Maternal vitamin D, oxidative stress, and pre‐eclampsia
Bibliographic record
Abstract
Abstract Objective To examine the associations between risk of pre‐eclampsia and pregnancy levels of maternal 25‐hydroxyvitamin D (25[OH]D) and oxidative stress biomarkers. Methods A nested case–control study (n = 99; 34 cases; 65 controls) within a prospective pregnancy cohort. Maternal 25(OH)D and oxidative stress markers (six isomers of F 2 ‐isoprostanes; F 2 ‐isoPs) were measured in plasma at 12–18 and 24–26 gestational weeks. Vitamin D deficiency was defined as 25[OH]D less than 50 nmol/L. Results Maternal vitamin D deficiency was associated with increased 8‐iso‐PGF 2α ( P = 0.037), 15( R )‐PGF 2α ( P = 0.004), (±)5‐iPF 2α ‐VI ( P = 0.026) at 12–18 weeks. Vitamin D deficiency was inversely associated with 8‐iso‐PGF 2α ( P = 0.019) and (±)5‐iPF 2α ‐VI isomer ( P = 0.010) at 24–26 weeks. Both maternal vitamin D deficiency (adjusted odds ratio [aOR], 4.79; 95% confidence interval [CI], 1.67–13.75) and increased (±)5‐iPF 2α ‐VI (aOR, 2.46; 95% CI, 1.16–5.22) at 24–26 weeks were associated with risk of pre‐eclampsia. However, the interaction test between 25(OH)D and (±)5‐iPF 2α ‐VI was not significant ( P = 0.143). Conclusion Plasma 25(OH)D below 50 nmol/L was associated with increased oxidative stress levels during pregnancy as measured by two F 2 ‐isoP isomers, including the well‐studied marker 8‐iso‐PGF 2α . Whether vitamin D‐induced oxidative stress mediates the risk of pre‐eclampsia warrants future study.
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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 | 0.002 |
| 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".