<i>Hes1</i>, an important gene for activation of hepatic stellate cells, is regulated by Notch1 and TGF-β/BMP signaling
Bibliographic record
Abstract
AIM: To determine the role of Notch1 and Hes1 in regulating the activation of hepatic stellate cells (HSCs) and whether Hes1 is regulated by transforming growth factor (TGF)/bone morphogenetic protein (BMP) signaling. METHODS: Immunofluorescence staining was used to detect the expression of desmin, glial fibrillary acidic protein and the myofibroblastic marker α-smooth muscle actin (α-SMA) after freshly isolated, normal rat HSCs had been activated in culture for different numbers of days (0, 1, 3, 7 and 10 d). The expression of α-SMA, collagen1α2 (COL1α2), Notch receptors (Notch1-4), and the Notch target genes Hes1 and Hey1 were analyzed by reverse transcriptase-polymerase chain reaction. Luciferase reporter assays and Western blot were used to study the regulation of α-SMA, COL1α1, COL1α2 and Hes1 by NICD1, Hes1, CA-ALK3, and CA-ALK5 in HSC-T6 cells. Moreover, the effects of inhibiting Hes1 function in HSC-T6 cells using a Hes1 decoy were also investigated. RESULTS: The expression of Notch1 and Hes1 mRNAs was significantly down-regulated during the culture of freshly isolated HSCs. In HSC-T6 cells, Notch1 inhibited the promoter activities of α-SMA, COL1α1 and COL1α2. On the other hand, Hes1 enhanced the promoter activities of α-SMA and COL1α2, and this effect could be blocked by inhibiting Hes1 function with a Hes1 decoy. Furthermore, co-transfection of pcDNA3-CA-ALK3 (BMP signaling activin receptor-like kinase 3) and pcDNA3.1-NICD1 further increased the expression of Hes1 compared with transfection of either vector alone in HSC-T6 cells, while pcDNA3-CA-ALK5 (TGF-β signaling activin receptor-like kinase 5) reduced the effect of NICD1 on Hes1 expression. CONCLUSION: Selective interruption of Hes1 or maintenance of Hes1 at a reasonable level decreases the promoter activities of α-SMA and COL1α2, and these conditions may provide an anti-fibrotic strategy against hepatic 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 | 0.000 | 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".