Leveraging RNA Interference to Impact Insecticide Resistance in the Colorado Potato Beetle, Leptinotarsa decemlineata
Bibliographic record
Abstract
The Colorado potato beetle, Leptinotarsa decemlineata Say, is a potato pest that can cause important economic losses to the potato industry worldwide. Diverse strategies have been deployed to target this insect such as biological control, crop rotation, and a variety of insecticides. Regarding the latter, this pest has demonstrated impressive abilities to develop resistance against the compounds used to regulate its spread. Substantial work has been conducted to better characterize the molecular signatures underlying this resistance, with the overarching objective of leveraging this information for the development of novel approaches, including RNAi-based techniques, to limit the damage associated with this insect. This review first describes the various strategies utilized to control L. decemlineata and highlights different examples of reported cases of resistances against insecticides for this insect. The molecular leads identified as potential players modulating insecticide resistance as well as the growing interest towards the use of RNAi aimed at these leads as part of novel means to control the impact of L. decemlineata are described subsequently. Finally, select advantages and limitations of RNAi are addressed to better assess the potential of this technology in the broader context of insecticide resistance for pest management.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".