Bone morphogenetic protein‐4 induced Rat hepatic progenitor cell (WB‐F344 cell) differentiation toward hepatocyte lineage
Bibliographic record
Abstract
Hepatic progenitor cells are local stem cells in the liver and they can be differentiated into either hepatocytes or cholangiocytes depending on different stimulations. These stimulations include extracellular growth factors and intracellular transcription factors. Bone morphogenetic protein 4 (BMP4) is a member of transforming growth factor beta (TGF-beta) superfamily and was first identified as growth factor to induce ectopic bone formation from skeletal muscle. Role of BMP4 in the liver is still unclear especially its role in hepatic progenitor cells (HPCs) differentiation. BMP4 was used to stimulate rat HPCs (WB-F344 cells) and differentiation of WB-F344 cells was investigated by reverse transcriptase polymerase chain reaction (RT-PCR) and Western blot analysis. Both adenovirus delivered BMP4 and recombinant BMP4 were able to induce expression of hepatocyte markers such as albumin, TAT-1, and G6Pase but not cholangiocyte markers such as beta4-integrin and CK19. BMP4 induced differentiation of WB-F344 cells toward hepatocytes was mediated by increase in phosphorylation of Smad1 and ERK1/2. Moreover, BMP4 also stimulated expression of transcription factor--C/EBP-alpha, which involved in differentiation of WB-F344 cells toward hepatocytes. BMP4 is able to stimulate WB-F344 cells differentiation toward hepatocyte lineage.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".