The use of probiotics is associated with a reduction in the incidence of nosocomial infections, VAP, and length of ICU stay but is not associated with an overall mortality advantage. However, the results should be interpreted cautiously due to the heterogeneity among study designs. Further large-scale, well-designed RCTs are needed.
Published studies on the associations between glutathione S-transferase (GST) polymorphisms and Alzheimer's disease reported controversial findings. A meta-analysis of published studies was performed to assess the associations between polymorphisms of GSTM1, GSTT1 and GSTP1, and Alzheimer's disease. PubMed, Embase, and other databases were searched for case-control on the associations between polymorphisms of GSTM1, GSTT1 and GSTP1, and Alzheimer's disease. The odds ratio (OR) and 95% confidence interval (95% CI) were used to assess the associations. Eleven articles were finally included into the meta-analysis, including eight studies on GSTM1 null genotype, six studies on GSTT1 null genotype, and six studies on GSTP1 Ile105Val polymorphism. Overall, GSTM1 null genotype was associated with increased risk of Alzheimer's disease (fixed effect OR = 1.34, 95% CI 1.10-1.64, P = 0.004). GSTT1 null genotype was not associated with risk of Alzheimer's disease (random effect OR = 1.15, 95% CI 0.68-1.92, P = 0.60). Besides, GSTP1 Ile105Val polymorphism was significantly associated with increased risk of Alzheimer's disease (Val vs Ile: OR = 1.45, 95% CI 1.05-1.99, P = 0.023; ValVal vs IleIle: OR = 1.87, 95% CI 1.30-2.69, P = 0.001; ValVal vs IleIle + IleVal: OR = 1.76, 95% CI 1.24-2.51, P = 0.002). No obvious risk of publication bias was observed in the meta-analysis. GSTM1 null genotype and GSTP1 Ile105Val polymorphism are associated with increased risk of Alzheimer's disease. More studies with large sample size are needed to validate the findings in the meta-analysis.
Background The aim of this study was to identify gene signals for lower-grade glioma (LGG) and to assess their potential as recurrence biomarkers. Material/Methods An LGG-related mRNA sequencing dataset was downloaded from The Cancer Genome Atlas (TCGA) Informix. Multiple bioinformatics analysis methods were used to identify key genes and potential molecular mechanisms in recurrence of LGG. Results A total of 326 differentially-expressed genes (DEGs), were identified from 511 primary LGG tumor and 18 recurrent samples. Gene ontology (GO) analysis revealed that the DEGs were implicated in cell differentiation, neuron differentiation, negative regulation of neuron differentiation, and cell proliferation in the forebrain. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database suggests that DEGs are associated with proteoglycans in cancer, the Wnt signaling pathway, ECM-receptor interaction, the PI3K-Akt signaling pathway, transcriptional deregulation in cancer, and the Hippo signaling pathway. The hub DEGs in the protein–protein interaction network are apolipoprotein A2 (APOA2), collagen type III alpha 1 chain (COL3A1), collagen type I alpha 1 chain (COL1A1), tyrosinase (TYR), collagen type I alpha 2 chain (COL1A2), neurotensin (NTS), collagen type V alpha 1 chain (COL5A1), poly(A) polymerase beta (PAPOLB), insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), and anomalous homeobox (ANHX). GSEA revealed that the following biological processes may associated with LGG recurrence: cell cycle, DNA replication and repair, regulation of apoptosis, neuronal differentiation, and Wnt signaling pathway. Conclusions Our study demonstrated that hub DEGs may assist in the molecular understanding of LGG recurrence. These findings still need further molecular studies to identify the assignment of DEGs in LGG.
Background Hepatocellular carcinoma (HCC) is among the most common and lethal malignancies worldwide. Apolipoproteins (APOs) have been reported increasingly for their relationships with tumors. We aim at exploring the potential relationships of apolipoprotein A (APOA) and apolipoprotein C (APOC) family members with HCC. Methods A data set, containing 212 hepatitis B virus‐related HCC patients, was used for analysis. The diagnostic and prognostic ability of APOA and APOC family genes was figured out. Risk score models and nomograms were developed for the HCC prognosis prediction. Moreover, molecular mechanism exploration were identified biological processes and metabolic pathways of these genes involved in. Validation analysis was carried out using online website. Results APOA1, APOC1, APOC3, and APOC4 showed robust diagnosis significance (all P < 0.05). APOA4, APOC3, and APOC4 were associated with the overall survival (OS) while APOA4 and APOC4 were linked to recurrence‐free survival (RFS, all P ≤ 0.05). Risk score models and nomograms had the advantage of predicting OS and RFS for HCC. Molecular mechanism exploration indicated that these genes were involved in the steroid metabolic process, the PPAR signaling pathway, and fatty acid metabolism. Besides that, validation analysis revealed that APOC1 and APOC4 had an association with OS; and APOC3 was associated with OS and RFS (all P ≤ 0.05). Conclusions APOA1, APOC1, APOC3, and APOC4 are likely to be potential diagnostic biomarkers and APOC3 and APOC4 are likely to be potential prognostic biomarkers for hepatitis B virus‐related HCC. They may be involved in the steroid metabolic process, PPAR signaling pathway, and fatty acid metabolism.
Hepatocellular carcinoma (HCC) is a lethal malignancy worldwide. HCC has traits of late diagnosis and high recurrence. This study explored potential diagnosis and prognosis significance of phospholipase C epsilon 1 (PLCE1) in HCC. The messenger RNA (mRNA) levels and diagnostic value of PLCE1 were determined by real-time polymerase chain reaction and online databases GEPIA, oncomine, and GSE14520 data set. Survival analysis used the Kaplan-Meier Plotter website. Cell cycle, proliferation, migration, and invasion assays were performed with downregulated PLCE1 expression in HCC-M and HepG2 cell lines. PLCE1 was differentially expressed and highly expressed in tumors and had low expression in nontumor tissues (all p < .05). The diagnostic value of PLCE1 was validated with the datasets (all p < .01, all areas under curves > 0.7). PLCE1 mRNA expression was associated with the overall and relapse-free survival (both p < .05). Functional experiments indicated that downregulation of PLCE1 expression led to increased G1 stage in cell cycle and decreased cell proliferation, migration, and invasion compared with a negative control group (all p ≤ .05). The oncogene PLCE1 was differentially expressed in HCC
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