Effects of a calcium (Ca) supplement (1000 mg) and a capsule containing vitamins C (500 mg) and B6 (75 mg) + proline (500 mg) on cardiovascular disease (CVD)‐related factors in osteopenic women.
Bibliographic record
Abstract
Nutritional intervention studies on CVD‐related factors in relation to vitamins and minerals are limited although they are known to play an essential role. Women (35–55 yrs old) in the present study were participants in a preventive Osteoporosis project whose selection criteria were to be healthy (no metabolic abnormality), active, non‐obese, non‐smoker, and not being on estrogen, drugs, nutritive supplements or a vegetarian diet. They were classified according to their bone mineral density (BMD). Group A (normal BMD; n=20) and two osteopenic groups B and C (n=20 in each) received respectively a placebo, Ca alone or combined to a vitamin‐proline capsule, to take daily for one year. Compliancy to the prescription in group C was verified by plasma (P) and erythrocyte (E) pyridoxal phosphate concentrations (vitamin B6 active form). At baseline, the 3 groups were comparable for age, physical activity, dietetic and anthropometric aspects, serum estradiol and all other biochemical parameters of interest. HDL increased (p<0.03) in the placebo group after the intervention. No changes occurred in the Ca group. PPLP and EPLP in group C were 3.7 and 6.8‐fold increased, respectively. Reductions of total cholesterol (p<0.02), LDL (p<0.02) and triglycerides (p<0.003) and the elevation of HDL (p<0.002) were all significant in this group. Only a trend (p<0.09) toward a reduction was observed for hCy. This study involving vitamins C and B6 clearly showed consistent beneficial effects on CVD‐related factors whereas Ca had no effect.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".