Effect of high-dose vitamin D supplementation in combination with weight loss diet on glucose homeostasis, insulin resistance, and matrix metalloproteinases in obese subjects with vitamin D deficiency: a double-blind, placebo-controlled, randomized clinical trial
Bibliographic record
Abstract
As there is limited and inconsistent evidence in potential role of vitamin D on insulin resistance and matrix metalloproteinases, this study aimed to examine the effect of vitamin D supplementation on glucose homeostasis, insulin resistance, and matrix metalloproteinases in obese subjects with vitamin D deficiency. A total of 44 participants with serum 25-hydroxyvitamin D (25(OH)D) level ≤ 50 nmol/L and body mass index (BMI) 30–40 kg/m2 were randomly allocated into receiving weight reduction diet with either 50 000 IU vitamin D3 pearl (n = 22) or placebo (n = 22) once weekly for 12 weeks. Primary outcomes were changes in fasting serum glucose (FSG), homeostasis model assessment of insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), and matrix metalloproteinases (MMPs). Secondary outcomes were changes in weight, BMI, 25(OH)D, calcium, phosphorous and parathyroid hormone (PTH). Sun exposure and dietary intakes were also assessed. Serum levels of 25(OH)D3 increased significantly with a simultaneous decrease in serum concentration of PTH in the vitamin D group. Weight, BMI, FSG, and MMP-9 decreased significantly in both groups, and there were significant differences in changes in weight, serum 25(OH)D3, PTH, and MMP-9 levels between the groups. Within- and between-groups analysis revealed no significant differences in serum calcium, phosphorous, serum insulin, HOMA-IR, QUICKI, and MMP-2 after intervention. Our results indicated that improvement in vitamin D status resulted in greater reductions in weight and MMP-9 during weight loss. These preliminary results are sufficient to warrant a bigger study group.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".