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.     

Can adiponectin have an additional effect on the regulation of food intake by inducing gastric motor changes?

The regulation of food intake is a complex mechanism, and the hypothalamus is the main central structure implicated. In particular, the arcuate nucleus appears to be the most critical area in the integration of multiple peripheral signals.Among these signals, those originating from the white adipose tissue and the gastrointestinal tract are known to be involved in the regulation of food intake.The present paper focuses on adiponectin, an adipokine secreted by white adipose tissue, which is reported to have a role in the control of feeding by acting centrally. The recent observation that adiponectin is also able to influence gastric motility raises the question of whether this action represents an additional peripheral mechanism that concurs with the central effects of the hormone on food intake. This possibility, which represents an emerging aspect correlating the central and peripheral effects of adiponectin in the hunger-satiety cycle, is discussed in the present paper.     

玳玳果黄酮降脂提取物体内组织分布规律及特征研究

目的：建立UPLC-MS/MS分析方法同时测定玳玳果黄酮降脂提取物效应组分新橙皮苷和柚皮苷在大鼠10种脏器组织中含量，分布规律及特征。方法：采用UPLC-MS/MS技术建立提取物效应组分新橙皮苷及柚皮苷在大鼠心、肝、脾、肺、肾、脑、胃、小肠、脂质、肌肉组织中的定量分析方法；大鼠给药后分别于0.33，0.67，1，4，8 h的5个时间点，分别摘取以上10种脏器组织，测定脏器组织及血液中效应组分的质量浓度，采用DAS（V 2.0）药动学软件对各样本的药物浓度-时间数据进行房室拟合，并计算不同组织效应组分的药-时曲线下面积（AUC）及平均滞留时间（MRT）。结果：所建立的UPLC-MS/MS定量分析方法具备良好的专属性、标准曲线及线性范围良好、方法准确度与精密度、定量下限均符合有关规定；玳玳果黄酮降脂提取物效应组分在血液中的分布符合一室模型，除肾脏及脑组织外，其余脏器中提取物效应组分的房室特征多为静脉注射的二室模型，柚皮苷在肾脏中的拟合结果为非静脉注射的二室模型，新橙皮苷在脑组织拟合结果为静脉注射的三室模型，给药后8 h各组织中效应组分新橙皮苷及柚皮苷AUC值大小顺序均为小肠 > 胃 > 肾 > 脂质 ≈ 脾脏 > 肺 > 肌肉 > 肝 > 心 > 脑，效应组分在各脏器中均无明显蓄积；效应组分在血液、肾脏、肝脏中的滞留时间较长，MRT均大于2 h，脂质最短，MRT不足1 h；各脏器中新橙皮苷的药-时曲线下面积约是柚皮苷的3倍，而心、肝、肾中则是3.5，2.1和3.4倍。结论：玳玳果黄酮降脂提取物效应组分在大鼠组织中分布迅速，达峰时间早于血液；效应组分在肠道内消除缓慢，给药8 h后在各脏器中的含量均显著下降且无特异的蓄积部位。研究结果揭示玳玳果黄酮降脂提取物效应组分在大鼠体内的分布特征及规律，为进一步理解玳玳果黄酮降脂提取物在体内的作用靶点及机制奠定了基础。     

动物瘢痕模型的相关研究进展

皮肤损伤后的异常愈合会导致病理性瘢痕的产生。病理性瘢痕的出现不仅影响美观,严重时还会造成心理和生理功能障碍。病理性瘢痕的机制研究对于瘢痕治疗有极为重要的意义。其中,动物瘢痕模型是目前研究病理性瘢痕的重要模型手段之一。理想的动物瘢痕模型应该在组织学、细胞学等层面尽可能接近于人类的病理性瘢痕。该文分别从传统技术动物瘢痕中的啮齿类动物模型、兔耳模型和猪模型,以及新技术动物瘢痕模型这两个方面,结合近年来在瘢痕领域应用较多的研究,进行了相应系统的阐述。     

Intraoperative cerebral blood flow monitoring in neurosurgery: A review of contemporary technologies and emerging perspectives

Intraoperative monitoring of cerebral blood flow (CBF) has become an invaluable adjunct to vascular and oncological neurosurgery, reducing the risk of postoperative morbidity and mortality. Several technologies have been developed during the last two decades, including laser-based techniques, videomicroscopy, intraoperative MRI, indocyanine green angiography, and thermography. Although these technologies have been thoroughly studied and clinically applied outside the operative room, current practice lacks an optimal technology that perfectly fits the workflow within the neurosurgical operative room. The different available technologies have specific strengths but suffer several drawbacks, mainly including limited spatial and/or temporal resolution. An optimal CBF monitoring technology should meet particular criteria for intraoperative use: excellent spatial and temporal resolution, integration in the operative workflow, real-time quantitative monitoring, ease of use, and non-contact technique. We here review the main contemporary technologies for intraoperative CBF monitoring and their current and potential future applications in neurosurgery.