Effect of Prenatal Vitamin D Supplementation on Placental Angiogenic Factors in Bangladesh (FS08-07-19)
Bibliographic record
Abstract
To determine the effect of prenatal vitamin D supplementation on expression of angiogenic factors in the placenta. This is a secondary analysis of the Maternal Vitamin D for Infant Growth trial, a randomized controlled trial of maternal vitamin D supplementation in Dhaka, Bangladesh. We examined the expression of angiogenic factors in placental tissues. Women (n = 1300) were enrolled at 17–24 weeks gestation and randomized to receive: placebo, 4200 IU/week, 16,800 IU/week or 28,000 IU/week until delivery. We examined a subset of randomly selected placentas (n = 80) collected at birth, which included 20 tissues (10 male & 10 female offspring) from each treatment group in maternal/fetal pairs. A full thickness placental core was collected; fixed in formalin and embedded in paraffin. Tissue sections were stained for vascular endothelial growth factor (VEGF) and placental growth factor (PlGF) using immunofluorescence. ImageJ was used to quantify intensity and % area of expression. T-tests were used to estimate the effects of each vitamin D dose on expression of angiogenic factors, compared to placebo. Interactions by fetal sex were also examined. The mean (SD) for % area of expression was 17.0 (4.0) for VEGF and 14.8 (1.9) for PlGF. The mean (SD) for intensity was 6520 (1549) for VEGF and 5716 (734) for PlGF. There were no significant differences in VEGF and PlGF between any vitamin D treatment groups versus placebo for % area or intensity of expression (Table 1). The effect of vitamin D treatment was not modified by fetal sex. Vitamin D supplementation starting from mid-pregnancy until delivery did not effect expression of two key angiogenic factors in the placenta at term. The impact of periconception vitamin D supplementation on expression of angiogenic factors in the placenta remains unknown. Bill and Melinda Gates Foundation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".