In Vitro and In Vivo Evidence towards Fibronectin’s Protective Effects against Prion Infection
Bibliographic record
Abstract
A distinctive signature of the prion diseases is the accumulation of the pathogenic isoform of the prion protein, PrPSc, in the central nervous system of prion-affected humans and animals. PrPSc is also found in peripheral tissues, raising concerns about the potential transmission of pathogenic prions through human food supplies and posing a significant risk to public health. Although muscle tissues are considered to contain levels of low prion infectivity, it has been shown that myotubes in culture efficiently propagate PrPSc. Given the high consumption of muscle tissue, it is important to understand what factors could influence the establishment of a prion infection in muscle tissue. Here we used in vitro myotube cultures, differentiated from the C2C12 myoblast cell line (dC2C12), to identify factors affecting prion replication. A range of experimental conditions revealed that PrPSc is tightly associated with proteins found in the systemic extracellular matrix, mostly fibronectin (FN). The interaction of PrPSc with FN decreased prion infectivity, as determined by standard scrapie cell assay. Interestingly, the prion-resistant reserve cells in dC2C12 cultures displayed a FN-rich extracellular matrix while the prion-susceptible myotubes expressed FN at a low level. In agreement with the in vitro results, immunohistopathological analyses of tissues from sheep infected with natural scrapie demonstrated a prion susceptibility phenotype linked to an extracellular matrix with undetectable levels of FN. Conversely, PrPSc deposits were not observed in tissues expressing FN. These data indicate that extracellular FN may act as a natural barrier against prion replication and that the extracellular matrix composition may be a crucial feature determining prion tropism in different tissues.
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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".