Objectives: The study aims to systematically identify the alterations in gut microbiota that observed in gastric cancer through comprehensive assessment of case–control studies.Methods: The systematic literature search of PubMed, Embase, Cochrane Library, and Web of Science was conducted to identify case–control studies that compared the microbiomes of individuals with and without gastric cancer. Quality of included studies was evaluated with the Newcastle-Ottawa Quality Assessment Scale (NOS). Meta-analyses utilized a random-effects model, and subgroup and sensitivity analyses were performed to assess study heterogeneity. All data analyses were performed using the “metan” package in Stata 17.0, and the results were described using log odds ratios (log ORs) with 95% confidence intervals (CIs).Results: A total of 33 studies involving 4,829 participants were eligible for analysis with 29 studies provided changes in α diversity and 18 studies reported β diversity. Meta-analysis showed that only the Shannon index demonstrated statistical significance for α-diversity [−5.078 (−9.470, −0.686)]. No significant differences were observed at the phylum level, while 11 bacteria at genus-level were identified significant changed, e.g., increasing in Lactobacillus [5.474, (0.949, 9.999)] and Streptococcus [5.095, (0.293, 9.897)] and decreasing in Porphyromonas and Rothia with the same [−8.602, (−11.396, −5.808)]. Sensitivity analysis indicated that the changes of 9 bacterial genus were robust. Subgroup analyses on countries revealed an increasing abundance of Helicobacter and Streptococcus in Koreans with gastric cancer, whereas those with gastric cancer from Portugal had a reduced Neisseria. Regarding the sample sources, the study observed an increase in Lactobacillus and Bacteroides in the gastric mucosa of people with gastric cancer, alongside Helicobacter and Streptococcus. However, the relative abundance of Bacteroides decreased compared to the non-gastric cancer group, which was indicated in fecal samples.Conclusion: This study identified robust changes of 9 bacterial genus in people with gastric cancer, which were country-/sample source-specific. Large-scale studies are needed to explore the mechanisms underlying these changes.Systematic Review: Unique Identifier: CRD42023437426 https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023437426.

Background: Metformin treatment has been the most recommended monotherapy of type 2 diabetes mellitus (T2DM) for decades but is challenged by new antidiabetic drugs. This study conducted a meta-analysis of randomized controlled trials (RCT) comparing the efficacy of metformin and glimepiride in monotherapy of T2DM. Methods: A literature search for RCTs on glimepiride and metformin was conducted on the bibliographic databases, including PubMed, Cochrane Library and ScienceDirect, from their inceptions to 25 Mar 2013. All RCTs were selected according to pre-specified eligibility criteria. The quality of articles was assessed with the Cochrane’s risk of bias tool. Statistical meta-analysis evaluated the overall effects and biochemical indices of T2DM. Sensitivity and subgroup analyses evaluated the robustness and explained the heterogeneity of the results. Begg and Egger’s tests quantified possible publication biases. Results were represented as "standard mean difference or odds ratio [95% confidence internals] P value". Results: Fifteen RCTs with 1681 adult T2DM patients were included for meta-analysis. Metformin was not better than glimepiride in overall efficacy in controlling the levels of HbA1c, postprandial blood sugar (PPBS), fasting plasma insulin (FINS), systolic and diastolic blood pressures (SBP and DBP), and high density lipoprotein (HDL). Metformin was only more effective than glimepiride in controlling the levels of total cholesterol (TC, 0.33 [0.03, 0.63], P = 0.03), low-density lipoprotein (LDL, 0.35 [0.16, 0.53], P = 0.0002) and triglycerides (TG, 0.26 [0.05, 0.46], P = 0.01). Odds ratios of adverse events showed that glimepiride was more likely to induce hypoglycemia episodes and metformin was with a higher risk of gastrointestinal upset. Conclusion: Metformin was not significantly better than glimepiride in glycemic control of T2DM, suggesting that glimepiride would be a good choice second to metformin in the monotherapy of T2DM.

Background: Few microRNAs were found consistently dysregulated in type 2 diabetes (T2D) that would gain confidence from Big Pharma to develop diagnostic or therapeutic biomarkers. This study aimed to corroborate evidence from eligible microRNAs-T2D association studies according to stringent quality criteria covering both biological and statistical significance in T2D for biomarker development. Methods and analyses: Controlled microRNA expression profiling studies on human with T2D will be retrieved from PubMed, ScienceDirect, and Embase for selecting the statistically significant microRNAs according to pre-specified search strategies and inclusion criteria. Multiple meta-analyses with restricted maximum-likelihood estimation and empirical Bayes estimation under the random-effects model will be conducted by metafor package in R. Subgroup and sensitivity analyses further examine the microRNA candidates for their disease specificity, tissue specificity, blood fraction specificity, and statistical robustness of evidence. Biologically relevant microRNAs will then be selected through genomic database corroboration. Their association with T2D is further measured by area under the curve (AUC) of receive operating characteristic (ROC). Meta-analysis of AUC of potential biomarkers will also be conducted. Enrichment analysis on potential microRNA biomarkers and their target genes will be performed by iPathwayGuide and clusterProfiler, respectively. The corresponding reporting guidelines will be used to assess the quality of included studies according to their profiling methods (microarray, RT-PCR, and RNA-Seq). Ethics and dissemination: No ethics approval is required since this study does not include identifiable personal patient data. Protocol registration number: CRD42017081659.

Introduction. The oral microbiota is the second most complex microbial community in the human body. It has been suggested that poor oral health may be associated with an increased risk of obesity. Hypothesis/Gap Statement. However, both previous observational and mechanistic studies on oral microbiota do not take into account the obesity-related acanthosis nigricans (AN), which is the most common dermatological manifestation in individuals with obesity. Aim. This study aimed to investigate the altered composition, function and diagnostic value of the oral microbiota in obesity with or without acanthosis nigricans (AN). Methodology. We characterized the oral bacteria signature in a Chinese cohort (ChiCTR2300073353) of 99 patients with obesity and obesity-related AN (Ob_AN) and 50 healthy controls using 16S rRNA gene V3–V4 region sequencing. Results. The microbial richness (abundance-based coverage estimators and observed species indices) was significantly greater in the Ob_AN and obesity groups than in the control group; however, microbial diversity (Shannon index) did not differ significantly. Distinct separation in the microbial community amongst the three groups was observed. Prevotella species, including Prevotella melaninogenica, Prevotella nanceiensis and Prevotella pallens, were associated with composition alterations and predicted functions (significant downregulation of ATP-binding cassette transporters) associated with microbial dysbiosis in the obesity and Ob_AN groups. Moreover, Prevotella and Lautropia genera assessments could indicate obesity and obesity-related AN risk. Conclusions. The notable reduction of plenty of oral microbiota and high levels of Prevotella spp. may play a critical role in obesity with AN. Oral microbiota may serve as biomarkers for diagnosing, preventing and even treating obesity-related AN.