基于分子克隆方法制备标准分子量片段混合物

目的制备标准分子量DNA片段混合物。方法选取pMD18-T载体部分序列作为插入片段,设计引物,制备包含不同大小的标准分子量片段的克隆。大量培养细菌提取质粒,用双酶切、连接荧光接头的方法制备不同大小的带有荧光的标准分子量片段,混合,纯化,最终获得标准分子量片段混合物(内标)。结果用分子克隆方法制备出具有实用性的标准分子量片段混合物,其单个标准分子量片段大小分别为80bp、124bp、194bp、224bp、254bp、304bp、349bp、399bp、424bp、454bp。并且这些标准分子量片段混合物可以准确地对DNATyper15试剂盒的扩增产物进行检测。结论应用该方法制备了能满足研究和实验室要求的标准分子量片段混合物,为DNA分子量标准物标准品的制作提供了一种新的方法。     

以科学发展观为统领不断推进工会工作创新发展

中关村科技园区海淀园是中国第一个高新技术产业开发区，汇聚了15000多家高新技术企业。目前园区基层工会组织多是小而分散，工会会员呈高学历、高素质、高收入群体特点。工会工作按照传统的组织体系和工作方式难以有效运作。因此，园区各级工会必须适应形势，在基层建设和工作领域方面走向社会化、网络化和开放化，从实际出发，建立健全工会组织体系，以科学发展观为统领，以维权为重点，围绕园区的稳定和发展，发挥工会组织的积极作用。     

论我国少数民族社会生产力的跨越式发展

生产力是少数民族社会发展的最终决定力量;科学技术是第一生产力,是推动少数民族社会全面进步的伟大杠杆。我国少数民族社会必须通过科技建设与技术创新、民族教育的建设与创新、管理创新、民族文化的创新和发展,实现生产力的跨越式发展,促进少数民族经济社会的全面发展。     

广西服务业科技发展的战略与对策

文章在对广西服务业发展现状、存在问题、面临的机遇与挑战等进行分析的基础上,系统探讨了广西服务业科技发展的战略选择、重大任务、重点领域、政策与保障措施等有关问题,对于促进广西服务业的进一步发展具有现实意义。     

基于38-plex InDels的青海地区三个族群遗传推断

目的 基于38-plex InDels族群推断体系研究青海地区汉族、回族及撒拉族的族群成分与遗传结构.方法 使用38-plex InDels复合扩增体系检测3个族群的220份样本并获取InDels位点分型,利用主成分分析、STRUCTURE聚类分析及系统发育树综合分析族群之间的遗传关系,使用族群推断软件DAA v1.0...     

Chemical Imaging of Human Fingermark by X-ray Photoelectron Spectroscopy (XPS)

X-ray photoelectron spectroscopy (XPS) is a widely used technique to characterize the surface chemistry of materials. It plays a crucial role in accessing qualitative and quantitative information and in detecting the presence of chemical functional groups on the surface of any material. The forensic methods available to detect and identify elements and organic/inorganic compounds are often destructive, so evidence cannot be re-analyzed. However, XPS allows rapid analysis of samples without damaging them. Recently, an increasing number of forensic researchers have begun to study certain chemical information on fingermarks. In this study, the authors aimed to present the applicability and power of XPS imaging in fingermark analysis which can also provide specific information about the fingermark chemical composition. Herein, monochromated X-ray (Al Kα) spot size was fixed at 50 μm. XPS mapping resulted in the acquisition of spectra at each pixel, in an array of 41 × 30 pixels with a step size of 50 μm. Then, a simple discussion has been made about how the scanned surface spectrum and basic snapshot spectra are used to identify different components at a fingertip of a scanned surface area (~3 mm²). Hence, a fingermark pattern contaminated with caffeine, TiO₂, and Pb/PbO deposited on the silicon wafer can be chemically mapped and visualized by XPS using principal component analysis (PCA). Thus, the present study showed the possible applicability of XPS for the identification of illicit drugs of abuse, gunshot residue, and skin care products on latent fingermark by mimicking a crime scene evidence.     

Distribution of the Minutiae in Hypothenar Palm Prints in Slovak Adults: Indications for Personal Identification

Minutiae are small distinguishing features found along every ridge flow, which make each friction ridge print unique. The most common friction ridge prints found at the crime scene are fingerprints; therefore, the most of the minutiae studies are focused exactly on this kind of prints. The authors believe that further examination and enlargement of the palm print database could result in better use of the palm prints for personal identification. We analyzed a total of 160 palm prints from 40 females and 40 males aged between 18 and 70 years from Slovakia. For the evaluation of the minutiae, the area of the hypothenar had to be marked out. The classification of the minutiae used for this study was based on a modified version of the classification system using the total of 13 types of minutiae. The frequency of every minutiae type was calculated and, using the chi-square test with Yates's correction, bilateral and sex differences were assessed. The relationship between the different types of minutiae was examined with Pearson's correlation test. During the initial phases of the identification process, the focus should be on the least common types of minutiae (Y or M and return), which were found not to correlate; thus, their mutual occurrence is random (e.g., overlap—Y or M, crossbar—return, or Y or M—dock). The results of the present study show which specific minutiae types are the most suitable for personal identification. These findings may be beneficial in more effective outcome of the identification process.     

The Error in “Error Rate”: Why Error Rates Are So Needed,Yet So Elusive

Establishing error rates is crucial for knowing how well one is performing, determining whether improvement is needed, measuring whether interventions are effective, as well as for providing transparency. However, the flurry of activities in establishing error rates for the forensic sciences has largely overlooked some fundamental issues that make error rates a problematic construct and limit the ability to obtain a meaningful error rate. These include knowing the ground truth, establishing appropriate databases, determining what counts as an error, characterizing what is an acceptable error rate, ecological validity, and transparency within the adversarial legal system. Without addressing these practical and theoretical challenges, the very notion of a meaningful error rate is limited.     

Composite Machine Learning Algorithm for Material Sourcing,

This study developed a composite machine learning algorithm for attribution of materials of forensic interest (like ammonium nitrate) to original sources. k-nearest neighbor and random forest models were used for source elimination and classification, respectively, in a two-step, composite algorithm based on particle color, size/shape, and trace element concentration features. Novel approaches for simulation to supplement within-source reference features based on empirically measured multi-lot analyses, an improved hold-one-lot-out method for cross-validation, an assessment of the likelihood of the presence of a reference sample, fusion of the source probabilities from the respective classification models, and the calculation of metrics for assessing ensemble sourcing performance are described. Excellent sourcing predictions were obtained; the sourcing algorithm identified the correct source as the top choice 89% of the time, and the correct source was identified to be an average of 2.7 times more likely than the most likely incorrect source.