Gray and white matter abnormalities in primary trigeminal neuralgia with and without neurovascular compression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Previous researches have reported gray and white matter microalterations in primary trigeminal neuralgia (TN) with neurovascular compression (NVC). The central mechanism underlying TN without NVC are unknown but may include changes in specific brain regions or circuitries. This study aimed to investigate abnormalities in the gray matter (GM) and white matter (WM) of the whole brain and the possible pathogenetic mechanism underlying this disease. METHODS: We analyzed brain morphologic images of TN patients, 23 with NVC (TN wNVC) and 22 without NVC (TN wNVC) compared with 45 healthy controls (HC). All subjects underwent 3T-magnetic resonance imaging and pain scale evaluation. Voxel-based morphometry (VBM) and surface-based morphometry (SBM) were used to investigate whole brain grey matter quantitatively; graph theory was applied to obtain network measures based on extracted DTI data based on DTI data of the whole brains. Sensory and affective pain rating indices were assessed using the visual analog scale (VAS) and short-form McGill Pain Questionnaire (SF-MPQ). RESULTS: The VBM and SBM analyses revealed widespread decreases in GM volume and cortical thickness in TN wNVC compared to TN woNVC, and diffusion metrics measures and topology organization changes revealed DTI showed extensive WM integrity alterations. However, above structural changes differed between TN wNVC and TN woNVC, and were related to specific chronic pain modulation mechanism. CONCLUSION: Abnormalities in characteristic regions of GM and WM structural network were found in TN woNVC compared with TN wNVC group, suggesting differences in pathophysiology of two types of TN.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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 it