African Swine Fever Virus (ASFV) poses a catastrophic threat to global swine production, with recent outbreaks across Europe, Asia, and the Caribbean, significantly elevating the biosecurity risk to the United...
Synthetic corticosteroids such as dexamethasone and prednisolone are widely used for the treatment of various conditions including tumors and skin disorders. Chronic exposure to synthetic corticosteroids leads to adverse health effects such as osteoporosis, hyperglycemia and hypertension. Several dietary and health supplements have recently been reported to be adulterated with synthetic corticosteroids. Conventional analytical techniques such as high-performance liquid chromatography (HPLC), thin-layer chromatography (TLC) and immunochromatography used for detection of these corticosteroids are time-consuming and require trained personnel, necessitating the development of rapid and cost-effective screening methods to ensure food safety. Here, a rapid and cost-effective colorimetric recognition chemistry has been developed for detection of synthetic corticosteroids in dietary supplements. The method employs spectrophotometric quantification of the chromogenic end product at 410 nm, which was further assessed using RGB-based image analysis. Selectivity and interference studies showed no significant matrix interference from the tested structurally similar steroids and common dietary supplement samples. The assay demonstrated a limit of detection (LOD) of 0.04 ± 0.008% (w/v) and a limit of quantification (LOQ) of 0.12 ± 0.027% (w/v) for prednisolone. The developed method is suitable for on-site detection of synthetic corticosteroids, and can be used by regulatory agencies and industries to ensure food safety and human health.
Uranium is a core key element in the nuclear industry, and the discharge of uranium-containing wastewater is likely to pose a significant threat to the ecological environment and human health....
We report a paper-based analytical device for total Fe detection in vitreous humor to estimate the post-mortem interval (PMI) for forensic applications. This method improves a previously reported approach by replacing 1,10-phenanthroline (o-phen) with bathophenanthroline (bato-phen) as the chromogenic reagent, enhancing analytical performance. A linear response was obtained over the range from 0.0 to 10.0 mg L-1 for both reagents. The limits of detection (LOD) and quantification (LOQ) were 0.30 and 0.90 mg L-1 for o-phen, and 0.05 and 0.15 mg L-1 for bato-phen, respectively. The higher sensitivity of bato-phen is attributed to its greater molar absorptivity, resulting in improved colorimetric response. The method was applied to ten human vitreous humor samples, enabling PMI estimation on an hourly scale. The proposed device provides a rapid, low-cost, and portable alternative for preliminary PMI estimation directly at the crime scene.
This work presents the efficient recognition of the hazardous chemical cyanide ions (CN- ions) using a newly designed organic molecule-based fluorescent receptor, (E)-4-(4-(diphenylamino)styryl)-1-propylquinolin-1-ium (TAME). CN- ion detection occurs via nucleophilic addition to the styryl group, inducing distinct electronic perturbations as well as blocking of the intramolecular charge transfer (ICT) process. Absorption spectral titration studies reveal a notable blue shift (517-507 nm) in the presence of CN- ions, while steady-state fluorescence measurements demonstrate significant fluorescence quenching (∼82%) with a strong red shift from 553 nm to 576 nm following the interaction of CN- ions with the receptor TAME. The lowest limit of detection (LOD) for this fluorescence-based sensing strategy was calculated to be 1.48 nM, which is much lower than the WHO-permissible limit for cyanide in drinking water. Furthermore, the probe was successfully employed as a paper strip, enabling the portable and effective recognition of CN- ions. Additionally, this sensing system illustrates a notable colour-changing behaviour, which was further exploited for CN- ion detection through a smartphone-based RGB color variation analysis technique. The real-world utility of the receptor TAME was established through its ability for the effective quantification of hazardous CN- ions in various real water and food samples.
Carbon quantum dots (CQDs) are promising fluorescent nanomaterials for analytical applications, but their structure-property relationships remain under-investigated, especially in biomass-derived systems. Herein, we report on the ultrafast, one-pot, microwave-assisted synthesis...
Abstract: Quantifying trace heavy metals in complex food and environmental matrices requires sorbents with exceptional selectivity and matrix tolerance. We synthesized a ternary hybrid matrix (nano-HAP@Tween80@SG) via an ultrasound-assisted secondary...
Pharmaceutical bioanalysis has undergone remarkable technological advancement with the widespread adoption of liquid chromatography-mass spectrometry (LC-MS) platforms, enabling highly sensitive and selective quantification of pharmaceuticals, metabolites, biomarkers, peptides, proteins, and oligonucleotides. Despite these developments, persistent challenges, including matrix effects, analytical instability, biological matrix complexity, data overload, and sustainability concerns, continue to compromise analytical reliability and translational applicability. This critical review comprehensively evaluates the current state of pharmaceutical bioanalysis by examining emerging LC-MS technologies, sustainable analytical strategies, and the growing role of artificial intelligence (AI) and machine learning (ML) in analytical optimization, spectral interpretation, biomarker discovery, and autonomous decision-making. Particular emphasis is placed on White Analytical Chemistry (WAC) as a multidimensional framework that simultaneously considers analytical performance, environmental sustainability, and practical feasibility. The review critically assesses the limitations of current AI-assisted and sustainability-driven approaches, highlighting issues with algorithmic transparency, regulatory acceptance, standardization, and insufficient real-world validation. Furthermore, it explores intelligent analytical ecosystems that integrate advanced LC-MS platforms, explainable AI, digital twins, automation, and cloud-based infrastructure. Finally, realistic future priorities are proposed to facilitate the transition to autonomous, reliable, and environmentally sustainable pharmaceutical bioanalysis that supports precision medicine and next-generation drug development.
In this manuscript, two newly designed near-infrared (NIR) emitting derivatives were synthesized by reacting dicyanoisophorone with 2-hydroxy5-nitrobenzaldehyde (IC25) and 2,4,5-trimethoxybenzaldehyde (IC27) through Knoevenagel condensation reactions. The compounds were structurally characterized...
Accurate detection of the widely used organophosphorus pesticide chlorpyrifos (CPF) is of great significance for the ecology and human health. In this study, a dual-recognition electrochemical sensing platform was constructed...
Plastic-mulched soils contain mineral particles, organic matter and weathered polymer fragments that complicate the joint measurement of microplastics and co-occurring antibiotics. We developed a matrix-adaptive workflow combining sequential Fenton-enzymatic digestion,...
Functionalized carbon dot nanoparticles are at the forefront of biological applications of carbon nanoparticles (CNPs), particularly in bioimaging and biosensing. In this study, both functionalized and unfunctionalized CNPs were utilized as fluorescent probes in cancer cell lines and Drosophila melanogaster. A human T lymphocyte (Jurkat), the MCF 10A cell line, and the wild-type Oregon strains of D. melanogaster were used in the study. N-doped CNPs were synthesized solely from o-phenylenediamine (oPD CNPs), and thiol-functionalized CNPs were synthesized from o-phenylenediamine and L-cysteine (SH-CNPs), both via a microwave-assisted synthesis. The synthesized SH-CNPs show maximum excitation and emission intensity at 340 nm and 412 nm, respectively. UV-vis absorption spectra present absorption peaks at 238 nm, ∼279 nm, and ∼297 nm, which are attributed to π → π* and n → π* transition states in thiol-containing aromatic systems. CNPs were spherical and polydisperse, with an average size of 64 ± 29 nm. Chemical characterization revealed the presence of the -SH functional group, characterized by an infrared absorption band at ∼2550 cm-1, alongside other functional groups (OH, CO, COO, CC, C-C, NH, NH2) on the surface of both the CNPs and their core. X-ray photoelectron spectroscopy analysis of S 2p also shows the binding energy of ∼164 eV allotted to C-SH. Scanning Electron Microscope/Energy Dispersive Spectroscope reveals the weight percentage (wt%) of the elemental composition of SH-CNPs to be 62.9 ± 0.2%, 17.2 ± 0.2%, 14.7 ± 0.1%, and 5.2 ± 0.1% for carbon, nitrogen, oxygen, and sulfur, respectively. A significant difference in the intensity of the SH-CNPs fluorescence between larvae treated with hydrogen peroxide (H2O2) and larvae treated with potassium superoxide (KO2), with the latter group showing reduced fluorescence intensity. Taken together, these results demonstrate that surface functionalization plays a critical role in modulating the biological response and sensing capability of carbon dot nanoparticles. While unfunctionalized oPD CNPs are effective for structural bioimaging, thiol-functionalized CNPs provide additional functional sensitivity to oxidative stress conditions.
Microplastics (MPs) are an emerging pollutant of global concern, creating an urgent need for rapid and accurate monitoring workflows. Deep learning-based computer vision has demonstrated strong performance in finding particles in microscopy images, but its use as a front-end module for automated IR/Raman microscope-based MP analysis remains insufficiently developed, particularly in workflows that convert image-level particle detection results into microscope-executable operations for particle morphological characterization and spectral acquisition planning. Here, we aim to address this gap. First, reference MPs were deposited on Anodisc filters and glass slides, from which 626 bright-field micrographs containing 7010 particles were collected. The dataset was randomly split into training, validation, and test sets in a 7 : 2 : 1 ratio, and an Ultralytics YOLO11 instance segmentation model was developed. At an intersection-over-union (IoU) threshold of 0.7, testing achieved precision, recall, and F1 scores of 0.86, 0.93, and 0.89, respectively, outperforming two benchmark methods: a threshold-based method (F1 = 0.25) and Mask R-CNN (F1 = 0.84). On another test set prepared from tap water (with a relatively clean background), the model achieved precision, recall, and F1 scores of 0.78, 0.90, and 0.83 at IoU = 0.7. However, particle detection performance decreased with dirtier image backgrounds, as shown by testing on the sample prepared from commercial salt. We addressed key technical challenges required for end-to-end automation, including per-field autofocus, recovering true microscope coordinates from YOLO style outputs, converting detections into particle descriptors for downstream characterization, and programmatic microscope control for image collection and spectrum acquisition planning. Full implementation, code, and well annotated data are released openly, enabling adoption and extension of this workflow for broader MP monitoring applications.
Rapid analysis of food and agricultural products is important for evaluating quality and detecting contaminants, but the chemical complexity and physical heterogeneity of these matrices can make traditional workflows challenging and time-consuming. In our previous work, a touch sensor for sheath-flow probe electrospray ionization (sfPESI) was developed to enable automated analysis of liquid samples by detecting displacement currents upon surface contact. By coupling the sfPESI probe with a table-top 3-axis robot, consecutive point analyses of various complex samples were performed. However, its applicability was limited to liquid and wet solid matrices. In this work, a touch sensor equipped with a lock-in amplifier was developed to enable the automated analysis of both wet and dry samples. The system was demonstrated across a range of matrices, including vegetables, meats, insecticides, and insect repellents, substantially expanding the applicability of automated sfPESI for rapid, surface-resolved chemical analysis of complex food and agricultural products.
Paraquat (PQ), a highly toxic herbicide banned in several countries yet still widely used globally, poses severe threats to human health and ecosystems through acute poisoning and chronic exposure via contaminated food and water. Despite numerous analytical methods, rapid, sensitive, and field-deployable detection remains essential for effective monitoring and regulatory enforcement. Unlike existing reviews focusing narrowly on specific nanomaterials or detection techniques, this review represents a systematic cross-platform comparison evaluating metallic nanoparticles (Au, Ag, Pt), carbon-based materials (graphene, carbon nanotubes, quantum dots), metal-organic frameworks, and hybrid nanocomposites across electrochemical detection mechanisms. Critically, this review examines how food and environmental matrix effects influence sensor performance and discusses the analytical validation requirements necessary for reliable paraquat determination, thereby addressing a major gap in studies that predominantly report performance under idealized buffer conditions. Novel enhancement strategies are evaluated, including molecularly imprinted polymers, aptamer functionalization, and disposable electrode integration for point-of-use testing. This review uniquely addresses the translational research gap by identifying why promising laboratory sensors fail in real-world applications, including challenges associated with matrix interference, selectivity, long-term stability, reproducibility, and practical validation based on reports over the past decade. Furthermore, economic feasibility and lifecycle aspects of nanomaterial-enabled sensing platforms are critically discussed to evaluate their potential for deployment in resource-limited settings. Thus, the review provides clear guidance for developing next-generation sensors capable of protecting public health through effective paraquat monitoring.
Ethanol, as a food additive, can effectively extend product shelf-life and improve food texture. However, its dosage requires stringent control, making ethanol quantification a critical quality assurance requirement in baked goods. Consequently, developing a rapid and simple method for detecting ethanol in baked food products is of great practical significance. This study fabricated a three-dimensional photonic crystal (PC) membrane by integrating plant membranes and a PC, utilizing an onion epidermal membrane as the natural substrate. PC arrays were imprinted onto the onion membrane at room temperature. The resulting onion-derived PC membrane biosensor demonstrated not only high sensitivity but also excellent selectivity towards ethanol. During detection, the spectral reflection peak of the onion-PC film shifted towards the red as the ethanol concentration increased, achieving signal stabilization within 5 min. Moreover, ethanol detection induced visually observable structural color changes (yellow-green to orange-red) on the membrane. The biosensor exhibited excellent practicability and retained stable performance after multiple reuse cycles. Overall, this onion-PC membrane demonstrates significant potential for the visual and rapid detection of ethanol in baked foods.
N-Acetylcysteine (NAC), a thiol-containing mucolytic agent for COPD, exhibits significant pharmacokinetic variability among patients, motivating the need for convenient therapeutic monitoring. Herein, a colorimetric platform based on copper-doped chiral carbon dots (Cu-D-CDs) was synthesized via a one-pot hydrothermal route using D-histidine and CuCl2 as precursors. The Cu-D-CDs displayed enhanced peroxidase-like activity, catalyzing H2O2-mediated oxidation of TMB to blue oxTMB (λmax = 652 nm). Upon NAC introduction, oxTMB was reduced via a thiol-disulfide redox reaction, producing an absorbance decrease proportional to NAC concentration. Under optimized conditions, the assay exhibited a linear dynamic range of 10-90 µM, a detection limit of 3.74 µM (LOD = 3σ/S), and recoveries of 96.00-106.60% (RSD < 4%) in mouse serum, demonstrating its feasibility for NAC quantification in serum samples. Beyond the single-wavelength readout at 652 nm, the full-spectral data were further processed by an LSTM network, which significantly improved prediction accuracy (R2 > 0.9998) compared with single-wavelength calibration (R2 = 0.9979), effectively mitigating matrix interference. This integrated colorimetric-LSTM strategy shows promise for COPD therapeutic drug monitoring and pharmaceutical quality control.
Rizatriptan benzoate (RZB), a first-line therapy for the acute treatment of migraine, requires sensitive and reliable monitoring in pharmaceutical formulations and biological matrices to ensure effective quality control and therapeutic drug monitoring. In this work, a sustainable, novel and cost-effective electrochemical sensor was established for the sensitive determination of RZB by modifying a carbon paste electrode (CPE) with nickel-doped zinc oxide nanoparticles (Ni-ZnO NPs) via a simple precipitation procedure. The prepared nanoparticles were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDX), and Fourier-transform infrared spectroscopy (FT-IR), confirming their crystalline nature. The Ni-ZnO/CPE demonstrated remarkable electrocatalytic efficiency for RZB oxidation in phosphate buffer solution at pH 6.0. Utilizing differential pulse voltammetry, the sensor showed linearity over the concentration interval of 0.04-20 µM. Moreover, the sensor showed excellent repeatability and intermediate precision, with relative standard deviation (RSD) values below 1.5%. The sensor was effectively employed for RZB detection in tablets and human plasma, exhibiting adequate recovery rates of 99.71-101.26% and 100.22-101.26%, respectively. The suggested approach revealed favorable analytical performance compared with previously reported DPV procedures, offering a lower limit of detection of 0.01 µM and enhanced sensitivity. Moreover, this is the first reported electrochemical method for RZB that combines drug determination with a comprehensive environmental assessment. Environmental sustainability was assessed utilizing modern metrics for greenness, blueness, and whiteness, and the findings revealed an excellent eco-profile with strong compliance with the principles of green analytical chemistry.
The gut microbiota influences host metabolism and synthesizes essential vitamins. Human Milk Oligosaccharides (HMOs), diverse non-conjugated polysaccharides, are the third major solid component in breast milk. We assessed maternal HMO...
In recent decades, smartphone-based analytical methods have gained increasing attention, mainly due to their widespread user-friendliness, enhanced computational capabilities, cost-effectiveness, and the ability to simultaneously acquire and process data. Accurate...
