苦参的毛细管电泳数字化指纹图谱研究

目的 建立苦参的毛细管电泳指纹数字化图谱（CEFP），考察Jaccard相似度Sb评价苦参CEFP的可行性和特征。方法 采用胶束电动毛细管电泳法，以30mmol·L^-1硼砂＋10mmol·L^-1 SDS为背景电解质，运行电压12kV，紫外检测波长205nm，以10个不同产地药材的电泳图谱建立了苦参的对照CEFP。与双定性相似度SF和S′F、双定量相似度C％和P％相比较考察Jaccard相似度参数Sb的可行性和特征。结果 以萘普生为参照物峰，确定15个共有峰，建立了苦参CEFP，并用“中药色谱指纹图谱超信息特征数字化评价系统3．0”软件挖掘苦参CEFP的指纹特征，结合双定性双定量相似度法客观、全面地评价了不同产地苦参的质量。结论 所建立的苦参毛细管电泳数字化指纹图谱具有较好的精密度和重现性，可为苦参质量控制提供新参考，Jaccard相似度Sb参数能够作为评价中药批间相似度一个较好的指标。     

医院智能导诊系统设计与实现

利用稀疏矩阵和杰卡德相似系数,结合医疗领域知识构建医院智能导诊系统,阐述系统需求、总体设计、关键技术和功能模块,包括智能导诊、综合信息查询、知识库管理及数据库设计,指出该系统能够在一定程度上克服医院现有分诊流程存在的弊端,缓解导诊服务压力。     

Automatic method for tracing regions of interest in rat brain magnetic resonance imaging studies

Purpose

To automatically extract regions of interest (ROIs) and simultaneously preserve the anatomical characteristics of each individual, we developed a new atlas‐based method utilizing a pair of coregistered brain template and digital atlas.

Materials and Methods

Unlike the previous atlas‐based method, this method treats each individual as the target image, and the template and atlas are each transformed to register with the individual. To evaluate the accuracy of this method we implemented it in extracting the hippocampus from two groups of T₂‐weighted structural images with different spatial resolutions and a group of T₂*‐weighted functional images. Furthermore, the results were compared against a manually segmented hippocampus and an atlas‐derived hippocampus.

Results

Jaccard similarity (JS) reached 84.7%–90.5%, and relative error in volume (RV) was 4.8%–12.7%. The consistency observed between the results of the proposed method and manual drawing was therefore considerable.

Conclusion

We developed a new atlas‐based method for ROI extraction that can automatically extract ROI and simultaneously preserve each individual's unique anatomical characteristics. J. Magn. Reson. Imaging 2010;32:830–835. © 2010 Wiley‐Liss, Inc.     

发泡垫在头颈肿瘤放疗定位中应用价值研究

目的 头颈部调强放疗技术高速发展,摆位精度要求越来越高.本研究通过定位发泡垫在头颈部调强放疗摆位中的应用,探讨其在定位中的价值.方法 选取上海交通大学附属第九人民医院2014-02-01-2014-05-30收治的20例舌癌患者为研究对象,分为发泡垫组和头枕组,两组患者放疗前后体质量变化＜5kg.每例患者在放疗前与放疗20次后,各完成1次定位CT扫描;将定位图像输入MIM软件,建立坐标系,分别勾画颈椎,利用DICE流程计算出的Dice系数、Jaccard系数、Hausdorff距离作为评价指标,分组研究颈椎位置变化.结果 定位发泡垫纽的Dice系数为0.79±0.07,Jaccard系数为0.65±0.10;头枕组的Dice系数为0.70±0.08,Jaccard系数为0.53±0.10,P＜0.000 1.定位发泡垫组的Hausdorff距离为0.65±0.12,头枕组的Hausdorff距离=0.84±0.15,统计值P＜0.05.定位发泡垫组颈椎中心间距为0.21±0.08,头枕组为0.30±0.10.定位发泡垫组的Dice系数、Jaccard系数、Hausdorff距离颈椎和颈椎中心间距均优于头枕组.结论 相对于传统的头枕,定位发泡垫减少患者横向纵向、以及旋转的误差,更适合临床应用.     

基于图数据模式匹配的《伤寒论》辨证论治计算机建模医理设计

以《伤寒论》的辨证论治原则为指导,提出一种模拟医生进行辨证论治思维的计算机模型设计。该模型设计基于Neo4j的图数据构建技术、Cypher语言的图模式匹配技术以及Jaccard相似度公式,旨在实现对输入症状进行分析、推理,以明确病证的诊断及鉴别诊断的结果,并给出对应的治疗方剂,即模拟《伤寒论》中"观其脉证,知犯何逆,随证治之"的辨证论治过程,以期为中医临床辅助诊疗模型的构建提供借鉴与启发。     

Predicting spatial similarity of freshwater fish biodiversity

A major issue in modern ecology is to understand how ecological complexity at broad scales is regulated by mechanisms operating at the organismic level. What specific underlying processes are essential for a macroecological pattern to emerge? Here, we analyze the analytical predictions of a general model suitable for describing the spatial biodiversity similarity in river ecosystems, and benchmark them against the empirical occurrence data of freshwater fish species collected in the Mississippi–Missouri river system. Encapsulating immigration, emigration, and stochastic noise, and without resorting to species abundance data, the model is able to reproduce the observed probability distribution of the Jaccard similarity index at any given distance. In addition to providing an excellent agreement with the empirical data, this approach accounts for heterogeneities of different subbasins, suggesting a strong dependence of biodiversity similarity on their respective climates. Strikingly, the model can also predict the actual probability distribution of the Jaccard similarity index for any distance when considering just a relatively small sample. The proposed framework supports the notion that simplified macroecological models are capable of predicting fundamental patterns—a theme at the heart of modern community ecology.     

Comparing medicinal plant knowledge using similarity indices: a case of the Brou, Saek and Kry in Lao PDR

Background

Medicinal plant traditional knowledge is one of the most widely known traditional ecosystem services, as it provides primary healthcare, contributes to subsistence livelihoods, and for its potential value as a source of novel pharmaceuticals. People living in close contact with their surroundings for many generations are hypothesized to have developed, through trial-and-error, in-depth knowledge of ecosystems, biodiversity, and their management and utility. In the case of medicinal plant knowledge it could lead to an asymptotic climax or a constantly evolving equilibrium of cures with proven efficacy and those under assessment.

Methods

An in-depth study of 97 plant species used in traditional medicine by the Brou, Saek and Kry ethnic groups in Lao PDR was made to test similarity in medicinal plant knowledge.

Results

Medicinal plants were used in 99 different ways in 510 species-use combinations. Medicinal uses could be generalized into 12 use categories with 747 species-category combinations. Similarity indices show Brou and Saek plant use appears to be most similar (QS_BS: 60.0; JI_BS: 75.1) followed by Kry and Saek (QS_KS: 51.6; JI_KS: 53.4), and then Kry and Brou (QS_BK: 46.9; JI_BK: 44.1).

Discussion

Intercultural similarities found are quite low, considering that all three groups share the same geographical and ecological area and have the same dependence on medicinal plants. Intercultural transmission is unimpeded but many treatments are likely to be ineffective. Comparison of the similarities found here with similarities computed from other data show that these results are homologous with other sympatric ethnic groups, and much higher than those for allopatrically living groups.

Conclusion

Medicinal plant knowledge does not reach a stable climax, but appears to evolve continually by trial-and-error, as effective cures to many ailments are unavailable.     

Distribution based Fuzzy Estimate Spectral Clustering for Cancer Detection with Protein Sequence and Structural Motifs

Objective: In biological data analysis, protein sequence and structural motifs are an amino-acid sequence patternsthat are widespread and used as tools for detecting the cancer at an earlier stage. To improve the cancer detection withminimum space and time complexity, Distribution based Fuzzy Estimate Spectral Clustering (DFESC) technique isdeveloped. Methods: Initially, the protein sequence motifs are taken from dataset to form the cluster. The Distributionbased spectral clustering is applied to group the protein sequence by measuring the generalized jaccard similaritybetween each protein sequences. To develop the clustering accuracy, soft computing technique namely fuzzy logic isapplied to calculate membership value of each sequence motifs. Results: The outcome showed that the presented DFESCtechnique effectively identifies the cancer in terms of clustering accuracy, false positive rate, and cancer detection timeand space complexity. Conclusion: Based on the observations, evaluation of DFESC technique provides improvedresult for premature detection of cancer using protein sequence and structural motifs.