Lewy-MSA hybrid fold drives distinct neuronal α-synuclein pathology
Bibliographic record
Abstract
ABSTRACT The ordered assembly of α-synuclein protein into filaments encoded by SNCA characterizes neurodegenerative diseases called synucleinopathies. Lewy body disease (LBD) shows predominantly neuronal α-synuclein pathology and multiple system atrophy (MSA) predominantly oligodendrocytic α-synuclein pathology affecting subcortical brain structures. Based on cryo-electron microscopy, it was reported that structures of α-synuclein filaments from LBD differ from MSA and juvenile onset synucleinopathy (JOS) caused by a 21-nucleotide duplication in the second exon of one allele of SNCA gene 1-3 . Importantly, a rare subtype of MSA, called atypical MSA 4 shows abundant neuronal argyrophilic α-synuclein inclusions in the limbic system. Current concepts indicate that disease entities are characterized by unique protofilament folds. Here we demonstrate that in addition to the MSA fold, α-synuclein can form a new Lewy-MSA hybrid fold in the same brain region, leading to the atypical histopathological form of MSA. Distinct biochemical characteristics of α-synuclein, as demonstrated by protease-sensitivity digestion assay, seed amplification assays (SAAs) and conformational stability assay (CSA), are also linked to cytopathological differences (e.g. neuronal or oligodendroglial). We expand the current structure-based classification of α−synucleinopathies and propose that cell-specific protein pathologies can be associated with distinct filament folds.
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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".