Control of directional change after mechanical stimulation in Drosophila
Bibliographic record
Abstract
BACKGROUND: Proper adjustment of moving direction after external mechanical stimulation is essential for animals to avoid danger (e.g. predators), and thus is vital for survival. This process involves sensory inputs, central processing and motor outputs. Recent studies have made considerable progress in identifying mechanosensitive neurons and mechanosensation receptor proteins. Our understandings of molecular and cellular mechanisms that link mechanosensation with the changes in moving direction, however, remain limited. RESULTS: In this study, we investigate the control of movement adjustment in Drosophila. In response to gentle touch at the anterior segments, Drosophila larvae reorient and select a new direction for forward movement. The extent of change in moving direction is correlated with the intensity of tactile stimuli. Sensation of gentle touch requires chordotonal organs and class IV da neurons. Genetic analysis indicates an important role for the evolutionarily conserved immunoglobulin (Ig) superfamily protein Turtle (Tutl) to regulate touch-initiated directional change. Tutl is required specifically in post-mitotic neurons at larval stage after the completion of embryonic development. Circuit breaking analysis identified a small subset of Tutl-positive neurons that are involved in the adjustment of moving direction. CONCLUSION: We identify Tutl and a small subset of CNS neurons in modulating directional change in response to gentle touch. This study presents an excellent starting point for further dissection of molecular and cellular mechanisms controlling directional adjustment after mechanical stimulation.
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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".