In Vivo Biotransformation Rates of Organic Chemicals in Fish: Relationship with Bioconcentration and Biomagnification Factors
Bibliographic record
Abstract
In vivo dietary bioaccumulation experiments for 85 hydrophobic organic substances were conducted to derive the in vivo gastrointestinal biotransformation rates, somatic biotransformation rates, bioconcentration factors (BCF), and biomagnification factors (BMF) for improving methods for bioaccumulation assessment and to develop an in vivo biotransformation rate database for QSAR development and in vitro to in vivo biotransformation rate extrapolation. The capacity of chemicals to be biotransformed in fish was found to be highly dependent on the route of exposure. Somatic biotransformation was the dominant pathway for most chemicals absorbed via the respiratory route. Intestinal biotransformation was the dominant metabolic pathway for most chemicals absorbed via the diet. For substances not biotransformed or transformed exclusively in the body of the fish, the BCF and BMF appeared to be closely correlated. For substances subject to intestinal biotransformation, the same correlation did not apply. We conclude that intestinal biotransformation and bioavailability in water can modulate the relationship between the BCF and BMF. This study also supports a fairly simple rule of thumb that may be useful in the interpretation of dietary bioaccumulation tests; i.e., chemicals with a BMF L of <1 tend to exhibit BCFs based on either the freely dissolved (BCF WW,fd ) or the total concentration (BCF WW,t ) of the chemical in the water that is less than 5000.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".