Characterization of an ideal amphipathic peptide as a procoagulant agent
Bibliographic record
Abstract
On the basis of previous evidence that amphipathic helical peptides accelerate Factor IXa activation of Factor X [Blostein, Rigby, Furie, Furie and Gilbert (2000) Biochemistry 39, 12000-12006], the present study was designed to assess the procoagulant activity of an IAP (ideal amphipathic peptide) of Lys(7)Leu(15) composition. The results show that IAP accelerates Factor X activation by Factor IXa in a concentration-dependent manner and accelerates thrombin generation by Factor Xa with a comparable peptide- and substrate-concentration-dependence. A scrambled helical peptide with the same amino acid composition as IAP, but with its amphipathicity abolished, eliminated most of the aforementioned effects. The Gla (gamma-carboxyglutamic acid)-rich domain of Factor X is required for IAP activity, suggesting that this peptide behaves as a phospholipid membrane. This hypothesis was confirmed, using fluorescence spectroscopy, by demonstrating direct binding between IAP and the Gla-rich domain of Factor X. In addition, the catalytic efficiencies of the tenase and prothrombinase enzymatic complexes, containing cofactors Factor VIIIa and Factor Va respectively, are enhanced by IAP. Finally, we show that IAP delays clot lysis in vitro. In summary, these observations demonstrate that IAP not only enhances essential procoagulant reactions required for fibrin generation, but also inhibits fibrinolysis, suggesting a potential role for IAP as a haemostatic agent.
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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) | 0.000 | 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".