Concentration dependence of in vitro biotransformation rates of hydrophobic organic sunscreen agents in rainbow trout S9 fractions: Implications for bioaccumulation assessment
Bibliographic record
Abstract
Abstract In vitro biotransformation studies were performed to support the bioaccumulation assessment of 3 hydrophobic organic ultraviolet filters (UVFs), 4-methylbenzylidene camphor (4-MBC), 2-ethylhexyl-4-methoxycinnamate (EHMC), and octocrylene. In vitro depletion rate constants (kdep) were determined for each UVF using rainbow trout liver S9 fractions. Incubations performed with and without added cofactors showed complete (4-MBC) or partial (EHMC and octocrylene) dependence of kdep on addition of the reduced form of nicotinamide adenine dinucleotide phosphate (NADPH), suggesting that hydrolysis of EHMC and octocrylene by NADPH-independent enzymes (e.g., carboxylesterases) is an important metabolic route. The concentration dependence of kdep was then evaluated to estimate Michaelis–Menten parameters (KM and Vmax) for each UVF. Measured kdep values were then extrapolated to apparent whole-body biotransformation rate constants using an in vitro–in vivo extrapolation (IVIVE) model. Bioconcentration factors (BCFs) calculated from kdep values measured at concentrations well below KM were closer to empirical BCFs than those calculated from kdep measured at higher test concentrations. Modeled BCFs were sensitive to in vitro binding assumptions employed in the IVIVE model, highlighting the need for further characterization of chemical binding effects on hepatic clearance. The results suggest that the tested UVFs are unlikely to accumulate to levels exceeding the European Union Registration, Evaluation, Authorisation, and Restriction regulation criterion for bioaccumulative substances (BCF > 2000 L kg−1). However, consideration of appropriate in vitro test concentrations and binding correction factors are important when IVIVE methods are used to refine modeled BCFs. Environ Toxicol Chem 2019;38:548–560. © 2018 SETAC
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".