GAOZHONG LI, FUXIN LI, NING WEI, QING JIA^*

BIOCELL, Vol.47, No.9, pp. 2081-2099, 2023, DOI:10.32604/biocell.2023.029986

Abstract Background: This study was aimed at identifying natural killer (NK) cell-related genes to design a risk prognosis model for the accurate evaluation of gastric cancer (GC) prognosis. Methods: We obtained NK cell-related genes from various databases, followed by Cox regression analysis and molecular typing to identify prognostic genes. Various immune algorithms and enrichment analyses were used to investigate the mutations, immune status, and pathway variations among different genotypes. The key prognostic genes were assessed using the least absolute shrinkage and selection operator (Lasso) regression analysis and univariate Cox regression analysis. Thereafter, the risk score (RS) prognosis model was constructed based… More > Graphic Abstract

SOHEILA HASANIAN¹, NOUR AMIRMOZAFARI², AHMAD FARAJZADEH SHEIKH^3,*, IRAJ MEHREGAN¹

BIOCELL, Vol.44, No.3, pp. 411-419, 2020, DOI:10.32604/biocell.2020.08976

Abstract Methicillin-resistant Staphylococcus aureus (MRSA) strains are the essential cause of infections in communities and hospitals. The present study was conducted to determine the molecular typing of MRSA, isolated from hospitalized patients, using the double-locus sequence typing (DLST). In total, 280 S. aureus isolated from clinical specimens by phenotypic (catalase, coagulase, DNase, oxacillin, vancomycin screening agar and antibiotic disk diffusion), and molecular methods (PCR for determining the mecA, vanA and nuc genes). The DLST and sequencing was performed for MRSA containing mecA. Out of 280 specimens, confirmed as Staphylococcus aureus (S. aureus), 123 (43.9%) strains were MRSA. The highest resistance toward… More >