Deficits in ascending and descending pain modulation pathways in patients with postherpetic neuralgia
Bibliographic record
Abstract
Postherpetic Neuralgia (PHN), develops after the resolution of the herpes zoster mucocutaneous eruption, is a debilitating chronic pain. However, there is a lack of knowledge regarding the underlying mechanisms associated with ascending and descending pain modulations in PHN patients. Here, we combined psychophysics with structural and functional magnetic resonance imaging (MRI) techniques to investigate the brain alternations in PHN patients. Psychophysical tests showed that compared with healthy controls, PHN patients had increased state and trait anxiety and depression. Structural MRI data indicated that PHN patients had significantly smaller gray matter volumes of the thalamus and amygdala than healthy controls, and the thalamus volume was negatively correlated with pain intensity (assessed using the Short-form of the McGill pain questionnaire) in PHN patients. When the thalamus and periaqueductal gray matter (PAG) were used as the seeds, resting-state functional MRI data revealed abnormal patterns of functional connectivity within ascending and descending pain pathways in PHN patients, e.g., increased functional connectivity between the thalamus and somatosensory cortices and decreased functional connectivity between the PAG and frontal cortices. In addition, subjective ratings of both Present Pain Index (PPI) and Beck-Depression Inventory (BDI) were negatively correlated with the strength of functional connectivity between the PAG and primary somatosensory cortex (SI), and importantly, the effect of BDI on PPI was mediated by the PAG-SI functional connectivity. Overall, our results provided evidence suggesting deficits in ascending and descending pain modulation pathways, which were highly associated with the intensity of chronic pain and its emotional comorbidities in PHN patients. Therefore, our study deepened our understanding of the pathogenesis of PHN, which would be helpful in determining the optimized treatment for the patients.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".