bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlates of Disclosing Sexual Victimization to a Resident Assistant: A Study of College Women
Authors: Rahman Anusha , Collibee Charlene , Orchowski Lindsay M. 
Published: August 2024

ABSTRACT
First-year college women are at a high risk for sexual victimization. Staff within residence halls play an important role in connecting students who experience harm with resources. This study utilized survey assessments to examine correlates of likelihood to disclose sexual victimization to a resident assistant among a sample of first-year college women (N = 374). History of sexual victimization, self-concealment, attitudes toward psychological care, and social support were evaluated as correlates of likelihood to disclose to a resident assistant. A history of sexual victimization, level of self-concealment, and attitudes toward seeking psychological care showed a negative association to perceived likelihood to report sexual victimization to a resident assistant. Self-esteem, tendency to disclose sensitive information, tendency to cope via problem solving, social support grounded in guidance, and social support providing reassurance of worth were positively associated with perceived likelihood to disclose to a resident assistant. Multivariate analyses revealed that having no history of prior sexual victimization, high levels of social support that offered reassurance of worth, and a greater tendency to disclose sensitive information emerged as salient multivariate predictors of college women's perceived likelihood to disclose sexual victimization to a resident assistant. Findings increase our understanding of the individual characteristics that influence whether someone seeks assistance from a resident assistant after sexual assault and which students may benefit from additional outreach to connect with university resources after experiences of sexual violence.
Investigating orientation adaptation following naturalistic film viewing
Authors: A-Izzeddin Emily J , Rideaux Reuben , Mattingley Jason B , Harrison William J 
Published: August 2024

AbstractHumans display marked changes to their perceptual experience of a stimulus following prolonged or repeated exposure to a preceding stimulus. A well-studied example of such perceptual adaptation is the tilt-aftereffect. Here, prolonged exposure to one orientation leads to a shift in the perception of subsequent orientations. Such a capacity to adapt suggests the visual system is dynamically tuned to our current visual environment. However, it remains unclear to what extent adaptation occurs in response to systematic features in naturalistic scenes. We therefore investigated orientation adaptation in response to natural viewing of filtered live-action film stimuli. Within a session, participants freely viewed 45 minutes of a film which had been filtered to include increased contrast energy within a specified orientation band (0°, 45°, 90°, or 135°; i.e., the adaptor). To measure adaptation effects, the film was intermittently interrupted to have participants perform a simple orientation judgement task. Having participants complete behavioural trials throughout the testing session, including 45 minutes of total adaptation time, allowed investigation of the accumulation of response biases and changes in such biases over the course of the session. We found participants exhibited stronger adaptation effects in response to cardinal adaptors compared to obliques. However, overall adaptation effects were weaker than those observed under typical tilt-aftereffect paradigms. Further, within a single session, adaptation effects developed inconsistently. The current findings therefore demonstrate a resistance to adaptation in response to naturalistic viewing conditions, suggesting barriers to understanding perceptual adaptation as experienced in nature.
Scalable information extraction from free text electronic health records using large language models
Authors: Gu Bowen , Shao Vivian , Liao Ziqian , Carducci Valentina , Brufau Santiago Romero , Yang Jie , Desai Rishi J 
Published: August 2024

ABSTRACTBackgroundA vast amount of potentially useful information such as description of patient symptoms, family, and social history is recorded as free-text notes in electronic health records (EHRs) but is difficult to reliably extract at scale, limiting their utility in research. This study aims to assess whether an “out of the box” implementation of open-source large language models (LLMs) without any fine-tuning can accurately extract social determinants of health (SDoH) data from free-text clinical notes.MethodsWe conducted a cross-sectional study using EHR data from the Mass General Brigham (MGB) system, analyzing free-text notes for SDoH information. We selected a random sample of 200 patients and manually labeled nine SDoH aspects. Eight advanced open-source LLMs were evaluated against a baseline pattern-matching model. Two human reviewers provided the manual labels, achieving 93% inter-annotator agreement. LLM performance was assessed using accuracy metrics for overall, mentioned, and non-mentioned SDoH, and macro F1 scores.ResultsLLMs outperformed the baseline pattern-matching approach, particularly for explicitly mentioned SDoH, achieving up to 40% higher Accuracymentioned. openchat_3.5 was the best-performing model, surpassing the baseline in overall accuracy across all nine SDoH aspects. The refined pipeline with prompt engineering reduced hallucinations and improved accuracy.ConclusionsOpen-source LLMs are effective and scalable tools for extracting SDoH from unstructured EHRs, surpassing traditional pattern-matching methods. Further refinement and domain-specific training could enhance their utility in clinical research and predictive analytics, improving healthcare outcomes and addressing health disparities.
Hierarchical Bayesian Augmented Hebbian Reweighting Model of Perceptual Learning
Authors: Lu Zhong-Lin , Yang Shanglin , Dosher Barbara 
Published: August 2024

AbstractThe Augmented Hebbian Reweighting Model (AHRM) has been effectively utilized to model the collective performance of observers in various perceptual learning studies. In this work, we have introduced a novel hierarchical Bayesian Augmented Hebbian Reweighting Model (HB-AHRM) to simultaneously model the learning curves of individual participants and the entire population within a single framework. We have compared its performance to that of a Bayesian Inference Procedure (BIP), which independently estimates the posterior distributions of model parameters for each individual subject without employing a hierarchical structure. To cope with the substantial computational demands, we developed an approach to approximate the likelihood function in the AHRM with feature engineering and linear regression, increasing the speed of the estimation procedure by 20,000 times. The HB-AHRM has enabled us to compute the joint posterior distribution of hyperparameters and parameters at the population, observer, and test levels, facilitating statistical inferences across these levels. While we have developed this methodology within the context of a single experiment, the HB-AHRM and the associated modeling techniques can be readily applied to analyze data from various perceptual learning experiments and provide predictions of human performance at both the population and individual levels. The likelihood approximation concept introduced in this study may have broader utility in fitting other stochastic models lacking analytic forms.
Caution when using network partners for target identification in drug discovery
Authors: Tan Dandan , Chen Yiheng , Ilboudo Yann , Liang Kevin Y. H. , Butler-Laporte Guillaume , Richards J Brent 
Published: August 2024

AbstractIdentifying novel, high-yield drug targets is challenging and often results in a high failure rate. However, recent data indicates that leveraging human genetic evidence to identify and validate these targets significantly increases the likelihood of success in drug development. Two recent papers from Open Targets claimed that around half of FDA-approved drugs had targets with direct human genetic evidence. By expanding target identification to include protein network partners—molecules in physical contact—the proportion of drug targets with genetic evidence support increased to two-thirds. However, the efficacy of using these network partners for target identification was not formally tested. To address this, we tested the approach on a list of robust positive control genes. We used the IntAct database to find molecular interacting proteins of genes identified by exome-wide association studies (ExWAS) and genome-wide association studies (GWAS) combined with a locus-to-gene mapping algorithm called the Effector Index (Ei). We assessed how accurately including interacting genes with the ExWAS and Effector Index selected genes identified positive controls, focusing on precision, sensitivity, and specificity. Our results indicated that although molecular interactions led to higher sensitivity in identifying positive control genes, their practical application is limited by low precision. Hence, expanding genetically identified targets to include network partners did not increase the chance of identifying drug targets, suggesting that such results should be interpreted with caution.
Beyond Differential Expression: Embracing Cell-to-Cell Variability in Single-Cell Gene Expression Data Analysis
Authors: Gatlin Victoria , Gupta Shreyan , Romero Selim , Chapkin Robert S. , Cai James J. 
Published: August 2024

AbstractSingle-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular variability by capturing gene expression profiles of individual cells. The importance of cell-to-cell variability in determining and shaping cell function has been widely appreciated. Nevertheless, differential expression (DE) analysis remains a cornerstone method in analytic practice, by focusing exclusively on mean expressional differences, current computational analyses overlook the rich information encoded by variability within the single-cell gene expression data. Thus, there is a need for more relevant approaches to assess data variability rather than the mean in order to offer a deeper understanding of cellular systems. Here we present spline-DV, a novel statistical framework for differential variability (DV) analysis using scRNA-seq data. The spline-DV method identifies genes exhibiting significantly increased or decreased expression variability among cells derived from two experimental conditions. Case studies show that DV genes identified using spline-DV are representative, and functionally relevant in the tested cellular conditions including obesity, fibrosis, and cancer.
Footprints of human migration in the population structure of wild wine yeast
Authors: Peña Jacqueline J. , Scopel Eduardo FC , Ward Audrey K. , Bensasson Douda 
Published: August 2024

ABSTRACTHumans have a long history of fermenting food and beverages that led to domestication of the wine yeast,Saccharomyces cerevisiae.Despite their tight companionship with humans, yeast species that are domesticated or pathogenic can also live on trees. Here we used over 300 genomes ofS. cerevisiaefrom oaks and other trees to determine whether tree-associated populations are genetically distinct from domesticated lineages and estimate the timing of forest lineage divergence. We found populations on trees are highly structured within Europe, Japan, and North America. Approximate estimates of when forest lineages diverged out of Asia and into North America and Europe coincide with the end of the last ice age, the spread of agriculture, and the onset of fermentation by humans. It appears that migration from human-associated environments to trees is ongoing. Indeed, patterns of ancestry in the genomes of three recent migrants from the trees of North America to Europe could be explained by the human response to the Great French Wine Blight. Our results suggest that human-assisted migration affects forest populations, albeit rarely. Such migration events may even have shaped the global distribution ofS. cerevisiae. Given the potential for lasting impacts due to yeast migration between human and natural environments, it seems important to understand the evolution of human commensals and pathogens in wild niches.
Cell-Type-Specific Regulation of TOR-Mediated Microtubule Acetylation Predicts Yki Loss-Induced Squamous Cell Carcinoma inDrosophila
Authors: Bhattacharya Rachita , Agarwal Shruti , Zafar Hamim , Sinha Pradip , Mohan Nitin 
Published: August 2024

ABSTRACTFlattened squamous epithelial tissues undergo extensive cytoskeletal remodeling and display perpetual nuclear signaling of the Hippo transcription cofactor, YAP/TAZ, in mammals and Yki inDrosophila. Loss of YAP in humans or Yki inDrosophilacauses squamous cell carcinoma (SCC), but only in select cell types. Here, we reveal a mechanism of Yki-loss induced SCC in the lumen-lining squamous epithelium of the male accessory gland (MAG) inDrosophila. Yki loss in the MAG triggers TOR signaling-mediated microtubule hyperacetylation, which causally underpins its SCC. By contrast, Yki loss in the oocyte-enveloping follicular squamous epithelium neither activates TOR nor induce microtubule hyperacetylation. Analysis of available single-cell transcriptomic data further revealed characteristic MAG and follicular squamous cell type-specific signatures of Yki and TOR signaling. Thus, the disparate epigenetic landscapes and distinct mechanosensory cues likely prefigures their susceptibility to Yki-loss, with lumen-lining squamous epithelia being oncogenically more susceptible.
Drosophila ring chromosomes interact with sisters and homologs to produce anaphase bridges in mitosis
Authors: Lin Ho-Chen , Golic Mary M. , Hill Hunter J. , Lemons Katherine F. , Vuong Truc T. , Smith Madison , Golic Forrest , Golic Kent G. 
Published: August 2024

AbstractRing chromosomes are known in many eukaryotic organisms, including humans. They are typically associated with a variety of maladies, including abnormal development and lethality. Underlying these phenotypes are anaphase chromatin bridges that can lead to chromosome loss, nondisjunction and breakage. By cytological examination of ring chromosomes inDrosophila melanogasterwe identified five causes for anaphase bridges produced by ring chromosomes. Catenation of sister chromatids is the most common cause and these bridges frequently resolve during anaphase, presumably by the action of topoisomerase II. Sister chromatid exchange and chromosome breakage followed by sister chromatid union also produce anaphase bridges. Mitotic recombination with the homolog was rare, but was another route to generation of anaphase bridges. Most surprising, was the discovery of homolog capture, where the ring chromosome was connected to its linear homolog in anaphase. We hypothesize that this is a remnant of mitotic pairing and that the linear chromosome is connected to the ring by multiple wraps produced through the action of topoisomerase II during establishment of homolog pairing. In support, we showed that in a ring/ring homozygote the two rings are frequently catenated in mitotic metaphase, a configuration that requires breaking and rejoining of at least one chromosome.
Bayesian estimation yields anti-Weber variability
Authors: Prat-Carrabin Arthur , Gershman Samuel J. 
Published: August 2024

AbstractA classic result of psychophysics is that human perceptual estimates are more variable for larger magnitudes. This ‘Weber behavior’ has typically not been the focus of the prominent Bayesian paradigm, which models human perception as an optimal statistical inference conducted on the basis of noisy internal signals. Here we examine the variability of the estimates of a Bayesian observer, in comparison with human subjects. In two preregistered experiments, we manipulate the prior distribution and the reward function in a numerosity-estimation task. When the large numerosities are more frequent, and when they are more rewarding, the Bayesian observer exhibits an ‘anti-Weber behavior’, in which larger magnitudes results in less variable responses. Human subjects exhibit a similar pattern, thus breaking a long-standing result of psychophysics by showing the opposite behavior. This allows subjects to minimize the errors they make about the more frequent or the more rewarding magnitudes. Nevertheless, model fitting suggests that subjects’ responses are best captured by a model that features a logarithmic encoding, a proposal of Fechner often regarded as accounting for Weber behavior. We thus obtain an anti-Weber behavior together with a Fechner encoding. Our results suggest that the increasing variability may be primarily due to the skewness of natural priors.
Dynamic Wt1 expression in the gastrulation-stage mouse embryo specifies vascular and visceral smooth muscle cell fate independently from mesothelial fate
Authors: Alsukari Suad H. , Ng Huei Teng , Lang Lilly , Lunn Sharna , Beglinger Shanthi , Carr Lauren , Boyes Michael , Turner David A. , Wilm Bettina 
Published: August 2024

AbstractThe Wilms’ Tumour protein (Wt1) had previously been shown to specify both the mesothelial lineage and vascular smooth muscle cell (vSMC) lineage in the mouse intestine, with evidence suggesting that intestinal vSMCs arise from the mesothelium. Here, we dissect the temporal relationship between these two mesodermal lineages, reporting that unexpectedly, Wt1 expression already in gastrulation stage embryos specifies a population of SMC precursor cells in the lateral plate mesoderm (LPM). Tamoxifen-induced genetic lineage tracing of Wt1-expressing cells revealed that vSMC and visceral smooth muscle cells (visSMCs) of the foetal mid-gut are labelled when Tamoxifen was administered at E7.5 or E8.5. By contrast, intestinal mesothelial cells were labelled after Tamoxifen dosing from E9.5 and later. Analysis of scRNAseq data of gastrulation stage mouse embryos and confocal microscopy demonstrated for the first time Wt1 expression in epiblast and primitive streak, emerging mesoderm and, from E7.5 onwards, in the LPM. In E8.5 mouse embryos, the co-expression of key smooth muscle fate markersTagln,Acta2,MrtfA/BandPdgfrbinWt1-expressing cells revealed that vSMC and visSMC fate is specified independently from visceral mesothelium formation. Together, our study provides insight into the developmental lineage of smooth muscle specified by Wt1 expression at gastrulation stages.
Delta opioid receptors engage multiple signaling cascades to differentially modulate prefrontal GABA release with input and target specificity
Authors: Alexander Ryan P. D. , Bender Kevin J. 
Published: August 2024

ABSTRACTOpioids regulate circuits associated with motivation and reward across the brain. Of the opioid receptor types, delta opioid receptors (DORs) appear to have a unique role in regulating the activity of circuits related to reward without a liability for abuse. In neocortex, DORs are expressed primarily in interneurons, including parvalbumin- and somatostatin-expressing interneurons that inhibit somatic and dendritic compartments of excitatory pyramidal cells, respectively. But how DORs regulate transmission from these key interneuron classes is unclear. We found that DORs regulate inhibition from these interneuron classes using different G-protein signaling pathways that both converge on presynaptic calcium channels, but regulate distinct aspects of calcium channel function. This imposes different temporal filtering effects, via short-term plasticity, that depend on how calcium channels are regulated. Thus, DORs engage differential signaling cascades to regulate inhibition depending on the postsynaptic target compartment, with different effects on synaptic information transfer in somatic and dendritic domains.
Identifying patterns differing between high-dimensional datasets with generalized contrastive PCA
Authors: de Oliveira Eliezyer Fermino , Garg Pranjal , Hjerling-Leffler Jens , Batista-Brito Renata , Sjulson Lucas 
Published: August 2024

AbstractHigh-dimensional data have become ubiquitous in the biological sciences, and it is often desirable to compare two datasets collected under different experimental conditions to extract low-dimensional patterns enriched in one condition. However, traditional dimensionality reduction techniques cannot accomplish this because they operate on only one dataset. Contrastive principal component analysis (cPCA) has been proposed to address this problem, but it has seen little adoption because it requires tuning a hyperparameter resulting in multiple solutions, with no way of knowing which is correct. Moreover, cPCA uses foreground and background conditions that are treated differently, making it ill-suited to compare two experimental conditions symmetrically. Here we describe the development of generalized contrastive PCA (gcPCA), a flexible hyperparameter-free approach that solves these problems. We first provide analyses explaining why cPCA requires a hyperparameter and how gcPCA avoids this requirement. We then describe an open-source gcPCA toolbox containing Python and MATLAB implementations of several variants of gcPCA tailored for different scenarios. Finally, we demonstrate the utility of gcPCA in analyzing diverse high-dimensional biological data, revealing unsupervised detection of hippocampal replay in neurophysiological recordings and heterogeneity of type II diabetes in single-cell RNA sequencing data. As a fast, robust, and easy-to-use comparison method, gcPCA provides a valuable resource facilitating the analysis of diverse high-dimensional datasets to gain new insights into complex biological phenomena.
Aspergillusspecies in Iceland: species distribution andcyp51Amutation testing in a 7.5-year clinical isolate collection
Authors: Hilmarsdottir Ingibjorg , Alcanzo Ervin Martien , Gerrits van den Ende Bert , Houbraken Jos , Hagen Ferry 
Published: August 2024

AbstractIntroduction.Among challenges in diagnosing and treating aspergillosis areAspergillusspecies identification, which can inform therapeutic choices, and detection of antifungal resistance. Increasing rates of triazole resistance have been reported for the most common species,Aspergillus fumigatus.Methods.A collection of clinicalAspergillusisolates cultured during 2014–2021, previously identified morphologically, were tested with the AsperGenius qPCR-kit for identification ofA. fumigatusandAspergillus flavusand the presence of acyp51Amutation encoding azole resistance (TR34/L98H and Y121F/T289A); other species were identified with calmodulin sequencing.Results.Identification of the 312 isolates (224 patients) tested revealed 19 species in nineAspergillussections. Rare or cryptic species were identified in 48 isolates (44 patients). Thirty-one isolates had been assigned an incorrect species name when initially cultured. The TR34/L98H and Y121F/T289A mutations were not found in any of the 202A. fumigatusisolates tested.Discussion.In this first study on clinicalAspergillusisolates in Iceland the proportion of cryptic and rare species was on par with findings from other countries. In contrast, unlike other studies we did not find the most common azole resistance-related mutations inA. fumigatus, possibly due to the absence of significant environmental antifungal pressure in the local agriculture.