The 20 <i>S</i> proteasome core, active within apoptotic exosome-like vesicles, induces autoantibody production and accelerates rejection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Autoantibodies to components of apoptotic cells, such as anti-perlecan antibodies, contribute to rejection in organ transplant recipients. However, mechanisms of immunization to apoptotic components remain largely uncharacterized. We used large-scale proteomics, with validation by electron microscopy and biochemical methods, to compare the protein profiles of apoptotic bodies and apoptotic exosome-like vesicles, smaller extracellular vesicles released by endothelial cells downstream of caspase-3 activation. We identified apoptotic exosome-like vesicles as a central trigger for production of anti-perlecan antibodies and acceleration of rejection. Unlike apoptotic bodies, apoptotic exosome-like vesicles triggered the production of anti-perlecan antibodies in naïve mice and enhanced anti-perlecan antibody production and allograft inflammation in mice transplanted with an MHC (major histocompatibility complex)-incompatible aortic graft. The 20S proteasome core was active within apoptotic exosome-like vesicles and controlled their immunogenic activity. Finally, we showed that proteasome activity in circulating exosome-like vesicles increased after vascular injury in mice. These findings open new avenues for predicting and controlling maladaptive humoral responses to apoptotic cell components that enhance the risk of rejection after transplantation.
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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 | 0.001 | 0.001 |
| 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 | 0.002 |
| 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