Critical reviews in analytical chemistry最新文献

Nucleic Acid Lateral Flow Assays (NALFAs) have been increasingly explored for the detection of DNA and RNA, in particular for the specific screening of pathogens. Traditional lateral flow assays developed for the detection of nucleic acids rely heavily on antibody-antigen interactions. However, there are plenty of solutions that resort fully or partially to the use of oligonucleotides as a way to perform specific recognition. This review covers the main detection strategies that are present in these systems, as well as readout strategies, signal amplification routes, and overall performance of the analytical parameters, as well as commercial potential. Special attention will be given to the detection of various RNA viruses infecting both human and animal hosts, mainly coronaviruses, given the abundance of recent literature about the subject. Moreover, various examples of commercial solutions related with oligonucleotide-based NALFAs are listed. While the compilation of such topics intends to be a pool of knowledge about oligonucleotide-based NALFA, new directions and emerging innovations are covered in detail.

Soil can be directly polluted with microplastics (MPs) and it additionally acts as a major sink for MPs from atmospheric deposition and surface waters. Accumulation of MPs in soil and their persistence in the soil environment prioritizes efforts to effectively assess pollution levels and undertake measures to protect soil from long-term adverse effects. Of various analytical techniques available for MP detection and characterization, portable instruments based on spectroscopic, electrochemical, mass spectrometric, and optical imaging methods gain an increasing interest. They are useful for initial screening and selection of soil samples for detailed analysis and reduce the risk of contamination during sample transport, storage, and laboratory treatment. They are more environmentally friendly and better comply with green analytical chemistry principles than their laboratory counterparts. However, their analytical performance needs to be improved. This article discusses portable analytical instruments used for in-situ analysis of MPs in soil and shows their advantages and limitations.

The creation of wearable biosensors has greatly progressed noninvasive health monitoring, providing immediate insights into biochemical and biophysical processes. Among various biofluids, sweat stands out as a remarkable medium because of its easy accessibility and diverse biomarker profile, allowing for the possibility of ongoing health evaluations outside of traditional clinical environments. Recent advancements in material science, flexible electronics, and biosensor technologies have significantly advanced sweat-based wearable biosensors, enabling the smooth incorporation of sensors into patches, tattoos, clothing, and accessories. These devices, designed to detect ions, metabolites, hormones, and various biomolecules, show great potential for monitoring metabolic, physiological, and environmental indicators associated with health and wellness. Traditional methods for sweat sampling depended significantly on laboratory tools and had restricted biosensing abilities; nonetheless, innovative microfluidic systems now allow for immediate, on-skin collection and analysis of sweat in real time. This review explores the progress in sensor technologies-including colorimetric, potentiometric, and amperometric methods-that enhance the sensitivity, selectivity, and durability of biosensors based on sweat analysis. Hybrid platforms that integrate electrochemical and optical sensors demonstrate significant potential in the analysis of multiple biomarkers, facilitating advancements in personalized health monitoring, chronic disease management, and performance tracking. Nonetheless, obstacles persist, such as sensor reliability, biofouling, fluctuations in the environment, and precision of data, especially in changing conditions. In tackling these challenges, the review delves into advancements in substrate materials, electrode fabrication, and microfluidic handling systems. Furthermore, it explores the incorporation of machine learning to improve data processing, the creation of self-sustaining systems through biofuel cells and triboelectric nanogenerators, and strategies for commercialization to facilitate widespread consumer acceptance. Future perspectives envision wearable sweat sensors integrating with medical diagnostics and real-time treatment options, ultimately enhancing personalized and accessible healthcare.

The increasing threat of pathogenic bacteria to public health has necessitated the development of rapid, sensitive, and cost-effective detection methods. Chitosan (CS), a naturally occurring biopolymer with excellent biocompatibility, biodegradability, and antimicrobial properties, has emerged as a versatile material in the construction of fluorescence and colorimetric biosensors. Recently substantial progress has been made in the design and application of CS-based sensing platforms for bacterial detection. Moreover, the integration of CS with quantum dots, metallic nanoparticles (such as AgNPs and AuNPs), organic dyes, and stimuli-responsive polymers has significantly enhanced the optical performance and specificity of these sensors. Reported limits of detection (LOD) for CS-based fluorescence and colorimetric biosensors range from as low as 6.8 CFU/mL to 900 CFU/mL, highlighting their remarkable sensitivity compared to conventional methods. This review comprehensively explores the advancements in CS-based fluorescence and colorimetric sensors for detecting a wide range of pathogenic bacteria. Emphasis is placed on the synthesis strategies, functionalization techniques, detection mechanisms, and sensitivity improvements achieved through nanomaterial hybridization. By critically analyzing the strengths and emerging trends, the review provides a roadmap for future research and development of CS-based optical biosensors for bacterial diagnostics in clinical, environmental, and food safety applications.

With growing concerns about water pollution, there is an urgent need to develop sensitive, selective, and fast detection technologies. This review provides a critical overview of the recent progress in novel electrochemical aptamer-based sensors (E-aptasensors) developed for priority water contaminants, such as cyanotoxins, pesticides, antibiotics, pathogenic bacteria, nanoplastics, and nitrogen. The combined application of nanomaterials (e.g., gold nanoparticles, graphene, carbon nanotubes, conducting polymers, and metal-organic frameworks) has made great strides in analytical sensing, advancing the detection of fM targets in heterogeneous media. Different electrochemical transductions, such as cyclic voltammetry (CV), linear sweep voltammetry (LSV), differential pulse voltammetry (DPV), electrochemical impedance spectroscopy (EIS), and square wave voltammetry (SWV), were compared in terms of sensitivity, selectivity, and applicability in authentic samples. Major issues, such as the reproducibility of sensors, matrix interference, and field deployment are addressed, and future directions are proposed, including miniaturization, integration with Internet of Things (IoT) platforms, and regulatory alignment for environmental surveillance.

3-monochloropropane-1,2-diol (3-MCPD) is a heat-induced food processing contaminant that shows a potential health concern. Therefore, quantification of 3-MCPD levels in foodstuffs has great importance in the context of food safety. Thus far, various approaches have been proposed for the 3-MCPD assay, including GC-MS, HPLC, HPLC-MS techniques, and chemical sensor technology. Among them, chemical sensor technology shows good promise as being robust, specific, sensitive, and capable of on-site measurements. Recently, chemical sensors based on electrochemical, UV-Vis spectroscopy, and fluorescence methods have been broadly employed in 3-MCPD sensing. Hence, the current review provides a concise introduction to chemical sensors, with a comprehensive discussion on the recent advances in the development and applications of electrochemical, UV-Vis spectroscopy, and fluorescence 3-MCPD sensors. Furthermore, a comparative analysis of the various sensor types was also highlighted. The detection challenges and future viewpoints of 3-MCPD sensors were discussed for the development of food safety monitoring applications in the food industry. Overall, electrochemical sensors demonstrate the best detection performance among others. On the other hand, fluorescence-based systems offer quick responses, and UV-Vis methods provide cost-effective alternatives, thereby highlighting their complementary strengths for the reliable detection of 3-MCPD in real-world samples. Finally, the findings outlined in this review are expected to promote the advances of more efficient and widely accessible monitoring devices for future food quality control.

Metoprolol, a widely prescribed beta-blocker used in the treatment of cardiovascular diseases, necessitates precise and reliable determination in pharmaceutical formulations and biological samples. Traditional analytical methods, while effective, often involve hazardous chemicals, extensive energy consumption, and the use of large volumes of solvents, raising environmental concerns. This review focuses on the green innovations in analytical methodologies for metoprolol determination. It examines alternative techniques that minimize environmental impact, including eco-friendly solvents, reagentless detection methods, and energy-efficient approaches. Key green technologies such as chromatography, spectrometry, and electrochemical techniques are discussed, with an emphasis on their potential to replace or enhance traditional methods. It introduces Analytical GREEnness Metric Approach, Green Analytical Procedure Index, Blue Applicability Grade Index, Carbon Footprint Reduction Index and Click analytical chemistry tools as critical frameworks for assessing the sustainability and efficiency of green analytical approaches. These tools provide a standardized approach to evaluate various green methods based on factors such as waste reduction, solvent use, energy consumption, and overall environmental footprint. Additionally, the review examines how these frameworks can guide the development of new green technologies in metoprolol analysis. The study concludes with recommendations for future research, emphasizing the importance of integrating green chemistry principles into pharmaceutical analysis and quality control while minimizing environmental impacts.

Globally, caffeine is one of the most frequently consumed psychoactive substances and is present in drinks, food products, and medicines. Moderate caffeine consumption benefits health, acting as an antioxidant, cardiovascular protector, neuroprotective agent, etc. Caffeine extraction and analysis by conventional approaches usually depend on toxic solvents and produce large volumes of waste, which constitutes an environmental challenge. Green analytical chemistry has been developed to provide sustainable alternatives that are green, affordable, and less hazardous methods. This article covers various green extraction methods. It also highlights green analytical techniques for caffeine determination while focusing on the reduction of solvent utilization and waste generation. Using different matrices, green electrochemical and fluorescence-based sensors are created for the sensitive and quick detection of caffeine. The expanding use of green chemistry principles for caffeine analysis is indicative of a growing need for further exploration and discovery of sustainable practices in the food, beverage, and pharmaceutical industries. This review presents a comprehensive overview of caffeine, emphasizing green extraction techniques, sustainable analytical approaches, and recent advances in electrochemical sensor and Fluorescence sensor applications.

Toxicity is a major problem for public health, across the world, with thousands of deaths happening each year, primarily in impoverished nations. Estimating the precise toxic substance that is responsible for the intoxication occurred and rendering accurate treatment is one of the most vital steps in healthcare. One type of toxin that is extremely dangerous to human health is pesticides. They may infiltrate the human body accidentally, purposefully, or through their line of work. These pesticides can cause symptoms ranging from minor skin rashes and vomiting to serious ones like impairing sperm quality, neural development, and conception rates. One such class of pesticides is the pyrethroids. Synthetic pyrethroids like cypermethrin cause various health issues such as numbness, itching, burning sensation, and in severe cases, loss of bladder, muscle weakness, salivation, shortness of breath and seizures. Several methods exist to determine and quantify cypermethrin that humans are exposed to. The review provides an up-to-date summary of analytical and extraction approaches for detecting cypermethrin residues, in human samples by simple methods like Thin Layer Chromatography (TLC) and by high end sensitive methods like Gas Chromatography-Mass Spectrometry (GC-MS), Gas Chromatography-Mass Spectrometry/Mass- Spectrometry (GC-MS/MS), Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS), High Performance Liquid Chromatography (HPLC) and Immunoassay techniques. It also adds light to the various sample preparation and clean-up techniques with a brief section on major analytical challenges associated with cypermethrin estimation in human samples.

Alzheimer's disease (AD) is a neurological ailment characterized by the degeneration of neurons in specific areas of the brain, resulting in memory loss, cognitive decline, and eventually dementia. AD is both lethal and currently incurable since the demise of brain cells cannot be reversed or stopped; however, ongoing advancements and research offer hope, aiming to uncover effective clinical and therapeutic strategies that could slow down the progression and improve patient outcomes. Surveys indicate that the treatment of AD is significantly expensive, with the global annual cost of treating AD amounting to US$1 trillion. Therefore, the early identification of this condition is of the utmost importance, as it can assist in slowing down the advancement of Alzheimer's and enable proper diagnosis. Biosensors are analytical instruments utilized for the early identification of AD and are in great demand due to their exceptional selectivity, sensitivity, and affordability. Biosensors integrated with transition-metal dichalcogenides (TMDCs) enhance the efficiency of a biosensor by significantly amplifying biosensing signals. This study examines AD and its underlying biochemical mechanisms, explicitly focusing on several hypotheses linked to AD, the biomarkers involved, and the use of TMDC-based biosensors for early detection of the illness with greater precision.