A method for measuring the bioaccessibility of polycyclic aromatic hydrocarbons in cell culture media
Bibliographic record
Abstract
Airborne polycyclic aromatic hydrocarbons (PAHs) and their derivatives are of particular concern for population health due to their abundance and toxicity via inhalation. Lung toxicity testing includes exposing lung epithelial cell lines to PAHs in a culture medium containing inorganic species, lipids, proteins, and other biochemicals where the cell response is influenced among others by the toxic chemical accessibility in the medium. While inhalation bioaccessibility of PAHs and other toxicants was previously studied in surrogate lung fluids, studies measuring bioaccessibility in cell culture media are rare. In this work, a method was developed to characterize PAH bioaccessibility in a culture medium used for mouse lung epithelial (FE1) cells. Further, the optimised method was tested using commercially available standard reference material of urban particulate matter (PM) as well as polyurethane foam passive air samplers (PUF-PAS). The method provided a high precision and recovery of analytes, indicating no losses during sample processing and analysis. PAHs had non-linear concentration-responses, with the culture medium approaching saturation with PM concentration of 500 μg mL−1. The results showed that phenanthrene, a 3-ring PAH, was significantly more bioaccessible than ≥4-ring congeners in the culture medium (up to ∼2.5 folds; p < 0.05). Finally, using pre-deployed PUF-PAS from a residential and an industrial site, five PAHs were found in the culture medium, including naphthalene, phenanthrene, anthracene, fluoranthene, and pyrene. This work provides a proof of concept to enable future studies to assess the inhalation bioaccessibility of polycyclic aromatic compounds and other airborne pollutants collected using PUF-PAS.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".