Thermosensitivity of muscle: high‐intensity thermal stimulation of muscle tissue induces muscle pain in humans
Bibliographic record
Abstract
Small-calibre afferent units responding to thermal stimuli have previously been reported to exist in muscle. The question as to whether these receptors in humans mediate subjective thermal sensations from muscle remains unresolved. The aims of the present study were to determine in humans whether intramuscular injection of warm and cold isotonic saline elicits temperature sensations, muscle pain or any other sensations. In 15 subjects, no thermal sensations assessed on a temperature visual analogue scale (VAS) could be detected with intramuscular injections of isotonic saline (1.5 ml) into the anterior tibial muscle at temperatures ranging from 8 to 48 degrees C. The same subjects recorded strongly increasing scores on a temperature VAS when thermal stimuli in the same intensity range were applied to the skin overlying the muscle by a contact thermode. However, I.M. isotonic saline of 48 degrees C induced muscle pain with peak scores of 3.2 +/- 0.8 cm on a VAS scale ranging from 0 to 10 cm. Using the the McGill pain questionnaire a subgroup, of subjects qualitatively described the pain using the 'thermal hot' and 'dullness' word groups. Temperature measurements within the muscle during the stimulating injections showed that the time course of the pain sensation elicited by saline at 48 degrees C paralleled that of the intramuscular temperature and far outlasted the injection time. The present data show that high-intensity thermal stimulation of muscle is associated with muscle pain. High-threshold warm-sensitive receptors may mediate the pain following activation by temperatures of 48 degrees C or more. Taken together, the data indicate that thermosensation from a given volume of muscle is less potent than nociception.
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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 | 0.001 |
| 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) | 0.003 | 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".