Loss of clusterin expression worsens renal ischemia-reperfusion injury
Bibliographic record
Abstract
Prevention of ischemia-reperfusion injury (IRI) is a challenge in clinical care of the patients with kidney transplants or acute kidney injury, and understanding of the intrinsic mechanisms of resistance to injury in the kidney will lead to a novel therapy. Clusterin, a secreted glycoprotein, is an antiapoptotic protein in cancer cells. Our study is to investigate the role of clusterin in renal IRI. Renal IRI in mice was induced by clamping renal vein and artery for 45 or 50 min at 32 degrees C. Apoptosis of renal tubular epithelial cells (TECs) was determined by FACS analysis. Clusterin expression was examined by Western blot or immunohistochemistry. Here, we showed that clusterin protein was induced in TECs following IRI, and more tubules expressed clusterin in the kidneys following ischemia at higher temperatures. In human proximal TEC HKC-8 cultures, clusterin was upregulated by removal of serum and growth factors in medium and was downregulated by TNF-alpha-IFN-gamma mixture. The levels of clusterin were positively correlated with cell survival in these conditions. Knockdown or knockout of clusterin expression enhanced the sensitivity of TECs to apoptosis. In experimental models of renal IRI, deficiency in clusterin expression worsened the injury, as indicated by a significant increase in renal tissue damage with higher levels of serum creatinine and blood urea nitrogen and by a poorer recovery from the injury in clusterin-deficient mice compared with wild-type mice. Our data indicate that the reduction of inducible expression of clusterin results in an increase in TEC apoptosis in the cultures and renders mice susceptibility to IRI, implying a protective role of clusterin in kidney injury.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".