In vivo susceptibility to energy failure parkinsonism and LRRK2 kinase activity
Bibliographic record
Abstract
The G2019S mutation of LRRK2 represents a risk factor for idiopathic Parkinson's disease. Here, we investigate whether LRRK2 kinase activity regulates susceptibility to the environmental toxin 1-methyl-4-phenyl-1,2,5,6-tetrahydropyridine (MPTP). G2019S knock-in mice (bearing enhanced kinase activity) showed greater nigro-striatal degeneration compared to LRRK2 knock-out, LRRK2 kinase-dead and wild-type mice following subacute MPTP treatment. LRRK2 kinase inhibitors PF-06447475 and MLi-2, tested under preventive or therapeutic treatments, protected against nigral dopamine cell loss in G2019S knock-in mice. MLi-2 also rescued striatal dopaminergic terminal degeneration in both G2019S knock-in and wild-type mice. Immunoblot analysis of LRRK2 Serine935 phosphorylation levels confirmed target engagement of LRRK2 inhibitors. However, MLi-2 abolished phosphoSerine935 levels in the striatum and midbrain of both wild-type and G2019S knock-in mice whereas PF-06447475 partly reduced phosphoSerine935 levels in the midbrain of both genotypes. In vivo and ex vivo uptake of the 18-kDa translocator protein (TSPO) ligand [18F]-VC701 revealed a similar TSPO binding in MPTP-treated wild-type and G2019S knock-in mice which was consistent with an increased GFAP striatal expression as revealed by Real Time PCR. We conclude that LRRK2 G2019S, likely through enhanced kinase activity, confers greater susceptibility to mitochondrial toxin-induced parkinsonism. LRRK2 kinase inhibitors are neuroprotective in this model.
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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) | 0.000 | 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) | 0.002 | 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".