Canadian Society of Pharmacology and Therapeutics
Bibliographic record
Abstract
Background & Objectives. We recently showed that application of muscarinic acetylcholine type 1 receptor (M 1 R) antagonists (pirenzepine (PZ) or muscarinic toxin 7 (MT7)) reverse nerve degeneration in different rodent models of peripheral neuropathy and -arrestin played a role in mediating these effects. To understand the mechanism of action of PZ and MT7, we investigated whether these drugs possess -arrestin-biased agonism at M1R. Methods. HEK 293 cells and cultured adult rat dorsal root ganglia (DRG) sensory neurons were used. Inositol-phosphate one (IP1) measurement, NanoBRET and luminescence-based M 1 R internalization assays were used. Phospho-specific immunoblotting for serine and threonine was performed on purified M 1 R. Gq inhibitor and -Arrestin KO HEK293 cells were used to determine the role of Gq-protein and arrestins. Western blot was used to measure ERK activation. Statistics was determined using one-way ANOVA followed by post hoc analysis (n = 3, minimum 2 assays). Results. M 1 R agonists and antagonists induced Halo-tagged -arrestin2 recruitment to M 1 R-Nluc in a dose-dependent manner at 5 and 30 min, respectively. Unlike MT7 and PZ, muscarine increased IP1 level, while PZ and MT7 dosedependently inhibited muscarine-induced IP1 generation. MT7 and PZ increased ERK phosphorylation in transfected HEK293 and DRG neurons. Results suggest PZ/MT7 possess arrestin-biased agonism. Unlike Gq protein, -arrestins are necessary for PZ/MT7-induced ERK phosphorylation. PZ/MT7 impacted serine/threonine phosphorylation status of M 1 R. Surprisingly, unlike carbachol, PZ/MT7 not only did not induce M1R internalization but increased surface expression of the receptor. Conclusion. Selective/specific muscarinic receptor antagonists act as biased agonists at M 1 R.
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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 | 0.001 |
| 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 | 0.000 |
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".