GABAA Receptor Availability Changes Underlie Symptoms in Isolated Cervical Dystonia
Bibliographic record
Abstract
GABAA receptor density changes within sensorimotor regions have been reported in some isolated forms of dystonia. Whether similar abnormalities underlie symptoms in cervical dystonia is not known. In the present study, a total of 15 cervical dystonia patients and 15 age- and sex-matched controls underwent 11C-flumazenil PET/CT scanning. The density of available GABAA receptors was estimated using a Simplified Reference Tissue Model 2. Group differences were evaluated using a two-sample T test, and correlations with dystonia severity, as measured by the Toronto Western Spasmodic Torticollis Rating Scale, and disease duration were evaluated using a regression analysis. Voxel-based analyses revealed increased GABAA availability within the right precentral gyrus in brain motor regions previously associated with head turning and the left parahippocampal gyrus. GABAA availability within the bilateral cerebellum was negatively correlated with dystonia severity, and GABAA availability within the right thalamus and a variety of cerebellar and cortical regions were negatively correlated with disease duration. While GABAA density changes within primary motor areas could represent a partial compensatory response to loss of inhibition within sensorimotor network, GABAergic signaling impairment within the cerebellum may be a key contributor to dystonia severity.
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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 | 0.001 | 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) | 0.003 | 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".