Relationship of clusterin with renal inflammation and fibrosis after the recovery phase of ischemia-reperfusion injury
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Long-term outcomes after acute kidney injury (AKI) include incremental loss of function and progression towards chronic kidney disease (CKD); however, the pathogenesis of AKI to CKD remains largely unknown. Clusterin (CLU) is a chaperone-like protein that reduces ischemia-reperfusion injury (IRI) and enhances tissue repair after IRI in the kidney. This study investigated the role of CLU in the transition of IRI to renal fibrosis. METHODS: IRI was induced in the left kidneys of wild type (WT) C57BL/6J (B6) versus CLU knockout (KO) B6 mice by clamping the renal pedicles for 28 min at the body temperature of 32 °C. Tissue damage was examined by histology, infiltrate phenotypes by flow cytometry analysis, and fibrosis-related gene expression by PCR array. RESULTS: Reduction of kidney weight was induced by IRI, but was not affected by CLU KO. Both WT and KO kidneys had similar function with minimal cellular infiltration and fibrosis at day 14 of reperfusion. After 30 days, KO kidneys had greater loss in function than WT, indicated by the higher levels of both serum creatinine and BUN in KO mice, and exhibited more cellular infiltration (CD8 cells and macrophages), more tubular damage and more severe tissue fibrosis (glomerulopathy, interstitial fibrosis and vascular fibrosis). PCR array showed the association of CLU deficiency with up-regulation of CCL12, Col3a1, MMP9 and TIMP1 and down-regulation of EGF in these kidneys. CONCLUSION: Our data suggest that CLU deficiency worsens renal inflammation and tissue fibrosis after IRI in the kidney, which may be mediated through multiple pathways.
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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) | 0.000 | 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 | 0.000 |
| 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 it