A novel association between platelet filamin A and soluble N-ethylmaleimide sensitive factor attachment proteins regulates granule secretion
Bibliographic record
Abstract
Background and Objective The molecular mechanisms that underpin platelet granule secretion remain poorly defined. Filamin A (FLNA) is an actin-crosslinking and signaling scaffold protein whose role in granule exocytosis has not been explored despite evidence that FLNA gene mutations confer platelet defects in humans. Methods and Results Using platelets from platelet-specific conditional Flna -knockout mice, we showed that the loss of FLNA confers a severe defect in alpha (α)- and dense (δ)-granule exocytosis, as measured based on the release of platelet factor 4 (aka CXCL4) and adenosine triphosphate (ATP), respectively. This defect was observed following activation of both immunoreceptor tyrosine-based activation motif (ITAM) signaling by collagen-related peptide (CRP) and G protein–coupled receptor (GPCR) signaling by thrombin and the thromboxane mimetic U46619. CRP–induced spikes in intracellular calcium [Ca 2+ ] i were impaired in FLNA-null platelets relative to controls, confirming that FLNA regulates ITAM-driven proximal signaling. In contrast, GPCR-mediated spikes in [Ca 2+ ] i in response to thrombin and U46619 were unaffected by FLNA. Normal platelet secretion requires complexing of the soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins synaptosomal-associated protein 23 (SNAP23) and syntaxin-11 (STX11). We determined that FLNA coimmunoprecipitates with both SNAP23 and STX11 upon platelet stimulation. Conclusion FLNA regulates GPCR-driven platelet granule secretion and associates with SNAP23 and STX11 in an activation-dependent manner.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".