Extent of extracellular signal-regulated kinases phosphorylation determines the sensitivity of hepatic stellate cells to staurosporine-induced apoptosis.
Bibliographic record
Abstract
OBJECTIVE: Hepatic stellate cells (HSCs) are the principal cells responsible for the development of hepatic fibrosis and cirrhosis. During the fibrotic process, HSCs undergo proliferation and transdifferentiation from a quiescent to myofibroblast-like phenotype. The fate of myofibroblast like HSCs includes apoptosis or reversion back to a quiescent phenotype. The mechanisms involved in the apoptotic process of HSCs have yet to be determined. The purpose of the present study is to determine the effects of extracellular signal-regulated kinases (ERKs) phosphorylation on the apoptosis of HSCs induced by staurosporine. METHODS: We used Western blot and flow cytometry to detect the expression level of ERK and cell apoptosis status in four rat hepatic stellate cell lines (CFSC-8B, -2G, -3H and-5H). RESULTS: Each hepatic stellate cell line had a distinct morphology consistent with their expression level of α-SMA and that CFSC-8B cells had the highest α-SMA expression. Although all four cell types expressed similar levels of ERK1/2, phosphorylation levels were significantly higher in CFSC- 8B and CFSC-2G than in CFSC-3H and CFSC-5H cells. When CFSC-8B cells (high ERK1/2 phosphorylation) and CFSC-5H cells (low ERK1/2 phosphorylation) were employed to examine staurosporine-induced apoptosis, CFSC-8B cells were significantly more sensitive. Staurosporine further increased ERK1/2 phosphorylation in both cell lines. CONCLUSION: ERK1/2 phosphorylation in HSCs determines the sensitivity of HSCs to staurosporine-induced apoptosis.
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 | 0.000 | 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) | 0.002 | 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".