Establishment and Characterization of Rat Portal Myofibroblast Cell Lines
Bibliographic record
Abstract
The major sources of scar-forming myofibroblasts during liver fibrosis are activated hepatic stellate cells (HSC) and portal fibroblasts (PF). In contrast to well-characterized HSC, PF remain understudied and poorly defined. This is largely due to the facts that isolation of rodent PF for functional studies is technically challenging and that PF cell lines had not been established. To address this, we have generated two polyclonal portal myofibroblast cell lines, RGF and RGF-N2. RGF and RGF-N2 were established from primary PF isolated from adult rat livers that underwent culture activation and subsequent SV40-mediated immortalization. Specifically, Ntpdase2/Cd39l1-sorted primary PF were used to generate the RGF-N2 cell line. Both cell lines were functionally characterized by RT-PCR, immunofluorescence, immunoblot and bromodeoxyuridine-based proliferation assay. First, immortalized RGF and RGF-N2 cells are positive for phenotypic myofibroblast markers alpha smooth muscle actin, type I collagen alpha-1, tissue inhibitor of metalloproteinases-1, PF-specific markers elastin, type XV collagen alpha-1 and Ntpdase2/Cd39l1, and mesenchymal cell marker ecto-5'-nucleotidase/Cd73, while negative for HSC-specific markers desmin and lecithin retinol acyltransferase. Second, both RGF and RGF-N2 cell lines are readily transfectable using standard methods. Finally, RGF and RGF-N2 cells attenuate the growth of Mz-ChA-1 cholangiocarcinoma cells in co-culture, as previously demonstrated for primary PF. Immortalized rat portal myofibroblast RGF and RGF-N2 cell lines express typical markers of activated PF-derived myofibroblasts, are suitable for DNA transfection, and can effectively inhibit cholangiocyte proliferation. Both RGF and RGF-N2 cell lines represent novel in vitro cellular models for the functional studies of portal (myo)fibroblasts and their contribution to the progression of liver fibrosis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".