Impact of the Mediterranean diet and weight loss on plasma cell adhesion molecule concentrations in men with the metabolic syndrome
Bibliographic record
Abstract
This study examined the impact of the Mediterranean diet (MedDiet) consumed under controlled feeding conditions, with and without weight loss, on plasma cell adhesion molecule (CAM) concentrations in men with the metabolic syndrome (MS). Twenty‐six men (age: 24–62 years) with the MS first consumed a control Western‐type diet for 5 weeks followed by a 5‐week MedDiet, both under weight‐maintaining isocaloric feeding conditions. They then underwent a 20‐week caloric restriction phase that led to a 10.2 ± 2.9% reduction in body weight (P <0.01), followed by the consumption of an isocaloric MedDiet for 5 weeks. All foods including red wine were provided during the isocaloric phases of the study. Although there was no change in any of the vascular CAM after the MedDiet without weight loss, participants with high E‐selectin at baseline (above median, 36.8 ng/mL) showed greater reductions in plasma E‐selectin levels on the MedDiet without weigh loss than those with low plasma E‐selectin at baseline (P for interaction <0.01). The MedDiet combined with weight loss reduced plasma intercellular CAM concentrations by 10.9% (P <0.01) compared with the control diet and by 6.8% (P =0.068) compared with the MedDiet without weight loss. These data suggest that weight loss may be required for the MedDiet to improve CAM levels in men with the MS.
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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 | 0.001 |
| 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) | 0.001 | 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".