Screening of Therapeutic Strategies for Huntington's Disease in YAC128 Transgenic Mice
Bibliographic record
Abstract
Huntington’s disease (HD) is a hereditary neurodegenerative disorder caused by an unstable expansion of cytosine-adenine-guanine (CAG) repeats in the HD gene. The symptoms include cognitive dysfunction and severe motor impairment with loss of voluntary movement coordination that is later replaced by bradykinesia and rigidity. The neuropathology is characterized by neuronal loss mainly in the striatum and cortex, and the appearance of neuronal intranuclear inclusions of mutant huntingtin. The mechanisms responsible for neurodegeneration are still not fully understood although excitotoxicity and a consequent increase in intracellular calcium concentration as well as the activation of caspases and calapins are known to play a key role. There is currently no satisfactory treatment or cure for this disease. The YAC128 transgenic mice express the full-length human HD gene with 128 CAG repeats and constitute a unique model for the study of HD as they replicate the slow and biphasic progression of behavioral deficits characteristic of the human condition and show striatal neuronal loss. As such, these transgenic mice have been an invaluable model not only for the elucidation of the neurodegenerative pathways in HD, but also for the screening and development of new therapeutic approaches. Here, I will review the unique characteristics of this transgenic HD model and will provide a summary of the therapies that have been tested in these mice, namely: potentiation of the protective roles of wild-type huntingtin and mutant huntingtin aggregation, transglutaminase inhibition, inhibition of glutamate- and dopamine-induced toxicity, apoptosis inhibition, use of essential fatty acids, and the novel approach of intrabody gene therapy. The insights obtained from these and future studies will help identify potential candidates for clinical trials and will ultimately contribute to the discovery of a successful treatment for this devastating neurodegenerative disorder.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".