Effects of Synbiotics on Inflammatory Markers in Patients With Type 2 Diabetes Mellitus
Bibliographic record
Abstract
INTRODUCTION: With regard to the relationship between inflammation and insulin resistance and due to the lack of researches conducted about the effect of synbiotics on inflammatory markers in diabetes patients, this study was designed to investigate the effect of these markers. METHODS: A double-blind, placebo-controlled trial was conducted among 44 type 2 diabetes patients. They were randomized to symbiotic or placebo group. Patients in the symbiotic group received one symbiotic tablet daily for 8 weeks whereas the placebo group received 1 placebo tablet. The hs-CRP concentration, TNF-α and IL-6 were measured by using ELISA kits. The dietary intakes of patients were assessed at the first and the end of the study and analyzed by Nutritionist IV. Data were analyzed by using SPSS 16.0 via paired and independent t-test. RESULTS: Anthropometric and dietary data were not significantly different between the two groups at the first and the end of the study. The serum concentrations of hs-CRP, IL-6 and TNF-α decreased significantly in the symbiotic group at the end of week 8 compared to baseline (p<0.05). Also, no significant changes were seen in the placebo group (p>0.05). The reduction in inflammatory markers in the symbiotic group were significant in compared to the placebo group (P<0.05). CONCLUSIONS: Symbiotic supplementation can reduce serum hs-CRP, IL-6 and TNF-α concentrations, a risk factor for cardiovascular diseases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".