Import and Export of Misfolded α-Synuclein
Bibliographic record
Abstract
In Parkinson's disease, intracellular α-synuclein (α-syn) inclusions form in neurons and are referred to as Lewy bodies. These aggregates spread through the brain following a specific pattern leading to the hypothesis that neuron-to-neuron transfer is critical for the propagation of Lewy body pathology. Here we review recent studies employing pre-formed fibrils generated from recombinant α-syn to evaluate the uptake, trafficking, and release of α-syn fibrils. We outline methods of internalization as well as cell surface receptors that have been described in the literature as regulating α-syn fibril uptake. Pharmacological and genetic studies indicate endocytosis is the primary method of α-syn internalization. Once α-syn fibrils have crossed the plasma membrane they are typically trafficked through the endo-lysosomal system with autophagy acting as the dominant method of α-syn clearance. Interestingly, both chaperone-mediated autophagy and macroautophagy have been implicated in the degradation of α-syn, although it remains unclear which system is chiefly responsible for the removal of α-syn fibrils. The major hallmark of α-syn spreading is the templating of misfolded properties onto healthy protein resulting in a conformational change; we summarize the evidence indicating misfolded α-syn can seed endogenous α-syn to form new aggregates. Finally, recent studies demonstrate that cells release misfolded and aggregated α-syn and that these processes may involve different chaperones. Nonetheless, the exact mechanism for the release of fibrillar α-syn remains unclear. This review highlights what is known, and what requires further clarification, regarding each step of α-syn transmission.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".