检索结果-内蒙古大学图书馆

Volatile organic compounds exposure, biological ageing, and increased sarcopenia risk: Association, interaction, and mechanistic exploration

引用

Journal of Hazardous Materials 2025年 495卷

作者： Le Hong Qing Liu Wei Liu Jiahao Song Shuhui Wan Zhiying Huo Yongfang Zhang Da Shi Ruyi Liang Bingdong Chen Yani Xiong Feifei Wang Pengfei Chen Weihong Chen Bin Wang Department of Occupational and Environmental Health School of Public Health Tongji Medical College Huazhong University of Science and Technology Wuhan Hubei 430030 China Key Laboratory of Environment and Health Ministry of Education & Ministry of Environmental Protection and State Key Laboratory of Environmental Health (Incubating) School of Public Health Tongji Medical College Huazhong University of Science and Technology Wuhan Hubei 430030 China Medical Big Data and Bioinformatics Research Centre First Affiliated Hospital of Gannan Medical University Ganzhou 341000 China School of Public Health and Health Management Gannan Medical University Ganzhou Jiangxi 341000 China Faculty of Agricultural Life and Environmental Sciences University of Alberta Edmonton Alberta T6G 2P5 Canada

Evidence on the impacts of volatile organic compounds (VOCs), a class of ubiquitous environmental toxics, on sarcopenia, a major age-related global health issue, remains scarce. data from 3007 adults in the National Health and Nutrition Examination Survey (2011–2018) were analyzed to assess the individual and mixture effects of 16 VOCs metabolites (VOCMs) on sarcopenia using multivariate logistic regression, weighted quantile sum (WQS), and Bayesian kernel machine regression (BKMR) models. Network pharmacology was employed to explore potential underlying mechanisms. The phenotypic age (PhenoAge), a biomarker of biological ageing, was used to evaluate its interaction with VOCMs. Several VOCMs, including 2-aminothiazoline-4-carboxylic acid (ATCA; odds ratio: 1.30, 95 % confidence interval: 1.07–1.57), N-acetyl-S-(2-carboxyethyl)-l-cysteine (CEMA; 1.40, 1.01–1.94), N-acetyl-S-(3,4-dihydroxybutyl)-l-cysteine (DHBMA; 2.35, 1.45–3.82), and 3-methylhippuric acid & 4-methylhippuric acid (3,4MHA; 1.32, 1.05–1.64), were associated with an increased risk of sarcopenia. The mixture of 16 VOCMs was linked to a higher sarcopenia risk in both BKMR and WQS (1.79, 1.30–2.49) models. The tumor necrosis factor (TNF) signaling pathway was identified as a key mechanism underlying the VOCs-sarcopenia relationship. PhenoAge was associated with an elevated sarcopenia risk (1.05, 1.01–1.09) and intensified the adverse effects of VOCMs ( P interaction <0.05). This study is the first to demonstrate that VOCs exposure, in interaction with biological ageing, may elevate sarcopenia risk, potentially through the TNF signaling pathway, offering novel insights into sarcopenia prevention in the context of VOCs exposure.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A novel tropical geometry-based interpretable machine learning method: Application in prognosis of advanced heart failure

arXiv

引用

arXiv 2021年

作者： Yao, Heming Derksen, Harm Golbus, Jessica R. Zhang, Justin Aaronson, Keith D. Gryak, Jonathan Najarian, Kayvan Department of Computational Medicine and Bioinformatics University of Michigan Ann ArborMI United States Department of Mathematics Northeastern University BostonMA United States Division of Cardiovascular Medicine Department of Internal Medicine University of Michigan Ann ArborMI United States Electrical and Computer Engineering College of Engineering University of Michigan Ann ArborMI United States Michigan Institute for Data Science University of Michigan Ann ArborMI United States Department of Emergency Medicine University of Michigan Ann ArborMI United States Michigan Center for Integrative Research in Critical Care University of Michigan Ann ArborMI United States

A model's interpretability is essential to many practical applications such as clinical decision support systems. In this paper, a novel interpretable machine learning method is presented, which can model the relationship between input variables and responses in humanly understandable rules. The method is built by applying tropical geometry to fuzzy inference systems, wherein variable encoding functions and salient rules can be discovered by supervised learning. Experiments using synthetic datasets were conducted to investigate the performance and capacity of the proposed algorithm in classification and rule discovery. Furthermore, the proposed method was applied to a clinical application that identified heart failure patients that would benefit from advanced therapies such as heart transplant or durable mechanical circulatory support. Experimental results show that the proposed network achieved great performance on the classification tasks. In addition to learning humanly understandable rules from the dataset, existing fuzzy domain knowledge can be easily transferred into the network and used to facilitate model training. From our results, the proposed model and the ability of learning existing domain knowledge can significantly improve the model generalizability. The characteristics of the proposed network make it promising in applications requiring model reliability and justification. Copyright © 2021, The Authors. All rights reserved.

关键词： Domain Knowledge

来源：评论

学校读者我要写书评

暂无评论

A Geoelectric Approach for Karst Groundwater Analysis

引用

IOP Conference Series: Earth and Environmental science 2022年第1期998卷

作者： Amallia Ferhat Taufik Seizarsyah Mohammad Prasanto Bimantio Nanda Satya Nugraha Dian Pratama Putra Teddy Suparyanto Alam Ahmad Hidayat Bens Pardamean Agribusiness Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Geophysical Engineering Department Universitas Pembangunan Nasional 'Veteran' Yogyakarta Indonesia Agricultural Crop Technology Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Forestry Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Agricultural Engineering Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Artesian well is one of the major efforts to obtain water source for fulfilling water demands in Eroniti Conservation park, Ponjong, Yogyakarta by drilling deep into several soil layers. Vertical Electrical Sounding (VES) method is the most common approach to determine the existence of groundwater. The method probes layers of rock below the ground surface based on their electrical properties, since the electrical resistivity of each layer is theoretically different. This study aims to utilize the VES approach for investigating the properties of the rock layers in the area to explore groundwater sources. We install six different VES points in the observation area using Schlumberger electrode configuration. The methodology of the work consists of three steps: the planning of the placement of the sounding points, the measurement step performed by a unit of IRIS SYSCAL Resistivity meter, and the data analysis and interpretation. Employing the resistivity analysis, we conclude that the observed region consists of Mediterranean soil as a result of weathering of limestone as well as lithology of the limestone. Furthermore, there are two types of aquifer found in the area: a perched aquifer found 27 meters below the ground surface of VES point 1 and a confined aquifer 166 meters below the ground surface of VES point 2 and 6.

关键词：

来源：评论

学校读者我要写书评

暂无评论

STATISTICAL DESIGN AND RATIONALE OF THE BIOMARKERS FOR EVALUATING SPINE TREATMENTS (BEST) TRIAL

arXiv

引用

arXiv 2025年

作者： Sperger, John Kidwell, Kelley M. Mauck, Matthew C. Zhao, Beibo Anstrom, Kevin J. Batorsky, Anna Carey, Timothy S. Clauw, Daniel J. Freeman, Nikki L.B. Greco, Carol M. Ivanova, Anastasia Berkeley, Sara Jones McLean, Samuel A. Psioda, Matthew A. Rowland, Bryce Sowa, Gwendolyn A. Wasan, Ajay D. Zitovsky, Joshua P. Kosorok, Michael R. Department of Biostatistics Gillings School of Global Public Health University of North Carolina Chapel Hill United States Department of Biostatistics School of Public Health University of Michigan United States Department of Anesthesiology University of North Carolina Chapel Hill United States Collaborative Studies Coordinating Center Department of Biostatistics Gillings School of Global Public Health University of North Carolina Chapel Hill United States Department of Medicine University of North Carolina Chapel Hill United States Department of Anesthesiology Chronic Pain & Fatigue Research Center University of Michigan Ann Arbor United States Department of Biostatistics and Bioinformatics Duke University United States Department of Psychiatry University of Pittsburgh School of Medicine United States Department of Epidemiology Gillings School of Global Public Health University of North Carolina Chapel Hill United States Department of Psychiatry University of North Carolina Chapel Hill United States Statistics and Data Science Innovation Hub Biostatistics GSK Department of Physical Medicine and Rehabilitation University of Pittsburgh School of Medicine United States Departments of Anesthesiology and Perioperative Medicine and Psychiatry University of Pittsburgh School of Medicine United States Amazon Postdoctoral Scientist United States Ferguson Laboratory for Orthopaedic and Spine Research Bethel Musculoskeletal Research Center Department of Orthopaedic Surgery University of Pittsburgh School of Medicine United States Department of Bioengineering University of Pittsburgh Swanson School of Engineering United States Clinical and Translational Science Institute University of Pittsburgh United States Carolina Pragmatic Trials Laboratory North Carolina Translational and Clinical Sciences Institute UNC School of Medicine United States Duke Clinical Research Institute United States

Background/Aims: Chronic low back pain (cLBP) is a widely prevalent condition with potentially severe impacts on day-to-day functioning and quality of life. A variety of evidence-based treatment modalities exist, but all approaches have modest average treatment effects—potentially due to individual variation in treatment response and the diverse etiologies of cLBP. The Biomarkers for Evaluating Spine Treatments (BEST) trial was designed to investigate the potential for using patient features including biomarkers and phenotypic measurements to inform cLBP treatment. Methods: We provide an overview of the BEST trial and detail the statistical rationale for key study design decisions. We discuss the salient features of the scientific and clinical context of cLBP treatment that motivated the study design and planned analysis, describe modifications to existing methods that were needed because of the setting, and present simulation studies that were used to inform the study design. Results: The BEST trial was designed as a multi-site sequential, multiple-assignment randomized trial (SMART) of four cLBP treatment modalities. The primary objective was to inform a precision medicine approach to the treatment of cLBP by estimating the optimal treatment or combination of treatments based on patient features and individual patient’s response to the initial treatment. The primary analysis includes estimating an interpretable dynamic treatment regime for recommending treatments based on patient features and investigating the subgroups that respond best to each one of the treatment modalities. The trial aimed to enroll 630 protocol completers. Broad eligibility criteria were used to improve the generalizability of study results. Notably, participants could be excluded from one of the four interventions and still be eligible for the study. We modified the minimization method for reducing covariate imbalance to allow for these exclusions. Conclusion: The BEST trial may pave the way

关键词： Patient treatment

来源：评论

学校读者我要写书评

暂无评论

The featurecloud AI store for federated learning in biomedicine and beyond

arXiv

引用

arXiv 2021年

作者： Matschinske, Julian Späth, Julian Nasirigerdeh, Reza Torkzadehmahani, Reihaneh Hartebrodt, Anne Orbán, Balázs Fejér, Sándor Zolotareva, Olga Bakhtiari, Mohammad Bihari, Béla Bloice, Marcus Donner, Nina C. Fdhila, Walid Frisch, Tobias Hauschild, Anne-Christin Heider, Dominik Holzinger, Andreas Hötzendorfer, Walter Hospes, Jan Kacprowski, Tim Kastelitz, Markus List, Markus Mayer, Rudolf Moga, Mónika Müller, Heimo Pustozerova, Anastasia Röttger, Richard Saranti, Anna Schmidt, Harald H.H.W. Tschohl, Christof Wenke, Nina K. Baumbach, Jan Chair of Computational Systems Biology University of Hamburg Hamburg Germany Institute of AI in Medicine and Healthcare Technical University of Munich Munich Germany Institute of Mathematics and Computer Science University of Southern Denmark Odense Denmark Gnome Design SRL Sfântu Gheorghe Romania Chair of Experimental Bioinformatics Technical University of Munich Freising Germany Institute for Medical Informatics Statistics and Documentation Medical University of Graz Graz Austria concentris research management gmbh Fürstenfeldbruck Germany SBA Research Gemeinnützige GmbH Vienna Austria Department of Mathematics and Computer Science Philipps-University of Marburg Marburg Germany Research Institute AG & Co KG Vienna Austria Division Data Science in Biomedicine Peter L. Reichertz Institute for Medical Informatics TU Braunschweig and Hannover Medical School Brunswick Germany Brunswick Germany Department of Pharmacology and Personalised Medicine MeHNS FHML Maastricht University Maastricht Netherlands

Machine Learning (ML) and Artificial Intelligence (AI) have shown promising results in many areas and are driven by the increasing amount of available data. However, this data is often distributed across different institutions and cannot be shared due to privacy concerns. Privacy-preserving methods, such as Federated Learning (FL), allow for training ML models without sharing sensitive data, but their implementation is time-consuming and requires advanced programming skills. Here, we present the FeatureCloud AI Store for FL as an all-in-one platform for biomedical research and other applications. It removes large parts of this complexity for developers and end-users by providing an extensible AI Store with a collection of ready-to-use apps. We show that the federated apps produce similar results to centralized ML, scale well for a typical number of collaborators and can be combined with Secure Multiparty Computation (SMPC), thereby making FL algorithms safely and easily applicable in biomedical and clinical environments. © 2021, CC BY.

关键词： bioinformatics

来源：评论

学校读者我要写书评

暂无评论

Biclustering Method to Capture the Spatial Pattern and to Identify the Causes of Social Vulnerability in Indonesia: A New Recommendation for Disaster Mitigation Policy

引用

Procedia Computer science 2019年 157卷 31-37页

作者： Puspita Anggraini Kaban Robert Kurniawan Rezzy Eko Caraka Bens Pardamean Budi Yuniarto Sukim Computational Statistics Department Polytechnic of Statistics - STIS Jakarta 13330 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia College of Informatics Chaoyang University of Technology Taichung City 41349 Taiwan (R.O.C.) Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Geographically, Indonesia is a meeting point of three continental plates. Scilicet, the Eurasian Plate, the Indo-Australian Plate, and the Pacific Plate. Therefore, Indonesia is part of the infamous volcanic zone called the ”Ring of Fire” and one of the areas prone to natural disasters such as volcanic eruptions, earthquakes, tsunamis, floods, and landslides. This study aims to capture the spatial pattern and identify the causes of social vulnerability in the districts/cities in Indonesia using the biclustering method. The data is extracted from the Indonesian National Socio-Economic Survey (SUSENAS) by BPS-Statistics in 2014. The biclustering result indicates that each district/city has its own social vulnerability characteristics and shows that the vulnerable aspects of each district/city are different. The adjacent observations tend to have social vulenrability characteristics. The results of this study can be used as a reference for national disaster mitigation policy in Indonesia.

关键词： biclustering disaster mitigation social vulnerability SoVI spatial pattern

来源：评论

学校读者我要写书评

暂无评论

Seeing or believing in hyperplexed spatial proteomics via antibodies: New and old biases for an image-based technology

引用

Biological imaging 2024年 4卷 e10页

作者： Maddalena M Bolognesi Lorenzo Dall'Olio Amy Maerten Simone Borghesi Gastone Castellani Giorgio Cattoretti Istituto di Bioimmagini e Fisiologia Molecolare - CNR Milan Italy. National Biodiversity Future Center (NBFC) Palermo Italy. Laboratorio di Data Science and Bioinformatics IRCCS Istituto delle Scienze Neurologiche di Bologna - AUSL BO Ospedale Bellaria Bologna Italy. Department of in vitro Toxicology and Dermato-Cosmetology Vrije Universiteit Brussel Jette Belgium. Department of Mathematics and Applications University of Milano Bicocca Milan Italy. Department of Experimental Diagnostic and Specialty Medicine University of Bologna Bologna Italy. Pathology Department of Medicine and Surgery Universitá di Milano-Bicocca Monza Italy.

Hyperplexed in-situ targeted proteomics via antibody immunodetection (i.e., >15 markers) is changing how we classify cells and tissues. Differently from other high-dimensional single-cell assays (flow cytometry, single-cell RNA sequencing), the human eye is a necessary component in multiple procedural steps: image segmentation, signal thresholding, antibody validation, and iconographic rendering. Established methods complement the human image evaluation, but may carry undisclosed biases in such a new context, therefore we re-evaluate all the steps in hyperplexed proteomics. We found that the human eye can discriminate less than 64 out of 256 gray levels and has limitations in discriminating luminance levels in conventional histology images. Furthermore, only images containing visible signals are selected and eye-guided digital thresholding separates signal from noise. BRAQUE, a hyperplexed proteomic tool, can extract, in a marker-agnostic fashion, granular information from markers which have a very low signal-to-noise ratio and therefore are not visualized by traditional visual rendering. By analyzing a public human lymph node dataset, we also found unpredicted staining results by validated antibodies, which highlight the need to upgrade the definition of antibody specificity in hyperplexed immunostaining. Spatially hyperplexed methods upgrade and supplant traditional image-based analysis of tissue immunostaining, beyond the human eye contribution.

关键词： dimensionality reduction algorithms flow cytometry human vision image analysis multiplex staining

来源：评论

学校读者我要写书评

暂无评论

bioinformatics Commons: The Cornerstone of Life and Health sciences

引用

Genomics,Proteomics & bioinformatics 2018年第4期16卷 223-225页

作者： Zhang Zhang Yu Xue Fangqing Zhao BIG Data Center and CAS Key Laboratory of Genome Sciences & Information Beijing Institute of Genomics Chinese Academy of Sciences Department of Bioinformatics & Systems Biology MOE Key Laboratory of Molecular Biophysics College of Life Science and Technology and the Collaborative Innovation Center for Biomedical Engineering Huazhong University of Science and Technology Beijing Institutes of Life Science Chinese Academy of Sciences

bioinformatics, an interdisciplinary field that combines biology, mathematics, computer science, medicine, and health science, to integrate, analyze, and interpret biological data, is now becoming increasingly data-intensive. To dig out the treasure from big data powered by high-throughput sequencing technologies, it is highly dependent on bioinformatics Commons that involves a variety of fundamental resources, includ-

关键词： bioinformatics Commons The Cornerstone of Life and Health sciences

来源：评论

学校读者我要写书评

暂无评论

Integrated querying and version control of context-specific biological networks

引用

database 2020年第2020期2020卷 baaa018-baaa018页

作者： Cowman, Tyler Coşkun, Mustafa Grama, Ananth Koyutürk, Mehmet Department of Computer and Data Sciences Case Western Reserve University Cleveland 44106 OH United States Center for Proteomics and Bioinformatics Case Western Reserve University Cleveland 44106 OH United States Department of Computer Engineering Abdullah Gül University Kayseri 38080 Turkey Department of Computer Science Purdue University West Lafayette 47906 IN United States

Motivation: Biomolecular data stored in public databases is increasingly specialized to organisms, context/pathology and tissue type, potentially resulting in significant overhead for analyses. These networks are often specializations of generic interaction sets, presenting opportunities for reducing storage and computational cost. Therefore, it is desirable to develop effective compression and storage techniques, along with efficient algorithms and a flexible query interface capable of operating on compressed data structures. Current graph databases offer varying levels of support for network integration. However, these solutions do not provide efficient methods for the storage and querying of versioned networks. Results: We present VerTIoN, a framework consisting of novel data structures and associated query mechanisms for integrated querying of versioned context-specific biological networks. As a use case for our framework, we study network proximity queries in which the user can select and compose a combination of tissue-specific and generic networks. Using our compressed version tree data structure, in conjunction with state-of-the-art numerical techniques, we demonstrate real-time querying of large network databases. Conclusion: Our results show that it is possible to support flexible queries defined on heterogeneous networks composed at query time while drastically reducing response time for multiple simultaneous queries. The flexibility offered by VerTIoN in composing integrated network versions opens significant new avenues for the utilization of ever increasing volume of context-specific network data in a broad range of biomedical applications. © 2020 The Author(s) 2020. Published by Oxford University Press.

关键词：

来源：评论

学校读者我要写书评

暂无评论

COVID-19 Testing Pipeline: Lesson Learned

引用

IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Dian Amirulloh Digdo Sudigyo Arif Budiarto Ika Nurlaila Erlin Listiyaningsih Andrew Simon Bens Pardamean Genetics Indonesia Jakarta Indonesia 12940 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Information System Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

The transmission of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) in Indonesia is seen to be uncontrollably increasing that urges the government to leverage the capacity for the disease detections. Real-time polymerase chain reaction (RT-PCR), rapid test and computed tomography (CT) scan are the most common methods to determine if one has been infected regardless of whether or not the common symptoms of such Corona Virus Disease 2019 (COVID-19) surface. Among these three, RT-PCR is considered the gold standard for qualitative and quantitative assessment of SARS CoV-2 detection. The present paper aims at elaborating the framework of Roche's RT-PCR machine employed specifically for SARS CoV-2 detection performed by Genetics Indonesia which is deemed to be efficient and relatively quicker than other detection kits. RT-PCR machine detected SARS Cov-2 with RNA amplification curve equals to 10 copies RNA below the cut off value of Crossing point (Cp) positive control. Also elucidated in the paper is the implementations of EAV RNA and LightCycler® 96 RT-PCR System through which analysis time, amounts of individual required sample, as well as the reagents, can be accordingly reduced.

关键词：

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：