Tor1a+/- mice develop dystonia-like movements via a striatal dopaminergic dysregulation triggered by peripheral nerve injury
Bibliographic record
Abstract
Isolated generalized dystonia is a central motor network disorder characterized by twisted movements or postures. The most frequent genetic cause is a GAG deletion in the Tor1a (DYT1) gene encoding torsinA with a reduced penetrance of 30-40 % suggesting additional genetic or environmental modifiers. Development of dystonia-like movements after a standardized peripheral nerve crush lesion in wild type (wt) and Tor1a+/- mice, that express 50 % torsinA only, was assessed by scoring of hindlimb movements during tail suspension, by rotarod testing and by computer-assisted gait analysis. Western blot analysis was performed for dopamine transporter (DAT), D1 and D2 receptors from striatal and quantitative RT-PCR analysis for DAT from midbrain dissections. Autoradiography was used to assess the functional DAT binding in striatum. Striatal dopamine and its metabolites were analyzed by high performance liquid chromatography. After nerve crush injury, we found abnormal posturing in the lesioned hindlimb of both mutant and wt mice indicating the profound influence of the nerve lesion (15x vs. 12x relative to control) resembling human peripheral pseudodystonia. In mutant mice the phenotypic abnormalities were increased by about 40 % (p < 0.05). This was accompanied by complex alterations of striatal dopamine homeostasis. Pharmacological blockade of dopamine synthesis reduced severity of dystonia-like movements, whereas treatment with L-Dopa aggravated these but only in mutant mice suggesting a DYT1 related central component relevant to the development of abnormal involuntary movements. Our findings suggest that upon peripheral nerve injury reduced torsinA concentration and environmental stressors may act in concert in causing the central motor network dysfunction of DYT1 dystonia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".