The determination of <i>Plutella xylostella</i> (L.) <scp>GSTs</scp> ( <scp>PxGSTs</scp> ) involved in the detoxification metabolism of Tolfenpyrad
Bibliographic record
Abstract
BACKGROUND: Insect glutathione S-transferases (GSTs) play a crucial role in insecticide detoxification. However, there remains a distinct lack of information regarding the role of GSTs in the detoxification of Tolfenpyrad (TFP) in insects. RESULTS: Real-time quantitative PCR showed significant upregulation of PxGSTs after exposure to TFP for 6 h. An in vitro inhibition assay showed that TFP could inhibit PxGSTδ, PxGSTε and PxGSTσ, and the most pronounced inhibitory effect was on PxGSTσ. Metabolism assays displayed that PxGSTσ was superior to other test PxGSTs in metabolizing TFP. The molecular docking of TFP and PxGSTσ revealed that the H-bond provided by the sidechains of Tyr107 and Tyr162 were key to the detoxification of TFP by PxGSTσ. Further tests using mutant PxGSTσ proteins at the sites of Tyr107 (PxGSTσY107A) and Tyr162 (PxGSTσY162A) corroborated that the individual replacement of Tyr107 and Tyr162 could greatly weaken the binding and metabolic abilities to TFP. CONCLUSION: Metabolic interactions between the Plutella xylostella (L.) GSTs (PxGSTs) and TFP were deciphered. This study illustrates the molecular metabolism mechanism of PxGSTσ towards TFP and provides theoretical underpinnings for the design and optimization of novel TFP-like insecticides. © 2020 Society of Chemical Industry.
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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) | 0.001 | 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".