Enhanced cuticular penetration as the mechanism for synergy of insecticidal constituents of rosemary essential oil in Trichoplusia ni
Bibliographic record
Abstract
Synergistic interactions between constituents of essential oils have been reported for several areas of research. In the present study, mechanisms that could explain the synergistic action of the two major insecticidal constituents of rosemary oil, 1,8-cineole and camphor against the cabbage looper, Trichoplusia ni were investigated. 1,8-Cineole was more toxic than camphor when applied topically to larvae, and when coadministered in their ratio naturally occurring in rosemary oil, the binary mixture was synergistic. However, when injected directly into larvae, camphor was more toxic than 1,8-cineole. GC-MS analyses showed that penetration of topically-applied camphor was significantly enhanced when it was mixed with 1,8-cineole in the natural ratio. A bioassay combining injection and topical application methods confirmed the increased penetration of both compounds when mixed, showing the same bioactivity as seen for higher amounts applied individually. Lowered surface tension as well as increased solubility of camphor by 1,8-cineole, along with the interaction between 1,8-cineole and the lipid layer of the insect's cuticle may explain the enhanced penetration of camphor. Because of the similarities in biological function of animal and microbial membranes, our finding has potential for application in other fields of study.
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 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".