Deciphering the role of endogenous opioids in high-frequency TENS using low and high doses of naloxone
Bibliographic record
Abstract
Previous human studies have shown that the analgesic effect of high-frequency TENS could not be reversed by low doses of naloxone. The aim of the present study was to reinvestigate the possible contribution of opioid receptors to high-frequency TENS analgesia by using low (0.02 mg/kg) and high (0.14 mg/kg) doses of naloxone. Naloxone (high and low doses) and saline were administered intravenously to young healthy adults using a triple-blind randomized cross-over design. For each visit, TENS (100 Hz, 60 μs) was applied for 25 min to the external surface of the left ankle. TENS intensity was adjusted to obtain strong but comfortable (innocuous) paresthesias. Experimental pain was evoked with a 1 cm(2) thermode applied on the lateral aspect of the left heel. Subjective pain scores were obtained before, during and after TENS. Because preliminary analyses showed that the order of presentation affected the pattern of results, only the first visit of every participant could be analyzed without fear of contamination from possible carry-over effects. These revealed that TENS maintained its analgesic properties following the injection of saline (p<.001) and the injection of a low dose of naloxone (p<.05). However, when a high dose of naloxone was administered, TENS analgesia was completely blocked (p=.20). These results suggest that high-frequency TENS involves opioid receptors. An insufficient amount of opioid antagonist likely prevented previous human studies from discovering the importance of opioid receptors in producing high-frequency TENS analgesia.
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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 | 0.001 | 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) | 0.001 | 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".