Effect of inulin supplementation on MDA level and expression of pyroptosis-related genes in type 2 diabetic patients
Bibliographic record
Abstract
Introduction: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder with significant health implications. Probiotic fibers like inulin have shown the potential to improve glucose metabolism by modulating gut microbiota and related signaling pathways. This study focuses on the effect of inulin on malondialdehyde (MDA) level and expression of pyroptosis-related genes (TLR4, ASC, NLRP3, and caspase-1) in type 2 diabetic patients. Methods: In the current clinical trial, 46 patients with T2DM were randomly allocated into inulin (n=23) or placebo (n=23) group for eight weeks. Pyroptosis-related genes expression analysis was performed using real-time polymerase chain reaction (PCR). Findings: Inulin supplementation significantly reduced weight, body mass index (BMI), and waist/hip circumferences. However, no significant changes were observed in Pyroptosis-related genes expression (TLR4, ASC, NLRP3, caspase-1) or MDA serum levels. Baseline differences in dietary intake were adjusted during the analysis. Conclusion: Inulin supplementation is linked to reductions in body weight, BMI, waist and hip circumference. However, no significant association was observed with serum MDA levels or the expression of TLR4, ASC, NLRP3, and caspase-1 genes. Trial Registration: Identifier: IRCT201605262017N29; https://irct.behdasht.gov.ir/.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 | 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".