Gas6 Induces Mesangial Cell Proliferation via Latent Transcription Factor STAT3
Bibliographic record
Abstract
Mesangial cell proliferation is essential for the pathogenesis and progression of glomerular disease. Previously, we showed that Gas6 plays a pivotal role in mesangial cell proliferation in vitro and in vivo. In the present study, we identified downstream targets of Gas6 signaling to examine the role in mesangial cell proliferation in vitro and in vivo. We found that Gas6 tyrosine phosphorylates STAT3 (signal transducers and activators of transcription) with concomitant translocation to the nucleus and induces STAT3-dependent transcriptional activation in cultured mesangial cells. Expressing dominant negative STAT3 inhibited Gas6-mediated transcriptional activation of STAT3 and abolished Gas6-induced mesangial cell proliferation. In a model of mesangial proliferative glomerulonephritis, STAT3 is phosphorylated in mesangial cells, and its phosphorylation peaks at day 8 after the injection of anti-Thy1.1 antibody. Inhibition of Gas6 by warfarin and the extracellular domain of its receptor, Axl, abolished phosphorylation of STAT3 in vivo. Thus, our in vitro and in vivo findings indicate that autocrine growth factor Gas6 induces mesangial cell proliferation via latent transcription factor STAT3. Therefore, STAT3 might be a new therapeutic target for kidney disease induced by mesangial proliferation.
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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) | 0.002 | 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".