The effect of date seed powder supplementation on anxiety- and depression-like behaviours, sleep quality and tryptophan–kynurenine metabolism in patients with type 2 diabetes: targeting gut–brain axis
Bibliographic record
Abstract
Abstract Recently, functional foods have been considered as an effective approach in management of type 2 diabetes mellitus. This trial aimed to evaluate the potential benefits of date seed powder (DSP) on inflammation anxiety- and depression-like behaviours, sleep quality and tryptophan (TRP)–kynurenine (KYN) metabolism in type 2 diabetes mellitus patients. In this trial, forty-three patients with type 2 diabetes were randomised to two groups: either 5 g/d of the DSP or placebo for 8 weeks. Depression, anxiety and stress scale, sleep quality, quality of life (QoL), levels of fasting blood glucose, endotoxin, anti-inflammatory/pro-inflammatory biomarkers, hypothalamus–pituitary–adrenal (HPA) axis-associated biomarkers (including brain-derived neurotrophic factor (BDNF)), KYN, TRP, cortisol and adrenocorticotropic hormone (ACTH) were assessed at baseline and after 8 weeks. An independent t test was used for baseline comparisons, while ANCOVA was used for post-intervention between-group comparisons. The results showed that supplementation with DSP significantly improved depression, anxiety and stress scale, sleep quality and QoL in comparison with placebo. In terms of biochemical parameters, the intervention group exhibited significantly reduced levels of endotoxin, and cortisol, KYN, KYN:TRP ratio as well as significantly elevated levels of IL-10, TRP concentrations and IL-10:IL-18 ratio compared to the placebo group. Changes in fasting sugar, C-reactive protein (hs-CRP), IL-18, ACTH, BDNF concentrations and cortisol:ACTH ratio were not different between groups. Supplementing with date seed may effectively improve anxiety- and depression-like behaviours, sleep quality and QoL by modulating metabolic endotoxemia, inflammation and HPA axis activity in patients with type 2 diabetes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 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".