The New Nematicide Cyclobutrifluram Targets the Mitochondrial Succinate Dehydrogenase Complex in Caenorhabditis elegans
Bibliographic record
Abstract
Today, agriculture around the world is challenged by parasitic nematode infections. Plant-parasitic nematodes (PPNs) can cause significant damage and crop loss and are a threat to food security. For a long time, the management of PPN infection has relied on nematicides that impact not only parasitic nematodes but also other organisms. More recently, new nematicides have been developed that appear to specifically target PPN. Cyclobutrifluram belongs to this new category of nematicides. Using the nematode Caenorhabditis elegans as a model organism, we show here that cyclobutrifluram strongly impacts the survival and fertility rates of the worm by decreasing the number of germ cells. Furthermore, using a genetic approach, we demonstrate that cyclobutrifluram functions by inhibiting the mitochondrial succinate dehydrogenase (SDH) complex. Transcriptomic analysis revealed a strong response to cyclobutrifluram exposure. Among the deregulated genes, we found genes coding for detoxifying proteins, such as cytochrome P450s and UDP-glucuronosyl transferases (UGTs). Overall, our study contributes to the understanding of the molecular mode of action of cyclobutrifluram, to the finding of new approaches against nematicide resistance, and to the discovery of novel nematicides. Furthermore, this study confirms that C. elegans is a suitable model organism to study the mode of action of nematicides.
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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) | 0.000 | 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 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".