Physiologically based modeling of <i>p</i>‐<i>tert</i>‐octylphenol kinetics following intravenous, oral or subcutaneous exposure in male and female Sprague–Dawley rats
Bibliographic record
Abstract
The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for p-tert-octylphenol (OP) for understanding the qualitative and quantitative determinants of its kinetics in Sprague-Dawley rats. Compartments of the PBPK model included the liver, richly perfused tissues, poorly perfused tissues, reproductive tissues, adipose tissue and subcutaneous space, in which OP uptake was described as a blood flow- or a membrane diffusion-limited process. The PBPK model successfully simulated previously published data on blood and tissue OP concentrations in Sprague-Dawley rats following oral, intravenous (i.v.) or subcutaneous (s.c.) routes. The model predicted that OP concentrations would reach 6.8, 13.8 and 27.9 ng ml(-1) (male) and 7.2, 14.7 and 31.4 ng ml(-1) (female), 4 h after a single i.v. dose of 2, 4 and 8 mg kg(-1), respectively. The model also predicted that OP concentrations would reach 53.3, 134.8 and 271.2 ng ml(-1) (male) and 87.4, 221.4 and 449.7 ng ml(-1) (female) 4 h after a single oral dose (50, 125 and 250 mg kg(-1)) and that, 4 h after a single s.c. dose (125 mg kg(-1)), OP concentrations would reach 111.3 ng ml(-1) (male) and 121.6 ng ml(-1). A marked sex difference was seen in blood and tissue OP concentrations. This was reflected in the model by a gender-specific maximal velocity of metabolism (V(max)) that was higher (1.77 x) in male than in female rats. Further studies are required to elucidate the mechanism underlying the gender differences and to evaluate whether that is also observed in humans.
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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 | 0.000 | 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 | 0.001 |
| 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".