A Syrian Golden Hamster Model Recapitulating Ebola Hemorrhagic Fever
Bibliographic record
Abstract
Ebola hemorrhagic fever (EHF) is a severe viral infection for which no effective treatment or vaccine is currently available. While the nonhuman primate (NHP) model is used for final evaluation of experimental vaccines and therapeutic efficacy, rodent models have been widely used in ebolavirus research because of their convenience. However, the validity of rodent models has been questioned given their low predictive value for efficacy testing of vaccines and therapeutics, a result of the inconsistent manifestation of coagulopathy seen in EHF. Here, we describe a lethal Syrian hamster model of EHF using mouse-adapted Ebola virus. Infected hamsters displayed most clinical hallmarks of EHF, including severe coagulopathy and uncontrolled host immune responses. Thus, the hamster seems to be superior to the existing rodent models, offering a better tool for understanding the critical processes in pathogenesis and providing a new model for evaluating prophylactic and postexposure interventions prior to testing in NHPs.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".