Ca2+ is a key factor in α-synuclein-induced neurotoxicity
Bibliographic record
Abstract
Aggregation of α-synuclein leads to the formation of oligomeric intermediates that can interact with membranes to form pores. However, it is unknown how this leads to cell toxicity in Parkinson's disease. We investigated the species-specific effects of α-synuclein on Ca(2+) signalling in primary neurons and astrocytes using live neuronal imaging and electrophysiology on artificial membranes. We demonstrate that α-synuclein induces an increase in basal intracellular Ca(2+) in its unfolded monomeric state as well as in its oligomeric state. Electrophysiology of artificial membranes demonstrated that α-synuclein monomers induce irregular ionic currents, whereas α-synuclein oligomers induce rare discrete channel formation events. Despite the ability of monomeric α-synuclein to affect Ca(2+) signalling, it is only the oligomeric form of α-synuclein that induces cell death. Oligomer-induced cell death was abolished by the exclusion of extracellular Ca(2+), which prevented the α-synuclein-induced Ca(2+) dysregulation. The findings of this study confirm that α-synuclein interacts with membranes to affect Ca(2+) signalling in a structure-specific manner and the oligomeric β-sheet-rich α-synuclein species ultimately leads to Ca(2+) dysregulation and Ca(2+)-dependent cell death.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".