G6b-B antibody-based cis-acting platelet receptor inhibitors (CAPRIs) as a new family of anti-thrombotic therapeutics
Bibliographic record
Abstract
Platelets are highly reactive fragments of megakaryocytes that play a fundamental role in thrombosis and hemostasis. Predictably, all conventional anti-platelet therapies elicit bleeding, raising the question whether the thrombotic activity of platelets can be targeted separately. In this study, we describe a novel approach of inhibiting platelet activation through the use of bispecific single-chain variable fragments (bi-scFvs), termed cis-acting platelet receptor inhibitors (CAPRIs) that harness the immunoreceptor tyrosine-based inhibition motif (ITIM)-containing co-inhibitory receptor G6b-B (G6B) to suppress immunoreceptor tyrosine-based (ITAM)-containing receptor-mediated platelet activation. CAPRI-mediated hetero-clustering of G6B with either the ITAM-containing GPVI-FcR γ-chain complex or FcγRIIA (CD32A) inhibited collagen- or immune complex-induced platelet aggregation. G6B-GPVI CAPRIs strongly and specifically inhibited thrombus formation on collagen under arterial shear, whereas G6B-CD32A CAPRI strongly and specifically inhibited thrombus formation to heparin-induced thrombocytopenia, vaccine-induced thrombotic thrombocytopenia and antiphospholipid syndrome complexes on Von Willebrand Factor-coated surfaces and photochemical-injured endothelial cells under arterial shear. Our findings provide proof-of-concept that CAPRIs are highly effective at inhibiting ITAM receptor-mediated platelet activation, laying the foundation for a novel family of anti-thrombotic therapeutics with potentially improved efficacy and fewer bleeding outcomes compared with current anti-platelet therapies. .
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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".