Abnormal brain spontaneous neural activity in neuromyelitis optica spectrum disorder with neuropathic pain
Bibliographic record
Abstract
Background: Neuropathic pain is one of the most common symptoms in neuromyelitis optica spectrum disorder (NMOSD). Notwithstanding, its underlying mechanism remains obscure. Methods: The amplitude of low-frequency fluctuations (ALFF) metric was employed to investigate spontaneous neural activity alterations via resting-state functional magnetic resonance imaging (rs-MRI) data from a 3.0 T MRI scanner, in a sample of 26 patients diagnosed with NMOSD with neuropathic pain (NMOSD-WNP), 20 patients with NMOSD but without neuropathic pain (NMOSD-WoNP), and 38 healthy control (HC) subjects matched for age and sex without the comorbidity of depressive or anxious symptoms. Results: It was observed that patients with NMOSD-WNP displayed a significant ALFF decrease in the left amygdala and right anterior insula, relative to both patients with NMOSD-WoNP and HC subjects. Furthermore, ALFF values in the left amygdala were negatively correlated with the scores of the Douleur Neuropathique en 4 Questions and McGill Pain Questionnaire (both sensory and affective descriptors) in patients with NMOSD-WNP. Additionally, there were negative correlations between the ALFF values in the right anterior insula and the duration of pain and the number of relapses in patients with NMOSD-WNP. Conclusion: The present study characterizes spontaneous neural activity changes in brain regions associated with sensory and affective processing of pain and its modulation, which underscore the central aspects in patients with NMOSD-WNP. These findings might contribute to a better understanding of the pathophysiologic basis of neuropathic pain in NMOSD.
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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 | 0.001 |
| 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".