α-Synuclein driven cell susceptibility in Parkinson’s disease
Bibliographic record
Abstract
Abstract Early cellular events in Parkinson’s disease (PD) remain elusive. While aggregation of α-synuclein (αSyn) into Lewy bodies marks advanced pathology, smaller αSyn oligomers have been implicated in prodromal stages. Here we map αSyn oligomers at single-particle resolution in post-mortem brain tissue from Braak stage 3/4 PD cases and matched controls. Quantitative imaging of 9,882 neurons across four regions captured over 112 million αSyn oligomers. Mean intracellular α-Syn burden was unchanged between groups, but PD samples contained a higher fraction of neurons whose oligomer load exceeded a specific aggregation threshold. We term these aggregation-susceptible cells (ASCs). ASC enrichment in vulnerable regions supports a population-level model in which early pathology arises from a stochastic shift in cellular composition rather than altered αSyn aggregation kinetics. This human-tissue, large-scale dataset provides a quantitative framework for detecting ASCs and for testing population-level interventions in PD and related proteinopathies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".