Zika structural genes determine the virulence of African and Asian lineages
Bibliographic record
Abstract
The Asian lineage of Zika virus (ZIKV) is responsible for the recent epidemics in the Americas and severe disease, whereas the African lineage of ZIKV has not been reported to cause epidemics or severe disease. We constructed a cDNA infectious clone (IC) of an African ZIKV strain, which, together with our previously developed Asian ZIKV strain IC, allowed us to engineer chimeric viruses by swapping the structural and non-structural genes between the two lineages. Recombinant parental and chimeric viruses were analyzed in A129 and newborn CD1 mouse models. In the A129 mice, the African strain developed higher viremia, organ viral loading, and mortality rate. In CD1 mice, the African strain exhibited a higher neurovirulence than the Asian strain. A chimeric virus containing the structural genes from the African strain is more virulent than the Asian strain, whereas a chimeric virus containing the non-structural genes from the African strain exhibited a virulence comparable to the Asian strain. These results suggest that (i) African strain is more virulent than Asian strain and (ii) viral structural genes primarily determine the virulence difference between the two lineages in mouse models. Other factors may contribute to the discrepancy between the mouse and epidemic results.
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 | 0.000 |
| 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) | 0.001 | 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".