Analysis of TGFβ1-Induced activin A gene expression in kidney mesangial cells
Bibliographic record
Abstract
Introduction The cytokine activin A is emerging as an important regulator of kidney fibrosis. Its expression, negligible in normal kidney, is significantly increased in various fibrotic kidney diseases. TGFβ1 is a cytokine belonging to the same family, which is well established to be a central mediator of kidney fibrosis. Although targeting TGFβ1 therapeutically is not feasible due to its homeostatic roles, we previously showed that activin A is upregulated by, and mediates the profibrotic effects of, TGFβ1. Methods We investigated the transcriptional regulation of activin A by TGFβ1 in primary kidney mesangial cells (MC). Cells were transfected with a luciferase reporter construct containing the activin A promoter or a series of deletion constructs. Guided by MatInspector, key TGFβ1-responsive consensus elements were identified. Results TGFβ1 increased transcription of the activin A subunit inhba. Using a series of deletion constructs of the inhba promoter, we identified a critical regulatory region located 350bp from the transcription start site that is responsive to TGFβ1. Analysis of this region for transcription factor regulatory elements, coupled with mutation analyses and transcription factor downregulation with siRNA, showed that Stat5 and FoxP1, but not Sox9, regulate inhba transcription by TGFβ1. Interestingly, although no consensus binding site in this region was identified for Smad3, a well-established mediator of TGFβ1 signaling, both a Smad3 inhibitor and use of MC isolated from Smad3 knockout kidneys, showed its requirement for the TGFβ1 response. We further identified a CT microsatellite just upstream of 350bp which suppressed promoter activity. Conclusion These findings provide insight into potential therapeutic targets for activin A targeting and attenuation of kidney 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".