Rapid Analysis of Vessel Elements (RAVE): A Tool for Studying Physiologic, Pathologic and Tumor Angiogenesis

Quantification of microvascular network structure is important in a myriad of emerging research fields including microvessel remodeling in response to ischemia and drug therapy, tumor angiogenesis, and retinopathy. To mitigate analyst-specific variation in measurements and to ensure that measurements represent actual changes in vessel network structure and morphology, a reliable and automatic tool for quantifying microvascular network architecture is needed. Moreover, an analysis tool capable of acquiring and processing large data sets will facilitate advanced computational analysis and simulation of microvascular growth and remodeling processes and enable more high throughput discovery. To this end, we have produced an automatic and rapid vessel detection and quantification system using a MATLAB graphical user interface (GUI) that vastly reduces time spent on analysis and greatly increases repeatability. Analysis yields numerical measures of vessel volume fraction, vessel length density, fractal dimension (a measure of tortuosity), and radii of murine vascular networks. Because our GUI is open sourced to all, it can be easily modified to measure parameters such as percent coverage of non-endothelial cells, number of loops in a vascular bed, amount of perfusion and two-dimensional branch angle. Importantly, the GUI is compatible with standard fluorescent staining and imaging protocols, but also has utility analyzing brightfield vascular images, obtained, for example, in dorsal skinfold chambers. A manually measured image can be typically completed in 20 minutes to 1 hour. In stark comparison, using our GUI, image analysis time is reduced to around 1 minute. This drastic reduction in analysis time coupled with increased repeatability makes this tool valuable for all vessel research especially those requiring rapid and reproducible results, such as anti-angiogenic drug screening

The chicken chorioallantoic membrane model in biology, medicine and bioengineering

The chicken chorioallantoic membrane (CAM) is a simple, highly vascularized extraembryonic membrane, which performs multiple functions during embryonic development, including but not restricted to gas exchange. Over the last two decades, interest in the CAM as a robust experimental platform to study blood vessels has been shared by specialists working in bioengineering, development, morphology, biochemistry, transplant biology, cancer research and drug development. The tissue composition and accessibility of the CAM for experimental manipulation, makes it an attractive preclinical in vivo model for drug screening and/or for studies of vascular growth. In this article we provide a detailed review of the use of the CAM to study vascular biology and response of blood vessels to a variety of agonists. We also present distinct cultivation protocols discussing their advantages and limitations and provide a summarized update on the use of the CAM in vascular imaging, drug delivery, pharmacokinetics and toxicology

Revamping research on unrelated diversification strategy: perspectives, opportunities and challenges for future inquiry

With the aim of achieving an advanced understanding of current research on unrelated diversification and providing fruitful groundwork to foster active interchange between disciplinary traditions, this paper detects articles from two relevant research streams; i.e., strategic management and financial economics. We first provide a brief overview of management thinking on unrelated diversification strategy. Then, we present a conceptual map that offers a comprehensive appreciation of unrelated diversification strategy antecedents (i.e., environmental and institutional, organizational value-enhancing, and managerial drivers), implementation process (i.e., managerial complexity, misallocation of resources, and structural inertia), and consequences (i.e., diversification premiums and discounts). Finally, we unpack the major gaps in our current knowledge that may help refocus the research agenda on unrelated diversification strategy and revamp the apparent waning proclivity of this issue