Phospholipid composition influences the binding of multimerin 1 and factor V/Va to the platelet membrane and modulates thrombin generation in plasma
Bibliographic record
Abstract
Multimerin 1 (MMRN1) binds coagulation factor V (FV) and its activated form (Va) with high affinity. Both proteins bind to activated platelets and to platelet‐like membranes containing phosphatidylserine (PS) and phosphatidylehtanolamine (PE). The attenuation of FV dependent plasma thrombin generation in vitro, and the activation dependent binding of MMRN1 to platelets, led us to evaluate MMRN1 and FV/Va binding to membranes of various lipid compositions. Binding was evaluated by phospholipid binding ELISA, and surface plasmon resonance. Like FVa, MMRN1‐lipid binding was enhanced by increasing PS content of PS:PC membranes, and by increasing PE and cholesterol content of low PS membranes. While FV binding was enhanced by increasing PE content, significant binding occurred without PE, and to pure PC. Lipid mixtures that were optimal for MMRN1 and FVa binding also enhanced thrombin generation in plasma (without MMRN1) as measured by modified calibrated automated thrombograms. The data suggest that activation‐induced changes in the platelet membrane lipid distribution, alter MMRN1 and FVa binding, and influence the ability of MMRN1 to modulate FV/Va function in coagulation. Supported by CIHR and HSFO grants
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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) | 0.002 | 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".