Use of chemometrics to optimize a glucose assay on a paper microfluidic platform.

We describe the use of a chemometrics-based computational platform to optimize a glucose assay on a microfluidic paper-based analytical device (μPAD). Glucose is colorimetrically detected in the presence of glucose oxidase (GOx), horseradish peroxidase (HRP), and potassium iodide (KI). Using a Y-shaped paper microfluidic chip, the concentration of glucose, volume of reagents, and the length and width of the microfluidic channel were examined.

A simple graphical approach to predict local residue conformation using NMR chemical shifts and density functional theory.

The dependency of amino acid chemical shifts on φ and ψ torsion angle is, independently, studied using a five-residue fragment of ubiquitin and ONIOM(DFT:HF) approach. The variation of absolute deviation of (13) C(α) chemical shifts relative to φ dihedral angle is specifically dependent on secondary structure of protein not on amino acid type and fragment sequence. This dependency is observed neither on any of (13) C(β) , and (1) H(α) chemical shifts nor on the variation of absolute deviation of (13) C(α) chemical shifts relative to ψ dihedral angle.

An improved alkaline direct formate paper microfluidic fuel cell.

Paper-based microfluidic fuel cells (MFCs) are a potential replacement for traditional FCs and batteries due to their low cost, portability, and simplicity to operate. In MFCs, separate solutions of fuel and oxidant migrate through paper due to capillary action and laminar flow and, upon contact with each other and catalyst, produce electricity. In the present work, we describe an improved microfluidic paper-based direct formate FC (DFFC) employing formate and hydrogen peroxide as the anode fuel and cathode oxidant, respectively.

CS-MINER: A Tool for Association Mining in Binding-Database.

This paper introduces the algorithms, implementation strategies, features, and applications of CS-MINER, a tool for visualization and analysis of drug-like chemical space. The CS-MINER is the abstract abbreviation for Chemical Space Miner and correlates the medicinal target space and chemical space, in a systematic way. The database in this software consists of a large collection of drug-like molecules.

How can chemometrics improve microfluidic research?

Chemometrics has the potential to embolden microfluidics to become that enabling technology for so long sought after. In this Feature article, we describe a historical perspective on microfluidics and its current challenges, a perspective on chemometric methods including response surface methodology (RSM), and how a combination of artificial neural network with experimental design (ANN-ED) have demonstrated promise in addressing basic microfluidic problems.

Elimination of chromatographic and mass spectrometric problems in GC-MS analysis of Lavender essential oil by multivariate curve resolution techniques: Improving the peak purity assessment by variable size moving window-evolving factor analysis.

In analysis of complex natural matrices by gas chromatography-mass spectrometry (GC-MS), many disturbing factors such as baseline drift, spectral background, homoscedastic and heteroscedastic noise, peak shape deformation (non-Gaussian peaks), low S/N ratio and co-elution (overlapped and/or embedded peaks) lead the researchers to handle them to serve time, money and experimental efforts. This study aimed to improve the GC-MS analysis of complex natural matrices utilizing multivariate curve resolution (MCR) methods. In addition, to assess the peak purity of the two-dimensional data, a method called variable size moving window-evolving factor analysis (VSMW-EFA) is introduced and examined.

Experimental design in analytical chemistry--part II: applications.

This paper reviews the applications of experimental design to optimize some analytical chemistry techniques such as extraction, chromatography separation, capillary electrophoresis, spectroscopy, and electroanalytical methods.

Experimental design in analytical chemistry--part I: theory.

This paper reviews the main concepts of experimental design applicable to the optimization of analytical chemistry techniques. The critical steps and tools for screening, including Plackett-Burman, factorial and fractional factorial designs, and response surface methodology such as central composite, Box-Behnken, and Doehlert designs, are discussed. Some useful routines are also presented for performing the procedures.

The use of multivariate curve resolution methods to improve the analysis of muramic acid as bacterial marker using gas chromatography-mass spectrometry: an alternative method to gas chromatography-tandem mass spectrometry.

In analysis of muramic acid (MA) as bacterial marker, two dominant disturbing factors lead the researchers to use gas chromatography-tandem mass spectrometry (GC-MS/MS) technique instead of gas chromatography-mass spectrometry (GC-MS). These factors are the trace concentration of MA and fundamental disturbance of base line mass channels in GC-MS technique. This study aimed to utilize multivariate curve resolution (MCR) methods combined with GC-MS to improve the analysis of MA.

Integrated One-Against-One Classifiers as Tools for Virtual Screening of Compound Databases: A Case Study with CNS Inhibitors.

A total of 21 833 inhibitors of the central nervous system (CNS) were collected from Binding-database and analyzed using discriminant analysis (DA) techniques. A combination of genetic algorithm and quadratic discriminant analysis (GA-QDA) was proposed as a tool for the classification of molecules based on their therapeutic targets and activities. The results indicated that the one-against-one (OAO) QDA classifiers correctly separate the molecules based on their therapeutic targets and are comparable with support vector machines.

Thorough tuning of the aspect ratio of gold nanorods using response surface methodology.

In the present work a central composite design based on response surface methodology (RSM) is employed for fine tuning of the aspect ratios of seed-mediated synthesized gold nanorods (GNRs). The relations between the affecting parameters, including ratio of l-ascorbic acid to Au(3+) ions, concentrations of silver nitrate, CTAB, and CTAB-capped gold seeds, were explored using a RSM model. It is observed that the effect of each parameter on the aspect ratio of developing nanorods highly depends on the value of the other parameters.

Multivariate curve resolution-particle swarm optimization: a high-throughput approach to exploit pure information from multi-component hyphenated chromatographic signals.

Multivariate curve resolution-particle swarm optimization (MCR-PSO) algorithm is proposed to exploit pure chromatographic and spectroscopic information from multi-component hyphenated chromatographic signals. This new MCR method is based on rotation of mathematically unique PCA solutions into the chemically meaningful MCR solutions. To obtain a proper rotation matrix, an objective function based on non-fulfillment of constraints is defined and is optimized using particle swarm optimization (PSO) algorithm.

Determination of volatile components of green, black, oolong and white tea by optimized ultrasound-assisted extraction-dispersive liquid-liquid microextraction coupled with gas chromatography.

Ultrasound assisted extraction (UAE) followed by dispersive liquid-liquid microextraction (DLLME) was used for extraction and preconcentration of volatile constituents of six tea plants. The preconcentrated compounds were analyzed by gas chromatography-mass spectrometry (GC-MS). Totally, 42 compounds were identified and caffeine was quantitatively determined.

Detection of addition of barley to coffee using near infrared spectroscopy and chemometric techniques.

The current study presents an application of near infrared spectroscopy for identification and quantification of the fraudulent addition of barley in roasted and ground coffee samples. Nine different types of coffee including pure Arabica, Robusta and mixtures of them at different roasting degrees were blended with four types of barley. The blending degrees were between 2 and 20 wt% of barley.

Chromatographic fingerprint analysis of secondary metabolites in citrus fruits peels using gas chromatography-mass spectrometry combined with advanced chemometric methods.

Multivariate curve resolution (MCR) and multivariate clustering methods along with other chemometric methods are proposed to improve the analysis of gas chromatography-mass spectrometry (GC-MS) fingerprints of secondary metabolites in citrus fruits peels. In this way, chromatographic problems such as baseline/background contribution, low S/N peaks, asymmetric peaks, retention time shifts, and co-elution (overlapped and embedded peaks) occurred during GC-MS analysis of chromatographic fingerprints are solved using the proposed strategy. In this study, first, informative GC-MS fingerprints of citrus secondary metabolites are generated and then, whole data sets are segmented to some chromatographic regions.

Navigating Drug-Like Chemical Space of Anticancer Molecules Using Genetic Algorithms and Counterpropagation Artificial Neural Networks.

A total of 6289 drug-like anticancer molecules were collected from Binding database and were analyzed by using the classification techniques. The collected molecules were encoded to a diverse set of descriptors, spanning different physical and chemical properties of the molecules. A combination of genetic algorithms and counterpropagation artificial neural networks was used for navigating the generated drug-like chemical space and selecting the most relevant molecular descriptors.

Resolution and quantification of complex mixtures of polycyclic aromatic hydrocarbons in heavy fuel oil sample by means of GC × GC-TOFMS combined to multivariate curve resolution.

Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS) combined to multivariate curve resolution-alternating least-squares (MCR-ALS) is proposed for the resolution and quantification of very complex mixtures of compounds such as polycyclic aromatic hydrocarbons (PAHs) in heavy fuel oil (HFO). Different GC × GC-TOFMS data slices acquired during the analysis of HFO samples and PAH standards were simultaneously analyzed using the MCR-ALS method to resolve the pure component elution profiles in the two chromatographic dimensions as well as their pure mass spectra. Outstandingly, retention time shifts within and between GC × GC runs were not affecting the results obtained using the proposed strategy and proper resolution of strongly coeluted compounds, baseline and background contributions was achieved.

Recent trends in application of multivariate curve resolution approaches for improving gas chromatography-mass spectrometry analysis of essential oils.

Essential oils (EOs) are valuable natural products that are popular nowadays in the world due to their effects on the health conditions of human beings and their role in preventing and curing diseases. In addition, EOs have a broad range of applications in foods, perfumes, cosmetics and human nutrition. Among different techniques for analysis of EOs, gas chromatography-mass spectrometry (GC-MS) is the most important one in recent years.

Modeling of retention behaviors of most frequent components of essential oils in polar and non-polar stationary phases.

The gas chromatography retention indices of 100 different components of essential oils, on three columns with stationary phases of different polarities, were used to develop robust quantitative structure-retention relationship (QSRR) models. Two linear models with only one variable, i.e.

Analysis of Iranian rosemary essential oil: application of gas chromatography-mass spectrometry combined with chemometrics.

This paper focuses on characterization of the components of Iranian rosemary essential oil using gas chromatography-mass spectrometry (GC-MS). Multivariate curve resolution (MCR) approach was used to overcome the problem of background, baseline offset and overlapping/embedded peaks in GC-MS. The analysis of GC-MS data revealed that sixty eight components exist in the rosemary essential oil.

Optimisation of a microwave-assisted method for extracting withaferin A from Withania somnifera Dunal. using central composite design.

Introduction: Recently, there have been growing attention on the modification and optimisation of new extraction and quantification methods, caused by the lack of environmentally friendly methodologies for the extraction of phytochemicals from complex matrices. In the case of pharmaceutical compounds, not only the extraction procedure but also the analysis method should be efficient, precise, fast and easy.

Objectives: The essential pharmaceutical characteristics and trace concentration of withanolides led us to modify and optimise the previously reported extraction and quantification procedure for withaferin A (WA) as a candidate for withanolides.

Towards obtaining more information from gas chromatography-mass spectrometric data of essential oils: an overview of mean field independent component analysis.

Mean field independent component analysis (MF-ICA) along with other chemometric techniques was proposed for obtaining more information from multi-component gas chromatographic-mass spectrometric (GC-MS) signals of essential oils (mandarin and lemon as examples). Using these techniques, some fundamental problems during the GC-MS analysis of essential oils such as varying baseline, presence of different types of noise and co-elution have been solved. The parameters affecting MF-ICA algorithm were screened using a 2(5) factorial design.

Self-modeling curve resolution techniques applied to comparative analysis of volatile components of Iranian saffron from different regions.

Volatile components of saffron from different regions of Iran were extracted by ultrasonic-assisted solvent extraction (USE) and were analyzed by gas chromatography-mass spectrometry (GC-MS). Self-modeling curve resolution (SMCR) was proposed for resolving the co-eluted GC-MS peak clusters into pure chromatograms and mass spectra. Multivariate curve resolution-objective function minimization (MCR-FMIN) and multivariate curve resolution-alternating least square (MCR-ALS) were successfully used for this purpose.

Characterization of volatile components of Iranian saffron using factorial-based response surface modeling of ultrasonic extraction combined with gas chromatography-mass spectrometry analysis.

The volatile components of Iranian saffron were extracted using ultrasonic solvent extraction (USE) technique and then were separated and detected by gas chromatography-mass spectrometry (GC-MS). Variables affecting the extraction procedure were screened by using a 2(5-1) fractional factorial design and among them; sample amount, solvent volume, solvent ratio and extraction time were optimized by applying a rotatable central composite design (CCD). The optimum values of factors were: 2.

Multivariate optimization of hydrodistillation-headspace solvent microextraction of thymol and carvacrol from Thymus transcaspicus.

In this paper multivariate response surface methodology (RSM) has been used for the optimization of hydrodistillation-headspace solvent microextraction (HD-HSME) of thymol and carvacrol in Thymus transcaspicus. Quantitative determination of compounds of interest was performed simultaneously using gas chromatography coupled with flame ionization detector (GC-FID). Parameters affecting the extraction efficiency were assessed and the optimized values were 5 min, 2 microL and 3 min for the extraction time, micro-drop volume and cooling time after extraction, respectively.