The contralateral modulatory effects of transcutaneous electrical nerve stimulation on tonic heat and cold pain
Bibliographic record
Abstract
Objective To investigate the modulation effect of transcutaneous electrical nerve stimulation(TENS)when applied controlatarally to the hand of pain induced by two types of thermal tonic noxious stimulations. Methods Twenty healthy male subjects participated in a baseline(only tonic thermal pain)condition and pain modulation conditions(pain and TENS).Subject put the non-dominant left hand into a thermal bath while the right hand received modulation.The ratings of pain intensity and distress were measured every 15 s during two separate tonic heat(47 ℃,3 min)and tonic cold(1 ℃,3 min)pain tests.Additionally,subjective perception scored on the short-form McGill pain questionnaire(SF-MPQ)was analyzed. Results TENS exhibited significant pain modulation effects of intensity and distress measures in the heat,but not cold test.Likewise,the SF-MPQ results showed significant reduction in the heat,but not cold test. Conclusion The results suggest that clinicians can use TENS contralaterally to the site of pain where injury area may be difficult to achieve.A central inhibitory mechanism is induced by contralateral TENS.The differential modulation effects on cold pain and heat pain suggest that the analgesia of TENS may be partly dependent on the quality of pain modality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.005 | 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".