bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alzheimer’s Disease Sequencing Project Release 4 Whole Genome Sequencing Dataset
Authors: Leung Yuk Yee , Lee Wan-Ping , Kuzma Amanda B , Nicaretta Heather , Valladares Otto , Gangadharan Prabhakaran , Qu Liming , Zhao Yi , Ren Youli , Cheng Po-Liang , Kuksa Pavel P , Wang Hui , White Heather , Katanic Zivadin , Bass Lauren , Saravanan Naveen , Greenfest-Allen Emily , Kirsch Maureen , Cantwell Laura , Iqbal Taha , Wheeler Nicholas R , Farrell John J. , Zhu Congcong , Turner Shannon L , Gunasekaran Tamil I , Mena Pedro R , Jin Jimmy , Carter Luke ,   Alzheimer’s Disease Sequencing Project, Zhang Xiaoling , Vardarajan Badri N , Toga Arthur , Cuccaro Michael , Hohman Timothy J , Bush William S , Naj Adam C , Martin Eden , Dalgard Clifton , Kunkle Brian W , Farrer Lindsay A , Mayeux Richard P , Haines Jonathan L , Pericak-Vance Margaret A , Schellenberg Gerard D , Wang Li-San 
Published: December 2024

AbstractThe Alzheimer’s Disease Sequencing Project (ADSP) is a national initiative to understand the genetic architecture of Alzheimer’s Disease and Related Dementias (AD/ADRD) by sequencing whole genomes of affected participants and age-matched cognitive controls from diverse populations. The Genome Center for Alzheimer’s Disease (GCAD) processed whole-genome sequencing data from 36,361 ADSP participants, including 35,014 genetically unique participants of which 45% are from non-European ancestry, across 17 cohorts in 14 countries in this fourth release (R4). This sequencing effort identified 387 million bi-allelic variants, 42 million short insertions/deletions, and 2.2 million structural variants. Annotations and quality control data are available for all variants and samples. Additionally, detailed phenotypes from 15,927 participants across 10 domains are also provided. A linkage disequilibrium panel was created using unrelated AD cases and controls. Researchers can access and analyze the genetic data via NIAGADS Data Sharing Service, the VariXam tool, or NIAGADS GenomicsDB.
Where and how can WASH work? Understanding limited impacts from a randomized control trial of water, sanitation, and hygiene interventions in a high burden setting
Authors: Kraay Alicia N. M. , Brouwer Andrew F. , Zahid Mondal H. , Njenga Sammy , Colford John M. , Freeman Matthew C. , Eisenberg Joseph N.S. 
Published: December 2024

AbstractBackgroundDespite their strong theoretical basis, water, sanitation, and hygiene (WASH) interventions have had inconsistent benefits on diarrhea in low- and middle-income settings. The WASH Benefits (WASH-B) Kenya randomized controlled trial evaluated a set of WASH interventions targeted at children under age 2 and found no effect on diarrheal prevalence.ObjectivesWe explored whether and how changes to intervention and contextual factors could impact health gains as a means to inform future WASH interventions.MethodsWe implemented a compartmental transmission model with environmental pathways and water (W), sanitation (S), and hygiene (H) interventions fit to WASH-B Kenya trial data (n=11,856) using a Bayesian sampling approach. We developed counterfactual simulations to predict how a trial might perform given improved 1) local contextual factors (i.e., reduced transmission, and increased completeness of transmission pathways targeted) and/or 2) intervention factors (i.e., increased intervention efficacy, compliance, and community coverage). We considered change in intervention effectiveness in the counterfactual scenarios for each intervention alone and in combination (WSH). We determined what combinations would be needed to achieve 50% reduction in child diarrhea compared to the control arm.ResultsWe found that high diarrheal prevalence in the WASH-B Kenya trial was likely the primary reason for ineffectiveness. While none of the tested counterfactual factors greatly impacted intervention effectiveness in isolation, we estimated that 50% reduction in child diarrhea in the combined WSH treatment arm could be achieved through a combination of substantial intervention improvements (i.e., 50% intervention efficacy, 100% compliance, and 60% community coverage), but could not be attained for the single intervention arms. With improvements to contextual factors (consistent, 7.5% diarrheal prevalence, 50% increase in completeness) coupled with more modest increases in intervention factors (i.e., 50% efficacy and 100% compliance but only 20% community coverage), could achieve a 50% reduction in diarrhea in the combined WSH arm.ConclusionsIn settings with high enteric pathogen prevalence, WASH interventions must be used by a substantial fraction the population and block all main transmission routes to achieve substantial reductions in diarrheal disease burden, including those over age 2. The WASH interventions and targeting strategy for the WASH-B Kenya trial were unlikely to appreciably reduce diarrheal disease because of the high burden. In settings with more modest transmission, there are intervention factor targets that could result in measurable reductions in diarrhea. Application of this simulation-based approach could inform WASH policies and programs, as well as the design of future trials.
Turncoat antibodies unmasked in a model of autoimmune demyelination: from biology to therapy
Authors: Taghipour-Mirakmahaleh Reza , Morin Françoise , Zhang Yu , Bourhoven Louis , Béland Louis-Charles , Zhou Qun , Jaworski Julie , Park Anna , Dominguez Juan Manuel , Corbeil Jacques , Flanagan Eoin P. , Marignier Romain , Larochelle Catherine , Kerfoot Steven , Vallières Luc 
Published: December 2024

AbstractAutoantibodies contribute to many autoimmune diseases, yet there is no approved therapy to neutralize them selectively. A popular mouse model, experimental autoimmune encephalomyelitis (EAE), could serve to develop such a therapy, provided we can better understand the nature and importance of the autoantibodies involved. Here we report the discovery of autoantibody-secreting extrafollicular plasmablasts in EAE induced with specific myelin oligodendrocyte glycoprotein (MOG) antigens. Single-cell RNA sequencing reveals that these cells produce non-affinity-matured IgG antibodies. These include pathogenic antibodies competing for shared binding space on MOG’s extracellular domain. Interestingly, the synthetic anti-MOG antibody 8-18C5 can prevent the binding of pathogenic antibodies from either EAE mice or people with MOG antibody disease (MOGAD). Moreover, an 8-18C5 variant carrying the NNAS mutation, which inactivates its effector functions, can reduce EAE severity and promote functional recovery. In brief, this study provides not only a comprehensive characterization of the humoral response in EAE models, but also a proof of concept for a novel therapy to antagonize pathogenic anti-MOG antibodies.
Two Key Actinomycetota Taxa in the Human Gut Microbiota are Associated withSchistosoma mansoniInfection Burden
Authors: Appiah-Twum Francis , Okyere Lydia , Sumboh Jeffrey Gabriel , Osabutey Dickson , Ismail Rahmat Bint Yusif , Darko Hilda , Ashong Yvonne , Wilson Michael D. , Akorli Jewelna 
Published: December 2024

AbstractIn this study, we sought to identify key microbial taxa associated with human gut dysbiosis duringS. mansoniinfection and whether the changes are linked to the intensity of helminth infection. Stool samples were obtained from 20 persons infected with schistosomiasis and an equal number of uninfected persons from an endemic rural community in Ghana. Infection intensity was scored as egg count per gram (EPG) using the Kato-Katz method. Positive stool samples were further stratified as low-moderate (<400 EPG, n=15) and high (>400 EPG, n=5) infection burden. The composition and diversity of the gut microbiota and potential microbial markers associated withS. mansoniinfection intensity were determined from 16S rRNA amplicon sequence analyses. No difference in ß-diversity was observed between positives and negatives (PERMANOVA: R2= 0.012,p= 0.723), although there was an increased abundance ofBifidobacterium(p= 0.008) in infected stool samples compared to the negatives. Further analyses showed thatBifidobacterium(p= 0.003) andCollinsella(p= 0.029) were elevated considerably among the low-moderate infected samples, while the pathobiontEscherichia-Shigellawas reduced (p= 0.0078). Our findings show that intestinal schistosomiasis results in human gut microbiota dysbiosis, which is only distinguished when the intensity of infection is considered, with two keyActinomycetotaspecies assuming importance depending on the infection burden.Author SummaryThis study investigates the relationship between Schistosoma mansoni infections, a major cause of intestinal schistosomiasis, and the human gut microbiome. Using samples from an endemic region in Ghana, the research examines how infection intensity impacts gut bacteria. The findings reveal that certain beneficial bacteria, such as Bifidobacterium and Collinsella, become more abundant in cases of low to moderate infection, potentially maintaining immune regulation and gut health. However, these effects are not seen in high-infection instances, possibly due to the aggressive hallmarks of high-intensity helminth infections. Understanding these dynamics could be pivotal for developing microbiome-based interventions to improve treatment outcomes for schistosomiasis and similar parasitic infections. This study sheds light on the complex interplay between infectious parasites and gut microbes, emphasising the promise of microbiome research in enhancing public health efforts in areas where parasitic diseases persist.
Between-movie variability severely limits generalizability of “naturalistic” neuroimaging
Authors: Leipold Simon , Ravi Rao Rajat , Schoffelen Jan-Mathijs , Bögels Sara , Toni Ivan 
Published: December 2024

Abstract“Naturalistic imaging” paradigms, where participants watch movies during fMRI, have gained popularity over the past two decades. Many movie-watching studies measure inter-subject correlation (ISC), which refers to the correlation between participants’ neural activation time series. Previous research has focused on explaining ISC differences during movie-watching based on individual states and traits, such as social distance, personality, and political orientation. For example, friends show higher ISC than strangers while watching movies.However, movies are not natural categories but cultural artifacts that evoke varying levels of ISC depending on content, directing style, or editing methods. This raises questions about how much trait- or state-like differences in ISC depend on the specific movies chosen, potentially limiting the generalizability of findings across different movies.Here, we used an fMRI dataset of 112 participants watching eight animated movies to (a) quantify between-movie variability in ISC across the brain and (b) assess the implications for the generalizability of trait- or state-like effects on ISC. We found substantial between-movie variability in ISC, with this variability differing across brain regions. Crucially, brain regions with the highest ISC exhibited the greatest variability, indicating that trait- or state-like differences in ISC from one movie may not generalize to others.We conclude that variability between movies limits the generalizability of trait- or state-like ISC differences. Using a specific movie in neuroscience should be treated similarly to using a particular task, requiring a comparable characterization of the constituent cognitive elements. Broad generalizations about “naturalistic imaging” or “movie watching” are not warranted.
DeepGraphMut: A graph-based deep learning method for cancer prognosis using somatic mutation profile
Authors: Jose Aswin , Srivastava Akansha , Vinod P.K. 
Published: December 2024

ABSTRACTCancer remains a leading cause of morbidity and mortality worldwide. Despite advances in genomics, identifying clinically relevant subtypes of cancer remains challenging due to its complex and heterogeneous nature. In this work, we propose DeepGraphMut (DGM), a novel graph-based deep-learning pipeline that integrates somatic mutation data with protein-protein interaction (PPI) networks. By employing a graph autoencoder with a graph attention layer and a node-level attention decoder, DGM generates patient-specific clinically relevant encodings for unsupervised and supervised tasks. We demonstrate the effectiveness of DGM across 16 cancer types comprising of 7352 samples from The Cancer Genome Atlas (TCGA). Unsupervised clustering reveals distinct subtypes with significant survival differences in 11 cancer types. In supervised analysis using a Cox regression model, DGM demonstrates excellent performance in predicting survival outcomes, achieving a high concordance index (c-index) value in the range of 0.7 across most cancers, underscoring its robust predictive performance using only somatic mutation data. Furthermore, DGM outperforms its lightweight variant and the network-based stratification method in both unsupervised and supervised analyses. In summary, this study presents a promising approach for cancer subtype identification and prognosis, especially in resource-limited settings where multi-omics data may not be readily available. By leveraging the strengths of graph learning and network biology, DGM offers a valuable tool for advancing personalized medicine.
Structural Dynamics of the Dengue Virus Non-structural 5 (NS5) Interactions with Promoter Stem Loop A (SLA)
Authors: Obi Juliet O. , Kihn Kyle C. , McQueen Linfah , Fields James K. , Snyder Greg A. , Deredge Daniel J. 
Published: December 2024

AbstractThe dengue virus (DENV) NS5 protein plays a central role in dengue viral RNA synthesis which makes it an attractive target for antiviral drug development. DENV NS5 is known to interact with the stem-loop A (SLA) promoter at the 5’-untranslated region (5’-UTR) of the viral genome as a molecular recognition signature for the initiation of negative strand synthesis at the 3’ end of the viral genome. However, the conformational dynamics involved in these interactions are yet to be fully elucidated. Our study explores the structural dynamics of NS5 from DENV serotype 2 (DENV2 NS5) in complex with SLA, employing surface plasmon resonance (SPR), hydrogen - deuterium exchange coupled to mass spectrometry (HDX-MS), computational modeling, and cryoEM single particle analysis to delineate the molecular details of their interaction. Our findings indicate that DENV2 NS5 binds SLA in a closed conformation with significant interdomain cooperation between the methyltransferase (MTase) and RNA-dependent RNA polymerase (RdRp) domains, a feature integral to the interaction. Our HDX-MS studies reveal SLA-induced conformational changes in both domains of DENV2 NS5, reflecting a potential mechanism for dengue NS5’s multifunctional role in viral replication. Lastly, our cryoEM structure provides the first visualization of the DENV2 NS5-SLA complex, confirming a conserved SLA binding mode across DENV serotypes. These insights obtained from our study enhance our understanding of dengue NS5’s complex conformational landscape, supporting the potential development of antiviral strategies targeting dengue NS5’s conformational states.
Comprehensive Network Analysis of miRNA Biogenesis Proteins and Their Ligand Interaction Sites to Identify Novel Targets for Cancer Therapeutics
Authors: Almhanna Hazem , Naser Hassan Hachim , Kumar Arun HS 
Published: December 2024

AbstractA network analysis of canonical microRNA (miRNA) biogenesis identified DROSHA, Exportin-5, and DICER1 as essential proteins for both precursor and mature miRNA processing. The analysis revealed strong interactions between these proteins and others involved in miRNA biogenesis, suggesting a complex regulatory network. Ligand binding sites on these key proteins were identified, suggesting potential targets for therapeutic intervention. Our findings indicate that modulating miRNA biogenesis through these proteins could influence cellular protein production and function, providing a promising avenue for developing advanced therapy medicinal products (ATMPs) to impact protein expression in diseases such as cancer.
Metagenomic analysis of marsupial gut microbiomes provides a genetic basis for the low methane economy
Authors: Bowerman Kate L. , Lu Yang , McRae Harley , Volmer James G. , Zaugg Julian , Pope Phillip B. , Hugenholtz Philip , Greening Chris , Morrison Mark , Soo Rochelle M. , Evans Paul N. 
Published: December 2024

AbstractThe potent greenhouse gas methane is an end-product of plant biomass digestion by gut microbiota, though the amount produced and/or released varies among herbivorous animals. On a per unit of feed basis, macropodid marsupials (e.g. kangaroos) are widely thought to be low methane-emitting herbivores compared to high methane-producing ruminant livestock. How the gut microbiome contributes to the low methane status of marsupials is not well understood but of high potential value for a low methane economy. Here, we analyse the faecal metagenomes of 14 different marsupial species and 1,394 derived metagenome-assembled genomes (MAGs), focusing on the functional distinction of the bacterial and archaeal communities compared to ruminant faecal microbiomes. Though composition and function of the marsupial gut microbiome considerably varied across and within animal species, there was a clear host-associated bacterial signature for the community that differed significantly between marsupial hosts and compared to ruminants. Of particular note was a range ofBacteroidota, Campylobacterota, Desulfobacterota,PseudomonadotaandVerrucomicrobiotaspecies that were enriched in marsupials and encode H2-uptake hydrogenases that mediate hydrogenotrophic respiration. Additionally, in support of an enrichment of electron sinks, enzymes for butyrate, propionate, and glutamate production, as well as nitrate, nitrite, and fumarate respiration were enriched in marsupials. Collectively, these data suggest that, by favoring an enrichment of alternate hydrogen sinks of bacterial origin, the low methane phenotype reported for marsupials is feasible and offers a genetic basis to pursue reductions of livestock methane emissions.
Gut microbiome speciesLevilactobacillus brevisregulates reproductive fitness inC. elegans
Authors: Braun Nicole J. , Mor Danielle E. 
Published: December 2024

AbstractThe human gut microbiome has attracted considerable attention in recent years due to its broad impact on various physiological processes; however, the mechanisms underlying host-microbiota interactions are not fully understood. In particular, direct causal relationships between specific species and host health outcomes remain to be established. Here we examined the effects of human gut microbiome speciesLevilactobacillus brevis(L. brevis) on host health usingC. elegansand found thatL. brevisfeeding caused significant reproductive dysfunction, including severe egg retention leading to fewer eggs laid, and abnormal egg morphologies. These effects were associated with impaired serotonin signaling in hermaphrodite-specific neurons (HSNs), which regulate egg-laying, while vulval muscle function remained intact. Progeny fromL. brevis-fed worms exhibited reduced viability and delayed development, suggesting an overall reduction inC. elegansreproductive fitness. Our findings align with emerging evidence linking gut dysbiosis to reproductive health disorders in humans, and underscore the need to explore specific roles of individual gut microbiota in host health and physiology. Our work also highlights the utility ofC. elegansas a model for studying the complex interactions between the microbiome and the host.
More than half of annotated human miRNAs are never expressed at levels sufficient for biological function
Authors: Kachooei Saba Ataei , Bracken Julie M , Pillman Katherine A , Gregory Philip A , Bracken Cameron P 
Published: December 2024

AbstractMicroRNAs (miRNAs) are widely studied for their role in post-transcriptional gene regulation, often using exogenous overexpression systems to reveal their functions. However, such approaches may not accurately reflect endogenous miRNA activity due to the substantially higher expression levels achieved experimentally. To address this, we sought to determine the minimal endogenous expression threshold required for a miRNA to exert biologically significant effects. By comparing these experimentally determined expression thresholds with small RNA sequencing datasets comprising hundreds of cell lines and tens of thousands of tissue samples, we found that more than half of all annotated miRNAs are never expressed at levels sufficient to be biologically relevant. This calls into question the conclusions of thousands of studies reporting functions for these lowly expressed miRNAs, whose results are likely attributable to artificial overexpression rather than physiological activity. Our study highlights the need for more rigorous evaluation of miRNA functionality in their native context, and provides further support to arguments that the size of the functional human “microRNAome” is far smaller than some estimates of miRNA numbers based upon small RNA sequencing data.
Engineering an Anthrax Toxin inspired protein-ligand for Nanoparticle-Mediated Treatment of Malignant Melanoma
Authors: Márquez-López Ana , Fanarraga Mónica L 
Published: December 2024

AbstractBackgroundMalignant melanoma is a highly aggressive cancer that presents significant treatment challenges, especially in metastatic stages where conventional therapies often fail due to resistance. Targeting the tumor’s supportive environment rather than the cancer cells themselves offers a promising strategy. The tumor endothelial marker 8 (TEM8), also known as anthrax toxin receptor 1, is overexpressed in tumor neovasculature endothelial cells and their precursors, making it an attractive therapeutic target. This study introduces PA17, a protein ligand derived from the anthrax toxin binding domain and specifically engineered to target TEM8, aiming to enhance the precision and effectiveness of nanomedicine.ResultsRecombinant and purified PA17 ligand protein exhibited high affinity for TEM8 bothin vitroandin vivoin preclinical melanoma models, demonstrating significant intrinsic antitumor activity and no detectable off-target effects. When PA17 was used to functionali ze doxorubicin-loaded mesoporous silica nanoparticles, it resulted in a 65% reduction in tumor mass with a single local administration and a 55% reduction after three systemic administrations. This treatment was significantly more effective than free doxorubicin or non-targeted doxorubicin-loaded nanoparticles and was associated with a marked decrease in tumor vascularization.ConclusionsThis study highlights the potential of toxin-derived ligands as novel targeti ng agents for tumor neovasculature in aggressive cancers such as malignant melanoma. PA17, with its intrinsic antitumor properties and exceptional targeting efficacy, enhances the efficacy of nanomedicine and addresses common challenges such as drug resistance. The use of natural ligands represents a transformative approach to nanomedicine delivery and offers a promising strategy to advance cancer nanotherapy.Graphical abstract image