Characterization of a novel STAT 2 knock-out hamster model of Crimean-Congo hemorrhagic fever virus pathogenesis
Bibliographic record
Abstract
Crimean-Congo hemorrhagic fever virus (CCHFV) is a tick-borne pathogen causing a febrile illness in humans, which can progress to hemorrhagic manifestations, multi-organ failure, and death. Current mouse models of CCHFV infection reliably succumb to virus challenge but vary in their ability to reflect signs of disease similar to humans. In this study, we established a signal transducer and activator of transcription 2 (STAT2) knockout hamster model to expand the repertoire of animal models of CCHFV pathogenesis that can be used for therapeutic development. These hamsters demonstrated a systemic and lethal disease in response to infection. Hallmarks of human disease were observed including petechial rash, blood coagulation dysfunction, and various biochemistry and blood cell count abnormalities. Furthermore, we also demonstrated the utility of this model for anti-CCHFV therapeutic evaluation. The STAT2 knock-out hamster model of CCHFV infection may provide some further insights into clinical disease, viral pathogenesis, and pave the way for testing of potential drug and vaccine candidates.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".