Characterization of In Vitro Hemostatic Peptide Effects by Thromboelastography
Bibliographic record
Abstract
In this study, we validated a thromboelastography (TEG) method to evaluate the hemostatic effects of 3 peptides. The first peptide is an ideal amphipathic peptide composed of 22 leucine and lysine in a ratio of 2:1. At a very low concentration, the peptide had a procoagulant effect shown by decreases in reaction time (R) and coagulation time (K) but was impaired by a decrease in maximum amplitude (MA). At higher concentrations, the peptide had an anticoagulant effect. The α angle was minimally affected by the peptide. The second peptide is melittin derived from bee venom. Melittin showed procoagulant effects reflected by a decrease in clotting time but led to lower MA. The third peptide derived from fibrinogen γ chain promoted hemostasis only at an optimal concentration and became anticoagulant at a higher concentration. The hemostatic mechanisms of each peptide were discussed. Our study would facilitate further development of peptides for either hemorrhage control or thrombosis treatment.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".