4D intravital imaging studies identify platelets as the predominant cellular procoagulant surface in a mouse hemostasis model
Bibliographic record
Abstract
ABSTRACT: Interplay between platelets, coagulation factors, endothelial cells (ECs), and fibrinolytic factors is necessary for effective hemostatic plug formation. This study describes a 4-dimensional (4D) imaging platform to visualize and quantify hemostatic plug components in mice with high spatiotemporal resolution. Fibrin accumulation after laser-induced vascular injury was observed at the platelet plug-EC interface, controlled by the antagonistic balance between fibrin generation and breakdown. We observed less fibrin accumulation in mice expressing low levels of tissue factor or F12-/-mice compared with controls, whereas increased fibrin accumulation, including on the vasculature adjacent to the platelet plug, was observed in plasminogen-deficient mice or wild-type mice treated with tranexamic acid. Phosphatidylserine (PS), a membrane lipid critical for the assembly of coagulation factors, was first detected at the platelet plug-EC interface, followed by exposure across the endothelium. Impaired PS exposure resulted in a significant reduction in fibrin accumulation in cyclophilin D-/-mice. Adoptive transfer studies demonstrated a key role for PS exposure on platelets, and to a lesser degree on ECs, in fibrin accumulation during hemostatic plug formation. Together, these studies suggest that (1) platelets are the functionally dominant procoagulant cellular surface, and (2) plasmin is critical for limiting fibrin accumulation at the site of a forming hemostatic plug.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".