Penetration-enhancement underlies synergy of plant essential oil terpenoids as insecticides in the cabbage looper, Trichoplusia ni
Bibliographic record
Abstract
Many plant essential oils and their terpenoid constituents possess bioactivities including insecticidal activity, and they sometimes act synergistically when mixed. Although several hypotheses for this have been proposed, the underlying mechanism has not been fully elucidated thus far. In the present study, we report that in larvae of the cabbage looper, Trichoplusia ni, most synergistic or antagonistic insecticidal activities among mixtures of plant essential oil constituents are pharmacokinetic effects, owing to changes in solubility as well as spreadability on a wax layer. Among the major constituents of rosemary (Rosmarinus officinalis) oil, in vitro analysis revealed up to a 19-fold increase in penetration of camphor in a binary mixture with 1,8-cineole through the larval integument, suggesting increased penetration as the major mechanism for synergy. A total of 138 synergistic or antagonistic interactions among 39 compounds were identified in binary mixtures via topical application, and these were highly correlated to changes in surface tension as measured by contact angle of the mixtures on a beeswax layer. Among compounds tested, trans-anethole alone showed evidence of internal synergy, whereas most of remaining synergistic or antagonistic combinations among the three most active compounds were identified as penetration-related interactions, confirmed via a divided-application bioassay.
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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".