Towards a Non-Human Primate Model of Alpha-Synucleinopathy for Development of Therapeutics for Parkinson’s Disease: Optimization of AAV1/2 Delivery Parameters to Drive Sustained Expression of Alpha Synuclein and Dopaminergic Degeneration in Macaque
Bibliographic record
Abstract
Recent failures in clinical trials for disease modification in Parkinson's disease have highlighted the need for a non-human primate model of the synucleinopathy underpinning dopaminergic neuron degeneration. The present study was defined to begin the development of such a model in cynomolgus macaque. We have validated surgical and vector parameters to define a means to provide a robust over-expression of alpha-synuclein which is associated with Lewy-like pathology and robust degeneration of the nigrostriatal pathway. Thus, an AAV1/2 vector incorporating strong transcription and transduction regulatory elements was used to deliver the gene for the human A53T mutation of alpha-synuclein. When injected into 4 sites within each substantia nigra (7 μl per site, 1.7 x 1012 gp/ml), this vector provided expression lasting at least 4 months, and a 50% loss of nigral dopaminergic neurons and a 60% reduction in striatal dopamine. Further studies will be required to develop this methodology into a validated model of value as a drug development platform.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".