Consumption of whole purple and regular wheat modestly improves metabolic markers in adults with elevated high-sensitivity C-reactive protein: a randomised, single-blind parallel-arm study
Bibliographic record
Abstract
Whole-grain wheat, in particular coloured varieties, may have health benefits in adults with chronic metabolic disease risk factors. Twenty-nine overweight and obese adults with chronic inflammation (high-sensitivity C-reactive protein) > 1·0 mg/l) replaced four daily servings of refined grain food products with bran-enriched purple or regular whole-wheat convenience bars (approximately 41-45 g fibre, daily) for 8 weeks in a randomised, single-blind parallel-arm study where body weight was maintained. Anthropometrics, blood markers of inflammation, oxidative stress, and lipaemia and metabolites of anthocyanins and phenolic acids were compared at days 1, 29 and 57 using repeated-measures ANOVA within groups and ANCOVA between groups at day 57, with day 1 as a covariate. A significant reduction in IL-6 and increase in adiponectin were observed within the purple wheat (PW) group. TNF-α was lowered in both groups and ferulic acid concentration increased in the regular wheat (RW) group. Comparing between wheats, only plasma TNF-α and glucose differed significantly (P < 0·05), that is, TNF-α and glucose decreased with RW and PW, respectively. Consumption of PW or RW products showed potential to improve plasma markers of inflammation and oxidative stress in participants with evidence of chronic inflammation, with modest differences observed based on type of wheat.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".