Effects of the essential oil constituent thymol and other neuroactive chemicals on flight motor activity and wing beat frequency in the blowfly <i>Phaenicia sericata</i>
Bibliographic record
Abstract
BACKGROUND: The effects were evaluated of the plant terpenoid thymol and eight other neuroactive compounds on flight muscle impulses (FMIs) and wing beat frequency (WBF) of tethered blowflies (Phaenicia sericata Meig.). RESULTS: The electrical activity of the dorsolongitudinal flight muscles was closely linked to the WBF of control insects. Topically applied thymol inhibited WBF within 15-30 min and reduced FMI frequency. Octopamine and chlordimeform caused a similar, early-onset bursting pattern that decreased in amplitude with time. Desmethylchlordimeform blocked wing beating within 60 min and generated a profile of continuous but lower-frequency FMIs. Fipronil suppressed wing beating and induced a pattern of continuous, variable-frequency spiking that diminished gradually over 6 h. Cypermethrin- and rotenone-treated flies had initial strong FMIs that declined with time. In flies injected with GABA, the FMIs were generally unidirectional and frequency was reduced, as was seen with thymol. CONCLUSIONS: Thymol readily penetrates the cuticle and interferes with flight muscle and central nervous function in the blowfly. The similarity of the action of thymol and GABA suggests that this terpenoid acts centrally in blowflies by mimicking or facilitating GABA action.
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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) | 0.001 | 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".