Výsledky vyhledávání - "Govind Benakatti"

Akademický článek

Advancing temporal sepsis biomarking: Covariate vascular endothelial growth factor A and B gene expression profiling in a murine model of SARS-CoV infection

Autor: Asrar Rashid, Feras Al-Obeidat, Kesava Ramakrishnan, Wael Hafez, Nouran Hamza, Zainab A. Malik, Raziya Kadwa, Muneir Gador, Govind Benakatti, Rayaz A Malik, Ibrahim Elbialy, Hekmieh Manad, Guftar Shaikh, Ahmed Al-Dubai, Amir Hussain

Publikováno v: Informatics in Medicine Unlocked, Vol 47, Iss , Pp 101474- (2024)

The limited specificity of standard inflammatory biomarkers poses a challenge for the diagnosis and monitoring of sepsis. The differential gene expression patterns of Vascular Endothelial Growth Factor A and B (VEGF-A and B) are promising candidates.

Externí odkaz: https://doaj.org/article/b93f785ba53f4b35af732524ce63b4c2

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Akademický článek

Advancing sepsis clinical research: harnessing transcriptomics for an omics-based strategy - a comprehensive scoping review

Publikováno v: Informatics in Medicine Unlocked, Vol 44, Iss , Pp 101419- (2024)

Sepsis continues to be recognized as a significant global health challenge across all ages and is characterized by a complex pathophysiology. In this scoping review, PRISMA-ScR guidelines were adhered to, and a transcriptomic methodology was adopted,

Externí odkaz: https://doaj.org/article/cc44dde4c7e94c67b131c70e3cb338e0

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Akademický článek

A dual covariant biomarker approach to Kawasaki disease, using vascular endothelial growth factor A and B gene expression; implications for coronary pathogenesis

Autor: Asrar Rashid, Govind Benakatti, Feras Al-Obeidat, Rajesh Phatak, Zainab A. Malik, Javed Sharief, Raziya Kadwa, Wael Hafez, Mohammed Toufiq, Damien Chaussabel, Rayaz Malik, Nasir Quraishi, Syed Ahmed Zaki, Guftar Shaikh, Amir Hussain

Publikováno v: Informatics in Medicine Unlocked, Vol 43, Iss , Pp 101384- (2023)

Introduction: Kawasaki disease (KD) is the most common vasculitis in young children, with coronary artery lesions (CALs) and coronary aneurysms (CAAs) being responsible for most KD-related deaths. Objective: We hypothesized that Vascular Endothelial

Externí odkaz: https://doaj.org/article/1f81859349614a23ba01a98f5f8fe9d4

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Akademický článek

Application of a gene modular approach for clinical phenotype genotype association and sepsis prediction using machine learning in meningococcal sepsis

Autor: Asrar Rashid, Arif R. Anwary, Feras Al-Obeidat, Joe Brierley, Mohammed Uddin, Hoda Alkhzaimi, Amrita Sarpal, Mohammed Toufiq, Zainab A. Malik, Raziya Kadwa, Praveen Khilnani, M Guftar Shaikh, Govind Benakatti, Javed Sharief, Syed Ahmed Zaki, Abdulrahman Zeyada, Ahmed Al-Dubai, Wael Hafez, Amir Hussain

Publikováno v: Informatics in Medicine Unlocked, Vol 41, Iss , Pp 101293- (2023)

Sepsis is a major global health concern causing high morbidity and mortality rates. Our study utilized a Meningococcal Septic Shock (MSS) temporal dataset to investigate the correlation between gene expression (GE) changes and clinical features. The

Externí odkaz: https://doaj.org/article/4337dceefb524a2694d6121bf865be05

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