Effects of inulin supplementation on inflammatory biomarkers and clinical symptoms of women with obesity and depression on a calorie-restricted diet: a randomised controlled clinical trial
Bibliographic record
Abstract
Abstract Major depressive disorder (MDD) is regarded as an inflammatory disorder. Gut microbiota dysbiosis, observed in both MDD and obesity, leads to endotoxemia and inflammatory status, eventually exacerbating depressive symptoms. Manipulation of gut microbiota by prebiotics might help alleviate depression. The present study aimed to investigate the effects of inulin supplementation on psychological outcomes and biomarkers of gut permeability, endotoxemia, inflammation, and brain-derived neurotrophic factor (BDNF) in women with obesity and depression on a calorie-restricted diet. In a double-blind randomised clinical trial, forty-five women with obesity and MDD were allocated to receive 10 g/d of either inulin or maltodextrin for 8 weeks; all the patients followed a healthy calorie restricted diet as well. Anthropometric measures, dietary intakes, depression, and serum levels of zonulin, lipopolysaccharide (LPS), inflammatory biomarkers (TNF- α , IL-10, monocyte chemoattractant protein-1, toll-like receptor-4 and high-sensitivity C-reactive protein), and BDNF were assessed at baseline and end of the study. Weight and Hamilton Depression Rating Scale (HDRS) scores decreased in both groups; between-group differences were non-significant by the end of study ( P = 0·333 for body weight and P = 0·500 for HDRS). No between-group differences were observed for the other psychological outcomes and serum biomarkers ( P > 0·05). In this short-term study, prebiotic supplementation had no significant beneficial effects on depressive symptoms, gut permeability, or inflammatory biomarkers in women with obesity and depression.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".