High-speed label-free confocal microscopy of Caenorhabditis elegans with near infrared spectrally encoded confocal microscopy
Bibliographic record
Abstract
Caenorhabditis elegans (C. elegans) is an optically transparent nematode that shares many gene orthologs and homologs with humans. C. elegans are widely used in large populations for genetic studies relevant to human biology and disease. Success of such studies frequently relies on the ability to image C. elegans structure at high-resolution and high-speed. In this manuscript, we report on the feasibility and suitability of a high-speed variant of reflectance confocal microscopy, known as spectrally encoded confocal microscopy (SECM), for label-free imaging of C. elegans. The developed system utilizes near-infrared illumination in conjunction with refractive and diffractive optics to instantaneously image a confocal image line at a speed of up to 147 kHz with lateral and axial resolutions of 2µm and 10µm, respectively. Our imaging results from wild-type C. elegans and four mutant strains (MT2124, MT1082, CB61, and CB648) demonstrate the ability of SECM in revealing the overall geometry, key internal organs, and mutation-induced structural variations, opening the door for downstream integration of SECM in microfluidic platforms for high throughput structural imaging of C. elegans.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".