Effects of n‐3 PUFA supplementation with or without low‐calorie cranberry juice cocktail on flow‐mediated vasodilation in men
Bibliographic record
Abstract
Consumption of fish as well as fruits and vegetables have been shown to have favorable effects on CVD risk. The present study was therefore undertaken in order to compare the effects of fish oil (FO) w/wo cranberry juice cocktail (CJC) supplementation on flow‐mediated vasodilation (FMD) in men. A group of 53 men was divided into 4 groups: 1) placebo, n=11, 2) 500 mL/day CJC, n=13, 3) 2.4 g/day of FO, n=15 and 4) CJC+FO, n=14. Before and after the intervention, FMD was measured by ultrasound echography of the brachial artery at 60 and 90 seconds after hyperemia. We found no difference in baseline brachial artery diameter (AD), FMD60 and FMD90 between the four groups. We noted that FMD60 (1.2 ± 1.8 %, p=0.029) and FMD90 (+2.5 ± 3.2 %, p=0.013) were significantly improved following the intervention in CJC+FO individuals only. CJC subjects showed no improvement in FMD but displayed a significantly increased resting brachial AD (+0.20 ± 0.24 mm, p=0.013) after the intervention. We also found that changes in FMD60 and FMD90 were negatively associated with brachial AD. In summary, we found that CJC+FO supplementation improved FMD in healthy overweight subjects and that drinking CJC on daily basis for 12 weeks was associated with an increase in resting brachial AD. Further studies are needed to confirm our results and verify the clinical relevance of our observations. Supported by the Canadian Institutes of Health Research (MOP‐64438)
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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) | 0.001 | 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 | 0.001 | 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".