The Midgut Microbiota of Colombian Aedes aegypti Populations with Different Levels of Resistance to the Insecticide Lambda-cyhalothrin
Bibliographic record
Abstract
Insecticide resistance in Aedes aegypti populations is a problem that hinders vector control and dengue prevention programs. In this study, we determined the susceptibility of Ae. aegypti populations from six Colombian regions to the pyrethroid lambda-cyhalothrin and evaluated the presence of the V1016I mutation in the sodium channel gene, which has been broadly involved in the resistance to this insecticide. The diversity of the gut microbiota of these mosquito populations was also analyzed. Only mosquitoes from Bello were susceptible to lambda-cyhalothrin and presented a lower allelic frequency of the V1016I mutation. Remarkably, there was not an important change in allelic frequencies among populations with different resistance ratios, indicating that other factors or mechanisms contributed to the resistant phenotype. Treatment of mosquitoes with antibiotics led us to hypothesize that the intestinal microbiota could contribute to the resistance to lambda-cyhalothrin. Beta diversity analysis showed significant differences in the species of bacteria present between susceptible and resistant populations. We identified 14 OTUs of bacteria that were unique in resistant mosquitoes. We propose that kdr mutations are important in the development of resistance to lambda-cyhalothrin at low insecticide concentrations but insect symbionts could play an essential role in the metabolization of pyrethroid insecticides at higher concentrations, contributing to the resistant phenotype in Ae. aegypti.
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".