Wireless amplified NMR detector for improved visibility of image contrast in heterogeneous lesions

To demonstrate the capability of a wireless amplified NMR detector (WAND) to improve the visibility of lesion heterogeneity without the use of exogenous contrast agents, a cylindrically symmetric WAND was constructed to sensitively detect and simultaneously amplify MR signals emitted from adjacent tissues. Based on a two‐leg high‐pass birdcage coil design, this WAND could be activated by a pumping field aligned along the main field (B₀), without perturbing MR signal reception. Compared with an equivalent pair of external detectors, the WAND could achieve more than 10‐fold gain for immediately adjacent regions. Even for regions with 3.4 radius distance separation from the detector's cylindrical center, the WAND was at least 1.4 times more sensitive than an equivalent pair of surface arrays or at least twice as sensitive as a single‐sided external surface detector. When the WAND was inserted into a rat's rectum to observe adjacent tumors implanted beneath the mucosa, it could enhance the detection sensitivity of lesion regions, and thus enlarge the observable signal difference between heterogeneous tissues and clearly identify lesion boundaries as continuous lines in the intensity gradient profile. Hyperintense regions observable by the WAND existed due to higher levels of blood supply, which was indicated by a similar pattern of signal enhancement after contrast agent administration. By better observing the endogenous signal contrast, the endoluminal WAND could characterize lesions without the use of exogenous contrast agents, and thus reduce contrast‐induced toxicity.     

大黄酸-泊洛沙姆188固体分散体的制备及释药性能研究

目的:制备大黄酸固体分散体,考察其分散状态及其释药性能。方法:以水溶性聚合物泊洛沙姆188为载体,采用溶剂法制备大黄酸固体分散体,以热重、红外分析法对其进行表征,高效液相色谱法测定释药性能。结果:优选得到大黄酸:泊洛沙姆188的最佳比例为1:5。导数热重法分析表明所制备的固体分散体中不存在药物结晶;红外光谱法分析表明大黄酸与泊洛沙姆188未发生化学反应;溶出度试验结果表明其在30min内药物释放达90%左右。结论:大黄酸-泊洛沙姆188型固体分散体具有良好的释药性能及临床应用前景。     

中美医学创新能力教育的差异

为了培养创新型医学人才,对比了中美医学教育,发现后者在以下方面有利于创新能力的培养:(1)自由的知识获取途径:①选课自由；②启发式教学；③学习时间机动,；(2)与兴趣物密切接触的机会:①实验室开放；②社会实践多；③协作的能力培养；(3)探索与冒险精神:①探索的文化氛围；②易获基金的支持.     

Microcystin-LR degradation utilizing a novel effective indigenous bacterial community YFMCD1 from Lake Taihu

Microcystins (MC) produced by species of cyanobacteria including Microcystis, Anabaena, and Aphanizomenon are a group of monocyclic hepatotoxins posing serious threat to public health. Microcystin-LR (MC-LR) is the most toxic and frequently encountered microcystin variant in the environment, and thus removal of this toxin using bacteria was shown to be a reliable, efficient, and cost-effective method that avoids utilization of chemicals that may produce potentially harmful by-products. The aim of this study was to determine whether a novel indigenous bacterial community designated YFMCD1 was effective in destroying MC. In addition, the influence of environmental factors such as temperature, MC concentration, and pH was examined on the effectiveness of YFMCD1 to degrade MC-LR. MC-degradation products were identified by high performance liquid chromatography coupled with an ultra-high resolution LTQ Orbitrap Velos Pro ETD mass spectrometry equipped with electrospray ionization interface (HPLC-ESI-MS). MC-LR underwent maximal degradation at rate of 0.5 µg/ml/hr with YFMCD1 containing Klebsiella sp. termed YFMCD1-1 or Stenotrophomonas sp. termed YFMCD1-2. Moreover, Adda (3-amino-9-methoxy-2, 6, 8-trimethyl-10-phenyldeca-4, 6-dienoic acid) is a constituent within the MC-LR molecule found to be responsible for biological activity expression and critical for MC-induced toxicity, which is also degraded by YFMCD1. The results showed that YFMCD1 effectively degraded MC-LR. The degradation rate was significantly affected by temperature, pH, and MC-LR concentrations. Data indicate that this bacterial community may prove beneficial in bioremediation of lakes containing MC.     

食品中非法添加和滥用化学染料的分析研究

建立了食品中碱性黄、碱性嫩黄、碱性橙II、酸性橙II、罗丹明B、对位红、苏丹类1-4号11种有机染料的高效液相色谱分析方法。在0.2-10μg/mL的浓度范围内线性相关系数良好,相关系数范围为0.9996-0.9999,检测限0.05μg/mL。该方法涉及的化学试剂少,操作简便,结果准确。对阳性样品进一步采用液质联用技术确证。     

Melatonin overcomes apoptosis resistance in human hepatocellular carcinoma by targeting Survivin and XIAP

Apoptosis resistance in hepatocellular carcinoma (HCC) is one of the most significant factors for hepatocarcinogenesis and tumor progression, and leads to resistance to conventional chemotherapy. It is well known that inhibitor of apoptosis proteins (IAPs) play key roles in apoptosis resistance, it has become an important target for antitumor therapy. In this study, we examined if melatonin, the main secretory product of the pineal gland, targeted IAPs, leading to the inhibition of apoptosis resistance. To accomplish this, we first observed that four members of IAPs (cIAP‐1, cIAP‐2, Survivin, and XIAP) were overexpressed in human HCC tissue. Interestingly, melatonin significantly inhibited the growth of HepG2 and SMMC‐7721 cells and promoted apoptosis along with the downregulation of Survivin and XIAP, but had no effect on the expression of cIAP‐1 and cIAP‐2. These data suggest that the inhibition of Survivin and XIAP by melatonin may play an important part in reversing apoptosis resistance. Notably, cIAP‐1, Survivin and XIAP were significantly associated with the coexpression of COX‐2 in human HCC specimens. Melatonin also reduced the expression of COX‐2 and inhibited AKT activation in HepG2 and SMMC‐7721 cells. Inhibition of COX‐2 activity with the selective inhibitor, NS398, and inhibition of AKT activation using the PI3K inhibitor, LY294002, in tumor cells confirmed that melatonin‐induced apoptosis was COX‐2/PI3K/AKT‐dependent, suggesting that the COX‐2/PI3K/AKT pathway plays a role in melatonin inhibition of IAPs. Taken together, these results suggest that melatonin overcomes apoptosis resistance by the suppressing Survivin and XIAP via the COX‐2/PI3K/AKT pathway in HCC cells.     

Morphology cluster and prediction of growth of human brain pyramidal neurons

Predicting neuron growth is valuable to understand the morphology of neurons, thus it is helpful in the research of neuron classification. This study sought to propose a new method of predicting the growth of human neurons using 1 907 sets of data in human brain pyramidal neurons obtained from the website of NeuroMorpho.Org. First, we analyzed neurons in a morphology field and used an expectation-maximization algorithm to specify the neurons into six clusters. Second, naive Bayes classifier was used to verify the accuracy of the expectation-maximization algorithm. Experiment results proved that the cluster groups here were efficient and feasible. Finally, a new method to rank the six expectation-maximization algorithm clustered classes was used in predicting the growth of human pyramidal neurons.