Differential expression of transcripts with potential relevance to chlorantraniliprole response in the Colorado potato beetle, <i>Leptinotarsa decemlineata</i>
Bibliographic record
Abstract
The Colorado potato beetle (Leptinotarsa decemlineata [Say]) is an insect pest that can significantly harm potato plants worldwide. Control of this insect relies heavily on chemical insecticides such as chlorantraniliprole. Nevertheless, the complete molecular signature associated with response to this compound is lacking in L. decemlineata. In this study, amplification and quantification by qRT-PCR (quantitative reverse transcription-polymerase chain reaction) of targets relevant to chlorantraniliprole were undertaken in insects exposed to this chemical. This approach showed modulation of numerous cytochrome P450s, such as CYP350D1 and CYP4Q3, as well as upregulation of microRNAs (miRNAs), including miR-1-3p and miR-305-5p, in chlorantraniliprole-exposed insects. Functional assessment of transcript targets predicted to be regulated by these miRNAs was performed and revealed their likely impact on transcriptional regulation. RNAi-based targeting of CYP350D1 notably provided preliminary evidence of its underlying implication for chlorantraniliprole response in L. decemlineata. Overall, this study strengthens the current knowledge of the molecular changes linked to chlorantraniliprole response in L. decemlineata and provides novel targets with potential relevance to chlorantraniliprole susceptibility in this insect pest of global relevance.
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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 | 0.000 |
| 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".