Age-related pathological impairments in induced neurons derived from patients with idiopathic Parkinson’s disease
Bibliographic record
Abstract
Abstract Understanding the pathophysiology of Parkinson’s disease has been hampered by the lack of models that recapitulate all the critical factors underlying its development. Here, we generated functional induced dopaminergic neurons (iDANs) that were directly reprogrammed from adult human dermal fibroblasts of patients with idiopathic Parkinson’s disease to investigate diseaserelevant pathology. We show that iDANs derived from Parkinson’s disease patients exhibit lower basal chaperone-mediated autophagy as compared to iDANs of healthy donors. Furthermore, stress-induced autophagy resulted in an accumulation of macroautophagic structures in induced neurons (iNs) derived from Parkinson’s disease patients, independently of the specific neuronal subtype but dependent on the age of the donor. Finally, we found that these impairments in patient-derived iNs lead to an accumulation of phosphorylated alpha-synuclein, a hallmark of Parkinson’s disease pathology. Taken together, our results demonstrate that direct neural reprogramming provides a patient-specific model to study aged neuronal features relevant to idiopathic Parkinson’s disease.
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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".