Regular Small-World Network

According to the deficiencies in Watts and Strogatz＇s small-world network model, we present a new regular model to establish the small-world network. Besides the property of the small-world, this model has other properties such as accuracy in controlling the average shortest path length L, and the average clustering coefficient C, also regular network topology as well as enhanced network robustness. This method improves the construction of the small-world network essentially, so that the regular small-world network closely resembles the actual network. We also present studies on the relationships among the quantities of a variety of edges, L and C in regular small-world network in detail, This research lays the foundation for the establishment of the regular small-world network and acts as a good guidance for further research of this model and its applications.     

直链淀粉-三[(S)-1-苯乙基氨基甲酸酯]手性固定相拆分布地奈德对映体及其制剂含量的测定

22R-布地奈德的药物活性比22S-布地奈德的强2~3倍,开发布地奈德对映体拆分和定量分析方法,可为其药物研发及质量控制提供重要依据。目前,主要以反相C₁₈固定相对布地奈德对映体进行拆分,而采用手性固定相对其进行拆分少有报道。通过考察固定相、流动相和柱温对布地奈德对映体拆分的影响,建立了基于直链淀粉-三[(S)-1-苯乙基氨基甲酸酯]手性固定相快速拆分和检测布地奈德对映体的高效液相色谱方法,其色谱条件如下:色谱柱为Chiralpak AS-RH色谱柱(150 mm×4.6 mm, 5.0 μm),流动相为乙腈-水(45∶55, v/v),柱温40 ℃,流速1.0 mL/min,二极管阵列检测器(DAD),检测波长246 nm,进样量10 μL。在该色谱条件下,布地奈德的两个对映体得到较好拆分,22R-布地奈德和22S-布地奈德的保留时间分别6.40 min和7.77 min,分离度为4.64; 22R-布地奈德和22S-布地奈德分别在各自范围内线性关系良好,相关系数(R²)均为0.9999,检出限分别为0.05 μg/mL和0.07 μg/mL,定量限分别为0.16 μg/mL和0.20 μg/mL; 4个添加水平的样品加标回收率为102.63%~104.17%,相对标准偏差(RSD)为0.08%~0.57%(n=6)。将该方法应用于1批次4个吸入用布地奈德混悬液实际样品进行检测,22R-布地奈德和22S-布地奈德的含量分别为283.15~284.63 μg/mL和259.86~261.51 μg/mL。该方法操作简便,分析时间短,重复性好,准确度高,可用于布地奈德对映体的拆分及其制剂的质量控制。     

高效液相色谱法快速同时检测全血中两种免疫抑制剂

环孢素A和西罗莫司是许多器官移植手术中广泛使用的免疫抑制剂,且一起使用时会产生协同效应,但这两种免疫抑制剂的治疗窗口都非常窄,仅在特定的血药浓度范围内有预期的治疗效果。因此,快速同时检测全血中这两种免疫抑制剂的浓度,可为患者器官移植手术后的给药方案提供有价值的信息。该工作首先考察了环孢素A和西罗莫司在生物液相色谱柱和传统液相色谱柱上的色谱行为,然后基于生物液相色谱柱,建立了可快速分离和检测全血中环孢素A和西罗莫司的高效液相色谱分析方法。全血样品经样品前处理后进样分析,采用ZORBAX 300SB C8柱（250 mm×4.6 mm, 5.0 μm）进行分离,以乙腈-水（70∶30, v/v）为流动相进行等度洗脱,柱温为60 ℃,流速为1.0 mL/min,检测波长为205 nm和278 nm,进样量为20 μL。结果表明,环孢素A和西罗莫司在6 min内可实现较好的分离;环孢素A和西罗莫司在各自的浓度范围内具有良好的线性关系（r>0.997）,检出限（S/N=3）分别为10 ng/mL和1 ng/mL,定量限（S/N=10）分别为30 ng/mL和2 ng/mL, 3个水平的平均加标回收率分别为83.5%~89.7%和95.8%~97.8%,相对标准偏差（RSD）分别为3.2%~9.0%和3.4%~6.7%（n=5）。该方法操作简便,流动相简单,分析时间短,线性范围宽,灵敏度高,可用于全血中环孢素A和西罗莫司的含量检测。     

An evolving network model with modular growth

In this paper, we propose an evolving network model growing fast in units of module, according to the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing the ratio of the number of inner-module edges and the number of inter-module edges. In view of the mean-field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module.