Cytokine imbalance in irritable bowel syndrome: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Irritable bowel syndrome (IBS) is a functional gastrointestinal disorder of unknown etiology; although infection and inflammation have recently been considered as important etiologic agents. A recent meta-analysis showed correlations between cytokine [interleukin-10 (IL-10) and tumor necrosis factor (TNF)] gene polymorphisms and IBS; however, it is still unknown whether patients with IBS have different cytokine profiles compared to healthy population. METHODS: To determine the relationships between serum/plasma levels or mucosal expression of IL-10/TNF-α and IBS, we conducted a systematic review and meta-analysis based on case-control studies retrieved from PubMed and EMBASE search through August 2013. Standardized mean difference (SMD) was generated by using the inverse variance method. Heterogeneity was assessed based on I(2) values. KEY RESULTS: Serum/plasma levels of TNF-α tended to be higher in IBS vs controls (p = 0.09); this reached significance in IBS subtypes vs controls and in female patients with IBS. However, serum/plasma levels of IL-10 were not significantly different in IBS patients vs controls. Further analysis of serum/plasma IL-10 levels in IBS subtypes did not show any difference; however, analysis based on gender showed a significantly lower serum/plasma IL-10 levels in male patients with IBS vs male controls (p = 0.02). Colonic IL-10 mRNA had a significantly lower expression in IBS vs control (p = 0.001). CONCLUSIONS & INFERENCES: There is an imbalance of proinflammatory TNF-α, and anti-inflammatory IL-10, cytokines in IBS. Stratifying IBS patients based on cytokine profile may represent an opportunity for personalized treatment of this condition.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.025 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".