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

Expensive Egos: Narcissistic Males Have Higher Cortisol

Background: Narcissism is characterized by grandiosity, low empathy, and entitlement. There has been limited research regarding the hormonal correlates of narcissism, despite the potential health implications. This study examined the role of participant narcissism and sex on basal cortisol concentrations in an undergraduate population. Methods and Findings: Participants were 106 undergraduate students (79 females, 27 males, mean age 20.1 years) from one Midwestern and one Southwestern American university. Narcissism was assessed using the Narcissistic Personality Inventory, and basal cortisol concentrations were collected from saliva samples in a laboratory setting. Regression analyses examined the effect of narcissism and sex on cortisol (log). There were no sex differences in basal cortisol, F(1,97) =.20, p =.65, and narcissism scores, F(1,97) =.00, p =.99. Stepwise linear regression models of sex and narcissism and their interaction predicting cortisol concentrations showed no main effects when including covariates, but a significant interaction, b =.27, p =.04. Narcissism was not related to cortisol in females, but significantly predicted cortisol in males. Examining the effect of unhealthy versus healthy narcissism on cortisol found that unhealthy narcissism was marginally related to cortisol in females, b =.27, p =.06, but significantly predicted higher basal cortisol in males, b =.72, p =.01, even when controlling for potential confounds. No relationship was found between sex, narcissism, or their interaction on selfreported stress