Apoptotic Exosome-Like Vesicles Aggravate Inflammation and Renal Injury After Ischemia-Reperfusion
Bibliographic record
Abstract
Background: Ischemia-reperfusion injury (IRI) is a common cause of acute kidney injury (AKI) and chronic kidney disease (CKD). Mounting evidence suggests that damage to microvascular peritubular capillaries (PTC) is a critical determinant of CKD transition after IRI. We previously identified anti-LG3/perlecan autoantibodies in patients with CKD, as a negative prognostic factor for long-term renal function after AKI. We also showed that a new class of extracellular vesicles produced by apoptotic endothelial cells (ApoExo), characterized by the LG3 autoantigen, active 20S proteasome and a specific pattern of immunogenic RNAs, can prompt the production of anti-LG3. Here, we test the hypothesis that ApoExo drive renal inflammation after renal IRI leading to anti-LG3 production, defective microvascular repair and loss of renal function. Methods: ApoExo were purified by sequential ultracentrifugation from serum-free media conditioned by apoptotic murine endothelial cells. Renal IRI in mice was performed with renal artery clamping for 30 minutes and contralateral nephrectomy. ApoExo were injected twice every other day before IRI and thereafter up to eight injections, and end-points were assessed at day 21 post-IRI. Interstitial inflammation was assessed with immunohistochemistry for CD3 and IL-17A. PTC rarefaction, complement activation and myofibroblasts accumulation were monitored by immunohistochemistry for MECA-32, C4d and α-SMA. Circulating anti-LG3 levels were measured by ELISA. Results: ApoExo injection enhanced tubular damage and interstitial inflammation with increased CD3+ lymphocytes infiltration and IL-17A staining (p=0.004 and p=0.002, respectively). PTC rarefaction, C4d deposition and interstitial accumulation of α-SMA+ cells were also increased in ApoExo treated mice (p=0.01, p=0.009 and p=0.04, respectively) as were anti-LG3, which correlated strongly and positively with PTC-C4d deposition and myofibroblasts accumulation (r=0.86, p=0.007 and r=0.75, p=0.03, respectively). Conclusions: Collectively, these results identify ApoExo as novel regulators of inflammation after renal IRI, driving anti-LG3 formation, complement activation and fibrosis. These results suggest that autoimmune pathways triggered by ApoExo can contribute to microvascular rarefaction and renal fibrosis. Funding: Private Foundation Support, Government Support - Non-U.S.
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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) | 0.002 | 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".