检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Vašíček, Jakub Skiadopoulou, Dafni Kuznetsova, Ksenia G. Käll, Lukas Vaudel, Marc Bruckner, Stefan Mohn Center for Diabetes Precision Medicine Department of Clinical Science University of Bergen Bergen Norway Computational Biology Unit Department of Informatics University of Bergen Bergen Norway Metabolism Program Broad Institute of MIT and Harvard CambridgeMA United States Science for Life Laboratory Department of Gene Technology KTH - Royal Institute of Technology Stockholm Sweden Department of Genetics and Bioinformatics Health Data and Digitalization Norwegian Institute of Public Health Oslo Norway Institute for Visual and Analytic Computing University of Rostock Rostock Germany

In mass spectrometry-based proteomics, experts usually project data onto a single set of reference sequences, overlooking the influence of common haplotypes (combinations of genetic variants inherited together from a parent). We recently introduced ProHap, a tool for generating customized protein haplotype databases. Here, we present ProHap Explorer, a visualization interface designed to investigate the influence of common haplotypes on the human proteome. It enables users to explore haplotypes, their effects on protein sequences, and the identification of non-canonical peptides in public mass spectrometry datasets. The design builds on well-established representations in biological sequence analysis, ensuring familiarity for domain experts while integrating novel interactive elements tailored to proteogenomic data exploration. User interviews with proteomics experts confirmed the tool's utility, highlighting its ability to reveal whether haplotypes affect proteins of interest. By facilitating the intuitive exploration of proteogenomic variation, ProHap Explorer supports research in personalized medicine and the development of targeted therapies. © 2025, CC BY.

关键词： Proteomics

来源：评论

学校读者我要写书评

暂无评论

Insights into the binding interactions of Macitentan to bovine serum Albumin: A Spectroscopic, electrochemical and computational study

引用

Journal of Molecular Liquids 2025年 429卷

作者： Sadak, Selenay Dindar, Çiğdem Kanbeş Kabir, Md.Zahirul Rehman, Fazal Mohamad, Saharuddin B. Yildirim, Sercan Uslu, Bengi Ankara University Faculty of Pharmacy Department of Analytical Chemistry Ankara06560 Turkey Ankara University The Graduate School of Health Sciences Ankara06110 Turkey Biochemistry Program Institute of Biological Sciences Faculty of Science University Malaya Kuala Lumpur Malaysia Faculty of Science Bioinformatics Programme Institute of Biological Sciences Malaysia Centre of Research for Computational Sciences and Informatics for Biology Bioindustry Environment Agriculture and Healthcare University of Malaya Kuala Lumpur Malaysia Karadeniz Technical University Faculty of Pharmacy Department of Analytical Chemistry Trabzon Turkey

Macitentan (MACI) is an endothelial receptor antagonist used to treat pulmonary arterial hypertension (PAH). The pharmacokinetics and therapeutic efficacy of MACI are significantly influenced by its interaction with plasma proteins, especially bovine serum albumin (BSA). In this study, spectroscopic (fluorescence and UV–visible absorption spectroscopy), electrochemical, and computational techniques were applied to explore the binding properties and interaction mechanisms between MACI and BSA. The results indicated that the MACI quenched BSA fluorescence through a static mechanism. The interaction possessed a moderate binding affinity with Ka values ranging from 1.27 × 104 to 7.25 × 104 M−1 at different temperatures. Hydrophobic forces and hydrogen bonds were identified as critical factors in stabilizing the complex based on thermodynamic parameters. The local environment of tryptophan residues in BSA was found to be altered following the addition of MACI, as revealed by synchronous and three-dimensional fluorescence spectra. The spectroscopic studies were supported by electrochemical analyses, which indicated the formation of an electro-inactive complex between MACI and BSA. From the molecular docking experiments, the most likely binding site for MACI was found to be site I of BSA. Several hydrogen bonds and hydrophobic contacts were observed during the interaction of MACI with site I of BSA. These findings provided detailed insight to understand the binding properties of MACI to BSA, which may be beneficial for medical and pharmaceutical applications in the future. © 2025 Elsevier B.V.

关键词： Hydrogen bonds

来源：评论

学校读者我要写书评

暂无评论

Characterizing Emergency Department Care for Patients With Histories of Incarceration

引用

JACEP Open 2025年第1期6卷 100022-100022页

作者： Huang, Thomas Socrates, Vimig Ovchinnikova, Polina Faustino, Isaac Kumar, Anusha Safranek, Conrad Chi, Ling Wang, Emily A. Puglisi, Lisa Wong, Ambrose H. Wang, Karen H. Taylor, R. Andrew Department of Emergency Medicine Yale School of Medicine New Haven CT United States Department for Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States SEICHE Center for Health and Justice Yale School of Medicine New Haven CT United States Equity Research and Innovation Center Yale School of Medicine Yale University New Haven CT United States

Objectives: Patients with a history of incarceration experience bias from health care team members, barriers to privacy, and a multitude of health care disparities. We aimed to assess care processes delivered in emergency departments (EDs) for people with histories of incarceration. Methods: We utilized a fine-tuned large language model to identify patient incarceration status from 480,374 notes from the ED setting. We compared socio-demographic characteristics, comorbidities, and care processes, including disposition, restraint use, and sedation, between individuals with and without a history of incarceration. We then conducted multivariable logistic regression to assess the independent correlation of incarceration history and management in the ED while adjusting for demographic characteristics, health behaviors, presentation, and past medical history. Results: We found 1734 unique patient encounters with a history of incarceration from a total of 177,987 encounters. Patients with history of incarceration were more likely to be male, Black, Hispanic, or other race/ethnicity, currently unemployed or disabled, and had smoking and substance use histories, compared with those without. This cohort demonstrated higher odds of elopement (OR: 3.59 [95% CI: 2.41–5.12]), leaving against medical advice (OR: 2.39 [95% CI: 1.46–3.67]), and being subjected to sedation (OR: 3.89 [95% CI: 3.19–4.70]) and restraint use (OR: 3.76 [95% CI: 3.06–4.57]). After adjusting for covariates, the association between incarceration and elopement remained significant (adjusted odds ratio: 1.65 [95% CI: 1.08–2.43]), while associations with other dispositions, restraint use, and sedation did not persist. Conclusion: This study identified differences in patient characteristics and care processes in the ED for patients with histories of incarceration and demonstrated the potential of using natural language processing in measuring care processes in populations that are largely hidden, but highly prev

关键词： artificial intelligence emergency medicine incarceration large language models quality of health care

来源：评论

学校读者我要写书评

暂无评论

The ESCRT protein CHMP5 promotes T cell leukemia by enabling BRD4-p300-dependent transcription

引用

Nature Communications 2025年第1期16卷 1-19页

作者： Umphred-Wilson, Katharine Ratnayake, Shashikala Tang, Qianzi Wang, Rui Chaudhary, Sneha Ghosh Ballachanda, Devaiah N. Trichka, Josephine Wisniewski, Jan Zhou, Lan Chen, Qingrong Meerzaman, Daoud Singer, Dinah S. Adoro, Stanley Experimental Immunology Branch National Cancer Institute National Institutes of Health Bethesda 20892 MD United States Immunology Training Program Department of Pathology Case Western Reserve University School of Medicine Cleveland 44106 OH United States Computational Genomics and Bioinformatics Branch Center for Biomedical Informatics & Information Technology National Cancer Institute National Institutes of Health Bethesda 20850 MD United States College of Animal Science and Technology Sichuan Agricultural University Chengdu 611130 China Department of Pathology and Genomic Medicine Houston Methodist Hospital Houston 77030 TX United States

Addiction to oncogene-rewired transcriptional networks is a therapeutic vulnerability in cancer cells, underscoring a need to better understand mechanisms that relay oncogene signals to the transcriptional machinery. Here, using human and mouse T cell acute lymphoblastic leukemia (T-ALL) models, we identify an essential requirement for the endosomal sorting complex required for transport protein CHMP5 in T-ALL epigenetic and transcriptional programming. CHMP5 is highly expressed in T-ALL cells where it mediates recruitment of the coactivator BRD4 and the histone acetyl transferase p300 to enhancers and super-enhancers that enable transcription of T-ALL genes. Consequently, CHMP5 depletion causes severe downregulation of critical T-ALL genes, mitigates chemoresistance and impairs T-ALL initiation by oncogenic NOTCH1 in vivo. Altogether, our findings uncover a non-oncogene dependency on CHMP5 that enables T-ALL initiation and maintenance. © This is a U.S. Government work and not under copyright protection in the US;foreign copyright protection may apply 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

iSNP: An integrated, automatically updated SNP database

iSNP: An integrated, automatically updated SNP database

引用

2012 7th International Symposium on health informatics and bioinformatics, HIBIT 2012

作者： Çarkacioǧlu, Levent Gedikoǧlu, Ceyhun Son, Yeşim Aydin Bioinformatics Graduate Program Middle East Technical University 06800 Ankara Turkey Health Informatics Department Middle East Technical University 06800 Ankara Turkey

ISBN: (纸本)9781467308786

Single Nucleotide Polymorphisms (SNP) is a DNA sequence variation that occurs when a single nucleotide differs between members of a biological species or paired chromosomes in an individual. Studies on SNP data are important for scientists to shed light on identifying genetic variations underlying complex diseases. While recent advances in high-throughput genotyping technologies are resulting in data accumulation at large scales, the need for collection and service of this data under a standard format and globally normalized and structured metadata that houses the structured SNP data is becoming essential. Here, we present iSNP that is a regularly updated, machine curated database that holds SNP and its associated metadata from publicly available databases under a structured standard format that can be efficiently utilized within different applications. © 2012 IEEE.

关键词： Metadata

来源：评论

学校读者我要写书评

暂无评论

GWAS with AHP based SNP prioritization approach to identify SNP biomarkers for Alzheimer's disease

GWAS with AHP based SNP prioritization approach to identify ...

引用

2012 7th International Symposium on health informatics and bioinformatics, HIBIT 2012

作者： Kadioǧlu, Onat Üstünkar, Gürkan Son, Yeşim Aydin Middle East Technical University Bioinformatics Graduate Program Ankara Turkey Middle East Technical University Informatics Institute Department of Information Science Ankara Turkey Middle East Technical University Informatics Institute Department of Health Informatics Ankara Turkey

ISBN: (纸本)9781467308786

Genome wide association studies (GWAS) aim to identify genomic variance associated with certain disease conditions. Major bottleneck of standard GWAS approaches are the prioritization and subset selection after the statistically significant SNPs are determined. Our group has recently developed an analysis pipeline, where p-value and combined p value statistics are integrated with the novel AHP based SNP prioritization algorithm for the detailed analysis of associated SNPs considering statistical significance and biological relevance. Following this pipeline, we have done the GWAS of Alzheimer's Disease (AD) on ADNI SNP genotyping data set where 148 AD cases and 182 controls are investigated. Among the top 100 SNPs 18 of them mapped to AD linked genes. Additionally further analysis of the gene and pathway results suggested new associations, providing basis for new hypothesis for the AD Biomarker research. © 2012 IEEE.

关键词： Genes

来源：评论

学校读者我要写书评

暂无评论

Machine Learning and Deep Learning Techniques for Prediction and Diagnosis of Leptospirosis: Systematic Literature Review

引用

JMIR Medical informatics 2025年 13卷

作者： Suhila Sawesi Arya Jadhav Bushra Rashrash Health Informatics and Bioinformatics Program College Of Computing Grand Valley State University 333 Michigan St. NE Grand Rapids MI United States Data Science College Of Computing Grand Valley State University Allendale MI United States Department of Biomedical Science College of Liberal Arts and Sciences Grand Valley State University Allendale MI United States

Background Leptospirosis, a zoonotic disease caused by Leptospira bacteria, continues to pose significant public health risks, particularly in tropical and subtropical regions. Objective This systematic review aimed to evaluate the application of machine learning (ML) and deep learning (DL) techniques in predicting and diagnosing leptospirosis, focusing on the most used algorithms, validation methods, data types, and performance metrics. Methods Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS), and Prediction model Risk of Bias Assessment Tool (PROBAST) tools, we conducted a comprehensive review of studies applying ML and DL models for leptospirosis detection and prediction, examining algorithm performance, data sources, and validation approaches. Results Out of a total of 374 articles screened, 17 studies were included in the qualitative synthesis, representing approximately 4.5% of the initial pool. The review identified frequent use of algorithms such as support vector machines, artificial neural networks, decision trees, and convolutional neural networks (CNNs). Among the included studies, 88% (15/17) used traditional ML methods, and 24% (4/17) used DL techniques. Several models demonstrated high predictive performance, with reported accuracy rates ranging from 80% to 98%, notably with the U-Net CNN achieving 98.02% accuracy. However, public datasets were underused, with only 35% (6/17) of studies incorporating publicly available data sources; the majority (65%, 11/17) relied primarily on private datasets from hospitals, clinical records, or regional surveillance systems. Conclusions ML and DL techniques demonstrate potential for improving leptospirosis prediction and diagnosis, but future research should focus on using larger, more diverse datasets, adopting transfer learning strategies, and integratin

关键词： leptospirosis machine learning deep learning prediction models diagnosis artificial intelligence convolutional neural networks support vector machines transfer learning zoonotic diseases

来源：评论

学校读者我要写书评

暂无评论

DYNAMIC VISUALIZATION OF PATHWAYS:USE DEATH-DOMAIN RELATED PATHWAYS AS AN EXAMPLE

DYNAMIC VISUALIZATION OF PATHWAYS:USE DEATH-DOMAIN RELATED P...

引用

The4thAsian-PacificOrgan...

作者： Kai-Lung Tang Der-Ming Liou Ueng-Cheng Yang Institute of Health Informatics and Decision Making Bioinformatics ProgramNational Yang-Ming UniversityTaipei Institute of Health Informatics and Decision Making Bioinformatics ProgramNational Yang-Ming UniversityTaipei Institute of Biochemistry Bioinformatics Research CenterNational Yang-Ming UniversityTaipei

＜正＞Most of the molecular, cellular, and developmental biology researches focus on studying the mechanism behind a biological phenomenon. The center of the above researches is thus a pathway-discovery and a pathway ...

关键词：

来源：评论

学校读者我要写书评

暂无评论

Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study

JMIR Aging

引用

JMIR Aging 2025年 8卷 e69504页

作者： Socrates, Vimig Wright, Donald S. Huang, Thomas Fereydooni, Soraya Dien, Christine Chi, Ling Albano, Jesse Patterson, Brian Kanaparthy, Naga Sasidhar Wright, Catherine X. Loza, Andrew Chartash, David Iscoe, Mark Taylor, Richard Andrew Department of Biomedical Informatics and Data Science School of Medicine Yale University New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States Department of Emergency Medicine School of Medicine Yale University New Haven CT United States VA Connecticut Healthcare System US Department of Veterans Affairs West Haven CT United States Department of Pharmacy Yale New Haven Hospital New Haven CT United States BerbeeWalsh Department of Emergency Medicine University of Wisconsin–Madison Madison WI United States Section of Cardiovascular Medicine Department of Internal Medicine Yale School of Medicine New Haven CT United States School of Medicine University College Dublin Dublin Ireland Department of Biostatistics School of Public Health Yale University New Haven CT United States

Background: Polypharmacy, the concurrent use of multiple medications, is prevalent among older adults and associated with increased risks for adverse drug events including falls. Deprescribing, the systematic process of discontinuing potentially inappropriate medications, aims to mitigate these risks. However, the practical application of deprescribing criteria in emergency settings remains limited due to time constraints and criteria complexity. Objective: This study aims to evaluate the performance of a large language model (LLM)–based pipeline in identifying deprescribing opportunities for older emergency department (ED) patients with polypharmacy, using 3 different sets of criteria: Beers, Screening Tool of Older People’s Prescriptions, and Geriatric Emergency Medication Safety Recommendations. The study further evaluates LLM confidence calibration and its ability to improve recommendation performance. Methods: We conducted a retrospective cohort study of older adults presenting to an ED in a large academic medical center in the Northeast United States from January 2022 to March 2022. A random sample of 100 patients (712 total oral medications) was selected for detailed analysis. The LLM pipeline consisted of two steps: (1) filtering high-yield deprescribing criteria based on patients’ medication lists, and (2) applying these criteria using both structured and unstructured patient data to recommend deprescribing. Model performance was assessed by comparing model recommendations to those of trained medical students, with discrepancies adjudicated by board-certified ED physicians. Selective prediction, a method that allows a model to abstain from low-confidence predictions to improve overall reliability, was applied to assess the model’s confidence and decision-making thresholds. Results: The LLM was significantly more effective in identifying deprescribing criteria (positive predictive value: 0.83;negative predictive value: 0.93;McNemar test for paired proportion

关键词： calibration deprescribing emergency medicine geriatrics large language models natural language processing potentially inappropriate medication list

来源：评论

学校读者我要写书评

暂无评论

iSNP: An integrated, automatically updated SNP database

iSNP: An integrated, automatically updated SNP database

引用

International Symposium on health informatics and bioinformatics (HIBIT)

作者： Levent Çarkacwğlu Ceyhun Gedikoğlu Yeşim Aydin Son Bioinformatics Graduate Program Middle East Technical University 06800 Ankara Turkey Bioinformatics Graduate Program Middle East Technical University Ankara Turkey Health Informatics Department Middle East Technical University Ankara Turkey

关键词： Databases bioinformatics Genomics Humans Diseases

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：