RVFV Infection in Goats by Different Routes of Inoculation
Bibliographic record
Abstract
Rift Valley Fever virus (RVFV) is a zoonotic arbovirus of the Phenuiviridae family. Infection causes abortions in pregnant animals, high mortality in neonate animals and mild to severe symptoms in both people and animals. There is currently an ongoing effort to produce safe and efficacious veterinary vaccines against RVFV in livestock to protect against both primary infection in animals and zoonotic infections in people. To test the efficacy of these vaccines it is essential to have a reliable challenge model in relevant target species, including ruminants. We evaluated two goats breeds (Nubian and LaMancha), three routes of inoculation (intranasal, mosquito-primed subcutaneous and subcutaneous) using an infectious dose of 107 pfu/ml, a virus strain from the 2006-07 Kenyan/Sudan outbreak and compared the effect of using virus stocks produced in either mammalian or mosquito cells. Our results demonstrated that Nubian goats achieved the highest levels and longer duration of viremia. In the Nubian goats, all three routes of inoculation were equally efficient at producing clinical signs, consistent viremia (peak viremia: 1.2x103 - 1.0x105 pfu/ml serum), nasal and oral shedding of viral RNA (1.5x101 – 8x106 genome copies/swab), a systemic infection of tissues, and robust antibody responses. The Nubian goat breed and a needle-free intranasal inoculation technique could both be utilized in future vaccine and challenge studies.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".