Survivin Mediates Renal Proximal Tubule Recovery from AKI
Bibliographic record
Abstract
AKI induces the renoprotective upregulation of survivin expression in kidney epithelial cells, but the underlying mechanisms have not been identified. To determine the role of survivin in renal recovery from AKI, we generated mice with renal proximal tubule-specific deletion of survivin (survivin(ptKO)). Renal survivin expression increased substantially in response to ischemia-reperfusion (I/R) injury in control littermates but remained minimal in survivin(ptKO) mice. Functional and histologic data indicated similar degrees of renal injury in survivin(ptKO) and control mice 24 hours after reperfusion, but recovery was markedly delayed in survivin(ptKO) mice. In MCT cells, a mouse renal proximal tubule cell line, ATP depletion by antimycin A treatment upregulated survivin expression through a phospho-STAT3-dependent pathway. In wild-type mice, inhibition of STAT3 kinase diminished I/R-induced upregulation of STAT3 phosphorylation and survivin expression and delayed recovery. Furthermore, I/R injury activated Notch-2 signaling, and a γ-secretase inhibitor suppressed I/R-induced Notch-2 signaling, STAT3 phosphorylation, and survivin expression and delayed recovery. In MCT cells, inhibition of γ-secretase similarly attenuated antimycin A-induced Notch-2 activation, upregulation of survivin, and phosphorylation of STAT3, but STAT3 kinase inhibition did not prevent Notch-2 activation. Therefore, these data suggest that STAT3 phosphorylation and subsequent upregulation of survivin expression mediated by Notch-2 signaling in renal proximal tubule epithelial cells aid in the functional and structural recovery of the kidney from AKI.
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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) | 0.001 | 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".