Endothelial cell biology has developed into a vibrant discipline and has become a critical instrument to study several disease processes on the cellular and molecular level. It is now widely recognized that dysfunctions of normal endothelial cell homeostasis are involved in some of the most important human diseases, including ischemic heart diseases, hypertension, atherosclerosis, tumors, diabetes, arthritis, and inflammation. Further, the increasing importance and recognition of the field of vascular biology in general requires in vitro and in vivo techniques in order to address the complex questions. Methods in Endothelial Cell Biology is a comprehensive practical "how-to"-guide summarizing the most relevant established techniques as well as a number of new emerging techniques. Easy-to-follow reliable protocols provide a useful lab bench resource for the experienced researcher and newcomer to the field.

This Open Access textbook provides students and researchers in the life sciences with essential practical information on how to quantitatively analyze data images. It refrains from focusing on theory, and instead uses practical examples and step-by step protocols to familiarize readers with the most commonly used image processing and analysis platforms such as ImageJ, MatLab and Python. Besides gaining knowhow on algorithm usage, readers will learn how to create an analysis pipeline by scripting language; these skills are important in order to document reproducible image analysis workflows. The textbook is chiefly intended for advanced undergraduates in the life sciences and biomedicine without a theoretical background in data analysis, as well as for postdocs, staff scientists and faculty members who need to perform regular quantitative analyses of microscopy images.

There can no longer be any doubt that the endothelium represents a very active tissue and is not, as had previously been thought, merely an inert lining material. On the contrary, the endothelium exerts a powerful influence on its environs through the release of multiple regulatory factors such as nitric oxide, endothelium derived hyperpolarizing factor and endothelin. It is therefore crucial to our understanding of the cardiovascular system that we are able to visualize the endothelial layer at the molecular level. Quantitative morphological studies permit visualization at this level, allowing the assessment of the changes that occur in the disease state. Modern methods of computerized image analysis have been applied to reconstruct the endothelial layer in three-dimensions - detecting even the most subtle of changes. Within these covers, an integrated text has been gathered by experts in each of their fields. They detail the latest technical and conceptual advances in the visualization of endothelium, its production of regulatory molecules and pathological changes.

This volume provides a timely and useful introduction to the theory and practical application of image analysis in histology. This powerful research technique can be used to detect not only stored products in a cell (immunocytochemistry) but the synthetic machinery and the genes that control it (in situ hybridisation), as well as the specific binding sites that act as receptors for a molecule following its release (in vitro autoradiography). The book provides a good introduction for beginners before looking in greater detail at more advanced material in selected areas. The volume highlights the importance of technique in gathering quantitative information. The book is divided into four sections: introductory material, image acquisition, image processing, and applications. The applications areas include quantitative immunochemistry, quantification of nerves and neurotransmitters and automated grain counting in in situ hybridisation histochemistry.

A comprehensive guide to the art and science of bioimaging data acquisition, processing and analysis Standard and Super-Resolution Bioimaging Data Analysis gets newcomers to bioimage data analysis quickly up to speed on the mathematics, statistics, computing hardware and acquisition technologies required to correctly process and document data. The past quarter century has seen remarkable progress in the field of light microscopy for biomedical science, with new imaging technologies coming on the market at an almost annual basis. Most of the data generated by these systems is image-based, and there is a significant increase in the content and throughput of these imaging systems. This, in turn, has resulted in a shift in the literature on biomedical research from descriptive to highly-quantitative. Standard and Super-Resolution Bioimaging Data Analysis satisfies the demand among students and research scientists for introductory guides to the tools for parsing and processing image data. Extremely well illustrated and including numerous examples, it clearly and accessibly explains what image data is and how to process and document it, as well as the current resources and standards in the field. A comprehensive guide to the tools for parsing and processing image data and the resources and industry standards for the biological and biomedical sciences Takes a practical approach to image analysis to assist scientists in ensuring scientific data are robust and reliable Covers fundamental principles in such a way as to give beginners a sound scientific base upon which to build Ideally suited for advanced students having only limited knowledge of the mathematics, statistics and computing required for image data analysis An entry-level text written for students and practitioners in the bioscience community, Standard and Super-Resolution Bioimaging Data Analysis de-mythologises the vast array of image analysis modalities which have come online over the past decade while schooling beginners in bioimaging principles, mathematics, technologies and standards.