Favourable impact of low-calorie cranberry juice consumption on plasma HDL-cholesterol concentrations in men
Bibliographic record
Abstract
A low HDL-cholesterol concentration is an independent risk factor for CVD. Studies have suggested that flavonoid consumption may be cardioprotective, and a favourable impact on circulating HDL-cholesterol concentrations has been suggested to partially explain this association. The aim of the present study was to determine the effect of consuming increasing daily doses of low-calorie cranberry juice cocktail (CJC) on the plasma lipid profile of abdominally obese men. For that purpose, thirty men (mean age 51 (SD 10) years) consumed increasing doses of CJC during three successive periods of 4 weeks (125 ml/d, 250 ml/d, 500 ml/d). Before the study and after each phase, we measured changes in physical and metabolic variables. We noted a significant increase in plasma HDL-cholesterol concentration after the consumption of 250 ml CJC/d (+8.6+/-14.0% v. 0 ml CJC/d; P<0.01), an effect that plateaued during the last phase of the study (500 ml CJC/d: +8.1+/-10.0% v. 0 ml CJC/d; P<0.0001). Multivariate analyses revealed that changes in plasma apo A-I (R(2)=48%, P<0.0001) and triacylglycerol (R(2)=16%, P<0.005) concentrations were the only variables significantly contributing to the variation in plasma HDL-cholesterol concentration noted in response to the intervention. No variation was observed in total as well as in LDL and VLDL cholesterol. The present results show that daily CJC consumption is associated with an increase in plasma HDL-cholesterol concentrations in abdominally obese men. We hypothesise that polyphenolic compounds from cranberries may be responsible for this effect, supporting the notion that the consumption of flavonoid-rich foods can be cardioprotective.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".