Further Evidence for Two Functional Forms of Prothrombinase Each Specific for Either of the Two Prothrombin Activation Cleavages
Bibliographic record
Abstract
Previous work showed that prothrombin derivatives cleavable only at Arg-320 (rMZ) or Arg-271 (rP2) are partial, rather than competitive, inhibitors of prothrombin activation by prothrombinase. A "ping-pong"-like model, which posits two equilibrating forms of prothrombinase, explained the inhibition pattern. The present studies were undertaken to further investigate this putative mechanism. Two models were developed, one allowing for one form of the enzyme and the other allowing for two forms. Both models also allowed channeling and ratcheting. The models were fit to full time courses of prothrombin, meizothrombin, prethrombin-2, and the B-chain. In the absence of ratcheting and channeling, neither model fits the data. In their presence, however, both models fit very well, and thus they could not be distinguished. Therefore, inhibition of rMZ activation by rP2 was studied. Inhibition was partial and the two-form model fit the data with randomly distributed residuals, whereas the one-form model did not. Initial rates of fluorescein-labeled prothrombin cleavage in the presence of various prothrombin derivatives reported by Brufatto and Nesheim (Brufatto, N., and Nesheim, M. E. (2003) J. Biol. Chem. 278, 6755-6764) were also analyzed using the two models. The two-form model fit the partial inhibition data well, whereas the one-form model did not. In addition, prothrombin at varying concentrations was activated, and subsequently, the initial rates were plotted with respect to the initial prothrombin concentration. When compared with the expected initial rates as determined by the simulation of the models, the two-form model fit the observed rates better than the one-form model. The results obtained here further support the existence of two functional forms of prothrombinase.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".