Time course and magnitude of alpha-synuclein inclusion formation and nigrostriatal degeneration in the rat model of synucleinopathy triggered by intrastriatal α-synuclein preformed fibrils
Bibliographic record
Abstract
Animal models that accurately recapitulate the accumulation of alpha-synuclein (α-syn) inclusions, progressive neurodegeneration of the nigrostriatal system and motor deficits can be useful tools for Parkinson's disease (PD) research. The preformed fibril (PFF) synucleinopathy model in rodents generally displays these PD-relevant features, however, the magnitude and predictability of these events is far from established. We therefore sought to optimize the magnitude of α-syn accumulation and nigrostriatal degeneration, and to understand the time course of both. Rats were injected unilaterally with different quantities of α-syn PFFs (8 or 16 μg of total protein) into striatal sites selected to concentrate α-syn inclusion formation in the substantia nigra pars compacta (SNpc). Rats displayed an α-syn PFF quantity-dependent increase in the magnitude of ipsilateral SNpc inclusion formation at 2 months and bilateral loss of nigral dopamine neurons at 6 months. Unilateral 16 μg PFF injection also resulted in modest sensorimotor deficits in forelimb adjusting steps associated with degeneration at 6 months. Bilateral injection of 16 μg α-syn PFFs resulted in symmetric bilateral degeneration equivalent to the ipsilateral nigral degeneration observed following unilateral 16 μg PFF injection (~50% loss). Bilateral PFF injections additionally resulted in alterations in several gait analysis parameters. These α-syn PFF parameters can be applied to generate a reproducible synucleinopathy model in rats with which to study pathogenic mechanisms and vet potential disease-modifying therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".