Influences of simulated gastrointestinal environment on physicochemical properties of gold nanoparticles and their implications on intestinal epithelial permeability

Gold nanoparticles (Au NPs) hold great promise in food, industrial and biomedical applications due to their unique physicochemical properties. However, influences of the gastrointestinal tract (GIT), a likely route for Au NPs administration, on the physicochemical properties of Au NPs has been rarely evaluated. Here, we investigated the influence of GIT fluids on the physicochemical properties of Au NPs (5, 50, and 100?nm) and their implications on intestinal epithelial permeability in vitro. Au NPs aggregated in fasted gastric fluids and generated hydroxyl radicals in the presence of H₂O₂. Cell studies showed that GIT fluids incubation of Au NPs affected the cellular uptake of Au NPs but did not induce cytotoxicity or disturb the intestinal epithelial permeability.     

不同年龄阿尔茨海默病患者脑核团ADC值与年龄的相关性

目的 探讨不同年龄阿尔茨海默病（AD）患者ADC值与年龄的相关性。方法 选取30例AD患者（AD组）和年龄与之相匹配的30名志愿者（对照组），按年龄段各分为6个亚组[55~59岁（n=3）、60~64岁（n=4）、65~70岁（n=9）、71~74岁（n=5）、75~80岁（n=6）、>80岁（n=3）]，测量双侧海马、红核、尾状核、杏仁体、壳核ADC值，并进行配对t检验、独立样本t检验、单因素方差分析及Pearson相关分析。结果 AD组红核左、右侧ADC值有统计学差异（P=0.022）。AD组不同年龄亚组右侧海马、双侧尾状核、右侧壳核ADC值差异有统计学意义（P均<0.05）；2组不同年龄亚组双侧海马、壳核、尾状核ADC值差异有统计学意义（P均<0.05）。AD组右侧海马（r=0.615，P<0.001）、右侧壳核（r=0.653，P=0.001）及双侧尾状核（左侧：r=0.397，P=0.030；右侧：r=0.429，P=0.020）ADC值与年龄呈正相关。结论 AD患者右侧海马和壳核、双侧尾状核ADC值随年龄增加而增大。ADC值可为临床预测和早期诊断AD脑内右侧海马和壳核、双侧尾状核神经退行性病变提供参考。     

Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.     

<i>Sinomenium</i> Inhibits the Viability of Hepatoma Carcinoma Cells through Activating IFNA2

Hepatocellular carcinoma (HCC) ranks the sixth place of most common cancers. Meanwhile, it is the tertiary mortality cause of cancer. There is no effective therapeutic method to prevent and treat the liver cancer. Sinomenine is a kind of Chinese traditional medicine herbal, it is reported that it can inhibit the viability of several cancer cells. The study is to explore whether sinomenine is also able to inhibit the cell viability of HCC and its potential mechanism. The IC50 of sinomenine in BEL-7402 cells was 5.351 mmol/L, and the IC50 of sinomenine in SMMC-7721 cells was 6.204 mmol/L. The gene expression results showed the relative expression of FGF2, CCND2, DCN, F3, MMP7, NRG1, HMGB1, TRIM29, HAS2, EHF, CTGF, PLK2 were down-regulated, and the relative expression of VEGF A, CITED2, NUPR1, DDX58, IRF9, NAMPT, MMP1, NDRG1, HMGA2, PPARGC1A, IFIT2, PARP9, HEY1, LOX, ETV1, ISG15, BACH, CYLD were up-regulated. Moreover, the IPA analysis results suggested that IFIT3, IFIT1, OAS1, MX1, IRF9, IFI6, IFITM1, ISG15 were up-regulated in BEL-7402 cells treated with sinomenine by activating IFNA2. The findings presented in this study may provide a promising method for the prevention and treatment of liver cancer.