bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nascent transcript O-MAP reveals the molecular architecture of a single-locus subnuclear compartment built by RBM20 and theTTNRNA
Authors: Kania Evan E. , Fenix Aidan , Marciniak Daphnée M. , Lin Qiaoyi , Bianchi Sara , Hristov Borislav , Li Shuai , Camplisson Conor K. , Fields Rose , Beliveau Brian J. , Schweppe Devin K. , Noble William S. , Ong Shao-En , Bertero Alessandro , Murry Charles E. , Shechner David M. 
Published: November 2024

ABSTRACTEukaryotic nuclei adopt a highly compartmentalized architecture that influences nearly all genomic processes. Understanding how this architecture impacts gene expression has been hindered by a lack of tools for elucidating the molecular interactions at individual genomic loci. Here, we adapt oligonucleotide-mediated proximity-interactome mapping (O-MAP) to biochemically characterize discrete, micron-scale nuclear neighborhoods. By targeting O-MAP to introns within theTTNpre-mRNA, we systematically map the chromatin loci, RNAs, and proteins within a muscle-specific RNA factory organized around theTTNlocus. This reveals an unanticipated compartmental architecture that organizescis- andtrans-interacting chromosomal domains, including a hub of transcriptionally silenced chromatin. The factory also recruits dozens of unique RNA-binding and chromatin-scaffolding factors, including QKI and SAFB, along with their target transcripts. Loss of the cardiac-specific splicing factor RBM20—a master regulator ofTTNsplicing that is mutated in dilated cardiomyopathy—remodels nearly every facet of this architecture. This establishes O-MAP as a pioneering method for probing single-locus, microcompartment-level interactions that are opaque to conventional tools. Our findings suggest new mechanisms by which coding genes can "moonlight" in nuclear-architectural roles.
Hantaan virus-derived peptides that stabilize HLA-E could abrogate inhibition of CD56dimNKG2A+NK cells
Authors: Xue Manling , Tang Kang , Zhang Yusi , Xu Xiaoyue , Zhang Chunmei , Zuo Jiajia , Wang Fenglan , Zhang Xiyue , Zheng Xuyang , Zhuang Ran , Zhang Yun , Jin Boquan , Ma Ying 
Published: November 2024

AbstractNK cells could participate in the pathogenesis process of virus infectious diseases through the inhibitory receptor CD94/NKG2A interacting with HLA-E/virus-derived peptide complex. However, the effects and mechanisms of NKG2A-HLA-E axis-mediated NK cell responses in hemorrhagic fever with renal syndrome (HFRS) caused by Hantaan virus (HTNV) infection remain unclear. Single-cell RNA sequencing and flow cytometry were employed to analyze the phenotype and function of different NK cell subsets in HFRS patients. The K562/HLA-E cells binding assay was used for peptide affinity detection. The binding capacity of HLA-E/peptide-CD94/NKG2A was detected using ligand-receptor binding assay and tetramer staining. The cytotoxicity assay of NK cells against peptide-pulsed K562/HLA-E cells was conducted for functional evaluation. In this study, CD56dimCD16+NKG2A+NK cells were the main subset in HFRS patients, showing activation and proliferation phenotypes with NKG2C−CD57−and the ability to secrete cytokines and cytotoxic mediators. Notably, none of the four identified HTNV epitopes presented by HLA-E could be recognized by CD94/NKG2A on CD56dimNKG2A+NK cells. Furthermore, the subset of CD56dimNKG2A+NK cells showed the enhanced cytolytic capacity against HTNV peptide pulsed K562/HLA-E cells ex vivo. Taken together, the findings demonstrate that HTNV-derived peptides presented by HLA-E could “abrogate” the inhibition of CD56dimNKG2A+NK cells, contributing to the antiviral immune response in HFRS patients.Author SummaryHantaan virus (HTNV) is one of the main pathogens causing hemorrhagic fever with renal syndrome (HFRS) characterized by fever, hemorrhage, renal injury, and thrombocytopenia. Recently, the studies have shown that the interaction of human leukocyte antigen E (HLA-E) and natural-killer group 2, member A (NKG2A) inhibitory receptors could regulate the functions of NK cells, participating the pathogenesis process of virus infectious diseases. However, the role of NK cell response induced by HTNV infection in the pathogenesis of HFRS has not been completely determined. Here, the findings demonstrate that the elevated percentage of CD56dimNKG2A+NK cell subset in peripheral blood of HFRS patients might exert antiviral effects through the unrecognize between CD94/NKG2A and HLA-E/HTNV peptide complex, which may abrogate the inhibition of NKG2A-expressing NK cells. This study may provide the mechanisms of NKG2A-HLA-E axis on regulating NK cell responses in HTNV infections.
Integrative metagenomics and metabolomics reveal age-associated gut microbiota and metabolite alterations in experimental COVID-19
Authors: Rodrigues Patrícia Brito , de Rezende Rodovalho Vinícius , Sencio Valentin , Benech Nicolas , Creskey Marybeth , Silva Angulo Fabiola , Delval Lou , Robil Cyril , Gosset Philippe , Machelart Arnaud , Haas Joel , Descat Amandine , Goosens Jean François , Beury Delphine , Maurier Florence , Hot David , Wolowczuk Isabelle , Sokol Harry , Zhang Xu , Ramirez Vinolo Marco Aurélio , Trottein François 
Published: November 2024

AbstractAging is a key contributor of morbidity and mortality during acute viral pneumonia. The potential role of age-associated dysbiosis on disease outcomes is still elusive. In the current study, we used high-resolution shotgun metagenomics and targeted metabolomics to characterize SARS-CoV-2-associated changes in the gut microbiota from young (2-month-old) and aged (22-month-old) hamsters, a valuable model of COVID-19. We show that age-related dysfunctions in the gut microbiota are linked to disease severity and long-term sequelae in older hamsters. Our data also reveal age-specific changes in the composition and metabolic activity of the gut microbiota during both the acute phase (day 7 post-infection, D7) and the recovery phase (D22) of infection. Aged hamsters exhibited the most notable shifts in gut microbiota composition and plasma metabolic profiles. Through an integrative analysis of metagenomics, metabolomics, and clinical data, we identified significant associations between bacterial taxa, metabolites and disease markers in the aged group. On D7 (high viral load and lung epithelial damage) and D22 (body weight loss and fibrosis), numerous amino acids, amino acid-related molecules, and indole derivatives were found to correlate with disease markers. In particular, a persistent decrease in phenylalanine, tryptophan, glutamic acid, and indoleacetic acid in aged animals positively correlated with poor recovery of body weight and/or lung fibrosis by D22. In younger hamsters, several bacterial taxa (Eubacterium,Oscillospiraceae,Lawsonibacter) and plasma metabolites (carnosine and cis-aconitic acid) were associated with mild disease outcomes. These findings support the need for age-specific microbiome-targeting strategies to more effectively manage acute viral pneumonia and long-term disease outcomes.
Nanoparticle-Supported, Rapid, Digital Quantification of Neutralizing Antibodies Against SARS-CoV-2 Variants
Authors: Mirjalili Seyedsina , Ikbal Md Ashif , Hou Ching-Wen , Mohammadi Maziyar Kalateh , Choi Yeji , Kelbauskas Laimonas , VanBlargan Laura A. , Hogue Brenda G. , Murugan Vel , Diamond Michael S. , Wang Chao 
Published: November 2024

AbstractThe measurement of neutralizing immune responses to viral infection is essential, given the heterogeneity of human immunity and the emergence of new virus strains. However, neutralizing antibody (nAb) assays often require high-level biosafety containment, sophisticated instrumentation, and long detection times. Here, as a proof-of-principle, we designed a nanoparticle-supported, rapid, electronic detection (NasRED) assay to assess the neutralizing potency of monoclonal antibodies (mAbs) against SARS-CoV-2. The gold nanoparticles (AuNPs) coated with human angiotensin-converting enzyme 2 (ACE2) protein as nAb potency reporters were mixed with the mAbs to be tested, as well as streptavidin-conjugated multivalent spike (S) protein or their receptor binding domains (RBD). High-affinity and ACE2-competitive nAbs alter the S (or RBD)-to-ACE2 binding level and modulate AuNP cluster formation and precipitation. The amount of free-floating AuNP reporters is quantified by a semiconductor-based readout system that measures the AuNPs’ optical extinction, producing nAb signals that can differentiate SARS-CoV-2 variants (Wuhan-Hu-1, Gamma, and Omicron). The modular design nature, short assay time (less than 30 minutes), and portable and inexpensive readout system make this NasRED-nAb assay applicable to measuring vaccine potency, immune responses to infection, and the efficacy of antibody-based therapies.
Reproducible processing of TCGA regulatory networks
Authors: Fanfani Viola , Shutta Katherine H. , Mandros Panagiotis , Fischer Jonas , Saha Enakshi , Micheletti Soel , Chen Chen , Ben Guebila Marouen , Lopes-Ramos Camila M. , Quackenbush John 
Published: November 2024

AbstractBackgroundTechnological advances in sequencing and computation have allowed deep exploration of the molecular basis of diseases. Biological networks have proven to be a useful framework for interrogating omics data and modeling regulatory gene and protein interactions. Large collaborative projects, such as The Cancer Genome Atlas (TCGA), have provided a rich resource for building and validating new computational methods resulting in a plethora of open-source software for downloading, pre-processing, and analyzing those data. However, for an end-to-end analysis of regulatory networks a coherent and reusable workflow is essential to integrate all relevant packages into a robust pipeline.FindingsWe developed tcga-data-nf, a Nextflow workflow that allows users to reproducibly infer regulatory networks from the thousands of samples in TCGA using a single command. The workflow can be divided into three main steps: multi-omics data, such as RNA-seq and methylation, are downloaded, preprocessed, and lastly used to infer regulatory network models with the netZoo software tools. The workflow is powered by the NetworkDataCompanion R package, a standalone collection of functions for managing, mapping, and filtering TCGA data. Here we show how the pipeline can be used to study the differences between colon cancer subtypes that could be explained by epigenetic mechanisms. Lastly, we provide pre-generated networks for the 10 most common cancer types that can be readily accessed.Conclusionstcga-data-nf is a complete yet flexible and extensible framework that enables the reproducible inference and analysis of cancer regulatory networks, bridging a gap in the current universe of software tools.
PLM-interact: extending protein language models to predict protein-protein interactions
Authors: Liu Dan , Young Francesca , Lamb Kieran D. , Claudio Quiros Adalberto , Pancheva Alexandrina , Miller Crispin , Macdonald Craig , Robertson David L , Yuan Ke 
Published: November 2024

AbstractComputational prediction of protein structure from amino acid sequences alone has been achieved with unprecedented accuracy, yet the prediction of protein-protein interactions (PPIs) remains an outstanding challenge. Here we assess the ability of protein language models (PLMs), routinely applied to protein folding, to be retrained for PPI prediction. Existing PPI prediction models that exploit PLMs use a pre-trained PLM feature set, ignoring that the proteins are physically interacting. Our novel method, PLM-interact, goes beyond a single protein, jointly encoding protein pairs to learn their relationships, analogous to the next-sentence prediction task from natural language processing. This approach provides a significant improvement in performance: Trained on human-human PPIs, PLM-interact predicts mouse, fly, worm,E. coliand yeast PPIs, with 16-28% improvements in AUPR compared with state-of-the-art PPI models. Additionally, it can detect changes that disrupt or cause PPIs and be applied to virus-host PPI prediction. Our work demonstrates that large language models can be extended to learn the intricate relationships among biomolecules from their sequences alone.
Data Resource Profile: Genomic Data in Multiple British Birth Cohorts (1946-2001)—Health, Social, and Environmental Data from Birth to Old Age
Authors: Shireby Gemma , Morris Tim T , Wong Andrew , Chaturvedi Nish , Ploubidis George B , Fitzsimmons Emla , Goodman Alissa , Sanchez-Galvez Adelaida , Davies Neil M , Wright Liam , Bann David 
Published: November 2024

AbstractBirth cohort studies have a rich history of contributing to science across disciplinary fields, notably health and social sciences. Here, we introduce a curated resource comprising genomic data from five British birth cohort studies—longitudinal studies with extensive data collected prospectively across life, each deliberately sampled to be nationally representative (born 1946–2001). These contain health and social data from birth to older age, enabling longitudinal and cross-cohort genetically informed research. The Millennium Cohort Study additionally includes data on parents and offspring, enabling within-family analyses. Across five cohorts born in 1946, 1958, 1970, 1989–90, and 2000–2002, 27,432 participants have harmonized, imputed, and quality-controlled genetic data from genotyping arrays covering 6.7 million common SNPs. The Millennium Cohort Study contains over 6,000 mother-offspring pairs and over 3,000 mother-father-offspring trios. Pseudonymized data are freely available to the global research community upon approval of a data access request (https://cls.ucl.ac.uk/data-access-training).
Optimal strategies for adapting open-source large language models for clinical information extraction: a benchmarking study in the context of ulcerative colitis research
Authors: Yim Richard P. , Silverman Anna L. , Wang Shan , Rudrapatna Vivek A. 
Published: November 2024

AbstractBackgroundClosed-source large language models (LLMs) like GPT-4o have shown promise for clinical information extraction but are potentially limited by cost, data security concerns, and inflexibility. Open-source models have emerged as an attractive alternative, with many LLM adaptation strategies developed in the literature. However, it is currently unclear what adaptation strategies are optimal, and how they ultimately compare to closed-source models.MethodsWe studied the effects of three common LLM adaptation strategies: chain-of-thought prompting, few-shot prompting, and fine-tuning. Our target for information extraction was the Mayo Endoscopic Subscore (MES). We applied those strategies in all combinations to six open-source models (8-70 billion parameters) using an annotated set of colonoscopy procedure reports from two centers: the University of California, San Francisco (N=608) and San Francisco General Hospital (N=217). We analyzed the relationship of these strategies to several performance metrics with a mixed-effects model, accounting for the variability between centers and LLMs. GPT-4o was not subject to QLoRA due to its closed-source nature but was used as a comparator in our benchmarks. We also provide in-depth commentary on the cost-effectiveness of these open-source LLMs and GPT-4o for MES extraction.ResultsAcross adaptation strategies, QLoRA statistically (p< 0.001) improves the performance of open-source LLMs by 8.3-15.6 percentage points across accuracy, precision and recall. However, GPT-4o with prompt engineering is superior to the best open-source model by a margin of 2.5-5.4%. Yet, a simple cost-effectiveness analysis suggests that GPT-4o is expensive compared to open-source models.ConclusionGPT-4o is currently the most performant LLM for MES extraction. If unavailable, open-source models optimized with QLoRA are a competitive alternative. However, our results also suggest that current instruction-following LLMs including GPT-4o do not fully follow user-provided instructions, leaving room for improvement. More work is needed to achieve consistent, near-perfect performance in clinical information extraction by LLMs.Brief DescriptionIn this study, we compare interactions of finetuning, chain-of-thought prompting, and few-shot prompting on open-source models to extract useful information from clinical notes. We conclude that QLoRA results in statistically and practically significant performance gains across several metrics while other strategies and their combinations have little impact.
Position Paper On Diagnostic Uncertainty Estimation from Large Language Models: Next-Word Probability Is Not Pre-test Probability
Authors: Gao Yanjun , Myers Skatje , Chen Shan , Dligach Dmitriy , Miller Timothy A , Bitterman Danielle , Chen Guanhua , Mayampurath Anoop , Churpek Matthew , Afshar Majid 
Published: November 2024

AbstractLarge language models (LLMs) are being explored for diagnostic decision support, yet their ability to estimate pre-test probabilities, vital for clinical decision-making, remains limited. This study evaluates two LLMs, Mistral-7B and Llama3-70B, using structured electronic health record data on three diagnosis tasks. We examined three current methods of extracting LLM probability estimations and revealed their limitations. We aim to highlight the need for improved techniques in LLM confidence estimation.
Differential KEAP1/NRF2 mediated signaling widens the therapeutic window of redox-targeting drugs in SCLC therapy
Authors: Samarin Jana , Nuskova Hana , Fabrowski Piotr , Malz Mona , Amtmann Eberhard , Taeubert Minerva J. , Pastor-Flores Daniel , Kazdal Daniel , Kurilov Roman , de Vries Nicole , Pink Hannelore , Deis Franziska , Hummel-Eisenbeiss Johanna , Kaushal Kamini , Dick Tobias P. , Hamilton Gerhard , Muckenthaler Martina , Mall Moritz , Lim Bryce , Kanamaru Taishi , Klinke Glynis , Sos Martin , Frede Julia , Miller Aubry K. , Alborzinia Hamed , Gunkel Nikolas 
Published: November 2024

AbstractSmall cell lung cancer (SCLC) patients frequently experience a remarkable response to first-line therapy. Follow up maintenance treatments aim to control residual tumor cells, but generally fail due to cross-resistance, inefficient targeting of tumor vulnerabilities, or dose-limiting toxicity, resulting in relapse and disease progression. Here, we show that SCLC cells, similar to their cells of origin, pulmonary neuroendocrine cells (PNECs), exhibit low activity in pathways protecting against reactive oxygen species (ROS). When exposed to a novel thioredoxin reductase 1 (TXNRD1) inhibitor, these cells quickly exhaust their ROS-scavenging capacity, regardless of their molecular subtype or resistance to first-line therapy. Importantly, unlike non-cancerous cells, SCLC cells cannot adapt to drug-induced ROS stress due to the suppression of ROS defense mechanisms by multiple layers of epigenetic and transcriptional regulation. By exploiting this difference in oxidative stress management, we safely increased the therapeutic dose of TXNRD1 inhibitorsin vivoby pharmacological activation of the NRF2 stress response pathway. This resulted in improved tumor control without added toxicity to healthy tissues. These findings underscore the therapeutic potential of TXNRD1 inhibitors for maintenance therapy in SCLC.Graphical summaryPharmacological induction of NRF2 leads to differential cyto-protection against TXNRD1 inhibitors in normal tissue but not in SCLC tumor cells. This results in a reduction of adverse effects, allowing to increase the therapeutic dose.
The conserved HIV-1 spacer peptide 2 triggers matrix lattice maturation
Authors: Stacey James C. V. , Hrebík Dominik , Nand Elizabeth , Shetty Snehith Dyavari , Qu Kun , Boicu Marius , Anders-Össwein Maria , Dick Robert A. , Mothes Walther , Kräusslich Hans-Georg , Müller Barbara , Briggs John A. G. 
Published: November 2024

AbstractHIV-1 particles are released in an immature, non-infectious form. Proteolytic cleavage of the main structural polyprotein Gag into functional domains induces rearrangement into mature, infectious virions. In immature virus particles, the Gag membrane binding domain, MA, forms a hexameric protein lattice that undergoes structural transition upon cleavage into a distinct, mature MA lattice. The mechanism of MA lattice maturation is unknown. Here we show that released spacer peptide 2 (SP2), a conserved peptide of unknown function situated ∼300 residues downstream of MA, binds MA to induce structural maturation. By high-resolution in-virus structure determination of MA, we show that MA does not bind lipid into a side pocket as previously thought, but instead binds SP2 as an integral part of the protein-protein interfaces that stabilise the mature lattice. Analysis of Gag cleavage site mutants showed that SP2 release is required for MA maturation, and we demonstrate that SP2 is sufficient to induce maturation of purified MA on lipid layers in vitro. SP2-triggered MA maturation correlated with faster fusion of virus with target cells. Our results reveal a new, unexpected interaction between two HIV-1 components, provide a high-resolution structure of mature MA, establish the trigger of MA structural maturation, and assign function to the SP2 peptide.
The AMD-associated genetic polymorphism CFH Y402H confers vulnerability to Hydroquinone-induced stress in iPSC-RPE cells
Authors: Armento Angela , Sonntag Inga , Almansa-Garcia Ana-Cristina , Sen Merve , Bolz Sylvia , Arango-Gonzalez Blanca , Kilger Ellen , Sharma Ruchi , Bharti Kapil , Fernandez-Godino Rosario , de la Cerda Berta , Clark Simon J , Ueffing Marius 
Published: November 2024

AbstractAge-related macular degeneration (AMD), a degenerative disease of the macula, is caused by an interplay of diverse risk factors (genetic predisposition, age and lifestyle habits). One of the main genetic risks includes the Y402H polymorphism in complement Factor H (FH), an inhibitor of complement system activation. There has been, and continues to be, much discussion around the functional consequences of this Y402H polymorphism, whether the soluble FH protein confers its risk association, or if the cells expressing the protein themselves are affected by the genetic alteration. In our study, we examined the cell characteristics of the retinal pigment epithelium (RPE) cells, which play a major role in retinal homeostasis and stability and which are synonymously linked to AMD.Here, we employ RPE cells derived from induced pluripotent stem cells (iPSC) generated from donors, carrying either homozygous 402Y (low risk) or 402H (high risk) variants of theCFHgene. RPE cells were treated with Hydroquinone (HQ), a component of cigarette smoke, to induce oxidative damage. Intriguingly, RPE cells carrying high genetic risk proved more vulnerable to oxidative insult when exposed to HQ, as demonstrated by increased cytotoxicity, caspase activation, compared to the low-risk RPE cells.The exposure of RPE cells to RPE conditioned medium, normal human serum (NHS) and inactivated NHS (iNHS) had minimal impact on cell cytotoxicity and caspase activation, nor did the presence of purified soluble FH rescue the observed effects. This suggests that the degree of cellular susceptibility to oxidative stress is not conferred by soluble FH protein and other complement sources, but intercellularly because of the corresponding genetic risk predisposition. Considering the known connection of oxidative stress to proteotoxic stress and degrading processes, we investigated the unfolded protein response (UPR) and autophagy. When exposed to HQ, RPE cells showed an increase in autophagy markers, however iPSC-RPE cells carrying high genetic risk showed an overall reduced autophagic flux. Our data support the hypothesis that RPE cells carrying high genetic risk are less resilient to oxidative stress.