In vivo quantification of glial activation in minipigs overexpressing human α‐synuclein
Bibliographic record
Abstract
Abstract Parkinson’s disease is characterized by a progressive loss of substantia nigra (SN) dopaminergic neurons and the formation of Lewy bodies containing accumulated alpha‐synuclein (α‐syn). The pathology of Parkinson’s disease is associated with neuroinflammatory microglial activation, which may contribute to the ongoing neurodegeneration. This study investigates the in vivo microglial and dopaminergic response to overexpression of α‐syn. We used positron emission tomography (PET) and the 18 kDa translocator protein radioligand, [11C](R)PK11195, to image brain microglial activation and (+)‐α‐[11C]dihydrotetrabenazine ([11C]DTBZ), to measure vesicular monoamine transporter 2 (VMAT2) availability in Göttingen minipigs following injection with recombinant adeno‐associated virus (rAAV) vectors expressing either mutant A53T α‐syn or green fluorescent protein (GFP) into the SN (4 rAAV‐α‐syn, 4 rAAV‐GFP, 5 non‐injected control minipigs). We performed motor symptom assessment and immunohistochemical examination of tyrosine hydroxylase (TH) and transgene expression. Expression of GFP and α‐syn was observed at the SN injection site and in the striatum. We observed no motor symptoms or changes in striatal [11C]DTBZ binding potential in vivo or striatal or SN TH staining in vitro between the groups. The mean [11C](R)PK11195 total volume of distribution was significantly higher in the basal ganglia and cortical areas of the α‐syn group than the control animals. We conclude that mutant α‐syn expression in the SN resulted in microglial activation in multiple sub‐ and cortical regions, while it did not affect TH stains or VMAT2 availability. Our data suggest that microglial activation constitutes an early response to accumulation of α‐syn in the absence of dopamine neuron degeneration.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".