SREBP-1 Mediates Angiotensin II-Induced TGF-β1 Upregulation and Glomerular Fibrosis
Bibliographic record
Abstract
Angiotensin II is an important mediator of CKD of diverse etiology. A common pathologic feature of CKD is glomerular fibrosis, a central mediator of which is the profibrotic cytokine TGF-β. The mechanisms underlying the induction of TGF-β and matrix by angiotensin II are not completely understood. Recent studies showed that overexpression of the transcription factor SREBP-1 induces glomerular sclerosis and that angiotensin II can activate SREBP-1 in tubular cells. We thus studied whether SREBP-1 is activated by angiotensin II and mediates angiotensin II-induced profibrogenic responses in primary rat mesangial cells. Treatment of cells with angiotensin II induced the upregulation and activation of SREBP-1. Angiotensin II-induced activation of SREBP-1 required signaling through the angiotensin II type I receptor and activation of PI3K/Akt in addition to the chaperone SCAP and protease S1P. Notably, angiotensin II-induced endoplasmic reticulum stress was identified as a key mediator of Akt-SREBP-1 activation, and inhibition of endoplasmic reticulum stress or SREBP-1 prevented angiotensin II-induced SREBP-1 binding to the TGF-β promoter, TGF-β upregulation, and downstream fibronectin upregulation. Endoplasmic reticulum stress alone, however, did not induce TGF-β upregulation despite activating SREBP-1. Although not required for SREBP-1 activation by angiotensin II, EGF receptor signaling was necessary for activation of the SREBP-1 cotranscription factor Sp1, which provided a required second signal for TGF-β upregulation. In vivo, endoplasmic reticulum stress and SREBP-1-dependent effects were induced in glomeruli of angiotensin II-infused mice, and administration of the SREBP inhibitor fatostatin prevented angiotensin II-induced TGF-β upregulation and matrix accumulation. SREBP-1 and endoplasmic reticulum stress thus provide potential novel therapeutic targets for the treatment of 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".