检索结果-内蒙古大学图书馆

P44—Toxicogenomic profiling of perfluorononanoic acid in wild-type and PPARα-null mice

Reproductive Toxicology 2012年第4期33卷 614-614页

作者： M.B. Rosen J.R. Schmid R.D. Zehr K.P. Das H. Ren B.D. Abbott C. Lau Integrated Systems Biology Research Triangle Park NC United States Biostatistics and Bioinformatics Research Triangle Park NC United States Toxicology Assessment Research Triangle Park NC United States Toxicogenomics Core NHEERL ORD U.S. EPA Research Triangle Park NC United States

来源：评论

学校读者我要写书评

暂无评论

Validation of the Prognostic Significance of Gene Expression Profiling (GEP) Analysis on Myeloma Irrespective of Disease Status or Stage - a Single Center Academic Center Experience

引用

BLOOD 2016年第22期128卷 4417-4417页

作者： Nishihori, Taiga Baz, Rachid Thapa, Ram Kim, Youngchul Chen, Dung-Tsa Migdady, Yazan Van Laar, Ryan K. Bender, Richard A. Siegel, Erin M. Williams, Vonetta Fournier, Michelle Alsina, Melissa Shain, Kenneth H. Department of Blood and Marrow Transplantation H. Lee Moffitt Cancer Center & Research Institute Tampa FL Department of Malignant Hematology H. Lee Moffitt Cancer Center and Research Institute Tampa FL Department of Biostatistics and Bioinformatics H. Lee Moffitt Cancer Center and Research Institute Tampa FL Department of Medicine Memorial Hospital of Rhode Island Pawtucket RI Signal Genetics Little Rock AR Signal Genetics Inc. Carlsbad CA Collaborative Data Services Core H. Lee Moffitt Cancer Center and Research Institute Tampa FL Tissue Core H. Lee Moffitt Cancer Center and Research Institute Tampa FL Department of Blood an Marrow Transplantation H. Lee Moffitt Cancer Center and Research Institute Tampa FL Department of Malignant Hematology H. Lee Moffitt Cancer Center & Research Institute Tampa FL

4417

关键词：

来源：评论

学校读者我要写书评

暂无评论

Time variation of high-risk groups for liver function deteriorations within fluctuating long-term liver function after hepatic radiotherapy in patients with hepatocellular carcinoma

引用

European Journal of Medical Research 2024年第1期29卷 104-104页

作者： Tsai, Yu-Lun Yu, Pei-Chieh Nien, Hsin-Hua Lu, Tzu-Pin Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Department of Radiation Oncology Cathay General Hospital Taipei Taiwan School of Medicine China Medical University Taichung Taiwan School of Medicine Fu Jen Catholic University New Taipei City Taiwan Institute of Biomedical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Bioinformatics and Biostatistics Core Center of Genomic and Precision Medicine National Taiwan University Taipei Taiwan Institute of Health Data Analytics and Statistics College of Public Health National Taiwan University Taipei Taiwan

PURPOSE: The purpose of this study is to find essential risk factors associated with liver function (LF) deteriorations within fluctuating long-term LF and their time-varying effects in patients with hepatocellular carcinoma (HCC) receiving hepatic radiotherapy and to identify high-risk groups for adverse LF deteriorations and their changes over time in facilitating the prevention of hepatic decompensation and the improvement of survival. MATERIALS AND METHODS: A total of 133 HCC patients treated by hepatic radiotherapy were enrolled. A study design was conducted to convert posttreatment long-term LF with fluctuating levels over time to recurrent LF events using defined upgrades in a grading scale. The hazard ratios (HR) of pretreatment biochemical, demographic, clinical, and dosimetric factors in developing posttreatment LF events were estimated using the Cox model. Methodologies of the counting process approach, robust variance estimation, goodness-of-fit testing based on the Schoenfeld residuals, and time-dependent covariates in survival analysis were employed to handle the correlation within subjects and evaluate the time-varying effects during long-term follow-up. RESULTS: Baseline LF score before radiotherapy and gender were significant factors. Initial HR in developing LF events was 1.17 (95% CI 1.11-1.23;P < 0.001) for each increase of baseline LF score and kept almost constant over time (HR, 1.00;95% CI 1.00-1.01;P = 0.065). However, no difference was observed regarding initial hazards for gender (HR, 1.00;95% CI 0.64-1.56;P = 0.994), but the hazard for women got higher monthly over time compared with men (HR, 1.04;95% CI 1.01-1.07;P = 0.006). CONCLUSIONS: High-risk groups for adverse LF deteriorations after hepatic radiotherapy may change over time. Patients with poor baseline LF are vulnerable from the beginning. Women require prevention strategies and careful monitoring for deteriorations at a later stage. © 2024. The Author(s).

关键词： Hepatic radiotherapy Hepatocellular carcinoma High-risk group Long-term liver function Time variation

来源：评论

学校读者我要写书评

暂无评论

SELF-NORMALIZING FOUNDATION MODEL FOR ENHANCED MULTI-OMICS DATA ANALYSIS IN ONCOLOGY

arXiv

引用

arXiv 2024年

作者： Waqas, Asim Tripathi, Aakash Ahmed, Sabeen Mukund, Ashwin Farooq, Hamza Schabath, Matthew B. Stewart, Paul Naeini, Mia Rasool, Ghulam Johnson, Joseph O. Departments of Cancer Epidemiology and Machine Learning EE Department Moffitt Cancer Center & Research Institute University of South Florida United States Department and Machine Learning Moffitt Cancer Center & Research Institute United States Center for Magnetic Resonance Research University of Minnesota United States Departments of Cancer Epidemiology and Thoracic Oncology Moffitt Cancer Center & Research Institute United States Department of Biostatistics and Bioinformatics Moffitt Cancer Center & Research Institute United States Department of Electrical Engineering University of South Florida United States Department of Machine Learning EE Department Moffitt Cancer Center & Research Institute University of South Florida United States Analytic Microscopy Core Facility Moffitt Cancer Center & Research Institute United States

Multi-omics research has enhanced our understanding of cancer heterogeneity and progression. Investigating molecular data through multi-omics approaches is crucial for unraveling the complex biological mechanisms underlying cancer, thereby enabling more effective diagnosis, treatment, and prevention strategies. However, predicting patient outcomes through the integration of all available multi-omics data is still an under-study research direction. Here, we present SeNMo (Self-normalizing Network for Multi-omics), a foundation model that has been trained on multi-omics data across 33 cancer types. SeNMo is particularly efficient in handling multi-omics data characterized by high-width (many features) and low-length (fewer samples) attributes. We trained SeNMo for the task of overall survival of patients using pan-cancer multi-omics data involving 33 cancer sites from the Genomics Data Commons (GDC). The training multi-omics data includes gene expression, DNA methylation, miRNA expression, DNA mutations, protein expression modalities, and clinical data. SeNMo was validated on two independent cohorts: Moffitt Cancer Center and CPTAC lung squamous cell carcinoma. We evaluated the model’s performance in predicting patient’s overall survival using the concordance index (C-Index). SeNMo performed consistently well in the training regime, reflected by the validation C-Index of 0.76 on GDC’s public data. In the testing regime, SeNMo performed with a C-Index of 0.758 on a held-out test set. The model showed an average accuracy of 99.8% on the task of classifying the primary cancer type on the pan-cancer test cohort. SeNMo demonstrated robust performance on the classification task of predicting the primary cancer type of patients. SeNMo further demonstrated significant performance in predicting tertiary lymph structures from multi-omics data, showing generalizability across cancer types, molecular data types, and clinical endpoints. We believe SeNMo and similar models are pois

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Resurgence of Syphilis in the United States: An Assessment of Contributing Factors

引用

Infectious diseases 2019年 12卷 1178633719883282页

作者： Rebecca Schmidt Paul James Carson Rick J Jansen Department of Public Health North Dakota State University Fargo ND USA. Center for Immunization Research and Education North Dakota State University Fargo ND USA. Biostatistics Core Facility North Dakota State University Fargo ND USA. Genomics and Bioinformatics Program North Dakota State University Fargo ND USA.

In the last decade, there has been a marked resurgence of syphilis in the United States despite the availability of effective treatments and previously reliable prevention strategies. The majority of cases are among the population of men who have sex with men (MSM); however, there has also been a recent increase among premenopausal women, coinciding with a concerning rise of congenital cases. The resurgence of syphilis can be largely attributed to changing social and behavioral factors, especially among young MSM. The biological association of syphilis with human immunodeficiency virus (HIV) transmission and acquisition is particularly alarming because of the increased individual and healthcare burden. In addition, some individual actions and public health efforts that are meant to reduce the risk of acquiring HIV may actually lead to risk compensation that facilitates the transmission of syphilis. Untreated syphilis is associated with detrimental health outcomes; therefore, both effective prevention strategies and treatment of this systemic disease have important short-term and long-term public health implications. This article offers a review of social and behavioral factors contributing to the current resurgence and recommendations for reducing syphilis incidence through medical and public health prevention strategies.

关键词： HIV coinfection HIV risk compensation Illicit drug abuse men who have sex with men sexual behavior sexually transmitted infection syphilis incidence

来源：评论

学校读者我要写书评

暂无评论

Publisher Correction: Transcriptomic and neurochemical analysis of the stellate ganglia in mice highlights sex differences

引用

Scientific reports 2019年第1期9卷 9506页

作者： R G Bayles A Olivas Q Denfeld W R Woodward S S Fei L Gao B A Habecker Department of Physiology and Pharmacology Oregon Health & Science University Portland Oregon 97239 USA. Biostatistics & Bioinformatics Core Oregon National Primate Research Center Oregon Health & Science University Beaverton OR 97006 USA. Department of Physiology and Pharmacology Oregon Health & Science University Portland Oregon 97239 USA. habecker@ohsu.edu.

A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Erratum to: Analysis, identification and visualization of subgroups in genomics

引用

Briefings in bioinformatics 2021年第6期22卷 bbab280页

作者： Gunnar Völkel Simon Laban Axel Fürstberger Silke D Kühlwein Nensi Ikonomi Thomas K Hoffmann Cornelia Brunner Donna S Neuberg Verena Gaidzik Hartmut Döhner Johann M Kraus Hans A Kestler Institute of Medical Systems Biology (MSB) Ulm University Ulm Germany. Department of Otorhinolaryngology Head and Neck Surgery Ulm University Medical Center Germany. MSB and deputy of Core Unit Bioinformatics Ulm University Ulm Germany. International Graduate School of Molecular Medicine Ulm University Germany. Department of Biostatistics Dana-Farber Cancer Institute Boston Massachusetts USA. Department of Internal Medicine III Ulm University Medical Center Germany. MSB Ulm University Germany. Institute of Medical Systems Biology and head of Core Unit Bioinformatics Ulm University Ulm Germany.

来源：评论

学校读者我要写书评

暂无评论

Learning and teaching biological data science in the Bioconductor community

arXiv

引用

arXiv 2024年

作者： Drnevich, Jenny Tan, Frederick J. Almeida-Silva, Fabricio Castelo, Robert Culhane, Aedin C. Davis, Sean Doyle, Maria A. Geistlinger, Ludwig Ghazi, Andrew R. Holmes, Susan Lahti, Leo Mahmoud, Alexandru Nishida, Kozo Ramos, Marcel Rue-Albrecht, Kevin Shih, David J.H. Gatto, Laurent Soneson, Charlotte Roy J. Carver Biotechnology Center University of Illinois Urbana-Champaign IL United States Johns Hopkins University Department of Biology BaltimoreMD United States Department of Plant Biotechnology and Bioinformatics Ghent University Ghent Belgium VIB Center for Plant Systems Biology Ghent Belgium Department of Medicine and Life Sciences Universitat Pompeu Fabra Barcelona Spain Limerick Digital Cancer Research Centre School of Medicine University of Limerick Ireland University of Colorado Anschutz School of Medicine DenverCO United States Core for Computational Biomedicine Department of Biomedical Informatics Harvard Medical School BostonMA United States Statistics Department Stanford University StanfordCA United States Department of Computing University of Turku Finland Channing Division of Network Medicine Harvard Medical School BostonMA United States RIKEN Center for Biosystems Dynamics Research 6-7-1 Minatojima Minamimachi Chuoku Hyogo Kobe Japan Department of Epidemiology and Biostatistics City University of New York School of Public Health New YorkNY United States MRC WIMM Centre for Computational Biology MRC Weatherall Institute of Molecular Medicine University of Oxford Oxford United Kingdom School of Biomedical Sciences Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong Computational Biology and Bioinformatics Unit de Duve Institute UCLouvain Brussels Belgium Friedrich Miescher Institute for Biomedical Research Basel Switzerland SIB Swiss Institute of Bioinformatics Basel Switzerland

Modern biological research is increasingly data-intensive, leading to a growing demand for effective training in biological data science. In this article, we provide an overview of key resources and best practices available within the Bioconductor project - an open-source software community focused on omics data analysis. This guide serves as a valuable reference for both learners and educators in the *** Codes 97K80 © 2024, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

2022-LBA-746-ESGO Implementation of a comprehensive cancer genome profiling programme into clinical practice: an italian experience in a referral centre for gynecological cancers

引用

International Journal of Gynecological Cancer 2022年 32卷 A468-A469页

作者： Camilla Nero Silvia Pelligra Simona Duranti Flavia Giacomini Floriana Camarda Elena Giudice Alessia Piermattei Francesca Sillano Angelo Minucci Maria de Bonis Giuseppina Raspaglio Luciano Giacò Emanuela Lucci Cordisco Marta de Donato Tina Pasciuto Diana Giannarelli Francesco Fanfani Gian Franco Zannoni Anna Fagotti Domenica Lorusso Giovanni Scambia Gynecologic Oncology Fondazione Policlinico Universitario Agostino Gemelli IRCCS Roma Italy Scientific Directorate Fondazione Policlinico Universitario Agostino Gemelli IRCCS Roma Italy Gynecologic Oncology and Breast Pathology Unit Fondazione Policlinico Universitario Agostino Gemelli IRCCS Roma Italy Genomics Core facility Fondazione Policlinico Universitario Agostino Gemelli IRCCS Roma Italy Bioinformatics Core facility Fondazione Policlinico Universitario Agostino Gemelli IRCCS Roma Italy Medical Genetics Unit Fondazione Policlinico Universitario Agostino Gemelli IRCCS Roma Italy Data Collection Core facility- GSTeP Fondazione Policlinico Universitario Agostino Gemelli IRCCS Roma Italy Epidemiology and Biostatistics core facility- GSTeP Fondazione Policlinico Universitario Agostino Gemelli IRCCS Roma Italy

来源：评论

学校读者我要写书评

暂无评论

Response to Dekker, Stege, and Versteeg

引用

Journal of the National Cancer Institute 2021年第10期113卷 1436-1437页

作者： Jeanne S Mandelblatt Xingtao Zhou Brent J Small Jaeil Ahn Wanting Zhai Tim Ahles Martine Extermann Deena Graham Paul B Jacobsen Heather Jim Brenna C McDonald Sunita K Patel James C Root Andrew J Saykin Harvey Jay Cohen Judith E Carroll Department of Oncology Cancer Prevention and Control Program Georgetown-Lombardi Comprehensive Cancer Center Georgetown University Washington DC USA. Department of Biostatistics Bioinformatics and Biomathematics Georgetown-Lombardi Comprehensive Cancer Center Georgetown University Washington DC USA. School of Aging Studies University of South Florida and Health Outcome and Behavior Program and Biostatistics Resource Core H. Lee Moffitt Cancer Center and Research Institute at the University of South Florida Tampa FL USA. Department of Biostatistics Bioinformatics and Biomathematics Georgetown-Lombardi Comprehensive Cancer Center Georgetown University Washington DC USA. Department of Psychiatry and Behavioral Sciences Memorial Sloan-Kettering Cancer Center New York NY USA. Department of Oncology Moffitt Cancer Center University of South Florida Tampa FL USA. John Theurer Cancer Center Hackensack NJ USA. Division of Cancer Control and Population Sciences Healthcare Delivery Research Program National Cancer Institute National Institutes of Health Bethesda MD USA. Department of Health Outcomes and Behavior Moffitt Cancer Center and Research Institute University of South Florida Tampa FL USA. Department of Radiology and Imaging Sciences and the Melvin and Bren Simon Cancer Center Center for Neuroimaging Indiana University School of Medicine Indianapolis IN USA. Departments of Population Sciences and Supportive Care Medicine City of Hope Comprehensive Cancer Center Duarte CA USA. Department of Psychiatry and Behavioral Sciences Memorial Sloan Kettering Cancer Center New York NY USA. Departments of Psychiatry and Anesthesiology Weill Medical College of Cornell University New York NY USA. Department of Radiology and Imaging Sciences and the Melvin and Bren Simon Cancer Center Center for Neuroimaging Indiana University School of Medicine Indianapolis IN USA. Department of Medicine Duke University School of Medicine Durham NC USA. UCLA Department of

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：