Decoding the RNA viromes in rodent lungs provides new insight into the origin and evolutionary patterns of rodent-borne pathogens in Mainland Southeast Asia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: As the largest group of mammalian species, which are also widely distributed all over the world, rodents are the natural reservoirs for many diverse zoonotic viruses. A comprehensive understanding of the core virome of diverse rodents should therefore assist in efforts to reduce the risk of future emergence or re-emergence of rodent-borne zoonotic pathogens. RESULTS: This study aimed to describe the viral range that could be detected in the lungs of rodents from Mainland Southeast Asia. Lung samples were collected from 3284 rodents and insectivores of the orders Rodentia, Scandentia, and Eulipotyphla in eighteen provinces of Thailand, Lao PDR, and Cambodia throughout 2006-2018. Meta-transcriptomic analysis was used to outline the unique spectral characteristics of the mammalian viruses within these lungs and the ecological and genetic imprints of the novel viruses. Many mammalian- or arthropod-related viruses from distinct evolutionary lineages were reported for the first time in these species, and viruses related to known pathogens were characterized for their genomic and evolutionary characteristics, host species, and locations. CONCLUSIONS: These results expand our understanding of the core viromes of rodents and insectivores from Mainland Southeast Asia and suggest that a high diversity of viruses remains to be found in rodent species of this area. These findings, combined with our previous virome data from China, increase our knowledge of the viral community in wildlife and arthropod vectors in emerging disease hotspots of East and Southeast Asia. Video abstract.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it