The cytotoxic T-lymphocyte antigen-4 (CTLA4) is essential in controlling T cell activity within the immune system. Thus, uncovering the molecular dynamics of single nucleotide polymorphisms (SNPs) within the CTLA4 gene is critical. We identified the non-synonymous SNPs (nsSNPs), examined their impact on protein stability, and identified the protein sequences associated with them in the human CTLA4 gene.
View Article and Find Full Text PDFSurface water plays a vital role in the spread of infectious diseases. Information on the spatial and temporal dynamics of surface water availability is thus critical to understanding, monitoring and forecasting disease outbreaks. Before the launch of Sentinel-1 Synthetic Aperture Radar (SAR) missions, surface water availability has been captured at various spatial scales through approaches based on optical remote sensing data.
View Article and Find Full Text PDFBackground: Juvenile Idiopathic arthritis (JIA) is one of the most common chronic diseases in children. It still remains a challenge to treat refractory poly-articular course JIA patients, especially in Bangladesh, where patients from low socio-economic backgrounds are unable to manage biological agents. Tofacitinib is one of the alternative options to biological agents, which can be taken orally and is cost effective.
View Article and Find Full Text PDFRoundup is one of the most widely used glyphosate-based harmful herbicides in the United States as well as globally, which poses a severe risk for terrestrial and aquatic organisms. In order to identify the detrimental effects of Roundup exposure in aquatic organisms, we investigated the environmentally relevant concentrations of Roundup exposure (low dose: 0.5 μg/L and high dose: 5.
View Article and Find Full Text PDFObjective: Functional magnetic resonance imaging data pose significant challenges due to their inherently noisy and complex nature, making traditional statistical models less effective in capturing predictive features. While deep learning models offer superior performance through their non-linear capabilities, they often lack transparency, reducing trust in their predictions. This study introduces the Time Reversal (TR) pretraining method to address these challenges.
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