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Record W2050051718 · doi:10.1109/iembs.2011.6089890

Fluorescence-based system for measurement of electrophysiological changes in stretched cultured cardiomyocytes

2011· article· en· W2050051718 on OpenAlexaff
James Elber Duverger, Jonathan Béland, Ange Maguy, Mouhamed M. Adegbindin, Philippe Comtois

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsFluorescenceVoltage-sensitive dyeElectrophysiologyMaterials scienceVoltagePhotodiodeSIGNAL (programming language)BiophysicsCalciumBiomedical engineeringMembrane potentialOptoelectronicsChemistryElectrical engineeringOpticsComputer sciencePhysicsBiologyMedicineEngineering

Abstract

fetched live from OpenAlex

Acute or sustained stretch of cardiac tissue is known to play a key role in arrhythmogenesis. Using a fluorescence approach, we designed a system measuring calcium transients and transmembrane potential changes in monolayers of cultured cardiomyocytes under uniaxial elongation and electrical stimulation. Cardiac myocytes are seeded on a rectangular PDMS template held and stretched by a motorized linear guide system. Electrical stimulation is performed with two parallel carbon electrodes supplied by amplified pulses from a digital-to-analog converter. The cells are stained with either voltage- or calcium-sensitive dye (di-4-ANEPPS and Fluo-4 AM respectively). The two available excitation light sources are both current-controlled LED arrays (λ = 523 ± 45 nm for di-4-ANEPPS and λ = 505 ± 15 nm for Fluo-4 AM). The filtered emitted fluorescence (λ > 610 nm for di-4-ANEPPS and λ = 535 ± 25 nm for Fluo-4 AM) is transduced to current with a photodiode, converted to amplified voltage signals and digitized. The design and preliminary validation results are presented.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.106
GPT teacher head0.247
Teacher spread0.140 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1
Published2011
Admission routes1
Has abstractyes

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