Segmentation is one of the most important steps in microscopy image analysis. Unfortunately, most of the methods use fluorescence images for this task, which is not suitable for analysis that requires a knowledge of area occupied by cells and an experimental design that does not allow necessary labeling. In this protocol, we present a simple method, based on edge detection and morphological operations, that separates total area occupied by cells from the background using only brightfield channel image. The resulting segmented picture can be further used as a mask for fluorescence quantification and other analyses. The whole procedure is carried out in open source software Fiji.

All-trans-retinoic acid (atRA) is a potent ligand that regulates gene expression and is used to treat several skin disorders. Hyaluronic acid (HA) was previously conjugated with atRA (HA-atRA) to obtain a novel amphiphilic compound. HA-atRA forms micelles that incorporate hydrophobic molecules and facilitate their transport through the skin. The aim of this study was to determine the influence of HA-atRA on gene expression in skin cells and to compare it with that of unbound atRA. Gene expression was investigated using microarrays and a luciferase system with a canonical atRA promoter. HA-atRA upregulated gene expression similarly to atRA. However, HA-atRA activated the expression of cholesterol metabolism genes, unlike atRA. Further investigation using HPLC and filipin III staining suggested that the treated cells induced cholesterol synthesis to replenish the cholesterol removed from the cells by HA-atRA. HA modified with oleate (HA-C18:1) removed cholesterol from the cells similarly to HA-atRA, suggesting that the cholesterol removal stemmed from the amphiphilic nature of the two derivatives. HA-atRA induces retinoid signaling. Thus, HA-atRA could be used to treat skin diseases, such as acne and psoriasis, where the combined action of atRA signaling and anti-inflammatory cholesterol removal may be potentially beneficial.