The African strain of Zika virus causes more severe <i>in utero</i> infection than Asian strain in a porcine fetal transmission model
Bibliographic record
Abstract
Studies in mice showed that African Zika virus (ZIKV) strains cause more damage in embryos. These studies, however, were limited to the mouse-adapted African MR766 strain or infection at early gestation. Here, we compared infection of Asian and African strains in the fetal pig model at midgestation. Both strains caused fetal infection. ZIKV was detected in placenta, amniotic membrane, amniotic fluid, fetal blood, and brain. The African strain produced more vigorous in utero infection as represented by more efficient virus transmission between siblings, and higher viral loads in fetal organs and membranes. Infection with both strains was associated with reduced fetal brain weight and increased number of placental CD163-positive cells, as well as elevated in utero interferon alpha and cortisol levels. This is the first large animal model study which demonstrated that African strain of ZIKV, with no passage history in experimental animals, can cause persistent infection in fetuses and fetal membranes at midgestation. Our studies also suggest that similar to Asian strains, ZIKV of African lineage might cause silent pathology which is difficult to identify in deceptively healthy fetuses. The findings emphasize the need for further studies to highlight the impact of ZIKV heterogeneity on infection outcomes during pregnancy.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".