The usage of phenols in the marketplace has been increasing tremendously, which has raised concerns about their toxicity and potential effect as emerging pollutants. Phenol's structure has closely bonded phenyl and hydroxy groups, thereby making its functional characteristics closely similar to that of alcohol. As a result, phenol is used as a base compound for commercial home-based products. Hence, a simple and efficient procedure is required to determine the low concentration of phenols in environmental water samples. In this research, a method of combining magnetic nanoparticles (MNPs) with surfactant Sylgard 309 was developed to overcome the drawbacks in the classical extraction methods. In addition, this developed method improved the performance of extraction when MNPs and the surfactant Sylgard 309 were used separately, as reported in the previous research. This MNP-Sylgard 309 was synthesised by the coprecipitation method and attracts phenolic compounds in environmental water samples. Response surface methodology was used to study the parameters and responses in order to obtain an optimised condition using MNP-Sylgard 309. The parameters included the effect of pH, extraction time, and concentration of the analyte. Meanwhile, the responses measured were the peak area of the chromatogram and the percentage recovery. From this study, the results of the optimum conditions for extraction using MNP-Sylgard 309 were pH 7, extraction time of 20 min, and analyte concentration of 10.0 μg mL-1. Under the optimized conditions, MNP-Sylgard 309 showed a low limit of detection of 0.665 μg mL-1 and the limit of quantification was about 2.219 μg mL-1. MNP-Sylgard 309 was successfully applied on environmental water samples such as lake and river water. High recovery (76.23%-110.23%) was obtained.
Due to the outbreak of the COVID-19 pandemic, practicing personal hygiene such as frequent hand sanitising has become a norm. The making of effective hand sanitiser products should follow the recommended formulations, but the high demand worldwide for such affordable products could have made them a candidate for counterfeiting, thus deserving forensic determination and profiling for source determination or supply chain tracing. In this study, determination and discrimination of hand sanitisers was carried out by employing attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics. Fifty commercially available hand sanitisers were obtained from the market and analysed. ATR-FTIR profiles of each sanitiser were compared and decomposed by principal component analysis (PCA) followed by linear discriminant analysis (LDA). Physical observation enabled the discrimination of seven samples based on their respective colours, the presence of beads and their colours, and the physical forms of formulations. Subsequently, eight distinct patterns were observed through visual comparison of ATR-FTIR profiles of the remaining 43 samples. An initial unsupervised exploratory PCA model indicated the separation of two main groups with ATR-FTIR profiles similar to those of ethanol and isopropanol, respectively. The PCA score-LDA model provided good predictions, with a 100% correct classification into eight different groups. In conclusion, this study demonstrated a quick determination and discrimination of hand sanitiser samples, allowing screening for any restricted components and sample-to-sample comparison.
Humans are subjected to various diseases; hence, proper diagnosis helps avoid further disease consequences. One such severe issue that could cause significant damage to the human liver is the hepatitis C virus (HCV). Several techniques are available to detect HCV under various categories, such as detection through antibodies, antigens, and RNA. Although immunoassays play a significant role in discovering hepatitis viruses, there is a need for point-of-care tests (POCT). Some developing strategies are required to ensure the appropriate selection of POCT for HCV detection, initiate appropriate antiviral therapy, and define associated risks, which will be critical in achieving optimal outcomes. Though molecular assays are precise, reproducible, sensitive, and specific, alternative strategies are required to enhance HCV diagnosis among the infected population. Herein, we described and assessed the potential of various microfluidic detection techniques and confirmatory approaches used in present communities. In addition, current key market players in HCV chip-based diagnosis and the future perspectives on the basis of which the diagnosis can be made easier are presented in the present review.
Protox inhibiting herbicides such as nitrofen have detrimental effects on the environment and human health. The current work aims to fabricate a Candida rugosa lipase (CRL)-based electrochemical sensor for rapid and sensitive detection of protox inhibiting herbicides (nitrofen). We proposed the use of poly(vinylpyrrolidone) (PVP) and amino-acids to promote accumulation of Zn2+ ions at the surfaces of Candida rugosa lipase (CRL) and subsequently induce self-assembly of a CRL-zeolitic imidazolate framework (ZIF) structure. This process can be easily and rapidly achieved via a one-pot facile self-assembly method. Steady-state fluorescence spectroscopy indicated that CRL has undergone a conformational change following encapsulation within the ZIF structure. This conformational change is beneficial as the prepared PVP/Glu/CRL@ZIF-8 exhibited enhanced catalytic activity (207% of native CRL), and higher substrate affinity (lower Km than native CRL) and showed high stability under harsh denaturing conditions. PVP/Glu/CRL@ZIF-8 was finally used for electrochemical biosensing of nitrofen. The fabricated biosensor has a wide linear detection range (0-100 μM), a lower limit of detection and a good recovery rate.
Unpredictable natural disasters, disease outbreaks, climate change, pollution, and war constantly threaten food crop production. Smart and precision farming encourages using information or data obtained by using advanced technology (sensors, AI, and IoT) to improve decision-making in agriculture and achieve high productivity. For instance, weather prediction, nutrient information, pollutant assessment, and pathogen determination can be made with the help of new analytical and bioanalytical methods, demonstrating the potential for societal impact such as environmental, agricultural, and food science. As a rising technology, biosensors can be a potential tool to promote smart and precision farming in developing and underdeveloped countries. This review emphasizes the role of on-field, in vivo, and wearable biosensors in smart and precision farming, especially those biosensing systems that have proven with suitably complex and analytically challenging samples. The development of various agricultural biosensors in the past five years that fulfill market requirements such as portability, low cost, long-term stability, user-friendliness, rapidity, and on-site monitoring will be reviewed. The challenges and prospects for developing IoT and AI-integrated biosensors to increase crop yield and advance sustainable agriculture will be discussed. Using biosensors in smart and precision farming would ensure food security and revenue for farming communities.
Borassus flabellifer L., commonly known as Asian palmyra, is native to South and Southeast Asia. The endosperms of B. flabellifer (known as nungu in Dravidian culture) are widely consumed during the summer season. It is rich in various nutrients and helps in reducing weight, treating skin and digestive issues, lowering body temperature, and managing migraines and diabetes. This study focuses on identifying the small molecules and proteins from the two varieties of B. flabellifer tender fruit endosperms collected from districts around Chennai, Tamil Nadu, India. The collected free nuclear endosperm was subjected to direct extraction and the mesocarp and cellular endosperms were lyophilized and homogenized. Metabolites were extracted by hexane, methanol, and chloroform and investigated using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). The compounds identified were from the classes of carboxylic acids, flavonoids, amino acids, alkaloids, fatty acids, oligopeptides, vitamins, and glycosides. High-performance liquid chromatography (HPLC) technique was employed to estimate the quantity of amino acids, wherein the total amino acid in the green variety was found to be higher than in the black variety. Proteins were identified after simulating with a gastrointestinal enzyme using liquid chromatography tandem mass spectrometry (LC-MS/MS)-based peptide mass fingerprinting. The different mineral oxides present in the tender fruit endosperm were identified using X-ray diffraction studies, which confirmed the presence of mineral oxides, such as Br1.25ClO2.75Pb3.88, calcium zirconium tantalum oxide, and barium fluoroniobate. This study validates the presence of bioactive metabolites in green and black varieties of B. flabellifer tender fruit endosperm with a range of activities, such as anti-inflammatory, antibacterial, anticancer, and anti-diabetic properties.
With increasing population there is a rise in pathological diseases that the healthcare facilities are grappling with. Sweat-based wearable technologies for continuous monitoring have overcome the demerits associated with sweat sampling and sensing. Hence, sweat as an alternative biofluid holds great promise for the quantification of a host of biomarkers and understanding the functioning of the body, thereby deducing ailments quickly and economically. This comprehensive review accounts for recent advances in sweat-based LOCs (Lab-On-Chips), which are a likely alternative to the existing blood-urea sample testing that is invasive and time-consuming. The present review is focused on the advancements in sweat-based Lab-On-Chips (LOCs) as an alternative to invasive and time-consuming blood-urea sample testing. In addition, different sweat collection methods (direct skin, near skin and microfluidic) and their mechanism for urea sensing are explained in detail. The mechanism of urea in biofluids in protein metabolism, balancing nitrogen levels and a crucial factor of kidney function is described. In the end, research and technological advancements are explained to address current challenges and enable its widespread implementation.