Methods: Microarray expression dataset GSE22255 was retrieved from the Gene Expression Omnibus (GEO) database. It includes messenger ribonucleic acid (mRNA) expression data for the peripheral blood mononuclear cells of 20 controls and 20 IS patients. The bioconductor-package 'affy' was used to calculate expression and a pairwise t-test was applied to screen DEGs (P < 0.01). Further, GSEA was used to determine the enrichment of DEGs specific to gene ontology (GO) annotations.
Results: GSEA analysis revealed 21 genes to be significantly plausible gene markers, enriched in multiple pathways among all the DEGs (n = 881). Ten gene sets were found to be core enriched in specific GO annotations. JunD, NCX3 and fibroblast growth factor receptor 4 (FGFR4) were under-represented and glycoprotein M6-B (GPM6B) was persistently over-represented.
Conclusion: The identified genes are either associated with the pathophysiology of IS or they affect post-IS neuronal regeneration, thereby influencing clinical outcome. These genes should, therefore, be evaluated for their utility as suitable markers for predicting IS in clinical scenarios.
METHODS: A total of 19 patients with genital C. trachomatis infection and 10 age-matched healthy controls were recruited for the study. Peripheral blood mononuclear cells (PBMCs) isolated from genital C. trachomatis-infected females were cultured in the presence of CPAF, HSP60 and MOMP antigens, and cytokines were measured by ELISA assay.
RESULTS: We reported that pro-inflammatory cytokines (TNF-α, IL-1β and IL-6) were robustly secreted following antigenic exposure. Notably, CPAP and MOMP were more potent in triggering IL-1β, as compared to HSP60. Elevated levels of the proinflammatory cytokines were also noted in the samples infected with plasmid-bearing C. trachomatis as compared to those infected with plasmid-free strains.
CONCLUSIONS: Our study highlights distinct ability of chlamydial antigens in triggering pro-inflammatory response in the host immune cells.
METHODS: This study included 159 septic patients admitted to an intensive care unit. Leukocytes count, procalcitonin (PCT), interleukin-6 (IL-6), and paraoxonase (PON) and arylesterase (ARE) activities of PON-1 were assayed from blood obtained on ICU presentation. Logistic regression was used to derive sepsis mortality score (SMS), a prediction equation describing the relationship between biomarkers and 30-day mortality.
RESULTS: The 30-day mortality rate was 28.9%. The SMS was [еlogit(p)/(1+еlogit(p))]×100; logit(p)=0.74+(0.004×PCT)+(0.001×IL-6)-(0.025×ARE)-(0.059×leukocytes count). The SMC had higher area under the receiver operating characteristic curve (95% Cl) than SOFA score [0.814 (0.736-0.892) vs. 0.767 (0.677-0.857)], but is not statistically significant. When the SMS was added to the SOFA score, prediction of 30-day mortality improved compared to SOFA score used alone [0.845 (0.777-0.899), p=0.022].
CONCLUSIONS: A sepsis mortality score using baseline leukocytes count, PCT, IL-6 and ARE was derived, which predicted 30-day mortality with very good performance and added significant prognostic information to SOFA score.