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SSRN 2025年

作者： Liu, Tianyu Zhang, Xiangyu Ying, Rex Zhao, Hongyu Interdepartmental Program in Computational Biology & Bioinformatics Yale University New HavenCT06511 United States Department of Biostatistics Yale University New HavenCT06511 United States Department of Computer Science Yale University New HavenCT06511 United States

Sequence-to-function models can predict gene expression from sequence data and be used to link genetic information with transcriptomics data to understand regulatory processes and their effects on complex phenotypes. The genomic language models are pre-trained with large-scale DNA sequences and can generate robust representations of these sequences by learning the genomic context. However, few studies can estimate the predictability of gene expression levels and bridge these two classes of models together to explore individualized gene expression prediction. In this manuscript, we propose UKBioBERT as a DNA language model pre-trained with genetic variants from UK BioBank. We demonstrate that UKBioBERT generates informative embeddings capable of identifying gene functions, and improving gene expression prediction in cell lines, thereby enhancing our understanding of gene expression predictability. Building upon these embeddings, we combine UKBioBERT with state-of-the-art sequence-to-function architectures, Enformer and Borzoi, to create UKBioFormer and UKBioZoi. These models exhibit better performance in predicting highly predictable gene expression levels and can be generalized across different cohorts. Furthermore, UKBioFormer effectively captures the relationship between genetic variants and expression variations, enabling in-silico mutation analyses. Collectively, our findings underscore the value of integrating genomic language models and sequence-to-function approaches for advancing functional genomics research. © 2025, The Authors. All rights reserved.

关键词： Genome

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Catalysis-Induced Highly-Stable Interface on Porous Silicon for High-Rate Lithium-Ion Batteries

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Nano-Micro Letters 2025年第8期17卷 548-563页

作者： Zhuobin Han Phornphimon Maitarad Nuttapon Yodsin Baogang Zhao Haoyu Ma Kexin Liu Yongfeng Hu Siriporn Jungsuttiwong Yumei Wang Li Lu Liyi Shi Shuai Yuan Yongyao Xia Yingying Lv Research Centre of Nanoscience and Nanotechnology Shanghai UniversityShanghai 200444People’s Republic of China Department of Chemistry Faculty of ScienceSilpakorn UniversityNakhon Pathom 73000Thailand Sinopec Shanghai Research Institute of Petrochemical Technology Co. Ltd.Shanghai 201208People’s Republic of China Department of Chemistry and Center of Excellence for Innovation in Chemistry Faculty of Science Ubon Ratchathani UniversityUbon Ratchathani 34190Thailand National University of Singapore(Chongqing)Research Institute Chongqing 401123People’s Republic of China Department of Chemistry Fudan UniversityShanghai 200433People’s Republic of China Emerging Industries Institute Shanghai University Jiaxing 314006ZhejiangPeople’s Republic of China Program in Bioinformatics and Computational Biology Graduate SchoolChulalongkorn UniversityBangkok 10330Thailand

Silicon stands as a key anode material in lithium-ion battery ascribing to its high energy ***,the poor rate performance and limited cycling life remain unresolved through conventional approaches that involve carbon composites or nanostructures,primarily due to the un-controllable effects arising from the substantial formation of a solid electrolyte interphase(SEI)during the ***,an ultra-thin and homogeneous Ti doping alumina oxide catalytic interface is meticulously applied on the porous Si through a synergistic etching and hydrolysis *** defect-rich oxide interface promotes a selective adsorption of fluoroethylene carbonate,leading to a catalytic reaction that can be aptly described as“molecular concentration-in situ conversion”.The resultant inorganic-rich SEI layer is electrochemical stable and favors ion-transport,particularly at high-rate cycling and high *** robustly shielded porous Si,with a large surface area,achieves a high initial Coulombic efficiency of 84.7%and delivers exceptional high-rate performance at 25 A g^(−1)(692 mAh g^(−1))and a high Coulombic efficiency of 99.7%over 1000 *** robust SEI constructed through a precious catalytic layer promises significant advantages for the fast development of silicon-based anode in fast-charging batteries.

关键词： Catalytic interface Mesoporous Inorganic-rich SEI Silicon anode Lithium-ion batteries

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OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

Advanced Intelligent Systems

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Advanced Intelligent Systems 2025年第3期7卷

作者： Chen, Po-Yuan Ko, Tai-Ming Institute of Bioinformatics and Systems Biology College of Engineering Bioscience National Yang Ming Chiao Tung University Hsinchu300 Taiwan Bioinformatics Program Institute of Statistical Science Taiwan International Graduate Program Academia Sinica Taipei115 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei115 Taiwan Institute of Statistical Science Academia Sinica Taipei115 Taiwan Department of Biological Science and Technology College of Engineering Bioscience National Yang Ming Chiao Tung University Hsinchu300 Taiwan National Yang Ming Chiao Tung University Hsinchu300 Taiwan School of Pharmacy College of Pharmacy Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung807 Taiwan

Oxidative stress, characterized by an imbalance between reactive oxygen species (ROS) and antioxidants, plays a pivotal role in inflammatory responses associated with both chronic diseases and acute injuries. In this study, OXidative Stress PREDictor (OxSpred), a supervised learning model tailored to accurately annotate the oxidative stress state of innate immune cells at the single-cell level, is introduced. Compared to the traditional gene-set-variation-analysis-based enrichment method, OxSpred demonstrates superior accuracy with an area under the receiver operating characteristic curve of 0.89 and offers interpretable embeddings with significant biological relevance. Using the predicted ROS states, precise elucidation and interpretation of the roles of novel innate immune cell subtypes can be achieved. Overall, OxSpred enhances the utility of single-cell transcriptomic datasets by providing a robust in silico method for determining intracellular oxidative stress states, thereby enriching the understanding of innate immune cell functions during inflammation. © 2024 The Author(s). Advanced Intelligent Systems published by Wiley-VCH GmbH.

关键词： Cells

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AlphaFold Protein Structure Database and 3D-Beacons: New Data and Capabilities

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Journal of Molecular Biology 2025年 168967页

作者： Fleming, Jennifer Magana, Paulyna Nair, Sreenath Tsenkov, Maxim Bertoni, Damian Pidruchna, Ivanna Lima Afonso, Marcelo Querino Midlik, Adam Paramval, Urmila Žídek, Augustin Laydon, Agata Kovalevskiy, Oleg Pan, Joshua Cheng, Jun Avsec, Žiga Bycroft, Clare Wong, Lai Hong Last, Meera Mirdita, Milot Steinegger, Martin Kohli, Pushmeet Váradi, Mihály Velankar, Sameer European Molecular Biology Laboratory European Bioinformatics Institute Hinxton United Kingdom Google DeepMind London United Kingdom School of Biological Sciences Seoul National University Seoul 08826 Cuba Interdisciplinary Program in Bioinformatics Seoul National University Seoul 08826 Cuba Institute of Molecular Biology and Genetics Seoul 08826 Cuba Artificial Intelligence Institute Seoul National University Seoul 08826 Cuba

The AlphaFold Protein Structure Database (https://***/) has made significant strides in enhancing its utility and accessibility for the life science research community. The recent integration of AlphaMissense predictions enables access to the pathogenicity of human protein missense variants, with an innovative and interactive heatmap and 3D visualisation that display variant data at the residue level. Users can now toggle between structure model quality (pLDDT) and average pathogenicity scores, providing insights into the implications of specific residue changes. The Foldseek integration offers a rapid and accurate method for protein structure searches and comparisons. Bulk data download options further facilitate comprehensive data analysis and integration with other computational tools. The 3D-Beacons framework (https://***/pdbe/pdbe-kb/3dbeacons/) has also been enhanced with detailed annotation endpoints (such as AlphaMissense data) and integrates LevyLab's dataset of homomeric AlphaFold 2 models. These advancements significantly improve the functionality and accessibility of these resources, enabling discoveries using structure data. © 2025 The Author(s)

关键词： AlphaFold Alphamissense Annotations Foldseek Training

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Impact of substance use disorders on critical care management and health outcomes in septic adolescents

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Annals of Intensive Care 2025年第1期15卷 1-9页

作者： Markus, Havell Ceneviva, Gary D. Thomas, Neal J. Krawiec, Conrad Pennsylvania State University College of Medicine P.O. Box 850 500 University Drive Hershey 17033-0850 PA United States Program in Bioinformatics and Genomics Pennsylvania State University Huck Life Sciences Building University Park 16802 PA United States Medical Scientist Training Program Pennsylvania State University College of Medicine 500 University Drive Hershey 17033 PA United States Pediatric Critical Care Medicine Department of Pediatrics Penn State Hershey Children’s Hospital P.O. Box 850 500 University Drive Hershey 17033-0850 PA United States Department of Public Health Sciences Pennsylvania State University College of Medicine 500 University Drive Hershey 17033-0850 PA United States

Background: Adult septic patients with substance abuse disorder (SUD) are at increased risk of poor outcomes, but the impact on adolescents is unknown. We aimed to determine if pre-existing SUD is associated with increased adverse outcomes and critical care resources in critically ill adolescents hospitalized with sepsis. We hypothesize that SUD is associated with increased risk of adverse outcomes and usage of critical care resources in this adolescent patient population. Methods: This was a retrospective cohort study utilizing the TriNetX© electronic health record (EHR) database, which consists of EHR from participating healthcare organizations predominantly in the United States. Critically ill adolescents with sepsis aged 12–21 years were divided into two groups (SUD history and no-SUD history). Data related to demographics, diagnostic, procedural, and medication codes were analyzed. The primary outcomes were organ dysfunction, critical care therapies, and all-cause 1-year mortality. Results: We included 5,436 critically ill adolescents with sepsis [730 (13.43%) SUD history and 4706 (86.57%) no-SUD history]. SUD history was associated with increased odds of organ dysfunction (adjusted odds ratio [aOR] 1.84;95% confidence interval [CI] 1.56–2.16;p < 0.001), vasoactive/inotropic drug usage (aOR 1.29;95% CI 1.10–1.52;p = 0.002), mechanical ventilation (aOR 2.19;95% CI 1.85–2.59;p < 0.001), but not mortality (aOR 1.03;95% CI 0.76–1.41;p = 0.83). Conclusions: Our retrospective analysis suggests history of SUD in critically ill septic adolescent patients is associated with increased utilization of critical care resources and organ dysfunction. Further study is needed to determine if substance abuse represents a potentially modifiable risk factor for critical illness in adolescent patients. © The Author(s) 2025.

关键词： Adolescent Critical care Electronic health records Substance use disorders Young adult

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U1 snRNP regulates alternative promoter activity by inhibiting premature polyadenylation

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Molecular Cell 2025年第10期85卷 1968-1981.e7页

作者： Kim, GyeungYun Carroll, Christine L. Wakefield, Zachary Peters Tuncay, Mustafa Fiszbein, Ana Biology Department Boston University Boston 02215 United States Graduate Program in Molecular Biology Cell Biology & Biochemistry Boston University Boston 02215 United States Graduate Program in Cell and Molecular Biology Boston University Boston 02215 United States Bioinformatics Program Faculty of Computing and Data Science Boston University Boston 02215 United States Center for Computing & Data Sciences Boston University Boston 02215 United States

Emerging evidence indicates that splicing factors mediate the close link between transcription and splicing. However, the mechanisms underlying this coupling remain unclear. U1 small nuclear ribonucleoprotein particle (U1 snRNP) not only initiates splicing but also plays a crucial role in preventing premature cleavage and polyadenylation, facilitating long-distance transcriptional elongation. Here, we show that U1 snRNP regulates alternative promoter activity in human cells by inhibiting premature polyadenylation. In genes carrying premature polyadenylation sites between two promoters, U1 snRNP inhibition with antisense oligonucleotides leads to a significant decrease in downstream promoter activity. Conversely, restoring U1 snRNP activity or inhibiting premature polyadenylation rescues downstream promoter activity. Mechanistically, U1 snRNP inhibition correlates with reduced chromatin accessibility, decreased RNA polymerase II serine 5 phosphorylation, and increased promoter-proximal pause at downstream promoters. Our findings support a model in which U1 snRNP favors productive elongation from upstream promoters, triggering downstream promoter activation by destabilizing nucleosomes and promoting promoter escape. © 2025 The Author(s)

关键词： alternative promoters dowsntream promoters promoter-proximal pause splicing factors splicing transcription transcription cooperativity transcription initiation transcription interfierence transcription start sites U1 snRNP

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Protein subcellular localization prediction of eukaryotes using a knowledge-based approach

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BMC bioinformatics 2009年第SUPPL. 15期10卷 1-13页

作者： Lin, Hsin-Nan Chen, Ching-Tai Sung, Ting-Yi Ho, Shinn-Ying Hsu, Wen-Lian Bioinformatics Program Taiwan International Graduate Program Academia Sinica Taipei Taiwan Bioinformatics Lab. Institute of Information Science Academia Sinica Taipei Taiwan Institute of Bioinformatics National Chiao Tung University Hsinchu Taiwan

Background: The study of protein subcellular localization (PSL) is important for elucidating protein functions involved in various cellular processes. However, determining the localization sites of a protein through wet-lab experiments can be time-consuming and labor-intensive. Thus, computational approaches become highly desirable. Most of the PSL prediction systems are established for single-localized proteins. However, a significant number of eukaryotic proteins are known to be localized into multiple subcellular organelles. Many studies have shown that proteins may simultaneously locate or move between different cellular compartments and be involved in different biological processes with different roles. Results: In this study, we propose a knowledge based method, called KnowPredsite, to predict the localization site(s) of both single-localized and multi-localized proteins. Based on the local similarity, we can identify the "related sequences" for prediction. We construct a knowledge base to record the possible sequence variations for protein sequences. When predicting the localization annotation of a query protein, we search against the knowledge base and used a scoring mechanism to determine the predicted sites. We downloaded the dataset from ngLOC, which consisted of ten distinct subcellular organelles from 1923 species, and performed ten-fold cross validation experiments to evaluate KnowPredsite's performance. The experiment results show that KnowPredsite achieves higher prediction accuracy than ngLOC and Blast-hit method. For single-localized proteins, the overall accuracy of KnowPredsite is 91.7%. For multi-localized proteins, the overall accuracy of KnowPredsite is 72.1%, which is significantly higher than that of ngLOC by 12.4%. Notably, half of the proteins in the dataset that cannot find any Blast hit sequence above a specified threshold can still be correctly predicted by KnowPredsite. Conclusion: KnowPredsite demonstrates the power of identifying rel

关键词： Proteins

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Correction: Diversity of sulfur cycling halophiles within the Salton Sea, California's largest lake

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BMC microbiology 2025年第1期25卷 225页

作者： Linton Freund Caroline Hung Talyssa M Topacio Charles Diamond Alyson Fresquez Timothy W Lyons Emma L Aronson Genetics Genomics and Bioinformatics Program University of California Riverside 900 University Ave Riverside CA 92521 USA. lintonfreund@***. Department of Microbiology and Plant Pathology University of California Riverside 900 University Ave Riverside CA 92521 USA. Department of Earth and Planetary Sciences University of California Riverside 900 University Ave Riverside CA 92521 USA.

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Juntas Contra el Virus del Papiloma Humano: protocol for a pilot randomized controlled trial of an HPV self-sampling intervention for underscreened Latinas

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Pilot and feasibility studies 2025年第1期11卷 65页

作者： Carolyn Y Fang Marisol Cora-Cruz Pratistha Koirala Sophia Perez Minzi Li Brian L Egleston Yuku Chen Gina Mantia-Smaldone Omar Martinez Cancer Prevention and Control Program Fox Chase Cancer Center 333 Cottman Ave. Philadelphia PA 19111 USA. carolyn.fang@fccc.edu. Cancer Prevention and Control Program Fox Chase Cancer Center 333 Cottman Ave. Philadelphia PA 19111 USA. Department of Gynecologic Oncology Fox Chase Cancer Center Philadelphia PA USA. Biostatistics and Bioinformatics Facility Fox Chase Cancer Center Philadelphia PA USA. College of Medicine University of Central Florida Orlando FL USA.

BACKGROUND:Rates of cervical cancer incidence and mortality are persistently higher among Latina women in the continental United States (US) and women in Puerto Rico (a US territory) compared with non-Hispanic White (NHW) women. Multiple factors contribute to low participation in cancer screening, including structural barriers (e.g., low access to healthcare services, racism/discrimination, lack of culturally and linguistically adequate information), cultural concerns, and low perceived risk and awareness of cervical cancer. Although community-based education and navigation support can be effective in overcoming some barriers to screening, structural barriers and limited access remain formidable challenges to overcome. Emerging technologies supporting self-sampling for high-risk human papillomavirus (HPV) testing may offer a valuable evidence-based strategy for empowering Latina women to engage in cervical cancer screening. Thus, the objective of this study is to assess the feasibility and acceptability of a novel HPV self-sampling intervention for underscreened Latina women. METHODS:The study will be a randomized controlled feasibility trial involving 100 Latina women who have not received cervical cancer screening within the recommended guidelines. Participants will be randomly assigned to the intervention condition, which includes a synchronous three-session group cervical cancer educational program delivered virtually along with a mailed HPV self-sampling kit (to obtain self-collected cervical samples for HPV testing), or to a comparison condition that involves receipt of the mailed HPV self-sampling kit with written information about cervical cancer screening and nearby clinics. Study assessments will be obtained at baseline (i.e., study entry) and 1-month post-program. The primary outcome of feasibility will be measured through study enrollment and intervention completion. In addition, acceptability of study materials and the self-sampling procedures will be a

关键词： Cervical cancer Human papillomavirus (HPV) Latinas Screening Self-sampling

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consexpressionR: an R package for consensus differential gene expression analysis

arXiv

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arXiv 2025年

作者： Costa-Silva, Juliana Menotti, David Lopes, Fabricio M. Department of Informatics Federal University of Paraná Rua Coronel Francisco Heráclito dos Santos 100 Paraná81531-990 Brazil Department of Computer Science Bioinformatics Graduate Program Federal University of Technology - Paraná Av. Alberto Carazzai 1640 - Cornélio Procópio ParanáPostal code: 86300-000 Brazil

Motivation: Bulk RNA-Seq is a widely used method for studying gene expression across a variety of contexts. The significance of RNA-Seq studies has grown with the advent of high-throughput sequencing technologies. Computational methods have been developed for each stage of the identification of differentially expressed genes. Nevertheless, there are few studies exploring the association between different types of methods. In this study, we evaluated the impact of the association of methodologies in the results of differential expression analysis. By adopting two data sets with qPCR data (to gold-standard reference), seven methods were implemented and assessed in R packages (EBSeq, edgeR, DESeq2, limma, SAMseq, NOISeq, and Knowseq), which was performed and assessed separately and in association. The results were evaluated considering the adopted qPCR data. Results: Here, we introduce consexpressionR, an R package that automates differential expression analysis using consensus of at least seven methodologies, producing more assertive results with a significant reduction in false positives. Availability: consexpressionR is an R package available via Source code and support are available at GitHub (https://***/costasilvati/consexpressionR). © 2025, CC BY-NC-ND.

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