Calpain-cleavage of alpha-synuclein: connecting proteolytic processing to disease-linked aggregation
Bibliographic record
Abstract
Parkinson's disease (PD) and dementia with Lewy bodies (DLB) are both characterized pathologically by the presence of neuronal inclusions termed Lewy bodies (LBs). A common feature found in LBs are aggregates of alpha-synuclein (alpha-Syn), and although it is now recognized that alpha-Syn is the major building block for these toxic filaments, the mechanism of how this occurs remains unknown. In the present study, we demonstrate that proteolytic processing of alpha-Syn by the protease calpain I leads to the formation of aggregated high-molecular weight species and adoption of a beta-sheet structure. To determine whether calpain-cleavage of alpha-Syn occurs in PD and DLB, we designed site-directed calpain-cleavage antibodies to alpha-Syn and tested their utility in several animal model systems. Detection of calpain-cleaved alpha-Syn was evident in mouse models of cerebral ischemia and PD and in a Drosophila model of PD. In the human PD and DLB brain, calpain-cleaved alpha-Syn antibodies immunolabeled LBs and neurites in the substantia nigra. Moreover, calpain-cleaved alpha-Syn fragments identified within LBs colocalized with activated calpain in neurons of the PD and DLB brains. These findings suggest that calpain I may participate in the disease-linked aggregation of alpha-Syn in various alpha-synucleinopathies
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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) | 0.000 | 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 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".