Selective striatal neuronal loss in a YAC128 mouse model of Huntington disease
Bibliographic record
Abstract
An expanded CAG repeat is the underlying genetic defect in Huntington disease, a disorder characterized by motor, psychiatric and cognitive deficits and striatal atrophy associated with neuronal loss. An accurate animal model of this disease is crucial for elucidation of the underlying natural history of the illness and also for testing experimental therapeutics. We established a new yeast artificial chromosome (YAC) mouse model of HD with the entire human HD gene containing 128 CAG repeats (YAC128) which develops motor abnormalities and age-dependent brain atrophy including cortical and striatal atrophy associated with striatal neuronal loss. YAC128 mice exhibit initial hyperactivity, followed by the onset of a motor deficit and finally hypokinesis. The motor deficit in the YAC128 mice is highly correlated with striatal neuronal loss, providing a structural correlate for the behavioral changes. The natural history of HD-related changes in the YAC128 mice has been defined, demonstrating the presence of huntingtin inclusions after the onset of behavior and neuropathological changes. The HD-related phenotypes of the YAC128 mice show phenotypic uniformity with low inter-animal variability present, which together with the age-dependent striatal neurodegeneration make it an ideal mouse model for the assessment of neuroprotective and other therapeutic interventions.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".