The interactive effect of vitamin D3 supplementation and vitamin D receptor polymorphisms on weight and body composition in overweight women with hypovitaminosis D: a randomized, double-blind, placebo-controlled clinical trial
Bibliographic record
Abstract
Different responses to vitamin D supplementation may be due to genes involved in vitamin D metabolism, including the vitamin D receptor ( VDR) gene. The present study aimed to determine the interactive effect of vitamin D supplementation and VDR polymorphisms, including FokI (rs2228570) and BsmI (1544410) on weight and body composition in overweight women with hypovitaminosis D. This study comprised two phases: a double-blind, randomized and a before-after clinical trial. In the first phase, 50 healthy overweight women aged 20–45 years with hypovitaminosis D were randomly categorized into intervention and control groups and were given 50 000 IU/w vitamin D3 or placebo for 12 weeks. In the second phase, 75 women received 50 000 IU/w of vitamin D3 for 12 weeks. All variables were measured at baseline and after 12 weeks. Circulating 25(OH)D was measured using an ELISA kit. Anthropometric indices were calculated according to standard protocol (WHO-TRH-854). Body composition was determined using the body impedance analysis method. The VDR polymorphisms were detected using the PCR sequence. Supplementation resulted in a significant increase in the level of 25(OH)D in the intervention group but did not affect the anthropometric profile of the subjects. When considering FokI genotypes, carriers of the FF genotype had higher fat mass reduction than carriers of Ff + ff genotypes.
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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) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".