Activity-driven relaxation of the cortical actomyosin II network synchronizes Munc18-1-dependent neurosecretory vesicle docking
Bibliographic record
Abstract
In neurosecretory cells, secretory vesicles (SVs) undergo Ca2+-dependent fusion with the plasma membrane to release neurotransmitters. How SVs cross the dense mesh of the cortical actin network to reach the plasma membrane remains unclear. Here we reveal that, in bovine chromaffin cells, SVs embedded in the cortical actin network undergo a highly synchronized transition towards the plasma membrane and Munc18-1-dependent docking in response to secretagogues. This movement coincides with a translocation of the cortical actin network in the same direction. Both effects are abolished by the knockdown or the pharmacological inhibition of myosin II, suggesting changes in actomyosin-generated forces across the cell cortex. Indeed, we report a reduction in cortical actin network tension elicited on secretagogue stimulation that is sensitive to myosin II inhibition. We reveal that the cortical actin network acts as a ‘casting net’ that undergoes activity-dependent relaxation, thereby driving tethered SVs towards the plasma membrane where they undergo Munc18-1-dependent docking. Secretory vesicles must cross a dense cortical actin network to dock and fuse with the plasma membrane. Papadopulos et al. reveal that, in neurosecretory cells, relaxation of this network acts as a 'casting net', driving tethered vesicles towards the plasma membrane.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".