Golgi Fragmentation Occurs in the Cells with Prefibrillar α-Synuclein Aggregates and Precedes the Formation of Fibrillar Inclusion
Bibliographic record
Abstract
Amyloid-like fibrillar aggregates of intracellular proteins are common pathological features of human neurodegenerative diseases. However, the nature of pathogenic aggregates and the biological consequences of their formation remain elusive. Here, we describe (i) a model cellular system in which prefibrillar alpha-synuclein aggregates and fibrillar inclusions are naturally formed in the cytoplasm with distinctive kinetics and (ii) a tight correlation between the presence of prefibrillar aggregates and the Golgi fragmentation. Consistent with the structural abnormality of Golgi apparatus, trafficking and maturation of dopamine transporter through the biosynthetic pathway were impaired in the presence of alpha-synuclein aggregates. Reduction in cell viability was also observed in the prefibrillar aggregate-forming condition and before the inclusion formation. The fibrillar inclusions, on the other hand, showed no correlation with Golgi fragmentation and were preceded by these events. Furthermore, at the early stage of inclusion formation, active lysosomes and mitochondria were enriched in the juxtanuclear area and co-aggregate into a compact inclusion body, suggesting that the fibrillar inclusions might be the consequence of an attempt of the cell to remove abnormal protein aggregates and damaged organelles. These results support the hypothesis that prefibrillar alpha-synuclein aggregates are the pathogenic species and suggest that Golgi fragmentation and subsequent trafficking impairment are the specific consequence of alpha-synuclein aggregation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".