β<sub>2</sub>‐adrenergic receptor activation decreases the mechanical sensitivity of rat masticatory muscle afferent fibres
Bibliographic record
Abstract
Abstract Background Activation of β2 adrenergic receptors reduces cutaneous mechanical pain thresholds in rats. While β2 adrenergic receptor activation may contribute to mechanisms that underlie temporomandibular joint pain, its effect on masticatory muscle pain sensitivity is uncertain. Objectives The current study sought to determine the extent to which β adrenergic receptors are expressed by masticatory muscle afferent fibres, and to assess the effect of local activation of these receptors on the mechanical sensitivity of masticatory muscle afferent fibres in rats. Methods Trigeminal ganglion neurons that innervate the rat (n = 12) masseter muscle and lower lip were identified by tissue injection of fluorescent dyes and were then stained with antibodies against β1 or β2 adrenergic receptors. Extracellular recordings from 60 trigeminal ganglion neurons that innervate the masticatory muscle were undertaken in a second group of anaesthetised rats of both sexes (n = 37) to assess afferent mechanical activation thresholds. Thresholds were assessed before and after injection of the β adrenergic receptor agonists into masticatory muscle. Results β1 and β2 adrenergic receptor expression was greater in labial skin than in masticatory muscle ganglion neurons (p < .05, one‐way ANOVA, Holm–Sidak test). There was a higher expression of β2 adrenergic receptors in masticatory muscle ganglion neurons in males than in females. The mixed β agonist isoproterenol increased afferent mechanical activation threshold in male but not female rats (p < .05, Mann–Whitney test). In male rats, salbutamol, a β2 selective agonist, also increased afferent mechanical activation threshold but hydralazine, a vasodilator, did not (p < .05, Mann–Whitney test). Conclusion Activation of β2 adrenergic receptors decreases the mechanical sensitivity of masticatory muscle afferent fibres in a sex‐related manner.
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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) | 0.004 | 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".