补肾健骨胶囊高效液相色谱指纹图谱及主成分分析

目的：建立补肾健骨胶囊的高效液相色谱法(HPLC)指纹图谱,并进行主成分分析。方法：采用HPLC,色谱柱为Thermo-Hypersil GOLD^TM-C18(250 mm×4.6 mm×5μm),流动相为乙腈-0.2%磷酸水溶液(梯度洗脱),流速为1.0 mL/min,检测波长为235 nm,柱温为30℃,进样量为10μL。根据15批样品的HPLC检测图谱,采用国家药典委员会《中药色谱指纹图谱相似度评价系统》(2012年版)进行相似度评价和共有峰的确定,并采用Minitab17.0软件进行主成分分析。结果：补肾健骨胶囊指纹图谱共标出13个共有峰,并指认了其中3个共有峰,分别为莫诺苷、马钱苷、淫羊藿苷;15批样品的相似度均大于0.9,各批次样品之间有良好的相似性。经主成分分析,共提取出2个主成分,方差累计贡献率为92.3%,样品中1、2、4、6、8、13号共有峰(特别是13号共有峰)对应成分的含量变化是导致样品质量差异的重要原因。结论：所建HPLC指纹图谱及主成分分析结果可为补肾健骨胶囊的质量评价提供参考。     

中药材白英XRD指纹图谱及相似度分析

目的:建立白英药材XRD的鉴定分析新方法。方法:对白英药材不同药用部位进行X射线衍射分析,并按2θ进行相似度计算与分析。结果:获得了白英药材不同药用部位的X射线衍射Fourier指纹图谱。结论:粉末X射线衍射Fourier指纹图谱鉴定法可用于白英药材不同药用部位的鉴定和识别,相似度的计算结果进一步证明了方法的可行性。     

基于改进SLNC的2D-3D医学图像配准

介绍了一种基于改进SLNC(sum of local normalized correlation,SLNC)的2D-3D医学图像配准方法。首先对CT体积数据进行三线性插值,得到各向分辨率相同的体积数据,采用光线跟踪算法对其进行数字图像重建。针对不同位置和方向的重建图像,在灰度级压缩的基础上,用改进SLNC函数评价其与X线透视图像的相似性,利用与Brent相结合的Powell优化方法,搜索出相似性最大时的投影变换参数。将此方法用于移动数字X线投影设备——Biplanar 500采集的X线透视图像与相应CT体积数据的配准实验,得到较好的2D-3D图像配准效果。     

Cross-reactivity studies and predictive modeling of “Bath Salts” and other amphetamine-type stimulants with amphetamine screening immunoassays

Introduction. The increasing abuse of amphetamine-like compounds presents a challenge for clinicians and clinical laboratories. Although these compounds may be identified by mass spectrometry-based assays, most clinical laboratories use amphetamine immunoassays that have unknown cross-reactivity with novel amphetamine-like drugs. To date, there has been a little systematic study of amphetamine immunoassay cross-reactivity with structurally diverse amphetamine-like drugs or of computational tools to predict cross-reactivity. Methods. Cross-reactivities of 42 amphetamines and amphetamine-like drugs with three amphetamines screening immunoassays (AxSYM^® Amphetamine/Methamphetamine II, CEDIA^® amphetamine/Ecstasy, and EMIT^® II Plus Amphetamines) were determined. Two- and three-dimensional molecular similarity and modeling approaches were evaluated for the ability to predict cross-reactivity using receiver–operator characteristic curve analysis. Results: Overall, 34%–46% of the drugs tested positive on the immunoassay screens using a concentration of 20,000 ng/mL. The three immunoassays showed differential detection of the various classes of amphetamine-like drugs. Only the CEDIA assay detected piperazines well, while only the EMIT assay cross-reacted with the 2C class. All three immunoassays detected 4-substituted amphetamines. For the AxSYM and EMIT assays, two-dimensional molecular similarity methods that combined similarity to amphetamine/methamphetamine and 3,4-methylenedioxymethampetamine most accurately predicted cross-reactivity. For the CEDIA assay, three-dimensional pharmacophore methods performed best in predicting cross-reactivity. Using the best performing models, cross-reactivities of an additional 261 amphetamine-like compounds were predicted. Conclusions. Existing amphetamines immunoassays unevenly detect amphetamine-like drugs, particularly in the 2C, piperazine, and β-keto classes. Computational similarity methods perform well in predicting cross-reactivity and can help prioritize testing of additional compounds in the future.     

Multilevel modelling of somatotype components: the Portuguese sibling study on growth,fitness, lifestyle and health

Background: Somatotype is a complex trait influenced by different genetic and environmental factors as well as by other covariates whose effects are still unclear.

Aims: To (1) estimate siblings’ resemblance in their general somatotype; (2) identify sib-pair (brother–brother (BB), sister–sister (SS), brother–sister (BS)) similarities in individual somatotype components; (3) examine the degree to which between and within variances differ among sib-ships; and (4) investigate the effects of physical activity (PA) and family socioeconomic status (SES) on these relationships.

Subjects and methods: The sample comprises 1058 Portuguese siblings (538 females) aged 9–20 years. Somatotype was calculated using the Health-Carter method, while PA and SES information was obtained by questionnaire. Multi-level modelling was done in SuperMix software.

Results: Older subjects showed the lowest values for endomorphy and mesomorphy, but the highest values for ectomorphy; and more physically active subjects showed the highest values for mesomorphy. In general, the familiality of somatotype was moderate (ρ?=?0.35). Same-sex siblings had the strongest resemblance (endomorphy: ρ_SS > ρ_BB > ρ_BS; mesomorphy: ρ_BB = ρ_SS > ρ_BS; ectomorphy: ρ_BB > ρ_SS > ρ_BS). For the ectomorphy and mesomorphy components, BS pairs showed the highest between sib-ship variance, but the lowest within sib-ship variance; while for endomorphy BS showed the lowest between and within sib-ship variances.

Conclusions: These results highlight the significant familial effects on somatotype and the complexity of the role of familial resemblance in explaining variance in somatotypes.     

中药龟甲HPLC指纹图谱研究

目的:建立中药龟甲的HPLC指纹图谱,以达到鉴别龟甲与其混伪品的目的。方法:收集不同产地的龟甲及其混伪品21批,按上下甲进行分类,共42个样品。通过盐酸水解、脱磷、脱钙等前处理,以6-氨基喹啉基-N-羟基琥珀酰亚胺基-氨基甲酸酯(AQC)进行衍生化反应,采用C18色谱柱(3. 9 mm×150 mm,3μm),柱温37℃,以乙腈,水,缓冲盐为流动相进行梯度洗脱,流速1. 00 m L/min,检测波长248 nm。采用"中药指纹图谱相似度评价系统"(《中华人民共和国药典》2012版)对正品龟甲上甲与下甲、正品与常见混伪品进行相似度分析。结果:所建立的指纹图谱具有较好的精密度、重现性和稳定性。正品龟甲的上下甲相似度为0. 932～0. 995。正品与混伪品的相似度在0. 90以下者占90. 91%。结论:正品上、下甲的HPLC图谱差异较小,正品与混伪品差异较明显。所建立的HPLC指纹图谱可用于龟甲的质量评价。     

香附药材HPLC指纹图谱研究及相似度评价

目的：研究香附药材的HPLC色谱,并对其进行相似度评价。方法：采用梯度洗脱法测定12批香附药材的HPLC色谱,流动相为甲醇一水线性梯度洗脱,检测波长为254nm;记录时间为70min。采用“中药色谱指纹图谱相似度评价系统2004A版”进行评价。结果：12批香附高效液相色谱与对照HPLC指纹图谱比较,中位数相关系数在0．901～0．993之间,均值相关系数在0．913～0．996之间。结论：香附药材指纹图谱相似度较高。表明该方法准确、重复性好。     

中医医案方剂多维相似度算法设计与探索＊

中医医案方剂具有多维度的特性，单独采用一种相似度算法难以展现方剂数据在各维度的相似情况，具有一定的局限性。本研究基于中医医案方剂的多维数据特点，结合中医临床遣方用药的思维过程，设计了中医医案方剂的多维相似度算法，并以七则国医大师医案为示例，详细展示了该算法的计算过程，同时将多维相似度算法计算结果与传统算法计算结果进行了对比分析。通过对比可以看出本算法能够相对全面地反映不同方剂间的相似度，且结果更为合理也更贴合中医临床实际。     

How do taxonomic versus thematic relations impact similarity and difference judgments? An ERP study

Taxonomically related concepts like “bee” and “butterfly” and thematically related concepts like “bee” and “honey” have different roles in similarity judgments. We examined the complex impact of taxonomic and thematic relations on similarity and difference judgments via ERPs in a S1–S2 paradigm. Subjects were required to remember a word denoting some object or animal (S1), and compare that to a second word (S2) that was either thematically related, taxonomically related or unrelated to S1, making a “high” or “low” similarity and difference judgments in separate blocks. We found two main differences that suggest thematic and taxonomic relations engage distinct neural processes. The first difference is an N400 effect peaking between 300 ms and 400 ms that is more negative for unrelated words than for thematically and taxonomically related words. The second difference is a frontally distributed P600 peaking between 500 ms and 600 ms that is larger for taxonomically related words than for both unrelated and thematically related words. These results suggest that the dual process model for perceiving similarity is superior to the comparison only model of similarity judgments, and furthermore, provide evidence that the thematic relations are dissociative from taxonomic relations in making similarity and difference judgments.     

A Novel Similarity Learning Method via Relative Comparison for Content-Based Medical Image Retrieval

Nowadays, the huge volume of medical images represents an enormous challenge towards health-care organizations, as it is often hard for clinicians and researchers to manage, access, and share the image database easily. Content-based medical image retrieval (CBMIR) techniques are employed to facilitate the above process. It is known that a few concrete factors, including visual attributes extracted from images, measures encoding the similarity between images, user interaction, etc. play important roles in determining the retrieval performance. This paper concentrates on the similarity learning problem of CBMIR. A novel similarity learning paradigm is proposed via relative comparison, and a large database composed of 5,000 images is utilized to evaluate the retrieval performance. Extensive experimental results and comprehensive statistical analysis demonstrate the superiority of adopting the newly introduced learning paradigm, compared with several conventional supervised and semi-supervised similarity learning methods, in the presented CBMIR application.