Somatic and gastrointestinal in vivo biotransformation rates of hydrophobic chemicals in fish
Bibliographic record
Abstract
To improve current bioaccumulation assessment methods, a methodology is developed, applied, and investigated for measuring in vivo biotransformation rates of hydrophobic organic substances in the body (soma) and gastrointestinal tract of the fish. The method resembles the Organisation for Economic Co-operation and Development (OECD) 305 dietary bioaccumulation test but includes reference chemicals to determine both somatic and gastrointestinal biotransformation rates of test chemicals. Somatic biotransformation rate constants for the test chemicals ranged between 0 d(-1) and 0.38 (standard error [SE] 0.03)/d(-1) . Gastrointestinal biotransformation rate constants varied from 0 d(-1) to 46 (SE 7) d(-1) . Gastrointestinal biotransformation contributed more to the overall biotransformation in fish than somatic biotransformation for all test substances but 1. Results suggest that biomagnification tests can reveal the full extent of biotransformation in fish. The common presumption that the liver is the main site of biotransformation may not apply to many substances exposed through the diet. The results suggest that the application of quantitative structure-activity relationships (QSARs) for somatic biotransformation rates and hepatic in vitro models to assess the effect of biotransformation on bioaccumulation can underestimate biotransformation rates and overestimate the biomagnification potential of chemicals that are biotransformed in the gastrointestinal tract. With some modifications, the OECD 305 test can generate somatic and gastrointestinal biotransformation data to develop biotransformation QSARs and test in vitro-in vivo biotransformation extrapolation methods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".