Metronidazole Metabolism in Neonates and the Interplay Between Ontogeny and Genetic Variation
Bibliographic record
Abstract
Metronidazole is commonly used to treat intra-abdominal infections in neonates.1,2 The parent drug is converted to 5 metabolites, with 2-hydroxy-metronidazole being the most clinically significant, as it possesses 30–65% of the antimicrobial activity of the parent compound.3,4 In vitro studies have demonstrated that cytochrome P450 2A6 (CYP2A6) is the primary catalyst responsible for metronidazole hydroxylation.5 This enzyme is initially expressed at low levels at birth, with expression increasing over the course of the first year of life to reach adult levels.6 CYP2A6 is known to be a highly polymorphic gene with more than 45 variant alleles that result in inactive to ultra-rapid metabolizer phenotypes. Additionally, certain allelic variants such as CYP2A6*17 have amino acid changes that alter metabolism for some but not other substrates, resulting in different metabolizing phenotypes for the same genotype.7 The role of genetic variation on variable metronidazole metabolism in neonates has not been previously described, nor has the effect of CYP2A6*17 on metronidazole been characterized. As such, the objective of this study was to evaluate the effect of CYP2A6 genetic variation on the pharmacokinetics of metronidazole in a small cohort of preterm neonates.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".