Spinal NK-1 receptor expressing neurons mediate opioid-induced hyperalgesia and antinociceptive tolerance via activation of descending pathways
Bibliographic record
Abstract
Opioids can induce hyperalgesia in humans and in animals. Mechanisms of opiate-induced hyperalgesia and possibly of spinal antinociceptive tolerance may be linked to pronociceptive adaptations occurring at multiple levels of the nervous system including activation of descending facilitatory influences from the brainstem, spinal neuroplasticity, and changes in primary afferent fibers. Here, the role of NK-1 receptor expressing cells in the spinal dorsal horn in morphine-induced hyperalgesia and spinal antinociceptive tolerance was assessed by ablating these cells with intrathecal injection of SP-saporin (SP-SAP). Ablation of NK-1 receptor expressing cells prevented (a) morphine-induced thermal and mechanical hypersensitivity, (b) increased touch-evoked spinal FOS expression, (c) upregulation of spinal dynorphin content and (d) the rightward displacement of the spinal morphine antinociceptive dose-response curve (i.e., tolerance). Morphine-induced hyperalgesia and antinociceptive tolerance were also blocked by spinal administration of ondansetron, a serotonergic receptor antagonist. Thus, NK-1 receptor expressing neurons play a critical role in sustained morphine-induced neuroplastic changes which underlie spinal excitability reflected as thermal and tactile hypersensitivity to peripheral stimuli, and to reduced antinociceptive actions of spinal morphine (i.e., antinociceptive tolerance). Ablation of these cells likely eliminates the ascending limb of a spinal-bulbospinal loop that engages descending facilitation and elicits subsequent spinal neuroplasticity. The data may provide a basis for understanding mechanisms of prolonged pain which can occur in the absence of tissue injury.
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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".