Stabilization Versus Inhibition of TAFIa by Competitive Inhibitors in Vitro
Bibliographic record
Abstract
Two competitive inhibitors of TAFIa (activated thrombin-activable fibrinolysis inhibitor), 2-guanidinoethylmercaptosuccinic acid and potato tuber carboxypeptidase inhibitor, variably affect fibrinolysis of clotted human plasma. Depending on their concentration, the inhibitors shortened, prolonged, or had no effect on lysis in vitro. The inhibitor-induced effects were both tissue-type plasminogen activator (tPA) and TAFIa concentration-dependent. Inhibitor-dependent prolongation was favored at lower tPA concentrations. The magnitude of the prolongation increased with TAFIa concentration, and the maximal prolongation observed at each TAFIa concentration increased saturably with respect to TAFIa. A theoretical maximal prolongation of 20-fold was derived from a plot of the maximum prolongation versus TAFIa. This represents, for the first time, a measurement of the maximal antifibrinolytic potential of TAFIa in vitro. Because TAFIa spontaneously decays, the stabilization of TAFIa was investigated as a mechanism explaining the inhibitor-dependent prolongation of lysis. Both inhibitors stabilized TAFIa in a concentration-dependent, non-saturable manner. Although their KI values differed by three orders of magnitude, TAFIa was identically stabilized when the fraction of inhibitor-bound TAFIa was the same. The data fit a model whereby only free TAFIa decays. Therefore, the variable effects of competitive inhibitors of TAFIa on fibrinolysis can be rationalized in terms of free TAFIa and lysis time relative to the half-life of TAFIa.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".