Assessing Receptor Activation in 2D and 3D Cultured Hepatocytes: Responses to a Single Compound and a Complex Mixture
Bibliographic record
Abstract
Responding to global standards and legislative updates in Canada, including Bill S-5 (2023), toxicity testing is shifting towards more ethical, in vitro methods. Traditional two-dimensional (2D) monolayer cell cultures, limited in replicating the complex in vivo environment, have prompted the development of more relevant three-dimensional (3D) spheroidal hepatocyte cultures. This study introduces the first 3D spheroid model for McA-RH7777 cells, assessing xenobiotic receptor activation, cellular signaling, and toxicity against dexamethasone and naphthenic acid (NA)-fraction components; NAFCs. Our findings reveal that 3D McA-RH7777 spheroids demonstrate enhanced sensitivity and more uniform dose–response patterns in gene expression related to xenobiotic metabolism (AhR and PPAR) for both single compounds and complex mixtures. Specifically, 3D cultures showed significant gene expression changes upon dexamethasone exposure and exhibited varying degrees of sensitivity and resistance to the apoptotic effects induced by NAFCs, in comparison to 2D cultures. The optimization of 3D culture conditions enhances the model’s physiological relevance and enables the identification of genomic signatures under varied exposures. This study highlights the potential of 3D spheroid cultures in providing a more accurate representation of the liver’s microenvironment and advancing our understanding of cellular mechanisms in toxicity testing.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".