Parallel-Channel Electrotaxis and Neuron Screening of Caenorhabditis elegans
Bibliographic record
Abstract
In this paper, we report a novel microfluidic method to conduct a Caenorhabditis elegans electrotaxis movement assay and neuronal imaging on up to 16 worms in parallel. C. elegans is a model organism for neurodegenerative disease and movement disorders such as Parkinson’s disease (PD), and for screening chemicals that alleviate protein aggregation, neuronal death, and movement impairment in PD. Electrotaxis of C. elegans in microfluidic channels has led to the development of neurobehavioral screening platforms, but enhancing the throughput of the electrotactic behavioral assay has remained a challenge. Our device consisted of a hierarchy of tree-like channels for worm loading into 16 parallel electrotaxis screening channels with equivalent electric fields. Tapered channels at the ends of electrotaxis channels were used for worm immobilization and fluorescent imaging of neurons. Parallel electrotaxis of worms was first validated against established single-worm electrotaxis phenotypes. Then, mutant screening was demonstrated using the NL5901 strain, carrying human α-synuclein in the muscle cells, by showing the associated electrotaxis defects in the average speed, body bend frequency (BBF), and electrotaxis time index (ETI). Moreover, chemical screening of a PD worm model was shown by exposing the BZ555 strain, expressing green fluorescence protein (GFP) in the dopaminergic neurons (DNs), to 6-hydroxydopamine neurotoxin. The neurotoxin-treated worms exhibited a reduction in electrotaxis swimming speed, BBF, ETI, and DNs fluorescence intensity. We envision our technique to be used widely in C. elegans-based movement disorder assays to accelerate behavioral and cellular phenotypic investigations.
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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) | 0.001 | 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 | 0.001 | 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".