ELISA assay optimization using hyperbolic regression

The enzyme-linked immunosorbent assay (ELISA) is routinely used for estimation of specific protein concentration in research and in manufacturing. To optimize both the sensitivity of the assay and its usable dynamic range, it is necessary to adjust the concentrations of reagents, as well as other experimental conditions. Hyperbolic regression is a novel mathematical technique which gives the investigator a quantitative analysis of the assay's kinetic response to variations in reagents and conditions. The equations for hyperbolic regression are easily programmed on a computer spreadsheet or even on a scientific pocket calculator. Hyperbolic regression can be used to facilitate the initial optimization of the assay conditions, or to estimate the concentrations of unknowns on a routine basis directly from the standard curve, or to monitor the long-term degradation in activity of antibody reagents and antigen standards.     

凝胶图像重叠蛋白质点分割算法研究

针对双向凝胶图像中的重叠蛋白质点检测,提出一种角点检测与多边形近似相结合的重叠蛋白质点分割方法。首先利用Harris角点检测法得到重叠蛋白质点的角点,然后利用角点对蛋白质点进行多边形近似并判断多边形顶点的凹凸性获得凹角点,最后通过凹点选取与匹配原则从凹角点中选取凹点并构造分离线完成对重叠蛋白质点的分割。实验结果表明该方法能准确快速地实现重叠蛋白质点的分割,尤其适用于重度重叠的蛋白质点。     

Analysis of chromium-51 release assay data using personal computer spreadsheet software

The Chromium-51 release assay is a widely used technique to assess the lysis of labeled target cells in vitro. We have developed a simple technique to analyze data from Chromium-51 release assays using the widely available LOTUS 1-2-3 spreadsheet software. This package calculates percentage specific cytotoxicity and lytic units by linear regression. It uses all data points to compute the linear regression and can determine if there is a statistically significant difference between two lysis curves. The system is simple to use and easily modified, since its implementation requires neither knowledge of computer programming nor custom designed software. This package can help save considerable time when analyzing data from Chromium-51 release assays.     

毛细管等电聚焦电泳(cIEF)及其理论模拟计算新进展

等电聚焦电泳(IEF)是一种在一个pH梯度内操作的特殊电泳。IEF是表征蛋白质电荷不均一性的强有力工具。在一个pH梯度内,酸碱两性物(例如蛋白质)在电场的作用下会被分离,并最后在pH梯度内pH值与两性物等电点(pI)值相等的地方被聚焦成很窄的区段。IEF的分辨率在所有基于电荷的分离技术中是最高的。薄层凝胶IEF从它在上世纪70年代初被发明的时间起就成为在生物实验室被广泛应用的分析技术。但薄层凝胶IEF的主要问题是不能做定量分析,全靠手工操作及分析速度低。当毛细管IEF(cIEF)在1985年被报道时,科学家们就都立即认为cIEF能够克服IEF所有的问题。虽然cIEF看起来有很多优势,但是20多年后的今天它并没有被生物实验室广泛接受为薄层凝胶IEF的替代技术。究其原因是使用通用毛细电泳仪器的cIEF在操作上有很多困难。这种技术在IEF过程后还需要一个额外的移动过程来把聚在毛细管分离柱内的蛋白质区段推到检测器的检测点。这是由于这些毛细电泳仪器都是使用单点检测器。检测点都是靠近毛细管的一端。这个移动过程破坏IEF的高分辨率,降低重现性并使得分析速度变慢,造成在方法的优化上耗很多时间。全柱检测cIEF是在1992年提出的。该技术结合了凝胶IEF及毛细管分离的全部优点;如定量和自动化。它的分离速度大大提高。本文简单综述cIEF对不同生物实验室样品的应用。这些样品包括单克隆抗体,重组蛋白质,蛋白质复合物及失活病毒。最后,本文简述cIEF理论模拟计算的新进展。     

A probability-based error spot filtering method in protein 2-DE image spot pattern matching analysis

Given a number of 2-DE gel images of the same kind, identifying the spot of each image for the same protein is an important task to monitor the expression level change of the protein. For this purpose, the gel-based two-dimensional electrophoresis method (2-DE) is widely used since it separates thousands of proteins in a sample cost-effectively. However, this approach suffers from inherent noises and irregular geometric distortions of spots observed in a 2-DE gel image. This paper proposes a probability-based error filtering method that can find more reliable spot-matching results, so that the accuracy of protein expression analysis can be improved. The performance of the proposed method is analyzed by various experiments on real 2-DE gel images of human liver tissues.     

柞蚕微粒子病蚕蛋白质组分变化的研究

罹微粒子病柞蚕幼虫血淋巴蛋白质量减少,随着龄期的增进,病症加重,蛋白质在质和量上的变化更为明显。４龄期Ｌｐ－ｓ６电泳带Ｒｆ值,病蚕小于健蚕;病蚕缺少Ｌｐ－ｍ９、Ｌｐ－ｆ１４电泳带;Ｌｐ－ｆ１６电泳带,病蚕蛋白质量高于健蚕。血淋巴蛋白质组分的变化,是微粒子原虫在蚕体内寄生与增殖所致。     

Using differential solubilization and 2-D gel electrophoresis to visualize increased numbers of proteins in the human cortex and caudate nucleus and putamen

The aim of this study was to determine if differential solubilization of human CNS proteins would increase the total number of proteins that could be visualized using 2-D gel electrophoresis. Hence, proteins were solubilized into Tris, CHAPS and SB3-10 before separation across a pH 4-7 IEF gradient and a 12-14% SDS polyacrylamide gel, which could be achieved with a run-to-run variation of 35% in spot intensity. Because Western blot analyses suggested proteins could be in more than one detergent fraction, we completed a conservative analyses of our 2-D gels assuming spots that appeared on multiple gels at the same molecular weight and pI were the same protein. These analyses show that we had visualized over 3000 unique protein spots across three 2-D gels generated from each sample of human frontal cortex and caudate-putamen. This represented, at worst, a significant increase in the number of spots visualized in the acidic protein spectrum compared to what has been reported in other studies of human CNS. This study, therefore, supports the proposal that the analysis of the human CNS proteome using 2-D gel electrophoresis, combined with appropriate sample preparation, can be used to expand the studies on the pathologies of neurological and psychiatric diseases.     

球壳孢目真菌同工酶电泳研究——Ⅰ.分类学意义的评价

对球壳孢目5属10种17个菌株进行了菌体可溶性蛋白、酯酶同工酶和过氧化物酶同工酶聚丙烯酰胺凝胶电泳分析,不同培养时间样品的电泳图谱显示菌体培养时间的长短对实验结果有一定的影响,球壳孢目真菌以培养5－10d为宜;不同种的菌株的图谱差异显,而种内不同菌株间的谱带一致性较高,表明可溶性蛋白和同工酶电泳图谱对球壳孢目真菌种级水平的分类具有重要作用,尤以酯酶同工酶酶谱为好。     

Region-based Statistical Analysis of 2D PAGE Images

A new comprehensive procedure for statistical analysis of two-dimensional polyacrylamide gel electrophoresis (2D PAGE) images is proposed, including protein region quantification, normalization and statistical analysis. Protein regions are defined by the master watershed map that is obtained from the mean gel. By working with these protein regions, the approach bypasses the current bottleneck in the analysis of 2D PAGE images: it does not require spot matching. Background correction is implemented in each protein region by local segmentation. Two-dimensional locally weighted smoothing (LOESS) is proposed to remove any systematic bias after quantification of protein regions. Proteins are separated into mutually independent sets based on detected correlations, and a multivariate analysis is used on each set to detect the group effect. A strategy for multiple hypothesis testing based on this multivariate approach combined with the usual Benjamini-Hochberg FDR procedure is formulated and applied to the differential analysis of 2D PAGE images. Each step in the analytical protocol is demonstrated by using an actual dataset. The effectiveness of the proposed methodology is shown using simulated gels in comparison with the commercial software packages PDQuest and Dymension. We also introduce a new procedure for simulating gel images.     

ELBAMAP: software for management of electrophoresis banding patterns

ELBAMAP (Electrophoresis Band Management Package) is a 41-kbyte program written in Borland Turbo Pascal, which will run on IBM PC compatible machines. The program consists of 16 procedures involved in data entry, calculation, comparison and graphic representation of banding patterns. These procedures are selected interactively in response to a main menu and a series of prompts. Database files may be stored for subsequent analysis or addition of data. Pairwise comparisons of banding patterns may be stored as a similarity matrix suitable for use by other packages which will carry out multivariate or cluster analysis. The system has been used successfully for storage and comparison of plasmid DNA digest patterns analysed by agarose gel electrophoresis and seed promoter profiles analysed by SDS-polyacrylamide gel electrophoresis.     

Elastic registration of electrophoresis images using intensity information and point landmarks

A key technique for protein analysis is the geometric alignment of gel electrophoresis images. While in previous work either intensity- or landmark-based approaches have been used for the registration of electrophoresis images, we here introduce a scheme incorporating both intensity and landmark information. With this approach, point landmarks are localized using a model fitting scheme and this geometric information is combined with intensity information for elastic image registration. By experiments on the basis of electrophoresis images of different levels of complexity, we demonstrate that the intensity information alone is generally not sufficient to accurately register corresponding images. However, it turns out that the incorporation of landmarks significantly improves the registration accuracy. This is supported by quantitative results.     

微流控制系统在DNA计算中的应用

DNA计算系统以人工合成或自然存在的DNA分子作为信息存储的媒介,通过分子生物工程技术例如PCR、凝胶电泳、酶反应实现计算过程。文章简要介绍了DNA计算的原理、特点及研究概况,从对DNA及蛋白质分子的操控及检测两个方面详细分析了微流控制系统在DNA计算中的应用。研究了生物芯片在集成DNA计算系统中的作用,随着可集成的功能通用化、结构三维化生物芯片系统的出现,基于生物芯片的DNA计算系统将可能成为DNA计算机的一种重要实现途径。     

基于尺度自适应与增量式学习的人脸对齐方法

针对传统基于回归的人脸对齐算法在人脸尺度归一化时会造成纹理的损失,以及为了提升算法模型的泛化能力必须扩充数据集重新训练而导致训练时间增加,甚至出现不收敛、不可计算等问题,提出一种基于尺度自适应与增量式学习（IL）的人脸对齐方法来提高定位精度。首先,建立初始人脸形状与标准人脸形状的映射关系;然后,通过映射关系实现纹理特征在原图上的提取和人脸尺度的归一化;最后,利用算法模型在新的数据集上进行增量式的学习,快速提高原模型的泛化能力。实验结果表明,与传统回归方法相比,所提方法有更高的对齐精度,特别是在AFW数据集（68个特征点）上提高了2~4个百分点;在10万级别的大数据集（5个特征点）上,所提方法的鲁棒性比基于深度学习的方法高1~2个百分点。同时,所提的增量式学习方法不仅适用于人脸对齐场景下的回归模型求解,还适用于其他应用场景下回归模型的求解。     

Semi-automatic analysis of two-dimensional electrophoretic gels

A powerful technique, two dimensional gel electrophoresis, has recently become available for the analysis of biological material. This technique allows the proteins of a sample to be mapped on a two-dimensional polyacrylamide gel. The research outlined here involves a multi-disciplinary approach to the semi-automatic comparison of two gels of biologically similar materials. The aim of the project is to identify the significant differences between the gels and point them out to the electrophoresis expert. This job, when done by hand, can be time consuming, since the gels are distorted and can contain hundreds of protein spots. Automatic analysis of 2D gel separations has proved to be extremely difficult using statistical methods. Non-reproducibility of gel separations is also difficult to overcome using automatic systems. However, the human eye is extremely good at recognizing patterns in images, and human intervention in semi-automatic computer systems can reduce the computational complexity. This paper focuses on the intelligent knowledge-based systems aspects of the project, and in particular the work of the first author. The results demonstrate that the semi-automatic approach can produce reliable results quickly. Further work, beyond the scope of this paper, focuses on creating a database of gels for comparison.     

Efficient Object Detection and Classification Approach Using HTYOLOV4 and M²RFO-CNN

Object detection and classification are the trending research topics in the field of computer vision because of their applications like visual surveillance. However, the vision-based objects detection and classification methods still suffer from detecting smaller objects and dense objects in the complex dynamic environment with high accuracy and precision. The present paper proposes a novel enhanced method to detect and classify objects using Hyperbolic Tangent based You Only Look Once V4 with a Modified Manta-Ray Foraging Optimization-based Convolution Neural Network. Initially, in the pre-processing, the video data was converted into image sequences and Polynomial Adaptive Edge was applied to preserve the Algorithm method for image resizing and noise removal. The noiseless resized image sequences contrast was enhanced using Contrast Limited Adaptive Edge Preserving Algorithm. And, with the contrast-enhanced image sequences, the Hyperbolic Tangent based You Only Look Once V4 was trained for object detection. Additionally, to detect smaller objects with high accuracy, Grasp configuration was observed for every detected object. Finally, the Modified Manta-Ray Foraging Optimization-based Convolution Neural Network method was carried out for the detection and the classification of objects. Comparative experiments were conducted on various benchmark datasets and methods that showed improved accurate detection and classification results.     

Covering with Ellipses

We address the problem of how to cover a set of required points by a small number of axis-parallel ellipses that avoid a second set of forbidden points. We study geometric properties of such covers and present an efficient randomized approximation algorithm for the cover construction. This question is motivated by a special pattern recognition task where one has to identify ellipse-shaped protein spots in two-dimensional electrophoresis images.     

Image analysis of restriction enzyme fingerprint autoradiograms

A genome mapping system has been developed that reads and assembles data from clones analysed by restriction enzyme fragmentation and polyacrylamide gel electrophoresis. Input data for the system can be most effectively obtained by the use of a scanning densitometer and image-processing package, such as that described in this article. The image-processing procedure involves preliminary location of bands, cooperative tracking of lanes by correlation of adjacent bands, a precise densitometric pass, alignment of the marker bands with the standard, optional interactive editing, and normalization of the accepted bands.     

BBC microcomputer controlled field inversion gel electrophoresis

Agarose gel electrophoresis to separate DNA molecules is a widely used technique in molecular biology but there is an upper limit to the sizes that can be resolved. Pulsed field techniques have extended this limit but require expensive equipment. Here we describe a home-made control unit to interface conventional electrophoresis equipment to a BBC microcomputer for the purposes of field inversion gel electrophoresis.     

Covering with Ellipses

We address the problem of how to cover a set of required points by a small number of axis-parallel ellipses that avoid a second set of forbidden points. We study geometric properties of such covers and present an efficient randomized approximation algorithm for the cover construction. This question is motivated by a special pattern recognition task where one has to identify ellipse-shaped protein spots in two-dimensional electrophoresis images.