In Vitro and In Vivo Characterization of Recombinant Ebola Viruses Expressing Enhanced Green Fluorescent Protein
Bibliographic record
Abstract
To facilitate an understanding of the molecular aspects of the pathogenesis of Zaire ebolavirus (ZEBOV) infection, we generated 2 different recombinant viruses expressing enhanced green fluorescent protein (eGFP) from additional transcription units inserted at different positions in the virus genome. These viruses showed in vitro phenotypes similar to that of wild-type ZEBOV (wt-ZEBOV) and were stable over multiple passages. Infection with one of the viruses expressing eGFP produced only mild disease in rhesus macaques, demonstrating a marked attenuation in this animal model. However, in mice lacking signal transducer and activator of transcription 1, both viruses expressing eGFP caused lethal cases of disease that were moderately attenuated, compared with that caused by wt-ZEBOV. In mice, viral replication could be easily tracked by the detection of eGFP-positive cells in tissues, by use of flow cytometry. These findings demonstrate that the incorporation of a foreign gene will attenuate ZEBOV in vivo but that these viruses still have potential for in vitro and in vivo research applications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".