Dimethyl sulfoxide (DMSO) is used to sustain or favor hepatocyte differentiation in vitro. Thus, DMSO is used in the differentiation protocol of the HepaRG cells that present the closest drug-metabolizing enzyme activities to primary human hepatocytes in culture. The aim of our study is to clarify its influence on liver-specific gene expression. For that purpose, we performed a large-scale analysis (gene expression and histone modification) to determine the global role of DMSO exposure during the differentiation process of the HepaRG cells. The addition of DMSO drives the upregulation of genes mainly regulated by PXR and PPARα whereas genes not affected by this addition are regulated by HNF1α, HNF4α, and PPARα. DMSO-differentiated-HepaRG cells show a differential expression for genes regulated by histone acetylation, while differentiated-HepaRG cells without DMSO show gene signatures associated with histone deacetylases. In addition, we observed an interplay between cytoskeleton organization and EMC remodeling with hepatocyte maturation.

In order to identify the peptides, selected from the literature, that exhibit the strongest tropism towards human hepatoma cells, cell uptake assays were performed using biotinylated synthetic peptides bound to fluorescent streptavidin or engrafted onto nanoparticles (NPs), prepared from biotin-poly(ethylene glycol)-block-poly(benzyl malate) (Biot-PEG-b-PMLABe) via streptavidin bridging. Two peptides, derived from the circumsporozoite protein of Plasmodium berghei- (CPB) and George Baker (GB) Virus A (GBVA10-9), strongly enhanced the endocytosis of both streptavidin conjugates and NPs in hepatoma cells, compared to primary human hepatocytes and non-hepatic cells. Unexpectedly, the uptake of CPB- and GBVA10-9 functionalized PEG-b-PMLABe-based NPs by hepatoma cells involved, at least in part, the peptide binding to apolipoproteins, which would promote NP’s interactions with cell membrane receptors of HDL particles. In addition, CPB and GBVA10-9 peptide–streptavidin conjugates favored the uptake by hepatoma cells over that of the human macrophages, known to strongly internalize nanoparticles by phagocytosis. These two peptides are promising candidate ligands for targeting hepatocellular carcinomas.

The progress of digital pathology in recent years has been an opportunity for the development of automated image analysis algorithms for quantitative measurements and computer aided diagnosis. With those new methods comes the need for high staining quality and reproducibility, as image analysis tools are typically more sensible to slight stain variations than trained pathologists. This article presents a method for the automated analysis of cytology slides stains specifically adapted to the challenges encountered in digital cytopathology. In particular, the variety of cell types in cytology slides, the 3D distribution of the cellular material, the presence of superposed cells and the need for independent analysis of sub‐cellular compartments are addressed. The proposed method is applied to the quantification of staining variations for quality control, resulting from changes in the staining protocol such as reagent immersion time or a reagent change. Another demonstrated application is the selection of staining protocol parameters that maximize the visible details in nucleus. Finally the analysis pipeline is also used to compare different stain normalization algorithms on digital cytology slides. Code available at: https://gitlab.com/vitadx/articles/automated_staining_analysis.

Urine cytology is non-invasive, easy to collect, with medium sensitivity and a high specificity. It is an effective way to detect high-grade bladder cancer (BC), but it is less effective on low-grade BC because the rate of equivocal results is much higher. Recently, the fluorescent properties of plasma membranes of urothelial tumor cells (UTC) found in urine cytology have been shown to be useful in improving the early detection of BC. This phenomenon is called peri-membrane fluorescence (PMF). Based on previous studies that have identified the PMF on UTCs, the main objective was to characterize this phenomenon. For this study, a software was specially created to quantify the PMF of all tested cells and different treatments performed. PMF was not found to be a morphological and discriminating feature of UTCs, all cells in shape and not from urine show PMF. We were able to highlight the crucial role of plasma membrane integrity in the maintenance of PMF. Finally, it was found that the induction of a strong cellular stress induced a decrease in PMF, mimicking what was observed in non-tumor cells collected from urine. These results suggest that PMF is found in cells able to resist this stress, such as tumor cells.