Effect of maternal and infant selenium status on child growth in a birth cohort from Dhaka, Bangladesh
Bibliographic record
Abstract
Abstract Deficiency of selenium, an essential trace element, has been implicated in adverse birth outcomes and the growth of infants and young children. We used data from a randomized controlled trial to examine associations between selenium biomarkers in whole blood (WBSe), serum and selenoprotein P (SEPP1) in maternal delivery and venous cord (VC) blood, and birth weight, and adverse birth outcomes. Furthermore, we examined associations between selenium biomarkers and infant growth outcomes (age adjusted length, weight, head circumference and weight-for-length z-scores) at birth, one, and two years of age using linear regression. WB and serum selenium in delivery and VC specimens were negatively associated with birth weight (adjusted β, 95% CI: WBSe delivery: -26.6 (−44.3, -8.9); WBSe VC: -19.6 (−33.0, -6.1)); however, delivery SEPP1 levels (adjusted β: -37.5 (−73.0, -2.0)) and VC blood (adjusted β: 82.3 (30.0, 134.7)) showed inconsistent associations across biomarkers. We found small to moderate associations between infant growth and WBSe VC (LAZ β, 95% CI, at birth: -0.05 (−0.1, -0.01)); 12-months (β: -0.05 (−0.08, -0.007)). WAZ also showed weak negative associations with delivery WBSe (at birth: -0.07 (−0.1, -0.02); 12-months: -0.05 (−0.1, -0.005)) and in WBSe VC (β at birth: -0.05 (−0.08, -0.02); 12-months: -0.05 (−0.09, -0.004)). Mechanisms connected to redox biology and its antioxidant effects have been causally associated with selenium’s protective properties. Given the fine balance between nutritional and toxic properties of selenium, it is possible that WB and serum selenium may negatively impact growth outcomes, both in utero and postpartum.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".