Platelet-activating Factor (PAF) and Adverse Inflammatory Reactions Associated with Anti-Erythrocyte Antibody Therapy
Bibliographic record
Abstract
Immune thrombocytopenia (ITP) is an autoimmune disease characterized by low platelet counts primarily due to anti-platelet autoantibodies. Anti-D is a donor-derived polyclonal antibody against the erythrocyte Rhesus-D antigen used to treat ITP. However, there is an FDA-issued black box warning for severe hemolysis with anti-D in ITP. TER119 is a monoclonal antibody against murine erythrocytes with therapeutic capability in murine ITP, which we use in this thesis as an anti-D surrogate to understand adverse events of anti-erythrocyte antibodies. We have observed that TER119 causes decreased body temperature, indicating adverse inflammation. Our work reveals the role of platelet-activating factor (PAF) in potentially driving inflammatory reactions induced by TER119. Body temperature decreases associated with TER119 was mitigated by PAF-receptor antagonist pretreatment, which did not interfere with the therapeutic effectiveness of TER119. Understanding and addressing the adverse inflammation associated with TER119 may improve the translational potential of monoclonal anti-erythrocyte antibodies in treating ITP.
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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) | 0.005 | 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".