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Record W4304606597 · doi:10.1101/2022.10.10.511562

Simultaneous widefield voltage and interferometric dye-free optical mapping quantifies electromechanical waves in human iPSC-cardiomyocytes

2022· preprint· en· W4304606597 on OpenAlexaff
Wei Liu, Julie Han, Jakub Tomek, Gil Bub, Emilia Entcheva

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsMcGill University
FundersDivision of Emerging Frontiers in Research and InnovationNational Institutes of HealthNational Science Foundation
KeywordsOptical mappingVoltage-sensitive dyeInduced pluripotent stem cellInterferometryMaterials scienceOptoelectronicsOpticsBiomedical engineeringPhysicsChemistryOptical imagingMedicine

Abstract

fetched live from OpenAlex

ABSTRACT Coupled electro-mechanical waves define heart’s function in health and disease. Genetic abnormalities, drug-triggered or acquired pathologies can disrupt and uncouple these waves with potentially lethal consequences. Optical mapping of electrical waves using fluorescent dyes or genetically-encoded sensors in human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) offers mechanistic insights into cardiac conduction abnormalities. Interferometric dye-free/label-free wave mapping (without specific sensors) presents an alternative, likely capturing the mechanical aspects of cardiac conduction. Because of its non-invasive nature and spectral flexibility (not restricted to a specific excitation wavelength), it is an attractive chronic imaging tool in iPSC-CMs, as part of all-optical high-throughput platforms. In this study, we developed simultaneous widefield voltage and interferometric dye-free optical imaging methodology that was used: 1) to validate dye-free optical mapping for quantification of cardiac wave properties in human iPSC-CMs; 2) to demonstrate low-cost optical mapping of electromechanical waves in hiPSC-CMs using recent near-infrared (NIR) voltage sensors and orders of magnitude cheaper miniature CMOS cameras; 3) to uncover previously underexplored frequency- and space-varying parameters of cardiac electromechanical waves in hiPSC-CMs. We find similarity in the frequency-dependent responses of electrical (NIR fluorescence imaged) and mechanical (dye-free imaged) waves, with the latter being more sensitive to faster rates and showing steeper restitution and earlier appearance of wave-front tortuosity. During regular pacing, the dye-free imaged conduction velocity and the electrical wave velocity are correlated; both modalities being sensitive to pharmacological uncoupling and both dependent on gap-junctional protein (connexins) determinants of wave propagation. We uncover strong frequency-dependence of the electromechanical delay (EMD) locally and globally in hiPSC-CMs on a rigid substrate. The presented framework and results offer new means to track the functional responses of hiPSC-CM inexpensively and non-invasively for counteracting heart disease and aiding cardiotoxicity testing and drug development.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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
Published2022
Admission routes1
Has abstractyes

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