Improved transient silencing of gene expression in the mosquito female <scp> <i>Aedes aegypti</i> </scp>
Bibliographic record
Abstract
Gene silencing using RNA interference (RNAi) has become a widely used genetic technique to study gene function in many organisms. In insects, this technique is often applied through the delivery of dsRNA. In the adult female Aedes aegypti, a main vector of human-infecting arboviruses, efficiency of gene silencing following dsRNA injection varies greatly according to targeted genes. Difficult knockdowns using dsRNA can thus hamper gene function analysis. Here, by analysing silencing of three different genes in female Ae. aegypti (p400, ago2 and E75), we show that gene silencing can indeed be dsRNA sequence dependent but different efficiencies do not correlate with dsRNA length. Our findings suggest that silencing is likely also gene dependent, probably due to gene-specific tissue expression and/or feedback mechanisms. We demonstrate that use of high doses of dsRNA can improve knockdown efficiency, and injection of a transfection reagent along with dsRNA reduces the variability in efficiency between replicates. Finally, we show that gene silencing cannot be achieved using siRNA injection in Ae. aegypti adult females. Overall, this work should help future gene function analyses using RNAi in adult females Ae. aegypti, leading toward a better understanding of physiological and infectious processes.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".