Recipient antigen‐processing pathways of allogeneic platelet antigens: essential mediators of immunity
Bibliographic record
Abstract
Clinical studies have convincingly demonstrated that WBC reduction of blood components can reduce the incidence of primary HLA antigen alloimmunization at least in patients with acute myeloid leukemia.1 However, despite receiving WBC‐reduced platelets, approximately 19 percent of acute myeloid leukemia patients still became alloimmunized.1 In addition, it is not known whether WBC reduction will prevent HLA antigen alloimmunization among those recipients who have an intact immune system (e.g., general surgery patients). The biologic mechanisms responsible for immune stimulation by blood components are still incompletely understood but are probably related to both donor and recipient factors. Animal models have proven indispensable for elucidating the basic mechanisms of immunity against foreign antigens and several such models have been developed to study various aspects of transfusion immunobiology.2-4 Our laboratory has developed a murine transfusion model that has allowed us to focus on recipient factors affecting the immune response to WBC‐reduced platelets. This article will describe how the murine immune response to platelet transfusion is critically dependent on recipient antigen‐processing and‐presentation pathways and how these pathways can be exploited to modulate immunization against WBC‐reduced platelets.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".