Evaluating the potential of <scp>RNA</scp> interference for control of striped cucumber beetle, <scp> <i>Acalymma vittatum</i> </scp> (Fabricius) (Coleoptera: Chrysomelidae)
Bibliographic record
Abstract
BACKGROUND: The striped cucumber beetle (SCB) is a serious pest of cucurbit crops, causing damage both by feeding on plants and by vectoring plant diseases. Cultural, biological and chemical methods are currently used for its management, however, RNA interference (RNAi) as a potential control strategy, has not yet been evaluated. RESULTS: Injecting dsRNA into the hemocoel of adult SCB resulted in significant gene knockdown and mortality for all seven genes tested (v-ATPaseA, rpt3, rop, α-snap, srp54k, β-actin and α-tubulin). However, oral delivery of the three dsRNAs found to be most lethal using injections, targeting β-actin, α-snap and rpt3, led to less efficient gene knockdown and mortality than injections. In silico analysis of the SCB transcriptome revealed the presence of five dsRNA-degrading nucleases, of which dsRNase5 had the highest expression in the gut. However, double knockdown of dsRNase5 and the rpt3 gene did not improve oral RNAi. Comparing dsRNA stability in digestive fluid and hemolymph of SCB and Colorado potato beetle (CPB) revealed differences in dsRNA-degrading nuclease activity. Furthermore, oral RNAi of the β-actin gene in CPB adults resulted in 100% mortality, whereas mortality was only 33.3% in SCB. CONCLUSION: Although SCB has a robust RNAi response to injected dsRNA, oral RNAi works less efficiently. Knockdown of the most highly expressed dsRNase gene in the SCB gut did not enhance oral RNAi. This suggests nucleases may not be the main reason for the reduced oral RNAi efficiency in SCB and other factors are likely to be involved. © 2025 His Majesty the King in Right of Canada. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. Reproduced with the permission of the Minister of Agriculture and Agri-Food.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".