Fluorescence and differential light absorption recordings with calcium probes and potential-sensitive dyes in skinned cardiac cells

1982 ◽  
Vol 60 (4) ◽  
pp. 556-567 ◽  
Author(s):  
Alexandre Fabiato
Keyword(s):  
Cardiac Cells ◽  
Arsenazo Iii ◽  
Optical Methods ◽  
Cardiac Cell ◽  
Differential Absorption ◽  
Fluorescence Measurements ◽  
Merocyanine 540 ◽  
Inverted Microscope ◽  
Optimum Wavelength ◽  
Absorption Measurements

This report describes an optical system for microspectrophotometry in a single cardiac cell from which the sarcolemma has been removed by microdissection (skinned cardiac cell). This system is attached to the high power inverted microscope used for the microdissection and includes (a) a single variable wavelength microspectrophotometer used to define the spectrum of a given dye or Ca2+ probe; and (b) a dual wavelength, differential microspectrophotometer used to record differentially between the optimum wavelength and a wavelength separated by 25–30 nm. Results are presented using the following optical methods: (a) fluorescence measurements with chlorotetracycline to monitor the amount of Ca2+ bound to the inner face of the sarcoplasmic reticulum (SR) membrane; (b) differential absorption measurements with arsenazo III to measure changes of myoplasmic [Ca2+]free resulting from Ca2+ release from the SR; (c) fluorescence and (or) differential absorption measurements with the potential-sensitive dyes merocyanine 540, NK 2367, and di-S-C3(5) to monitor changes of charge distribution on the SR membrane during Ca2+ accumulation in the SR, as well as before and during Ca2+-induced release of Ca2+ from the SR. A small and rapid signal is observed which precedes the Ca2+-induced release of Ca2+ from the SR. It is detected as an increase of Ca2+ binding inside the SR with chlorotetracycline and as a "hyperpolarization" with potential-sensitive dyes, while no transient change of myoplasmic [Ca2+]free is detected with arsenazo III. This small and rapid signal preceding the Ca2+ release may be a first hint to an understanding of the mechanism whereby a small increase of [Ca2+]free outside the SR triggers Ca2+ release from the SR.

Differential absorption measurements of Cr4+-doped forsterite under picosecond excitation

1997 ◽  
Author(s):  
Konstantin V. Yumashev ◽  
Nickolai V. Kuleshov ◽  
P. V. Prokoshin ◽  
Alexander M. Malyarevich ◽  
Victor P. Mikhailov
Keyword(s):  
Differential Absorption ◽  
Picosecond Excitation ◽  
Absorption Measurements

scholarly journals H2S Protects against Cardiac Cell Hypertrophy through Regulation of Selenoproteins

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Adam Greasley ◽  
Yanjie Zhang ◽  
Bo Wu ◽  
Yanxi Pei ◽  
Nelson Belzile ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Cardiac Hypertrophy ◽  
Critical Role ◽  
Thioredoxin Reductase ◽  
Cardiac Cells ◽  
Keshan Disease ◽  
Mouse Heart ◽  
Cardiac Cell ◽  
Cell Hypertrophy ◽  
Expression Of Genes

Cardiac hypertrophy is defined as the enlargement of the cardiac myocytes, leading to improper nourishment and oxygen supply due to the increased functional demand. This increased stress on the cardiac system commonly leads to myocardial infarction, contributing to 85% of all cardiac-related deaths. Cystathionine gamma-lyase- (CSE-) derived H2S is a novel gasotransmitter and plays a critical role in the preservation of cardiac functions. Selenocysteine lyase (SCLY) has been identified to produce H2Se, the selenium homologue of H2S. Deficiency of selenium is often found in Keshan disease, a congestive cardiomyopathy. The interaction of H2S and H2Se in cardiac cell hypertrophy has not been explored. In this study, cell viability was evaluated with a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Oxidative stress and cell size were observed through immunostaining. The expression of genes was determined by real-time PCR and western blot. Here, we demonstrated that incubation of rat cardiac cells (H9C2) with H2O2 lead to increased oxidative stress and cell surface area, which were significantly attenuated by pretreatment of either H2S or H2Se. H2S incubation induced SCLY/H2Se signaling, which next caused higher expressions and activities of selenoproteins, including glutathione peroxidase and thioredoxin reductase. Furthermore, deficiency of CSE inhibited the expressions of SCLY and selenoprotein P in mouse heart tissues. We also found that both H2S and H2Se stimulated Nrf2-targeted downstream genes. These data suggests that H2S protects against cardiac hypertrophy through enhancement of a group of antioxidant proteins.

scholarly journals An Automated Workflow for Segmenting Single Adult Cardiac Cells from Large-Volume Serial Block-Face Scanning Electron Microscopy Data

2018 ◽  
Author(s):  
Akter Hussain ◽  
Shouryadipta Ghosh ◽  
Siavash Beikoghli Kalkhoran ◽  
Derek J. Hausenloy ◽  
Eric Hanssen ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Heart Function ◽  
Cardiac Cells ◽  
Scanning Electron Microscopy Data ◽  
Cardiac Cell ◽  
Branching Points ◽  
Face Scanning ◽  
Block Face ◽  
Scanning Electron

ABSTRACTThis paper presents a new algorithm to automatically segment the myofibrils, mitochondria and nuclei within single adult cardiac cells that are part of a large serial-block-face scanning electron microscopy (SBF-SEM) dataset. The algorithm only requires a set of manually drawn contours that roughly demarcate the cell boundary at routine slice intervals (every 50th, for example). The algorithm correctly classified pixels within the single cell with 97% accuracy when compared to manual segmentations. One entire cell and the partial volumes of two cells were segmented. Analysis of segmentations within these cells showed that myofibrils and mitochondria occupied 47.5% and 51.6% on average respectively, while the nuclei occupy 0.7% of the cell for which the entire volume was captured in the SBF-SEM dataset. Mitochondria clustering increased at the periphery of the nucleus region and branching points of the cardiac cell. The segmentations also showed high area fraction of mitochondria (up to 70% of the 2D image slice) in the sub-sarcolemmal region, whilst it was closer to 50% in the intermyofibrillar space. We finally demonstrate that our segmentations can be turned into 3D finite element meshes for cardiac cell computational physiology studies. We offer our large dataset and MATLAB implementation of the algorithm for research use at www.github.com/CellSMB/sbfsem-cardiac-cell-segmenter/. We anticipate that this timely tool will be of use to cardiac computational and experimental physiologists alike who study cardiac ultrastructure and its role in heart function.

scholarly journals Reproducible model development in the Cardiac Electrophysiology Web Lab

2018 ◽  
Author(s):  
Aidan C. Daly ◽  
Michael Clerx ◽  
Kylie A. Beattie ◽  
Jonathan Cooper ◽  
David J. Gavaghan ◽  
...  
Keyword(s):  
Experimental Data ◽  
Cardiac Electrophysiology ◽  
Model Building ◽  
Research Effort ◽  
Model Development ◽  
Cardiac Cells ◽  
Cardiac Cell ◽  
Cell Models ◽  
Experimental Protocol ◽  
Wide Range

AbstractThe modelling of the electrophysiology of cardiac cells is one of the most mature areas of systems biology. This extended concentration of research effort brings with it new challenges, foremost among which is that of choosing which of these models is most suitable for addressing a particular scientific question. In a previous paper, we presented our initial work in developing an online resource for the characterisation and comparison of electrophysiological cell models in a wide range of experimental scenarios. In that work, we described how we had developed a novel protocol language that allowed us to separate the details of the mathematical model (the majority of cardiac cell models take the form of ordinary differential equations) from the experimental protocol being simulated. We developed a fully-open online repository (which we termed the Cardiac Electrophysiology Web Lab) which allows users to store and compare the results of applying the same experimental protocol to competing models. In the current paper we describe the most recent and planned extensions of this work, focused on supporting the process of model building from experimental data. We outline the necessary work to develop a machine-readable language to describe the process of inferring parameters from wet lab datasets, and illustrate our approach through a detailed example of fitting a model of the hERG channel using experimental data. We conclude by discussing the future challenges in making further progress in this domain towards our goal of facilitating a fully reproducible approach to the development of cardiac cell models.

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