Iron and complementary feeding of breast‐fed infants (247.3)
Bibliographic record
Abstract
The American Pediatric Society and Health Canada both recommend that iron fortified cereal (most iron unabsorbed) or meat (most iron absorbed) be introduced to all breast‐fed infants at six months of age to support iron stores and linear growth. Evidence suggests that the iron contained in these foods, particularly cereal, is not fully absorbed and will collect in the colon with the possibility of free radical generation and intestinal inflammation. Objectives: To assess the safety of the recommended first solid food for exclusively breast‐fed infants from a free radical perspective. Methods: Ninety exclusively breastfed infants are being randomized to 1 of 3 feeding groups: iron fortified cereal (FeCer), iron fortified cereal with fruit (FeCF) or meat (M). Urine and stool samples are collected before introduction of study foods (4‐5.5 months) and 3 weeks after introduction of these foods to assess: urinary F2 isoprostanes (LC‐MS‐MS), urinary 8OH‐deoxy guanosine, fecal calprotectin (ELISA), reactive oxygen species (ROS‐HPLC) and non‐heme iron generation (Colorimetric) in the stool, and the fecal microbiome by 16S RNA gene pyrosequencing. Preliminary results are: urinary isoprostanes (base: 10.1+7.2; after feeds 12.8 + 7.6 ng/mg/ml creatinine; n=25) did not differ over time or between feeding groups at either baseline or after feeds. ROS did not differ between groups at either sampling time nor within the FeCF and M group over time, however there was a trend to increased free radical generation in the FeCer group (base: 0.018 + 0.019; after feeds 0.037 + 0.015 RU; n=12; P = 0.087). Conclusion: Our hypothesis was that iron fortified cereals would provide unabsorbed iron that would reduce the ability of the colon to resist oxidative stress and has been supported from this preliminary subset. The newborn breast‐fed infant may not cope with large amounts of unabsorbed iron in the colon. Grant Funding Source : Supported by CIHR
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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 | 0.001 |
| 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) | 0.002 | 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".