Mixture Interactions in Moth Olfactory Physiology: Examining the Effects of Odorant Mixture, Concentration, Distal Stimulation, and Antennal Nerve Transection on Sensillar Responses
Bibliographic record
Abstract
The insect olfactory system is challenged to decipher valid signals from among an assortment of chemical cues present in the airborne environment. In the moth, Heliothis virescens, males rely upon detection and discrimination of a unique blend of components in the female sex pheromone to locate mates. The effect of variable odor mixtures was used to examine physiological responses from neurons within sensilla on the moth antenna sensitive to female sex pheromone components. Increasing concentrations of heliothine sex pheromone components applied in concert with the cognate stimulus for each neuronal type resulted in mixture suppression of activity, except for one odorant combination where mixture enhancement was apparent. Olfactory receptor neuron (ORN) responses were compared between moths with intact and transected antennal nerves to determine whether specific instances of suppression might be influenced by central mechanisms. Type A sensilla showed little variation in response between transected and intact preparations; however, recordings from type B sensilla with transected antennal nerves exhibited reduced mixture suppression. Testing by parallel stimulation of distal antennal segments while recording and stimulating proximal segments dismissed the possibility of interneuronal or ephaptic effects upon sensillar responses. The results indicate that increasing concentrations of "noncognate" odorants in an odor mixture or antennal nerve transection can produce variation in the intensity and temporal dynamics of physiological recordings from H. virescens ORNs.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".