bluuebunny/crossref_metadata_2025_split huggingface dataset:
The genetic basis of dermatophytosis skin infection susceptibility
Authors: Haapaniemi Hele , Eghtedarian Reyhane , Tervi Anniina ,   Estonian Biobank Research Team,   FinnGen, Abner Erik , Ollila Hanna M. 
Published: November 2024

AbstractDermatophytosis is an infection caused by fungi that utilize keratinized tissues, such as skin, nails, and hair, as their energy source. This infection commonly presents as red, itchy and ring-like patches on the skin, nail thickening, or hair loss. With ever-increasing case numbers, it has become a significant public health concern estimated to affect 20 % of the world’s population. Despite the high prevalence, the genetic risk factors for dermatophytosis are poorly understood. Our goal was to elucidate the biological mechanisms underlying individual susceptibility to dermatophytosis and to explore its genetic associations with other diseases and traits. We performed a large-scale genome-wide association meta-analysis of dermatophytosis infections with over 250,000 cases and 1,370,000 controls using data from FinnGen, Estonian Biobank, UK Biobank and Million Veterans Program. We identified 30 genome-wide significant loci including seven missense variants and two variants in high linkage disequilibrium with missense variants. The strongest associations were with variants within or closest toZNF646(p = 6.60×10−79, beta = 0.07),HLA-DQB1(p = 1.42×10−36, beta = 0.05),FLG(p = 1.96×10−27, beta = −0.22),FTO(p = 5.75×10−26, beta = −0.04),SLURP2(p = 3.33×10−24, beta = 0.04) andKRT77(p = 1.28×10−15, beta = 0.03) genes. Overall, our findings implicate keratin lifecycle and skin integrity, immune defense, and obesity as risk factors for dermatophytosis. Our findings highlight the clinical comorbidities with other skin diseases and with high BMI and identify novel genetic variants some of which are novel candidates for managing dermatophytosis infection.
Reduced brain structural similarity is associated with maturation, neurobiological features, and clinical status in schizophrenia
Authors: García-San-Martín Natalia , Bethlehem Richard AI , Mihalik Agoston , Seidlitz Jakob , Sebenius Isaac , Alemán-Morillo Claudio , Dorfschmidt Lena , Shafiei Golia , Morgan Sarah E. , Ruiz-Veguilla Miguel , Ayesa-Arriola Rosa , Vázquez-Bourgon Javier , Misic Bratislav , Suckling John , Crespo-Facorro Benedicto , Romero-García Rafael 
Published: November 2024

AbstractSchizophrenia spectrum disorders (SSD) are characterized by atypical brain maturation, including reduced structural similarity between regions. However, the maturational and neurobiological underpinnings of the complex interactions between abnormal development and network reorganization remain poorly characterized. Using structural MRI data from 195 healthy controls (HC) and 352 individuals with SSD, we constructed individual Morphometric INverse Divergence (MIND) networks. Compared to HC, individuals with SSD exhibited reduced structural similarity in the temporal and cingulate lobes, with more pronounced reductions in individuals exhibiting a ‘poor’ clinical status (more impaired cognitive functioning and more severe symptomatology). These alterations in MIND networks were associated with cortical hierarchy and maturational events, locating MIND reductions in higher-order association areas that predominantly mature later. Finally, we mapped 46 neurobiological features from healthy individuals onto MIND networks revealing a high presence of neurotransmitters, astrocytes, and microglia, along with decreased metabolism and microstructure, in regions with reduced similarity in SSD. Taken together, these findings provide evidence on the complex interplay between structural dysconnectivity, maturational events, and the underlying neurobiology in determining clinical status of individuals with SSD.
Variable selection for competing risk regression models: recommendations for analyzing data from epidemiological studies
Authors: Mullaert J. , Schmeller Sandra , Austin Peter C. , Latouche A. 
Published: November 2024

AbstractWhen fitting competing risks regression models, a variety of variable selection methods exist, including backward selection on the subdistribution hazard, on the cause-specific hazards, and penalized methods. However, a benchmark study comparing these different procedures is lacking.We conducted an extensive simulation study to compare three variable selection procedures in terms of both model selection ability and predictive accuracy. 5120 datasets were simulated in various conditions aiming at being representative of real applications in clinical epidemiology. Results show that the backward selection procedure can lead to high false discovery rate (FDR) because of implementation choices. Even for scenarios with a high numbers of events per variable (EPV), the true model is rarely identified by any of the tested procedures. Survival predictions were assessed with time-dependent AUC and show similar performances for all methods. We also provide an application on real data from stem cell transplanted patients in hematology.We conclude that the identification of the true model in competing risk regression is a very difficult task, and suggest some recommendations to analysts: (1) to report event per variable for the event type of interest and (2) to use multiple methods to deal with model uncertainty and avoid implementation pitfalls.
Analysis of 470,000 exome-sequenced UK Biobank participants identifies genes containing rare variants which confer dementia risk
Authors: Gibbons Lily , Curtis David 
Published: November 2024

AbstractBackgroundPrevious studies have reported that rare coding variants in a handful of genes have major effects on risk of Alzheimer’s disease (AD). A recent exome wide association study (ExWAS) of dementia in a subset of the UK Biobank cohort implicated a number of genes, including five which were novel. Here we report a similar analysis, carried out on the full cohort of 470,000 exome-sequenced participants.MethodsA score was assigned to each participant depending on individual and/or parental diagnosis of dementia. Regression analysis includingAPOEε3 and ε4 doses as covariates was applied to gene-wise tests for association with loss of function (LOF) and nonsynonymous variants. 45 tests using different pathogenicity predictors were applied to the first cohort of 200,000 participants. Subsequently the 100 genes showing strongest evidence for association were analysed in the second cohort of 270,000 participants, using only the best-performing predictor for each gene.ResultsThree genes achieved statistical significance,TREM2, SORL1andABCA7. The five genes reported as novel in the ExWAS did not produce any appreciable evidence for association in this study. The effects and frequencies of variants in different functional categories were characterised for these genes.ConclusionsRare coding variants in a small number of genes have important effects on dementia risk. Further study of individual variant effects might elucidate mechanisms of pathogenesis. Incorporating rare variant effects for individual risk assessment might become important if preventative treatments for dementia become available.
A 2-year longitudinal investigation of insula subregional volumes in early psychosis
Authors: Kittleson Andrew R. , McHugo Maureen , Liu Jinyuan , Vandekar Simon N. , Armstrong Kristan , Rogers Baxter , Woodward Neil D. , Heckers Stephan , Sheffield Julia M. 
Published: November 2024

AbstractBackgroundThe insula is a heterogeneous cortical region with three cytoarchitectural subregions— agranular, dysgranular, and granular—that have distinct functional roles. Previous cross- sectional studies have shown smaller volume of all insula subregions in individuals with psychotic disorders. However, longitudinal trajectories of insula subregions in early psychosis, and the relationship between subregional volumes and relevant clinical phenomena, such as perceptual aberrations, have not been previously examined.Methods66 early psychosis (EP) and 65 healthy comparison (HC) participants completed 2-4 study visits over 2 years. T1-weighted structural brain images were processed using longitudinal voxel- based morphometry in CAT12 and segmented into anatomic subregions. At baseline, participants completed the Perceptual Aberrations Scale (PAS) to capture bodily distortions. The EP group was further examined based on diagnostic trajectory over two years (stable schizophrenia, stable schizophreniform, and conversion from schizophreniform to schizophrenia).ResultsEP participants had smaller insula volumes in all subregions compared to HC participants, and these volumes were stable over two years. Compared to HC, insula volumes were significantly smaller in EP participants with a stable diagnosis of schizophrenia, but other diagnostic trajectory groups did not significantly differ from HC or the stable schizophrenia group. While perceptual aberrations were significantly elevated in EP participants, PAS scores were not significantly related to insula volume.ConclusionsWe find that all insula subregions are smaller in early psychosis and do not significantly decline over two years. These data suggest that all insula subregions are structurally impacted in schizophrenia-spectrum disorders and may be the result of abnormal neurodevelopment.
Association between handgrip strength, handgrip strength asymmetry, and anxiety in Korean older adults: The Korean National Health and Nutrition Examination Survey 2022
Authors: Choi Sang-Youn , Park Su-Min , Park Eun-Cheol 
Published: November 2024

AbstractLow handgrip strength (HGS) and HGS asymmetry are associated with age-related physical and mental disorders in older adults. This study aimed to examine the association between HGS-related factors and anxiety to evaluate whether HGS assessments can assist in identifying anxiety risk. In total, 1,750 participants from the Korea National Health and Nutrition Examination Survey of 2022 were included in this study. Individuals whose HGS values were below the 20th percentile of the study population stratified by sex were classified into the low-HGS group. Anxiety was assessed using the generalized anxiety disorder with a 7-item scale. Multiple logistic regression was used to analyze the relationship between HGS level and asymmetry and anxiety, adjusting for covariates. Overall, 70 (8.7%) men and 123 (13.0%) women had anxiety. Elevated odds of anxiety were observed in older women with low HGS (adjusted odds ratio: 2.17, 95% confidence interval: 1.31–3.61). There was a positive correlation between the degree of asymmetrical HGS and anxiety among women. This study found positive associations between low HGS, HGS asymmetry, and anxiety in older Korean women. This population may require specific interventions to help maintain good mental health.
Anxiolytic management in eating disorder patients receiving cognitive behavioral therapy: A quality improvement brief report
Authors: Smith Brad E.R. , Greenberg Katelyn A. , Vadapalli Sreya , Garrison Sheldon R. 
Published: November 2024

AbstractEating disorders (EDs) are serious lifelong and debilitating health conditions characterized by complex adverse eating behaviors resulting in weight loss and decreased quality of life. One evidence-based treatment is a form of cognitive-behavioral therapy (CBT) called exposure therapy where patients progress through a hierachy of exposures. This treatment approach results in concern related to CBT efficacy for patients concurrently treated with anxiolytic medications. These medications, which are being incorporated into treatment protocols, may impact the anxiety-provoking components of the exposure response, potentially limiting its efficacy. Therefore, patients were assessed in multiple ways to ensure that providers could prescribe anxiolytics without risk to diminishing the well-established response to CBT. To ensure that patients treated with anxiolytics progressed at a similar rate to those who did not receive them, a quality improvement study was conducted to compare all patients in residential, partial hospitalization and intensive outpatient eating disorder treatment programs.
OrthologAL: A Shiny application for quality-aware humanization of non-human pre-clinical high-dimensional gene expression data
Authors: Chowdary Rishika , Suter Robert K. , D’Antuono Matthew , Gomes Cynthia , Stein Joshua , Lee Ki-Bum , Lee Jae K , Ayad Nagi G. 
Published: November 2024

ABSTRACTSingle-cell and spatial transcriptomics provide unprecedented insight into the inner workings of disease. Pharmacotranscriptomic approaches are powerful tools that leverage gene expression data for drug repurposing and treatment discovery in many diseases. Multiple databases attempt to connect human cellular transcriptional responses to small molecules for use in transcriptome-based drug discovery efforts. However, pre-clinical research often requiresin vivoexperiments in non-human species, which makes capitalizing on such valuable resources difficult. To facilitate the application of pharmacotranscriptomic databases to pre-clinical research models and to facilitate human orthologous conversion of non-human transcriptomes, we introduce OrthologAL. OrthologAL leverages the BioMart database to access different gene sets from Ensembl, facilitating the interaction between these servers without needing user-generated code. Researchers can input their single-cell or other high-dimensional gene expression data from any species, and OrthologAL will output a human ortholog-converted dataset for download and use. To demonstrate the utility of this application, we characterized orthologous conversion in single-cell, single-nuclei, and spatial transcriptomic data derived from common pre-clinical models, including patient-derived orthotopic xenografts of medulloblastoma, and mouse and rat models of spinal cord injury. We show that OrthologAL can convert these data types efficiently to that of corresponding orthologs while preserving the dimensional architecture of the original non-human expression data. OrthologAL will be broadly useful for applying pre-clinical, high-dimensional transcriptomics data in functional small molecule predictions using existing human-annotated databases.
The mechanical anisotropy of adipose tissues regulates ovarian cancer invasion
Authors: Gonzalez-Molina Jordi , Nabili Parisa , Marciano Daniele , Abdelnabi Sara , Gultekin Okan , Rasul Mohammed Fatih , Zhang Yikun , Nadal Clémence , Chrysanthou Alexandra , Alkasalias Twana , Salehi Sahar , Balkwill Frances , Lehti Kaisa , Gautrot Julien E. 
Published: November 2024

AbstractHigh-grade serous ovarian cancer, the most common and aggressive form of ovarian cancer, generally metastasises to visceral adipose tissues. In these tissues, the extracellular matrix through which ovarian cancer cells adhere and migrate is confined by the presence and preponderance of adipocytes. How cells migrate in this unique environment is not known, yet critical to understanding metastatic progression. To study these processes, we develop biomimetic organo-hydrogels that recreate structural and mechanical properties of human visceral adipose tissues. We show that ovarian cancer cells present invasive tropism towards organo-hydrogels, replicating the behaviour observed in native adipose tissues. This migration is facilitated by the mechanical anisotropy and microstructure of organo-hydrogels and adipose tissues, allowing the formation of cell force-induced migratory tracks, a process regulated by TGFβ in an MMP degradation-independent manner. These results highlight the contribution of adipocytes to tissue biophysical features as a key regulatory factor of ovarian cancer cell migration.
Unlocking the Secrets of Amphibious Plant Adaptation: The Role of RNA Modifications
Authors: Maździarz Mateusz , Krawczyk Katarzyna , Szablińska-Piernik Joanna , Paukszto Łukasz , Szczecińska Monika , Sulima Paweł , Sawicki Jakub 
Published: November 2024

AbstractPost-transcriptional RNA modifications, such as N6-methyladenosine (m6A), 5-methylcytosine (m5C), and pseudouridine (Ψ), are critical regulators of plant development, stress responses, and environmental adaptation. The modifications m6A, m5C, and Ψ were insufficiently studied in plant stress responses. To investigate the epitranscriptomic landscape of these modifications, we employed direct RNA sequencing (DRS) to analyze native RNA from the amphibious plantRiccia fluitansgrown in both aquatic and terrestrial environments. Our study revealed the presence of Ψ, m5C, and m6A modifications inR. fluitanstranscriptomes from diverse environments. We observed correlations between the occurrence of these modifications and transcript length, as well as poly(A) tail length. Furthermore, we analyzed the expression of genes encoding Ψ synthases and methyltransferases to gain initial insights into the regulatory mechanisms underlying these processes inR. fluitans. By understanding how RNA modifications are regulated in response to environmental changes, we can unlock the secrets of the remarkable adaptability of amphibious plants. This knowledge could have eventually led to the understanding of the mechanisms of plant land colonization.
A reinforcement learning based software simulator for motor brain-computer interfaces
Authors: Liang Ken-Fu , Kao Jonathan C. 
Published: November 2024

AbstractIntracortical motor brain-computer interfaces (BCIs) are expensive and time-consuming to design because accurate evaluation traditionally requires real-time experiments. In a BCI system, a user interacts with an imperfect decoder and continuously changes motor commands in response to unexpected decoded movements. This “closed-loop” nature of BCI leads to emergent interactions between the user and decoder that are challenging to model. The gold standard for BCI evaluation is therefore real-time experiments, which significantly limits the speed and community of BCI research. We present a new BCI simulator that enables researchers to accurately and quickly design BCIs for cursor control entirely in software. Our simulator replaces the BCI user with a deep reinforcement learning (RL) agent that interacts with a simulated BCI system and learns to optimally control it. We demonstrate that our simulator is accurate and versatile, reproducing the published results of three distinct types of BCI decoders: (1) a state-of-the-art linear decoder (FIT-KF), (2) a “two-stage” BCI decoder requiring closed-loop decoder adaptation (ReFIT-KF), and (3) a nonlinear recurrent neural network decoder (FORCE).
Enhanced immunogenicity of aClostridioides difficileTcdB vaccine adjuvanted with a synthetic dual-TLR ligand adjuvant
Authors: Naz Farha , Hagspiel Nicholas , Xu Feifan , Thompson Brandon , Moreau G. Brett , Young Mary , Herbein Joel , Fox Christopher B , Petri William A , Abhyankar Mayuresh M 
Published: November 2024

AbstractWe report a comprehensive evaluation of the toxin B (TcdB) vaccine adjuvanted with a dual Toll-like receptor ligand liposome adjuvant forClostridioides difficileinfection (CDI). The vaccine completely protected mice from a lethal infection. Compared to alum adjuvanted TcdB, it generated functionally superior systemic antibodies and supported strong memory B cell and gut IgA responses. This pharmaceutically acceptable adjuvant platform holds promise for developing a next-generation CDI vaccine.
Atrial Granules in Atrial Cardiomyocytes as Acidic Calcium Stores
Authors: Akerman Emily , Aston Daniel , Rog-Zielinska Eva , Boland Barry , Schotten Ulrich , Verheule Sander , Capel Rebecca A , Burton Rebecca A.B. 
Published: November 2024

AbstractAcidic calcium stores significantly influence basal calcium transient amplitude and β-adrenergic responses in cardiomyocytes. Atrial myocytes express a small acidic organelle called atrial granules (AG), which store and excrete atrial natriuretic peptide and are not expressed by healthy ventricular myocytes. AG are known to be acidic with a high calcium content. The number and position of these calcium-rich organelles relative to other signaling sites has not been investigated. Staining of acidic organelles in adult guinea pig cardiomyocytes showed the presence of fluorescent acidic puncta throughout the cytosol. Atrial myocytes exhibited an increased concentration of acidic organelles at the nuclear poles. Live cell fluorescent studies using PBA to inhibit peptidylglycine α-amidating monooxygenase, a crucial component of AG membranes, effectively eliminated staining at the nuclear poles and most acidic puncta in atrial cells. The application of PBA to ventricular myocytes did not affect LysoTracker staining. Electron microscopy studies on goat atrial fibrillation (AF) and sham control tissue, allowed visualization of AGs. Quantitative analysis revealed AGs to be in close apposition to the sarcoplasmic reticulum and mitochondria. AGs were significantly increased in AF goat samples when compared to sinus rhythm from 3D electron tomography images. Our imaging studies suggest that AGs make up a large percentage of atrial acidic stores, with AG associated with the sarcoplasmic reticulum and their number increasing during AF. We raise the question whether the positioning of AGs are strategic to communicate with other calcium organelles. Further studies to investigate whether AGs contribute to physiological calcium signalling are required.
TimeFlies: an snRNA-seq aging clock for the fruit fly head sheds light on sex-biased aging
Authors: Tennant Nikolai , Pavuluri Ananya , O’Connor-Giles Kate , Singh Gunjan , Larschan Erica , Singh Ritambhara 
Published: November 2024

AbstractAlthough multiple high-performing epigenetic aging clocks exist, few are based directly on gene expression. Such transcriptomic aging clocks allow us to extract age-associated genes directly. However, most existing transcriptomic clocks model a subset of genes and are limited in their ability to predict novel biomarkers. With the growing popularity of single-cell sequencing, there is a need for robust single-cell transcriptomic aging clocks. Moreover, clocks have yet to be applied to investigate the elusive phenomenon of sex differences in aging. We introduce TimeFlies, a pan-cell-type scRNA-seq aging clock for theDrosophila melanogasterhead. TimeFlies uses deep learning to classify the donor age of cells based on genome-wide gene expression profiles. Using explainability methods, we identified key marker genes contributing to the classification, with lncRNAs showing up as highly enriched among predicted biomarkers. The top biomarker gene across cell types is lncRNA:roX1, a regulator of X chromosome dosage compensation, a pathway previously identified as a top biomarker of aging in the mouse brain. We validated this finding experimentally, showing a decrease in survival probability in the absence of roX1in vivo. Furthermore, we trained sex-specific TimeFlies clocks and noted significant differences in model predictions and explanations between male and female clocks, suggesting that different pathways drive aging in males and females.Graphical Abstract