Ibrahim Zaghloul Abdelbaky
Asst. Professor
Machine learning based identification potential feature genes for prediction of drug efficacy in nonalcoholic steatohepatitis animal model
Lipids in Health and Disease • 2024
Publication Information
Authors
Marwa Matboli, Ibrahim Abdelbaky, Abdelrahman Khaled, Radwa Khaled, Shaimaa Hamady, Laila M Farid, Mariam B Abouelkhair, Noha E El-Attar, Mohamed Farag Fathallah, Manal S Abd EL Hamid, Gena M Elmakromy, Marwa Ali
Keywords
Not Available
Journal
Lipids in Health and Disease
Publisher
BioMed Central
Volume
23
Issue
1
Pages
266
publication.type
International
Paper Link
Open Link
Supplementary Materials
Not Available
Abstract
Background
Nonalcoholic Steatohepatitis (NASH) results from complex liver conditions involving metabolic, inflammatory, and fibrogenic processes. Despite its burden, there has been a lack of any approved food-and-drug administration therapy up till now.
Purpose
Utilizing machine learning (ML) algorithms, the study aims to identify reliable potential genes to accurately predict the treatment response in the NASH animal model using biochemical and molecular markers retrieved using bioinformatics techniques.
Methods
The NASH-induced rat models were administered various microbiome-targeted therapies and herbal drugs for 12 weeks, these drugs resulted in reducing hepatic lipid accumulation, liver inflammation, and histopathological changes. The ML model was trained and tested based on the Histopathological NASH score (HPS); while (0–4) HPS considered Improved NASH and (5–8) considered non …
Nonalcoholic Steatohepatitis (NASH) results from complex liver conditions involving metabolic, inflammatory, and fibrogenic processes. Despite its burden, there has been a lack of any approved food-and-drug administration therapy up till now.
Purpose
Utilizing machine learning (ML) algorithms, the study aims to identify reliable potential genes to accurately predict the treatment response in the NASH animal model using biochemical and molecular markers retrieved using bioinformatics techniques.
Methods
The NASH-induced rat models were administered various microbiome-targeted therapies and herbal drugs for 12 weeks, these drugs resulted in reducing hepatic lipid accumulation, liver inflammation, and histopathological changes. The ML model was trained and tested based on the Histopathological NASH score (HPS); while (0–4) HPS considered Improved NASH and (5–8) considered non …