Mice lacking caspase-2 are protected from behavioral changes, but not pathology, in the YAC128 model of Huntington disease
Bibliographic record
Abstract
BACKGROUND: Huntington Disease (HD) is a neurodegenerative disorder in which caspase activation and cleavage of substrates, including the huntingtin protein, has been invoked as a pathological mechanism. Specific changes in caspase-2 (casp2) activity have been suggested to contribute to the pathogenesis of HD, however unique casp2 cleavage substrates have remained elusive. We thus utilized mice completely lacking casp2 (casp2-/-) to examine the role played by casp2 in the progression of HD. This 'substrate agnostic' approach allows us to query the effect of casp2 on HD progression without pre-defining proteolytic substrates of interest. RESULTS: YAC128 HD model mice lacking casp2 show protection from well-validated motor and cognitive features of HD, including performance on rotarod, swimming T-maze, pre-pulse inhibition, spontaneous alternation and locomotor tasks. However, the specific pathological features of the YAC128 mice including striatal volume loss and testicular degeneration are unaltered in mice lacking casp2. The application of high-resolution magnetic resonance imaging (MRI) techniques validates specific neuropathology in the YAC128 mice that is not altered by ablation of casp2. CONCLUSIONS: The rescue of behavioral phenotypes in the absence of pathological improvement suggests that different pathways may be operative in the dysfunction of neural circuitry in HD leading to behavioral changes compared to the processes leading to cell death and volume loss. Inhibition of caspase-2 activity may be associated with symptomatic improvement in HD.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".