCell biology is increasingly focused on cellular heterogeneity and multicellular systems. To make the fullest use of experimental, clinical, and computational efforts, we need standardized data formats, community-curated “public data libraries”, and tools to combine and analyze shared data. To address these needs, our multidisciplinary community created MultiCellDS (MultiCellular Data Standard): an extensible standard, a library of digital cell lines and tissue snapshots, and support software. With the help of experimentalists, clinicians, modelers, and data and library scientists, we can grow this seed into a community-owned ecosystem of shared data and tools, to the benefit of basic science, engineering, and human health.
Practical Use of Methods for Imputation of HLA Alleles from SNP Genotype Data
Authors: Motyer Allan , Vukcevic Damjan , Dilthey Alexander , Donnelly Peter , McVean Gil , Leslie Stephen 
Published: December 2016

AbstractThe human leukocyte antigen (HLA) genes play an essential role in immune function. Typing of HLA alleles is critical for transplantation and is informative for many disease associations. The high cost of accurate lab-based HLA typing has precluded its use in large-scale disease-association studies. The development of statistical methods to type alleles using linkage disequilibrium with nearby SNPs, called HLA imputation, has allowed large cohorts of individuals to be typed accurately, so that massive numbers of affected individuals and controls may be studied. This has resulted in many important findings. Several HLA imputation methods have been widely used, however their relative performance has not been adequately addressed. We have conducted a comprehensive study to evaluate the most widely used HLA imputation methods. We assembled a multi-ethnic panel of 10,561 individuals with SNP genotype data and lab-based typing of alleles at 11 HLA genes at two-field resolution, and used it to train and validate each method. Use of this panel leads to imputation accuracy far superior to what is currently publicly available. We present a highly-accurate new imputation method, HLA*IMP:03. We address the question of optimal use of HLA imputations in tests of genetic association, showing that it is usually not necessary to apply a probability threshold to achieve maximal power. We also investigated the effect on accuracy of SNP density and population stratification at the continental level and show that neither of these are a significant concern.
Direct and context-dependent effects of light, temperature, and phytoplankton shape bacterial community composition
Authors: Paver Sara F. , Kent Angela D. 
Published: December 2016

AbstractSpecies interactions, environmental conditions, and stochastic processes work in concert to bring about changes in community structure. However, the relative importance of specific factors and how their combined influence affects community composition remain largely unclear. We conducted a multi-factorial experiment to 1) disentangle the direct and interaction-mediated effects of environmental conditions and 2) augment our understanding of how environmental context modulates species interactions. We focus on a planktonic system where interactions with phytoplankton effect changes in the composition of bacterial communities, and light and temperature conditions can influence bacteria directly as well as through their interactions with phytoplankton. Epilimnetic bacteria from two humic lakes were combined with phytoplankton assemblages from each lake (“home” or “away”) or a no-phytoplankton control and incubated for 5 days under all combinations of light (surface, ∼25% surface irradiance) and temperature (5 levels from 10°C to 25°C). Observed light effects were primarily direct while phytoplankton and temperature effects on bacterial community composition were highly interdependent. The influence of temperature on aquatic bacteria was consistently mediated by phytoplankton and most pronounced for bacteria incubated with “away” phytoplankton treatments, likely due to the availability of novel phytoplankton-derived resources. The effects of phytoplankton on bacterial community composition were generally increased at higher temperatures. Incorporating mechanisms underlying the observed interdependent effects of species interactions and environmental conditions into modeling frameworks may improve our ability to forecast ecological responses to environmental change.
Yorkie is required to restrict the injury responses in planarians
Authors: Lin Alexander Y.T. , Pearson Bret J. 
Published: December 2016

AbstractRegeneration requires the precise integration of cues that initiate proliferation, direct differentiation, and ultimately re-pattern tissues to the proper size and scale. Yet how these processes are integrated with wounding cues remains relatively unknown. The freshwater planarian,Schmidtea mediterranea, is an ideal model to study the stereotyped proliferative and transcriptional responses to injury due to its high capacity for regeneration. Here, we characterize the effector of the Hippo signalling cascade,yorkie, during planarian regeneration and its role in restricting early injury responses. Inyki(RNAi)regenerating animals, wound responses are hyper-activated; the bimodal proliferation kinetics are heighted and prolonged, while the transcriptional injury responses are similarly augmented with dysregulated temporal patterns. We also uncovered novel wound-induced genes by RNAseq that are primarily associated with tissue patterning. Indeed, a high proportion of non-wound- and wound-induced patterning molecules are mis-expressed inyki(RNAi), which we demonstrate is in part due to an expanded muscle cell population. These altered injury responses have consequential effects on regenerative outcomes, specifically sensing the size of a given injury and appropriately scaling organ and tissue sizes. Taken together, our results suggest thatykifunctions as a key node to integrate the injury responses of proliferation, apoptosis, injury-induced transcription, and patterning to coordinate regeneration.
NextSV: a meta-caller for structural variants from low-coverage long-read sequencing data
Authors: Fang Li , Hu Jiang , Wang Depeng , Wang Kai 
Published: December 2016

AbstractBackgroundStructural variants (SVs) in human genomes are implicated in a variety of human diseases. Long-read sequencing delivers much longer read lengths than short-read sequencing and may greatly improve SV detection. However, due to the relatively high cost of long-read sequencing, it is unclear what coverage is needed and how to optimally use the aligners and SV callers.ResultsIn this study, we developed NextSV, a meta-caller to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different analysis purposes. We evaluated SV calling performance of NextSV under different PacBio coverages on two personal genomes, NA12878 and HX1. Our results showed that, compared with running any single SV caller, NextSV stringent call set had higher precision and balanced accuracy (F1 score) while NextSV sensitive call set had a higher recall. At 10X coverage, the recall of NextSV sensitive call set was 93.5% to 94.1% for deletions and 87.9% to 93.2% for insertions, indicating that ~10X coverage might be an optimal coverage to use in practice, considering the balance between the sequencing costs and the recall rates. We further evaluated the Mendelian errors on an Ashkenazi Jewish trio dataset.ConclusionsOur results provide useful guidelines for SV detection from low coverage whole-genome PacBio data and we expect that NextSV will facilitate the analysis of SVs on long-read sequencing data.
Evolutionary rescue through partly heritable phenotypic variability
Authors: Carja Oana , Plotkin Joshua B. 
Published: December 2016

AbstractEnvironmental variation is commonplace, but unpredictable. Populations that encounter a deleterious environment can sometimes avoid extinction by rapid evolutionary adaptation. Phenotypic variability, whereby a single genotype can express multiple different phenotypes, might play an important role in rescuing such populations from extinction. This type of evolutionary bet-hedging need not confer a direct benefit to a single individual, but it may increase the chance of long-term survival of a lineage. Here we develop a population-genetic model to explore how partly heritable phenotypic variability influences the probability of evolutionary rescue and the mean duration of population persistence in changing environments. We find that the probability of population persistence depends non-monotonically on the degree of phenotypic heritability between generations: some heritability can help avert extinction, but too much heritability removes any benefit of phenotypic variability. We discuss the implications of these results in the context of therapies designed to eradicate populations of pathogens or aberrant cellular lineages.
LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell
Authors: Sperschneider Jana , Catanzariti Ann-Maree , DeBoer Kathleen , Petre Benjamin , Gardiner Donald M. , Singh Karam B , Dodds Peter N. , Taylor Jennifer M. 
Published: December 2016

AbstractPathogens are able to deliver effector proteins into plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. Although many computational methods exist to predict plant protein subcellular localization, they perform poorly for effectors. We introduce LOCALIZER for predicting plant and effector protein localization to chloroplasts, mitochondria, and nuclei. LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial targeting compared to other methods for 652 plant proteins. For 108 eukaryotic effectors, LOCALIZER outperforms other methods and predicts a previously unrecognized chloroplast transit peptide for the ToxA effector, which we show translocates into tobacco chloroplasts. Secretome-wide predictions and confocal microscopy reveal that rust fungi might have evolved multiple effectors that target chloroplasts or nuclei. LOCALIZER is the first method for predicting effector localisation in plants and is a valuable tool for prioritizing effector candidates for functional investigations. LOCALIZER is available athttp://localizer.csiro.au/.
On the origin of nonequivalent states: how we can talk about preprints
Authors: Neylon Cameron , Pattinson Damian , Bilder Geoffrey , Lin Jennifer 
Published: December 2016

AbstractIncreasingly, preprints are at the center of conversations across the research ecosystem. But disagreements remain about the role they play. Do they “count” for research assessment? Is it ok to post preprints in more than one place? In this paper, we argue that these discussions often conflate two separate issues, the history of the manuscript and the status granted it by different communities. In this paper, we propose a new model that distinguishes the characteristics of the object, its “state”, from the subjective “standing” granted to it by different communities. This provides a way to discuss the difference in practices between communities, which will deliver more productive conversations and facilitate negotiation on how to collectively improve the process of scholarly communications not only for preprints but other forms of scholarly contributions.
Familial heterogeneity in breast cancer predisposition: a study of 22 Utah families
Authors: O’Brien Elizabeth , Kerber Richard A. , White Raymond L. 
Published: December 2016

AbstractThe problem of “missing heritability” in genome-wide analyses of complex diseases is thought to be attributable to some combination of: rare variants of moderate to large effect, common variants of very small effect, and epigenetic, epistatic, or shared environmental effects. Rare variants do not affect large numbers of people by definition, but identified genes and pathways frequently lead to important insights into pathogenesis, and become targets of chemoprevention or therapy. Family studies remain an efficient way to identify rare variants with sizable effects on disease risk. We present a genome-wide study of breast cancer in 22 large high-risk families including 154 women diagnosed with breast cancer. Appropriate marker spacing was achieved by simulation studies of founder haplotypes to reduce the chance that linkage disequilibrium produced spurious linkage peaks. For each family, we generated 100 simulations of null linkage genome-wide to estimate the probability that individual results were due to chance. We identified a total of 12 putative susceptibility regions with per-family genome-wide probability < 0.05. These regions were located on 10 chromosomes; 10 of the 22 families showed linkage at these locations; two or more families showed linkage to 6 regions on 5 chromosomes (4q, 5q, 6p, 14q, 18p, and 18q). These results indicate that there is considerable heterogeneity among families in genomic regions and thus variants predisposing to breast cancer. Moreover, they suggest that uncommon high– or medium-risk genetic variants remain to be found, and that family designs can be an efficient way to identify them.
Paradoxes in Leaky Microbial Trade
Authors: Kallus Yoav , Miller John H. , Libby Eric 
Published: December 2016

ABSTRACTMicrobes produce metabolic resources that are important for cell growth yet leak across membranes into the extracellular environment. Other microbes in the same environment can use these resources and adjust their own metabolic production accordingly—causing other resources to leak into the environment. The combined effect of these processes is an economy in which organismal growth and metabolic production are coupled to others in the community. We propose a model for the co-evolving dynamics of metabolite concentrations, production regulation, and population frequencies for the case of two cell types, each requiring and capable of producing two metabolites. In this model, beneficial trade relations emerge without any coordination, via individual-level production decisions that maximize each cell’s growth rate given its perceived environment. As we vary production parameters of the model, we encounter three paradoxical behaviors, where a change that should intuitively benefit some cell type, actually harms it. (1) If a cell type is more efficient than its counterpart at producing a metabolite and becomes even more efficient, its frequency in the population can decrease. (2) If a cell type is less efficient than its counterpart at producing a metabolite but becomes less inefficient, the growth rate of the population can decrease. (3) Finally, if a cell type controls its counterpart’s production decisions so as to maximize its own growth rate, the ultimate growth rate it achieves can be lower than if the two cell types each maximized their own growth. These three paradoxes highlight the complex and counter-intuitive dynamics that emerge in simple microbial economies.
Impact of implementation choices on quantitative predictions of cell-based computational models
Authors: Kursawe Jochen , Baker Ruth E. , Fletcher Alexander G. 
Published: December 2016

Abstract‘Cell-based’ models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.