Effects of infant formula, cow milk and human milk on drug metabolizing enzymes
Bibliographic record
Abstract
Background Caffeine, used for treating neonatal apnea, is eliminated 3-fold slower in breastfed infants than in formula-fed infants. Caffeine is metabolized by cytochrome P450 (CYP) 1A and CYP3A4, which are regulated by aryl hydrocarbon receptor (AhR) and pregnane X receptor (PXR) respectively. Here we hypothesized that formula but not human milk induces CYP1A and/or CYP3A4 via their regulatory pathways. Methods Human milk samples from healthy lactating women were collected. Infant formula and cow milk were purchased. Lipid fraction of milk samples was obtained by organic extraction. mRNA and protein expression were measured by RT-PCR and western blotting. Reporter plasmids containing receptor response elements were tested for their activation. Results CYP1A expression and AhR activity were induced by formula and cow milk but not by human milk. The AhR activation by formula was abolished by co-treatment of Ah antagonist. Formula and human milk also had differential effects on AhR activation by dibenz[a,h]anthracene, an AhR agonist. In addition, lipid fraction of formula but not human milk activated AhR. Both formula and human milk showed mild induction of CYP3A4 mRNA and PXR. However, co-transfection of hPXR did not increase PXR activation by milk treatments, suggesting a non PXR-mediated pathway. Conclusion Infant formula but not human milk contains AhR agonist(s) that induces CYP1A expression. Both infant formula and human milk induce CYP3A4 through non PXR-mediated pathway. Clinical Pharmacology & Therapeutics (2005) 77, P46–P46; doi: 10.1016/j.clpt.2004.12.068
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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 | 0.000 |
| 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".