Bilirubin neurotoxicity has been studied for decades and has been shown to affect various mechanisms via significant modulation of gene expression. This suggests that vital regulatory mechanisms of gene expression, such as epigenetic mechanisms, could play a role in bilirubin neurotoxicity. Histone acetylation has recently received attention in the CNS due to its role in gene modulation for numerous biological processes, such as synaptic plasticity, learning, memory, development and differentiation. Aberrant epigenetic regulation of gene expression in psychiatric and neurodegenerative disorders has also been described. In this work, we followed the levels of histone 3 lysine 14 acetylation (H3K14Ac) in the cerebellum (Cll) of the developing (2, 9, 17 days after the birth) and adult Gunn rat, the natural model for neonatal hyperbilirubinemia and kernicterus. We observed an age-specific alteration of the H3K14Ac in the hyperbilirubinemic animals. The GeneOntology analysis of the H3K14Ac linked chromatin revealed that almost 45% of H3K14Ac ChiP-Seq TSS-promoter genes were involved in CNS development including maturation and differentiation, morphogenesis, dendritogenesis, and migration. These data suggest that the hallmark Cll hypoplasia in the Gunn rat occurs also via epigenetically controlled mechanisms during the maturation of this brain structure, unraveling a novel aspect of the bilirubin-induced neurotoxicity.

Freezing—cryosurgery, and electrolysis—electrochemical therapy (EChT), are two important minimally invasive surgery tissue ablation technologies. Despite major advantages they also have some disadvantages. Cryosurgery cannot induce cell death at high subzero freezing temperatures and requires multiple freeze thaw cycles, while EChT requires high concentrations of electrolytic products—which makes it a lengthy procedure. Based on the observation that freezing increases the concentration of solutes (including products of electrolysis) in the frozen region and permeabilizes the cell membrane to these products, this study examines the hypothesis that there could be a synergistic effect between freezing and electrolysis in their use together for tissue ablation. Using an animal model we refer to as vivens ex vivo, which may be of value in reducing the use of animals for experiments, combined with a Hematoxylin stain of the nucleus, we show that there are clinically relevant protocols in which the cell nucleus appears intact when electrolysis and freezing are used separately but is affected by certain combinations of electrolysis and freezing.

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Deep learning is widely applied in bioinformatics and biomedical imaging, due to its ability to perform various clinical tasks automatically and accurately. In particular, the application of deep learning techniques for the automatic identification of glomeruli in histopathological kidney images can play a fundamental role, offering a valid decision support system tool for the automatic evaluation of the Karpinski metric. This will help clinicians in detecting the presence of sclerotic glomeruli in order to decide whether the kidney is transplantable or not. In this work, we implemented a deep learning framework to identify and segment sclerotic and non-sclerotic glomeruli from scanned Whole Slide Images (WSIs) of human kidney biopsies. The experiments were conducted on a new dataset collected by both the Siena and Trieste hospitals. The images were segmented using the DeepLab V2 model, with a pre-trained ResNet101 encoder, applied to 512 × 512 patches extracted from the original WSIs. The results obtained are promising and show a good performance in the segmentation task and a good generalization capacity, despite the different coloring and typology of the histopathological images. Moreover, we present a novel use of the CD10 staining procedure, which gives promising results when applied to the segmentation of sclerotic glomeruli in kidney tissues.