Computational Characterization of Environmental Enteropathy

环境性肠病的计算表征

基本信息

批准号：
10627838
负责人：
Sana Syed
金额：
$ 19.26万
依托单位：
UNIVERSITY OF VIRGINIA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-01 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10627838
关键词：
5 year old Address Age Antigens Asia Bangladeshi Bile Acids Biochemical Biological Biological Markers Biopsy Birth Caring Celiac Disease Cessation of life Child Childhood Chronic Classification Clinical Clinical Markers Clinical Research Cognitive deficits Cohort Studies Collaborations Computing Methodologies Data Science Detection Development Development Plans Diagnosis Diagnostic Duodenum Environmental Risk Factor Etiology Exhibits Exposure to Failure Foundations Funding Gastroenterologist Genetic Transcription Gluten Goals Growth Health Histologic Histology Histopathology Human Pathology Image Impairment Inflammation Injury Intestinal permeability Intestines K-Series Research Career Programs Knowledge Lactulose Lamina Propria Lead Length Link Lymphocytosis MS4A1 gene Malnutrition Measurement Measures Mediating Mentors Mentorship Metabolic Milieu Therapy Morphology Mucositis Multiomic Data Neurocognitive Pakistan Pathogenesis Pathologic Pathway interactions Pattern Physicians Population Populations at Risk Prevalence Publications Research Resource-limited setting Rhamnose Risk Factors Role Scientist Severities Small Intestines Standardization Structure System Time Tissues Training Translational Research Universities Validation Villous Villous Atrophy Virginia Visual Work absorption career career development circulating biomarkers clinical phenotype cohort deep learning diagnostic algorithm dietary disorder control effective intervention effective therapy enteric pathogen epithelium regeneration genetic risk factor imaging approach improved intraepithelial low and middle-income countries microbiome mortality multiple omics novel novel marker novel therapeutics nutrient absorption nutrition oral vaccine patient oriented socioeconomics systemic inflammatory response tissue injury transcriptome urinary vaccine immunogenicity

项目摘要

PROJECT SUMMARY/ABSTRACT Undernutrition afflicts 20% of children < 5 years of age in low- and middle-income countries (LMICs) and is a major risk factor for mortality. Linear growth failure (or stunting) in children is tightly linked to irreversible physical and cognitive deficits, with profound implications for development. A common cause of stunting in LMICs is Environmental Enteropathy (EE) which has also been linked to decreased oral vaccine immunogenicity. To date, there are no universally accepted, clear diagnostic algorithms or non-invasive biomarkers for EE making this a critical priority. In this K23 Mentored Career Development Award application, Dr. Sana Syed, a Pediatric Gastroenterologist with advanced training in Nutrition at the University of Virginia, proposes to 1) Develop and validate a Deep Learning Net to identify morphological features of EE versus celiac and healthy small intestinal tissue, 2) correlate the Deep Learning Net identified distinguishing EE intestinal tissue findings with clinical phenotype, measures of gut barrier and absorption, and bile acid deconjugation, and 3) Use a Deep Learning Net computational approach to identify distinguishing multiomic patterns of EE versus celiac disease. This work will be carried out in the context of an ongoing birth cohort study of environmental enteropathy in Pakistan (SEEM). Dr. Syed proposes a career development plan which includes mentorship, fieldwork, coursework, publications, and clinical time that will situate her as an independent physician-scientist with expertise in translational research employing computational `omics and image approaches to elucidate biologic mechanisms of stunting pathways and in identification of novel and effective therapies for EE.

项目概要/摘要在低收入和中等收入国家 (LMIC)，20% 的 5 岁以下儿童面临营养不良问题，死亡的主要危险因素。儿童线性生长障碍（或发育迟缓）与不可逆的生长密切相关身体和认知缺陷，对发展具有深远影响。发育迟缓的一个常见原因 LMIC 是环境性肠病 (EE)，也与口服疫苗减少有关免疫原性。迄今为止，还没有普遍接受的、明确的诊断算法或非侵入性的诊断算法。 EE 的生物标志物使其成为重中之重。在这份 K23 指导职业发展奖申请中， Sana Syed 博士是一位儿科胃肠病学家，在弗吉尼亚大学接受过高级营养学培训，建议 1) 开发并验证深度学习网络来识别 EE 与乳糜泻和健康小肠组织，2) 将深度学习网络识别出的区分 EE 关联起来肠道组织发现与临床表型、肠道屏障和吸收的测量以及胆汁酸解共轭，以及 3) 使用深度学习网络计算方法来识别不同的多组学 EE 与乳糜泻的模式。这项工作将在持续出生队列的背景下进行巴基斯坦环境性肠病研究（SEEM）。 Syed 博士提出了职业发展计划包括指导、实地考察、课程作业、出版物和临床时间，这些将使她成为一名独立医师科学家，拥有利用计算组学和转化研究的专业知识图像方法阐明发育迟缓途径的生物学机制并识别新的和 EE 的有效治疗方法。

项目成果

期刊论文数量（25）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Ten simple rules for engaging with artificial intelligence in biomedicine.

DOI：
10.1371/journal.pcbi.1008531
发表时间：
2021-03
期刊：
PLoS computational biology
影响因子：
4.3
作者：
Malik A;Patel P;Ehsan L;Guleria S;Hartka T;Adewole S;Syed S
通讯作者：
Syed S

Diagnosis of Celiac Disease and Environmental Enteropathy on Biopsy Images Using Color Balancing on Convolutional Neural Networks.

DOI：
10.1007/978-3-030-32520-6_55
发表时间：
2020
期刊：
Proceedings of the Future Technologies Conference (FTC) 2019. Future Technologies Conference (2019 : San Francisco, Calif.)
影响因子：
0
作者：
Kowsari K;Sali R;Khan MN;Adorno W;Ali SA;Moore SR;Amadi BC;Kelly P;Syed S;Brown DE
通讯作者：
Brown DE

Deep Learning for Whole-Slide Tissue Histopathology Classification: A Comparative Study in the Identification of Dysplastic and Non-Dysplastic Barrett's Esophagus.

DOI：
10.3390/jpm10040141
发表时间：
2020-09-23
期刊：
Journal of personalized medicine
影响因子：
0
作者：
Sali R;Moradinasab N;Guleria S;Ehsan L;Fernandes P;Shah TU;Syed S;Brown DE
通讯作者：
Brown DE

Advancing Eosinophilic Esophagitis Diagnosis and Phenotype Assessment with Deep Learning Computer Vision.

DOI：
10.5220/0010241900440055
发表时间：
2021-03
期刊：
Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference)
影响因子：
0
作者：
Adorno W 3rd;Catalano A;Ehsan L;Vitzhum von Eckstaedt H;Barnes B;McGowan E;Syed S;Brown DE
通讯作者：
Brown DE

CeliacNet: Celiac Disease Severity Diagnosis on Duodenal Histopathological Images Using Deep Residual Networks.

DOI：
10.1109/bibm47256.2019.8983270
发表时间：
2019-11
期刊：
Proceedings. IEEE International Conference on Bioinformatics and Biomedicine
影响因子：
0
作者：
Sali R;Ehsan L;Kowsari K;Khan M;Moskaluk CA;Syed S;Brown DE
通讯作者：
Brown DE