bluuebunny/crossref_metadata_2025_split huggingface dataset:
A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records
Authors: Shuey Megan M. , Lee Kyung Min , Keaton Jacob , Khankari Nikhil K. , Breeyear Joseph H. , Walker Venexia M. , Miller Donald R. , Heberer Kent R. , Reaven Peter D. , Clarke Shoa L. , Lee Jennifer , Lynch Julie A. , Vujkovic Marijana , Edwards Todd L. 
Published: December 2022

AbstractObjectivesThe identification of novel uses for existing drug therapies has the potential to provide a rapid, low-cost approach to drug (re)discovery. In the current study we developed and tested a genetically-informed drug-repurposing pipeline for diabetes management.DesignWe developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR).SettingThe SCCS experiments were completed using two EHRs: the Million Veterans Program (USA) as the discovery and the Vanderbilt University Medical Center (Tennessee, USA) as the replication.ResultsAfter filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p=0.01 and -0.85 mg/dL, p=0.02, respectively; MR: OR=0.84, 95% CI=0.81, 0.87, p=5.0×10-25).ConclusionsOur results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions.Summary BoxesSection 1: What is already known on this topicMedications with genetic support are significantly more likely to make it through clinical trials.Section 2: What this study addsOur results identified two anti-hypertensive medication classes, calcium channel blockers and angiotensin-converting enzyme inhibitors, as genetically supported drug-repurposing targets that demonstrated glycemic measurement reduction in real-world clinical populations. These results suggest patients with diabetes or pre-diabetes could benefit from preferential use of these medication classes when they present with comorbid hypertension or other cardiovascular conditions. Finally, this study demonstrates a successful implementation of a novel genetically-supported drug-repurposing pipeline for diabetes treatment that can be readily adapted and applied to other diseases and as such it has the potential to identify/prioritize drug repurposing targets for these other conditions.
Structural Variants in Linkage Disequilibrium with GWAS-Significant SNPs
Authors: Liang Hao , Sedillo Joni , Schrodi Steven J. , Ikeda Akihiro 
Published: December 2022

AbstractSummaryWith the recent expansion of structural variant identification in the human genome, understanding the role of these impactful variants in disease architecture is critically important. Currently, a large proportion of genome-wide-significant GWAS SNPs are functionally unresolved, raising the possibility that some of these SNPs are associated with disease through linkage disequilibrium with causal structural variants. Hence, understanding the linkage disequilibrium between newly discovered structural variants and statistically significant SNPs may provide a resource for further investigation into disease-associated regions in the genome. Here we present a resource cataloging structural variant-significant SNP pairs in high linkage disequilibrium.AvailabilityAll data files including those detailing SV and GWAS SNP associations and results of GWAS-SNP-SV pairs are available athttps://github.com/hliang-SchrodiLab/SV_SNPs.
Eye structure shapes neuron function inDrosophilamotion vision
Authors: Zhao Arthur , Gruntman Eyal , Nern Aljoscha , Iyer Nirmala A. , Rogers Edward M. , Koskela Sanna , Siwanowicz Igor , Dreher Marisa , Flynn Miriam A. , Laughland Connor W. , Ludwig Henrique D.F. , Thomson Alex G. , Moran Cullen P. , Gezahegn Bruck , Bock Davi D. , Reiser Michael B. 
Published: December 2022

SummaryMany animals rely on vision to navigate through their environment. The pattern of changes in the visual scene induced by self-motion is theoptic flow1, which is first estimated in local patches by directionally selective (DS) neurons2–4. But how should the arrays of DS neurons, each responsive to motion in a preferred direction at a specific retinal position, be organized to support robust decoding of optic flow by downstream circuits? Understanding this global organization is challenging because it requires mapping fine, local features of neurons across the animal’s field of view3. InDrosophila, the asymmetric dendrites of the T4 and T5 DS neurons establish their preferred direction, making it possible to predict DS responses from anatomy4,5. Here we report that the preferred directions of fly DS neurons vary at different retinal positions and show that this spatial variation is established by the anatomy of the compound eye. To estimate the preferred directions across the visual field, we reconstructed hundreds of T4 neurons in a full brain EM volume6and discovered unexpectedly stereotypical dendritic arborizations that are independent of location. We then used whole-head μCT scans to map the viewing directions of all compound eye facets and found a non-uniform sampling of visual space that explains the spatial variation in preferred directions. Our findings show that the organization of preferred directions in the fly is largely determined by the compound eye, exposing an intimate and unexpected connection between the peripheral structure of the eye, functional properties of neurons deep in the brain, and the control of body movements.
Prediction of white matter hyperintensities evolution one-year post-stroke from a single-point brain MRI and stroke lesions information
Authors: Rachmadi Muhammad Febrian , Valdés-Hernández Maria del C. , Makin Stephen , Wardlaw Joanna , Skibbe Henrik 
Published: December 2022

ABSTRACTPredicting the evolution of white matter hyperintensities (WMH), a common feature in brain magnetic resonance imaging (MRI) scans of older adults (i.e., whether WMH will grow, remain stable, or shrink with time) is important for personalised therapeutic interventions. However, this task is difficult mainly due to the myriad of vascular risk factors and comorbidities that influence it, and the low specificity and sensitivity of the image intensities and textures alone for predicting WMH evolution. Given the predominantly vascular nature of WMH, in this study, we evaluate the impact of incorporating stroke lesion information to a probabilistic deep learning model to predict the evolution of WMH 1-year after the baseline image acquisition, taken soon after a mild stroke event, using T2-FLAIR brain MRI. The Probabilistic U-Net was chosen for this study due to its capability of simulating and quantifying the uncertainties involved in the prediction of WMH evolution. We propose to use an additional loss called volume loss to train our model, and incorporate stroke lesions information, an influential factor in WMH evolution. Our experiments showed that jointly segmenting the disease evolution map (DEM) of WMH and stroke lesions, improved the accuracy of the DEM representing WMH evolution. The combination of introducing the volume loss and joint segmentation of DEM of WMH and stroke lesions outperformed other model configurations with mean volumetric absolute error of 0.0092ml(down from 1.7739ml) and 0.47% improvement on average Dice similarity coefficient in shrinking, growing and stable WMH.
DNA metabarcoding reveals the dietary profiles of a benthic marine crustacean,Nephrops norvegicus
Authors: Shum Peter , Wäge-Recchioni Janine , Sellers Graham S , Johnson Magnus L , Joyce Domino A. 
Published: December 2022

AbstractNorwegian lobster,Nephrops norvegicus, are a generalist scavenger and predator capable of short foraging excursions but can also suspension feed. Existing knowledge about their diet relies on a combination of methods including morphology-based stomach content analysis and stable isotopes, which often lack the resolution to distinguish prey items to species level particularly in species that thoroughly masticate their prey. DNA metabarcoding overcomes many of the challenges associated with traditional methods and it is an attractive approach to study the dietary profiles of animals. Here, we present the diet of the commercially valuableNephrops norvegicususing DNA metabarcoding of gut contents. Despite difficulties associated with host amplification, our cytochrome oxidase I (COI) molecular assay successfully achieves higher resolution information than traditional approaches. We detected taxa that were likely consumed during different feeding strategies. Dinoflagellata, Chlorophyta and Bacillariophyta accounted for almost 50% of the prey items consumed, and are associated with suspension feeding, while fish with high fisheries discard rates were detected which are linked to active foraging. In addition, we were able to characterise biodiversity patterns by consideringNephropsas natural samplers, as well as detecting parasitic dinoflagellates (e.g.,Hematodiniumsp.), which are known to influence burrow related behaviour in infected individuals in over 50% of the samples. The metabarcoding data presented here greatly enhances a better understanding of a species’ ecological role and could be applied as a routine procedure in future studies for proper consideration in the management and decision-making of fisheries.
A Noninvasive Skin Biopsy of Free Nerve Endings via Realtime Third-Harmonic Microscopy
Authors: Wu Pei-Jhe , Tseng Hsiao-Chieh , Chao Chi-Chao , Liao Yi-Hua , Yen Chen-Tung , Lin Wen-Ying , Hsieh Sung-Tsang , Sun Wei-Zen , Sun Chi-Kuang 
Published: December 2022

AbstractSkin biopsy was the only method to provide free-intraepidermal-nerve-endings (FINEs) structural information for the differential diagnosis of small fiber neuropathy (SFN). Its invasive nature was particularly unfavorable for patients with diabetic coagulation abnormalities thus there is an unmet clinical need for a non-invasive FINEs imaging tool. Here we show a tightly-focused epi-Third-harmonic-generation microscope (TFETM) for unmyelinated FINEs imaging. Its label-free capability was confirmed by PGP9.5 immunohistochemistry staining and a longitudinal spared nerve injury model study. Moreover, through proposing a dot-connecting algorithm, we established the operational protocol to count three-dimensionally the intraepidermal nerve fibers (IENF) and define the quantitative IENF index. Our clinical trial showed that the label-free IENF index can differentially identify SFN (P-value=0.0102) and was well correlated with IENF density of skin biopsy (Pearson’s correlation, R-value= 0.98) in the DPN group. Our study suggested that the unstained dot-connecting third-harmonic microscopy imaging can noninvasively provide FINEs structure information assisting diagnosing SFN.
Kestrels of the same colony do not overwinter together
Authors: García-Macía Jorge , Chaouni Munir , Morollón Sara , Bustamante Javier , López-Ricaurte Lina , Martínez-Dalmau Juan , Rodríguez-Moreno Beatriz , Urios Vicente 
Published: December 2022

ABSTRACTColoniality is one of the most common strategies in birds. While the lesser kestrel (Falco naumanni) is a colonial raptor during the breeding period, it is not known whether individuals from the same breeding colony aggregate during the non-breeding period too. We GPS-tracked 40 adult lesser kestrels from different Spanish breeding colonies to study the degree of spatial aggregation between individuals from the same breeding colony in their West African non-breeding range. Lesser kestrels in our study used a large area from a wide longitudinal strip in the western Sahel: individuals used 143,697 ± 98,048 km2on average during the entire non-breeding period (95% KDE), and 1,359 ± 1,424 km2per week. On the other hand, the individuals traveled 6205 ± 2407 km on average during the entire non-breeding period, and 41.1 ± 11.8 km per day. There were no differences between the sexes in any of those variables. Individuals from the same breeding colony were not aggregated during the non-breeding period because the overlap between their areas (38.8 ± 21.4 %) was not higher than that randomly expected. In conclusion, our study reveals some aspects of the non-breeding spatial ecology of the lesser kestrel, allowing a better understanding of the relationship of colonial birds out of the breeding season.
Trapalyzer: A computer program for quantitative analyses in fluorescent live-imaging studies of Neutrophil Extracellular Trap formation
Authors: Ciach Michał Aleksander , Bokota Grzegorz , Manda-Handzlik Aneta , Kuźmicka Weronika , Demkow Urszula , Gambin Anna 
Published: December 2022

AbstractNeutrophil extracellular traps (NETs), pathogen-ensnaring structures formed by neutrophils by expelling their DNA into the environment, are believed to play an important role in immunity and autoimmune diseases. In recent years, a growing attention has been put into developing software tools to quantify NETs in fluorescent microscopy images. However, current solutions require extensive training data sets, are difficult to use for users without background in computer science, or have limited capabilities.In this work we present Trapalyzer, a computer program for an automatic quantification of NETs in terms of their area and an approximation of their number. In addition, Trapalyzer counts neutrophils at different stages of NET formation, and is the first tool that makes this possible without extensive training data sets. We validate our approach on a publicly available benchmark data set and apply it in a neutrophil-bacteria co-culture experiment. The software and usage tutorials are available athttps://github.com/Czaki/Trapalyzer.
Autofluorescence is a biomarker of neural stem cell activation state
Authors: Morrow Christopher S. , Tweed Kelsey , Arndt Zachary P. , Walsh Alex J. , Peng Bo , Risgaard Ryan D. , Klosa Payton C. , Chi Michelle M. , Wallace Eli P. , Jones Mathew V. , Roopra Avtar , Skala Melissa C. , Moore Darcie L. 
Published: December 2022

AbstractNeural stem cells (NSCs) in the adult brain are primarily quiescent but can activate and enter the cell cycle to produce newborn neurons. NSC quiescence can be regulated by disease, injury, and age, however our understanding of NSC quiescence is limited by technical limitations imposed by the bias of markers used to isolate each population of NSCs and the lack of live-cell labeling strategies. Fluorescence lifetime imaging (FLIM) of autofluorescent metabolic cofactors has previously been used in other cell types to study shifts in cell states driven by metabolic remodeling that change the optical properties of these endogenous fluorophores. Here we asked whether autofluorescence could be used to discriminate NSC activation state. We found that quiescent NSCs (qNSCs) and activated NSCs (aNSCs) each have unique autofluorescence intensity and fluorescence lifetime profiles. Additionally, qNSCs specifically display an enrichment of a specific autofluorescent signal localizing to lysosomes that is highly predictive of cell state. These signals can be used as a graded marker of NSC quiescence to predict cell behavior and track the dynamics of quiescence exit at single cell resolutionin vitroandin vivo. Through coupling autofluorescence imaging with single-cell RNA sequencingin vitroandin vivo, we provide a high-resolution resource revealing transcriptional features linked to rapid NSC activation and deep quiescence. Taken together, we describe a single-cell resolution, non-destructive, live-cell, label-free strategy for measuring NSC activation statein vitroandin vivoand use this tool to expand our understanding of adult neurogenesis.
Deep learning-based image-analysis identifies a DAT-negative subpopulation of dopaminergic neurons in the lateral Substantia nigra
Authors: Burkert Nicole , Roy Shoumik , Häusler Max , Wuttke Dominik , Müller Sonja , Wiemer Johanna , Hollmann Helene , Oldrati Marvin , Ramirez-Franco Jorge , Benkert Julia , Fauler Michael , Duda Johanna , Goaillard Jean-Marc , Pötschke Christina , Münchmeyer Moritz , Parlato Rosanna , Liss Birgit 
Published: December 2022

AbstractHere we present a deep learning-based image analysis platform (DLAP), tailored to autonomously quantify cell numbers, and fluorescence signals within cellular compartments, derived from RNAscope or immunohistochemistry. We utilized DLAP to analyse subtypes of tyrosine hydroxylase (TH)-positive dopaminergic midbrain neurons in mouse and human brain sections. These neurons modulate complex behaviour, and are differentially affected in Parkinson’s and other diseases. DLAP allows the analysis of large cell numbers, and facilitates the identification of small cellular subpopulations. Specifically, we identified a small subpopulation of TH-positive neurons (∼5%), mainly located in the very lateral Substantia nigra (SN), that was immunofluorescence-negative for the plasmalemma dopamine transporter (DAT), with ∼40% smaller cell bodies. These neurons were negative for aldehyde dehydrogenase 1A1, with a lower co-expression rate for dopamine-D2-autoreceptors, but a ∼7-fold higher likelihood of calbindin-d28k co-expression (∼70%). Our results have important implications, as DAT is crucial for dopamine-signalling, and is commonly used as a marker for dopaminergic SN neurons.
Amphetamine disrupts dopamine axon growth in adolescence by a sex-specific mechanism
Authors: Reynolds Lauren M. , Hernandez Giovanni , Popescu Christina , MacGowan Del , Nouel Dominique , Cuesta Santiago , Burke Samuel , Savell Katherine E. , Zhao Janet , Restrepo-Lozano Jose Maria , Pokinko Matthew , Giroux Michel , Israel Sonia , Orsini Taylor , He Susan , Wodzinski Michael , Epelbaum Julia G. , Trudeau Louis-Éric , Kolb Bryan , Day Jeremy J. , Flores Cecilia 
Published: December 2022

AbstractInitiating drug use during adolescence increases the risk of developing addiction and psychiatric disorders later in life, with long-term outcomes varying according to sex and exact timing of use. Even though most individuals begin experimenting with drugs of abuse in adolescence, to date, the cellular and molecular underpinnings explaining differential sensitivity to detrimental drug effects remain unknown. The Netrin-1/DCC guidance cue system plays a critical role in the adolescent development of mesocorticolimbic dopamine circuitry, segregating the cortical and limbic pathways. Adolescent experiences, including exposure to drugs of abuse, can regulateDccexpression in male mice, placing Netrin-1/DCC signaling as a potential molecular link between experience and enduring changes to circuitry and behavior. Here we show that exposure to a recreational-like regimen of amphetamine (AMPH) in adolescence induces sex- and age-specific alterations inDccexpression in the ventral tegmental area. Female mice are protected against the deleterious long-term effects of AMPH-inducedDccregulation by compensatory changes in the expression of its binding partner, Netrin-1. AMPH induces targeting errors in mesolimbic dopamine axons and triggers their ectopic growth to the prefrontal cortex, only in early-adolescent male mice, underlying a male-specific vulnerability to its enduring cognitive effects. Upregulating DCC receptor expression in dopamine neurons in adolescent males using a neuron-optimized CRISPR/dCas9 Activation System induces female-like protection against the persistent effects of AMPH in early adolescence on inhibitory control. Netrin-1/DCC signaling is therefore a molecular switch which can be differentially regulated in response to the same experience as function of age and sex of the individual, leading to divergent long-term outcomes associated with vulnerable or resilient phenotypes.
Crowdsourcing Temporal Transcriptomic Coronavirus Host Infection Data: resources, guide, and novel insights
Authors: Flynn James , Ahmadi Mehdi M. , McFarland Chase T. , Kubal Michael D. , Taylor Mark A. , Cheng Zhang , Torchia Enrique C. , Edwards Michael G. 
Published: December 2022

AbstractThe emergence of SARS-CoV-2 reawakened the need to rapidly understand the molecular etiologies, pandemic potential, and prospective treatments of infectious agents. The lack of existing data on SARS-CoV-2 hampered early attempts to treat severe forms of COVID-19 during the pandemic. This study coupled existing transcriptomic data from SARS-CoV-1 lung infection animal studies with crowdsourcing statistical approaches to derive temporal meta-signatures of host responses during early viral accumulation and subsequent clearance stages. Unsupervised and supervised machine learning approaches identified top dysregulated genes and potential biomarkers (e.g., CXCL10, BEX2, and ADM). Temporal meta-signatures revealed distinct gene expression programs with biological implications to a series of host responses underlying sustained Cxcl10 expression and Stat signaling. Cell cycle switched from G1/G0 phase genes, early in infection, to a G2/M gene signature during late infection that correlated with the enrichment of DNA Damage Response and Repair genes. The SARS-CoV-1 meta-signatures were shown to closely emulate human SARS-CoV-2 host responses from emerging RNAseq, single cell and proteomics data with early monocyte-macrophage activation followed by lymphocyte proliferation. The circulatory hormone adrenomedullin was observed as maximally elevated in elderly patients that died from COVID-19. Stage-specific correlations to compounds with potential to treat COVID-19 and future coronavirus infections were in part validated by a subset of twenty-four that are in clinical trials to treat COVID-19. This study represents a roadmap to leverage existing data in the public domain to derive novel molecular and biological insights and potential treatments to emerging human pathogens. The data from this study is available in an interactive portal (http://18.222.95.219:8047).