A therapeutic target for CKD: activin A facilitates TGFβ1 profibrotic signaling
Bibliographic record
Abstract
Abstract Background TGFβ1 is a major profibrotic mediator in chronic kidney disease (CKD). Its direct inhibition, however, is limited by adverse effects. Inhibition of activins, also members of the TGFβ superfamily, blocks TGFβ1 profibrotic effects, but the mechanism underlying this and the specific activin(s) involved are unknown. Methods Cells were treated with TGFβ1 or activins A/B. Activins were inhibited generally with follistatin, or specifically with neutralizing antibodies or type I receptor downregulation. Cytokine levels, signaling and profibrotic responses were assessed with ELISA, immunofluorescence, immunoblotting and promoter luciferase reporters. Wild-type or TGFβ1-overexpressing mice with unilateral ureteral obstruction (UUO) were treated with an activin A neutralizing antibody. Results In primary mesangial cells, TGFβ1 induces secretion primarily of activin A, which enables longer-term profibrotic effects by enhancing Smad3 phosphorylation and transcriptional activity. This results from lack of cell refractoriness to activin A, unlike that for TGFβ1, and promotion of TGFβ type II receptor expression. Activin A also supports transcription through regulating non-canonical MRTF-A activation. TGFβ1 additionally induces secretion of activin A, but not B, from tubular cells, and activin A neutralization prevents the TGFβ1 profibrotic response in renal fibroblasts. Fibrosis induced by UUO is inhibited by activin A neutralization in wild-type mice. Worsened fibrosis in TGFβ1-overexpressing mice is associated with increased renal activin A expression and is inhibited to wild-type levels with activin A neutralization. Conclusions Activin A facilitates TGFβ1 profibrotic effects through regulation of both canonical (Smad3) and non-canonical (MRTF-A) signaling, suggesting it may be a novel therapeutic target for preventing fibrosis in CKD.
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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 | 0.001 | 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".