Inhibition of plasmin generation in plasma by heparin, low molecular weight heparin, and a covalent antithrombin–heparin complex
Bibliographic record
Abstract
: The clinical limitations of unfractionated heparin (UFH) and low molecular weight heparin (LMWH) led to the development of an antithrombin-heparin covalent complex (ATH), which displays superior anticoagulant abilities compared with UFH. A recent study investigating its interaction with fibrinolysis showed that ATH inhibited free and fibrin bound plasmin and decreased plasmin generation on fibrin clots. These studies were conducted using purified components and did not elucidate the interaction of ATH with plasmin in the presence of its natural inhibitors α2-antiplasmin (α2-AP) and α2-macroglobulin (α2-M). The aim of this study was to determine the effects of ATH, UFH, and LMWH on plasmin generation in plasma, under more physiological conditions. Plasmin generation in plasma in the absence and presence of anticoagulants was initiated by tissue plasminogen activator and soluble fibrin fragments, and plasmin and plasmin-α2-M complexes generated over time were quantified chromogenically. Generation of plasmin-α2-AP complexes and consumption of plasminogen were quantified by ELISA. Plasmin generation was decreased in the presence of UFH and ATH, whereas LMWH had no effect. Neither plasminogen consumption nor generation of plasmin-α2-AP complexes were affected by UFH or ATH. However, plasmin-α2-M complexes were slightly reduced by ATH suggesting that ATH may be able to compete with α2-M for plasmin. Plasmin generation may be mildly inhibited by heparin-based anticoagulants; however, heparin-catalyzed antithrombin activity is not a major inhibitor of plasmin, as compared to its natural inhibitors α2-AP and α2-M. This adds to our understanding of ATH mechanisms of action and aids in its development for clinical use.
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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 | 0.001 | 0.001 |
| 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".