Covalent antithrombin-heparin effect on thrombin-thrombomodulin and activated protein C reaction with factor V/Va
Bibliographic record
Abstract
Thrombomodulin (TM), which variably contains a chondroitin sulfate (+/-CS), forms an anticoagulant complex with thrombin (IIa). IIa-TM(+/-CS) converts protein C (PC) into activated PC (APC), which then inactivates activated factors V (FVa) and VIII (FVIIIa). This reduces prothrombinase and tenase complexes that generate IIa. Heparin (H) increases the rate of IIa-TM inhibition by antithrombin (AT) and enhances FV cleavage by APC. Our novel covalent AT-H (ATH) product, has superior anticoagulant activity compared to AT + unfractionated H (UFH). We studied mechanisms by which ATH versus AT + UFH inhibits IIa-TM(+/-CS), and ATH influences on APC cleavage of FV/FVa compared to UFH. Findings would determine how these reactions moderate ATH's overall effects as an anticoagulant. Discontinuous second order rate inhibition assays of IIa-TM(+/-CS) inhibition by AT + UFH or ATH were performed in presence or absence of human umbilical vein endothelial cells (HUVECs). FV/FVa cleavage by APC in the presence of UFH or ATH was analysed by Western blots. ATH increased IIa-TM(+/-CS) inhibition to a greater degree than AT + UFH, both on plastic and HUVEC surfaces. Unlike UFH, ATH did not accelerate FV cleavage by APC, but ATH did enhance FVa cleavage relative to UFH. Increased IIa-TM inhibition by ATH downregulates PC activation. However, ATH does accelerate downstream inactivation of FVa, which increases its potency for IIa generation inhibition compared to UFH. This trend holds true in the presence of APC's cofactor, protein S. Overall, ATH may have a balanced function towards inhibiting or accelerating PC pathway activities.
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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) | 0.002 | 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".