Avenanthramide‐Enriched Oats Have an Anti‐Inflammatory Action: A Pilot Clinical Trial
Bibliographic record
Abstract
Regular consumption of oats has been shown to benefit heart health by lowering serum lipids in humans, an effect mediated primarily via beta-glucan. Other components of oats, including the polyphenolic avenanthramides (AV), may also contribute to reducing the risk of atherogenesis. In vivo, oat AV enhance antioxidant activity, and in vitro, these compounds attenuate the expression and/or secretion of pro-inflammatory cytokines and chemokines. The anti-inflammatory properties of oat AV in a whole food form (oat flour) have only recently been demonstrated in humans. To determine whether the AV-enriched bran from “false malted” oat kernels (US Patent Application 20120082740) reduces biomarkers of inflammation, we conducted a randomized, placebo-controlled, double-blind pilot study in 16 healthy men and postmenopausal women age 蠅45 y and BMI of 28-38 kg/m2 with central adiposity. Subjects consumed daily either a smoothie made with AV-enriched oat bran (containing 90 mg AV) or a macronutrient and fiber-matched placebo absent oats for 8 wk. Fasting blood samples were collected at baseline, 4, and 8 wk. Among subjects with CRP levels 蠅3.0 mg/L, the oat smoothie lowered VCAM-1 concentrations at 4 wk (P=0.031) and 8 wk (P>0.05) by 13 and 10%, respectively, compared to placebo. Non-significant reductions at 4 and 8 wk of 18 and 43%, respectively, were observed for serum amyloid A-1, an acute phase reactant in inflammation. These pilot data suggest that consuming AV in whole food form, i.e., AV-enriched oat bran, may affect specific biomarkers of inflammation in older, overweight or obese adults. (Supported by USDA and AAFC)
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".