Salivary beta-endorphin and substance P are not biomarkers of neuropathic chronic pain propensity
Bibliographic record
Abstract
OBJECTIVE: The pathophysiology of chronic pain is complex, with most of our knowledge being derived from preclinical studies. The search for biomarkers mirroring the pathophysiology of chronic pain is ongoing, and there is an increasing interest in saliva as a diagnostic tool. Given what is known about salivary substance P and salivary gland innervation, we hypothesized that salivary substance P and/or beta-endorphin might reflect the basal activity of these neuropeptides in the central nervous system, thereby perhaps mirroring a general propensity to chronic pain. Based on this overall hypothesis, our aim was to compare salivary levels of these neuropeptides in chronic neuropathic pain patients with healthy controls. An additional aim was to relate salivary levels to plasma levels. MATERIALS AND METHODS: We compared salivary concentrations of beta-endorphin and substance P in 14 chronic neuropathic pain patients with concentrations in 18 healthy controls using a Luminex technology kit. Salivary-to-plasma quotients were also calculated. RESULTS: We found no significant difference between the groups' salivary concentrations of substance P and beta-endorphin. No correlation was found between salivary and plasma concentrations of each neuropeptide, which we hypothesize might point to local production of beta-endorphin and/or substance P in the salivary glands. Given high substance P salivary-to-plasma quotients, such a local production seems more likely for substance P than for beta-endorphin. CONCLUSIONS: Propensity to neuropathic chronic pain was not substantiated by our analysis of salivary levels of substance P and/or beta-endorphin. However, we report salivary-to-plasma quotients that give potentially important physiological insight about these neuropeptides.
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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 | 0.000 |
| 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 | 0.000 |
| 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".