Engagement of descending inhibition from the rostral ventromedial medulla protects against chronic neuropathic pain
Bibliographic record
Abstract
A puzzling observation is why peripheral nerve injury results in chronic pain in some, but not all, patients. We explored potential mechanisms that may prevent the expression of chronic pain. Sprague Dawley (SD) or Holtzman (HZ) rats showed no differences in baseline sensory thresholds or responses to inflammatory stimuli. However, spinal nerve ligation (SNL)-induced tactile allodynia occurred in approximately 85% of SD and 50% of HZ rats, respectively. No apparent differences were observed in a survey of dorsal root ganglion or spinal neuropathic markers after SNL regardless of allodynic phenotype. SNL-induced allodynia was reversed by administration of lidocaine within the rostral ventromedial medulla (RVM), a site that integrates descending pain modulation via pain inhibitory (ie, OFF) and excitatory (ie, ON) cells. However, in SD or HZ rats with SNL but without allodynia, RVM lidocaine precipitated allodynia. Additionally, RVM lidocaine produced conditioned place preference in allodynic SD or HZ rats but conditioned place aversion in nonallodynic HZ rats. Similarly, RVM U69,593 (kappa opioid agonist) or blockade of spinal α(2) adrenergic receptors precipitated allodynia in previously nonallodynic HZ rats with SNL. All rats showed an equivalent first-phase formalin responses. However, HZ rats had reduced second-phase formalin behaviors along with fewer RVM OFF cell pauses and RVM ON cell bursts. Thus, expression of nerve injury-induced pain may ultimately depend on descending modulation. Engagement of descending inhibition protects in the transition from acute to chronic pain. These unexpected findings might provide a mechanistic explanation for medications that engage descending inhibition or mimic its consequences.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".