Exploring the Structural and Functional Consequences of Deleterious Missense Nonsynonymous SNPs in the Gene: A Computational Approach.

Background: Mutations in the gene can disrupt its normal signaling pathways, leading to hematological disorders such as polycythemia vera and other myeloproliferative diseases.

Methodology: In this study, a range of bioinformatics tools, including SIFT, PolyPhen-2, SNAP2, SNPs & Go, PhD-SNP, I-Mutant2.0, MuPro, MutPred, ConSurf, HOPE, and Interpro were used to assess the deleterious effects of missense nonsynonymous single nucleotide polymorphisms (nsSNPs) on protein structure and function.

Computational Analysis of Deleterious nsSNPs in Gene Associated with Permanent Neonatal Diabetes Mellitus.

gene mutations affect the structure of insulin and are considered a leading cause of neonatal diabetes and permanent neonatal diabetes mellitus PNDM. These mutations can affect the production and secretion of insulin, resulting in inadequate insulin levels and subsequent hyperglycemia. Early discovery or prediction of PNDM can aid in better management and treatment.

Clinico-Epidemiological Laboratory Findings of COVID- 19 Positive Patients in a Hospital in Saudi Arabia.

Background: Understanding COVID-19's onset and clinical effects requires knowing host immune responses.

Objective: To investigate the presence of IgM, IgG, and cytokine levels (IL-2 and IL-6) in individuals with COVID-19 who have had their diagnosis confirmed by PCR.

Methods: This cross-sectional research included 70 adult ICU patients from King Abdullah Hospital in Bisha, Saudi Arabia.