Journal Article10.1016/j.isci.2024.110013
Machine-learning-based integrative –‘omics analyses reveal immunologic and metabolic dysregulation in environmental enteric dysfunction
F. Zulqarnain,Kenneth D.R. Setchell,Yash Sharma,Phillip Fernandes,Sanjana Srivastava,Aman Shrivastava,Lubaina Ehsan,Varun Jain,Shyam Raghavan,Christopher Moskaluk,Y. Haberman,Lee Denson,Khyati Mehta,Najeeha Talat Iqbal,Najeeb Rahman,Kamran Sadiq,Zubair Ahmad,Romana Idress,Junaid Iqbal,Sheraz Ahmed,Aneeta Hotwani,Fayyaz Umrani,Beatrice Amadi,Paul Kelly,Donald E. Brown,Sean R. Moore,Syed Asad Ali,Sana Syed +27 more
TL;DR: Machine-learning-based integrative 'omics analyses reveal immunologic and metabolic dysregulation in environmental enteric dysfunction, a subclinical enteropathy characterized by overlapping tissue features with other inflammatory enteropathies, challenging diagnosis.
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Abstract: Environmental enteric dysfunction (EED) is a subclinical enteropathy challenging to diagnose due to an overlap of tissue features with other inflammatory enteropathies. EED subjects (
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