高效液相色谱分析磷脂研究进展

天然磷脂是含磷酸的类脂化合物，广泛存在于自然界中，在工业生产、食品科学、医药学、生命科学等研究方面都有重要的作用。磷脂的研究手段多样，高效液相色谱在磷脂的分离、检测方面具有优势。结合近年来国内外对高效液相色谱分离磷脂的研究报道，分析了液相色谱分离磷脂所用固定相、流动相、检测器等关键因素，认为液相色谱与质谱联用是未来液相色谱分析磷脂的技术方向。     

高效液相色谱色谱法测定牛奶及乳制品中维生素A的研究分析

维生素A为一种重要的脂溶性物质,现阶段对该物质的含量测定方法主要有:薄层色谱法、分光光度法、液相色谱法、气相色谱法等,高效液相色谱法为一种操作简单、快速、灵敏、准确的测定维生素A的方法,本文从样品处理、色谱分离以及检测等几个方面对高效液相色谱色谱法测定牛奶及乳制品中维生素A的研究进行综述。     

高效液相色谱层析在环境分析中的应用研究

随着环境污染程度的加重与污染环境的化学物质种类的增多，如何在分析中快速准确的鉴定出污染物种类与性质是当前环境研究中面临的一大难题。高效液相色谱层析是一种结合了经典液相色谱法和气相色谱法的分离特点并在高科技水平基础上发展起来的一种新型分离方法。由于高效液相色谱层析法分离能力高，分离速度快，应用范围广．所以在化学，生物等方面快速、广泛的应用开来。本文对高效液相色谱层析法进行了简单介绍，重点分析了该方法在环境分析领域的应用，期望对环境分析起到指导作用。     

高效液相色谱法测定白酒中糖精钠的方法探讨

主要参照GB 5009.28—2016标准,从三个方面:改变流动相配比、改变色谱柱和改变液相色谱的检测器,运用高效液相色谱法将白酒中存在的干扰糖精钠检测的物质:糠醇、糠醛得以分离,以达到对白酒中糖精钠准确测定的目的。     

色谱分析法在斑蝥黄测定中的研究进展

本文从斑蝥黄的稳定性、样品的前处理技术和检测方法等方面,着重阐述了色谱技术在斑蝥黄测定中的应用,包括高效液相色谱法、高效液相色谱-串联质谱法。     

氨基柱高效液相色谱法检测大豆提取物中的磷脂酰胆碱

建立一种利用高效液相色谱检测大豆提取物中磷脂酰胆碱的简便方法.色谱柱为氨基色谱柱(250?mm×4.6?mm,5?μm),流动相洗脱条件为20％(V/V)乙腈水溶液等度洗脱,检测波长为206?nm,流量为0.8?mL/min,以峰面积为指标进行定量分析.结果表明,磷脂酰胆碱的保留时间为5.292?min,峰面积与浓度之...     

四环素类抗生素的柱前衍生化-HPLC分离-荧光增敏检测法

本文通过柱前衍生的方法,并通过对四种常用的四环素类抗生素残留检测方法的比较研究,建立了一种高效灵敏的四环素类抗生素残留的高效液相色谱检测的方法,适合于日常检测需要的HPLC-FLD分离检测分析方法。     

高效液相色谱的色谱柱的类型和流动相的选择方法

高效液相色谱仪的核心是色谱柱。另外,流动相对改善分离效果也有重要的辅助效应。色谱柱的关键内容是制备出高效的填料。现代高效液相色谱填料多使用键合固定相。色谱柱的填充技术直接影响柱效的发挥。在研究制定一个高效液相色谱方法时,选择适宜的流动相也很重要。     

超高效液相色谱产生的理论和技术背景

阐述了超高效液相色谱产生的理论和技术背景,指出液相色谱速率理论、色谱保留理论等的研究,色谱仪器的整体优化、新型色谱填料(球形亚二微米填料、整体化材料、核壳型填料、色谱饼等)的开发大大推进了色谱科学的发展,共同推进了超高效液相色谱的产生。新型色谱填料的研发仍将是今后研究的重点,分析在科学人才培养方面则应注意理论研究与技术创新相结合。     

关于维护高效液相色谱仪的探讨

高效液相色谱（hplc）作为一种分离技术和方法,目前已经发展到一个全新的阶段。高精度的输液泵,应用广泛的色谱分离柱,低噪音、高灵敏度的各种检测器和功能强大的数据处理软件系统的出现,都推动了液相色谱技术的迅猛发展。液相色谱仪正以它分辨率高、分析速度快和应用广泛的优点倍受仪器分析工作者的青睐,广泛地应用于医药卫生、环境监测、食品检测等领域。     

水和废水中氯苯的气相色谱分析方法研究

本文研究了水和废水中氯苯的萃取及分析方法。采用气相色谱法、大口径毛细管柱分离氯苯,以ECD进行检测,得到了良好的分离效果和较高的灵敏度,方法的检出限可达0.01mg/L。本方法完全能满足环境样品分析的要求。     

金属型与半导体型碳纳米管的分离方法

根据导电性质的不同,碳纳米管可分为金属型和半导体型.在碳纳米管的合成过程中,不同导电性能的碳纳米管总是混合在一起,很难把它们分离开来.分别从物理、化学和生物的角度介绍了目前分离金属型和半导体型碳纳米管的方法,认为DNA自组装分离碳纳米管的方法优于其它的方法,能够将不同类型的碳纳米管分离出来,并且,在分离的数量上优于所有其它的分离方法.     

Detection of voltage sag sources based on instantaneous voltage and current vectors and orthogonal Clarke?s transformation

Different methods for voltage sag source detection are discussed. They are based either on disturbance energy, voltage-current characteristic or active (real) current component. It is shown that, in the cases of asymmetrical voltage sags, both current-based methods known from literature do not work well. These two methods are therefore generalised using a vector-space approach. Furthermore, three new methods are introduced using orthogonal Clarke's transformation, which can be used to detect the sources of those voltage sags provoked by earth faults. All the discussed methods for voltage sag source detection have been tested by applying extensive simulations, laboratory tests and field testing. The results obtained show the very high effectiveness of the proposed methods, which are superior to the methods known from literature, especially for detecting sources of asymmetrical voltage sags.     

Quantitative and wide-ranging profiling of phospholipids in human plasma by two-dimensional liquid chromatography/mass spectrometry

Normal-phase or reverse-phase liquid chromatography has been used in phospholipidomics for lipid separation prior to mass spectrometry analysis. However, separation using a single separation mode is often inadequate, as high-abundance phospholipids can mask large numbers of low-abundance lipids of interest. In order to detect and quantify low-abundance phospholipids, we present a novel two-dimensional (2D) approach for sensitive and quantitative global analysis of phospholipids. The methodology monitors individual glycerolipids and phospholipids through the use of a new quantitative normal-phase, solid-phase extraction procedure, followed by molecular characterization and relative quantification using an ion-trap Orbitrap equipped with a reverse-phase liquid chromatograph, with data processing by MS++ software. The CV (%) of the peak area of each lipid standard was less than 15% with this extraction method. When the method was applied to a liver sample, we could detect more phosphatidylserine (PS) compared to the previous method. Finally, our developed method was applied to Alzheimer's disease (AD) plasma samples. Several hundred peaks were detected from a 60 μL plasma sample. A partial-least-squares discriminant analysis (PLS-DA) plot using peak area ratio gave a unique group of PLS scores which could distinguish plasma samples of Alzheimer's disease (AD) patients from those of age-matched healthy controls.     

Graphical Methods for Influential Data Points in Cluster Analysis

In cluster analysis, many numerical measures to detect which data points are influential have been proposed in the past literature. These numerical measures provide only limited information about which data points are influential but fail to reveal deeper relationships between the observations. They describe an overall pattern but fail to provide details about the mechanism that exists among the influential data points. In this paper, several graphical methods are described for detecting this mechanism. In the process, each data point is decomposed to show the pattern, how it influences other observations and the partitioning in cluster analysis. The approach also allows comparison of different clustering methods and how these options impact the relationship between observations. Copyright © 2014 John Wiley & Sons, Ltd.     

利用单张现场照片测量现场的方法

本文从分析案发现场照片入手，给出了如何利用单张案发现场照片勘查案发现场的方法，为对已不复存在的现场再次勘查，提供了一条行之有效的途径。     

Extracting mode components in laser intensity distribution by independent component analysis

With increasingly sophisticated laser applications in industry and science, a reliable method to characterize the intensity distribution of the laser beam has become a more and more important task. However, traditional optic and electronic methods can offer only a laser beam intensity profile but, cannot separate the main mode components in the laser beam intensity distribution. Recently, independent component analysis has been a surging and developing method in which the goal is to find a linear representation of a non-Gaussian data set. Such a linear representation seems to be able to capture the essential structure of a laser beam profile. After assembling image data of a laser spot, we propose a new analytical approach to extract laser beam mode components based on the independent component analysis technique. For noise reduction and laser spot area location, wavelet thresholding, Canny edge detection, and the Hough transform are also used in this method before extracting mode components. Finally, the experimental results show that our approach can separate the principal mode components in a real laser beam efficiently.     

Polarization-based and specular-reflection-based noncontact latent fingerprint imaging and lifting

In forensic science the finger marks left unintentionally by people at a crime scene are referred to as latent fingerprints. Most existing techniques to detect and lift latent fingerprints require application of a certain material directly onto the exhibit. The chemical and physical processing applied to the fingerprint potentially degrades or prevents further forensic testing on the same evidence sample. Many existing methods also have deleterious side effects. We introduce a method to detect and extract latent fingerprint images without applying any powder or chemicals on the object. Our method is based on the optical phenomena of polarization and specular reflection together with the physiology of fingerprint formation. The recovered image quality is comparable to existing methods. In some cases, such as the sticky side of tape, our method shows unique advantages.