Comparative analysis of Parkinson's disease–associated genes in mice reveals altered survival and bioenergetics of Parkin-deficient dopamine neurons
Bibliographic record
Abstract
Many mutations in genes encoding proteins such as Parkin, PTEN-induced putative kinase 1 (PINK1), protein deglycase DJ-1 (DJ-1 or PARK7), leucine-rich repeat kinase 2 (LRRK2), and α-synuclein have been linked to familial forms of Parkinson's disease (PD). The consequences of these mutations, such as altered mitochondrial function and pathological protein aggregation, are starting to be better understood. However, little is known about the mechanisms explaining why alterations in such diverse cellular processes lead to the selective loss of dopamine (DA) neurons in the substantia nigra (SNc) in the brain of individuals with PD. Recent work has shown that one of the reasons for the high vulnerability of SNc DA neurons is their high basal rate of mitochondrial oxidative phosphorylation (OXPHOS), resulting from their highly complex axonal arborization. Here, we examined whether axonal growth and basal mitochondrial function are altered in SNc DA neurons from Parkin-, Pink1-, or DJ-1-KO mice. We provide evidence for increased basal OXPHOS in Parkin-KO DA neurons and for reduced survival of DA neurons that have a complex axonal arbor. The surviving smaller neurons exhibited reduced vulnerability to the DA neurotoxin and mitochondrial complex I inhibitor MPP+, and this reduction was associated with reduced expression of the DA transporter. Finally, we found that glial cells play a role in the reduced resilience of DA neurons in these mice and that WT Parkin overexpression rescues this phenotype. Our results provide critical insights into the complex relationship between mitochondrial function, axonal growth, and genetic risk factors for PD.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".