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Record W3161828682 · doi:10.1364/boe.427685

High-speed label-free confocal microscopy of Caenorhabditis elegans with near infrared spectrally encoded confocal microscopy

2021· article· en· W3161828682 on OpenAlexafffund
Sadaf Rashtchian, Khaled Youssef, Pouya Rezai, Nima Tabatabaei

Bibliographic record

VenueBiomedical Optics Express · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCaenorhabditis elegansConfocalConfocal microscopyMicroscopyMicroscopeOpticsBiologyBiophysicsMaterials scienceCell biologyPhysicsGeneGenetics

Abstract

fetched live from OpenAlex

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 .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.604
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.262
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreMethods

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".

Quick stats

Citations5
Published2021
Admission routes2
Has abstractyes

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