Oral administration of lactoferrin increases hemoglobin and total serum iron in pregnant womenThis paper is one of a selection of papers published in this Special Issue, entitled 7th International Conference on Lactoferrin: Structure, Function, and Applications, and has undergone the Journal's usual peer review process.
Bibliographic record
Abstract
Iron deficiency anemia (IDA) during pregnancy continues to be of world-wide concern. IDA is a risk factor for preterm delivery and subsequent low birth weight, and possibly for poor neonatal health. Iron supplementation in pregnancy is a widely recommended practice, yet intervention programs have met with many controversies. In our study, 300 women at different trimesters of pregnancy were enrolled in a trial of oral administration of ferrous sulfate (520 mg once a day) or 30% iron-saturated bovine lactoferrin (bLf) (100 mg twice a day). Pregnant women refusing treatment represented the control group. In this group hemoglobin and total serum iron values measured after 30 d without treatment decreased significantly, especially in women at 18-31 weeks of pregnancy. In contrast, after 30 d of oral administration of bLf, hemoglobin and total serum iron values increased and to a greater extent than those observed in women treated orally for 30 d with ferrous sulfate, independently of the trimester of pregnancy. Unlike ferrous sulfate, bLf did not result in any side effects. These findings lead us to hypothesize that lactoferrin could influence iron homeostasis directly or through other proteins involved in iron transport out of the intestinal cells into the blood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".