Rap1 Activation in Collagen Phagocytosis Is Dependent on Nonmuscle Myosin II-A
Bibliographic record
Abstract
Rap1 enhances integrin-mediated adhesion but the link between Rap1 activation and integrin function in collagen phagocytosis is not defined. Mass spectrometry of Rap1 immunoprecipitates showed that the association of Rap1 with nonmuscle myosin heavy-chain II-A (NMHC II-A) was enhanced by cell attachment to collagen beads. Rap1 colocalized with NM II-A at collagen bead-binding sites. There was a transient increase in myosin light-chain phosphorylation after collagen-bead binding that was dependent on myosin light-chain kinase but not Rho kinase. Inhibition of myosin light-chain phosphorylation, but not myosin II-A motor activity inhibited collagen-bead binding and Rap activation. In vitro binding assays demonstrated binding of Rap1A to filamentous myosin rods, and in situ staining of permeabilized cells showed that NM II-A filaments colocalized with F-actin at collagen bead sites. Knockdown of NM II-A did not affect talin, actin, or beta1-integrin targeting to collagen beads but targeting of Rap1 and vinculin to collagen was inhibited. Conversely, knockdown of Rap1 did not affect localization of NM II-A to beads. We conclude that MLC phosphorylation in response to initial collagen-bead binding promotes NM II-A filament assembly; binding of Rap1 to myosin filaments enables Rap1-dependent integrin activation and enhanced collagen phagocytosis.
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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 | 0.001 |
| 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".