Actinomyces viscosus promotes neuroprotection in C. elegans models of Parkinson’s disease
Bibliographic record
Abstract
Parkinson's Disease is characterized by selective degeneration of dopaminergic neurons, primarily in the substantia nigra pars compacta, as well as accumulation of alpha-synuclein enriched protein aggregates within neurons. The pathogenesis of PD is still not completely understood, and no treatments exist that alter disease progression. Obvious genetic causes are detected in only a small number of PD patients (5-10 %), suggesting that environmental factors play a significant role the development of PD. Correlative studies suggest that the microbiota could be an important environmental modifier of neurodegeneration. We identified a microbiotal isolate, Actinomyces viscosus, that reduced neurodegeneration in C. elegans expressing a pathological mutant form (G2019S) of leucine-rich repeat kinase 2 (LRRK2) in dopaminergic neurons. A. viscosus also suppressed autophagic dysfunction in these animals and reduced alpha-synuclein aggregation in a synucleinopathy model. Global gene expression analysis revealed increased expression of aspartic cathepsins in response to A. viscosus. Consistent with the involvement of these proteins in neuroprotection, we found that reducing aspartic cathepsin function increased neurodegeneration in the LRRK2 transgenic model. Our findings contribute to the current understanding of how the gut microbiota may influence PD, elucidating one potential mechanism of microbiota-mediated neuroprotection.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".