Defective dentate nucleus GABA receptors in essential tremor
Bibliographic record
Abstract
The development of new treatments for essential tremor, the most frequent movement disorder, is limited by a poor understanding of its pathophysiology and the relative paucity of clinicopathological studies. Here, we report a post-mortem decrease in GABA(A) (35% reduction) and GABA(B) (22-31% reduction) receptors in the dentate nucleus of the cerebellum from individuals with essential tremor, compared with controls or individuals with Parkinson's disease, as assessed by receptor-binding autoradiography. Concentrations of GABA(B) receptors in the dentate nucleus were inversely correlated with the duration of essential tremor symptoms (r(2) = 0.44, P < 0.05), suggesting that the loss of GABA(B) receptors follows the progression of the disease. In situ hybridization experiments also revealed a diminution of GABA(B(1a+b)) receptor messenger RNA in essential tremor (↓27%). In contrast, no significant changes of GABA(A) and GABA(B) receptors (protein and messenger RNA), GluN2B receptors, cytochrome oxidase-1 or GABA concentrations were detected in molecular or granular layers of the cerebellar cortex. It is proposed that a decrease in GABA receptors in the dentate nucleus results in disinhibition of cerebellar pacemaker output activity, propagating along the cerebello-thalamo-cortical pathways to generate tremors. Correction of such defective cerebellar GABAergic drive could have a therapeutic effect in essential tremor.
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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".