Modelling Lyssavirus Infections in Human Stem Cell-Derived Neural Cultures
Bibliographic record
Abstract
Rabies is a zoonotic neurological infection caused by lyssavirus that continues to result in devastating loss of human life. Many aspects of rabies pathogenesis in human neurons are not well understood. Lack of appropriate ex-vivo models for studying rabies infection in human neurons has contributed to this knowledge gap. In this study, we utilize advances in stem cell technology to characterize rabies infection in human stem cell-derived neurons. We show key cellular features of rabies infection in our human neural cultures, including upregulation of inflammatory chemokines, lack of neuronal apoptosis, and axonal transmission of viruses in neuronal networks. In addition, we highlight specific differences in cellular pathogenesis between laboratory-adapted and field strain lyssavirus. This study therefore defines the first stem cell-derived ex-vivo model system to study rabies pathogenesis in human neurons. This new model system demonstrates the potential for enabling an increased understanding of molecular mechanisms in human rabies, which could lead to improved control methods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".