Isolation and Identification of Mosquito (Aedes aegypti) Biting Deterrent Fatty Acids from Male Inflorescences of Breadfruit (Artocarpus altilis (Parkinson) Fosberg)
Bibliographic record
Abstract
Dried male inflorescences of breadfruit ( Artocarpus altilis , Moraceae) are burned in communities throughout Oceania to repel flying insects, including mosquitoes. This study was conducted to identify chemicals responsible for mosquito deterrence. Various crude extracts were evaluated, and the most active, the hydrodistillate, was used for bioassay-guided fractionation. The hydrodistillate and all fractions displayed significant deterrent activity. Exploratory GC-MS analysis revealed more than 100 distinctive peaks, and more than 30 compounds were putatively identified, including a mixture of terpenes, aldehydes, fatty acids, and aromatics. A systematic bioassay-directed study using adult Aedes aegypti females identified capric, undecanoic, and lauric acid as primary deterrent constituents. A synthetic mixture of fatty acids present in the most active fraction and individual fatty acids were all significantly more active than N,N-diethyl-m-toluamide (DEET). These results provide support for this traditional practice and indicate the potential of male breadfruit flowers and fatty acids as mosquito repellents.
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) | 0.000 | 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".