Current Analytical Chemistry - Volume 19, Issue 3, 2023

High levels of metallic ions, particularly heavy metals, can cause serious damage not only to public health but to the whole ecosystem. Therefore, rapid and precise detection and monitoring of heavy metals have become vital. The detection of heavy metals in water using conventional monitoring approaches based on physicochemical and analytical procedures, e.g., inductively coupled plasma combined with atomic absorption spectroscopy, X-ray fluorescence, instrumental neutron activation analysis, etc., has been immensely utilized. However, the sophisticated sample preparation and evaluation procedures for most of the mentioned methods are time- and labor-intensive, and economically more favorable detection approaches, e.g., sensors and lab-on-a-chip techniques, are being developed. Chemical sensors (electrochemical, optical, and piezogravimetric) with different sensing platforms (nanostructures, biological, polymeric, and macrocyclic) have been considered to be the most promising ones, owing to their strong adsorption of target elements, fast electron transfer kinetics, and biocompatibility, which are very apt for sensing applications. The combination of electrochemical, optical, and piezogravimetric techniques with nanomaterials has enhanced the sensitivity, limit of detection, and robustness of the chemosensors. Following this perspective, this review highlights surface modification platforms of sensors that enhance the detection properties (sensitivity, selectivity, limit of detection, and linear range) of the proposed devices, including nanostructures, biological networks, polymers, and macrocycles with a special emphasis on calixarenes/resorcinarenes oligomers. The capabilities, limitations, and prospect assessments of the covered techniques in detection and monitoring have been highlighted.

Background: Worldwide, the prescriptions for asthma drugs are on the rise. However, antiasthma drugs have side effects and can lead to fatal death at higher doses. Quite often, these drugs are abused as growth promoters in poultry/livestock as well as by athletes to enhance their performance. Consequently, it is vital to design uncomplicated, portable, rapid and highly sensitive means of detecting these anti-asthma drugs in pharmaceutical formulations and other sample matrices. This review highlights the use of electrochemical sensors as alternative methods to conventional analytical techniques for detecting anti-asthma drugs in pharmaceuticals and biological fluids. Methods: Literature covering diverse detection methods for anti-asthma drugs were reviewed to provide background information in this area of research. Next, the literature survey focused primarily on the emergence of the nanotechnology platform, including the strengths and weaknesses of this approach. Finally, a perspective on the future direction of this method was summarized. Results: Electrochemical sensors offer several advantages over conventional methods, which require long and tedious extraction, pre-concentration and clean up steps. Moreover, electrochemical sensor techniques are less expensive, easy to operate and avoid the need for harmful reagents known to generate a huge amount of non-environmental friendly chemicals. Conclusion: Nanotechnology-based electrochemical sensors represent a promising platform for analysing anti-asthma drugs in pharmaceuticals and biological fluids given their beneficial effects such as low cost, use of less health hazardous materials, and compatibility with environmental health.

In recent decades, increased demand for food has been caused by a rapid rise in the human population, which triggers agricultural intensification. To resist undesired pests from infecting crops, farmers widely utilize pesticides to improve agricultural production during the pre-harvest period. Despite the fact that pesticides cause a number of health risks, there is insufficient monitoring of these toxins. Therefore, it is important to develop a specific, accurate, and efficient method for determining the pesticides in varied samples in order to safeguard health against potential risks. Due to the lower concentrations of active compounds and their diversity of availability, it is challenging to detect pesticide residues in different samples. In this case, to effectively separate, identify, and accurately quantify pesticides at low concentrations in a variety of samples, a reliable analytical methodology is needed. Recently, the application of high-performance thin layer chromatography (HPTLC) offers a wider scope with excellent separation, identification, and quantitative/qualitative determination in pesticide analysis. In spite of their extremely low quantities, pesticide residues can be accurately and precisely identified using HPTLC. HPTLC has a number of benefits, such as easy sample preparation, automation, densitometry, and hyphenation, and is particularly well suited for identification and detection. Concerning this, the proposed review paper provides an overview of stationary phases, mobile phases, sample applicators, visualization, derivatization, and detection of HPTLC utilized for the identification and detection of pesticide residues in agriculture and environmental samples.

Background: Sertraline (ST) hydrochloride is an anti-depressant of the selective serotonin reuptake inhibitor (SSRI) class. Potentiometric sensors are an appealing route for detecting drugs due to some advantages in terms of sensitivity, feasibility, selectivity, fast response, tolerance to turbidity and colour of solutions, and cost-effectiveness. Methods: A mixture of polyvinyl chloride powder (PVC) with o-nitrophenyl octyl ether and the ion association complex was dissolved in tetrahydrofuran (THF) to prepare the membrane for the proposed sensor. The sensor was calibrated and then electrochemically used for detecting ST in pharmaceutical samples. Results: The near Nernstian response was observed for a concentration of 1.0 x 10^-8 - 1.0 x 10^-2 mol L^-1 with 58.62 mV as a slope per concentration decade. This direct potentiometric measurement resulted in average recoveries of 96.0 ± 0.2%. Moreover, good selectivity for sertraline with respect to many inorganic and organic cations was observed. Conclusion: The proposed sensor was simple to use and produced accurate and precise results. The molecule's chemical and biological activities were revealed using theoretical calculations. Regarding the chemical activities, calculations were made on the 3-21g and 6-31g while the SDD bases were set at B3LYP, HF, and the M062X level. Molecular docking calculations were designed against cancer proteins in order to have details regarding the molecule's biological activity.

Background: In the current research, a green, fast and cheap extraction method based on deep eutectic solvent was developed for the preconcentration of phenylalanine. Then, high performance liquid chromatography (HPLC) as a sensitive and accurate technique was used to determine amounts of preconcentrated phenylalanine. Objective: The combination of the HPLC technique and extraction procedure using deep eutectic solvent makes it possible to find a good procedure for the preconcentration of phenylalanine in different media with acceptable precision and accuracy. Methods: Decanoic acid and tetrabuthylammonium bromide were used as the components of the green solvent. Then, the synthesized green solvent was used for the preconcentration of phenylalanine. HPLC equipped with a UV-VIS detector, a C18 column, a mixture of sodium dihydrogen phosphate 2-hydrate (20 mM, pH 6.60)-ACN (70-30%) as the mobile phase, and the wavelength of 245 nm were selected as the best separation. Results: The chief characteristic of deep eutectic solvent was identified using Fourier transform infrared spectroscopy. Central composite design to evaluate the effects of preconcentration parameters showed that the pH value of 6.31, salt concentration of 0.272 M, DES volume of 226 μL, and stirrer time of 5.60 min were suggested as the best conditions of separation. Total analysis time was 5.50 min. Conclusion: Validation of designed analysis exposed good linearity (0.015-1.50 μg/mL), suitable sensitivity, excellent preconcentration (32.50) and enrichment (21.15) factors, acceptable relative standard deviation (3.07%), and low amounts of detection limit (0.015 μg/mL). Finally, the designed method was effectively used for the determination of phenylalanine in cheese and yoghurt with relative recoveries of 113.33 to 125.00% and 94.00 to 100.00%, respectively.