Rapid Absolute Determination Platform of Nucleic Acid for Point-of-care Testing

Nowadays nucleic acid tests are promising to be considered as point-of-care testing(POCT). However, no such devices are currently available that can perform all the functions, including absolute nucleic acid determination, worldwide on-site detection, rapid analysis and real-time results reporting via ubiquitous mobile networks simultaneously with full package and automated means of measurement. In this study, we presented a compact low-cost portable POC automated testing platform with all attributes mentioned above. A disposable self-priming compartmentalization(SPC) microfluidic chip is used to conduct isothermal amplification. The platform also includes a micro-computer controlled heating unit, an inexpensive optical imaging setup, and a mobile device with customized software. It may become a useful tool for the rapid on-site detection of infectious diseases as well as other pathogens.     

Nanostructure evolution studies of bulk polymer materials with synchrotron radiation: progress in method development

The prospects of a modern analysis of nanostructure evolution during the processing of polymer materials by means of scattering from synchrotron radiation are demonstrated in examples. The beam sources have gained stability, shortages are located in beamline setups and in method development for the quantitative analysis of voluminous data sets.By using the proposed multidimensional chord distribution function (CDF) analysis method, nanostructure information from small-angle X-ray scattering (SAXS) data are extracted and visualised. The method can be automated if the beamline setup is able to deliver a full data set with simple constraints. In this case even a simultaneous data evaluation is possible (while one pattern is accumulated, the previous one is analysed). The advantages of the method are demonstrated in a study of the straining of a thermoplastic elastomer. The possibilities of an automated analysis are demonstrated in an investigation of the crystallisation behaviour of high-pressure injection-moulded polyethylene (HPIM-PE). The achievable results of nanostructure analysis of polymer materials are discussed. It is shown that the time-resolved SAXS of polymer materials studied during a transformation and analysed by the CDF method is not just a powerful tool to investigate the relationship between structure and properties of materials; the information that can be gained concerning the processes that control nanostructure evolution is equally important. In the future the enlightenment of such relationships may help to tailor polymer materials with respect to their properties and, beyond that, to improve assessments concerning their aging.     

A high‐throughput bioanalytical platform using automated infusion for tandem mass spectrometric method optimization and its application in a metabolic stability screen

Liquid chromatography/tandem mass spectrometry (LC/MS/MS) is the bioanalytical method of choice to support plate‐based, in vitro early ADME (Absorption, Distribution, Metabolism and Excretion) screens such as metabolic stability (Metstab) assessment. MS/MS method optimization has historically been the bottleneck in this environment, where samples from thousands of discrete compounds are analyzed on a monthly basis, mainly due to the lack of a high‐quality commercially available platform to handle the necessary MS/MS method optimization steps for sample analysis by selected reaction monitoring (SRM) on triple quadrupole mass spectrometers. To address this challenge, we recently developed a highly automated bioanalytical platform by successfully integrating QuickQuan? 2.0, a unique high‐throughput solution featuring MS/MS method optimization by automated infusion, with a customized in‐house software tool in support of a Metstab screen. In this platform, a dual‐column setup running parallel chromatography was also implemented to reduce the bioanalytical cycle time for LC/MS/MS sample analysis. A set of 45 validation compounds was used to demonstrate the speed, quality and reproducibility of MS/MS method optimization, sample analysis, and data processing using this automated platform. Metstab results for the validation compounds in microsomes from multiple species (human, rat, mouse) showed good consistency within each batch, and also between batches conducted on different days. We have achieved and maintained a monthly throughput of 1300 compound assays representing 500 discrete compounds per instrument per month on this platform, and it has been used to generate metabolic stability data for more than 25 000 compounds to date with an overall success rate of more than 95%. Copyright © 2009 John Wiley & Sons, Ltd.     

Direct coupling of a flow–flow electromembrane extraction probe to LC-MS

A fully integrated and automated electromembrane extraction LC-MS (EME-LC-MS) system has been developed and characterized. Hyphenation of a flow–flow EME probe to LC-MS was accomplished by using an in-built 10-port switching valve of the LC-MS system. The 10-port switching valve decoupled the high pressure of the UHPLC-system from the low pressure required for operation of the EME-probe by automated switching between a sample extraction/analysis and a sample load position. In the sample load position the extracted analytes were loaded into a HPLC sample loop. By switching the valve to the sample extraction/analysis position the setup allowed simultaneous analysis of previously loaded analytes while extracting a new sample. Performance of the system was characterized with respect to precision and linearity (RSD < 2.5%, R²: 0.998) and the setup was applied for studying the in-vitro metabolism of methadone by rat liver microsomes. As the metabolic reaction proceeded, methadone and its metabolites were extracted and analyzed in parallel by LC-MS using either isocratic or gradient elution. Compared to a conventional in-vitro metabolism analysis based on protein precipitation followed by LC-MS analysis the fully automated EME-LC-MS system offers a significant time saving and in addition demonstrates increased sensitivity as the analytes were automatically enriched during the extraction process. The experiment revealed 6 to 16 times higher S/N ratios of the EME-LC-MS method compared to protein precipitation followed by LC-MS and thus concomitantly lower LOD and LOQ. The setup integrates a complete analytical workflow of rapid extraction, enrichment, separation and detection of analytes in a fully automated manner. These attributes make the developed system a powerful alternative approach for a wide range of analytical applications.     

单纯形自动优化的顺序注射分析系统

报道了具有自动优化功能的微机控制的顺序注射光度分析系统的研制。系统主要由注射汞、十位选择阀和带流通池的分光光度检测器构成。操作参数设定、数据采集和处理通过微机完成。采用改进单纯形方法进行系统优化,其算法集成到ＳＩＡ系统控制程序中使优化过程在微机的控制下自动完成。系统研究了ＳＩＡ钼蓝法测磷的操作条件对结果的影响。     

Extension of least squares spectral resolution algorithm to high-resolution lipidomics data

Lipidomics, which focuses on the global study of molecular lipids in biological systems, has been driven tremendously by technical advances in mass spectrometry (MS) instrumentation, particularly high-resolution MS. This requires powerful computational tools that handle the high-throughput lipidomics data analysis. To address this issue, a novel computational tool has been developed for the analysis of high-resolution MS data, including the data pretreatment, visualization, automated identification, deconvolution and quantification of lipid species. The algorithm features the customized generation of a lipid compound library and mass spectral library, which covers the major lipid classes such as glycerolipids, glycerophospholipids and sphingolipids. Next, the algorithm performs least squares resolution of spectra and chromatograms based on the theoretical isotope distribution of molecular ions, which enables automated identification and quantification of molecular lipid species. Currently, this methodology supports analysis of both high and low resolution MS as well as liquid chromatography-MS (LC-MS) lipidomics data. The flexibility of the methodology allows it to be expanded to support more lipid classes and more data interpretation functions, making it a promising tool in lipidomic data analysis.     

Kinetics Studies on a Multicomponent Knoevenagel−Michael Domino Reaction by an Automated Flow Reactor

The optimization of complex chemical reaction systems is often a troublesome and time-consuming process. The application of modern technologies, including automated reactors and analytics, opens the avenue for generating large data sets on chemical reaction processes in a short period of time. In this work, an automated flow reactor is used to present detailed kinetics and mechanistic studies about an amine-catalyzed Knoevenagel−Michael domino reaction to yield tetrahydrochromene derivatives. High-performance monoliths as catalyst supports and online coupled HPLC analysis allow for time-efficient data generation. We show that the two-step multicomponent domino reaction does not follow the kinetics of consecutive reaction steps proceeding independently from each other. Instead, the starting materials of both individual reactions compete for the active sites on the heterogeneous catalyst, which lowers the rate constants of both steps. This knowledge was used to implement a more efficient experimental setup which increased the turnover numbers of the catalyst, without adjusting common reaction parameters like temperature, reaction time, and concentrations.     

Automated analysis of proton NMR spectra from combinatorial rapid parallel synthesis using self-organizing maps

It is now quite routine to acquire proton NMR spectra of compounds in 96-well plates prepared in a rapid parallel synthesis fashion using a flow-NMR automation setup. However, the analysis of 96 NMR spectra obtained in this manner is often laborious and painstakingly slow. We have developed a new, automated method for rapidly analyzing 96 NMR spectra of compounds synthesized in an 8 x 12 matrix using self-organizing maps (SOM). This unsupervised neural network is capable of clustering together NMR spectra containing a common pattern of -R groups and identifying outliers from within such clusters. Analysis of these outlier spectra can quickly help indicate the presence of undesired products, impurities, starting materials, and other unexpected errors in a 96-well plate synthesis by focusing the chemists' attention on the aberrant NMR spectra. Thus, SOM can be a valuable tool in performing efficient quality control on combinatorial libraries.     

A Multifunctional Microfluidic Platform for High-Throughput Experimentation of Electroorganic Chemistry

Electroorganic synthesis is a promising tool to design sustainable transformations and discover new reactivities. However, the added setup complexity caused by electrodes in the system impedes efficient screening of reaction conditions. Herein, we present a microfluidic platform that enables automated high-throughput experimentation (HTE) for electroorganic synthesis at a 15-microliter scale. Two HTE modules are demonstrated: 1) the rapid electrochemical reaction condition screening for a radical–radical cross-coupling reaction on micro-fabricated interdigitated electrodes, and 2) measurements of kinetics for mediated anodic oxidations using the microliter-scale cyclic voltammetry. The presented modular approach could be deployed for a range of other electroorganic chemistry applications beyond the demonstrated functionalities.     

A fully robust PARAFAC method for analyzing fluorescence data

Parallel factor analysis (PARAFAC) is a widespread method for modeling fluorescence data by means of an alternating least squares procedure. Consequently, the PARAFAC estimates are highly influenced by outlying excitation–emission landscapes (EEM) and element‐wise outliers, like for example Raman and Rayleigh scatter. Recently, a robust PARAFAC method that circumvents the harmful effects of outlying samples has been developed. For removing the scatter effects on the final PARAFAC model, different techniques exist. Newly, an automated scatter identification tool has been constructed. However, there still exists no robust method for handling fluorescence data encountering both outlying EEM landscapes and scatter. In this paper, we present an iterative algorithm where the robust PARAFAC method and the scatter identification tool are alternately performed. A fully automated robust PARAFAC method is obtained in that way. The method is assessed by means of simulations and a laboratory‐made data set. Copyright © 2009 John Wiley & Sons, Ltd.     

Photoreactive fluorinated polyimide protected by tetrahydropyranyl (THP) group based on chemical amplification: Acid generation in polyimide film and lithographic properties

The photochemistry of photoacid generator (PAG), diphenyliodonium 9,10-dimethoxyanthracene-2-sulfonate (DIAS) and diphenyliodonium 8-anilinonaphthalene-1-sulfonate (DIANS) was investigated in both alkalinesoluble polyimide (6FDA-AHHFP) and novolak films. The quantum yields of photodissociation of DIAS and DIANS in both 6FDA-AHHFP and novolak films. The quantum yields of photodissociation of DIAS and DIANS in both 6FDA-AHHFP and novolak films were determined as 0.11, 0.21, 0.12 and 0.26, respectively. On the other hand, the quantum yields for acid generation from DIAS and DIANS in both of these films were 0.07, 0.18, 0.09 and 0.22, respectively, in the presence of an acid indicator. These results indicate that the values of the quantum yields of photodissociation and photoacid formation for DIAS and DIANS in 6FDA-AHHFP film are lower than those in novolak film. In order to elucidate the lowering of the quantum yields in 6FDA-AHHFP film, fluorescence quenchings of sodium 9,10-dimethoxy-anthracene-2-sulfonate and ammonium 8-anilinonaphthalene-1-sulfonate by a model compound of polyimide was carried out in acetonitrile. The fluorescences of these two salts were efficiently quenched by the model compound with the diffusion-controlled rate constant in acetonitrile, suggesting that a strong electron-accepting capability of the imide carbonyl group may hinder the electron transfer process within PAG molecules in 6FDA-AHHFP film. Although a polyimide (6F-THP) protected by tetrahydropyranyl group is insoluble in aqueous base, 6F-THP film containing PAG became soluble in a 2:1 mixture of 2.0 wt% tetramethylammonium hydroxide (TMAH) and methanol by exposure to 365 nm light and successive post-exposure baking (PEB) at 120°C for 10 min. The sensitivity and contrast of 6F-THP with DIANS after the PEB conditions mentioned above were 110 mJ/cm² and 3.7, respectively. A high-resolution pattern with a good profile was transferred into the 3 μm thickness of the 6F-THP film.     

Imaging as a tool for improving length and accuracy of sequence analysis in automated fluorescence-based DNA sequencing

A new method of signal analysis for automated fluorescence-based DNA sequencing is presented. Signal resolution is a limiting factor in obtaining accurate sequence information beyond 400-450 nucleotides per gel lane. We have developed a computer program for the imaging of DNA bands in sequencing gels. The image analysis shows that distortions in the shapes of the bands decrease resolution of peaks observed served in the standard data plots. Reconstruction of the undistorted band shape prior to signal analysis substantially improves the resolution of peaks and may improve the accuracy and length of the contiguous sequence read. Image analysis identified other factors limiting the accuracy and length of automated DNA sequence analysis and provided a tool for evaluating various remedies. Our techniques should also be applicable in other systems, for example, in gel electrophoresis of proteins and DNA restriction fragments, and in scranning densitometry.     

On-line preparation of microsamples prior to CE

An experimental setup is presented here for the automated analysis of microsamples, based on the on-line coupling of a capillary SPE module and a CE unit using a two-position six-port valve, an open-closed valve to isolate electrically the sample preparation from the CE unit and a "T" interface. A C18 trapping microcolumn (dimensions 2.5 cm x 100 microm id x 360 microm od) was used for the SPE step. The utility of the proposed experimental setup was demonstrated by applying it to the determination of quinolone antibiotics in serum microsamples, which was efficiently carried out in less than 20 min (4 min for protein denaturation and 15 min for analytes preconcentration and CE-UV separation-determination). A complete optimization study was performed for preconcentration and cleanup of quinolones, the coupling of sample preparation module to the CE unit and electrophoretic separation of quinolones. A preconcentration factor of 10.4 was achieved. The volume injected with the proposed method was 125 nL versus 160 nL introduced by hydrodynamic injection. The volume required for the analysis was 2 microL, which makes the proposed experimental setup very useful for the analysis of microsamples in fields of current interest such as metabolomics or proteomics.     

Automated Generation and Reactions of 3‐Hydroxymethylindoles in Continuous‐Flow Microreactors

An automated sequential approach for the generation and reactions of 3‐hydroxymethylindoles in continuous‐flow microreactors is described. Consecutive halogen–magnesium exchanges of four 3‐iodoindoles followed by addition to three aldehydes provided twelve 3‐hydroxymethylindoles in a multi‐microreactor setup. The synthetic flow strategy could be coupled with an in line continuous liquid–liquid extraction workup protocol for each reaction. Further elaboration of each of these indoles within the fluidic setup was achieved by acid‐catalysed nucleophilic substitutions with allyltrimethylsilane and methanol used as nucleophiles. Overall, a set of four 3‐iodoindoles was converted into thirty‐six indole derivatives by a range of transformations including iodo–magnesium exchange/electrophile trapping and acid‐catalysed nucleophilic substitution in a fully automated sequential fashion.     

Procrustes rotation as a diagnostic tool for projection pursuit analysis

Projection pursuit (PP) is an effective exploratory data analysis tool because it optimizes the projection of high dimensional data using distributional characteristics rather than variance or distance metrics. The recent development of fast and simple PP algorithms based on minimization of kurtosis for clustering data has made this powerful tool more accessible, but under conditions where the sample-to-variable ratio is small, PP fails due to opportunistic overfitting of random correlations to limiting distributional targets. Therefore, some kind of variable compression or data regularization is required in these cases. However, this introduces an additional parameter whose optimization is manually time consuming and subject to bias. The present work describes the use of Procrustes analysis as diagnostic tool that can be used to evaluate the results of PP analysis in an efficient manner. Through Procrustes rotation, the similarity of different PP projections can be examined in an automated fashion with “Procrustes maps” to establish regions of stable projections as a function of the parameter to be optimized. The application of this diagnostic is demonstrated using principal components analysis to compress FTIR spectra from ink samples of ten different brands of pen, and also in conjunction with regularized PP for soybean disease classification.     

Automated analysis of 13C/12C ratios in CO2 and dissolved inorganic carbon for ecological and environmental applications

Stable carbon isotope ratios (13C/12C) are a valuable tool for studying a wide range of environmental processes, including carbon cycling and subsurface microbial activity. Recent advances in automated analysis provide the opportunity to increase greatly the ease and consistency of isotopic analysis. This study evaluated an automated headspace sampler linked to a commercially available CO2 preconcentration system and continuous flow isotope ratio mass spectrometer. Field sampling and analysis methods are illustrated for delta13C of soil respired CO2, from both tracer and natural abundance experiments, and dissolved inorganic carbon from contaminated groundwater. The automated system demonstrated accuracy, precision, and linearity, with standard errors below 0.1 per thousand for replicate gas standards run at concentrations varying five-fold. It measured 40 samples per 10-hour run, with concentrations ranging from ppb to percentage levels. In the field, gas samples were injected into nitrogen-filled autosampler vials, thereby allowing use of small sample volumes, control of analyte concentration, and direct analysis by the automated system with no further preparation. A significant linear relationship between standard concentrations and peak area allows for accurate estimates of sample CO2 concentration from the mass spectrometric data. The ability to analyze multiple small-volume samples with minimal off-line preparation should enhance the application of isotopes to well-replicated field experiments for process-level studies and spatial and temporal scaling.     

Opportunities and challenges in applying machine learning to voltammetric mechanistic studies

Voltammetry is a powerful tool for providing quantitative mechanistic information associated with a broad range of chemically or biologically important electron transfer processes. An important step in voltammetric data analysis is to compare experimental data with those derived by simulations based on a mechanism chosen by the experimenter to determine the ‘best fit’, which can be achieved either heuristically or by a computationally supported automated method. In recent years, machine learning methods have emerged as a powerful tool in mechanism classification and parametrisation, owing to the rapid increase in computing power and widespread accessibility of machine learning platforms. This opinion article gives an overview of the historical development and current status of machine learning in this field, highlights the opportunities and challenges, and predicts possible future directions.     

Harvesting chemical information from the Internet using a distributed approach: ChemXtreme

The Internet is a comprehensive resource of chemical information which is at the same time largely unstructured. It provides a wealth of scientific information such as experimental data and requires a suitable automated data mining and analysis tool for its meaningful exploration. The Java based software presented here, ChemXtreme, is developed for harvesting chemical information from the Internet employing the Google API in combination with a distributed client/server text analysis architecture based on JavaRMI. It represents the first and until now the only toolkit for automated structured data retrieval from the Internet which is itself open source. ChemXtreme employs the "search the search engine" strategy, where the URLs returned from the search engine are analyzed further via textual pattern analysis. This process resembles the manual analysis of the hit list, where relevant data are captured and, by means of human intervention, are mined into a format suitable for further analysis. ChemXtreme on the other hand transforms chemical information automatically into a structured format suitable for storage in databases and further analysis and also provides links to the original information source. The query data retrieved from the search engine by the server is encoded, encrypted, and compressed and then sent to all the participating active clients in the network for parsing. Relevant information identified by the clients on the retrieved Web sites is sent back to the server, verified, and added to the database for data mining and further analysis. The distributed further analysis of URLs in a client/server architecture scales very favorably, thus producing only minimal overhead.     

Setup for high-throughput impedance screening of gas-sensing materials

This paper reports on the setup for a high-throughput impedance measurement system that allows rapid screening of the electrical and dielectrical properties of solid-state sample libraries in variable atmospheres and temperatures. Using multielectrode arrays, most time-consuming steps in the workflow are parallelized. In addition, an approach for automated data evaluation of impedance spectra is presented. For reasons of verification of robust measuring results and reproducibility, screening results of a sample library composed of doped indium(III) oxide as a resistive-type gas-sensing material are discussed on the basis of the determined sensitivities focusing temperature and testing gas gradients.     

Automated analysis of SEM X-ray spectral images: a powerful new microanalysis tool.

Spectral imaging in the scanning electron microscope (SEM) equipped with an energy-dispersive X-ray (EDX) analyzer has the potential to be a powerful tool for chemical phase identification, but the large data sets have, in the past, proved too large to efficiently analyze. In the present work, we describe the application of a new automated, unbiased, multivariate statistical analysis technique to very large X-ray spectral image data sets. The method, based in part on principal components analysis, returns physically accurate (all positive) component spectra and images in a few minutes on a standard personal computer. The efficacy of the technique for microanalysis is illustrated by the analysis of complex multi-phase materials, particulates, a diffusion couple, and a single-pixel-detection problem.