Comparing Gut Microbiota Discrepancies between Primary Sjogren's Syndrome and Healthy Controls: A Systematic Review
Bibliographic record
Abstract
Abstract Background: The importance of the gut microbiota in primary Sjogren’s syndrome is gaining significant recognition. This systematic review summarized the previous findings on the discrepancies in gut microbiota between patients with primary Sjogren’s syndrome and healthy controls. Methods: From the establishment of the database until September 1, 2023, we conducted searches using electronic databases. We were interested in identifying specific bacterial changes between primary Sjogren’s syndrome and healthy controls as our primary outcomes. Secondary outcomes included exploring the relationship between gut microbiota and clinical parameters. To assess the quality of the included studies, we used the Newcastle-Ottawa scale. Results: A total of 9 articles were included in the analysis, comprising 504 case groups and 1313 control groups. According to two or more of the included studies, it was found that the gut microbiota of primary Sjogren’s syndrome patients was characterized by decreased butyrate-producing bacteria and increased pro-inflammatory microorganisms, as well as significantly lower levels of Actinobacteria, Firmicutes, Fusobacteria, and Proteobacteria. Furthermore, the Firmicutes/Bacteroidetes ratio was lower in patients with primary Sjogren’s syndrome than in controls. Finally, it was found that Roseburia has been shown to have a negative correlation with disease activity, as well as a negative correlation with IL-12 and IL-6. Conclusions: Patients with primary Sjogren’s syndrome exhibited reduced diversity in their gut microbiota and decreased abundance of short-chain fatty acid producers, which may offer potential therapeutic targets for future interventions. Trial registration: CRD42023421915.
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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 | 0.008 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".