Versatile Analytical Tool Research Articles

Long-Term Stability of Redox Mediators in Carbonate Solvents.

Scanning electrochemical microscopy (SECM) used in the feedback mode is one of the most powerful versatile analytical tools used in the field of battery research. However, the application of SECM in the field of lithium-ion batteries (LIBs) faces challenges associated with the selection of a suitable redox mediator due to its high reactivity at low potentials at lithium metal or lithiated graphite electrodes. In this regard, the electrochemical/chemical stability of 2,5-di-tert-butyl-1,4-dimethoxybenzene (DBDMB) is evaluated and benchmarked with ferrocene. This investigation is systematically carried out in both linear and cyclic carbonates of the electrolyte recipe. Measurements of the bulk current with a microelectrode prove that while DBDMB decomposes in ethyl methyl carbonate (EMC)-containing electrolyte, bulk current remains stable in cyclic carbonates, ethylene carbonate (EC) and propylene carbonate (PC). Ferrocene was studied as an alternative redox mediator, showing superior electrochemical performance in ethyl methyl carbonate-containing electrolytes in terms of degradation. The resulting robustness of ferrocene with SECM is essential for a quantitative analysis of battery materials over extended periods. SECM approach curves depict practical problems when using the decomposing DBDMB for data acquisition and interpretation. This study sheds light towards the use of SECM as a probing tool enabled by redox mediators.

Efficient Stochastic Programming in Julia

We present StochasticPrograms.jl, a user-friendly and powerful open-source framework for stochastic programming written in the Julia language. The framework includes both modeling tools and structure-exploiting optimization algorithms. Stochastic programming models can be efficiently formulated using an expressive syntax, and models can be instantiated, inspected, and analyzed interactively. The framework scales seamlessly to distributed environments. Small instances of a model can be run locally to ensure correctness, whereas larger instances are automatically distributed in a memory-efficient way onto supercomputers or clouds and solved using parallel optimization algorithms. These structure-exploiting solvers are based on variations of the classical L-shaped, progressive-hedging, and quasi-gradient algorithms. We provide a concise mathematical background for the various tools and constructs available in the framework along with code listings exemplifying their usage. Both software innovations related to the implementation of the framework and algorithmic innovations related to the structured solvers are highlighted. We conclude by demonstrating strong scaling properties of the distributed algorithms on numerical benchmarks in a multinode setup. Summary of Contribution: This paper presents StochasticPrograms.jl, an open-source framework for stochastic programming implemented in the Julia programming language. The framework includes an expressive syntax for formulating stochastic programming models as well as versatile analysis tools and parallel optimization algorithms. The framework will prove useful to researchers, educators, and industrial users alike. Researchers will benefit from the readily extensible open-source framework, in which they can formulate complex stochastic models or quickly typeset and test novel optimization algorithms. Educators of stochastic programming will benefit from the clean and expressive syntax. Moreover, the framework supports analysis tools and stochastic programming constructs from classical theory and leading textbooks. We strongly believe that the StochasticPrograms.jl framework can reduce the barrier to entry for incoming practitioners of stochastic programming. Industrial practitioners can make use of StochasticPrograms.jl to rapidly formulate complex models, analyze small instances locally, and then run large-scale instances in production. In doing so, they get distributed capabilities for free without changing the code and access to well-tested state-of-the-art implementations of parallel structure-exploiting solvers. As the framework is open-source, anyone from these target audiences can contribute with new functionality to the framework. In conclusion, by providing both an intuitive interface for new users and an extensive development environment for expert users, StochasticPrograms.jl has strong potential to further the field of stochastic programming.

Comparison of two pyrolytic graphite representatives in the construction of hybrid electrochemical DNA biosensors for monitoring DNA damage

• Fabrication of hybrid electrochemical DNA biosensors via electrostatic adsorption. • In-depth optimization process of the most crucial biosensor parameters. • Large potential window allowing dsDNA cathodic/anodic processes at single electrode. • First direct monitoring of DNA damage via cathodic signals at a carbon electrode. Electrochemical DNA biosensors represent a variety of versatile analytical tools successfully used in many important applications. Their utilization in the area of monitoring DNA damage is considered as the prominent field that can provide us with an improved general knowledge regarding DNA damaging events occurring in vivo by an unorthodox overall insight employing the various electrochemical methods. Herein, we present development, optimization process, and subsequent analytical testing of the novel hybrid electrochemical DNA biosensors based on the two representatives of the pyrolytic graphite – “basal-plane” pyrolytic graphite (BPPG) and “edge-plane” pyrolytic graphite (EPPG) – and low-molecular-weight double-stranded DNA (dsDNA). Closer resolution of the nature of the oxidation/reduction signals of the dsDNA, as well as the most important optimization of parameters securing satisfying operational stability of the proposed hybrid biosensors, is investigated. Subsequent analytical testing of the novel hybrid biosensors and the evaluation of their advantages/disadvantages in terms of monitoring DNA damage caused by an UV light irradiation employing various voltammetric methods (square wave (SWV), linear sweep (LSV), or cyclic (CV) voltammetry) and electrochemical impedance spectroscopy (EIS) is also presented.

Performance improved fluorescence polarization for easy and accurate authentication of chicken adulteration

Rapid, accurate, and effective authentication of unlabeled meat components in commercial meat products is of great significance for guaranteeing food safety and human health. In this research, we have constructed a single-strand binding protein (SSB)-assisted performance improved fluorescence polarization (FP) protocol for authentication of chicken component in meat products. The SSB-assisted FP strategy involves the use of fluorescein isothiocyanate (FITC)-labeled primers to perform polymerase chain reaction (PCR). In addition, FP enhancement was accomplished by mixing the amplified product with SSB. Based on the designed mechanism, the free primers in the final amplified product can be tightly bound by SSB, which greatly restricts the rotation of FITC, thereby resulting a high FP signal. In the presence of chicken DNA, the transformation of single-stranded primers to double-stranded amplicons greatly hinders the combination of SSB and primers, leading to the decrease of FP signal. This method well couples the advantages of both PCR and FP technology. Through this new strategy, as low as 0.035% (wt. %) of chicken adulteration in meat samples can be well authenticated. Moreover, this method is also available for commercial meat products. We expect this SSB-assisted FP strategy will provide new insights into the construction of versatile analysis tools in the field of food safety detection. • Fluorescence polarization protocol for rapid sensing of chicken adulteration. • Fluorescence polarization adopted for analysis of PCR products. • Single strand binding protein adopted to improve detection limit of adulteration. • Successful authentication of commercial meat products with improved FP strategy.

Rational incorporating of loop-mediated isothermal amplification with fluorescence anisotropy for rapid, sensitive and on-site identification of pork adulteration

Meat and meat products are one of the valuable foods that provide a variety of essential nutrients for human beings, and their authentication is of great significance for guaranteeing food quality and safety and also the human health. In this research, we present a proof-of-concept strategy of loop-mediated isothermal amplification (LAMP) coupled fluorescence-anisotropy (FP) for rapid, sensitive and accurate judgement of adulteration. Relationship between LAMP and FP is easily constructed by using FITC-labeled primer, which shows limited FP signal at its free state because of fast rotation. With pork DNA, the short primer can be efficiently amplified into macromolecules by LAMP, undergoing significant increase of molecular weight restricting the rotation of FITC. This change leads to a dramatic enhancement of FP signal for adulteration screening. Results show that LAMP-FP well integrates the high efficiency of LAMP with the simplicity of FP, achieving detection limit of 0.01% (wt. %). The performance of LAMP-FP strategy is comparable to those of qPCR. Importantly, this unique method is also available for the commercial processed products. We expect this LAMP-FP will provide a new direction to build versatile analytical tools in food safety monitoring.

Cell2location maps fine-grained cell types in spatial transcriptomics.

Spatial transcriptomic technologies promise to resolve cellular wiring diagrams of tissues in health and disease, but comprehensive mapping of cell types in situ remains a challenge. Here we present сell2location, a Bayesian model that can resolve fine-grained cell types in spatial transcriptomic data and create comprehensive cellular maps of diverse tissues. Cell2location accounts for technical sources of variation and borrows statistical strength across locations, thereby enabling the integration of single-cell and spatial transcriptomics with higher sensitivity and resolution than existing tools. We assessed cell2location in three different tissues and show improved mapping of fine-grained cell types. In the mouse brain, we discovered fine regional astrocyte subtypes across the thalamus and hypothalamus. In the human lymph node, we spatially mapped a rare pre-germinal center B cell population. In the human gut, we resolved fine immune cell populations in lymphoid follicles. Collectively, our results present сell2location as a versatile analysis tool for mapping tissue architectures in a comprehensive manner.

Exploiting the formation of adducts in mobile phases with ammonium fluoride for the enhancement of annotation in liquid chromatography-high resolution mass spectrometry based lipidomics

Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) based lipidomics has become the most versatile analytical tool to discover and detect lipids using a non-targeted approach. A way to improve the ionization performance of specific lipid classes in electrospray sources is to modify their electrostatic interactions with both mobile and stationary phases. So far, studies on mobile phases additives, in particular ammonium fluoride, have focused on increasing ionization efficiency and reproducibility of the conditions. However, little attention has been paid to the different rules that apply in adducts formation: type of adducts, their relative intensities, and how this affects the annotation/identification process. In this study, we evaluated the performance of ammonium fluoride as an additive salt in a non-targeted MS-based lipidomic study under both the positive and negative electrospray ionization modes. The new molecular ion adducts observed can lead to wrong identifications if they are not known or considered, while the disappearance of other adducts such as those with sodium can change the traditional identification rules.

CATBOSS: Cluster Analysis of Trajectories Based on Segment Splitting.

Molecular dynamics (MD) simulations are an exceedingly and increasingly potent tool for molecular behavior prediction and analysis. However, the enormous wealth of data generated by these simulations can be difficult to process and render in a human-readable fashion. Cluster analysis is a commonly used way to partition data into structurally distinct states. We present a method that improves on the state of the art by taking advantage of the temporal information of MD trajectories to enable more accurate clustering at a lower memory cost. To date, cluster analysis of MD simulations has generally treated simulation snapshots as a mere collection of independent data points and attempted to separate them into different clusters based on structural similarity. This new method, cluster analysis of trajectories based on segment splitting (CATBOSS), applies density-peak-based clustering to classify trajectory segments learned by change detection. Applying the method to a synthetic toy model as well as four real-life data sets–trajectories of MD simulations of alanine dipeptide and valine dipeptide as well as two fast-folding proteins–we find CATBOSS to be robust and highly performant, yielding natural-looking cluster boundaries and greatly improving clustering resolution. As the classification of points into segments emphasizes density gaps in the data by grouping them close to the state means, CATBOSS applied to the valine dipeptide system is even able to account for a degree of freedom deliberately omitted from the input data set. We also demonstrate the potential utility of CATBOSS in distinguishing metastable states from transition segments as well as promising application to cases where there is little or no advance knowledge of intrinsic coordinates, making for a highly versatile analysis tool.

Revisão sobre cromatografia líquida acoplada à espectrometria de massas aplicada à análise toxicológica de alimentos

A cromatografia líquida de alta eficiência (HPLC) acoplada à espectrometria de massas (EM) constitui-se como uma das mais importantes técnicas analíticas utilizadas na determinação de compostos não voláteis ou instáveis termicamente. A combinação de ambas une a excelência da separação do analito de interesse na matriz através da técnica da cromatografia líquida de alto desempenho, juntamente com a técnica da espectrometria de massas que confirma a identificação química. Dentre as alternativas disponíveis, a espectrometria de massas é a que melhor fornece as informações estruturais necessárias. O acoplamento entre estas duas técnicas dá origem a uma ferramenta analítica robusta, versátil e de grande potencial na análise qualitativa e quantitativa em toxicologia de alimentos. O presente artigo apresenta uma revisão de literatura que tem o objetivo de apresentar os fundamentos da aplicação do acoplamento da Cromatografia Líquida e Espectrometria de Massas na área de análise de alimentos.

A mathematical method for calibrating the signal drift in liquid chromatography - mass spectrometry analysis

Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has become the most versatile analytical tool for profiling small-molecule compounds and increasingly been applied in many fields. Nevertheless, LC-MS based quantification still face some challenges, such as signal drift in LC-MS, which may affect the validity of the obtained data and lead to misinterpretation of biological results. Here, we established a calibration method known as “RIM” to compensate the signal drift of LC-MS. To this end, a mixture of d4-2-dimethylaminoethylamine (d4-DMED)-coded normal fatty acids (C5–C23) was used as calibrants to construct RIM calibration. With the addition of calibrants, not only the MS signal drift, but also the mass accuracy and LC retention time can be calibrated, thereby improving the reliability of quantitative data. The effectiveness of RIM was carefully validated using a human serum extract spiked with 34 standards and then RIM was applied for rat brain untargeted metabolome research. In addition, to expand the functionality and flexibility of RIM for data handling, we generated a MATLAB-based RIM program, which implements the above concepts and allows automatic data process. Taken together, the proposed RIM method has potential application in large-scale quantitative study of complex samples.

Analysis of oceanaut operating performance using an integrated Bayesian network aided by the fuzzy logic theory

Because the oceanaut plays a significant role in safety and capability during manned deep-diving scientific tasks, preventing oceanaut performance decline is of paramount importance. However, the factors responsible for oceanaut performance are almost entirely unexplored. To address the preceding issues, a quantitative method of fuzzy integrated Bayesian network (FIBN) was modeled within the limits of oceanaut operating procedures. To quantify the probabilities of the influencing factors, the probability of each node in the FIBN was calculated using integrated expert judgement, fuzzy logic theory, and Bayesian network. By considering a total of 28 factors related to oceanaut performance in the “Jiaolong” manned submersible, this study found that difficult sampling, long sampling times, cabin equipment failure, oceanaut physical decline, and declining decision-making ability are important factors that affect oceanaut performance. The FIBN proposed in our study fused the qualitative and quantitative methods and can be developed into a versatile tool for analysis of comprehensive systems that contain both static and dynamic factors. Relevance to industryThe results provide a powerful basis for the design of manned submersible and assignment of tasks to oceanauts, while the fuzzy integrated Bayesian network (FIBN) method proposed can be effectively applied to various quantitative assessment fields which direct researchers to deal with analysis problems of complex systems.

Heterogeneous kinetics of CuO nanoflakes in simultaneous decolorization of Eosin Y and Rhodamine B in aqueous media

This study describes the heterogeneous photocatalysis of CuO nanoflakes for the effective degradation of hazardous dyes. The successful synthesis of CuO nanoflakes was carried out by exploiting aqueous chemical growth method. The synthesized material was characterized by versatile analytical tools including XRD, FE-SEM, EDX, AFM, ZP and FT-IR. The engineered CuO reveals nanoflakes texture having average size of 18.3 nm and (− 36.5 ± 3 mV) surface charge with excellent phase purity and crystalline nature. The catalytic kinetics exposed that CuO nanocatalyst exhibits an exceptional degradation over 97% for Eosin Y (EY) and Rhodamine B (RB) dyes in the aqueous medium using minimum catalyst dose of 120 and 140 μg individually and simultaneously, within 3 min of time period under sunlight. Due to ultrafine processing, cost-effective synthetic outline, supreme reduction percentage in short time and intense recyclability with an insignificant decrease in degradation abilities, the proposed nanocatalyst is extremely useful. Consequentially, the nanocatalyst presented here is more useful and realistic, hence can be suggested as an effective candidate for the successful degradation of complex dyes at the commercial level.

Lab on a Tip: Atomic Force Microscopy as a Versatile Analytical Tool for Nano-bioscience

Lab on a Tip: Atomic Force Microscopy as a Versatile Analytical Tool for Nano-bioscience

Unipept Desktop: A Faster, More Powerful Metaproteomics Results Analysis Tool

Metaproteomics has become an important research tool to study microbial systems, which has resulted in increased metaproteomics data generation. However, efficient tools for processing the acquired data have lagged behind. One widely used tool for metaproteomics data interpretation is Unipept, a web-based tool that provides, among others, interactive and insightful visualizations. Due to its web-based implementation, however, the Unipept web application is limited in the amount of data that can be analyzed. In this manuscript we therefore present Unipept Desktop, a desktop application version of Unipept that is designed to drastically increase the throughput and capacity of metaproteomics data analysis. Moreover, it provides a novel comparative analysis pipeline and improves the organization of experimental data into projects, thus addressing the growing need for more efficient and versatile analysis tools for metaproteomics data.

Investigation of Silphium perfoliatum as Feedstock for a Liquid Hot Water–Based Biorefinery Process Towards 2,3-Butanediol

The aim of the present study was to generate a consistent data set for biorefinery intermediates from novel energy crop Silphium perfoliatum compared with Fagus sylvatica, including process streams from liquid hot water pretreatment, enzymatic hydrolysis, and fermentation with Bacillus licheniformis. The consistency of the data set was further supported by the application of a consistent analytical method based on high performance anion exchange chromatography with pulsed amperometric detection and validated for process intermediates, which renders the technique a versatile analytical tool also for alcoholic compounds. For the first time, Silphium perfoliatum was used for liquid hot water pretreatment which resulted in a maximal absolute glucose recovery after enzymatic hydrolysis for feedstock pretreated with 200 °C, 20 min, 20% solid loading. Under these conditions, 68% glucose were recovered for Silphium perfoliatum and 62% for Fagus sylvatica. Further, enzymatic hydrolyzates of both feedstocks were successfully used as single carbon sources for 2,3-butanediol fermentation with Bacillus licheniformis resulting in a 2,3-butanediol yield of 39% and 31% of the theoretical yield for Silphium perfoliatum and Fagus sylvatica, respectively. Thus, the technical suitability of Silphium perfoliatum as feedstock for a liquid hot water–based biorefinery process was comprehensively demonstrated and successfully bore the comparison with Fagus sylvatica.

Low-cost and versatile analytical tool with purpose-made capillary electrophoresis coupled to contactless conductivity detection: Application to antibiotics quality control in Vietnam.

In this study, the development of our purpose-made capacitively coupled contactless conductivity detection (C4 D) for CE is reported. These systems have been employed as a simple, versatile, and cost-effective analytical tool. CE-C4 D devices, whose principle is based on the control of the ion movements under an electrical field, can be constructed even with a modest financial budget and limited infrastructure. A featured application was developed for quality control of antimicrobial drugs using CE-C4 D, with most recent work on determination of aminoglycoside and glycopeptide antibiotics being communicated. For aminoglycosides, the development of CE-C4 D methods was adapted to two categories. The first one includes drugs (liquid or powder form) for intravenous injection, containing either amikacin, streptomycin, kanamycin A, or kanamycin B. The second one covers drugs for eye drops (liquid or ointment form), containing either neomycin, tobramycin, or polymyxin. The CE-C4 D method development was also made for determination of some popular glycopeptide antibiotics in Vietnam, including vancomycin and teicoplanin. The best detection limit achieved using the developed CE-C4 D methods was 0.5mg/L. Good agreement between results from CE-C4 D and the confirmation method (HPLC- Photometric Diode Array ) was achieved, with their result deviations less than 8% and 13% for aminoglycoside and glycopeptide antibiotics, respectively.

A thorough evaluation of matrix-free laser desorption ionization on structurally diverse alkaloids and their direct detection in plant extracts.

Alkaloids represent a major group of natural products (NPs), derived from highly diverse organisms. These structurally varied specialized metabolites are widely used for medicinal purposes and also known as toxic contaminants in agriculture and dietary supplements. While the detection of alkaloids is generally facilitated by GC- or LC-MS, these techniques do require considerable efforts in sample preparation and method optimization. Bypassing these limitations and also reducing experimental time, matrix-free laser desorption ionization (LDI) and related methods may provide an interesting alternative. As many alkaloids show close structural similarities to matrices used in matrix-assisted laser desorption ionization (MALDI), they should ionize upon simple laser irradiation without matrix support. With this in mind, the current work presents a systematic evaluation of LDI properties of a wide range of structurally diverse alkaloids. Facilitating a direct comparison between LDI and ESI-MS fragmentation, all tested compounds were further studied by electrospray ionization (ESI). Moreover, crude plant extracts of Atropa belladonna, Cinchona succirubra, and Colchicum autumnale were analyzed by LDI in order to evaluate direct alkaloid detection and dereplication from complex mixtures. Finally, dose-dependent evaluation of MALDI and LDI detection using an extract of Rosmarinus officinalis spiked with atropine, colchicine, or quinine was conducted. Overall, present results suggest that LDI provides a versatile analytical tool for analyzing structurally diverse alkaloids as single compounds and from complex mixtures. It may further serve various potential applications ranging from quality control to the screening for toxic compounds as well as the build up of MS databases. Graphical abstract.

A brief introduction to the basics of NMR spectroscopy and selected examples of its applications to materials characterization

AbstractNuclear magnetic resonance (NMR) spectroscopy is an analytical technique that gives information on the local magnetic field around atomic nuclei. Since the local magnetic field of the nucleus is directly influenced by such features of the molecular structure as constitution, configuration, conformation, intermolecular interactions, etc., NMR can provide exhaustive information on the chemical structure, which is unrivaled by any other analytical method. Starting from the 1950s, NMR spectroscopy first revolutionized organic chemistry and became an indispensable tool for the structure elucidation of small, soluble molecules. As the technique evolved, NMR rapidly conquered other disciplines of chemical sciences. When the analysis of macromolecules and solids also became feasible, the technique turned into a staple in materials characterization, too. All aspects of NMR spectroscopy, including technical and technological development, as well as its applications in natural sciences, have been growing exponentially since its birth. Hence, it would be impossible to cover, or even touch on, all topics of importance related to this versatile analytical tool. In this tutorial, we aim to introduce the reader to the basic principles of NMR spectroscopy, instrumentation, historical development and currently available brands, practical cost aspects, sample preparation, and spectrum interpretation. We show a number of advanced techniques relevant to materials characterization. Through a limited number of examples from different fields of materials science, we illustrate the immense scope of the technique in the analysis of materials. Beyond our inherently limited introduction, an ample list of references should help the reader to navigate further in the field of NMR spectroscopy.

Applications of Raman Spectroscopy in Mineralogy and Geochemistry

The application of Raman spectroscopy for the identification and characterization of minerals and related materials has increased appreciably during recent years. Raman spectroscopy has proven to be a most valuable and versatile analytical tool. Successful applications cover virtually all the mineralogical sub-disciplines, and have become more numerous in geochemistry. We present a general summary of present applications, illustrated by selected examples. In addition, we briefly point out several aspects of spectral acquisition, data reduction, and interpretation of Raman results that are important for the application of Raman spectroscopy as a reliable analytical tool.

Use of NMR as an analytical tool in the process development of conjugate vaccines against Haemophilus influenzae type b (Hib) and meningococcal serogroup A (MenA)

The native structure of the bacterial polysaccharide is the key immunogenic component of conjugate vaccines and antibodies raised against the polysaccharide structure are responsible for providing protection against the corresponding pathogen. The manufacturing process of conjugate vaccines is very complex and has various biological and chemical steps. It is important to monitor the process to ensure that the structural identity of the polysaccharide is maintained throughout the process. NMR spectroscopy can be used as a versatile analytical tool to monitor the structural integrity of the polysaccharide component from isolated polysaccharide to conjugate vaccine and for identifying different impurities generated during the process.