Large-scale visualization of α-synuclein oligomers in Parkinson’s disease brain tissue
Why this work is in the frame
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Bibliographic record
Abstract
Parkinson's disease (PD) is a neurodegenerative condition characterized by the presence of intraneuronal aggregates containing fibrillar ɑ-synuclein known as Lewy bodies. These large end-stage species are formed by smaller soluble protein nanoscale assemblies, often termed oligomers, which are proposed as early drivers of pathogenesis. Until now, this hypothesis has remained controversial, at least in part because it has not been possible to directly visualize nanoscale assemblies in human brain tissue. Here we present Advanced Sensing of Aggregates-Parkinson's Disease, an imaging method to generate large-scale α-synuclein aggregate maps in post-mortem human brain tissue. We combined autofluorescence suppression with single-molecule fluorescence microscopy, which together enable the detection of nanoscale α-synuclein aggregates. To demonstrate the use of this platform, we analysed ~1.2 million nanoscale aggregates from the anterior cingulate cortex in human post-mortem brain samples from patients with PD and healthy controls. Our data reveal a disease-specific shift in a subpopulation of nanoscale assemblies that represent an early feature of the proteinopathy that underlies PD. We anticipate that quantitative information about this distribution provided by Advanced Sensing of Aggregates-Parkinson's Disease will enable mechanistic studies to reveal the pathological processes caused by α-synuclein aggregation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 it