Covalently linking heparin to antithrombin enhances prothrombinase inhibition on activated platelets
Bibliographic record
Abstract
Factor (F)Xa within the prothrombinase complex is protected from inhibition by unfractionated heparin (UFH), enoxaparin and fondaparinux. We have developed a covalent antithrombin-heparin complex (ATH) with enhanced anticoagulant activity. We have also demonstrated that ATH is superior at inhibiting coagulation factors when assembled on artificial surfaces. The objective of the present study is to determine the ability of ATH vs AT+UFH to inhibit FXa within the prothrombinase complex when the enzyme complex is assembled on the more native platelet system. Discontinuous inhibition assays were performed to determine final k2-values for inhibition of FXa, FXa within the platelet-prothrombinase, or FXa within prothrombinase devoid of various components. Thrombin generation and plasma clotting was also assayed in the presence of resting/activated platelets ± inhibitors. Protection of FXa was not observed for ATH, whereas a moderate 60% protection was observed for AT+UFH. ATH inhibited platelet-prothrombinase ~4-fold faster than AT+UFH. Relative to intact prothrombinase, ratesfor FXa inhibition by AT+UFH in prothrombinase complexes devoid of either prothrombin (II)/activated platelets/FVa were higher. However, inhibition by AT+UFH of prothrombinase devoid of FII yielded slightly lower rates compared to free FXa inhibition. Thrombin generation and plasma clotting was enhanced with activated platelets, while inhibition was better by ATH compared to AT+UFH, thus suggesting an overall enhanced anticoagulant activity of ATH against platelet-bound prothrombinase complexes.
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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".