ابراهيم زغلول بشير عبد الباقى
أستاذ مساعد
Machine learning based identification potential feature genes for prediction of drug efficacy in nonalcoholic steatohepatitis animal model
Lipids in Health and Disease • 2024
معلومات البحث
المؤلفون
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
الكلمات المفتاحية
Not Available
المجلة العلمية
Lipids in Health and Disease
الناشر
BioMed Central
المجلد
23
العدد
1
الصفحات
266
publication.type
International
رابط البحث
Open Link
المواد المرفقة
Not Available
الملخص
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 …