α-Synuclein Strain Propagation is Independent of Cellular Prion Protein Expression in Transgenic Mice
Bibliographic record
Abstract
Abstract The cellular prion protein, PrP C , has been postulated to function as a receptor for α-synuclein, potentially facilitating cell-to-cell spreading and/or toxicity of α-synuclein aggregates in neurodegenerative disorders such as Parkinson’s disease. To test this hypothesis, we compared the propagation behavior of two different α-synuclein aggregate strains in M83 transgenic mice that either expressed or did not express PrP C . Following intracerebral inoculation with the S or NS strain, the presence of PrP C had minimal influence on α-synuclein strain-specified attributes such as the kinetics of disease progression, the extent of cerebral α-synuclein deposition, selective targeting of specific brain regions and cell types, the morphology of induced α-synuclein deposits, and the structural fingerprints of protease-resistant α-synuclein aggregates. Likewise, there were no appreciable differences in disease manifestation between PrP C -expressing and PrP C -lacking M83 mice following intraperitoneal inoculation of the S strain. Interestingly, intraperitoneal inoculation with the NS strain resulted in two distinct disease phenotypes, indicative of α-synuclein strain evolution, but this was also independent of PrP C expression. Overall, these results suggest that PrP C plays at most a minor role in the propagation, neuroinvasion, and evolution of α-synuclein strains. Thus, other putative receptors or cell-to-cell propagation mechanisms may play a larger role in the spread of α-synuclein aggregates during disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".