A hepatoprotective role of peritumoral non-parenchymal cells in early liver tumorigenesis
Bibliographic record
Abstract
Various 3D models of hepatocytes (HCs) have been established to assess liver functions in vitro. The contribution of the hepatic non-parenchymal cells (NPCs), however, is largely neglected in these models. Here, we report a comparative study of hepatic spheroids generated from freshly isolated mouse whole liver cells (WLCs) and HCs (referred to as SphWLC and SphHC, respectively). We found that HC differentiation was preserved better in SphWLC than in SphHC, and, when co-cultured with liver tumor spheroids (SphT), SphWLC showed more potent suppression of SphT growth compared to SphHC. Histological characterization revealed marked activation and accumulation of hepatic stellate cells (HSCs) at the SphWLC:SphT interface. We found that mixing HSCs in both 3D and 2D HC:tumor co-cultures provided potent protection to HCs against tumor-induced cell death. Activation of HSCs at the tumor border was similarly found in liver tumors from both mice and patients. Overall, our study suggests a hepatoprotective role of peritumoral HSCs in liver tumorigenesis and the potential application of SphWLC as a useful 3D model for dissecting the liver's response to tumorigenesis in vitro.
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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".