Agrin-Induced Phosphorylation of the Acetylcholine Receptor Regulates Cytoskeletal Anchoring and Clustering
Bibliographic record
Abstract
At the developing neuromuscular junction, a motoneuron-derived factor called agrin signals through the muscle-specific kinase receptor to induce postsynaptic aggregation of the acetylcholine receptor (AChR). The agrin signaling pathway involves tyrosine phosphorylation of the AChR beta subunit, and we have tested its role in receptor localization by expressing tagged, tyrosine-minus forms of the beta subunit in mouse Sol8 myotubes. We find that agrin-induced phosphorylation of the beta subunit occurs only on cell surface AChR, and that AChR-containing tyrosine-minus beta subunit is targeted normally to the plasma membrane. Surface AChR that is tyrosine phosphorylated is less detergent extractable than nonphosphorylated AChR, indicating that it is preferentially linked to the cytoskeleton. Consistent with this, we find that agrin treatment reduces the detergent extractability of AChR that contains tagged wild-type beta subunit but not tyrosine-minus beta subunit. In addition, agrin-induced clustering of AChR containing tyrosine-minus beta subunit is reduced in comparison to wild-type receptor. Thus, we find that agrin-induced phosphorylation of AChR beta subunit regulates cytoskeletal anchoring and contributes to the clustering of the AChR, and this is likely to play an important role in the postsynaptic localization of the receptor at the developing synapse.
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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 | 0.000 |
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 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".