From Mosquito Bites to Sexual Transmission: Evaluating Mouse Models of Zika Virus Infection
Bibliographic record
Abstract
Following the recent outbreak of Zika virus (ZIKV) infections in Latin America, ZIKV has emerged as a global health threat due to its ability to induce neurological disease in both adults and the developing fetus. ZIKV is largely mosquito-borne and is now endemic in many parts of Africa, Asia, and South America. However, several reports have demonstrated persistent ZIKV infection of the male reproductive tract and evidence of male-to-female sexual transmission of ZIKV. Sexual transmission may broaden the reach of ZIKV infections beyond its current geographical limits, presenting a significant threat worldwide. Several mouse models of ZIKV infection have been developed to investigate ZIKV pathogenesis and develop effective vaccines and therapeutics. However, the majority of these models focus on mosquito-borne infection, while few have considered the impact of sexual transmission on immunity and pathogenesis. This review will examine the advantages and disadvantages of current models of mosquito-borne and sexually transmitted ZIKV and provide recommendations for the effective use of ZIKV mouse models.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".