The Factor V Activation Paradox
Bibliographic record
Abstract
The prothrombinase complex consists of the protease factor Xa, Ca2+, and factor Va assembled on an anionic membrane. Factor Va functions both as a receptor for factor Xa and a positive effector of factor Xa catalytic efficiency and thus is key to efficient conversion of prothrombin to thrombin. The activation of the procofactor, factor V, to factor Va is an essential reaction that occurs early in the process of tissue factor-initiated blood coagulation; however, the catalytic sequence leading to formation of factor Va is a subject of disagreement. We have used biophysical and biochemical approaches to establish the second order rate constants and reaction pathways for the activation of phospholipid-bound human factor V by native and recombinant thrombin and meizothrombin, by mixtures of prothrombin activation products, and by factor Xa. We have also reassessed the activation of phospholipid-bound human prothrombin by factor Xa. Numerical simulations were performed incorporating the various pathways of factor V activation including the presence or absence of the pathway of factor V-independent prothrombin activation by factor Xa. Reaction pathways for factor V activation are similar for all thrombin forms. Empirical rate constants and the simulations are consistent with the following mechanism for factor Va formation. alpha-Thrombin, derived from factor Xa cleavage of phospholipid-bound prothrombin via the prethrombin 2 pathway, catalyzes the initial activation of factor V; generation of factor Va in a milieu already containing factor Xa enables prothrombinase formation with consequent meizothrombin formation; and meizothrombin functions as an amplifier of the process of factor V activation and thus has an important procoagulant role. Direct activation of factor V by factor Xa at physiologically relevant concentrations does not appear to be a significant contributor to factor Va formation.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".