Cornus officinalis vinegar reduces body weight and attenuates hepatic steatosis in mouse model of nonalcoholic fatty liver disease

This study aimed to determine the main bioactive components of Cornus officinalis vinegar (COV) and assess the effects of COV on the body weight (BW) and hepatic steatosis in a nonalcoholic fatty liver disease (NAFLD) mouse model. Seven-week-old KM female mice were divided into five treatment groups: (1) Normal control (NC) group, (2) high fat diet (HFD) group, (3) low concentration treatment group (3.5% COV), (4) medium concentration treatment group (5.0% COV), and (5) high concentration treatment group (6.5% COV). Mice in the NC group were fed with a normal chow diet, and those in the other four groups were fed with a HFD known for causing obesity for 10 weeks. Then, mice in the three COV treatment groups were orally administered with COV once a day for 6 weeks. Results showed that the contents of loganin and morroniside in COV reached 16.82 and 51.17 µg/ml, respectively, and COV also contained multiple organic acids. COV significantly reduced BW, abdominal fat weight, liver weight, and the levels of glucose, triglyceride, and low-density lipoprotein cholesterol of serum and increased the levels of high-density lipoprotein cholesterol of serum (p < 0.05). COV also improved the liver function and anti-oxidant activity of liver (p < 0.05). COV treatments increased the interleukin-10 expression and reduced the tumor necrosis factor-α expression in the liver tissue of NAFLD mice (p < 0.05). Histopathological observation revealed that COV suppressed hepatic lipid accumulation and steatosis. The results suggest that COV may contribute to the alleviation of NAFLD and obesity.     

谷氨酰胺代谢在原发性肝癌发生发展及治疗中的研究进展

肝癌是我国高发并且危害性极大的恶性肿瘤，其具有高死亡率并起病隐匿等特点。目前，肝癌治疗主要是以靶向药物，手术和放化疗为主，容易出现复发率高、耐药性强等现象。本文以谷氨酰胺代谢为切入点，对目前研究较多的肝癌相关的谷氨酰胺代谢酶及相关基因分别予以综述，以期为肝癌的发病机制及药物治疗提供开放性新思路。     

The Age-Sensitive Efficacy of Calorie Restriction on Mitochondrial Biogenesis and mtDNA Damage in Rat Liver

Calorie restriction (CR) is the most efficacious treatment to delay the onset of age-related changes such as mitochondrial dysfunction. However, the sensitivity of mitochondrial markers to CR and the age-related boundaries of CR efficacy are not fully elucidated. We used liver samples from ad libitum-fed (AL) rats divided in: 18-month-old (AL-18), 28-month-old (AL-28), and 32-month-old (AL-32) groups, and from CR-treated (CR) 28-month-old (CR-28) and 32-month-old (CR-32) counterparts to assay the effect of CR on several mitochondrial markers. The age-related decreases in citrate synthase activity, in TFAM, MFN2, and DRP1 protein amounts and in the mtDNA content in the AL-28 group were prevented in CR-28 counterparts. Accordingly, CR reduced oxidative mtDNA damage assessed through the incidence of oxidized purines at specific mtDNA regions in CR-28 animals. These findings support the anti-aging effect of CR up to 28 months. Conversely, the protein amounts of LonP1, Cyt c, OGG1, and APE1 and the 4.8 Kb mtDNA deletion content were not affected in CR-28 rats. The absence of significant differences between the AL-32 values and the CR-32 counterparts suggests an age-related boundary of CR efficacy at this age. However, this only partially curtails the CR benefits in counteracting the generalized aging decline and the related mitochondrial involvement.     

Idiosyncratic Drug-Induced Liver Injury: Mechanistic and Clinical Challenges

Idiosyncratic drug-induced liver injury (IDILI) remains a significant problem for patients and drug development. The idiosyncratic nature of IDILI makes mechanistic studies difficult, and little is known of its pathogenesis for certain. Circumstantial evidence suggests that most, but not all, IDILI is caused by reactive metabolites of drugs that are bioactivated by cytochromes P450 and other enzymes in the liver. Additionally, there is overwhelming evidence that most IDILI is mediated by the adaptive immune system; one example being the association of IDILI caused by specific drugs with specific human leukocyte antigen (HLA) haplotypes, and this may in part explain the idiosyncratic nature of these reactions. The T cell receptor repertoire likely also contributes to the idiosyncratic nature. Although most of the liver injury is likely mediated by the adaptive immune system, specifically cytotoxic CD8+ T cells, adaptive immune activation first requires an innate immune response to activate antigen presenting cells and produce cytokines required for T cell proliferation. This innate response is likely caused by either a reactive metabolite or some form of cell stress that is clinically silent but not idiosyncratic. If this is true it would make it possible to study the early steps in the immune response that in some patients can lead to IDILI. Other hypotheses have been proposed, such as mitochondrial injury, inhibition of the bile salt export pump, unfolded protein response, and oxidative stress although, in most cases, it is likely that they are also involved in the initiation of an immune response rather than representing a completely separate mechanism. Using the clinical manifestations of liver injury from a number of examples of IDILI-associated drugs, this review aims to summarize and illustrate these mechanistic hypotheses.     

Delivery of cisplatin by folic acid-targeted liposomal nanoparticles into liver cancer cell line

This study aimed to prepare cisplatin-loaded PEGylated liposomal nanoparticles targeted with folic acid and evaluate their efficacy on liver cancer cell line PLC/PRF/5 (Alexander hepatoma cell line). Nanoparticles were prepared by reverse phase evaporation technique and characterized by dynamic light scattering, scanning electron microscopy, transmission electron microscopy, inductively coupled plasma optical emission spectrometry, Fourier transform infrared spectroscopy, and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide techniques. Nanoscale particles with appropriate drug encapsulation efficiency (13%) were prepared. Cytotoxicity results indicated that the superior potency of targeted cisplatin-loaded nanoparticles compared to the nontargeted counterpart with 23% more cytotoxicity. Findings of this study confirmed the potency of targeted PEGylated liposomal nanoparticles.     

结合注意力的3D卷积网络脑胶质瘤分割算法

为了提升脑胶质瘤分割精度，提出一种结合注意力机制的3D卷积神经网络算法。输入3个不同尺度的图像块，经过9个卷积层和1个分类层后得到3个不同的分类结果，将分类结果与注意力学习到的权重相乘并逐体素相加得到输出。此外该算法采用了一种混合Dice损失函数与Focal损失函数的超参数损失函数。实验表明，该算法的Dice系数在整体区域、核心区域以及增强区域分别达到了95.31%、80.12%、82.25%。与已有的一种脑胶质瘤分割算法deepmedic相比，整体区域、核心区域以及增强区域的Dice系数分别提升了3%、2%、6%。在脑胶质瘤分割方面，具有重要的临床意义。     

基于卷积神经网络的单目深度估计

针对利用深度学习方法对街道图像进行深度估计，提出采用语义分割的方法解决深度图出现边界模糊等问题；估计深度通过左右视角图生成视差图进行无监督的训练。在网络模型中添加语义分割层，采取多个空洞卷积并行的结构增加感受野，同时减少了图像下采样的次数，降低了由于下采样带来的信息损失，使得的结果更加准确。这也是在深度估计中首次与空洞卷积相结合增加准确率。通过对KITTI街道数据集进行训练，与现有结果相比，除了增加检测准确性，降低错误率之外，使得效果图中的物体更加清晰，并且在效果图中还保留了一些原模型中被忽视掉的细节信息，将原始图像更加完整的表现出来。     

Pro-Resolving Lipid Mediator Resolvin E1 Mitigates the Progress of Diethylnitrosamine-Induced Liver Fibrosis in Sprague-Dawley Rats by Attenuating Fibrogenesis and Restricting Proliferation

Liver fibrosis is a complex process associated to most types of chronic liver disease, which is characterized by a disturbance of hepatic tissue architecture and the excessive accumulation of extracellular matrix. Resolvin E1 (RvE1) is a representative member of the eicosapentaenoic omega-3 lipid derivatives, and is a drug candidate of the growing family of endogenous resolvins. Considering the aforementioned, the main objective of this study was to analyze the hepatoprotective effect of RvE1 in a rat model of liver fibrosis. Male Sprague-Dawley rats received diethylnitrosamine (DEN, 70 mg/mg body weight intraperitoneally (i.p)) as an inductor of liver fibrosis once weekly and RvE1(100 ng/body weight i.p) twice weekly for four weeks. RvE1 suppressed the alterations induced by DEN, normalizing the levels of alanine aminotransferase (ALT), albumin, and lactate dehydrogenase (LDH), and ameliorated DEN injury by decreasing the architecture distortion, inflammatory infiltration, necrotic areas, and microsteatosis. RvE1 also limited DEN-induced proliferation through a decrease in Ki67-positive cells and cyclin D1 protein expression, which is related to an increase of the levels of cleaved caspase-3. Interestingly, we found that RvE1 promotes higher nuclear translocation of nuclear factor κB (NF-κB)p65 than DEN. RvE1 also increased the levels of nuclear the nuclear factor erythroid 2–related factor 2 (Nrf2), but with no antioxidant effect, measured as an increase in glutathione disulfide (GSSG) and a decrease in the ratio of glutathione (GSH)/GSSG. Taken together, these results suggest that RvE1 modulates the fibrogenesis, steatosis, and cell proliferation in a model of DEN induced fibrosis.     

基于机器视觉的运煤车车号识别技术研究

在铁路运煤装车过程中为了快速、准确地识别车号,提出一种基于机器视觉的运煤车车号识别技术。将连通区域提取与投影分割法结合,实现车号的粗定位、细分割,并对图像中的断裂字符进行二次分割,构建了基于BP神经网络的分类模型进行车号识别,提升了煤炭装车的效率和精度。     

R2D2: A scalable deep learning toolkit for medical imaging segmentation

Deep learning has gained a significant popularity in recent years thanks to its tremendous success across a wide range of relevant fields of applications, including medical image analysis domain in particular. Although convolutional neural networks (CNNs) based medical applications have been providing powerful solutions and revolutionizing medicine, efficiently training of CNNs models is a tedious and challenging task. It is a computationally intensive process taking long time and rare system resources, which represents a significant hindrance to scientific research progress. In order to address this challenge, we propose in this article, R2D2, a scalable intuitive deep learning toolkit for medical imaging semantic segmentation. To the best of our knowledge, the present work is the first that aims to tackle this issue by offering a novel distributed versions of two well-known and widely used CNN segmentation architectures [ie, fully convolutional network (FCN) and U-Net]. We introduce the design and the core building blocks of R2D2. We further present and analyze its experimental evaluation results on two different concrete medical imaging segmentation use cases. R2D2 achieves up to 17.5× and 10.4× speedup than single-node based training of U-Net and FCN, respectively, with a negligible, though still unexpected segmentation accuracy loss. R2D2 offers not only an empirical evidence and investigates in-depth the latest published works but also it facilitates and significantly reduces the effort required by researchers to quickly prototype and easily discover cutting-edge CNN configurations and architectures.