SREBP inhibition ameliorates renal injury after unilateral ureteral obstruction
Bibliographic record
Abstract
Tubulointerstitial fibrosis is a major feature associated with declining kidney function in chronic kidney disease of diverse etiology. No effective means as yet exists to prevent the progression of fibrosis. We have shown that the transcription factor sterol-regulatory element-binding protein 1 (SREBP-1) is an important mediator of the profibrotic response to transforming growth factor-β (TGF-β) and angiotensin II, both key cytokines in the fibrotic process. Here, we examined the role of SREBP in renal interstitial fibrosis in the unilateral ureteral obstruction (UUO) model. The two isoforms of SREBP (-1 and -2) were activated by 3 days after UUO, with SREBP-1 showing a more sustained activation to 21 days. We then examined whether SREBP1/2 inhibition with the small-molecule inhibitor fatostatin could attenuate fibrosis after 14 days of UUO. SREBP activation was confirmed to be inhibited by fatostatin. Treatment decreased interstitial fibrosis, TGF-β signaling, and upregulation of α-smooth muscle actin (SMA), a marker of fibroblast activation. Fatostatin also attenuated inflammatory cell infiltrate and apoptosis. Associated with this, fatostatin preserved proximal tubular mass. The significant increase in atubular glomeruli observed after UUO, known to correlate with irreversible renal functional decline, was also decreased by treatment. In cultured primary fibroblasts, TGF-β1 induced the activation of SREBP-1 and -2. Fatostatin blocked TGF-β1-induced α-SMA and matrix protein upregulation. The inhibition of SREBP is thus a potential novel therapeutic target in the treatment of fibrosis in chronic kidney disease.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".