α-Synuclein mutation impairs processing of endomembrane compartments and promotes exocytosis and seeding of α-synuclein pathology
Bibliographic record
Abstract
Neuronal loss in Parkinson's disease (PD) is associated with impaired proteostasis and accumulation of α-syn microaggregates in dopaminergic neurons. These microaggregates promote seeding of α-synuclein (α-syn) pathology between synaptically linked neurons. However, the mechanism by which seeding is initiated is not clear. Using human pluripotent stem cell (hPSC) models of PD that allow comparison of SNCA mutant cells with isogenic controls, we find that SNCA mutant neurons accumulate α-syn deposits that cluster to multiple endomembrane compartments, specifically multivesicular bodies (MVBs) and lysosomes. We demonstrate that A53T and E46K α-syn variants bind and sequester LC3B monomers into detergent-insoluble microaggregates on the surface of late endosomes, increasing α-syn excretion via exosomes and promoting seeding of α-syn from SNCA mutant neurons to wild-type (WT) isogenic controls. Finally, we show that constitutive inactivation of LC3B promotes α-syn accumulation and seeding, while LC3B activation inhibits these events, offering mechanistic insight into the spread of synucleinopathy in 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) | 0.000 | 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) | 0.001 | 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".