Destabilization of PF4-antigenic complexes in heparin-induced thrombocytopenia
Bibliographic record
Abstract
ABSTRACT: Heparin-induced thrombocytopenia (HIT) is initiated by antibodies that recognize large antigenic complexes composed of multiple molecules of cationic platelet factor 4 (PF4) and polyanions such as unfractionated heparin (UFH) that bind to each other primarily through electrostatic interactions. We asked whether the formation and stability of these HIT antigenic or ultralarge immune complexes (ULICs) would be inhibited by biocompatible synthetic polycationic molecules shown previously to dissociate UFH from antithrombin III and to inhibit polyphosphates. Members of this family of molecules, designated universal heparin reversal agents (UHRAs), inhibited formation and dissociated preformed ultralarge PF4-UFH (antigenic) complexes (ULCs), dissociated ULICs composed of the HIT-like monoclonal antibody KKO and ULCs, blocked binding of human HIT immunoglobulin G antibodies to PF4/heparin, binding of KKO to platelets, KKO-induced adhesion of platelets to activated human endothelium under flow, and microvascular thrombosis induced by KKO in a mouse model of HIT. These data suggest that UHRAs might provide a rationale intervention that acts at an early step in the pathogenesis of HIT to enhance the benefits and lessen the risks of nonheparin anticoagulants. Destabilization of immune complexes using polycationic inhibitors might also find a role in management of other polyanion PF4-antibody-mediated conditions, including vaccine-induced thrombocytopenia/thrombosis, postviral, and autoimmune HIT.
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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 | 0.000 |
| 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".