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A micro-LED array based platform for spatio-temporal optogenetic control of various cardiac models.

ABSTRACT: Optogenetics relies on dynamic spatial and temporal control of light to address emerging fundamental and therapeutic questions in cardiac research. In this work, a compact micro-LED array, consisting of 16 × 16 pixels, is incorporated in a widefield fluorescence microscope for controlled light stimulation. We describe the optical design of the system that allows the micro-LED array to fully cover the field of view regardless of the imaging objective used. Various multicellular cardiac models are used in the experiments such as channelrhodopsin-2 expressing aggregates of cardiomyocytes, termed cardiac bodies, and bioartificial cardiac tissues derived from human induced pluripotent stem cells. The pacing efficiencies of the cardiac bodies and bioartificial cardiac tissues were characterized as a function of illumination time, number of switched-on pixels and frequency of stimulation. To demonstrate dynamic stimulation, steering of calcium waves in HL-1 cell monolayer expressing channelrhodopsin-2 was performed by applying different configurations of patterned light. This work shows that micro-LED arrays are powerful light sources for optogenetic control of contraction and calcium waves in cardiac monolayers, multicellular bodies as well as three-dimensional artificial cardiac tissues.

SUBMITTER: Junge S

PROVIDER: S-EPMC10636122 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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A micro-LED array based platform for spatio-temporal optogenetic control of various cardiac models.

Junge Sebastian S Ricci Signorini Maria Elena ME Al Masri Masa M Gülink Jan J Brüning Heiko H Kasperek Leon L Szepes Monika M Bakar Mine M Gruh Ina I Heisterkamp Alexander A Torres-Mapa Maria Leilani ML

Scientific reports 20231109 1

Optogenetics relies on dynamic spatial and temporal control of light to address emerging fundamental and therapeutic questions in cardiac research. In this work, a compact micro-LED array, consisting of 16 × 16 pixels, is incorporated in a widefield fluorescence microscope for controlled light stimulation. We describe the optical design of the system that allows the micro-LED array to fully cover the field of view regardless of the imaging objective used. Various multicellular cardiac models are ...[more]

PMID: 37945622

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Project description:Often, in environmental data collection, data arise from two sources: numerical models and monitoring networks. The first source provides predictions at the level of grid cells, while the second source gives measurements at points. The first is characterized by full spatial coverage of the region of interest, high temporal resolution, no missing data but consequential calibration concerns. The second tends to be sparsely collected in space with coarser temporal resolution, often with missing data but, where recorded, provides, essentially, the true value. Accommodating the spatial misalignment between the two types of data is of fundamental importance for both improved predictions of exposure as well as for evaluation and calibration of the numerical model. In this article we propose a simple, fully model-based strategy to downscale the output from numerical models to point level. The static spatial model, specified within a Bayesian framework, regresses the observed data on the numerical model output using spatially-varying coefficients which are specified through a correlated spatial Gaussian process.As an example, we apply our method to ozone concentration data for the eastern U.S. and compare it to Bayesian melding (Fuentes and Raftery 2005) and ordinary kriging (Cressie 1993; Chilès and Delfiner 1999). Our results show that our method outperforms Bayesian melding in terms of computing speed and it is superior to both Bayesian melding and ordinary kriging in terms of predictive performance; predictions obtained with our method are better calibrated and predictive intervals have empirical coverage closer to the nominal values. Moreover, our model can be easily extended to accommodate for the temporal dimension. In this regard, we consider several spatio-temporal versions of the static model. We compare them using out-of-sample predictions of ozone concentration for the eastern U.S. for the period May 1-October 15, 2001. For the best choice, we present a summary of the analysis. Supplemental material, including color versions of Figures 4, 5, 6, 7, and 8, and MCMC diagnostic plots, are available online.

Dataset Information

A micro-LED array based platform for spatio-temporal optogenetic control of various cardiac models.

Publications

A micro-LED array based platform for spatio-temporal optogenetic control of various cardiac models.

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