Anti-D initially stimulates an Fc-dependent leukocyte oxidative burst and subsequently suppresses erythrophagocytosis via interleukin-1 receptor antagonist
Bibliographic record
Abstract
Previous results have demonstrated that anti-D therapy in children with chronic auto-immune thrombocytopenic purpura (AITP) induced a significant increase in several pro- and anti-inflammatory plasma cytokines within 2 hours of administration. To investigate the biologic basis of these early in vivo responses, we developed a flow cytometric assay to measure Fc-dependent responses of human peripheral leukocytes with fluorescently labeled and anti-D-opsonized red blood cells (RBCs). When anti-D-opsonized RBCs were incubated with peripheral blood leukocytes, the earliest detectible event observed was a significant oxidative burst in both monocytes (P <.05) and granulocytes (P <.0001), characterized by the production of hydrogen peroxide (H2O2), peroxynitrite (ONOO-), superoxide (O -2), and hydroxyl (OH) by 10 minutes which declined by 1 hour. By 2 hours, the opsonized RBCs were phagocytosed, particularly by granulocytes (P <.001), but the phagocytosis subsequently declined by 6 hours of incubation. The decline in phagocytosis was correlated with a significant production of interleukin-1 receptor antagonist (IL1ra) by both monocytes (P =.036) and granulocytes (P =.0002) within 4 hours. None of these events occurred if the RBCs were coated with anti-D F(ab)'2 fragments. When recombinant IL1ra was titrated into the assay, phagocytosis of the opsonized RBCs was significantly inhibited (P =.002). Taken together, these results suggest that at least one mechanism of action of anti-D is via the production of the anti-inflammatory cytokine IL1ra which can negatively regulate the ability of leukocytes to phagocytose opsonized cells.
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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) | 0.000 | 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 | 0.001 |
| 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".