Metabolic Activation of Benzo[a]pyrene by Human Tissue Organoid Cultures
Bibliographic record
Abstract
Organoids are 3D cultures that to some extent reproduce the structure, composition and function of the mammalian tissues from which they derive, thereby creating in vitro systems with more in vivo-like characteristics than 2D monocultures. Here, the ability of human organoids derived from normal gastric, pancreas, liver, colon and kidney tissues to metabolise the environmental carcinogen benzo[a]pyrene (BaP) was investigated. While organoids from the different tissues showed varied cytotoxic responses to BaP, with gastric and colon organoids being the most susceptible, the xenobiotic-metabolising enzyme (XME) genes, CYP1A1 and NQO1, were highly upregulated in all organoid types, with kidney organoids having the highest levels. Furthermore, the presence of two key metabolites, BaP-t-7,8-dihydrodiol and BaP-tetrol-l-1, was detected in all organoid types, confirming their ability to metabolise BaP. BaP bioactivation was confirmed both by the activation of the DNA damage response pathway (induction of p-p53, pCHK2, p21 and γ-H2AX) and by DNA adduct formation. Overall, pancreatic and undifferentiated liver organoids formed the highest levels of DNA adducts. Colon organoids had the lowest responses in DNA adduct and metabolite formation, as well as XME expression. Additionally, high-throughput RT-qPCR explored differences in gene expression between organoid types after BaP treatment. The results demonstrate the potential usefulness of organoids for studying environmental carcinogenesis and genetic toxicology.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 0.001 |
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".