bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic assessment of efficacy and safety profiles of coagulation cascade proteins identifies Factors II and XI as actionable anticoagulant targets
Authors: Gagnon Eloi , Girard Arnaud , Bourgault Jérôme , Abner Erik ,   Estonian Biobank Research Team, Gill Dipender , Thériault Sébastien , Vohl Marie-Claude , Tchernof André , Esko Tõnu , Mathieu Patrick , Arsenault Benoit J. 
Published: December 2023

ABSTRACTBackgroundAnticoagulants are routinely used by millions of patients worldwide to prevent blood clots. Yet, problems with anticoagulant therapy remain, including a persistent and cumulative bleeding risk in patients undergoing prolonged anticoagulation. New safer anticoagulant targets are needed.MethodsWe performed two-sample Mendelian randomization (MR) and genetic colocalization to prioritize anticoagulant targets with the strongest efficacy (venous thromboembolism [VTE] prevention) and safety (low bleeding risk) profiles. We leveraged three large-scale plasma protein datasets (deCODE, n=35,559; Fenland n = 10,708; ARIC n= 7,213) and one liver gene expression dataset (n =246) to evaluate evidence for a causal effect of 26 coagulation cascade plasma proteins on VTE from a new genome-wide association meta-analysis of 44,232 VTE cases and 847,152 controls (from the UK Biobank, FinnGen and Estonian Biobank), stroke subtypes (from UK Biobank and International Stroke Genetics consortium 73,652 cases and 1,234,808 controls), bleeding outcomes (FinnGen, n=309,154) and over one million parental lifespans (UK Biobank and LifeGen consortium).ResultsGenetically predicted reductions in F2 blood levels were associated with lower VTE risk (OR [odds ratio] per 1 standard deviation [SD] lower F2=0.44, 95% CI=0.38-0.51, p=2.6E-28) and cardioembolic stroke risk (OR = 0.55, 95% CI=0.39-0.76, p=4.2e-04) but not with bleeding (OR = 1.13, 95% CI=0.93-1.36, p=2.2e-01). Genetically predicted F11 reduction were associated with lower risk of VTE (OR = 0.61, 95% CI=0.58-0.64, p=4.1e-85) and cardioembolic stroke (OR = 0.77, 95% CI=0.69-0.86, p=4.1e-06), but not with bleeding (OR = 1.01, 95% CI=0.95-1.08, p=7.5e-01) (Figure 3). These MR associations were concordant across the three blood protein datasets and the hepatic gene expression dataset as well as three different MR and colocalization analyses.ConclusionThese results provide strong genetic evidence that F2 and F11 may represent safe and efficacious therapeutic targets to prevent VTE and cardioembolic strokes without substantially increasing bleeding risk.
A Multi-State Markov Model for the Longitudinal Analysis of Clinical Composite Outcomes in Heart Failure
Authors: Lora Pablos David , Leiva-García Andrea , Bernal José Luis , Vélez Jorge , Palacios Beatriz , Villarreal Miriam , Capel Margarita , Rosillo Nicolás , Hernández Miguel , Bueno Héctor 
Published: December 2023

AbstractBackgroundThe statistical analysis of composite outcomes is challenging. The Clinical Outcomes, HEalthcare REsource utilizatioN, and relaTed costs (COHERENT) model was developed to describe and compare all components (incidence, timing and duration) of composite outcomes, but its statistical analysis remained unsolved. The aim of the study is to assess a multi-State Markov model as one statistical solution for the COHERENT model.MethodsA cohort of 3280 patients admitted to the emergency department or hospital for heart failure during year 2018 were followed during one year. The state of the patient was registered at the end of each day during 365 days as: home, emergency department (ED), hospital, re-hospital, re-ED, and death. Outcomes of patients with or without severe renal disease (sRD) were compared as an example. A Multi-State Markov model was developed to explain transitions to and from these states during follow-up.ResultsA Multi-State Markov model showed, adjusted for age and sex, a significantly lower likelihood of patients with sRD to return home regardless of the state in which they were (ED → HOME (HR, 0.72; 95%CI, 0.54-0.95), RE-ED → HOME (HR, 0.83; 95%CI, 0.75-0.93), HOSPITAL → HOME (HR, 0.77; 95%CI, 0.69-0.86), RE-HOSPITAL → HOME (HR, 0.82; 95%CI, 0.74-0.92) and a higher mortality risk, in particular at the hospital and at home (HOME → Death [HR, 1.54; 95%CI, 1.01-2.37] and HOSPITAL → Death [HR, 1.71; 95%CI, 1.30-2.24].ConclusionMulti-state Markov models offer a statistical solution for the comprehensive analysis of composite outcomes assessed as transitions from different clinical states.Clinical PerspectiveWhat is new?An integrated analysis of all components of composite endpoints including its incidence and duration is possible using the COHERENT model with analysis of transition risks.A statistical approach based on Markov chain models is a new potential statistical solution for the multivariate estimation of the risk of transitions in mutually exclusive composite endpoints.What are the clinical implications?The use of the COHERENT model and Markov models is an opportunity to analyze composite endpoints and understand better the relationships between its components and, potentially, to improve the performance of statistical analysis in randomized controlled trials.The utilization of the COHERENT model and Markov models in randomized controlled trials should be validated in future observational studies and in randomized controlled trials.
Machine learning-based meta-analysis reveals gut microbiome alterations associated with Parkinson’s disease
Authors: Romano Stefano , Wirbel Jakob , Ansorge Rebecca , Schudoma Christian , Ducarmon Quinten Raymond , Narbad Arjan , Zeller Georg 
Published: December 2023

AbstractThere is strong interest in exploring the potential of the gut microbiome for Parkinson’s disease (PD) diagnosis and treatment. However, a consensus on the microbiome features associated with PD and a multi-study assessment of their diagnostic value is lacking. Here, we present a machine learning meta-analysis of PD microbiome studies of unprecedented scale (including 4,490 samples). Within most studies, microbiome-based machine learning models could accurately classify PD patients. However, models were study-specific and did not generalise well across other studies. By training models on multiple datasets, we could improve their general applicability and disease specificity as assessed against microbiomes from other neurodegenerative diseases. Meta-analysis of shotgun metagenomes moreover delineated PD-associated microbial pathways potentially contributing to the deterioration of gut health and favouring the translocation of pathogenic molecules along the gut-brain axis. Strikingly, diverse microbial pathways for the biotransformation of solvents and pesticides were enriched in PD. These results align with the epidemiological evidence that exposure to these molecules increases PD risk and raise the question of whether gut microbial metabolism modulates their toxicity. Taken together, we offer the most comprehensive overview to date about the PD gut microbiome and provide future reference for its diagnostic and functional potential.
wQFM-DISCO: DISCO-enabled wQFM improves phylogenomic analyses despite the presence of paralogs
Authors: Hakim Sheikh Azizul , Ratul MD Rownok Zahan , Bayzid Md. Shamsuzzoha 
Published: December 2023

AbstractGene trees often differ from the species trees that contain them due to various factors, including incomplete lineage sorting (ILS), gene duplication and loss (GDL), and horizontal gene transfer (HGT). Several highly accurate species tree estimation methods have been introduced to explicitly address ILS, including AS-TRAL, a widely used statistically consistent method, and wQFM, a quartet amalgamation approach that is experimentally shown to be more accurate than ASTRAL. Two recent advancements, ASTRAL-Pro and DISCO, have emerged in the field of phylogenomics to consider gene duplication and loss (GDL) events. ASTRAL-Pro introduces a refined measure of quartet similarity, accounting for both orthology and paralogy. DISCO, on the other hand, offers a general strategy to decompose multicopy gene family trees into a collection of single-copy trees, allowing the utilization of methods previously designed for species tree inference in the context of single-copy gene trees. In this study, we first introduce some variants of DISCO to examine its underlying hypotheses and present analytical results on the statistical guarantees of DISCO. In particular, we introduce DISCO-R, a variant of DISCO with a refined and improved pruning strategy that provides more accurate and robust results. We then propose wQFM-DISCO (wQFM paired with DISCO) as an adaptation of wQFM to handle multicopy gene trees resulting from GDL events. Extensive evaluation studies on a collection of simulated and real data sets demonstrate that wQFM-DISCO is significantly more accurate than ASTRAL-Pro and other competing methods.
Evolution of a biological thermocouple by adaptation of cytochrome c oxidase in a subterrestrial metazoan
Authors: Guerin Megan N. , Ellis TreVaughn , Ware Mark J. , Manning Alexandra , Coley Ariana , Amini Ali , Chung George , Gunsalus Kristin C. , Bracht John R. 
Published: December 2023

AbstractIn this study we report a naturally evolved temperature-sensing electrical regulator in the cytochrome c oxidase of the Devil Worm,Halicephalobus mephisto.This extremophile metazoan was isolated 1.3 km underground in a South African goldmine, where it adapted to heat and potentially to hypoxia, making its mitochondrial sequence a likely target of adaptational change. We obtained the full mitochondrial genome sequence of this organism, and show through dN/dS analysis statistically robust evidence of positive selection inH. mephistocytochrome c oxidase subunits. Seventeen of these positively-selected amino acid substitutions were localized in proximity to the H- and K-pathway proton channels of the complex. Surprisingly, theH. mephistocytochrome c oxidase proton pump completely shuts down at low temperatures (20°C) leading to approximately a 4.8-fold reduction in the transmembrane proton gradient voltage (ΔΨm) compared to optimal temperature (37°C). Direct measurement of oxygen consumption found a corresponding 4.7-fold drop at 20°C compared to 37°C. Correspondingly, the lifecycle ofH. mephistotakes four-fold longer at the low temperature compared to higher. This elegant evolutionary adaptation creates a finely-tuned mitochondrial temperature sensor, allowing this ectothermic organism to maximize its reproductive success in varying environmental temperatures. Our study shows that evolutionary innovation may remodel core metabolism to make it more accurately map onto environmental variation.
Accurate multi-population imputation of MICA, MICB, HLA-E, HLA-F and HLA-G alleles from genome SNP data
Authors: Tammi Silja , Koskela Satu , Biobank Blood Service , Hyvärinen Kati , Partanen Jukka , Ritari Jarmo 
Published: December 2023

AbstractIn addition to the classical HLA genes, the major histocompatibility complex (MHC) harbors a high number of other polymorphic genes with less established roles in disease associations and transplantation matching. To facilitate studies of the non-classical and non-HLA genes in large patient and biobank cohorts, we trained imputation models for MICA, MICB, HLA-E, HLA-F and HLA-G alleles on genome SNP array data. We show, using both population-specific and multi-population 1000 Genomes references, that the alleles of these genes can be accurately imputed for screening and research purposes. The best imputation model for MICA, MICB, HLA-E, -F and -G achieved a mean accuracy of 99.3% (min, max: 98.6, 99.9). Furthermore, validation of the 1000 Genomes exome short-read sequencing-based allele calling against a clinical-grade reference data showed an average accuracy of 99.8%, testifying for the quality of the 1000 Genomes data as an imputation reference. The imputation models, trained using the HIBAG algorithm, are available at GitHub (https://github.com/FRCBS/HLA_EFG_MICAB_imputation) and can be run locally, thus avoiding the need of sending sensitive genome data to remote portals.
Metagenome-based microbial community analysis of urine-derived fertilizer
Authors: Woldeyohannis Nebiyat N. , Desta Adey F. 
Published: December 2023

AbstractThe present study aimed to understand the bacterial portion of the microbial community composition and dynamics of plasmid-mediated antimicrobial resistant genes during the optimized process of struvite production from composite human urine. Samples for DNA extraction was collected from fresh urine, stored urine and struvite during the process of struvite production. Shotgun metagenomic analysis was employed to understand the bacterial community. The most dominant phyla in the fresh and stored urine samples were Pseudomonadata, which comprised of 60% and 43% respectively, followed by Bacillota, comprised of 25% and 39% respectively. The struvite sample was dominated by the phylum Bacilliota (61%), Pseudomonadota (18%) and bacteroidota (12%). The members of the above phyla persisted in dominating each sample accordingly. Member of the family Morganellaceae was dominant in the fresh sample while the stored urine and struvite samples were dominated by the family Clostridiaceae. A decrease of members of the class Gammaproteobacteria was observed from the fresh to the struvite sample though not statistically significant. The genusPseudomonasremained to be the most dominant member of Gammaproteobacteria in the fresh and stored urine sample with OTU count of 12,116 and 6,155 with a marked decrease by half in the stored sample. On the other hand, members of the generaClostridium, Enterococcus, Bacteroidesin the stored samples andClostridium, AlkaliphilusandPseudomonasin the struvite samples were dominant. Ninety-six percent of the identified genera were shared in all the samples and the antimicrobial resistance genes (ARGs) identified in the fresh urine were shared by the struvite but not by the stored urine (eg.sul, cat, aphandaacmembers). the presence of high abundance of ARGs in struvite needs attention in the persistence and transmissibility of the ARGs before application for agriculture.
Unraveling the role of γδ T cells in the pathogenesis of an oncogenic avian herpesvirus
Authors: Sabsabi Mohammad A. , Kheimar Ahmed , You Yu , von La Roche Dominik , Härtle Sonja , Göbel Thomas W. , von Heyl Theresa , Schusser Benjamin , Kaufer Benedikt B. 
Published: December 2023

AbstractMarek’s disease virus (MDV) is an oncogenic alphaherpesvirus that causes deadly T cell lymphomas in chickens. MDV is highly cell associated which allows the virus to evade antibody-mediated virus neutralization. Therefore, T cell-mediated immune responses are thought to be crucial for combating this deadly pathogen. In chickens, gamma delta (γδ) T cells represent a major population with up to 50% of all peripheral T cells. However, their role in MDV pathogenesis and tumor formation remains poorly understood. To investigate the role of γδ T cells in MDV pathogenesis, we infected genetically modified chickens that lack γδ T cells (TCR Cγ-/-) with very virulent MDV. Strikingly, disease and tumor incidence were highly increased in the absence of γδ T cells, indicating that γδ T cells play an important role in the immune response against MDV. In the absence of γδ T cells, virus replication was increased by up to 89-fold in the thymus and spleen, both potential sites of T cell transformation. Taken together, our data provide the first evidence that γδ T cells play an important role in restricting MDV replication, pathogenesis and tumors caused by this deadly pathogen.Author Summaryγδ T cells are the most abundant T cells in chickens, but their role in fighting pathogens remains poorly understood. Marek’s disease virus (MDV) is an important veterinary pathogen, causes one of the most frequent cancers in animals and is used as a model for virus-induced tumor formation. Our study revealed that γδ T cells play a crucial role in combating MDV, as disease and tumor incidence was drastically increased in the absence of these cells. γδ T cells restricted virus replication in the key lymphoid organs, thereby decreasing the likelihood of causing tumors and disease. This study provides novel insights into the role of γδ T cells in the pathogenesis of this highly oncogenic virus.
Beta and theta oscillations track effort and previous reward in human basal ganglia and prefrontal cortex during decision making
Authors: Hoy Colin W. , de Hemptinne Coralie , Wang Sarah S. , Harmer Catherine J. , Apps Mathew A. J. , Husain Masud , Starr Philip A. , Little Simon 
Published: December 2023

AbstractChoosing whether to exert effort to obtain rewards is fundamental to human motivated behavior. However, the neural dynamics underlying the evaluation of reward and effort in humans is poorly understood. Here, we investigate this with chronic intracranial recordings from prefrontal cortex (PFC) and basal ganglia (BG; subthalamic nuclei and globus pallidus) in people with Parkinson’s disease performing a decision-making task with offers that varied in levels of reward and physical effort required. This revealed dissociable neural signatures of reward and effort, with BG beta (12-20 Hz) oscillations tracking subjective effort on a single trial basis and PFC theta (4-7 Hz) signaling previous trial reward. Stimulation of PFC increased overall acceptance of offers in addition to increasing the impact of reward on choices. This work uncovers oscillatory mechanisms that guide fundamental decisions to exert effort for reward across BG and PFC, as well as supporting a causal role of PFC for such choices.
Pseudomonas aeruginosa kills Staphylococcus aureus in a polyphosphate-dependent manner
Authors: Shah Ritika , Jankiewicz Olivia , Johnson Colton , Livingston Barry , Dahl Jan-Ulrik 
Published: December 2023

ABSTRACTDue to their frequent coexistence in many polymicrobial infections, including in patients with burn or chronic wounds or cystic fibrosis, recent studies have started to investigate the mechanistic details of the interaction between the opportunistic pathogensPseudomonas aeruginosaandStaphylococcus aureus.P. aeruginosarapidly outcompetesS. aureusunderin vitroco-cultivation conditions, which is mediated by several ofP. aeruginosa’s virulence factors. Here, we report that polyphosphate (polyP), an efficient stress defense system and virulence factor inP. aeruginosa, plays a role for the pathogen’s ability to inhibit and killS. aureusin a contact-independent manner. We show thatP. aeruginosacells characterized by low polyP level are less detrimental toS. aureusgrowth and survival while the gram-positive pathogen is significantly more compromised by the presence ofP. aeruginosacells that produce high level of polyP. We show that the polyP-dependent phenotype could be a direct effect by the biopolymer, as polyP is present in the spent media and causes significant damage to theS. aureuscell envelope. However, more likely is that polyP’s effects are indirect through the regulation of one ofP. aeruginosa’svirulence factors, pyocyanin. We show that pyocyanin production inP. aeruginosaoccurs polyP-dependent and harmsS. aureusthrough membrane damage and the generation of reactive oxygen species, resulting in increased expression of antioxidant enzymes. In summary, our study adds a new component to the list of biomolecules that the gram-negative pathogenP. aeruginosagenerates to compete withS. aureusfor resources.IMPORTANCEHow do interactions between microorganisms shape the course of polymicrobial infections? Previous studies have provided evidence that the two opportunistic pathogensP. aeruginosaandS. aureusgenerate molecules that modulate their interaction with potentially significant impact on disease outcomes. Our study identified the biopolymer polyP as a new effector molecule that impactsP. aeruginosa’s interaction withS. aureus. We show thatP. aeruginosakillsS. aureusin a polyP-dependent manner, which occurs primarily through the polyP-dependent production of theP. aeruginosavirulence factor pyocyanin. Our findings add a new role for polyP to an already extensive list of functions. A more in-depth understanding of how polyP influences interspecies interactions is critical, as targeting polyP synthesis in bacteria such asP. aeruginosamay have a significant impact on other microorganisms and potentially result in dynamic changes in the microbial composition.
Astrocyte-dependent local neurite pruning and Hox gene-mediated cell death in Beat-Va neurons
Authors: Lehmann Katherine S , Hupp Madison T , Jefferson Amanda , Cheng Ya-Chen , Sheehan Amy E , Kang Yunsik , Freeman Marc R 
Published: December 2023

AbstractNeuronal remodeling is extensive and mechanistically diverse across the nervous systems of complex metazoans. To explore circuit refinement mechanisms, we screened for new neuronal subtypes in theDrosophilanervous system that undergo remodeling early in metamorphosis. We find Beat-VaMneurons elaborate a highly branched neurite network during larval stages that undergoes local neurite pruning during early metamorphosis. Surprisingly, Beat-VaMneurons remodel their branches despite blockade of steroid hormone signaling and instead depend on signaling from astrocytes to activate pruning. We show Beat-VaLneurons undergo steroid hormone-dependent cell death in posterior but not anterior abdominal segments. Correct activation of apoptotic cell death relies on segment-specific expression of the hox geneAbd-B, which is capable of activating cell death in any Beat-VaLneuron. Our work provides new model cells in which to study neuronal remodeling, highlights an important role for astrocytes in activating local pruning inDrosophilaindependent of steroid signaling, and defines a Hox gene-mediated mechanism for segment-specific cell elimination.SummaryLehmann et al. characterize two new populations of neurons that undergo remodeling duringDrosophilametamorphosis. Beat-VaMneurons undergo drastic neurite pruning that is largely independent of ecdysone signaling and instead is driven by astrocytes. Beat-VaLneurons undergoAbd-Bmediated, caspase driven cell death in a segmentally restricted manner.
A Convolutional Neural Network based system for classifying malignant and benign skin lesions using mobile-device images
Authors: Mhedbi Rim , Chan Hannah O. , Credico Peter , Joshi Rakesh , Wong Joshua N. , Hong Collin 
Published: December 2023

AbstractThe escalating incidence of skin lesions, coupled with a scarcity of dermatologists and the intricate nature of diagnostic procedures, has resulted in prolonged waiting periods. Consequently, morbidity and mortality rates stemming from untreated cancerous skin lesions have witnessed an upward trend. To address this issue, we propose a skin lesion classification model that leverages the efficient net B7 Convolutional Neural Network (CNN) architecture, enabling early screening of skin lesions based on camera images. The model is trained on a diverse dataset encompassing eight distinct skin lesion classes: Basal Cell Carcinoma (BCC), Squamous Cell Carcinoma (SCC), Melanoma (MEL), Dysplastic Nevi (DN), Benign Keratosis-Like lesions (BKL), Melanocytic Nevi (NV), and an ‘Other’ class. Through multiple iterations of data preprocessing, as well as comprehensive error analysis, the model achieves a remarkable accuracy rate of 87%.