S. Ali

The paper analyzes mutations in 611 SARS-CoV-2 genomes from India, identifying their impact on proteins and noting higher mutation rates in females and specific regions.

This study evaluates the predictivity of zebrafish as a toxicology model by testing 24 compounds from two classes on embryo development and larval behavior, finding poor correlation with rodent toxicity data.

The paper analyzes 611 SARS-CoV-2 genomes from India to construct a phylo-geo-network and identify haplogroups, revealing local viral evolution and predominant lineages.

The paper isolates and tests bacterial strains from Pakistani wastewaters to bioremediate contaminants, finding three strains effective in degrading pharmaceutical pollutants.

The paper examines the incidence and antimicrobial susceptibility patterns of urine bacterial flora in young females, finding a high prevalence of polymicrobial cultures and resistance to common antibiotics.

This study develops a multi-epitope subunit vaccine against Norovirus using computational vaccinology, selecting antigenic epitopes and modeling the vaccine structure for potential experimental validation.

The paper investigates genome-wide uracil distribution changes in human cells after chemotherapy, finding drug-induced shifts toward active genomic regions.

This study investigates changes in the tumor microenvironment (TME) in response to different therapies in a glioblastoma model, finding that TME-targeting therapies improve survival.

The paper identifies two distinct MYCN amplicon structures in neuroblastoma, showing how enhancer hijacking compensates for loss of local regulatory elements.

This study shows that TMEM163 is a zinc efflux transporter, designated ZNT11, based on functional assays and sequence analysis.

The paper assesses fecal contamination in urban Dhaka using E. coli MPN measurements across different environmental samples and finds higher contamination in low-income areas compared to high-income and transient neighborhoods.

This paper develops a CNN-based CAD system for early detection of non-proliferative diabetic retinopathy using OCT images, achieving 94% accuracy with transfer learning.