Cooperative Regulation by Rac and Rho of Agrin-induced Acetylcholine Receptor Clustering in Muscle Cells
Bibliographic record
Abstract
A key aspect of neuromuscular synapse formation is the clustering of muscle acetylcholine receptors (AChR) at synaptic sites in response to neurally secreted agrin. Agrin-induced AChR clustering in cultured myotubes proceeds via the initial formation of small microclusters, which then aggregate to form AChR clusters. Here we show that the coupling of agrin signaling to AChR clustering is dependent on the coordinated activities of Rac and Rho GTPases. The addition of agrin induces the sequential activation of Rac and Rho in C2 muscle cells. The activation of Rac is rapid and transient and constitutes a prerequisite for the subsequent activation of Rho. This temporal pattern of agrin-induced Rac and Rho activation reflects their respective roles in AChR cluster formation. Whereas agrin-induced activation of Rac is necessary for the initial phase of AChR cluster formation, which involves the aggregation of diffuse AChR into microclusters, Rho activation is crucial for the subsequent condensation of these microclusters into full-size AChR clusters. Co-expression of constitutively active forms of Rac and Rho is sufficient to induce the formation of mature AChR clusters in the absence of agrin. These results establish that Rac and Rho play distinct but complementary roles in the mechanism of agrin-induced AChR clustering.
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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 | 0.001 |
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".