Antiperlecan Antibodies Are Novel Accelerators of Immune-Mediated Vascular Injury
Why this work is in the frame
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Bibliographic record
Abstract
Acute vascular rejection (AVR) is characterized by immune-mediated vascular injury and heightened endothelial cell (EC) apoptosis. We reported previously that apoptotic ECs release a bioactive C-terminal fragment of perlecan referred to as LG3. Here, we tested the possibility that LG3 behaves as a neoantigen, fuelling the production of anti-LG3 antibodies of potential importance in regulating allograft vascular injury. We performed a case-control study in which we compared anti-LG3 IgG titers in kidney transplant recipients with AVR (n=15) versus those with acute tubulo-interstitial rejection (ATIR) (n=15) or stable graft function (n=30). Patients who experienced AVR had elevated anti-LG3 titers pre and posttransplantation compared to subjects with ATIR or stable graft function (p<0.05 for both mediators). Elevated pretransplant anti-LG3 titers (OR: 4.62, 95% CI: 1.08-19.72) and pretransplant donor-specific antibodies (DSA) (OR 4.79, 95% CI: 1.03-22.19) were both independently associated with AVR. To address the functional role of anti-LG3 antibodies in AVR, we turned to passive transfer of anti-LG3 antibodies in an animal model of vascular rejection based on orthotopic aortic transplantation between fully MHC-mismatched mice. Neointima formation, C4d deposition and allograft inflammation were significantly increased in recipients of an ischemic aortic allograft passively transferred with anti-LG3 antibodies. Collectively, these data identify anti-LG3 antibodies as novel accelerators of immune-mediated vascular injury and obliterative remodeling.
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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