HD1, a thrombin- and prothrombin-binding DNA aptamer, inhibits thrombin generation by attenuating prothrombin activation and thrombin feedback reactions
Bibliographic record
Abstract
HD1, a DNA aptamer, binds exosite 1 on thrombin and blocks its clotting activity. Because HD1 also binds prothrombin and inhibits its activation by prothrombinase, we hypothesised that HD1 would be a more potent inhibitor of coagulation than other exosite 1-directed ligands, such as Hir(54-65)(SO(3)(-)). Supporting this concept, the effect of HD1 on the prothrombin time and activated partial thromboplastin time was two-fold greater than that of Hir(54-65)(SO(3)(-)) even though both agents inhibited thrombin-mediated factor (F) V and FVIII activation to a similar extent. In thrombin generation assays, HD1 (a) delayed the lag time, (b) reduced peak thrombin concentration, and (c) decreased endogenous thrombin potential to a greater extent than Hir54-65(SO(3)(-)). To eliminate thrombin feedback, studies were repeated in FV- and/or FVIII-deficient plasma supplemented with FVa and/or FVIIIa. Only HD1 prolonged the lag time in FV- and FVIII-deficient plasma supplemented with FVa and FVIIIa. In contrast, HD1 and Hir54-65(SO(3)(-)) inhibited the lag time in FVIII-deficient plasma supplemented with FVIIIa and in normal plasma. The more potent anticoagulant properties of HD1, therefore, reflect its capacity to attenuate FV activation by thrombin and inhibit prothrombinase assembly. These findings identify prothrombin as a potential target for new anticoagulants.
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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".