Low-parachor solvents extraction and thermostated micro-thin-layer chromatography separation for fast screening and classification of spirulina from pharmaceutical formulations and food samples

Investigation of Hybrid Methods for Elimination of Brilliant Blue Dye from Water Phase Using Various Nanomaterials Combined with Activated Sludge and Duckweed

The main goal of this experimental work is screening of different natural and synthetic nanomaterials and biopolymers that may improve elimination of stable micropollutants from water phase. In this work, as a target chemical acting as the micropollutant molecule, the Brilliant Blue (BB) dye was selected. We tested different active matrices dispersed in water phase including activated carbon (AC), lyophilized graphene oxide (GO), β-cyclodextrin (CD), raw dandelion pappus (DP), microcrystalline cellulose(MC), and raw pine pollen (PP), as well as two types of Egyptian Blue mineral pigments (EB1 and EB2). Graphene oxide and Egyptian Blue nanomaterials were synthesized in our laboratory. We investigated potential application of such nanoparticles and biopolymer conglomerates as additives that may tune the activated sludge (AS) microorganisms or duckweed water plant (DW) and increase efficiency of micropollutants removal from wastewater. Studied nanomaterials/biopolymers were used in two different experimental modes involving real activated sludge microorganisms (24 h experiment) as well as duckweed plant (16 day experiment). Quantitative data of BB were obtained using microfluidic type device based on micro-TLC plate. This approach enabled direct determination of target component without sample pre-treatment like pre-concentration or pre-purification. Within single analytical run calibration line, retention standard spots (methyl red) and multiple samples were analyzed simultaneously. Due to the multivariate nature of these experiments, quantitative data were explored with chemometric tools including AHC (agglomerative hierarchical clustering), PCA (principal component analysis), and FA (factor analysis). Experimental data and multivariate calculations revealed that BB is strongly resistant on biodegradation, however, inclusion complexes formation with β-cyclodextrinmay induce degradation of this dye in the presence of duckweed. It is hoped that results of our experimental work can be used for designing of future experiments for fast screening of different additives and improvement of technological processes, focusing on purification of sewage and water from micropollutants.

Two-Dimensional Thin Layer Chromatography-Bioautography Designed to Separate and Locate Metabolites with Antioxidant Activity Contained on Spirulina platensis

Spirulina platensis contains several biologically active compounds, some of them with antioxidant activity. Nevertheless, not all of these compounds have been identified to date. As a first step to achieving such identification, a methodology to perform two-dimensional thin layer chromatography bioautographies on silica gel thin layer chromatography plates was proposed. Starting with a reference binary system, 5 other binary systems were tested, in which the relative polarity was systematically increased. To further improve the separation behavior, a phase modifier (NH₄OH) was used. The best separation results were obtained with the isopropyl alcohol/ethyl acetate/NH₄OH ternary system. This experimental system allowed four well-resolved spots showing antioxidant activity as well as two additional areas with mixtures containing antioxidant compounds. Although the proposed methodology was designed with a specific application, it would be predictable that its field of use could be considerably greater, making the convenient modifications on the solvent polarity and “masking level” produced by the ammonium derivatives.

Green techniques in comparison to conventional ones in the extraction of Amaryllidaceae alkaloids: Best solvents selection and parameters optimization

An undisputed trend in sample preparation at present is to meet the requirements of green chemistry especially in the field of natural products. Green technology continuously pursues new solvents to replace common organic solvents that possess inherent toxicity. Over the past two decades, non-ionic surfactants have gained enormous attention from the scientific community. The micelle-mediated extraction and cloud-point preconcentration (CPE) methods offer a convenient alternative to the conventional extraction systems. Recently, natural deep eutectic solvents (NDESs) have emerged as green and sustainable solvents for efficient extraction of bioactive compounds or drugs. They are generally composed of neutral, acidic or basic compounds that form liquids of high viscosity when mixed in certain molar ratio. The presented work aimed to comprehensively compare and evaluate the potential and effectiveness of NDES as well as non-ionic surfactants (Genapol X-080, Triton X-100 and Triton X-114) for extraction of Amaryllidaceae alkaloids from Crinum powellii bulbs as representative example of plant material, in comparison to the conventional solvents (methanol, ethanol and water).A new validated high-performance thin-layer chromatographic (HPTLC) method has been developed for the simultaneous quantitation of three alkaloids markers, lycorine, crinine and crinamine, in the bulbs of C. powellii. Extraction efficiency of the targeted alkaloids from the bulb matrix with organic and ecofriendly (green) solvents were studied. Results revealed that NDES and surfactants were significantly more efficient in alkaloid extraction than previous methods requiring the consumption of organic solvents and water. Genapol X-80 demonstrated 138%, 149% and 145%, while choline chloride: fructose (5:2): H₂O (35%) NDES mixture demonstrated 243%, 225% and 238% of the total alkaloidal extraction capacity of ethanol, methanol and water, respectively at 50 °C for extraction time 1 h using ultrasonication for all experiments. Furthermore, Box-Behnken response surface design combined with the overall desirability value were successfully employed to optimize and study the individual and interactive effect of process variables such as extraction temperature, time and surfactant %, for Genapol X-80, and sonication extraction temperature, time and water concentration, for choline chloride: fructose: H₂O NDES mixture, on the alkaloidal yield from C. powellii. It was evident that parameters interacting together can act in synergism if adjusted properly according to the optimized conditions to obtain maximum alkaloids extractability. It is for the first time that the efficiency of micelle-mediated extraction has been compared to that of natural deep eutectic solvents for the extraction of alkaloids and the results thoroughly discussed.

Proof-of-Principle of rTLC, an Open-Source Software Developed for Image Evaluation and Multivariate Analysis of Planar Chromatograms

High-performance thin-layer chromatography (HPTLC) is an advantageous analytical technique for analysis of complex samples. Combined with multivariate data analysis, it turns out to be a powerful tool for profiling of many samples in parallel. So far, chromatogram analysis has been time-consuming and required the application of at least two software packages to convert HPTLC chromatograms into a numerical data matrix. Hence, this study aimed to develop a powerful, all in one open-source software for user-friendly image processing and multivariate analysis of HPTLC chromatograms. Using the caret package for machine learning, the software was set up in the R programming language with an HTML-user interface created by the shiny package. The newly developed software, called rTLC, is deployed online, and instructions for direct use as a web application and for local installation, if required, are available on GitHub. rTLC was created especially for routine use in planar chromatography. It provides the necessary tools to guide the user in a fast protocol to the statistical data output (e.g., data extraction, preprocessing techniques, variable selection, and data analysis). rTLC offers a standardized procedure and informative visualization tools that allow the user to explore the data in a reproducible and comprehensive way. As proof-of-principle of rTLC, German propolis samples were analyzed using pattern recognition techniques, principal component analysis, hierarchic cluster analysis, and predictive techniques, such as random forest and support vector machines.

Recent advances in hopanoids analysis: Quantification protocols overview, main research targets and selected problems of complex data exploration

Pentacyclic triterpenoids, particularly hopanoids, are organism-specific compounds and are generally considered as useful biomarkers that allow fingerprinting and classification of biological, environmental and geological samples. Simultaneous quantification of various hopanoids together with battery of related non-polar and low-molecular mass compounds may provide principal information for geochemical and environmental research focusing on both modern and ancient investigations. Target compounds can be derived from microbial biomass, water columns, sediments, coals, crude fossils or rocks. This create number of analytical problems due to different composition of the analytical matrix and interfering compounds and therefore, proper optimization of quantification protocols for such biomarkers is still the challenge. In this work we summarizing typical analytical protocols that were recently applied for quantification of hopanoids like compounds from different samples. Main steps including components of interest extraction, pre-purification, fractionation, derivatization and quantification involving gas (1D and 2D) as well as liquid separation techniques (liquid-liquid extraction, solid-phase extraction, planar and low resolution column chromatography, high-performance liquid chromatography) are described and discussed from practical point of view, mainly based on the experimental papers that were published within last two years, where significant increase in hopanoids research was noticed. The second aim of this review is to describe the latest research trends concerning determination of hopanoids and related low-molecular mass lipids analyzed in various samples including sediments, rocks, coals, crude oils and plant fossils as well as stromatolites and microbial biomass cultivated under different conditions. It has been found that majority of the most recent papers are based on uni- or bivariate approach for complex data analysis. Data interpretation involves number of physicochemical parameters and hopanoids quantities or given biomarkers mass ratios derived from high-throughput separation and detection systems, typically GC-MS and HPLC-MS. Based on quantitative data reported in recently published experimental works it has been demonstrated that multivariate data analysis using e.g. principal components computations may significantly extend our knowledge concerning proper biomarkers selection and samples classification by means of hopanoids and related non-polar compounds.

Thin-layer chromatographic identification of Chinese propolis using chemometric fingerprinting

INTRODUCTION

Poplar tree gum has a similar chemical composition and appearance to Chinese propolis (bee glue) and has been widely used as a counterfeit propolis because Chinese propolis is typically the poplar-type propolis, the chemical composition of which is determined mainly by the resin of poplar trees. The discrimination of Chinese propolis from poplar tree gum is a challenging task.

OBJECTIVE

To develop a rapid thin-layer chromatographic (TLC) identification method using chemometric fingerprinting to discriminate Chinese propolis from poplar tree gum.

METHODS

A new TLC method using a combination of ammonia and hydrogen peroxide vapours as the visualisation reagent was developed to characterise the chemical profile of Chinese propolis. Three separate people performed TLC on eight Chinese propolis samples and three poplar tree gum samples of varying origins. Five chemometric methods, including similarity analysis, hierarchical clustering, k-means clustering, neural network and support vector machine, were compared for use in classifying the samples based on their densitograms obtained from the TLC chromatograms via image analysis.

RESULTS

Hierarchical clustering, neural network and support vector machine analyses achieved a correct classification rate of 100% in classifying the samples. A strategy for TLC identification of Chinese propolis using chemometric fingerprinting was proposed and it provided accurate sample classification.

CONCLUSION

The study has shown that the TLC identification method using chemometric fingerprinting is a rapid, low-cost method for the discrimination of Chinese propolis from poplar tree gum and may be used for the quality control of Chinese propolis.

Microfluidic Paper-Based Analytical Devices (μPADs) and Micro Total Analysis Systems (μTAS): Development, Applications and Future Trends

Microfluidic paper-based analytical devices and micro total analysis systems are relatively new group of analytical tools, capable of analyzing complex biochemical samples containing macromolecules, proteins, nucleic acids, toxins, cells or pathogens. Within one analytical run, fluidic manipulations like transportation, sorting, mixing or separation are available. Recently, microfluidic devices are a subject of extensive research, mostly for fast and non-expensive biochemical analysis but also for screening of medical samples and forensic diagnostics. They are used for neurotransmitter detection, cancer diagnosis and treatment, cell and tissue culture growth and amplification, drug discovery and determination, detection and identification of microorganisms. This review summarizes development history, basic fabrication methods, applications and also future development trends for production of such devices.