Reduced Basal Ganglia μ-Opioid Receptor Availability in Trigeminal Neuropathic Pain: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: Although neuroimaging techniques have provided insights into the function of brain regions involved in Trigeminal Neuropathic Pain (TNP) in humans, there is little understanding of the molecular mechanisms affected during the course of this disorder. Understanding these processes is crucial to determine the systems involved in the development and persistence of TNP. FINDINGS: In this study, we examined the regional μ-opioid receptor (μOR) availability in vivo (non-displaceable binding potential BPND) of TNP patients with positron emission tomography (PET) using the μOR selective radioligand [11C]carfentanil. Four TNP patients and eight gender and age-matched healthy controls were examined with PET. Patients with TNP showed reduced μOR BPND in the left nucleus accumbens (NAc), an area known to be involved in pain modulation and reward/aversive behaviors. In addition, the μOR BPND in the NAc was negatively correlated with the McGill sensory and total pain ratings in the TNP patients. CONCLUSIONS: Our findings give preliminary evidence that the clinical pain in TNP patients can be related to alterations in the endogenous μ-opioid system, rather than only to the peripheral pathology. The decreased availability of μORs found in TNP patients, and its inverse relationship to clinical pain levels, provide insights into the central mechanisms related to this condition. The results also expand our understanding about the impact of chronic pain on the limbic system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".