Search Results (565)

Rapid, low-cost ethanol quantification is vital for beverage quality control, biofuel production, and pharmaceutical applications, yet current approaches are costly, reagent- or label-dependent, or rely on spectroscopy with substantial sample preparation. We introduce a purely cell-based, label-free biosensor that exploits temperature-gradient-induced spontaneous detachment of Saccharomyces cerevisiae from a chip surface. The readout is the detachment half-time, t_d50, derived from time-resolved changes in interfacial thermal resistance, R_th, at the solid–liquid interface. Cells were pre-exposed to ethanol (0–70% v/v) and the detachment kinetics monitored using the heat transfer method (HTM). Under these conditions, cells display a pronounced non-monotonic t_d50 response with a peak around 20% v/v ethanol. Overall, the t_d50 rises from ~45 min (0% ethanol) to ≳10 h (20%) and then decreases, with no detachment at 60% and beyond. Critically, cell quality gates the detachment window. Fresh yeast responds up to ~50%, whereas aged yeast ceases to detach above ~8%, demonstrating a dual-function assay. Complementary measurements show that ethanol decreases surface tension monotonically, as expected, while optical/SEM imaging reveals aggregation above the detachment window. Requiring only a heater and a temperature probe, this platform offers a compact and low-cost strategy for ethanol sensing. Its applicability in a complex matrix is further demonstrated using whiskey diluted to selected alcohol concentrations, which produced responses consistent with the ethanol calibration trend. Potentially, it also offers a thermal assay for real-time monitoring of microbial cell quality across biotechnology and bioengineering applications. Considering ethanol as a proxy for drugs, the strategy may also support label-free drug screening on cells. At a fundamental level, the non-monotonic effect of ethanol, and especially the sharp maximum at 20%, remains unresolved and invites further studies. Full article

Food allergies are one of the most critical food safety issues, with epidemiological studies confirming a global increase. In this context, effective and sensitive analytical methods play a crucial role in ensuring allergen-free food products. To face this issue, electrochemical biosensors offer powerful, sensitive, selective, and cost-effective alternatives to conventional methods for food allergen analysis while enabling rapid on-site detection. In this study, we developed a sandwich electrochemical magneto-genoassay aimed at the parallel detection of soy (Glycine max) and mustard (Sinapis alba) allergens, suitable for implementation on multichannel instrumentation. The assay involves the functionalization of magnetic microbeads functionalized with peptide nucleic acid-based (PNA) capture probes, capable of undergoing target-induced bio-orthogonal ligation with biotin-labelled signalling probes. Carbon nanotubes-modified screen-printed carbon electrodes were exploited for the voltammetric readout. We demonstrated the effectiveness of functional PNA probes by comparing their performance with those achieved using analogous DNA probes. The developed method exhibited excellent selectivity in terms of cross-reactivity, sensitivity, and precision, achieving detection limits of 16 and 19 pM for soy and mustard, respectively. Finally, by successfully applying the biosensor platform to genomic DNA extracted from plant-based food ingredients, we demonstrated its potential as a valuable tool in food safety risk management. Full article

Background: The rapid rise in antimicrobial resistance (AMR) represents one of the most pressing global health challenges of the 21st century, threatening antibiotic effectiveness, compromising clinical outcomes, and undermining healthcare systems. Understanding how resistant pathogens emerge and spread across human, animal, and environmental sectors is essential for effective global response. Main body: This review evaluates traditional and advanced AMR detection methodologies, including phenotypic assays, molecular diagnostics, whole-genome sequencing (WGS), metagenomics, and biosensor-based technologies. It also highlights the role of bioinformatics tools, surveillance databases, and integrated platforms that support real-time analysis. Genomic surveillance provides unparalleled resolution for characterizing resistance mechanisms, transmission patterns, and evolutionary trajectories of multidrug-resistant organisms. Techniques such as WGS and metagenomics allow timely and precise identification of resistance genes, improving outbreak detection and strengthening antimicrobial stewardship. Despite these advantages, the adoption of genomic surveillance faces barriers in low- and middle-income countries, including high costs, limited infrastructure, insufficient technical expertise, and the lack of standardized data frameworks. Conclusions: Genomic surveillance is a transformative tool for combating AMR and strengthening global health systems. Effective implementation requires sustained investment, capacity-building, coordinated cross-sector collaboration, and commitment to the One Health approach to ensure equitable access and long-term global impact. Full article

Hormones regulate numerous physiological processes and are essential for maintaining metabolic homeostasis. Accurate hormone quantification is crucial for the diagnosis and monitoring of endocrine and metabolic disorders. Electrochemical biosensors have recently emerged as promising platforms for hormone detection, offering simplicity, rapid response, cost-effectiveness, and high sensitivity compared to conventional techniques such as chromatography and mass spectrometry. This review summarizes the advances in electrochemical biosensors for detecting clinically relevant hormones, including cortisol, estrogen, progesterone, thyroid-stimulating hormone, parathyroid hormone, prolactin, and insulin, since 2010. Particular attention has been paid to developments in electrode modification strategies, including nanomaterials, redox enzymes, and novel recognition elements, which significantly improve the sensitivity and selectivity. These advances enable hormone detection at lower concentrations in various biological and environmental matrices. Despite these promising developments, challenges related to sensor stability, fabrication costs, and regeneration procedures limit their large-scale commercialization. Future research should focus on improving robustness, optimizing immobilization strategies, and integrating innovative materials to enhance the analytical performance. Continued collaboration among researchers, engineers, and healthcare professionals is essential. With ongoing technological progress, electrochemical biosensors are expected to play an important role in clinical diagnosis, point-of-care testing, and personalized medicine. Full article

RNA aptamer sensors are promising for environmental and clinical detection, but their poor stability limits practical application. Here, we developed a tRNA-fused strategy to enhance the stability of unmodified RNA aptamer sensors. The tRNA scaffold was fused to the 3′ end of Spinach aptamer to construct tRNA-Spinach. In vitro stability assays showed that tRNA-Spinach retained 50% of its initial fluorescence for 84 days at 25 °C (60% humidity), a 7-fold improvement compared with native Spinach (12 days). The tRNA-fused strategy also doubled the in vivo half-life of Spinach from 20 min to 40 min in KM mice. Based on this strategy, a tobramycin sensor was constructed, which exhibited a LOD of 30 nM, a linear range of 30–100 nM (R² = 0.9905). The biosensor could be detected with a handheld UV lamp within 10 min. This tRNA-fused strategy enables room-temperature storage of RNA aptamer sensors without chemical modification, providing a scalable and cost-effective platform for point-of-care diagnostics in resource-limited settings. Full article

Protein biomarkers can be used for monitoring the occurrence and development of diseases. Accurate, sensitive, and low-cost methods for protein detection can facilitate therapeutic intervention, improve clinical outcome, and reduce economic pressure for patients. Molecularly imprinted polymers (MIPs) have been considered as a type of biomimetic materials for developing biosensing technologies due to their advantages of high stability, low preparation cost, and good reusability over classical biometric recognition elements such as antibodies and aptamers. Electrochemical biosensors have become the most promising technology in sensing applications in view of their high sensitivity, fast response speed, cost-effectiveness, good stability, and ease of miniaturization. Efforts have been made to develop various electrochemical biosensors for protein detection with MIPs as recognition elements. This article provides an overview of the progress in molecular imprinting methods for the design and application of electrochemical protein biosensors. The strategies for imprinting and removing templates and preparing MIPs-modified sensing electrodes are comprehensively discussed. Finally, the challenges and future perspectives of protein-imprinted electrodes are addressed. This work will contribute to the development of innovative analytical devices based on MIPs for monitoring and managing various diseases by determining protein biomarkers. Full article

This study presents a rapid, eukaryotic impedimetric biosensor that applies the yeast Saccharomyces cerevisiae as a robust, cost-effective biorecognition element for monitoring the acute toxicity of two representative pharmaceuticals, naproxen and isoniazid, in aquatic systems. The biosensor utilizes a previously developed three-electrode system made from type 316 stainless steel. Yeast cells seeded onto these electrodes serve as the biosensing element. By monitoring changes in electrical impedance, the system quantifies the cellular stress induced by pharmaceutical exposure. Electrochemical Impedance Spectroscopy (EIS) revealed a concentration-dependent decrease in both resistance and capacitance, attributed to cell death and subsequent desorption from the working electrode surface. These findings were validated through optical density at 600 nm (OD₆₀₀) growth curve analysis and methylene blue viability staining, which confirmed metabolic inhibition and membrane damage. Results indicate a linear response for naproxen within the 2.5 mM to 20 mM range, with a LOD of 0.509 mM, and for isoniazid within the 10 mM to 100 mM range, with a LOD of 0.684 mM. Naproxen demonstrated a more pronounced cytotoxic effect, with cell viability dropping to 41.08% at 10 mM compared to 68.79% for isoniazid. While conventional analytical methods focus on chemical quantification, this proof-of-concept biosensor provides a rapid toxic/non-toxic signal, offering a biologically relevant tool for real-time monitoring of industrial waste streams and acute environmental contamination. Full article

Exosomes are a kind of nanoscale extracellular vesicle secreted by almost all cell types and considered promising biomarkers for disease diagnosis since they could carry abundant proteins, nucleic acids, and lipids that reflect parental cell states. However, conventional exosome detection methods suffer from several limitations including insufficient specificity, low throughput, high costs, and inadequate sensitivity for clinical applications. By contrast, field-effect transistor (FET) biosensors are a promising alternative by enabling label-free, real-time, and ultrasensitive detection of exosomes through direct transduction of biorecognition events into electrical signals. This review first introduces the fundamental principles and device structure of FET biosensors, as well as exosome isolation strategies. The recent advances in exosome analysis using FET-based biosensors are then presented, which are categorized into two primary strategies: (1) direct detection of intact exosomes based on surface markers, including tetraspanin proteins (CD9, CD63, CD81, etc.) and disease-specific biomarkers, and (2) detection of exosomal contents including microRNA and protein biomarkers following exosome lysis. Finally, we discuss current challenges of FET-based exosome detection and provide perspectives on future developments. Full article

Background: Metabolic syndrome is characterized by dysregulated glucose metabolism and is a major risk factor for type 2 diabetes mellitus and cardiovascular disease. Although glucose-lowering therapies such as glucagon-like peptide-1 receptor (GLP-1R) agonists are effective, their use may be limited by cost, administration route, side effects and tolerability. Bergamot (Citrus bergamia Risso et Poiteau) extract, rich in flavanones, has shown favorable metabolic effects in clinical studies, although its mechanisms of action remain insufficiently defined. This study aimed to investigate the potential glucose-modulating mechanisms of a standardized phospholipid-formulated bergamot extract (BP) (Vazguard™) in vitro. Methods: GLP-1R activation was assessed in a U2OS cell line expressing cyclic adenosine monophosphate (cAMP)-sensitive Nomad Biosensors™. Dipeptidyl peptidase-4 (DPP4) activity was evaluated using a cell-free enzymatic assay, while Glucose transporter type 4 (GLUT4)-mediated glucose uptake was assessed in CHO-K1 cells stably expressing human GLUT4 using an adenosine triphosphate (ATP)-based readout. Cytotoxicity was also using lactate dehydrogenase (LDH), MTT, and nuclei count assays. Results: BP exhibited a dose-dependent (0.31–5 mg/mL) increase in cAMP biosensor fluorescence, consistent with GLP-1R-associated signaling and a maximal response of approximately 60% relative to the positive control (GLP-1R agonist II). No cytotoxic effects were observed. In contrast, BP showed no inhibitory effect on DPP4 activity and did not alter GLUT4-mediated glucose uptake under the experimental conditions tested. Conclusions: These findings provide novel mechanistic evidence that phospholipid-formulated bergamot extract suggests a possible involvement in GLP-1R-associated signaling in vitro, without detectable effects on DPP4 or GLUT4 pathways under the conditions tested. This suggests a mechanism consistent with weak agonist or allosteric modulation of GLP-1R and supports further investigation of bergamot formulated with phospholipids as potential natural adjuncts in metabolic health management. Full article

Biosensors have emerged as a rapidly evolving area of research, offering transformative potential across biomedical diagnostics, environmental monitoring, and pharmaceutical applications. Among the diverse range of biosensing technologies, graphene-based surface plasmonic resonance (SPR) biosensors have attracted particular interest due to their exceptional sensitivity, scalability for mass production, and cost-effective fabrication processes. This study explores the operational principles and current design methodologies of graphene-based SPR biosensors, with a special emphasis on the role of electrolyte gating and its impact on sensor performance. Furthermore, the influence of graphene’s quantum capacitance is investigated as a critical parameter for improving the accuracy and reliability of performance predictions in the proposed sensor configuration. Computational analysis of sensitivity and key performance metrics was conducted. Notably, key performance metrics of the sensor improved upon incorporating quantum capacitance effects into the simulation framework. At a β₂-microglobulin concentration of 0.00118 g/L, the sensitivity increased to 174 GHz·g/L, the figure of merit reached 0.55 L/g, the quality factor was 0.01, the signal-to-noise ratio (SNR) rose to 0.008, and the detection accuracy (DA) reached 0.08 L/THz, demonstrating the significant impact of quantum capacitance on the sensor’s performance. These findings highlight the potential of quantum-electrostatic considerations to enhance the precision and efficacy of graphene-based SPR biosensors, paving the way for the development of next-generation biosensing platforms with improved analytical capabilities. Unlike conventional graphene SPR biosensors, which primarily detect refractive index changes near the graphene surface, our model explicitly considers the electrostatic effect of biomolecules on graphene’s Fermi energy. By modelling β2-microglobulin as a charged species, we compute the resulting electric double layer and incorporate quantum capacitance in series. This amplifies the charge-induced modulation of graphene’s optical conductivity, and, combined with a graphene perfect absorber design, leads to enhanced plasmonic resonance shifts. Consequently, our approach achieves higher sensitivity and more precise detection of biomolecular interactions compared to traditional simulations. Full article

Dopamine (DA) is a crucial catecholamine neurotransmitter, and its abnormal levels are closely associated with neurological disorders such as Parkinson’s disease. Electrochemical sensing technology offers a rapid and cost-effective platform for DA detection; however, it often suffers from interference from coexisting biomolecules such as ascorbic acid (AA) and uric acid (UA). In this study, we report a novel electrochemical biosensor based on PdMo bimetallene, a nanomaterial synthesized via a facile wet-chemical approach, aiming to enhance the detection performance and selectivity for DA. PdMo bimetallene is a highly curved, atomically thin two-dimensional nanosheet featuring abundant strained sites and a high density of active centers, enabling the selective and sensitive detection of DA. The results demonstrate that the as-prepared PdMo bimetallene-modified glassy carbon electrode (GCE) exhibits excellent electrocatalytic activity toward the oxidation of DA. The sensor displays a good linear response over the concentration range from 10 nM to 200 µM, with an ultrahigh sensitivity of 80 µA·µM⁻¹ cm⁻² and a low detection limit of 0.14 µM (S/N = 3). Owing to the synergistic electronic effect between Pd and Mo, the high density of exposed active sites, and the unique strained lattice structure of the bimetallene, the sensor enables accurate determination of DA concentrations even in the presence of interfering species such as AA and UA. In summary, the successfully fabricated PdMo bimetallene-based sensor offers the advantages of low cost, facile synthesis, a wide linear range, and high sensitivity, positioning it as a promising candidate for neurotransmitter detection applications. Full article

Chloramphenicol is a broad-spectrum antimicrobial agent whose use in food-producing animals is prohibited in many countries due to its association with severe adverse effects, including idiosyncratic aplastic anemia and genotoxicity. Despite these restrictions, chloramphenicol residues continue to be detected in food products, environmental compartments, and biological matrices, highlighting the need for reliable and sensitive analytical monitoring. This review provides a comprehensive overview of current analytical strategies for the detection of drugs in food and environmental samples, covering screening and confirmatory techniques, sample preparation approaches, and regulatory aspects. Rapid screening methods, such as enzyme-linked immunosorbent assays (ELISAs), lateral flow immunoassays (LFIAs), and biosensors based on antibodies, aptamers, and molecularly imprinted polymers, enable fast and cost-effective preliminary detection. Recent advances in nanomaterials and signal amplification strategies, including fluorescent reporters and surface-enhanced Raman scattering (SERS), have significantly improved sensitivity and assay performance. However, confirmatory methods based on liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) remain the reference standard due to their superior selectivity, sensitivity, and quantitative reliability. Attention is given to sample preparation workflows, including QuEChERS-based protocols and microextraction techniques, which enable efficient analysis of complex matrices. Finally, current regulatory frameworks and analytical challenges related to zero-tolerance policies are discussed, emphasizing the importance of robust and validated analytical methods for effective monitoring and food safety assurance. Full article

Antimicrobial resistance (AMR) is increasingly becoming a major global public health concern, as antibiotics are losing their effectiveness at an alarming rate due to drug resistance. The ß-lactam group of antibiotics are widely used in dairy farms to treat animal infections, and their presence in the food chain is a significant concern. Addressing this issue requires the development of effective analytical tools for the rapid detection of antibiotics. In this work, a miniaturized Biosensor-on-Pillar platform was developed for detecting ß-lactam antibiotics in milk, which operates in a rapid, cost-effective, and user-friendly format, making it particularly suitable for resource-limited settings. The platform employs an enzyme induction-based approach, wherein Bacillus cereus spores germinate in the presence of β-lactam antibiotics, leading to the production of β-lactamase enzyme, which is then recognized using a chromogenic substrate functionalized on paper associated with the pillar platform. The developed biosensor can detect 12 β-lactam antibiotics with limits of detection (LODs) ranging from 1 to 1000 ppb, achieving sensitivity at or below the maximum residue limits (MRLs) set by regulatory bodies (FSSAI/CODEX) for the majority of the tested antibiotics. The performance of the platform, including the design, fabrication, and working principle, was further evaluated by analyzing six blind milk samples, yielding significant results compared to the commercially available AOAC-approved gold-standard method. Hence, the developed biosensor demonstrates promising potential for the rapid, cost-effective and high-throughput screening of milk samples for β-lactam antibiotics, benefiting the dairy industry and ensuring food safety. Full article

Heavy metal contamination of foods remains a persistent global challenge for food safety and public health, driven by industrialization, mining activities, intensive agriculture, and ongoing environmental degradation. This scoping review synthesizes peer-reviewed literature on the occurrence of priority toxic metals—arsenic, cadmium, lead, mercury, and nickel—in food matrices, with emphasis on contamination pathways, analytical detection strategies, and documented human health effects. The reviewed studies reveal widespread accumulation of heavy metals in staple foods, including cereals, vegetables, seafood, and processed products, with concentrations frequently approaching or exceeding international regulatory limits, particularly in regions exposed to strong anthropogenic pressure. Conventional laboratory-based techniques, such as atomic absorption spectrometry and inductively coupled plasma methods, remain the reference standards for quantitative determination and regulatory compliance; however, their application to large-scale or continuous monitoring is often constrained by cost, infrastructure, and operational complexity. Consequently, increasing attention has been directed toward emerging detection approaches, including portable X-Ray fluorescence, Raman/SERS spectroscopy, electrochemical biosensors, electronic tongues, and in situ magnetic measurements, as complementary tools for rapid screening and field-based surveillance. Among these, environmental magnetism and in situ magnetic techniques stand out as non-destructive, low-cost proxies capable of identifying metal-associated particulate contamination linked to food production systems. Chronic dietary exposure to heavy metals is consistently associated with neurotoxicity, nephrotoxicity, carcinogenicity, and oxidative stress, underscoring the need for integrated, multi-tiered monitoring frameworks to support early detection, risk assessment, and prevention. Full article

Chimeric antigen receptor (CAR) T-cell therapy is an effective treatment for hematologic malignancies. However, it is limited by high costs, risk of severe toxicities such as cytokine release syndrome and neurotoxicity, and heterogeneous patient responses. The current therapy monitoring depends largely on subjective symptom assessment, routine laboratory tests, and basic vital signs, without real-time, quantitative evaluation of CAR T-cell expansion or activation in clinical practice. This lack of timely immune monitoring hampers individualized care and contributes to increased treatment costs. To address this need, we present a proof-of-concept, label-free rapid optical imaging (ROI) biosensor with automated machine learning analysis for direct quantification of CAR T-cells from whole blood. This microfluidic platform integrates red blood cell (RBC) removal, CAR T-cell capture, and imaging-based quantification on a single chip, eliminating the need for centrifugation, staining, and operator-dependent interpretation. For validation, 50 μL whole blood samples spiked with Jurkat cells expressing CD19 CARs underwent RBC depletion by agglutination and microfiltration. The remaining blood components were then incubated on a sensor chip functionalized with recombinant CD19 protein. Captured CAR T-cells were imaged by brightfield microscopy and automatically enumerated using a machine learning algorithm trained on fluorescence-validated cells. The CD-19 cells’ capture performance was validated by flow cytometry and fluorescence imaging. The trained machine learning model validated at 88% sensitivity and 96% specificity. Buffer and whole blood calibration curves were established across clinically relevant concentrations (1–1000 cells/µL) with triple replicates. The results showed high correlation (0.975 and 0.990 R²) between the spiked concentration and the detected CAR T-cells, with a 95% certainty limit of detection (LOD) and quantification (LOQ) of 0.6 and 1.1 cells/µL for spiked buffer, and 14 and 67 cells/µL for spiked whole-blood, respectively. Full article