Gelsolin Modulates Platelet Dense Granule Secretion and Hemostasis via the Actin Cytoskeleton
Bibliographic record
Abstract
Background and Objective The mechanisms underlying platelet granule release are not fully understood. The actin cytoskeleton serves as the platelet's structural framework that is remodeled upon platelet activation. Gelsolin is a calcium-dependent protein that severs and caps existing actin filaments although its role in modulating platelet granule exocytosis is unknown. Methods The hemostatic function of wild-type (WT) and gelsolin null (Gsn−/− ) mice was measured ex vivo by rotational thromboelastometry analysis of whole blood. Platelets were purified from WT and Gsn−/− mouse blood and activated with thrombin. Platelet aggregation was assessed by light-transmission aggregometry. Clot retraction was measured to assess outside-in integrin signaling. Adenosine triphosphate (ATP) release and surface P-selectin were measured as markers of dense- and α-granule secretion, respectively. Results The kinetics of agonist-induced aggregation, clot retraction, and ATP release were accelerated in Gsn−/− platelets relative to WT. However, levels of surface P-selectin were diminished in Gsn−/− platelets. ATP release was also accelerated in WT platelets pretreated with the actin-depolymerizing drug cytochalasin D, thus mimicking the kinetics observed in Gsn−/− platelets. Conversely, ATP release kinetics were normalized in Gsn−/− platelets treated with the actin polymerization agonist jasplakinolide. Rab27b and Munc13–4 are vesicle-priming proteins known to promote dense granule secretion. Co-immunoprecipitation indicates that the association between Rab27b and Munc13–4 is enhanced in Gsn−/− platelets. Conclusions Gelsolin regulates the kinetics of hemostasis by modulating the platelet's actin cytoskeleton and the protein machinery of dense granule exocytosis.
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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) | 0.001 | 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".