Matrix Softness-Mediated 3D Zebrafish Hepatocyte Modulates Response to Endocrine Disrupting Chemicals

Fish hepatocyte spheroids - A powerful (though underexplored) alternative in vitro model to study hepatotoxicity

In vitro fish cell cultures are considered alternative models to in vivo toxicological studies. The two-dimensional (2D) cultures have been used in toxicity testing, but those models have well-known drawbacks, namely in culture longevity and in the maintenance of some in vivo cellular functions. In this context, three-dimensional (3D) systems are now proposed to better mimic in vivo effects. The use of 3D cultures in fish is still limited (e.g., toxicity testing, drug biotransformation and bioaccumulation studies) compared to the number of studies with mammalian cells exploring the potential of these systems. In fish, the liver spheroids have been the most used 3D model, deriving from either liver cell lines or primary cultures of hepatocytes. Because the liver is the main organ for xenobiotic detoxification, hepatocyte spheroids represent a promising alternative to test concentration-responses to xenobiotics and explore mechanistic or ecotoxicological perspectives. Evidence shows that fish hepatocytes cultured in spheroids closely resemble the in vivo counterparts, additionally having higher basal metabolic capacity than hepatocytes cultured in monolayer. This graphical review is an updated critical sum-up of data published with 3D fish hepatocytes and provides background knowledge for the upcoming studies using this model. It further addresses the culture conditions for obtaining fish hepatocyte spheroids and discusses the main factors that can influence the biometry and functionality of spheroids over time in culture and the 2D versus 3D distinct metabolic capacities.

Non-radical mechanism and toxicity analysis of β-cyclodextrin functionalized biochar catalyzing the degradation of bisphenol A and its analogs by peroxydisulfate

Bisphenols (BPs) are distributed in worldwide as typical environmental hormones, which potentially harm the ecological environment and human health. In this study, four BPs, i.e., bisphenol A, bisphenol F, bisphenol S, and bisphenol AF, were used as prototypes to identify the intrinsic differences in degradation mechanisms correlated with the molecular structures in peroxydisulfate (PDS)-based advanced oxidation processes (AOPs). Electron transfer was the main way of modified biochar to trigger the heterogenous catalysis of PDS, which can cause the degradation of BPs. Phenolic hydroxyl groups on bisphenol pollutants were considered as possible active sites, and the existence of substituents was the main reason for the differentiation in the degradation efficiency of various bisphenols. Results of ecotoxicity prediction showed that most intermediates produced by the degradation of BPs in the β-SB/PDS system, which was dominated by the electron transfer pathway, had a lower toxicity than the parent molecules, while the toxicity of several ring cleavage intermediates was higher. This study presents a simple modification scheme for the conversion of biochar into functional catalysts and provides insights into the mechanism of heterogeneous catalytic degradation mediated by modified biochar as well as the degradation differences of bisphenol pollutants and their potential ecotoxicity.

Multiscale Assay of Unlabeled Neurite Dynamics Using Phase Imaging with Computational Specificity

Primary neuronal cultures have been widely used to study neuronal morphology, neurophysiology, neurodegenerative processes, and molecular mechanism of synaptic plasticity underlying learning and memory. However, the unique behavioral properties of neurons make them challenging to study, with phenotypic differences expressed as subtle changes in neuronal arborization rather than easy-to-assay features such as cell count. The need to analyze morphology, growth, and intracellular transport has motivated the development of increasingly sophisticated microscopes and image analysis techniques. Due to its high-contrast, high-specificity output, many assays rely on confocal fluorescence microscopy, genetic methods, or antibody staining techniques. These approaches often limit the ability to measure quantitatively dynamic activity such as intracellular transport and growth. In this work, we describe a method for label-free live-cell cell imaging with antibody staining specificity by estimating the associated fluorescence signals via quantitative phase imaging and deep convolutional neural networks. This computationally inferred fluorescence image is then used to generate a semantic segmentation map, annotating subcellular compartments of live unlabeled neural cultures. These synthetic fluorescence maps were further applied to study the time-lapse development of hippocampal neurons, highlighting the relationships between the cellular dry mass production and the dynamic transport activity within the nucleus and neurites. Our implementation provides a high-throughput strategy to analyze neural network arborization dynamically, with high specificity and without the typical phototoxicity and photobleaching limitations associated with fluorescent markers.