The Emerging Importance of Non-HLA Autoantibodies in Kidney Transplant Complications
Bibliographic record
Abstract
Antibodies that are specific to organ donor HLA have been involved in the majority of cases of antibody-mediated rejection in solid organ transplant recipients. However, recent data show that production of non-HLA autoantibodies can occur before transplant in the form of natural autoantibodies. In contrast to HLAs, which are constitutively expressed on the cell surface of the allograft endothelium, autoantigens are usually cryptic. Tissue damage associated with ischemia-reperfusion, vascular injury, and/or rejection creates permissive conditions for the expression of cryptic autoantigens, allowing these autoantibodies to bind antigenic targets and further enhance vascular inflammation and renal dysfunction. Antiperlecan/LG3 antibodies and antiangiotensin II type 1 receptor antibodies have been found before transplant in patients with de novo transplants and portend negative long-term outcome in patients with renal transplants. Here, we review mounting evidence suggesting an important role for autoantibodies to cryptic antigens as novel accelerators of kidney dysfunction and acute or chronic allograft rejection.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".