Early synaptic dysfunction induced by α-synuclein in a rat model of Parkinson’s disease
Bibliographic record
Abstract
Abstract Evidence suggests that synapses are affected first in Parkinson’s disease (PD). Here, we tested the claim that pathological accumulation of α-synuclein, and subsequent synaptic disruption, occur in absence of dopaminergic neuron loss in PD. We determined early synaptic changes in rats that overexpress human α-synuclein by local injection of viral-vectors in midbrain. We aimed to achieve α-synuclein levels sufficient to induce terminal pathology without significant loss of nigral neurons. We tested synaptic disruption in vivo by analyzing motor defects and binding of a positron emission tomography (PET) radioligand to the vesicular monoamine transporter 2, (VMAT2), [ 11 C]dihydrotetrabenazine (DTBZ). Animals overexpressing α-synuclein had progressive motor impairment and, 12 weeks post-surgery, showed asymmetric in vivo striatal DTBZ binding. The PET images matched ligand binding in post-mortem tissue, and histological markers of dopaminergic integrity. Histology confirmed the absence of nigral cell death with concomitant significant loss of striatal terminals. Progressive aggregation of proteinase-K resistant and Ser129-phosphorylated α-synuclein was observed in dopaminergic terminals, in dystrophic swellings that resembled axonal spheroids and contained mitochondria and vesicular proteins. In conclusion, pathological α-synuclein in nigro-striatal axonal terminals leads to early axonal pathology, synaptic disruption, dysfunction of dopaminergic neurotransmission, motor impairment, and measurable change of VMAT2 in the absence of cell loss.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".