A novel immunosuppressive pathway involving peroxynitrate‐mediated nitration of platelet antigens within antigen‐presenting cells
Bibliographic record
Abstract
BACKGROUND: Studies have demonstrated that immunity against platelet (PLT) transfusions is dependent on recipient antigen-presenting cells (APCs) and their ability to produce nitric oxide (NO). To further analyze this, we focused on NO's major metabolite peroxynitrite (ONOO(-)) and its ability to affect PLT immunity. STUDY DESIGN AND METHODS: To address how NO and its major metabolite may mediate PLT immunity, GP91(PHOX) knockout (KO) mice that lack the ability to produce the ONOO(-) were transfused weekly with allogeneic BALB/c PLTs, and donor antibody development was analyzed. RESULTS: Compared with controls, GP91(PHOX) KO mice developed significantly (p < 0.0001) higher-titered immunoglobulin G (IgG) donor antibodies by two transfusions, and this immune response could be inhibited by treating the recipient mice with aminoguanidine, a relatively selective inhibitor of inducible nitric oxide synthase. In vitro nitration of PLTs did not alter PLT antibody binding but significantly inhibited the transfused PLT's ability to stimulate IgG immunity in either wild-type or KO mice. The lack of nitrated PLT immunity correlated with an inability of APCs to mediate phagocytosis of nitrated PLTs. The lack of nitrated PLT immunity could only be restored when normal PLTs were mixed with the nitrated PLTs and transfused. CONCLUSION: The results identify a dual role for NO metabolism within APCs that significantly modulates PLT immunity; nitration of PLT antigens leads to lack of immunity due to an inability of APCs to move PLT antigens intracellularly whereas there exists an NO-dependent pathway that stimulates anti-PLT immunity.
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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) | 0.000 | 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) | 0.001 | 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 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".