Syrian Hamsters ( <i>Mesocricetus auratus</i> ) Oronasally Inoculated With a Nipah Virus Isolate From Bangladesh or Malaysia Develop Similar Respiratory Tract Lesions
Bibliographic record
Abstract
Nipah virus is a paramyxovirus in the genus Henipavirus, which has caused outbreaks in humans in Malaysia, India, Singapore, and Bangladesh. Whereas the human cases in Malaysia were characterized mainly by neurological symptoms and a case fatality rate of ∼40%, cases in Bangladesh also exhibited respiratory disease and had a case fatality rate of ∼70%. Here, we compared the histopathologic changes in the respiratory tract of Syrian hamsters, a well-established small animal disease model for Nipah virus, inoculated oronasally with Nipah virus isolates from human cases in Malaysia and Bangladesh. The Nipah virus isolate from Bangladesh caused slightly more severe rhinitis and bronchointerstitial pneumonia 2 days after inoculation in Syrian hamsters. By day 4, differences in lesion severity could no longer be detected. Immunohistochemistry demonstrated Nipah virus antigen in the nasal cavity and pulmonary lesions; the amount of Nipah virus antigen present correlated with lesion severity. Immunohistochemistry indicated that both Nipah virus isolates exhibited endotheliotropism in small- and medium-caliber arteries and arterioles, but not in veins, in the lung. This correlated with the location of ephrin B2, the main receptor for Nipah virus, in the vasculature. In conclusion, Nipah virus isolates from outbreaks in Malaysia and Bangladesh caused a similar type and severity of respiratory tract lesions in Syrian hamsters, suggesting that the differences in human disease reported in the outbreaks in Malaysia and Bangladesh are unlikely to have been caused by intrinsic differences in these 2 virus isolates.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".