High-Content Microscopy Analysis of Subcellular Structures: Assay Development and Application to Focal Adhesion Quantification.

High-content analysis (HCA) converts raw light microscopy images to quantitative data through the automated extraction, multiparametric analysis, and classification of the relevant information content. Combined with automated high-throughput image acquisition, HCA applied to the screening of chemicals or RNAi-reagents is termed high-content screening (HCS). Its power in quantifying cell phenotypes makes HCA applicable also to routine microscopy. However, developing effective HCA and bioinformatic analysis pipelines for acquisition of biologically meaningful data in HCS is challenging. Here, the step-by-step development of an HCA assay protocol and an HCS bioinformatics analysis pipeline are described. The protocol's power is demonstrated by application to focal adhesion (FA) detection, quantitative analysis of multiple FA features, and functional annotation of signaling pathways regulating FA size, using primary data of a published RNAi screen. The assay and the underlying strategy are aimed at researchers performing microscopy-based quantitative analysis of subcellular features, on a small scale or in large HCS experiments. © 2016 by John Wiley & Sons, Inc.

Preliminary validation of PRISM (Pictorial Representation of Illness and Self Measure) - a brief method to assess suffering.

BACKGROUND: Alleviation of suffering is widely acknowledged as one of the main goals of medicine. However, no measure to assess this crucial aspect of illness has been developed to date. AIMS: To validate PRISM (Pictorial Representation of Illness and Self-Measure) as a simple quantitative method of assessing the perceived burden of suffering due to illness. METHODS: Validity and reliability studies to date have involved over 700 patients with a variety of chronic physical illnesses. RESULTS: Reliability of PRISM is good (test-retest reliability r = 0.95; p < or = 0.001, interrater reliability r = 0.79; p < or = 0.001). Qualitative data indicate that the interpretation of the PRISM task is not only consistent among patients, but also consistent with that expected from existing literature on suffering. As expected, PRISM shows strong correlations with psychological variables (notably depression and coping resilience) and also correlates with SF-36 subscale scores. Prospective longitudinal data demonstrate that PRISM is sensitive to therapeutic change. It is very acceptable to patients and takes less than 5 min to administer. CONCLUSION: In the absence of a 'gold standard' measure of suffering, our validation data must be interpreted with caution. However, the performance of PRISM is entirely consistent with what would be expected of a measure of suffering, based on current published work.