Effect of endothelium on the anticoagulant activity of a covalent antithrombin-heparin complex
Bibliographic record
Abstract
We developed a covalent antithrombin-heparin complex (ATH) with superior In vivo anticoagulant efficacy compared to non-covalent antithrombin (AT) + unfractionated heparin (H). Previous in vitro studies of ATH, investigating the mechanisms behind its efficacy, were done in the absence of endothelium. Since the endothelial surface modulates hemostasis, we investigated its impact on the in vitro anticoagulant properties of ATH and AT+H. Discontinuous second order rate constant enzyme inhibition assays, fibrin formation, and plasma clot generation were performed in the presence of ATH or AT+H, with and without endothelium present. ATH had an increased rate of direct inhibition of IIa and Xa, and increased inhibition of IIa-induced fibrin formation, compared to AT+H. When compared at equal anti-Xa levels, ATH was less effective than AT+H at catalyzing inhibition of plasma clot generation. These results were found in both the presence and absence of endothelium. Endothelium decreased the rate of IIa inhibition, and reduced clot time in IIa-induced fibrin formation and plasma clot generation assays, for both ATH and AT+H. Endothelium did not impact the activity of ATH differently to AT+H. This supports the growing body of evidence suggesting ATH may be a beneficial anticoagulant for potential clinical use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".