Ontogeny of rat CYP2E1 and CYP1A2 : a characterization and a pharmacokinetic model
Bibliographic record
Abstract
Infantile exposure to xenobiotics, e.g. from breastfeeding, poses a serious toxicity risk. Since the toxicokinetic mechanisms that principally determine exposure outcomes undergo a significant developmental maturation, infants may respond to exposures in a different way than adults. Hence, suitable model systems are required to provide risk relevant information in pediatric populations. This dissertation's primary goal was to provide a critical evaluation of two such model systems; first, a pharmacokinetic model that may predict an infant's capacity to eliminate toxicants by cytochrome P-450 (CYP) mechanisms and second, the developing rat as a model of human CYP2E1 and CYP1A2 ontogeny.\n\nThe first objective was to evaluate underlying assumptions of a pharmacokinetic model that describes the ontogeny of hepatic CYP activity using the rat. The study recognized some discrepancies with the stated assumptions. The impact of these discrepancies on the potential applicability of the model is discussed. As proof-of-concept, the observed data were fit to a model describing rat CYP2E1 and CYP1A2 ontogeny. A reasonable correlation (r = 0.75) was observed between observed and predicted oral clearance values of a CYP2E1 substrate indicating the potential applicability of such a model in risk assessment.\n\nThe second objective was to conduct an extensive characterization of rat hepatic CYP2E1 and CYP1A2 ontogeny at mRNA, protein, activity and intrahepatic expression levels. The results were compared to available human data to determine the appropriateness of the rat for assessment of toxicokinetic mechanisms underlying age-dependent differences in susceptibility to toxicity. Similarities in age-dependent changes in mRNA, activity and zonal hepatic expression patterns were noted between the rat and human prior to weaning. Unlike human data, rats show good correlation between changes in CYP2E1 and CYP1A2 activity and transcript levels, but not with the immunoquantifiable protein. Recognizing such similarities and differences between rats and human regarding onset, rate and pattern of CYP ontogeny will improve the accuracy of rat-to-human extrapolation of developmental toxicokinetic data.\n\nOverall, the dissertation research provides mounting and supportive evidence for the use of such model systems in providing risk-relevant information in pediatric populations and to identify toxicokinetic mechanisms underlying age-dependent differences in susceptibility to toxicity.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".