Taï Forest Virus Does Not Cause Lethal Disease in Ferrets
Bibliographic record
Abstract
Filoviruses are zoonotic, negative-sense RNA viruses, most of which are capable of causing severe disease in humans and nonhuman primates, often with high case fatality rates. Among these viruses, those belonging to the Ebolavirus genus—particularly Ebola virus, Sudan virus, and Bundibugyo virus—represent some of the most pathogenic to humans. Taï Forest virus (TAFV) is thought to be among the least pathogenic ebolaviruses; however, only a single non-fatal case has been documented in humans, in 1994. With the recent success of the ferret as a lethal model for a number of ebolaviruses, we set out to evaluate its suitability as a model for TAFV. Our results demonstrate that, unlike other ebolaviruses, TAFV infection in ferrets does not result in lethal disease. None of the intramuscularly inoculated animals demonstrated any overt signs of disease, whereas the intranasally inoculated animals exhibited mild to moderate weight loss during the early stage of infection but recovered quickly. Low levels of viral RNA were detected in the blood and tissues of several animals, particularly the intranasally inoculated animals, and all animals mounted a humoral immune response, with high titers of GP-specific IgG detectable as early as 14 days post-infection. These data provide additional insight into the pathogenesis of TAFV.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".