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Nonalcoholic steatohepatitis (NASH) is a disease entity with an increasing incidence, with involvement of several metabolic pathways. Various organs, including the liver, kidneys, and the vasculature, are damaged in NASH, indicating the urgent need to develop a standard therapy. Therefore, this study was conducted to investigate the effects of drugs targeting various metabolic pathways and their combinations on a high-fat diet (HFD)-induced NASH medaka model.To investigate the effects of drugs on vascular structures, the NASH animal model was developed using the fli::GFP transgenic medaka fed with HFD at 20 mg/fish daily. The physiological changes, histological changes in the liver, vascular structures in the fin, and serum biochemical markers were evaluated in a time-dependent manner after treatment with selective peroxisome proliferator-activated receptor α modulator (pemafibrate), statin (pitavastatin), sodium-glucose cotransporter 2 inhibitor (tofogliflozin), and their combinations. Furthermore, to determine the mechanisms underlying the effects, whole transcriptome sequencing was conducted using medaka liver samples.Histological analyses revealed significant suppression of fat accumulation and fibrotic changes in the liver after treatment with drugs and their combinations. The expression levels of steatosis- and fibrosis-related genes were modified by the treatments. Moreover, the HFD-induced vascular damages in the fin exhibited milder changes after treatment with the drugs.The effects of treating various metabolic pathways on the medaka body, liver, and vascular structures of the NASH medaka model were evidenced. Moreover, to our knowledge, this study is the first to report whole genome sequence and gene expression evaluation of medaka livers, which could be helpful in clarifying the molecular mechanisms of drugs.

The number of patients with non-alcoholic steatohepatitis (NASH) and inflammatory bowel disease (IBD) is increasing. This study elucidates the effect of both NASH and IBD on hepatocellular carcinoma (HCC) using a mouse model combining NASH and IBD. The melanocortin 4 receptor-deficient (Mc4r-KO) mice were divided into four groups with or without a high-fat diet (HFD) and with or without dextran sulfate sodium (DSS) to induce colitis, and the differences in liver damage and occurrence of HCC were analyzed. In the HFD + DSS group, the body weight, liver weight/body weight ratio, and serum levels of albumin and alanine aminotransferase were significantly lower than those in the HFD group. We further found that steatosis was significantly lower and lobular inflammation was significantly higher in the HFD + DSS group than those in the HFD group, and that individual steatosis and lobular inflammation state in the HFD + DSS mice varied. We detected HCC only in the HFD + DSS group, and mice with severe steatosis and mild colitis were found to be at high risk of HCC. Presently, the prediction of HCC is very difficult. In some cases, severe colitis reverses the fat accumulation due to appetite loss. Our findings clearly showed that severe steatohepatitis and mild colitis are simultaneously essential for the occurrence of HCC in patients with NASH and IBD.

Cyclin D1 binding protein 1 (CCNDBP1) is considered a tumor suppressor, and when expressed in tumor cells, CCNDBP1 can contribute to the viability of cancer cells by rescuing these cells from chemotherapy-induced DNA damage. Therefore, this study focused on investigating the function of CCNDBP1, which is directly related to the survival of cancer cells by escaping DNA damage and chemoresistance. Hepatocellular carcinoma (HCC) cells and tissues obtained from Ccndbp1 knockout mice were used for the in vitro and in vivo examination of the molecular mechanisms of CCNDBP1 associated with the recovery of cells from DNA damage. Subsequently, gene and protein expression changes associated with the upregulation, downregulation, and irradiation of CCNDBP1 were assessed. The overexpression of CCNDBP1 in HCC cells stimulated cell growth and showed resistance to X-ray-induced DNA damage. Gene expression analysis of CCNDBP1-overexpressed cells and Ccndbp1 knockout mice revealed that Ccndbp1 activated the Atm–Chk2 pathway through the inhibition of Ezh2 expression, accounting for resistance to DNA damage. Our study demonstrated that by inhibiting EZH2, CCNDBP1 contributed to the activation of the ATM–CHK2 pathway to alleviate DNA damage, leading to chemoresistance.

The etiology of non-alcoholic fatty liver disease (NAFLD) consists of various factors, including neural signal pathways. However, the molecular mechanisms of the autonomic neural signals influencing NAFLD progression have not been elucidated. Therefore, we examined the involvement of the gut-liver neural axis in NAFLD development and tested the therapeutic effect of modulation of this axis in this study. To test the contribution of the gut-liver neural axis, we examined NAFLD progression with respect to body weight, hepatic steatosis, fibrosis, intestinal tight junction, microbiota and short-chain fatty acids in NAFLD models of choline-deficient defined L-amino-acid and high-fat diet-fed mice with or without blockades of autonomic nerves from the liver. Blockade of the neural signal from the liver to the gut in these NAFLD mice models ameliorated the progression of liver weight, hepatic steatosis and fibrosis by modulating serotonin expression in the small intestine. It was related to the severity of the liver pathology, the tight junction protein expression, microbiota diversity and short-chain fatty acids. These effects were reproduced by administrating serotonin antagonist, which ameliorated the NAFLD progression in the NAFLD mice models. Our study demonstrated that the gut-liver neural axis is involved in the etiologies of NAFLD progression and that serotonin expression through this signaling network is the key factor of this axis. Therefore, modulation of the gut-liver neural axis and serotonin antagonist ameliorates fatty and fibrotic changes in non-alcoholic fatty liver, and can be a potential therapeutic target of NAFLD. This article has an associated First Person interview with the first author of the paper., Summary: The gut-liver neural axis is involved in NAFLD progression and serotonin is the key factor in allowing this pathway to change the expression of tight junction molecules, microbiota diversity and short-chain fatty acids.

Chronic intestinal pseudo-obstruction (CIPO) is a severe and refractory intestinal motility disorder. However, due to its rarity and difficult histological investigation, its pathophysiology has not been characterized. Therefore, in this study, we aimed to determine the role of esophageal high-resolution manometry (HRM) in CIPO and the histological and clinical characteristics of the disease. Patients with CIPO were analyzed for clinical characteristics; histological findings; and clinical courses after therapeutic intervention. In addition, HRM was performed to determine the esophageal involvement. Eleven patients were diagnosed with CIPO, and five required the long period of parenteral nutrition showing impaired esophageal motility including achalasia and absent contractility diagnosed with HRM. The four of these five cases showed acute onset of the CIPO following the triggering events of pregnancy, appendicitis, and surgery. In contrast, other six patients with normal or Jackhammer esophagus on HRM had moderate severity of CIPO with gradual onset. The histological analyses revealed that the loss of the intestinal neural ganglion cells and layers by inflammation, destruction, and atrophy are related to the severity of the clinical course of the disease and esophageal HRM findings of achalasia and absent contractility. HRM may be useful to diagnose the severity of the clinical course and to determine the therapeutic options for CIPO.

Radar technology is one of key elements integrated in autonomous driving systems and advanced driver assistance systems (ADAS). Development of ADAS requires extensive validation of the involved radar systems, and real test driving for the validation can be costly. Although promising as a replacement for real test driving, virtual test driving to simulate radar systems in detail using physics-based electromagnetic simulation techniques is time consuming. This paper describes a data-driven approach to reduce the computation time for such simulations. As an initial attempt to introduce a machine learning model to simulate electromagnetic reflection property of vehicles based on their shapes, convolutional neural networks (CNN) whose input and output are the vehicle shape and its radar cross-section (RCS), respectively, are trained. The correlation coefficient between the estimated and ground truth RCSs can be as high as around 0.8 while the computation speed is significantly increased with a speed-up of approximately 50 times with respect to the ray-tracing method.

We propose RoadNetGAN, a road network generation method as an extension to NetGAN, a generative model that can generate graphs similar to real-world networks with the acquisition of similarity measure through learning. Our main contribution is twofold. Firstly, we added displacement attributes to the random walks to generate not only the sequence but also the spatial position of nodes as intersections within a road network to be generated, which increases the diversity of generated road network patterns including the shape of the city blocks. Secondly, we make the generator and discriminator neural networks conditional. This allows for learning of the specification of the initial node of random walks over a graph, which is especially important for interactive road network generation that is mostly used in the applications for urban planning of road networks. We demonstrate that the proposed method can generate road networks that mimic the real road networks with the desired similarity.

BACKGROUND The correlation of the growth hormone (GH) and insulin-like growth factor-1 (IGF-1) with non-alcoholic fatty liver disease (NAFLD) has been reported in epidemiological studies. However, the mechanisms of molecular and inter-organ systems that render these factors to influence on NAFLD have not been elucidated. In this study, we examined the induction of ghrelin which is the GH-releasing hormone and IGF-1, and involvement of autonomic neural circuits, in the pathogenesis of NAFLD. METHODS The expression of gastric and hypothalamic ghrelin, neural activation in the brain, and serum IGF-1 were examined in NAFLD models of choline-deficient defined l-amino-acid diet-fed, melanocortin 4 receptor knockout mice, and partial hepatectomy mice with or without the blockades of autonomic nerves to test the contribution of neural circuits connecting the brain, liver, and stomach. KEY RESULTS The fatty changes in the liver increased the expression of gastric ghrelin through the autonomic pathways which sends the neural signals to the arcuate nucleus in the hypothalamus through the afferent vagal nerve which reached the pituitary gland to release GH and then stimulate the IGF-1 release from the liver. In addition, high levels of ghrelin expression in the arcuate nucleus were correlated with NAFLD progression regardless of the circuits. CONCLUSIONS Our study demonstrated that the fatty liver stimulates the autonomic nervous signal circuits which suppress the progression of the disease by activating the gastric ghrelin expression, the neural signal transduction in the brain, and the release of IGF-1 from the liver.

During the development of the advanced driver assistance systems equipped with millimeter-wave radar and a camera, testing under actual driving conditions is extremely expensive. Therefore, it is necessary to develop sensor simulation methods for virtual assessment of such systems. In the present paper, we propose a novel method that reproduces radio wave propagation and reflection in the millimeter-wave band. There are two key points regarding the proposed method. One is that we perform rapid 1-pass algorithm by ray tracing using a GPU, which enables a huge number of parallel computations. Second, we perform highly accurate calculations (i.e., influence of polarization) by considering the wave characteristics in ray tracing. In experiments, we evaluate the correlation between measured experimental data and the simulation results for the vehicle. We show that the correlation coefficient for the proposed method is approximately twice that for the conventional method. We also show that the proposed method is approximately 10 times faster than the conventional method.

Radar technology is one of the key technologies used in automotive scene recognition for autonomous driving systems and advanced driver assistance systems (ADAS). ADAS development requires the exhaustive validation of participating radar systems, and validation through actual test driving can be expensive. Although promising as a replacement for real test driving, virtual test driving is time-consuming owing to the fact that it simulates radar systems in detail, employing physics-based electromagnetic simulation techniques. This paper describes a hybrid physics-based and data-driven approach to reduce the computation time required for such simulations. The radar cross-section (RCS) of a vehicle is chosen as a target result obtained through electromagnetic simulations. The data-driven model is implemented with a cascade of two convolutional neural networks (CNNs) which are trained using ground truth data calculated with a physics-based ray-tracing method. The ray-tracing method is employed for generating both the training data and a part of the input to one of the CNNs. The correlation coefficient between the estimated and ground truth RCSs can be approximately 0.8 while the computation time is lower than 120 ms.

A 76-year-old female was referred to our hospital because of liver dysfunction. Abdominal contrasted computed tomography (CT) revealed a tumor of 7.5cm in the hepatic hilar area. Based on the biopsy, the tumor was diagnosed by as combined hepatocellular-cholangiocellular carcinoma (with stem-cell features). The tumor was considered unresectable;hence, the patient underwent transcatheter arterial chemoembolization (TACE). However, a CT scan revealed the treatment to be ineffective. Subsequently, systemic gemcitabine (GEM) chemotherapy was administered and tumor shrinkage was observed with reperfusion of the umbilical portion of the left portal vein. The patient's condition is currently stable 17 months after diagnosis, with no tumor regrowth on account of repeated TACE and GEM therapy. The present case of unresectable combined hepatocellular-cholangiocellular carcinoma was successfully treated using TACE and systemic GEM chemotherapy.

Background and aim Awareness of eosinophilic esophagitis (EoE) has gradually increased in Japan, therefore the characteristics of this disease in the Japanese patient population need to be elucidated. This study aimed to investigate the features of EoE in the Japanese population. Methods During a 2-year period, all gastrointestinal endoscopies were performed with maximum attention being paid to identify EoE through endoscopic findings. Clinical features and findings were analyzed among this population. Results Among a total of 8589 patients (general gastrointestinal endoscopy, performed for evaluation of symptoms or disease follow-up: 3669; medical check-up endoscopy, routinely performed in asymptomatic patients: 4920), 17 patients (0.20%) were diagnosed with esophageal eosinophilia (mean age ± standard deviation: 44±11.9 years; 1 female). Only 6 patients with esophageal eosinophilia were diagnosed by general gastrointestinal endoscopy; among them, 3 patients had dysphagia and 3 were asymptomatic. The remaining 11 patients were diagnosed by medical check-up endoscopy. All patients were treated with a proton pump inhibitor (PPI); 5 were diagnosed with EoE and 12 with PPI responsive esophageal eosinophilia. Chronological endoscopy analysis showed that EoE findings could be observed for a mean of 6.1 years prior to diagnosis, and the disease did not significantly progress in severity. Conclusions Most Japanese patients with EoE have mild and slowly progressing disease, which can be diagnosed when close attention is paid to the endoscopic findings. Medical check-up endoscopy in Japan could be a great opportunity for the early diagnosis of EoE.

We describe a 52-year-old male who underwent endoscopic retrograde biliary drainage for acute cholangitis associated with common bile duct stones. Endoscopic papillary balloon dilatation was performed, and the stones were removed using a balloon catheter. Simultaneously, we initiated edoxaban for portal vein thrombosis. Approximately one month later, he visited our hospital complaining of tarry stools and dizziness. Contrast-enhanced computed tomography revealed a pseudoaneurysm in the hepatic artery (A7), and he was diagnosed with hemobilia from bile duct perforation associated with the hepatic arterial pseudoaneurysm. We performed an emergent transcatheter arterial embolization. Notably, re-bleeding has not occurred to date. Hepatic arterial pseudoaneurysms can occur after acute cholangitis;therefore, careful follow-up is essential.

The optimum retreatment strategy for chronic hepatitis C virus (HCV) patients who failed directly-acting antiviral agents (DAA)-based therapy is unknown. We herein report the outcomes of an HCV genotype (GT) 2a-infected patient with virologic failure following treatment with sofosbuvir plus ribavirin (SOF+RBV) who was successfully retreated with ombitasvir/paritaprevir/ritonavir plus ribavirin (OBV/PTV/r+RBV).

Despite a large body of research on response properties of neurons in the inferior temporal (IT) cortex, studies to date have not yet produced quantitative feature descriptions that can predict responses to arbitrary objects. This deficit in the research prevents a thorough understanding of object representation in the IT cortex. Here we propose a fragment-based approach for finding quantitative feature descriptions of face neurons in the IT cortex. The development of the proposed method was driven by the assumption that it is possible to recover features from a set of natural image fragments if the set is sufficiently large. To find the feature from the set, we compared object responses predicted from each fragment and responses of neurons to these objects, and search for the fragment that revealed the highest correlation with neural object responses. Prediction of object responses of each fragment was made by normalizing Euclidian distance between the fragment and each object to 0 to 1 such that the smaller distance gives the higher value. The distance was calculated at the space where images were transformed to a local orientation space by a Gabor filter and a local max operation. The method allowed us to find features with a correlation coefficient between predicted and neural responses of 0.68 on average (number of object stimuli, 104) from among 560,000 feature candidates, reliably explaining differential responses among faces as well as a general preference for faces over to non-face objects. Furthermore, predicted responses of the resulting features to novel object images were significantly correlated with neural responses to these images. Identification of features comprising specific, moderately complex combinations of local orientations and colors enabled us to predict responses to upright and inverted faces, which provided a possible mechanism of face inversion effects. (292/300).

Anti-programmed cell death-1 therapy with microspheres is an effective treatment for metastatic liver tumors.

In order to achieve harmony in the mixed traffic, it is crucial to have autonomous vehicles behave like human drivers. This work addresses a vision-based approach toward human-like lane following behavior in complex urban environment. At first, a deep architecture is adopted to generate a set of vehicle hypotheses. Subsequently, a hybrid merging procedure is performed to jointly output the final detection results based on both the image evidence and the statistical support of vehicle hypotheses. After that, the detected vehicles are classified into six categories by Bayesian Network, i.e., leader vehicle, parking vehicle, tail-end vehicle, exiting vehicle, merging vehicle and other vehicle. With this information, a learning-based instance-level behavior-induction potential map is constructed to generate a safe as well as reasonable local path for following a predefined lane-level route. Experimental results in various typical but challenging urban traffic scenes substantiated the effectiveness of the proposed approach.