Alterations in Gastric Mucosal Microbiota in Gastric Carcinogenesis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The gastric microbiota profile alters during gastric carcinogenesis. We aimed to identify the alterations in the alpha diversity and relative abundance of bacterial phyla and genera of gastric microbiota in the development of gastric cancer (GC). Methods: The systematic review was performed based on a published protocol with the registration number CRD42020206973. We searched through PubMed, EMBASE and Cochrane databases, as well as conference proceedings and references of review articles (May 2021) for observational studies reporting either the relative abundance of bacterial phyla or genera, or alpha diversity indexes in both GC and non-cancer groups. Selection of studies and data extraction were performed independently by two researchers, with disagreements resolved through discussion. Risk of bias was assessed using the self-modified Newcastle-Ottawa Scale. Results of random-effects meta-analyses were presented as mean differences (MD). Results: Our systematic review included 751 GC patients and 792 non-cancer patients from 14 case-control studies. Gastric cancer group had fewer operational taxonomic units (OTUs) (MD = −68.52, 95%CI: −126.65 to −10.39) and a lower Simpson index (MD = −0.13, 95%CI: −0.20 to −0.07) compared with non-cancer group. At the phylum level, gastric cancer group had a higher abundance of Firmicutes (MD = 7.11, 95%CI: 1.76 to 12.46). At the genus level, Streptococcus (MD = 3.03, 95%CI: 0.07 to 6.00) and Lactobacillus (MD = 5.15, 95%CI: 1.27 to 9.04) were found to be enriched in GCgroup. The relative abundance of the rest bacterial phyla or genera analyzed in our study did not significantly differ between two groups. Subgroup analyses indicated that the source of samples was the major source of interstudy heterogeneity. Conclusion: This systematic review suggested that gastric microbiota dysbiosis occurred in gastric carcinogenesis, with alpha diversity declined and microbiota composition altered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".