Octopamine receptor gene influences social grouping in the masked birch caterpillar
Bibliographic record
Abstract
OBJECTIVE: Group-living plays a key role in the success of many insects, but the mechanisms underlying group formation and maintenance are poorly understood. Here we use the masked birch caterpillar, Drepana arcuata, to explore genetic influences on social grouping. These larvae predictably transition from living in social groups to living solitarily during the 3rd instar of development. Our previous study showed a notable shift in the D. arcuata transcriptome that correlates with the transition from grouping to solitary behavior. We noted that one differentially regulated gene, octopamine receptor gene (DaOAR), is a prominent 'social' gene in other insect species, prompting us to test the hypothesis that DaOAR influences grouping behavior in D. arcuata. This was done using RNA interference (RNAi) methods by feeding second instar larvae synthetic dsRNAs. RESULTS: RT-qPCR analysis confirmed a significant reduction in DaOAR transcript abundance in dsRNA-fed larvae compared to controls. Behavioral trials showed that caterpillars with reduced transcript abundance of DaOAR remained solitary throughout the observation period compared to controls. These results provide evidence that regulation of the octopamine receptor gene influences social grouping in D. arcuata, and that specifically, a decrease in octopamine receptor expression triggers the larval transition from social to solitary.
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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".