Localization of myosin Va is dependent on the cytoskeletal organization in the cell
Bibliographic record
Abstract
Myosin V plays an important role in membrane trafficking events. Its implication in the transport of pigment granules in melanocytes and synaptic vesicles in neurons is now well established. However, less is known about its function(s) in other cell types. Finding a common function is complicated by the diversity of myosin V expression in different tissues and organisms and by its association with different subcellular compartments. Here we show that myosin V is present in a variety of cells. Within the same cell type under different physiological conditions, we observed two main cellular locations for myosin V that were dependent on the dynamics of the plasma membrane: in cells with highly dynamic membranes, myosin V was specifically concentrated at the leading edge in membrane ruffles, whereas in cells with less dynamic membranes, myosin V was enriched around the microtubule-organizing center. The presence of myosin V in the leading ruffling edge of the cell was induced by growth factor stimulation and was dependent on the presence of a functional motor domain. Moreover, myosin V localization at the microtubule-organizing center was dependent on the integrity of the microtubules. In polarized epithelial cells (WIF-B), where the microtubule-organizing region is close to the actin-rich apical surface, one single pool of myosin V, sensitive to the integrity of both microtubules and actin filaments, was observed.
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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 | 0.000 |
| 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".