HF_IDS_Cam: Fast Video Capture with ImageJ for Real-Time Analysis

Fast online video analysis is currently a key issue for dynamic studies in biology; however, very few tools are available for these concerns. Here we present an ImageJ plug-in: HF_IDS_Cam, which allows for video capture at very high speeds using IDS (Imaging Development Systems GmbH) cameras and image analysis software ImageJ. The software has been optimized for real time video analysis with ImageJ native function and other plug-ins and scripts. The plug-in was written in Java and requires ImageJ 1.47v or higher. HF_IDS_Cam offers a wide range of applications for exploration of dynamic phenomena in biology, from in vitro/ex vivo studies, such as fast fluorescent calcium imaging and voltage optical mapping in cardiac myocytes and neurons, to in-vivo behavioral studies

Automatic quantitative analysis of t-tubule organization in cardiac myocytes using ImageJ

International audienceThe transverse tubule system in mammalian striated muscle is highly organized and contributes to optimal and homogeneous contraction. Diverse pathologies such as heart failure and atrial fibrillation include disorganization of t-tubules and contractile dysfunction. Few tools are available for the quantification of the organization of the t-tubule system. We developed a plugin for the ImageJ/Fiji image analysis platform developed by the National Institutes of Health. This plugin (TTorg) analyzes raw confocal microscopy images. Analysis options include the whole image, specific regions of the image (cropping), and z-axis analysis of the same image. Batch analysis of a series of images with identical criteria is also one of the options. There is no need to either reorientate any specimen to the horizontal or to do a thresholding of the image to perform analysis. TTorg includes a synthetic "myocyte-like" image generator to test the plugin's efficiency in the user's own experimental conditions. This plugin was validated on synthetic images for different simulated cell characteristics and acquisition parameters. TTorg was able to detect significant differences between the organization of the t-tubule systems in experimental data of mouse ventricular myocytes isolated from wild-type and dystrophin-deficient mice. TTorg is freely distributed, and its source code is available. It provides a reliable, easy-to-use, automatic, and unbiased measurement of t-tubule organization in a wide variety of experimental conditions

SarcOptiM for ImageJ: high-frequency online sarcomere length computing on stimulated cardiomyocytes

International audienceAccurate measurement of cardiomyocyte contraction is a critical issue for scientists working on cardiac physiology and physiopathology of diseases implying contraction impairment. Cardiomyocytes contraction can be quantified by measuring sarcomere length but few tools are available for this and none is freely distributed. We developed a plug-in (SarcOptiM) for the ImageJ/Fiji image analysis platform developed by the National Institute of Health. SarcOptiM computes sarcomere length via FFT analysis of video frames captured or displayed in ImageJ and thus is not tied to a dedicated video camera. It can work in real time or offline, the latter overcoming rotating motion or displacement related artifacts. SarcOptiM includes a simulator and video generator of cardiomyocyte contraction. Acquisition parameters such as pixel size and camera frame rate were tested with both experimental recordings of rat ventricular cardiomyocytes and synthetic videos. It is freely distributed and its source code is available. It works under Windows, Mac or Linux operating systems. The camera speed is the limiting factor since the algorithm can compute online sarcomere shortening at frame rates above 10 kHz. In conclusion, SarcOptiM is a free and validated user-friendly tool for studying cardiomyocyte contraction in all species including human

SarConfoCal: simultaneous sarcomere length and cytoplasmic calcium measurements for laser scanning confocal microscopy images

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Spiky: An ImageJ Plugin for Data Analysis of Functional Cardiac and Cardiomyocyte Studies

Introduction and objective: Nowadays, investigations of heart physiology and pathophysiology rely more and more upon image analysis, whether for the detection and characterization of events in single cells or for the mapping of events and their characteristics across an entire tissue. These investigations require extensive skills in image analysis and/or expensive software, and their reproducibility may be a concern. Our objective was to build a robust, reliable and open-source software tool to quantify excitation–contraction related experimental data at multiple scales, from single isolated cells to the whole heart. Methods and results: A free and open-source ImageJ plugin, Spiky, was developed to detect and analyze peaks in experimental data streams. It allows rapid and easy analysis of action potentials, intracellular calcium transient and contraction data from cardiac research experiments. As shown in the provided examples, both classical bi-dimensional data (XT signals) and video data obtained from confocal microscopy and optical mapping experiments (XYT signals) can be analyzed. Spiky was written in ImageJ Macro Language and JAVA, and works under Windows, Mac and Linux operating systems. Conclusion: Spiky provides a complete working interface to process and analyze cardiac physiology research data

Spiky: An ImageJ Plugin for Data Analysis of Functional Cardiac and Cardiomyocyte Studies

Introduction and objective: Nowadays, investigations of heart physiology and pathophysiology rely more and more upon image analysis, whether for the detection and characterization of events in single cells or for the mapping of events and their characteristics across an entire tissue. These investigations require extensive skills in image analysis and/or expensive software, and their reproducibility may be a concern. Our objective was to build a robust, reliable and open-source software tool to quantify excitation–contraction related experimental data at multiple scales, from single isolated cells to the whole heart. Methods and results: A free and open-source ImageJ plugin, Spiky, was developed to detect and analyze peaks in experimental data streams. It allows rapid and easy analysis of action potentials, intracellular calcium transient and contraction data from cardiac research experiments. As shown in the provided examples, both classical bi-dimensional data (XT signals) and video data obtained from confocal microscopy and optical mapping experiments (XYT signals) can be analyzed. Spiky was written in ImageJ Macro Language and JAVA, and works under Windows, Mac and Linux operating systems. Conclusion: Spiky provides a complete working interface to process and analyze cardiac physiology research data

Evaluation of the Ability of Streptococcus agalactiae Strains Isolated from Genital and Neonatal Specimens To Bind to Human Fibrinogen and Correlation with Characteristics of the fbsA and fbsB Genes

The ability of 111 Streptococcus agalactiae strains to bind to human fibrinogen was quantified. We correlated the percentages of bacteria that bound to immobilized fibrinogen with fibrinogen-binding (fbs) gene characteristics of strains and with clinical origin, serotypes, and phylogenetic positions of strains. Percentages varied from 0.4 to 29.9%. Fifty-five strains (49.5%) had the fbsB gene sensu stricto described by Gutekunst et al. (Infect. Immun., 72:3495-3504, 2004), allowing adhesion to human fibrinogen, and all of the other strains had an fgag variant gene. Ninety strains (81.1%) had a fbsA gene and 55 of them also had the fbsB gene. The other 21 strains (18.9%) had a truncated form of fbsA without the fbsB gene sensu stricto. The numbers of 48-nucleotide repeat sequences (rs) in the fbsA gene varied from 2 to 26. The population of strains with the highest ability to bind to human fibrinogen significantly more frequently had the fbsB gene sensu stricto and 4 to 7 rs in the fbsA gene (P < 0.05). However, the single strain that carried the highest number of rs (26 rs) in the fbsA gene showed high fibrinogen-binding activity (24.3%). Strains exhibiting significantly higher levels of binding to human fibrinogen belonged to a phylogenetic group of strains associated with neonatal meningitis, currently known as the ST-17 clone, that is mostly composed of serotype III strains. These findings indicate that S. agalactiae strains possess a wide variety of fbs gene content that markedly influences the ability of strains to bind to human fibrinogen. Variations in the configuration and the expression of the Fbs proteins may therefore partly explain the variability of virulence in S. agalactiae species