The FGLamide-Allatostatins Influence Foraging Behavior in Drosophila melanogaster
Bibliographic record
Abstract
Allatostatins (ASTs) are multifunctional neuropeptides that generally act in an inhibitory fashion. ASTs were identified as inhibitors of juvenile hormone biosynthesis. Juvenile hormone regulates insect metamorphosis, reproduction, food intake, growth, and development. Drosophila melanogaster RNAi lines of PheGlyLeu-amide-ASTs (FGLa/ASTs) and their cognate receptor, Dar-1, were used to characterize roles these neuropeptides and their respective receptor may play in behavior and physiology. Dar-1 and FGLa/AST RNAi lines showed a significant reduction in larval foraging in the presence of food. The larval foraging defect is not observed in the absence of food. These RNAi lines have decreased for transcript levels which encodes cGMP- dependent protein kinase. A reduction in the for transcript is known to be associated with a naturally occurring allelic variation that creates a sitter phenotype in contrast to the rover phenotype which is caused by a for allele associated with increased for activity. The sitting phenotype of FGLa/AST and Dar-1 RNAi lines is similar to the phenotype of a deletion mutant of an AST/galanin-like receptor (NPR-9) in Caenorhabditis elegans. Associated with the foraging defect in C. elegans npr-9 mutants is accumulation of intestinal lipid. Lipid accumulation was not a phenotype associated with the FGLa/AST and Dar-1 RNAi lines.
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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".