Activity of cGMP-Dependent Protein Kinase (PKG) Affects Sucrose Responsiveness and Habituation in<i>Drosophila melanogaster</i>
Bibliographic record
Abstract
The cGMP-dependent protein kinase (PKG) has many cellular functions in vertebrates and insects that affect complex behaviors such as locomotion and foraging. The foraging (for) gene encodes a PKG in Drosophila melanogaster. Here, we demonstrate a function for the for gene in sensory responsiveness and nonassociative learning. Larvae of the natural variant sitter (for(s)) show less locomotor activity during feeding and have a lower PKG activity than rover (for(R)) larvae. We used rover and sitter adult flies to test whether PKG activity affects (1) responsiveness to sucrose stimuli applied to the front tarsi, and (2) habituation of proboscis extension after repeated sucrose stimulation. To determine whether the differences observed resulted from variation in the for gene, we also tested for(s2), a sitter mutant produced on a rover genetic background. We found that rovers (for(R)) were more responsive to sucrose than sitters (for(s) and for(s2)) at 1-, 2-, and 3-wk old. This was true for both sexes. Differences in sucrose responsiveness between rovers and sitters were greater after 2 h of food deprivation than after 24 h. Of flies with similar sucrose responsiveness, for(R) rovers showed less habituation and generalization of habituation than for(s) and for(s2) sitters. These results show that the PKG encoded by for independently affects sensory responsiveness and habituation in Drosophila melanogaster.
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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 | 0.001 |
| 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".