Resilience of three-dimensional sinusoidal networks in liver tissue

Tryptophan Prevents the Development of Non-Alcoholic Fatty Liver Disease

Purpose

The main aim of this research is to study the protective effects of tryptophan on the histomorphological and biochemical abnormalities in the liver caused by a high-calorie diet (HCD), as well as its ability to normalize mitochondrial functions in order to prevent the development of non-alcoholic fatty liver disease (NAFLD).

Methods

The study was conducted in male Wistar rats aged 3 months at the start of the experiment. Control animals (group I) were fed a standard diet. Group II experimental animals were fed a diet with an excess of fat (45%) and carbohydrates (31%) for 12 weeks. Group III experimental animals also received L-tryptophan at a dose of 80 mg/kg body weight in addition to the HCD. The presence of NAFLD, functional activity, physiological regeneration, and the state of the liver parenchyma and connective tissue were assessed using physiological, morphological, histo-morphometric, biochemical, and biophysical research methods.

Results

HCD induced the development of NAFLD, which is characterized by an increase in liver weight, hypertrophy of hepatocytes and an increase in the concentration of lipids, cholesterol and triglycerides in liver tissue. Increased alanine aminotransferase activity in the liver of obese rats also confirm hepatocytes damage. Tryptophan added to the diet lowered the severity of NAFLD by reducing fat accumulation and violations of bioelectric properties, and prevented a decrease in mitochondrial ATP synthesis.

Conclusion

The addition of tryptophan can have a potential positive effect on the liver, reducing the severity of structural, biochemical, mitochondrial and bioelectric damage caused by HCD.

Demand-driven design of bicycle infrastructure networks for improved urban bikeability

Cycling is crucial for sustainable urban transportation. Promoting cycling critically relies on sufficiently developed infrastructure; however, designing efficient bike path networks constitutes a complex problem that requires balancing multiple constraints. Here we propose a framework for generating efficient bike path networks, explicitly taking into account cyclists' demand distribution and route choices based on safety preferences. By reversing the network formation, we iteratively remove bike paths from an initially complete bike path network and continually update cyclists' route choices to create a sequence of networks adapted to the cycling demand. We illustrate the applicability of this demand-driven approach for two cities. A comparison of the resulting bike path networks with those created for homogenized demand enables us to quantify the importance of the demand distribution for network planning. The proposed framework may thus enable quantitative evaluation of the structure of current and planned cycling networks, and support the demand-driven design of efficient infrastructures.

Multiscale biomechanics and mechanotransduction from liver fibrosis to cancer

A growing body of multiscale biomechanical studies has been proposed to highlight the mechanical cues in the development of hepatic fibrosis and cancer. At the cellular level, changes in mechanical microenvironment induce phenotypic and functional alterations of hepatic cells, initiating a positive feedback loop that promotes liver fibrogenesis and hepatocarcinogenesis. Tumor mechanical microenvironment of hepatocellular carcinoma facilitates tumor cell growth and metastasis, and hinders the drug delivery and immunotherapy. At the molecular level, mechanical forces are sensed and transmitted into hepatic cells via allosteric activation of mechanoreceptors on the cell membrane, leading to the activation of various mechanotransduction pathways including integrin and YAP signaling and then regulating cell function. Thus, the application of mechanomedicine concept in the treatment of liver diseases is promising for rational design and cell-specific delivery of therapeutic drugs. This review mainly discusses the correlation between biomechanical cues and liver diseases from the viewpoint of mechanobiology.

Automated Detection of Portal Fields and Central Veins in Whole-Slide Images of Liver Tissue

Many physiological processes and pathological phenomena in the liver tissue are spatially heterogeneous. At a local scale, biomarkers can be quantified along the axis of the blood flow, from portal fields (PFs) to central veins (CVs), i.e., in zonated form. This requires detecting PFs and CVs. However, manually annotating these structures in multiple whole-slide images is a tedious task. We describe and evaluate a fully automated method, based on a convolutional neural network, for simultaneously detecting PFs and CVs in a single stained section. Trained on scans of hematoxylin and eosin-stained liver tissue, the detector performed well with an F1 score of 0.81 compared to annotation by a human expert. It does, however, not generalize well to previously unseen scans of steatotic liver tissue with an F1 score of 0.59. Automated PF and CV detection eliminates the bottleneck of manual annotation for subsequent automated analyses, as illustrated by two proof-of-concept applications: We computed lobulus sizes based on the detected PF and CV positions, where results agreed with published lobulus sizes. Moreover, we demonstrate the feasibility of zonated quantification of biomarkers detected in different stainings based on lobuli and zones obtained from the detected PF and CV positions. A negative control (hematoxylin and eosin) showed the expected homogeneity, a positive control (glutamine synthetase) was quantified to be strictly pericentral, and a plausible zonation for a heterogeneous F4/80 staining was obtained. Automated detection of PFs and CVs is one building block for automatically quantifying physiologically relevant heterogeneity of liver tissue biomarkers. Perspectively, a more robust and automated assessment of zonation from whole-slide images will be valuable for parameterizing spatially resolved models of liver metabolism and to provide diagnostic information.

Myostatin Knockout Regulates Bile Acid Metabolism by Promoting Bile Acid Synthesis in Cattle

Myostatin (MSTN) is a major negative regulator of skeletal muscle mass and causes a variety of metabolic changes. However, the effect of MSTN knockout on bile acid metabolism has rarely been reported. In this study, the physiological and biochemical alterations of serum in MSTN^+/- and wild type (WT) cattle were investigated. There were no significant changes in liver and kidney biochemical indexes. However, compared with the WT cattle, lactate dehydrogenase, total bile acid (TBA), cholesterol, and high-density lipoprotein (HDL) in the MSTN^+/- cattle were significantly increased, and glucose, low-density lipoprotein (LDL), and triglycerides (TG) were significantly decreased, indicating that MSTN knockout affected glucose and lipid metabolism and total bile acids content. Targeted metabolomic analysis of the bile acids and their derivatives was performed on serum samples and found that bile acids were significantly increased in the MSTN^+/- cattle compared with the WT cattle. As the only bile acid synthesis organ in the body, we performed metabolomic analysis on the liver to study the effect of MSTN knockout on hepatic metabolism. Metabolic pathway enrichment analysis of differential metabolites showed significant enrichment of the primary bile acid biosynthesis and bile secretion pathway in the MSTN^+/- cattle. Targeted metabolomics data further showed that MSTN knockout significantly increased bile acid content in the liver, which may have resulted from enhanced bile acid synthesis due to the expression of bile acid synthesis genes, cholesterol 7 alpha-hydroxylase (CYP7A1) and sterol 27-hydroxylase (CYP27A1), and upregulation in the liver of the MSTN^+/- cattle. These results indicate that MSTN knockout does not adversely affect bovine fitness but regulates bile acid metabolism via enhanced bile acid synthesis. This further suggests a role of MSTN in regulating metabolism.

Quantification of nematic cell polarity in three-dimensional tissues

How epithelial cells coordinate their polarity to form functional tissues is an open question in cell biology. Here, we characterize a unique type of polarity found in liver tissue, nematic cell polarity, which is different from vectorial cell polarity in simple, sheet-like epithelia. We propose a conceptual and algorithmic framework to characterize complex patterns of polarity proteins on the surface of a cell in terms of a multipole expansion. To rigorously quantify previously observed tissue-level patterns of nematic cell polarity (Morales-Navarrete et al., eLife 2019), we introduce the concept of co-orientational order parameters, which generalize the known biaxial order parameters of the theory of liquid crystals. Applying these concepts to three-dimensional reconstructions of single cells from high-resolution imaging data of mouse liver tissue, we show that the axes of nematic cell polarity of hepatocytes exhibit local coordination and are aligned with the biaxially anisotropic sinusoidal network for blood transport. Our study characterizes liver tissue as a biological example of a biaxial liquid crystal. The general methodology developed here could be applied to other tissues and in-vitro organoids.