Force-Controlled Mechanical Stimulation and Single-Neuron Fluorescence Imaging of <i>Drosophila</i> Larvae
Bibliographic record
Abstract
Studying the neural response of a Drosophila larva to touch stimulation could decipher neural basis of the creature's danger-escaping behaviors. This letter reports force-controlled robotic mechanical stimulation and single-neuron fluorescence imaging of Drosophila larvae. A force control architecture based on a model compensation-prediction scheme and a switched fuzzy-PID controller was used for regulating the touch force applied to a larva at the micronewton level. The developed force control system demonstrates a settling time of 0.15 s, zero overshoot and a resolution of <; 50 μN. Established based on a high-resolution inverted fluorescence microscope, our robotic system is capable of simultaneously applying a controlled touch force to a larva and quantifying the fluorescence signal transmission inside a single neuron responsive to body touch stimulation. Using this system, we examined, for the first time, the quantitative relationship between the applied force level (range: 0.25-2 mN) and the change in transmission signal of the class III ddaA neuron. The touch force threshold at which the neuron starts to get activated was determined to be in the range of 0.25-0.5 mN. This work may contribute to new studies on sensory mechanotransduction in Drosophila larvae.
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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) | 0.000 | 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".