Bioavailability of enteric‐coated microencapsulated calcium during pregnancy: a randomized crossover trial in Bangladesh (804.4)
Bibliographic record
Abstract
Prenatal calcium (Ca) and iron (Fe) supplements are recommended in settings of low dietary Ca intake and high prevalence of anemia. However, concurrent Ca and Fe administration may inhibit Fe absorption. Therefore, we developed a multi‐micronutrient powder containing Fe (60 mg), folic acid (400 µg), and Ca (0.5, 1.0 or 1.5 g) in which calcium carbonate granules were microencapsulated with a pH‐sensitive enteric coating to delay intestinal release and limit Ca‐Fe interactions. To compare the fractional intestinal absorption (fAb) of Ca from enteric‐coated (EC) Ca granules versus uncoated (non‐EC) granules, we conducted a randomized crossover trial among pregnant women (n=49) in Dhaka. fAb was estimated by a dual stable isotope method ( 44 Ca‐labeled granules and intravenous 42 Ca), based on the relative recovery of 44 Ca vs 42 Ca in urine over 48 hours. Mean (±SD) fAb from EC Ca was significantly less than from non‐EC Ca (2.7±2.2 % vs. 16.5±10.0 %; p<0.0001) at all 3 Ca doses. In conclusion, the pH‐sensitive enteric coating substantially reduced Ca absorption. Therefore, in its current formulation this novel enteric‐coated Ca‐Fe supplement is not suitable for clinical use. Grant Funding Source : Supported by Saving Lives at Birth
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".