An ELISA-like time-resolved fluorescence immunoassay for microcystin detection

Background: A time-resolved fluorescence immunoassay (TRFIA), based on anti-microcystin-LR (MCLR) monoclonal antibodies (MAbs) and europium-labeled antimouse IgG conjugate, was first developed for microcystin detection. Methods: Anti-MCLR MAbs were prepared by a standard method, and the attained MAbs showed a good cross reactivity with MCLR, MCRR and MCYR. The TRFIA was performed in an indirect competitive mode. The detection method of TRFIA was compared with indirect competitive enzyme-linked immunosorbent assay (ELISA) and high-performance liquid chromatography (HPLC). Results: The TRFIA exhibited a typical sigmoidal response for MCLR at concentrations of 0.005-50 ng/ml, with a wide quantitative range between 0.01 and 10 ng/ml, indicating the broadest detective range and the most sensitive of all the methods for microcystins (MCs) detection. Additionally, the TRFIA maintained good reliability through its quantitative range, as evidenced by low coefficients of variation (1.6-12.2%). The toxin data of algal samples assayed from TRFIA were in the same range as those with ELISA and HPLC, implying that the method was reliable and practical for the detection of MCs. Conclusions: The TRFIA may offer a valuable alternative or a substitute for conventional ELISA for microcystin detection. (C) 2004 Elsevier B.V. All rights reserved.

Separation and detection of chlorpromazine hydrochloride and promethazine hydrochloride using electrochemiluminescence followed by capillary electrophoresis

Phenothiazine drugs, chlorpromazine hydrochloride (CPZ) and promethazine hydrochloride (PMZ), were determined with Ru(bpy)(3)(2+) electrochemiluminescene by the capillary electrophoresis (CE-ECL). It was found that both CPZ and PMZ could produce an intermediate that acted as coreactants to react with Ru(bpy)(3)(2+) to produce excited states which were capable of emitting light. This CE-ECL detection method had high sensitivity, good selectivity and reproducibility for CPZ and PMZ determination.

Detection of neurotransmitters by a light scattering technique based on seed-mediated growth of gold nanoparticles

A simple light scattering detection method for neurotransmitters has been developed, based on the growth of gold nanoparticles. Neurotransmitters (dopamine, L-dopa, noradrenaline and adrenaline) can effectively function as active reducing agents for generating gold nanoparticles, which result in enhanced light scattering signals. The strong light scattering of gold nanoparticles then allows the quantitative detection of the neurotransmitters simply by using a common spectrofluorometer.

Colorimetric detection of mercury ion (Hg2+) based on DNA oligonucleotides and unmodified gold nanoparticles sensing system with a tunable detection range

Here, we report a simple and Sensitive colorimetric detection method for Hg2+ ions With a tunable detection range based on DNA oligonucleotides and unmodified gold nanoparticles (DNA/AuNPs) sensing system. Complementary DNA strands with T-T mismatches could effectively protect AuNPs from salt-induced aggregation. While in the presence of Hg2+ ions T-Hg2+-T coordination chemistry leads to the formation of DNA duplexes, and AuNPs are less well protected thus aggregate at the same salt concentration, accompanying by color change from red to blue. By rationally varying the number of T-T mismatches in DNA oligonucleotides, the detection range could be tuned.

Fluorescent conjugated polymer-stabilized gold nanoparticles for sensitive and selective detection of cysteine

We report a new fluorescent detection method for cysteine based on one-step prepared fluorescent conjugated polymer-stabilized gold nanoparticles. The as-prepared fluorescent conjugated polymer-stabilized gold nanoparticles fluoresce weakly due to the fluorescence resonance energy transfer between the fluorophore and the gold nanoparticles. Upon the addition of cysteine, a thiol-containing amino acid, the fluorescence of the colloidal solution increases significantly, indicating that cysteine can modulate the energy transfer between fluorophore and gold. This phenomenon then allows for sensitive detection of cysteine with a limit of detection (LOD) of 25 nM. The linear range of determination of cysteine is from 5 x 10(-8) to 4 x 10(-6) M. None of the other amino acids found in proteins interferes with the determination. Moreover, due to the excellent protecting ability of the fluorescent conjugated polymers, the synthesis of metal nanoparticles and modifying with fluorophores can be accomplished within one step, which makes our method much simpler than conventional methods. We also expect that it will be possible to detect other biologically important analytes based on the fluorescent conjugated polymer-stabilized metal nanoparticles.

Real-time PCR microfluidic devices with concurrent electrochemical detection

Electrochemistry-based detection methods hold great potential towards development of hand-held nucleic-acid analyses instruments. In this work, we demonstrate the implementation of in situ electrochemical (EC) detection method in a microfluidic flow-through EC-qPCR (FTEC-qPCR) device, where both the amplification of the target nucleic-acid sequence and subsequent EC detection of the PCR amplicon are realized simultaneously at selected PCR cycles in the same device. The FTEC-qPCR device utilizes methylene blue (MB), an electroactive DNA intercalator, for electrochemical signal measurements in the presence of PCR reagent components. Our EC detection method is advantageous, when compared to other existing EC methods for PCR amplicon analysis, since FTEC-qPCR does not require probe-modified electrodes, or asymmetric PCR, or solid-phase PCR. Key technical issues related to surface passivation, electrochemical measurement, PCR inhibition by metal electrode, bubble-free PCR, were investigated. By controlling the concentration of MB and the exposure of PCR mixture to the bare metal electrode, we successfully demonstrated electrochemical measurement of MB in solution-phase, symmetric PCR by amplifying a fragment of lambda phage DNA.

Progress in amperometric detection for capillary electrophoresis

As a high efficiency separation technique, capillary electrophoresis(CE) has been widely used in various fields of analytical science. Amperometry is one of the most sensitive electrochemical detection methods in CE. The capillary/electrode decoupling mechanism, applications,of new electrode systems in CE, detection cell technique are discussed in detail. Amperometric detection is compatible with microfabricated CE chips and will make the concept of lab-on-a-chip become a reality. Because of these progresses, amperometry is becoming a widely acceptable detection method,for more chemical and biological analytes.

End-column amperometric detection of 5-fluorouracil by capillary zone electrophoresis with a carbon fiber microelectrode

A rapid and sensitive detection method for the determination of 5-fluorouracil(5-FU) in real samples such as human urine and bovine serum albumin (BSA) was described. A carbon fiber microdisk electrode was used to perform end-column amperometric detection in capillary zone electrophoresis. The detection limit was as low as 2.5x10(-7) M and the wider linear range for the concentration was between 5x10(-6) and 1x10(-4) M with a correlation coefficient of 0.995.

Simultaneous determination of monoamine and amino acid neurotransmitters in rat endbrain tissues by pre-column derivatization with high-performance liquid chromatographic fluorescence detection and mass spectrometric identification

A sensitive and efficient method for simultaneous determination of glutamic acid (Glu), gamma-amino-butyric acid (GABA), dopamine (DA), 5-hydroxytryptamine (5-HT) and 5-hydroxyindole acetic acid (5-HIAA) in rat endbrains was developed by high-performance liquid chromatography (HPLC) with fluorescence detection and on-line mass spectrometric identification following derivatization with 1,2-benzo-3,4-dihydrocarbazole-9-ethyl chloroformate (BCEOC). Different parameters which influenced derivatization and separation were optimized. The complete separation of five neurotransmitter (NT) derivatives was performed on a reversed-phase Hypersil BDS-C-18 column with a gradient elution. The rapid structure identification of five neurotransmitter derivatives was carried out by on-line mass spectrometry with electrospray ionization (ESI) source in positive ion mode, and the BCEOC-labeled derivatives were characterized by easy-to-interpret mass spectra. Stability of derivatives, repeatability, precision and accuracy were evaluated and the results were excellent for efficient HPLC analysis. The quantitative linear range of five neurotransmitters were 2.441-2 x 10(4) nM, and limits of detection were in the range of 0.398-1.258 nM (S/N = 3:1). The changes of their concentrations in endbrains of three rat groups were also studied using this HPLC fluorescence detection method. The results indicated that exhausting exercise could obviously influence the concentrations of neurotransmitters in rat endbrains. The established method exhibited excellent validity, high sensitivity and convenience, and provided a new technique for simultaneous analysis of monoamine and amino acid neurotransmitters in rat brain. (C) 2008 Elsevier B.V. All rights reserved.

基于Zernike矩边缘检测的焊缝信息获取

针对目前焊缝坐标提取方法存在精度较低,难于实现视觉引导的机器人激光焊接高速度、高精度的要求,提出一种基于Zernike正交矩的曲线焊缝位置坐标信息获取算法,该算法首先采用Zernike边缘检测算法识别焊缝边缘,然后提取出焊缝的中心线,最后计算出该中心线的亚像素坐标。通过试验验证了该算法的可行性。

基于Zernike正交矩的图像亚像素边缘检测算法改进

介绍了Zernike矩及基于Zernike矩的图像亚像素边缘检测原理,针对Ghosal提出的基于Zernike矩的亚像素图像边缘检测算法检测出的图像存在边缘较粗及边缘亚像素定位精度低等不足,提出了一种改进算法.推导了7×7 Zernike矩模板系数,提出一种新的边缘判断依据.改进的算法能较好检测图像边缘并实现了较高的边缘定位.最后,设计了3组不同的实验.实验结果同Canny算子及Ghosal算法相比,证明了改进算法的优越性.

基于数学形态学的激光拼焊熔池图像处理研究

基于拼板激光焊接工程中的实时检测系统,应用数学形态学中的相关图像处理技术,提出了一种新的熔池图像处理流程模型,并通过实验得到了三种清晰的熔池边缘图像,同时验证了该模型的正确性。将算法与经典算法进行比较,证明了该算法对于激光拼焊的适用性和鲁棒性。

地震岩性与物性联合反演技术研究和应用

This paper studies how to more effectively invert seismic data and predict reservoir under complicated sedimentary environment, complex rock physical relationships and fewer drills in offshore areas of China. Based on rock physical and seismic amplitude-preserving process, and according to depositional system and laws of hydrocarbon reservoir, in the light of feature of seismic inversion methods present applied, series methods were studied. A joint inversion technology for complex geological condition had been presented, at the same time the process and method system for reservoir prediction had been established. This method consists four key parts. 1)We presented the new conception called generalized wave impedance, established corresponding inversion process, and provided technical means for joint inversion lithology and petrophysical on complex geological condition. 2)At the aspect of high-resolution nonlinear seismic wave impedance joint inversion, this method used a multistage nonlinear seismic convolution model rather than conventional primary structure Robinson seismic convolution model, and used Caianiello neural network implement inversion. Based on the definition of multistage positive and negative wavelet, it adopted both deterministic and statistical physical mechanism, direct inversion and indirect inversion. It integrated geological knowledge, rock physical theory, well data, and seismic data, and improved the resolution and anti-noise ability of wave impedence inversion. 3)At the aspect of high-resolution nonlinear reservoir physical property joint inversion, this method used nonlinear rock physical model which introduced convolution model into the relationship between wave impedance and porosity/clay. Through multistage decomposition, it handles separately the large- and small-scale components of the impedance-porosity/clay relationships to achieve more accurate rock physical relationships. By means of bidirectional edge detection with wavelets, it uses the Caianiello neural network to finish statistical inversion with combined applications of model-based and deconvolution-based methods. The resulted joint inversion scheme can integrate seismic data, well data, rock physical theory, and geological knowledge for estimation of high-resolution petrophysical parameters. 4)At the aspect of risk assessment of lateral reservoir prediction, this method integrated the seismic lithology identification, petrophysical prediction, multi-scale decomposition of petrophysical parameters, P- and H-spectra, and the match relationship of data got from seismics, well logging and geology. It could describe the complexity of medium preferably. Through applications of the joint inversion of seismic data for lithologic and petrophysical parameters in several selected target areas, the resulted high-resolution lithologic and petrophysical sections(impedance, porosity, clay) show that the joint inversion can significantly improve the spatial description of reservoirs in data sets involving complex deposits. It proved the validity and practicality of this method adequately.

高分辨率非线性岩性物性联合反演方法和应用

In the prediction of complex reservoir with high heterogeneities in lithologic and petrophysical properties, because of inexact data (e.g., information-overlapping, information-incomplete, and noise-contaminated) and ambiguous physical relationship, inversion results suffer from non-uniqueness, instability and uncertainty. Thus, the reservoir prediction technologies based on the linear assumptions are unsuited for these complex areas. Based on the limitations of conventional technologies, the thesis conducts a series of researches on various kernel problems such as inversions from band-limited seismic data, inversion resolution, inversion stability, and ambiguous physical relationship. The thesis combines deterministic, statistical and nonlinear theories of geophysics, and integrates geological information, rock physics, well data and seismic data to predict lithologic and petrophysical parameters. The joint inversion technology is suited for the areas with complex depositional environment and complex rock-physical relationship. Combining nonlinear multistage Robinson seismic convolution model with unconventional Caianiello neural network, the thesis implements the unification of the deterministic and statistical inversion. Through Robinson seismic convolution model and nonlinear self-affine transform, the deterministic inversion is implemented by establishing a deterministic relationship between seismic impedance and seismic responses. So, this can ensure inversion reliability. Furthermore, through multistage seismic wavelet (MSW)/seismic inverse wavelet (MSIW) and Caianiello neural network, the statistical inversion is implemented by establishing a statistical relationship between seismic impedance and seismic responses. Thus, this can ensure the anti-noise ability. In this thesis, direct and indirect inversion modes are alternately used to estimate and revise the impedance value. Direct inversion result is used as the initial value of indirect inversion and finally high-resolution impedance profile is achieved by indirect inversion. This largely enhances inversion precision. In the thesis, a nonlinear rock physics convolution model is adopted to establish a relationship between impedance and porosity/clay-content. Through multistage decomposition and bidirectional edge wavelet detection, it can depict more complex rock physical relationship. Moreover, it uses the Caianiello neural network to implement the combination of deterministic inversion, statistical inversion and nonlinear theory. Last, by combined applications of direct inversion based on vertical edge detection wavelet and indirect inversion based on lateral edge detection wavelet, it implements the integrative application of geological information, well data and seismic impedance for estimation of high-resolution petrophysical parameters (porosity/clay-content). These inversion results can be used to reservoir prediction and characterization. Multi-well constrains and separate-frequency inversion modes are adopted in the thesis. The analyses of these sections of lithologic and petrophysical properties show that the low-frequency sections reflect the macro structure of the strata, while the middle/high-frequency sections reflect the detailed structure of the strata. Therefore, the high-resolution sections can be used to recognize the boundary of sand body and to predict the hydrocarbon zones.

Remote Detection and Identification of Organic Remains: An Assessment of Archaeological Potential

This paper reviews the various methods of using natural or induced light spectra as analytical tools in forensic archaeology. Chemical identi?cation can be made at long range and wide scale (tens of metres) down to short range and very small scale (nanometres). The identi?cation of organic gases and materials has used either chemical capture and chromatography, induced (laser or ultraviolet) light sources or laser Raman microscope spectroscopy. The remote gas detection method relies on the identi?cation of atmospheric gases by their characteristic light spectra. Modern spectroscopes can detect gases down to a few parts per million of an atmosphere. When the light source (wavelength) and direction is controlled, so laser-induced spectroscopy may be used to monitor the emission of gases such methane from buried organic remains. In order to identify the location of buried organic remains, a grid of sample points must be established using a base line or global
positioning system. When matched to base line or ground-positioning systems, such data can be manipulated by geographical information system packages. This would enable pinpointing of anomalies for excavation or avoidance. Microscope-based laser Raman spectroscopy can be used to directly analyse captured gases, swabs and surfaces without the problems of long-path detection. Copyright ? 2002 John Wiley & Sons, Ltd.