Simulated Microgravity Inhibits the Proliferation of Chang Liver Cells by Attenuation of the Major Cell Cycle Regulators and Cytoskeletal Proteins

Simulated microgravity (SMG) induced the changes in cell proliferation and cytoskeleton organization, which plays an important factor in various cellular processes. The inhibition in cell cycle progression has been considered to be one of the main causes of proliferation inhibition in cells under SMG, but their mechanisms are still not fully understood. This study aimed to evaluate the effects of SMG on the proliferative ability and cytoskeleton changes of Chang Liver Cells (CCL-13). CCL-13 cells were induced SMG by 3D clinostat for 72 h, while the control group were treated in normal gravity at the same time. The results showed that SMG reduced CCL-13 cell proliferation by an increase in the number of CCL-13 cells in G0/G1 phase. This cell cycle phase arrest of CCL-13 cells was due to a downregulation of cell cycle-related proteins, such as cyclin A1 and A2, cyclin D1, and cyclin-dependent kinase 6 (Cdk6). SMG-exposed CCL-13 cells also exhibited a downregulation of α-tubulin 3 and β-actin which induced the cytoskeleton reorganization. These results suggested that the inhibited proliferation of SMG-exposed CCL-13 cells could be associate with the attenuation of major cell cycle regulators and main cytoskeletal proteins.     

Stacked Gated Recurrent Unit Classifier with CT Images for Liver Cancer Classification

Liver cancer is one of the major diseases with increased mortality in recent years, across the globe. Manual detection of liver cancer is a tedious and laborious task due to which Computer Aided Diagnosis (CAD) models have been developed to detect the presence of liver cancer accurately and classify its stages. Besides, liver cancer segmentation outcome, using medical images, is employed in the assessment of tumor volume, further treatment plans, and response monitoring. Hence, there is a need exists to develop automated tools for liver cancer detection in a precise manner. With this motivation, the current study introduces an Intelligent Artificial Intelligence with Equilibrium Optimizer based Liver cancer Classification (IAIEO-LCC) model. The proposed IAIEO-LCC technique initially performs Median Filtering (MF)-based pre-processing and data augmentation process. Besides, Kapur’s entropy-based segmentation technique is used to identify the affected regions in liver. Moreover, VGG-19 based feature extractor and Equilibrium Optimizer (EO)-based hyperparameter tuning processes are also involved to derive the feature vectors. At last, Stacked Gated Recurrent Unit (SGRU) classifier is exploited to detect and classify the liver cancer effectively. In order to demonstrate the superiority of the proposed IAIEO-LCC technique in terms of performance, a wide range of simulations was conducted and the results were inspected under different measures. The comparison study results infer that the proposed IAIEO-LCC technique achieved an improved accuracy of 98.52%.     

32P-玻璃微球介入治疗肝细胞肝癌的临床初步应用

采用Ｓｅｌｄｉｎｇｅｒｓ穿刺法,导管超选择至肝固有动脉以远,灌注＾３２Ｐ－玻璃微球（＾３２Ｐ－ＧＭＳ）,对９７例肝细胞肝癌（ＨＣＣ）实施了９９次内照射介入治疗。结果表明,Ａ方案半年及１、２、３年生存率分别为１００％、９６．７％、５６．７％和４３．３％;Ｂ方案分别为９７．９％、９１．８％、６１．２％和５１．０％。经治后的中位生存时间为５８５天。多因素分析显示：肝功能、肿瘤大小、临床类型及＾３２Ｐ－Ｇ     

高风险肝癌经皮热消融治疗中的辅助技术

随着医疗设备的发展和技术的进步,经皮热消融已成为肝癌治疗领域不可或缺的重要手段,超声是最常用的热消融引导技术,在因多种不利因素导致常规超声显示不清肝癌病灶或病灶位于极易引起严重并发症的危险部位时,经皮热消融在肝癌治疗中的应用范围受到限制。近年来一些新的辅助技术被用于克服这些高风险或困难因素,已取得了良好疗效,扩大了热消融在肝癌治疗中的适应症。本文就近年来在超声引导下对高风险肝癌进行经皮热消融治疗时所使用的辅助技术进行综述。     

奥曲肽和垂体后叶素在救治肝硬化上消化道出血的疗效比较

目的 探讨奥曲肽和垂体后叶素在救治肝硬化上消化道出血的疗效差异。方法 选择我院2008年12月至2010年12月肝硬化上消化道出血患者90例,将上述患者随机分为2组,观察组和对照组。2组均给予基础治疗。观察组给予奥曲肽,对照组给予垂体后叶素。观察2组患者止血和不良反应发生情况。结果 观察组有效率为95.6%,对照组有效率为77.8%,2组总有效率比较,差异有统计学意义(P<0.05);观察组不良反应率与对照组比较,差异有统计学意义(P<0.05)。结论 奥曲肽治疗肝硬化上消化道出血临床效果显著,不良反应少,值得借鉴。     

Estimated exposure to hepatitis E virus through consumption of swine liver and liver sausages

A quantitative risk assessment was undertaken following the Codex Alimentarius principles in order to predict the exposure of consumers to hepatitis E virus (HEV) through food consumption. Taking into account the tropism of HEV, fresh liver and liver sausages were regarded as having a higher risk of contamination. The model entailed a hypothetical food pathway and was based on worst case scenario where the intake of contaminated food derived from a 100% HEV-infected pig population was estimated. As no data on the prevalence of infectious HEV was available, the HEV-RNA prevalence in food matrices and the seroprevalence of HEV-specific antibodies in swine were assessed and adjusted for diagnostic misclassification and sampling uncertainty. Considering a HEV prevalence of 100% in pigs and excluding further cross-contamination events, a food portion consisting of 130 gr of liver or of 32.5 gr of sausage (containing 30% of liver) yielded an estimated exposure of 8047 and 210 RNA copies (median values), respectively. These findings take into account the effect of thermal treatment on the HEV-RNA concentration of food. Due to the lack of information concerning the correlation between HEV-RNA concentration and the amount of infectious virus as well as the dose-response relationship of HEV, the calculated RNA copies do not allow direct conclusions to be drawn on the risk of infection following ingestion of these food types. The true prevalence was estimated for Switzerland and Germany, leading to an overall prevalence of HEV-RNA in food of 6.2% (90% Highest Density Intervals (HDIs): 2.5%–11.2%). In comparison with fresh liver, liver sausages showed a higher prevalence, most likely due to the presence of more than one liver within the same sausage. The true prevalence of anti-HEV IgG ranged between 59.4% (HDIs 56.5%–62.4%) and 62.6% (HDIs 58.8%–64.3%) and between 7.6% (HDIs 3.3%–13.2%) and 30.5% (HDIs 23.2%–38.2%) in pigs and wild boars, respectively. The high prevalence of antibodies support the evidence that these animals can act as reservoirs for HEV and can contribute epidemiologically to the maintenance of the virus in the surroundings. This study is a preliminary investigation and highlights the major existing gaps needed to be filled in order to enable a refined HEV risk assessment that can drive future decisions for the implementation of food safety and of control measures.