Important Analytical Techniques Research Articles

Miniaturized liquid chromatography applied to the analysis of residues and contaminants in food: A review.

The humankind is pretty dependent on food to control several biological processes into the organism. As the world population increases, the demand for foodstuffs follows the same trend claiming for a high food production situation. For this reason, a substantial amount of chemicals is used in agriculture and livestock husbandries every year, enhancing the likelihood of contaminated foodstuffs being commercialized. This outlook becomes a public health concern; thus, the governmental regulatory agencies impose laws to control the residues and contaminants in food matrices. Currently, one of the most important analytical techniques to perform it is LC. Despite its already recognized effectiveness, it is often time consuming and requires significant volumes of reagents, which are transformed into toxic waste. In this context, miniaturized LC modes emerge as a greener and more effective analytical technique. They have remarkable advantages, including higher sensitivity, lower sample amount, solvent and stationary phase requirements, and more natural coupling to MS. In this review, most of the critical characteristics of them are discussed, focusing on the benchtop instruments and their related analytical columns. Additionally, a discussion regarding the last 10 years of publications reporting miniaturized LC application for the analysis of natural and industrial food samples is categorized. The main chemical classes as applied in the crops are highlighted, including pesticides, veterinary drugs, and mycotoxins.

Detection of Fungal Jasmonates by Liquid Chromatography Paired with Mass Spectrometry.

Liquid chromatography-mass spectrometry (LC-MS) is one of the most important analytical chemistry techniques for the detection and characterization of biologically active compounds of low abundance-for example, hormones. Gas chromatography (GC) coupled with mass spectrometry has been a method of choice to detect jasmonic acid, the well-known defense hormone in plants. Recently, we identified structural and functional analogs of phytohormone jasmonic acid (JA) and its derivatives, in the rice-blast fungus Magnaporthe oryzae. Here, we describe protocols of LC-MS/MS-based identification and quantification of fungal jasmonates, especially during pathogenic development in the rice blast fungus.

A few important features of global atmospheric boundary layer heights estimated using COSMIC radio occultation retrieved data

This research reports the global atmospheric boundary layer height (ABLH, which is also known as the planetary boundary layer, PBLH) features estimated using COSMIC radio occultation (RO) retrieved temperature profiles during March, April, and May in 2015. Important analytical techniques including the vertical gradient and logarithmic gradient methods applied effectively on temperature profiles have revealed a few interesting features. Mainly, west coasts of the majority of the continents are associated with relatively lower magnitudes during the daytime hours, first of its kind observations reported using a space-based remote sensing technique. Secondly, over landmasses and desert areas, ABLHs show relatively higher magnitudes during the daytime hours, due to higher sensible heat flux. Thirdly, the cold land areas show relatively lower ABLHs, whereas cold oceans depict moderately higher values. In order to explain relatively low marine ABL (MABL) heights over the west coasts of the continents, we present a schematic diagram which includes various possible physical mechanisms that might be responsible for these extremely low MABL heights. This research emphasizes that the COSMIC RO is a powerful global technique, which is able to unravel the link between ocean and the Earth’s lower atmospheric dynamics.

Spectroscopic Studies of Food Colorings

In chemical education, it is often a challenge to understand the basic principles of spectroscopic techniques due to missing connections to the real world. Therefore, the present contribution offers context-based applications of UV/Vis spectroscopy for analytics of food colorings with which learners can improve their skills regarding this method. The spectroscopic determination of food colorings seems to be a promising approach due to the long tradition and omnipresence of dyes in supermarket products. The therefor-required spectral data for commonly used dyes are provided for educational usage. Qualitative and quantitative analytics of food colorings in four different lemonades and chocolate beans have been used to introduce learners to important analytical techniques like sample preparation or elimination of confounding factors. These analytics also display the limitations of the method in the visible range of light in the case of tartrazine and curcumin. By applying Lambert-Beer-Bouguer’s Law in different variations, typical calculations of concentrations can be studied in quantitative analyses. The studied food samples demonstrate the different usage of food colorings depending on the country of sale. Finally, a 3D-printable low-cost photometer suitable for the discussed quantitative analytics in educational contexts is presented.

A comparative study on the performance of artificial neural networks and regression models in modeling the heat source model parameters in GTA welding

Welding is one the most important joining methods Analytical and FEM techniques are commonly employed to model various welding processes. The heat source model is a key part of welding simulation. Proper determination of heat source parameters is one of the main factors in the accuracy of the welding simulation. In this study, artificial neural networks and regression modeling have been employed to establish the relationships between welding input variables and the parameters for the Goldak heat source model. The 27 data needed for modeling has been gathered based on full factorial design. While ANN slightly outperforms regression, both ANN and second order regression functions have good agreements with actual experiments. The approach presented here may be used to accurately specify heat source parameters for any given set of welding process variables.

New procedure for determination of availability and reliability of complex cogeneration systems by improving the approximated Markov method

There are two procedures to solve reliability problems: analytical techniques and stochastic simulation. Each has advantages and disadvantages. One of the important analytical techniques for repairable systems is the Markov method. This method uses state space to consider all states that may occur. To use this method for complex systems, the model of the system must be simplified. For this purpose, many states are removed from the space state. In this way, although the probabilities of the states are calculated, these probabilities are often not accurate. In the present work, a new approach is proposed that considers both the simplified system and the calculation of the probability of each state accurately. The new method can calculate the probabilities by taking into account minimum states. Site utility systems are used to illustrate the procedure for applying this method. Site utilities have several repairable components (e.g. steam turbine, gas turbine, HRSG, de-aerator, boiler). So, this system can generate a large and complex state space for which it is difficult to calculate the probability. The new procedure can reduce the number of states and aggregates of the exploded state space due to the high number of components. The results show that the new procedure can predict state probabilities with high accuracy.

An Overview on the Importance of Combining Complementary Analytical Platforms in Metabolomic Research.

The analytical bias introduced by most of the commonly used techniques in metabolomics considerably hinders the simultaneous detection of all metabolites present in complex biological samples. In order to solve this limitation, the combination of complementary approaches is emerging in recent years as the most suitable strategy in order to maximize metabolite coverage. This review article presents a general overview of the most important analytical techniques usually employed in metabolomics: nuclear magnetic resonance, mass spectrometry and hybrid approaches. Furthermore, we emphasize the potential of integrating various tools in the form of metabolomic multi-platforms in order to get a deeper metabolome characterization, for which a revision of the existing literature in this field is provided. This review is not intended to be exhaustive but, rather, to give a practical and concise guide to readers not familiar with analytical chemistry on the considerations to account for the proper selection of the technique to be used in a metabolomic experiment in biomedical research.

Ammonium hydroxide enhancing electrospray response and boosting sensitivity of bisphenol A and its analogs

As one of the most important analytical techniques for accurate quantification of bisphenol compounds, liquid chromatography coupled to online electrospray ionization (ESI) tandem mass spectrometry exhibits relative weak ESI response in negative mode, which greatly reduces their sensitivity and limits their detection at trace levels, especially in complex samples such as blood. Based on the facilitated deprotonation of bisphenol molecule under alkaline condition, post-column injection of ammonium hydroxide (NH3·H2O) to mass spectrometer was explored to enhance the ionization efficiency of BPA and its eight analogs and improve their analytical sensitivity. Parameters effecting response intensity and stability were investigated, including mass concentration and flow rate of NH3·H2O. Under the optimal conditions with the addition of 2% (w/w) of NH3·H2O at 4 μL min−1, the instrument detection limits for bisphenol compounds were greatly lowered to 0.001–0.04 ng mL−1, which were 2–28.6 times lower than the result obtained without injecting NH3·H2O, except TBBPA (0.03 ng mL−1 in either case). The relative standard deviations (RSDs) for instrument repeatability of BPA and its analogs at three different concentration levels were in a range of 1.2–20%. Furthermore, a decreased matrix effects (90–111%) for bisphenols (except TBBPA) analysis in serum extracts were found compared with the result obtained without NH3·H2O injection (43–111%). The results demonstrated that the improved instrumental method coupled with suitable pretreatment techniques is more feasible to analyze bisphenol compounds in complex bio-samples.

Rapid monitoring the water extraction process of Radix Paeoniae Alba using near infrared spectroscopy

Near infrared (NIR) spectroscopy has been developed into one of the most important process analytical techniques (PAT) in a wide field of applications. The feasibility of NIR spectroscopy with partial least square regression (PLSR) to monitor the concentration of paeoniflorin, albiflorin, gallic acid, and benzoyl paeoniflorin during the water extraction process of Radix Paeoniae Alba was demonstrated and verified in this work. NIR spectra were collected in transmission mode and pretreated with smoothing and/or derivative, and then quantitative models were built up using PLSR. Interval partial least squares (iPLS) method was used for the selection of spectral variables. Determination coefficients ([Formula: see text] and [Formula: see text]), root mean squares error of prediction (RMSEP), root mean squares error of calibration (RMSEC), and residual predictive deviation (RPD) were applied to verify the performance of the models, and the corresponding values were 0.9873 and 0.9855, 0.0487[Formula: see text]mg/mL, 0.0545[Formula: see text]mg/mL and 8.4 for paeoniflorin; 0.9879, 0.9888, 0.0303[Formula: see text]mg/mL, 0.0321[Formula: see text]mg/mL and 9.1 for albiflorin; 0.9696, 0.9644, 0.0140[Formula: see text]mg/mL, 0.0145[Formula: see text]mg/mL and 5.1 for gallic acid; 0.9794, 0.9781, 0.00169[Formula: see text]mg/mL, 0.00171[Formula: see text]mg/mL and 6.9 for benzoyl paeoniflorin, respectively. The results turned out that this approach was very efficient and environmentally friendly for the quantitative monitoring of the water extraction process of Radix Paeoniae Alba.

Metabolomics in Alzheimer's disease: The need of complementary analytical platforms for the identification of biomarkers to unravel the underlying pathology.

Alzheimer's disease is a complex neurodegenerative disorder characterized by a multi-factorial etiology, not completely understood to date. In this context, the application of metabolomics is emerging in the last years because of its potential to monitor molecular alterations associated with disease pathogenesis and progression, as well as to discover candidate diagnostic biomarkers. However, the huge heterogeneity and dynamism of the human metabolome makes impossible the simultaneous determination of the entire set of metabolites from complex biological samples. Thus, the most common strategy to get a comprehensive overview of the organism's phenotypic expression is the combined use of complementary metabolomic platforms. In this review, we summarize the advantages and limitations of the most important analytical techniques usually employed in metabolomics, including nuclear magnetic resonance, direct infusion mass spectrometry and hyphenated approaches based on the coupling of orthogonal separation mechanisms (i.e. liquid chromatography, gas chromatography, capillary electrophoresis) with mass spectrometry. Moreover, the suitability of metabolomics to unravel the complex pathology underlying to Alzheimer's disease is also presented.

Metabolomics, Nutrition, and Potential Biomarkers of Food Quality, Intake, and Health Status.

Diet, dietary patterns, and other environmental factors such as exposure to toxins are playing an important role in the prevention/development of many diseases, like obesity, type 2 diabetes, and consequently on the health status of individuals. A major challenge nowadays is to identify novel biomarkers to detect as early as possible metabolic dysfunction and to predict evolution of health status in order to refine nutritional advices to specific population groups. Omics technologies such as genomics, transcriptomics, proteomics, and metabolomics coupled with statistical and bioinformatics tools have already shown great potential in this research field even if so far only few biomarkers have been validated. For the past two decades, important analytical techniques have been developed to detect as many metabolites as possible in human biofluids such as urine, blood, and saliva. In the field of food science and nutrition, many studies have been carried out for food authenticity, quality, and safety, as well as for food processing. Furthermore, metabolomic investigations have been carried out to discover new early biomarkers of metabolic dysfunction and predictive biomarkers of developing pathologies (obesity, metabolic syndrome, type-2 diabetes, etc.). Great emphasis is also placed in the development of methodologies to identify and validate biomarkers of nutrients exposure.

Demonstrating Electrophoretic Separation in a Straight Paper Channel Delimited by a Hydrophobic Wax Barrier

A demonstration is described of electrophoretic separation of carmine and sunset yellow with a paper-based device. The channel in the paper device was fabricated by hand with a wax pen. Electrophoretic separation of carmine and sunset yellow was achieved within a few minutes by applying potential on the channel using a simple and inexpensive power supply. This demonstration could not only motivate the students’ passion in learning analytical chemistry but also introduce two important analytical techniques (microfluidic paper-based analytical devices and electrophoresis) to the classroom. With further modification and improvement, this demonstration may be suitable for students to perform as a laboratory experiment in the teaching lab.

Precise small volume sample handling for capillary electrophoresis.

CE is one of the most important analytical techniques. Although the injected sample volume in CE is only in the nanoliter range, most commercial CE instruments need approximately 50 μL of the sample in the injection vial to perform the analysis. Hence, in order to fully profit from the low injection volumes, smaller vial volumes are required. Thus experiments were performed using silicone oil, which has higher density than water (1.09 g/mL) to replace sample dead volume in the vial. The results were compared to those performed without using the silicone oil in the sample vial. As an example five standard proteins namely beta-lactoglobulin, BSA, HSA, myoglobin, and ovalbumin, and one of the coagulation cascade involved proteins called vitonectin were investigated using CE. Mobility ratios and peak areas were compared. However, no significant changes were observed (RSDs% for mobility ratios and peak areas were better than 0.9 and 5.8%, respectively). Afterwards, an affinity CE method was used to investigate the interactions of two proteins, namely HSA and vitronectin, with three ligands namely enoxaparin sodium, unfractionated heparin, and pentosan polysulfate sodium. Mobility shift precision results showed that the employment of the filling has no noticeable effect on any of the protein-ligand interactions. Using a commercial PrinCE instrument and an autosampler the required sample volume is reduced down to 10 μL, and almost this complete volume can be subsequently injected during repeated experiments.

Pesticides Analysis: Advantages of Increased Dimensionality in Gas Chromatography and Mass Spectrometry

For a century, pesticides have been an integral component of the environmental system of the world. There has been increasing attention paid to the regulation and analysis of these compounds. Gas chromatography (GC) and mass spectrometry (MS) are two of the most important analytical techniques employed for high throughput pesticide analysis. This review features applications, advantages, and comparison of different GC and MS techniques based on applied separation dimensionalities related to column and/or mass analyzers. A brief historical perspective, a primary focus on recent developments, and a view to future trends will be highlighted here. Multidimensional analysis, employing novel types of stationary phases for GC, will be considered, along with the role of hyphenation with emerging MS technologies.

GWmodel: AnRPackage for Exploring Spatial Heterogeneity Using Geographically Weighted Models

Spatial statistics is a growing discipline providing important analytical techniques in a wide range of disciplines in the natural and social sciences. In the R package GWmodel we present techniques from a particular branch of spatial statistics, termed geographically weighted (GW) models. GW models suit situations when data are not described well by some global model, but where there are spatial regions where a suitably localized calibration provides a better description. The approach uses a moving window weighting technique, where localized models are found at target locations. Outputs are mapped to provide a useful exploratory tool into the nature of the data spatial heterogeneity. Currently, GWmodel includes functions for: GW summary statistics, GW principal components analysis, GW regression, and GW discriminant analysis; some of which are provided in basic and robust forms.

ALK-positive anaplastic large cell lymphoma an evolving story

Human exposure to nanoparticles has increased considerably due to anthropogenic activities dominated by coal and diesel oil fuel combustion. Not only the inhalation of nanoparticles, which nowadays is considered to be the most significant via of exposure to nanomaterials, but also the gradually more employment of nanoparticles in products such as cosmetics, deodorants, textiles, or even food is broadening the exposure to those materials. Developing the previous applications will obviously require the use of analytical methodologies to analyse biological matrices in order to assess potential risks in their use and take appropriate corrective actions. This chapter describes a general overview of the most important analytical techniques for the analysis of nanoparticles in biological matrices.

Laser-Induced Plasma Spectrometry With Chemical Seeding and Application to Flow Mixing Analysis in Methane–Air Flames

Spectroscopic measurements of flames are amongst the most important analytical diagnostic techniques that allow one to improve thermal and energy efficiency of industrial furnaces. A chemical seeding laser-induced plasma spectroscopy (CS-LIPS) was successfully developed and applied for mixing analysis of a methane–air diffusion flame. The results obtained showed that sensitivity of this system was much improved using silica rod as the target material in place of the tungsten material used in our previous studies. Profiling of Mg spectral emission and mixing in the flame was made more clearly with the introduction of magnesium aerosols as a tracer into the combustion air flow.

Plant micro- and nanomechanics: experimental techniques for plant cell-wall analysis

In the last few decades, micro- and nanomechanical methods have become increasingly important analytical techniques to gain deeper insight into the nanostructure and mechanical design of plant cell walls. The objective of this article is to review the most common micro- and nanomechanical approaches that are utilized to study primary and secondary cell walls from a biomechanics perspective. In light of their quite disparate functions, the common and opposing structural features of primary and secondary cell walls are reviewed briefly. A significant part of the article is devoted to an overview of the methodological aspects of the mechanical characterization techniques with a particular focus on new developments and advancements in the field of nanomechanics. This is followed and complemented by a review of numerous studies on the mechanical role of cellulose fibrils and the various matrix components as well as the polymer interactions in the context of primary and secondary cell-wall function.

Barbaloin: A concise report of its pharmacological and analytical aspects

Barbaloin is C-glucoside of aloe emodin anthrone which is found in the plant name as Aloe vera is a perennial succulent (Liliaceal), also called the healing plant. Barbaloin have variety of pharmacological activity such as strong inhibitory effect on histamine release, anti-inflammatory, cathartic, antiviral, antimicrobial, anticancer, antioxidant activity and alternative for pharmaceutical or cosmetic applications. The peak amount of barbaloin was reached about 3 h after oral administration. Concentration of barbaloin in Aloe vera leaves was shown to depend on the leaf part, age, and position of the leaf. Young leaves contain more barbaloin compared to old one. Various researches have been done on barbaloin but still the relationship between the barbaloin and its overall effect has not been clarified. A more specific perceptive of the pharmacological activities of barbaloin is required to develop for pharmaceutical purpose. Many attempts have been made regarding its isolation, biological activity to examine their effects, and clarify their functional mechanism. This review gives a brief idea about its uses, ethnomedicinally and commercially important analytical techniques and their pharmacological activities.

Molecular markers: progress and prospects for understanding reproductive ecology in elasmobranchs

Application of modern molecular tools is expanding the understanding of elasmobranch reproductive ecology. High-resolution molecular markers provide information at scales ranging from the identification of reproductively isolated populations in sympatry (i.e. cryptic species) to the relationships among parents, offspring and siblings. This avenue of study has not only augmented the current understanding of the reproductive biology of elasmobranchs but has also provided novel insights that could not be obtained through experimental or observational techniques. Sharing of genetic polymorphisms across ocean basins indicates that for some species there may be gene flow on global scales. The presence, however, of morphologically similar but genetically distinct entities in sympatry suggests that reproductive isolation can occur with minimal morphological differentiation. This review discusses the recent findings in elasmobranch reproductive biology like philopatry, hybridization and polyandry while highlighting important molecular and analytical techniques. Furthermore, the review examines gaps in current knowledge and discusses how new technologies may be applied to further the understanding of elasmobranch reproductive ecology.