Effect of the mediterranean diet with and without weight loss on markers of inflammation in men with metabolic syndrome
Bibliographic record
Abstract
OBJECTIVE: Intervention studies on the Mediterranean Diet (MedDiet) have often led to weight loss, which may have contributed to the purported anti-inflammatory effects of the MedDiet. To investigate the impact of the MedDiet consumed under controlled feeding conditions before (-WL) and after weight loss (+WL) on markers of inflammation in men with metabolic syndrome (MetS). DESIGN AND METHODS: Subjects (N = 26, male, 24-65 years) with MetS first consumed a North American control diet for 5 weeks followed by a MedDiet for 5 weeks both in isocaloric feeding conditions. After a 20-week weight loss period in free-living conditions (10 ± 3% reduction in body weight, P < 0.01), participants consumed the MedDiet again under isocaloric-controlled feeding condition for 5 weeks. RESULTS: MedDiet - WL significantly reduced plasma C-reactive protein (CRP) concentrations (-26.1%, P = 0.02) and an arbitrary inflammatory score (-9.9%, P = 0.01) that included CRP, interleukin-6 (IL-6), IL-18, and tumor necrosis factor-α (TNF-α) compared with the control diet. The MedDiet + WL significantly reduced plasma IL-6 (-20.7%) and IL-18 (-15.6%, both P ≤ 0.02) concentrations compared with the control diet but had no further significant impact on plasma CRP concentration. Participants with a reduction in waist circumference ≥8.5 cm after MedDiet + WL showed significantly greater reductions in inflammation markers than those with a change in waist circumference <8.5 cm. CONCLUSIONS: Thus, consuming MedDiet even in the absence of weight loss significantly reduces inflammation. However, the degree of waist circumference reduction with weight loss magnifies the impact of the MedDiet on other markers of inflammation associated with MetS in men.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".