Does intra-epidermal electrical stimulation activate mechano- and thermo-nociceptors? A discrimination approach
Bibliographic record
Abstract
BACKGROUND: Objective laboratory tests are needed to diagnose lesions within the nociceptive system accurately. One approach is assessing pain-related evoked potentials (PREPs) in response to intra-epidermal electrical stimulation (IES). In this context, peripheral characterization of the specificity of nociceptor activation with IES is needed. NEW METHOD: As IES directly depolarizes free nerve endings, it might allow a more comprehensive nociceptor activation than classical contact heat stimulation. Hence, this study aimed to investigate whether mechano-nociceptors are activated by IES. To test this hypothesis, a heat pain model was used to assess whether IES would show comparable pain hypersensitivity in the experimentally-induced area of secondary mechanical hyperalgesia (SMH), as known for pinprick but not for contact heat stimuli. Pain ratings and PREPs were recorded in response to 15 contact heat and pinprick stimuli as well as IES applied to the volar forearm before (PRE) and after (POST) a heat pain model inducing an area of SMH (EXP) or a control model (CTRL). RESULTS AND COMPARISON WITH EXISTING METHODS: All 24 participants (25.5 ± 4.7 y, 10 f/14 m) presented with SMH in POST-EXP condition. Pain ratings were significantly increased in EXP versus CTRL for IES (p = 0.016) and pinprick (p = 0.006) but not for contact heat (p = 0.683). PREP NP-amplitude between EXP and CTRL was only increased in response to pinprick (p = 0.027), but not to IES (p = 0.547) and contact heat stimuli (p = 0.070). CONCLUSIONS: Psychophysical assessments suggest mechano-nociceptor activation by IES, while PREPs do not support this assumption, indicating the predominant activation of thermo-nociceptors by IES.
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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 | 0.001 | 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) | 0.000 | 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".