Callitrichine gammaherpesvirus 3 and Human alphaherpesvirus 1 in New World Primate negative for yellow fever virus in Rio de Janeiro, Brazil
Bibliographic record
Abstract
BACKGROUND: Herpesvirus transmission between humans and non-human primate (NHP) can occur through contact scratches with lesions, infected saliva, and mainly through contaminated food. Therefore, cross-infection can lead to severe illness or even death for both the animal and human. In 2017, during the yellow fever (YF) outbreak in Brazil, species of the New World Primates (NWP) from Rio de Janeiro state, tested negative for yellow fever virus (YFV) detection. OBJECTIVES: To evaluate herpesvirus in the population NWP in Rio de Janeiro. METHODS: To investigate, liver samples of 283 NWP, from several regions of the state of Rio de Janeiro, were tested for the herpesvirus family using a Pan-polymerase chain reaction (Pan-PCR) and sequencing. FINDINGS: 34.6% (98/283) tested positive for at least one herpesvirus; 29.3% (83/283) tested positive to Human alphaherpesvirus 1 (HSV-1), this virus from humans can be lethal to New World monkey; 13% (37/283) were detected Callitrichine gammaherpesvirus 3 (CalHV-3), responsible for lymphoproliferative disease that can be fatal in NWP. In addition, CalHV-3 / HSV-1 co-infection was in 11.6% (33/283) of the samples. MAIN CONCLUSIONS: Pan-herpesvirus was useful to identify species-specific herpesviruses and virus from human that can infect animals. Furthermore, during an outbreak of YF other infections should be monitored.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".