Mobilization of chrysene from soil in a model digestive system
Bibliographic record
Abstract
Accurate estimates for the oral bioavailability of hydrophobic contaminants bound to solid matrices are challenging to obtain because of sorption to organic matter. The purpose of this research was to measure the bioavailability of [14C]chrysene sorbed to soil using an in vitro model of gastrointestinal digestion and absorption to a surrogate intestinal membrane, ethylene vinyl acetate (EVA) thin film. The [14C]chrysene moved rapidly from soil into the aqueous compartment and reached steady state within 2 h. Equilibrium was reached in the EVA film within 32 h. Aging the spiked soil for 6 or 12 months had no effect on chrysene mobilization. This was supported by the finding that the data best fit a one-compartment model. Despite significant decreases in [14C]chrysene mobilization when water or nonneutralized gastrointestinal fluids were used in place of the complete medium, the equilibrium concentration of [14C]chrysene in EVA film remained the same in all conditions. Thus, the driving force for uptake was the fugacity gradient between the aqueous phase and the EVA film. Cultured human enterocytes (human colorectal carcinoma cell line [Caco-2 cells]) had a higher lipid-normalized fugacity capacity than EVA film, but the elimination rate constants were the same, suggesting that the rate was controlled by the resistance of the unstirred aqueous layer at the membrane-water interface.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 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 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".