Environmental pollution caused by hazardous trace metals, such as arsenic, mercury, uranium, and iron, presents significant risks to both human health and ecosystems, underscoring the need for advanced detection technologies. Metal-organic frameworks (MOFs), known for their high surface area, tunable porosity, and selective metal-binding properties, have emerged as promising candidates for detecting these hazardous metals in environmental matrices. This review explores the potential of MOFs in trace metal detection and their applications in monitoring pollutants in water, soil, and food. The review covers recent advancements in MOF-based sensors, focusing on their ability to provide rapid, sensitive, and selective detection methods, which are crucial for public health protection and industrial safety. Furthermore, it highlights the role of MOFs in addressing environmental concerns related to heavy metal contamination. The manuscript also examines key challenges faced by MOF-based sensing technologies, including issues of stability, scalability, and cost-efficiency, and proposes future research directions to overcome these barriers. By exploring the current state of research and identifying emerging opportunities, this review emphasizes the transformative potential of MOFs in environmental monitoring and hazardous material management. MOF-based technologies offer sustainable solutions for the detection and remediation of toxic contaminants, addressing the global challenges posed by heavy metal pollution in environmental contexts.
The strengthening and growth of forensic science is vital for a Nation's law enforcement and criminal justice system. Forensic agencies serve the criminal justice system by analyzing crime scene evidence, such as DNA, ballistic, gunshot residue, fingerprints, and questioned documents. With the constraint of minimal quantity of evidence recovered from crime scenes, there is a growing need for nondestructive analysis techniques that can preserve evidence for further testing or legal proceedings. The advent of Laser-Induced Breakdown Spectroscopy (LIBS) in the late twentieth century has revolutionized forensic science by providing a rapid, nondestructive, and highly accurate method for elemental analysis. LIBS provides an in-situ, faster, minimally-destructive method of elemental analysis. Integrating LIBS into the forensic science workflow can significantly improve evidence analysis's speed, accuracy, and efficiency. This article presents a comprehensive review of the transformative potential of LIBS in various forensic applications, emphasizing its advantages over traditional forensic methods. The article details the working principle of LIBS, which involves using a laser to create a plasma that emits light characteristic of the sample's elemental composition. This versatile technique is capable of analyzing various crime scene evidences and thus making it a fascinating tool for forensic scientists.
Therapeutic sedatives, including benzodiazepines, barbiturates, and Z-drugs, are widely prescribed for anxiety, insomnia, and related disorders but are associated with dependence, overdose, and abuse, creating a need for rapid and selective monitoring. Conventional analytical techniques provide high accuracy but remain limited by cost, infrastructure requirements, and poor portability. Recent advances in nanomaterial-based electrochemical and optical biosensors have enabled sensitive and point-of-care detection of sedatives in complex biological and environmental matrices. This review critically evaluates electrochemical, fluorescence, colorimetric, and SERS-based sensing platforms, with emphasis on nanomaterial-analyte interactions, sensing mechanisms, and structure-function relationships governing analytical performance. Platform-specific advantages, limitations, multiplexing capability, and challenges associated with real-sample analysis and point-of-care translation are discussed, together with emerging directions in AI-assisted, smartphone-integrated, and wearable biosensing.
Food safety can be ensured by rapid, accurate, and inexpensive methods to detect food additives, which can be harmful when consumed beyond a permissible limit. Although variety of highly sensitive traditional techniques are available for the quantification of food additives, their application is limited due to high instrumentation cost, time-consuming procedure, and complex sample preparation. In contrast, electrochemical sensors have gained prominence and are used as an alternative technique due to their portability, inexpensive nature, high sensitivity, and real-time detection capabilities. This review explores the use of metal oxides, doped metal oxides, and carbon-based nanomaterials to enhance the performance of an electrochemical sensor. It emphasizes the role of dopants, hybrid nanocomposites, their structural features, and synergistic effects to improve the electron transfer, selectivity, and sensitivity. The importance of electroanalytical techniques, including CV, DPV, SWV, and EIS, is highlighted for monitoring food safety. Furthermore, the review discusses the current challenges such as reproducibility, electrode fouling, environmental impact, and stability when used in real food matrices. Further, it discusses the new developments for fabricating next-generation sustainable electrochemical sensors for food monitoring, such as integration of nanomaterials with IoT- and IoT-based platform offering a future perspective on the development of electrochemical sensors.
Environmental pollution is a major global challenge that adversely affects human health, biodiversity, and ecosystems. In this regard, the development of portable and wearable sensing technologies has become increasingly important for real-time, on-site monitoring of environmental pollutants. Laser-induced graphene (LIG) has recently emerged as a promising carbon nanomaterial distinguished by its porous architecture, high conductivity, and exceptional electrochemical performance. Its ability to immobilize diverse biological and chemical probes has established LIG as a powerful platform for next-generation portable sensors. This study outlines recent advances in LIG electrodes used in portable and wearable electrochemical devices, with a particular focus on the functionalization of electrode materials and their application in detecting environmental pollutants. The advancement of LIG electrodes is thoroughly examined through various surface functionalization techniques, including the incorporation of polymers, metal nanoparticles, and metal complexes. Moreover, the review explores the practical implementation of LIG-based electrochemical platforms for quantifying and detecting pesticides, phenolic compounds, antibiotic residues, and heavy metals. Finally, it outlines existing limitations and emerging challenges in translating LIG technologies into fully portable and wearable systems, and proposes future research directions to accelerate their deployment in real-world environmental monitoring.
Amphetamine-type stimulants (ATSs) are among the most widely abused drugs globally, posing serious threats to public health through addiction, physical and psychological harm, and associated social problems such as increased crime rates. Effective clinical management of ATSs overdose and abuse monitoring demand analytical methods that are not only sensitive, accurate, but also rapid and adaptable to real‑world settings. However, conventional detection approaches often face challenges including limited sensitivity, prolonged analysis time, insufficient selectivity in complex matrices, and poor suitability for on‑site or point‑of‑care testing. These limitations underscore the urgent need for advanced analytical strategies that can overcome such hurdles. This review comprehensively summarizes progress since 2017 in sample pretreatment and detection techniques for ATSs. It covers established methods such as ultrasonic‑assisted extraction and liquid‑liquid extraction, as well as emerging approaches including solid‑phase microextraction and liquid-phase microextraction, with a particular focus on the role of innovative materials-such as multi‑walled carbon nanotubes and metal‑organic frameworks-in improving extraction efficiency and analytical performance. For detection, chromatographic-based methods are discussed, alongside the rapidly evolving field of high-resolution mass spectrometry technology. Finally, the review critically compares the advantages and limitations of current techniques and outlines promising directions for future development.
Bisphenol A (BPA) is a well-known endocrine-disrupting chemical that poses risks to human health by interfering with hormonal systems. Despite regulatory restrictions, BPA remains widely used in polycarbonates and epoxy resins, leading to its continuous release into the environment. Its presence in aquatic systems and subsequent transfer through ecosystems highlight the need for effective detection methods. Sensing of BPA in environmental samples remains challenging due to complex matrices, low concentration levels, and the requirements for high selectivity and sensitivity. These demands have driven the rapid development of advanced functional materials for sensing applications. This review provides a critical overview of recent strategies for BPA detection, with focuses on electrochemical and optical sensing methodologies. Emphasis is placed on the development and application of different types of functional materials, including organic, inorganic, and metal-organic based systems. The advantages and limitations of these approaches are discussed to highlight current challenges and future perspectives in BPA monitoring.
Cannabis-based products used in medicine and wellness are chemically complex mixtures of cannabinoids, terpenes, flavonoids (including cannflavins), and degradation products whose profiles can shift substantially with cultivar genetics, cultivation conditions, extraction workflows, formulation choices, and storage history. This field-to-field and lab-to-lab variability, compounded by inconsistent analytical practices and uneven validation standards, can undermine potency labeling, cross-product comparability, and the interpretation of clinical and pharmacological findings. This review critically summarizes current quantitative and fingerprint-based strategies for measuring cannabinoids and related constituents across major product types (flowers/biomass, oils, edibles, and vape products) and proposes a practical "field-to-result" framework spanning sampling, method selection, validation, and lifecycle quality control. Drawing on peer-reviewed literature and metrological guidance, we evaluate LC-UV/LC-MS/MS, GC-FID/GC-MS, quantitative and structural NMR, and selected spectroscopic and aerosol approaches, with emphasis on isotope-dilution concepts, calibration design, matrix effects, validation criteria, and chemometric tools for multivariate fingerprints. The evidence is synthesized to map analyte classes and matrices to fit-for-purpose platforms and sample preparation schemes, highlight best practices for internal standards and matrix-matched calibration, and summarize commonly applied acceptance expectations for accuracy and precision. Strategies to reduce or correct matrix effects are detailed, and the role of high-dimensional fingerprints is explained as a complement to targeted potency panels for identity confirmation, process drift monitoring, lot release decisions, and traceability. Overall, combining validated potency assays with statistically governed fingerprinting offers a pragmatic route to harmonize cannabinoid testing, improve data integrity, and better support future phytomedicine research, clinical translation, and regulatory oversight.
Rapid, accurate, and reliable detection of pathogenic bacteria remains a critical need in clinical, food, and environmental monitoring. In today's context, nucleic acid amplification-mediated biosensing have emerged as a prominent approach to improve detection sensitivity, whereas dual-mode signal readout approaches have more enhanced analytical robustness and reliability. This review outlines recent advances in nucleic acid signal amplification strategies, including enzyme-based methods like LAMP, RPA, and RCA, as well as enzyme-free approaches like HCR, CHA, and EDR. Special attention is given to incorporating these amplification methods into dual-mode biosensing systems that combine both optical and electrochemical transduction mechanisms. This integration enables complementary signal generation and improves detection accuracy by reducing false-positive and false-negative results. This study critically examines the advancement of nucleic acid signal amplification strategies (NASAS)-mediated dual-mode sensing systems for detecting major pathogenic bacteria, including Escherichia coli, Salmonella, Listeria monocytogenes, Staphylococcus aureus, and Vibrio species, focusing on selectivity, sensitivity, assay design, and real-sample applicability. Finally, the review highlights present challenges related to system integration, standardization, and point-of-care applications. Additionally, it outlines potential future directions for rendering nucleic acid amplification-based dual-mode probes into practical diagnostic devices. Overall, this study affords a comprehensive synthesis of emerging approaches and design mechanisms for next-generation diagnostic scaffold for pathogen analysis.
Targeted Drug Delivery Systems (TDDS) have been proposed as an innovative approach for enhancing therapeutic efficiency through selective targeting of drugs. Although there has been substantial progress in the area of targeted therapy, the application of TDDS into clinical practice has been impeded by difficulties in their bioanalysis. Existing bioanalytical methods designed for small-molecule drugs are not sufficient for proper characterization of the complex structure, dynamics, and functionality of the advanced delivery systems. This article reviews various methods of bioanalysis used in the assessment of TDDS at the molecular,cellular, tissue,and in vivo levels. Special emphasis is placed on problems such as separation of encapsulated and released drugs, the formation of the protein corona, matrix effects, biodistribution analysis, and detection of very low drug concentrations. Additionally, the review highlights important translational bottlenecks, such as non-standardization of protocols, regulatory challenges, method validation difficulties, and scaling problems.Emerging approaches like artificial intelligence-enabled bioanalysis, multi-omics, smart biosensing, personalized assessment, and digital twin technology are analyzed as possible remedies to tackle the existing challenges.Collectively, these advancements underscore the importance of integrated and standardized bioanalytical frameworks for bridging preclinical evaluation with clinical translation, thereby enabling the successful development and implementation of next-generation targeted drug delivery systems.
Sustainability has become an essential consideration in modern chemical analysis. The green analysis focused on reducing pollution, energy consumption, and waste generation. In addition, the sustainability rules take into account both economic and societal ramifications. Switchable Solvents (SSs) are green solvents developed last year to address pollution issues. This study provides a full examination of SSs, including their designation, characteristics, and applications, with a focus on their importance in sustainability. In this context, the present review examines the types of SS solvents used in sample preparation processes. In contrast, this work shifts the focus from "what" these solvents can do to "how" they align with global sustainability standards. This work introduces the computational tools necessary to measure environmental impact. By applying the Sustainability of Analytical Methods Index (SAMI) software and SIX Score tool for the first time, these provide an objective, data-driven score for sample preparation. In addition, this review adds strategic evaluation by using tools like the sample preparation metric of sustainability (SPMS) and need-quality-sustainability (NQS). This transition from a purely chemical perspective to a "sustainability-first" perspective is essential for the future. Furthermore, this review critically examines sustainability goals, sustainability tools, study cases, reproducibility analysis, conclusions, and future perspectives.
MXenes are fascinating 2D-materials with great potential for electrochemical sensing interfaces owing to their high metallic conductivity, rich surface chemistry, and redox activity. MOFs are unique crystalline structures with ultra-large surface areas and rich adsorption and tunable porous active sites, yet their poor electrical conductivity, charge transport efficiency and chemical and mechanical robustness hinder their practical electrochemical sensing feasibility. Recently, integrating MXenes with MOFs enables designing novel hybrid materials with unique interfacial and synergized properties that resolve this porosity-conductivity trade off. However, engineering MXene@MOFs hybrids with desired heterointerfacial structures and synergized electrochemical sensing properties and behaviors remains under explored. This critical Review discusses the progress of in-situ, ex-situ and derivative methods to engineer MXene@MOFs hybrids with emphasis on interface covalent and non-covalent bonding, distribution of crystallized MOFs into MXenes' interlayer spacing, synergized heterojunctions' formation, and heterointerface sensing mechanism. Moreover, it comprehensively discusses and summaries the progress of these intriguing hybrid materials across wide spectrum of hazardous compounds and environmental pollutants such as antibiotics residuals, heavy metal ions, pesticides, mycotoxins, phenolic, synthetic molecules, and various health related diseases including cancer, amino acids, vitamins, hormones, wearable noninvasive analysis (sweat, saliva, tears and L-cysteine), cardiovascular disease (CVD), glucose, creatinine, and metabolic biomarkers. MXene@MOFs hybrid materials demonstrate unique synergized sensing performance such as the high stability, low signal to noise ratio and lower skin interference impedance compared to Ag/AgCL commercial electrodes. Finally, the sensing mechanism and properties (sensitivity, selectivity, long term stability and reproducibility), commercialization prospects and challenges, future direction and opportunities are discussed.
In this review, we emphasize on ternary deep eutectic solvents (TDESs) utilized in environmental and analytical chemistry for separation and sensing purposes in contrast to their binary counterparts, known as simple deep eutectic solvents (DESs). To ensure food security, high water quality, and environmental protection from the current industrialized era of the twenty-first century, it is of utmost importance to determine and separate effluents, pollutants, or any undesired materials in our related day-to-day utilities, foods, or nature using a more efficient and green separating media or sensor. For this reason, there is no better choice for an analytical chemist to design and use hybrid and natural ternary deep eutectic solvents, with enhanced physicochemical properties. Since the discovery of simple binary DESs, they have been applied in sensing and separation sciences, but the invention of ternary deep eutectic solvents has made them a more interesting and suitable candidate for the development of separation or sensor methodologies based on TDESs. Furthermore, we explore TDES structure-property relationships, showing how the choice of components dictates macroscopic properties. This molecular-level understanding facilitates the rational design of tailored solvents for analytical applications. This review consolidates recent advances in TDES-based sensing and separation to support future research.
Arsenic contamination in food and water remains a major global health issue, particularly across South and Southeast Asia. Although advanced analytical methods such as ICP-MS and GFAAS offer high sensitivity and precision, they are costly, laboratory-bound, and require skilled operators. In contrast, electrochemical nano-biosensors have emerged as a practical and cost-effective alternative, offering low cost, rapid detection, and portability suitable for field applications. This review recent advances in developing green-engineered nanomaterials for electrochemical arsenic detection, emphasizing eco-friendly synthesis routes and environmentally responsible design principles. Green fabrication of metal and metal-oxide nanoparticles, carbon-based materials, and hybrid composites has significantly improved sensor performance by enhancing surface area, conductivity, and catalytic activity while minimizing environmental impact. Key biosensing strategies are discussed, including aptamer-, enzyme-, and whole-cell-based systems capable of distinguishing between arsenic species. The review also highlights innovations in biodegradable polymers, waste-derived carbons, and renewable substrates that align with circular-economy principles. Finally, future perspectives highlight the integration of Internet of Things (IoT) and artificial intelligence (AI) technologies for real-time, decentralized monitoring. Collectively, these green nano-biosensing systems represent a critical step toward accessible, and efficient arsenic detection for global water safety.
Biological macromolecules form the cornerstone of cellular architecture and function through diverse structural arrangements and dynamic interactions. Recent methodological breakthroughs have revolutionized our understanding of these complex biomolecular systems by providing unprecedented resolution of their three-dimensional organization and conformational landscapes. This review examines significant advances in both structural elucidation and functional characterization approaches that bridge the critical gap between static snapshots and dynamic behaviors exhibited within cellular environments. Non-cell-based analytical platforms have similarly evolved, offering enhanced sensitivity, multiplexing capabilities, and reduced sample requirements for interrogating molecular interactions under near-physiological conditions. The integration of experimental approaches with computational modeling has enabled the construction of comprehensive structure-function relationships that more accurately represent macromolecular behavior in native contexts. This review aims to provide a contemporary assessment of biological macromolecule research, highlighting how technological advancements continue to fill the existing bridge and integrate the prior understanding of complex biomolecular systems while addressing persistent technical challenges in their characterization, with finesse.
Tea is a widely consumed beverage known for its variety of flavors and aromas, with major health benefits. However, the use of pesticides to protect against pests renders tea a potential health hazard, especially when consumed in large amounts. The tea leaf matrix is perplexing, as it is filled with organic acids, polyphenols, natural pigments, catechins, flavonols, and a mix of metallic and nonmetallic elements. This makes it difficult for analytical processes to work. The leaf complex matrix is one of the factors enabling accurate detection of pesticides. Therefore, we critically assessed the progression and implementation of advanced methodologies, encompassing the advancement of highly sensitive biosensors and the enhancement of chromatographic techniques, including liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-tandem mass spectrometry (GC-MS/MS). This review also examines how different types of tea affect analytical results and compares sample-preparation methods, from traditional liquid-liquid extraction to newer solid-phase extraction methods. This review highlights major advancements in analytical methods for pesticide detection in tea, emphasizing modern, effective techniques and future perspectives. This study highlights the critical role of sample preparation methods in achieving accurate results within a challenging tea matrix to safeguard consumer health.
Tofu is a traditional soy-based food of global importance, requiring stringent quality control to ensure safety and support industrial modernization. However, real-time monitoring in industrial-scale production is challenging because traditional methods are subjective, time-consuming, and destructive. In response to this challenge, a suite of rapid detection technologies based on optical, electrochemical, sensor, and physical field principles has emerged as a transformative solution. These technologies enhance detection speed, accuracy, and functionality, thus enabling the intelligent upgrading of the tofu industry. This review comprehensively summarizes and critically evaluates recent advancements in rapid detection methods for tofu, encompassing near-infrared spectroscopy, Raman spectroscopy, hyperspectral imaging, electronic nose/tongue, low-field nuclear magnetic resonance, ultrasonic testing, and photoelectrochemical sensors. For each technology, the underlying principles, application performance, and representative case studies are elucidated. In addition, persistent challenges such as model robustness, signal interference, and lack of standardization are analyzed. Finally, future trends are foreseen, with emphasis placed on multi-technology integration, intelligent automation driven by artificial intelligence, and the development of portable and online systems. This work aims to serve as a valuable reference for guiding future research and promoting the practical application of rapid detection technologies in the tofu industry.
Liquid biopsy enables noninvasive cancer detection through circulating tumor cells (CTCs) and extracellular vesicles (EVs), yet current technologies face challenges in sensitivity, specificity, and clinical scalability. DNA hydrogels-three-dimensional nucleic acid networks with sequence-programmable recognition and stimulus-responsive behavior-have emerged as promising platforms to address these limitations. This review critically evaluates DNA hydrogel-based biosensors for CTC and EV detection, encompassing design principles, functionalization strategies (aptamers, DNAzymes, nanomaterials), separation/enrichment approaches, and multimodal detection methods including electrochemical, optical, and magnetic resonance platforms. We introduce a unified Analytical Figures of Merit (AFoM) framework for standardized performance evaluation, define the Clinical-Analytical Translation Gap (CATG) to quantify performance degradation in clinical matrices, and present a systematic gap analysis revealing that fewer than 5% of studies report batch-to-batch reproducibility and over 80% lack validation in unprocessed clinical specimens. Despite remarkable programmability and multifunctional integration, DNA hydrogel biosensors require rigorous inter-laboratory reproducibility studies, systematic CATG characterization, head-to-head comparisons with FDA-cleared reference methods, and standardized analytical reporting before clinical translation can be realized.
Solid-phase microextraction (SPME) has evolved into a key sample preparation technique in forensic drug analysis due to its solvent-free operation, high sensitivity, and compatibility with complex matrices. This review critically evaluates recent advances (2018-2025) in SPME sorbent materials, with particular emphasis on their design, functionalization, and analytical performance. Advanced sorbents, including metal-organic frameworks (MOFs), covalent organic frameworks (COFs), molecularly imprinted polymers (MIPs), carbon nanotubes (CNTs), hydrophilic-lipophilic balance (HLB) materials, and polymeric ionic liquids (PILs), demonstrate significant improvements over conventional coatings such as polydimethylsiloxane (PDMS) and polyacrylate (PA). Reported enhancements include up to 24-fold higher adsorption capacity (SPME Arrow), 1.7-2245-fold increases in enrichment factors (COF-based sorbents), and LOD as low as ≤ 0.25-2 ng/mL in biological matrices. Recovery rates across advanced materials typically range from ∼77% to >100%, with hybrid and HLB-based systems achieving 81-120% and improved matrix tolerance. Additionally, CNT- and MOF-based sorbents exhibit high durability, maintaining performance over 50-300 extraction cycles, while MIP-based systems provide high selectivity with protein exclusion up to 98%. The review systematically correlates sorbent chemistry, fabrication strategies, and extraction mechanisms with analytical figures of merit, including sensitivity, linearity, and precision. By integrating these quantitative comparisons, this work highlights how rational sorbent design enhances extraction efficiency, reduces matrix effects, and improves reproducibility. The findings provide a comprehensive framework for selecting and developing next-generation SPME materials to support reliable, high-throughput, and legally defensible forensic drug analysis.
Food safety remains a major concern in global public health and regulatory governance. The illicit adulteration of melamine in food products has raised persistent concerns in food safety due to its potential health risks and the limitations of conventional protein determination methods. This review critically summarizes recent advances in melamine detection in food matrices, covering its physicochemical properties, recognition mechanisms, and major strategies, including conventional physicochemical analysis, optical and spectroscopic detection, electrochemical sensing, molecular recognition, and intelligent integrated platforms. Conventional chromatographic and mass spectrometric methods remain the gold standard for regulatory confirmation, but require costly instrumentation and complex pretreatment. Emerging optical, electrochemical, molecular recognition, and intelligent systems offer rapid, portable, and high-throughput screening, yet still face matrix interference, limited stability, reproducibility issues, insufficient standardization, and challenges in large-scale implementation. Future research should improve robustness, selectivity, portability, data-processing capability, and validation standards. Overall, this review provides a critical assessment of current melamine detection technologies and offers insights into developing practical, reliable, and intelligent platforms for food safety monitoring.
