Liaisons dangereuses: cross-border gene flow and dispersal of insecticide resistance-associated genes in the mosquito Aedes aegypti from Brazil and French Guiana
Bibliographic record
Abstract
BACKGROUND: In recent years, South America has suffered the burden of continuous high impact outbreaks of dengue, chikungunya and Zika. Aedes aegypti is the main mosquito vector of these arboviruses and its control is the only solution to reduce transmission. OBJECTIVES: In order to improve vector control it is essential to study mosquito population genetics in order to better estimate the population structures and the geneflow among them. METHODS: We have analysed microsatellites and knockdown resistance (kdr) mutations from a trans-border region in Amazonia between the state of Amapá (Brazil) and French Guiana (overseas territory of France), to provide further knowledge on these issues. These two countries have followed distinct vector control policies since last century. For population genetic analyses we evaluated variability in 13 well-established microsatellites loci in Ae. aegypti from French Guiana (Saint Georges and Cayenne) and Brazil (Oiapoque and Macapá). The occurrence and frequency of kdr mutations in these same populations were accessed by TaqMan genotype assays for the sites 1016 (Val/Ile) and 1534 (Phe/Cys). FINDINGS: We have detected high levels of gene flow between the closest cross-border samples of Saint-Georges and Oiapoque. These results suggest one common origin of re-colonisation for the populations of French Guiana and Oiapoque in Brazil, and a different source for Macapá, more similar to the other northern Brazilian populations. Genotyping of the kdr mutations revealed distinct patterns for Cayenne and Macapá associated with their different insecticide use history, and an admixture zone between these two patterns in Saint Georges and Oiapoque, in accordance with population genetic results. MAIN CONCLUSIONS: The present study highlights the need for regional-local vector surveillance and transnational collaboration between neighboring countries to assess the impact of implemented vector control strategies, promote timely actions and develop preparedness plans.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".