On a Long and Winding Road: Alloantibodies in Organ Transplantation
Bibliographic record
Abstract
Today we know that both the humoral and the cellular arm of the immune system are engaged in severe immunological challenges. A close interaction between B and T cells can be observed in most "natural" challenges, including infections, malignancies, and autoimmune diseases. The importance and power of humoral immunity are impressively demonstrated by the current coronavirus disease 2019 pandemic. Organ transplant rejection is a normal immune response to a completely "artificial" challenge. It took a long time before the multifaceted action of different immunological forces was recognized and a unified, generally accepted opinion could be formed. Here, we address prominent paradigms and paradigm shifts in the field of transplantation immunology. We identify several instances in which the transplant community missed a timely paradigm shift because essential, available knowledge was ignored. Moreover, we discuss key findings that critically contributed to our understanding of transplant immunology but sometimes developed with delay and in a roundabout way, as was the case with antibody-mediated rejection-a main focus of this article. These include the discovery of the molecular principles of histocompatibility, the recognition of the microcirculation as a key interface of immune damage, the refinement of alloantibody detection, the description of C4d as a footmark of endothelium-bound antibody, and last but not least, the developments in biopsy-based diagnostics beyond conventional morphology, which only now give us a glimpse of the enormous complexity and pathogenetic diversity of rejection.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".