基于文本挖掘的DNA微阵列表达数据方法研究

DNA微阵列技术是近年来发展起来的一种功能基因组学研究技术.利用DNA微阵列技术,可以从基因组水平上鉴定出相关的功能基因及其表达调控网络,有助于阐明这些基因的生物学功能及其机理.结合文本挖掘的相关研究结果.探讨了DNA微阵列技术的原理和特点,数据的分析和解释,基因的聚类方法和基于文献的DNA微阵列分析.通过基于文献的微阵列分析方法,找出隐舍的、具有语义关联的生物概念,并进行推理,发现隐性的新知识.具体阐述了基于统计、基于自然语言处理、基于关联规则挖掘,基于模式识别的4种分析方法.基于文本挖掘的DNA微阵列技术,有利于发现基因或蛋白质之间的相互作用关系,自动识别生物学名词,提高数据分析效率等.     

基于证据推理及评估用例的信息系统安全评估模型

为了实现信息系统安全评估的规范准确,根据评估过程的实际需要,在《信息系统安全保障评估框架》标准基础上建立了证据推理模型,把系统的安全等级、评估规约、直接证据融合入模型之中。引入软件测试理论中测试用例的概念构造评估用例,定义了安全指标的3种类型,提出了基于这3种类型的评估规则,最后给出了模型的实现方式。从实例分析可以看出,该评估方法提高了评估工作的规范性,减少了人为因素对评估结果的影响。     

现代“肺阳虚”方药数据库的建立及数据分析

全面检索现代期刊文献,查找治疗＂肺阳虚＂的方药并建立数据库,使用频数、聚类及关联规则的方法进行数据分析,结果显示现代治疗肺阳虚的方剂均是以补虚、化痰止咳平喘、解表及温里药为主,药性以温、平、热为主,药味多辛、甘、苦味,主要归肺经;关联规则分析得常用药对6对,药组1组。     

基于小波变换医学图像融合算法的对比分析

小波变换融合方法具有重要的应用价值,而融合规则的选取直接影响着融合效果。为了获得医学临床上实用的小波融合算法,选择标准CT/MRI图像,通过调整和组合各种小波变换低频及高频融合规则进行仿真实验,深入对比分析各种融合规则对医学图像融合性能的影响。在此基础上,提出低频能量取大与高频系数绝对值取大相结合的融合改进算法,比目前基于传统小波融合规则的融合质量及各项客观评价指标都有明显提高,在各种算法比较中最优。采用多聚焦图像和临床实际的CT/MRI图像进行对比验证,表明了方法的有效性。理论分析和实验结果证明:选取合适的融合规则对融合结果影响很大,本研究提出的算法简单有效。     

中药防治放射性口腔干燥症用药规律的探讨

目的探讨中医药防治放射性口腔干燥症的用药规律,为临床应用提供参考。方法对1998年至2010年期间有关放射性口腔干燥症的文献进行统计分析,文献入选标准为：口腔损伤系放射治疗所致,有完整方剂且用中药汤剂治疗。结果查询到相关方剂103首,用药114味;常用中药为补虚药、清热药;其中使用频次在前10位的中药有麦冬、玄参、生地、茯苓、白芍、山药、金银花、丹皮、丹参、五味子。结论治疗放射性口腔干燥症主要以养阴润燥、清热解毒为主。     

新疆居民西北燥证罹患率的民族分布规律探讨

[目的]探讨新疆居民西北燥证罹患率的民族分布规律。[方法]利用西北燥证调查量表调查新疆伊犁、哈密和乌鲁木齐地区西北燥证罹患率。[结果]农村西北燥证罹患率的大致规律是汉族、哈萨克族高于维吾尔族;域市西北燥证罹患率是汉族高于维吾尔族;城乡比较则是城市居民西北燥证罹患率高于农村居民,三民族无差异。[结论]饮食习惯上的民族差异或许导致西北燥证罹患率出现民族差异,而城乡居住环境的差异则是导致西北燥证罹患率出现民族差异的另一个原因。     

从肿瘤基因表达数据挖掘分类规则的研究

基于肿瘤基因表达数据,利用信息科学的方法和技术建立肿瘤预测分类模型,对肿瘤基因表达模式研究和肿瘤的诊断识别具有重要意义.本研究提出一种从肿瘤基因表达数据中直接挖掘分类规则建立肿瘤预测分类器的方法.该方法首先抽取实验样本集,分别找出标记肿瘤和正常组织样本的分类特征,由此生成可预测样本类别的分类规则,对每个未知类别样本,按照置信度最高原则,选择一个分类规则作为预测结构.本研究的实验数据来自Broad Institute的前列腺癌基因表达数据,实验结果显示该方法的预测精度在90%以上,且同时获得了大量结构透明的分类预测规则,表明本研究的方法是可行的和有效的.     

A stability-indicating HPLC assay with diode array detection for the determination of a benzylpenicillin prodrug in aqueous solutions

The aim of this study was to develop a stability-indicating HPLC assay for the determination of penethamate (PNT), an ester prodrug of benzylpenicillin (BP), in aqueous solutions. The method was validated by subjecting PNT to forced decomposition under stress conditions of acid, alkali, water hydrolysis and oxidation. A quenching solution was developed to limit degradation to negligible levels before and during the analysis. Both PNT and BP were simultaneously determined and separated in presence of degradation products on a C₁₈ column using a mobile phase consisting of methanol–acetonitrile–acetate buffer. Different degradation products were formed in the stress conditions. The peak purity indexes of PNT and BP obtained by diode array detection were >0.999, confirming the absence of other co-eluting substances. The assay was linear for both analytes in the concentration range 1–100 μg mL⁻¹. The LOD and LOQ of PNT were 0.03 and 0.09 μg mL⁻¹ respectively. Degradation of PNT followed pseudo-first-order kinetics with t_1/2 of 43.6 min at pH 2.01 and 4.2 min at pH 9.31. In addition, the absence of BP in the acidic solutions of PNT emphasises the futility of monitoring BP to assess the stability of PNT. In conclusion, the assay is rapid and stability-indicating with adequate precision and accuracy, and in conjunction with the quenching solution, can be used for stability studies of PNT with simultaneous quantitation of BP. The degradation studies provide useful information for formulation development of PNT.     

Stability of ricobendazole in aqueous solutions

The chemical stability of ricobendazole (RBZ) was investigated using a stability-indicating high performance liquid chromatographic (HPLC) assay with ultraviolet detection. The degradation kinetics of RBZ in aqueous solution was evaluated as a function of pH, buffer strength and temperature. The oxidation reaction in hydrogen peroxide solution was also studied. Degradation products were analyzed by mass spectroscopy and degradation pathways are proposed. Degradation of RBZ followed pseudo first-order kinetics and Arrhenius behavior over the temperature range 24–55 °C. A V-shaped pH-rate profile over the pH range 2–12 was observed with maximum stability at pH 4.8. The shape of the pH-rate profile was rationalized by catalytic effects of various components in the solution on each RBZ species. At pH 11 the activation energy for hydrolysis was 79.5 kJ/mol, and phosphate catalysis was not observed. Oxidation occurred in hydrogen peroxide solutions and was catalyzed by the presence of copper (Cu²⁺) ions. Ricobendazole amine and albendazole sulfone were identified by MS assay to be the degradation products of hydrolysis and oxidation respectively.     

Return to Work in a Cohort of Low Back Pain Patients: Development and Validation of a Clinical Prediction Rule

Background From the viewpoint of cost prevention, it is necessary to identify patients that are of high risk for long-term work disability, production loss and sick-leave. Methods Secondary data analysis in a cohort of 628 workers on sick-leave between 3 and 6 weeks due to low back pain (LBP). The association of a broad set of demographic, work, LBP and psychosocial related factors on lasting return to work was studied using Cox regression analysis with backward selection. The most relevant factors were used to derive a clinical prediction rule to determine the risk of sick-leave of more than 6 months. Variable and model selection and clinical model performance were performed with bootstrapping techniques. Also the test characteristics of the clinical model were considered. Results Longer work absence is related to “moderate” to “poor” job satisfaction, a higher score of fear avoidance beliefs, higher pain intensity at baseline, a longer duration of complaints and being of female gender. Calibration and discrimination of the clinical prediction rule were 0.90 (slope) and 0.63 (c-index), respectively. The explained variance of 6% of the prediction rule was low and the clinical performance in terms of sensitivity, specificity, positive and negative predictive values at specific cut-off points was moderate. Conclusions Our study confirmed the importance of demographic, work, LBP and psychosocial related factors on the prediction of long-term sick-leave. When these factors were used to derive a clinical prediction rule the performance was moderate. As a consequence, prudence has to be taken when using the prediction rule in practice.