Selective vulnerability in α-synucleinopathies
Bibliographic record
Abstract
Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy are neurodegenerative disorders resulting in progressive motor/cognitive deficits among other symptoms. They are characterised by stereotypical brain cell loss accompanied by the formation of proteinaceous aggregations of the protein α-synuclein (α-syn), being, therefore, termed α-synucleinopathies. Although the presence of α-syn inclusions is a common hallmark of these disorders, the exact nature of the deposited protein is specific to each disease. Different neuroanatomical regions and cellular populations manifest a differential vulnerability to the appearance of protein deposits, cell dysfunction, and cell death, leading to phenotypic diversity. The present review describes the multiple factors that contribute to the selective vulnerability in α-synucleinopathies. We explore the intrinsic cellular properties in the affected regions, including the physiological and pathophysiological roles of endogenous α-syn, the metabolic and genetic build-up of the cells and their connectivity. These factors converge with the variability of the α-syn conformational strains and their spreading capacity to dictate the phenotypic diversity and regional vulnerability of each disease. Finally, we describe the exogenous and environmental factors that potentially contribute by igniting and modulating the differential pathology in α-synucleinopathies. In conclusion, we think that it is the confluence of this disruption of the cellular metabolic state and α-syn structural equilibrium through the anatomical connectivity which appears to initiate cascades of pathological processes triggered by genetic, environmental, or stochastic events that result in the "death by a thousand cuts" profile of α-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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".